Access to substance abuse treatment in the Cape Town metropole ...

Access to substance abuse treatment in the Cape Town metropole ...

Access to substance abuse treatment in the CapeTown metropoleFinal report: 2007Bronwyn Myers 1 , Johann Louw 2 , Nuraan Fakier 11 Alcohol and Drug Abuse Research Unit, Medical Research Councilof South Africa2 Psychology Department, University of Cape TownAcknowledgementsThis study was funded by the Western Cape’s Provincial Departmentof Social Development, the Open Society Foundation of Soluth Africa,The First Rand Foundation, and the National Research Foundation ofSouth Africa.

SUMMARYThis report summarises findings from a multi-phase study of access to substanceabuse treatment among historically disadvantaged communities (HDCs) in theCape Town metropole. The study collected information on access to servicesamong 989 substance users, who had either been in treatment or had not beenable to access treatment.More specifically, findings from both quantitative and qualitative data analysisconfirm that access to treatment is not equitable in the Cape Town metropole.Instead of “need for treatment” being the factor that determines whether personsutilize treatment services (or not), socio-demographic factors and the extent towhich barriers to treatment are experienced are the strongest determinants ofwhether persons access care.When gender and race were controlled for, the strongest predictors of access tocare were barriers related to the awareness of treatment services, barriersrelated to the availability of affordable treatment services, barriers related to thegeographical accessibility of treatment facilities, and negative perceptions withinHDCs about the availability and accessibility of effective treatment services. Arange of contextual, community and treatment system factors were identified thatseem to underpin and contribute to these barrier variables-including resourceallocation to the substance abuse treatment system, delays in accessing caredue to the process of accessing services, and treatment capacity issues.In order to provide a foundation for the development of interventions that addresssome of these barriers, we also identified socio-demographic (gender and race)differences on several of the barrier variables: with women having moreaffordability and geographical accessibility barriers than men and Black/Africansreporting more awareness, affordability and geographical accessibility barriersthan Coloured participants. Based on the overall findings, we make extensiverecommendations of ways in which each of these barrier variables can beaddressed and access to treatment potentially improved.1

CONTENTSINTRODUCTION ................................................................................ 51.1. THE NEED FOR SUBSTANCE ABUSE TREATMENT IN SOUTHAFRICA ......................................................................................................................... 51.1.1. Prevalence of substance use in South Africa ................................ 51.1.2. The burden of harm associated with substance use disordersin South Africa ........................................................................................................ 61.2. THE NEED FOR SUBSTANCE ABUSE TREATMENT IN THE CAPETOWN METROPOLE.................................................................................................. 71.3. IS ACCESS TO SUBSTANCE ABUSE TREATMENT IMPORTANT? .. 81.4. HOW ACCESSIBLE ARE SUBSTANCE ABUSE TREATMENTSERVICES IN SOUTH AFRICA? ............................................................................. 81.4.1. Racial inequities in access to health and social services .......... 81.4.2. Racial disparities in the need for and access to treatment ...... 101.4.3. Access to treatment in Cape Town ................................................. 111.5. PRIOR RESEARCH AND THE WAY FORWARD ................................... 121.6. OVERALL PURPOSE OF THE STUDY .................................................... 13CONCEPTUAL MODEL................................................................... 142.1. POPULATION CHARACTERISTICS INFLUENCING HEALTHSERVICES UTILIZATION ........................................................................................ 152.1.1. Predisposing characteristics............................................................ 152.1.2. The enabling variable domain .......................................................... 162.1.3. Need for health services .................................................................... 172.2. THE CONTEXTUAL / ENVIRONMENT DOMAIN.................................... 182.2.1. Health care system factors................................................................ 192.2.2. Factors within the external environment....................................... 202.3. THE HEALTH BEHAVIOUR DOMAIN: UTILIZATION ........................... 202.4. WHEN IS ACCESS EQUITABLE?............................................................. 21METHOD.......................................................................................... 223.1. STUDY AIMS & OBJECTIVES...................................................................... 223.2. STUDY DESIGN.............................................................................................. 233.3. PHASE 1: CASE-CONTROL STUDY ........................................................ 253.3.1. Sample characteristics....................................................................... 253.3.2. Procedures............................................................................................. 263.3.3. Data collection tools ........................................................................... 283.3.4. Data analysis......................................................................................... 343.4. PHASE 2: QUALITATIVE CASE STUDY ................................................. 353.4.1. Sample characteristics....................................................................... 353.4.2. Procedures................................................................................................. 363.4.3. The Access to Treatment Interview Schedule.............................. 363.4.4. Data analysis......................................................................................... 363.5. ETHICS............................................................................................................ 37RESULTS: PHASE ONE ................................................................. 382

4.1. VARIABLES ASSOCIATED WITH ACCESS TO SUBSTANCE ABUSETREATMENT: BIVARIATE ANALYSES............................................................... 384.1.1. Predisposing variables associated with access to treatment . 384.1.2. Need for treatment variables associated with access totreatment ................................................................................................................ 414.1.3. Enabling and restricting variables associated with access..... 424.2. PREDICTORS OF ACCESS TO SUBSTANCE ABUSE TREATMENT464.2.1. Model 1: Need for treatment variables ........................................... 464.2.2. Model 2: Predisposing variables and need variables ............... 504.2.3. Model 3: Need for treatment, predisposing, and enablingvariables ................................................................................................................. 514.2.4. A more parsimonious model of access to treatment: Model 4 534.3. SOCIODEMOGRAPHIC DIFFERENCES ON PREDISPOSING, NEEDFOR TREATMENT AND ENABLING VARIABLE DOMAINS........................... 554.3.1. Gender differences on predictors of access among individualswho did not access treatment .......................................................................... 554.3.2. Factors that differentiate between male and female subjectsthat did not access treatment........................................................................... 584.3.3. Race differences on predictors of access among subjects whodid not access treatment ................................................................................... 604.3.4. Factors that differentiate between Black/African and Colouredsubjects that did not access treatment.......................................................... 644.4. VARIABLES ASSOCIATED WITH PREDICTORS OF ACCESS TOTREATMENT AMONG CONTROLS...................................................................... 664.4.1. Relationships between predisposing variables and predictorsof access to treatment among controls......................................................... 674.4.2. Relationships between need for treatment variables andpredictors of access among respondents who did not access treatment684.4.3. Relationships between enabling variables and predictors ofaccess among respondents who did not access treatment..................... 694.4.4. Predictors of awareness, competing needs, travelling time totreatment, and community views about treatment access....................... 714.5. SUMMARY OF FINDINGS........................................................................... 75RESULTS: PHASE TWO................................................................. 785.1. THEMES RELATED TO BROAD SYSTEM DYNAMICS ....................... 785.1.1. Provincial government’s responses to substance abuse ............. 785.1.2. Allocation of resources to the social welfare and healthsectors 825.2. THEMES RELATED TO TREATMENT SYSTEM DYNAMICS ............. 885.2.1. Organisation of the substance abuse treatment system .......... 885.2.2. Resource allocation within the treatment system....................... 915.3. THEMES RELATED TO COMMUNITY DYNAMICS ............................... 975.3.1. Community expectations about treatment.................................... 975.3.2. Community enabling/restricting resources ................................ 1003

5.4. SUMMARY.................................................................................................... 107DISCUSSION AND RECOMMENDATIONS.................................. 1096.1. IS ACCESS TO SUBSTANCE ABUSE TREATMENT EQUITABLE?1096.2. FACTORS THAT PREDICT ACCESS TO SERVICES......................... 1096.2.1. Awareness of substance abuse treatment.................................. 1106.2.2. Geographical accessibility .............................................................. 1136.2.3. Availability of affordable treatment............................................... 1156.2.4. Negative perceptions of treatment................................................ 1176.3. TREATMENT SYSTEM FACTORS ASSOCIATED WITH ACCESS TOSUBSTANCE ABUSE TREATMENT................................................................... 1206.3.1. Organisational barriers to accessing substance abusetreatment .............................................................................................................. 1206.3.2. Resource-related barriers within the treatment system.......... 1216.4. RECOMMENDATIONS............................................................................... 124Based on study findings, a number of recommendations for interventions thataddress barriers to accessing substance abuse treatment services withinHDCs can be made. Some of these recommendations are described below:1246.4.1. Recommendations for interventions that address awarenessrelatedbarriers ....................................................................................................... 1246.4.2. Recommendations for interventions that address geographicalaccessibility barriers............................................................................................. 1256.4.3. Recommendations for interventions that address affordabilitybarriers 1276.4.4. Recommendations for interventions that address negativeperceptions about treatment............................................................................... 1286.4.5. Recommendations for interventions within the treatment system:129In order to improve access to treatment for people from HDCs, interventionsare also required at the level of the treatment system. ...................................... 129REFERENCES............................................................................... 1364

INTRODUCTION1.1. THE NEED FOR SUBSTANCE ABUSE TREATMENT IN SOUTHAFRICAIn South Africa, changes in the pattern of substance use highlight the need foraccessible treatment services. During apartheid, the country’s physical andeconomic isolation, strict monitoring of external borders, and stringent internalcontrols restricted access to drugs; with alcohol, locally cultivated cannabis,Mandrax (methaqualone combined with an anti-histamine), and prescriptionmedicines being the only substances readily available. Since the collapse ofapartheid, socio-political changes (such as reductions in internal and externalborder controls and increases in travel and trade), together with the country’spoorly resourced law enforcement agencies and advanced banking, transport,and communication systems made South Africa an attractive new market for drugcartels. South Africa’s geographic location also made it attractive to traffickers,with the country being a convenient trans-shipment point for drugs from drugproducingcountries to drug markets. With these changes, South Africans nowhave access to a broad range of drugs and indicators suggest that the domesticdrug market is expanding, with drug prices decreasing and availability increasing(Parry et al., 2002a; Parry et al., 2002b).Apart from these changes in the pattern of use and drug markets, anecdotalreports from treatment service providers and communities point to an increaseddemand for substance abuse treatment, with waiting lists for treatment slotsincreasing and communities mobilizing around drug-related issues. Thisincreased demand has placed substance abuse treatment facilities underpressure to increase their coverage and provision of services.1.1.1. Prevalence of substance use in South AfricaPrevalence studies provide one indication of extent to which substance abusetreatment is needed in South Africa. In recent years, several national householdsurveys on substance use have been conducted in South Africa (e.g. Pettifor et5

al., 2004; Reddy et al., 2003; Shisana et al., 2005). However these studies areseverely limited in their ability to estimate treatment need. Firstly, householdsurveys have a limited ability to estimate the prevalence of less commonly usedsubstances, especially if sample sizes are small (Parry et al., 2002a). In addition,as these surveys did not screen participants for substance use disorders (or askabout self-reported treatment need), they provide little indication of the need forsubstance abuse treatment. An exception to this is the 1998 South AfricanDemographic and Health Survey (SADHS) which included a screeningquestionnaire for lifetime alcohol dependence. This study found that 28% of maleand 10% of female respondents screened positive for lifetime symptoms ofalcohol dependence (Parry et al., 2005).1.1.2. The burden of harm associated with substance use disorders inSouth AfricaAnother indication of treatment need is provided by ad hoc studies that documentthe burden of harm associated with untreated substance use disorders. Studieshave reported high levels of mortality and morbidity that accrue from episodes ofacute alcohol intoxication (Matzopoulos, 2005; Pluddemann et al., 2004). FASrates in South Africa also point to the high levels of harm associated withsubstance abuse. These high rates of FAS point to the need for substanceabuse treatment among pregnant women (Carter et al., 2005; May et al., 2000).Emerging evidence also points to the need for substance abuse treatment amongHIV-positive persons. In a study of 149 recently diagnosed HIV-positive patients,9% met DSM-IV criteria for alcohol abuse, 10% met criteria for alcoholdependence, and 2% met criteria for drug dependence (Olley et al., 2004).In South Africa, a strong association has also been found between substanceabuse and crime, with a high proportion of arrestees reporting the need forsubstance abuse treatment (Parry, Pluddemann, Louw & Leggett, 2004). This isfurther evidence of the need for substance abuse treatment in South Africa.When considered together, these findings present a strong argument for theneed for accessible substance abuse treatment in South Africa.6

1.2. THE NEED FOR SUBSTANCE ABUSE TREATMENT IN THE CAPETOWN METROPOLECompared to other sites in South Africa, the need for accessible substanceabuse treatment is particularly evident in the Cape Town metropole. Forexample, findings from national household surveys have reported higherprevalence rates for risky drinking in the Western Cape Province relative to otherprovinces (Reddy et al., 2002; Shisana et al., 2005). The higher proportion ofsubstance-related traumatic injuries and alcohol-positive non-natural deaths inCape Town, relative to other sites also confirms the need for accessibletreatment services in this region (Matzopoulos, 2005; Peden et al., 2001;Pluddemann et al., 2004). In addition, compared to other sites, arrestees in CapeTown were more likely to be drug-positive than arrestees in Durban andJohannesburg (Parry et al., 2004b).Compared to other sites in the country, the widest range of drugs used alsooccurs in Cape Town. For example, in the second half of 2005, Cape Town wasthe only site reporting methamphetamine abuse, with 25% of patients attendingtreatment centres reporting this as their primary substance of abuse(Pluddemann et al., 2006). While treatment centre statistics only representpatterns of substance use among people who are able to access treatment;taken together with findings from household surveys and mortality, trauma andcrime studies, they illustrate that Cape Town, relative to other sites, has a higherprevalence of substance-related problems. These findings present a compellingargument for the need for accessible substance abuse treatment in this region.Consequently, this study focuses on access to substance abuse treatment in theCape Town metropole. In this study, access to treatment is defined as bothpotential access to services (namely, the degree to which factors that enable aperson to use a needed treatment service are present and the opportunity toseek needed services) and/or realized access (or the actual use of neededservices)(Andersen, 1995).7

1.3. IS ACCESS TO SUBSTANCE ABUSE TREATMENT IMPORTANT?There is strong evidence that access to effective treatment helps reduce theharms associated with substance abuse and benefits both the individual andbroader society. Although few treatment outcome studies have been conductedin South Africa, international research conducted across a variety of treatmentsettings and client populations provides considerable evidence of the benefits ofsubstance abuse treatment. These benefits include reductions in substance use,reductions in criminal activity, improvements in physical and psychological health,and improvements in social functioning (e.g. Gossop et al., 2001; McKay &Weiss, 2001; Paraherakis et al., 2000; Simpson, Joe & Brown, 1997). Giventhese benefits, a strong case can be made for the need to ensure that peoplewith substance use disorders are able to access treatment services.1.4. HOW ACCESSIBLE ARE SUBSTANCE ABUSE TREATMENTSERVICES IN SOUTH AFRICA?Despite the increased demand for substance abuse treatment services andevidence of the benefits associated with treatment, access to substance abusetreatment is limited in South Africa, particularly in Cape Town. This is partly dueto the limited availability of treatment services, with existing resources in CapeTown only able to serve approximately 2500 to 3000 people per year(Pluddemann et al., 2006). This is grossly inadequate, given that there are anestimated 15 000 heroin users in the city (Dewing et al., 2006) and thatconservative estimates from the SADHS suggest that at least 10% of thepopulation meet DSM-IV criteria for alcohol abuse and/or dependence (Parry etal., 2005). In a region that is home to about 3 million people (Statistics SouthAfrica, 2005), this would translate to about 300 000 people requiring sometreatment for alcohol-related problems.1.4.1. Racial inequities in access to health and social servicesWhile the limited availability of substance abuse treatment restricts access totreatment for all South Africans, substance abuse treatment seems to be8

particularly difficult to access for poor Black/African and Coloured South Africans 1who were historically disadvantaged during the apartheid regime. For theseracially-defined social groups, several socio-political factors historically restrictedaccess to substance abuse treatment. Under the apartheid system ofgovernance, funding to substance abuse treatment was generally inadequateand treatment facilities were poorly distributed; with services being concentratedin urban areas that were historically reserved for Whites. Major disparities alsoexisted between the racially-defined social groups in terms of the allocation ofresources to and the quality of substance abuse treatment services, withtreatment facilities serving White South Africans being relatively better resourcedand providing relatively more comprehensive services than facilities servingblack 2 South Africans (Myers et al, 2004; Myers & Parry, 2005).Since South Africa’s transition to democracy in 1994, the health and socialservice sector has worked hard to improve service delivery and reverse racialdisparities in the provision of services for historically underserved groups. Yetconcerns about disparities in both the need for and accessibility of health andsocial welfare services between the socially advantaged and the sociallydisadvantaged remain, with socio-economic disadvantage remaining associatedwith race (Sanders & Chopra, 2006).In summary, despite the political and social transformations that have occurredsince 1994, many racial inequities remain in the Cape Town metropole, withhistorically disadvantaged communities (HDCs) still characterised by poverty,limited access to basic services and high levels of crime-related violence(Kalichman et al., 2006). Given these inequities, it is plausible that similar racialinequities exist in access to substance abuse treatment.1 The terms “White, Black/African, Asian/Indian, and Coloured” refer to demographic markers anddo not signify inherent characteristics. These markers were chosen for their historicalsignificance. These markers are important as accurate user profiles assist in identifyingvulnerable sections of the population and in planning effective intervention programmes.2 The term “black South African” refers to all groups who were historically disadvantaged underthe apartheid regime including ethnic Black/African, Coloureds of mixed race descent andIndian/Asians.9

1.4.2. Racial disparities in the need for and access to treatmentEmerging evidence suggests that poor Black/African and Coloured communitiesmay be especially vulnerable to substance use disorders, due to thepsychological stress associated with rapid urbanization, poverty, neighbourhoodsocial dysfunction, and a lack of basic infrastructure (Flisher & Charlton, 2001;Kalichman et al., 2006) – factors that characterise these communities. Severalstudies point to relatively high levels of substance abuse in these communities.For example, a study of 110 community-based organisations (CBOs) that provideservices to mainly to HDCs reported that 27% of the clients served by thesefacilities had alcohol-related problems and 23% had drug-related problems(Pasche, Myers & Louw, in press). In addition, a survey of 384 predominantlyBlack/African and Coloured patients attending general practitioners’ practices inCape Town found that 60% of current drinkers drank at problematic levels(Koopman, Reagon, Parry & Myers, unpublished). Finally, a study conducted inBlack/African and Coloured residential areas in Cape Town found a prevalencerate of 45% for alcohol use and 19% for cannabis use (Kalichman et al., 2006).These studies suggest that a significant proportion of black clients haveuntreated substance use disorders.However these studies are still likely to under-report treatment need, especiallyas they preceded Cape Town’s methamphetamine epidemic. While these studiesstill do not directly examine whether unmet treatment need is greater forBlack/Africans and Coloureds relative to Whites, the current study argues that inthe light of persisting racial inequities in income and access to essential services,poor Black/African and Coloured substance users experience more difficultyaccessing substance abuse treatment services than their White counterparts.Concerns about the accessibility of substance abuse treatment for poor blackSouth Africans seem justified. According to recent findings (Myers et al., 2004;Myers & Parry, 2005; Pluddemann et al., 2006), the race profile of clients attreatment facilities does not reflect the demographics of the general population.In Cape Town, specifically there has been an under-representation of Black and10

an over-representation of White South Africans in treatment facilities. Forexample, the proportion of Black/African clients declined from 12% in 2000 to 7%of all clients in treatment in 2004 (Myers et al., 2004) – despite the fact thatBlack/Africans comprise roughly 32% of the general population in the Cape Townmetropole (Smith, 2005). This is worrisome as the high levels of substance useamong Black/African and Coloured communities suggest that this pattern ofservice utilization reflects the limited extent to which black South Africans haveaccess to treatment rather than lower levels of substance use in thesecommunities (Myers et al., 2004; Myers & Parry, 2005).1.4.3. Access to treatment in Cape TownIn the Cape Town metropole, residential treatment is provided by approximately16 inpatient clinics, one of which is a specialized ward of a general statepsychiatric hospital and another of which is a state facility providing free services.The remainder of these facilities are either private non-profit facilities (n= 7)offering low-cost services (but requiring co-payment fees) or private for-profitfacilities charging high fees (n = 7). Outpatient treatment services are provided byfour agencies, one of which has several satellite offices. These facilities providelow-cost services, however clients are required to pay for each visit. Eventhough relatively affordable, the costs of these services can still be exorbitant formany indigent clients.Despite the apparent availability of substance abuse treatment in the metropole,for the uninsured, who are disproportionately represented by poor, black SouthAfricans (Goosen et al., 2003), the availability of affordable substance abusetreatment remains limited. The shortage of publicly-funded substance abusetreatment centres, together with the increased demand for treatment in HDCs,has given rise to a growing private non-profit treatment sector. Although many ofthese are professionally-run accredited facilities with solid treatmentprogrammes, in recent years several facilities have been started by well-meaningcommunity members with little knowledge of how to treat substance usedisorders and few resources. Often these community-based facilities operate11

illegally and are unregulated by the state. Although private non-profit facilities arerelatively more accessible to HDCs than for-profit services, the quality of servicesprovided by these facilities is often variable and waiting lists at the betterresourced facilities are often lengthy. In addition, many of the accredited nonprofitfacilities require clients to make some form of financial contribution towardstheir treatment (Myers, 2004b). Quality of services, waiting lists, and co-paymentfees may all restrict access to treatment for persons from HDCs.1.5. PRIOR RESEARCH AND THE WAY FORWARDTo date, planning and decision-making around substance abuse treatment in theCape Town metropole has been hampered by a lack of accurate information onsubstance abuse treatment need, patterns of service delivery, and patterns oftreatment utilization (Myers & Parry, 2005). Substance abuse treatment servicesresearch (which could address this issue) has been characterised by a largelydescriptive focus on (i) the extent to which treatment centres are used by clientsfrom historically disadvantaged population groups and (ii) the extent to whichtreatment facilities target factors thought to be barriers to service utilization(Myers, 2004a; Myers, 2004b; Myers & Parry, 2002). This early research hasseveral limitations. Firstly, as it has not compared recipients of services withcommunity-based samples of untreated substance users, it has been difficult toidentify factors that facilitate or restrict access to treatment. This has hamperedthe development of interventions to improve access for under-served groups.Secondly, previous studies have tended to extrapolate findings from developedcountries and apply them directly to the South African context. As the factorsthat enable and restrict access to substance abuse treatment among historicallydisadvantaged communities in South Africa have not been directly examined, thedegree to which findings from developed country settings can be extrapolated tothe South African context remains unclear. This is cause for concern as theidentification of locally-relevant environmental and contextual barriers is essentialfor the development of interventions that are theoretically sound, acceptable to,12

and culturally-appropriate for the communities they target. The current studydirectly addresses this gap in South African treatment services research.Thirdly, prior research on access to substance abuse treatment services hasgenerally been atheoretical. These earlier studies failed to incorporate analyticalmodels that provide a theoretical context for the interpretation of findings andthus provide limited insight into how barriers interact with need to predict accessto treatment. This atheoretical approach not only limits our understanding of therelationships between predictors of access but also makes it difficult to developinterventions that effectively enhance access to services. This study redressesthis limitation by applying a widely accepted theory of health service utilization tothe substance abuse treatment arena.Finally, a study that describes whether difficulties in access to substance abusetreatment exist (and the reasons for these difficulties) is useful as it can (i)identify areas that can be changed by policy, (ii) guide the design of interventionsto improve access, and (iii) suggest ways in treatment service delivery can beimproved (Thind & Andersen, 2003). In addition, through developing evidencebasedinterventions to improve access, this study could help redress inequities inservice delivery.1.6. OVERALL PURPOSE OF THE STUDYThe purpose of this study is to explore access to substance abuse treatment forpeople from HDCs in the Cape Town metropole. The study aims to identifyfactors associated with access to treatment in HDCs and to determine whetheraccess is equitable. Using the Behavioural Health Services Utilization Model as aframework, this study compares and contrasts out-of-treatment substanceabusers and recipients of treatment on a range of factors thought to beassociated with treatment utilization. It is hoped that findings from this study willbe used to develop interventions that enhance access to substance abusetreatment for persons from these communities.13

CONCEPTUAL MODELThis study’s conceptual model (Figure 1) is an adaptation of the BehaviouralModel of Health Services Utilization (BHSU) (Andersen, 1995). The BHSU is awell-established framework for understanding the determinants of health careaccess and continues to be a relevant and revolving model in health servicesresearch (Aday & Awe, 1997). This model adopts a systems approach thatintegrates a range of individual, contextual and provider-related variablesassociated with the use of health services (Phillips et al., 1998).Figure 1.Conceptual model of access to treatment based on the BHSUEnvironmentHealth system• Policy• Resources• OrganizationSubstanceabusetreatmentsystem• Policy• Resources• OrganizationExternalenvironment• Power• Historicaland politicalinfluences• Economics• PolicyPopulationCharacteristicsPredisposingattributes• Demographic• Socialstructure• Health beliefs• SocialcognitiveEnablingattributes• Personal• Community• ProviderNeed• Perceivedneed (internal)• Perceivedneed (external)• EvaluatedneedHealth behaviourUse of substanceabuse treatmentservices• Type• Site• Purpose• Frequency14

2.1. POPULATION CHARACTERISTICS INFLUENCING HEALTHSERVICES UTILIZATIONThe BHSU suggests that health service utilization is partly a function of theseparate and combined influence of three categories of populationcharacteristics: predisposing factors, factors which enable/restrict health serviceuse, and need for care variables (Andersen, 1995; Andersen & Davidson, 1997).2.1.1. Predisposing characteristicsThis model defines predisposing characteristics as variables that exist within theindividual prior to the onset of a particular health need and that predispose theindividual to take a particular course of action (Andersen, 1995; Andersen &Newman, 1973). These variables reflect the propensity of an individual to useservices and seem to be associated with help-seeking in the presence of needvia their influence on enabling factors (Andersen, 1995). The following areincluded in the predisposing variable domain: demographic, social structure, andattitudinal-belief variables. This study also includes social-cognitive variables. Demographic and social structural factorsDemographic variables (such as age and gender) represent biologicalcharacteristics that may be associated with the probability of a person usinghealth services (Andersen, 1968; Andersen, 1995). Although demographicvariables are generally immutable and not easily influenced by policy changes,these variables can reflect opportunities for intervention (Booth et al., 2001).Social structural characteristics reflect the location (status) of the individual insociety, as measured by ethnicity/race; socio-economic status; education; andsocial environment, including neighbourhood disadvantage, state of physicalenvironment and community resources (Andersen, 1968; Andersen & Newman,1973; Thind & Andersen, 2003). These weakly mutable characteristics mayimpact on ability to access treatment via their influence on (i) status within acommunity and (ii) enabling/restricting factors such as ability to cope with15

presenting problems and ability to gather resources to address problems(Andersen, 1995; Andersen & Davidson, 1996; Thind & Andersen, 2003). Attitudinal-belief variablesAttitudinal-belief variables refer to the attitudes and beliefs that people haveabout specific health problems and health services. Beliefs about the efficacy ofhealth care and attitudes towards service providers may influence (i) perceptionsof need and (ii) whether individuals seek care (Andersen, 1995; Booth et al.,2001; Thind & Andersen, 2003, Wallace et al., 2004). Attitudinal-belief variablesmay help account for how social structural factors influence enabling factors anduse of services (Andersen, 1995). The present study includes measures ofhealth beliefs that are specific to the substance abuse treatment context, namelybeliefs about treatment and community views about access to treatment. Psychological predisposing variablesStudies using the BHSU as an organizing framework have generally excludedpsychological characteristics from their understandings of predisposing factors(Andersen, 1995; Bradley et al., 2002) – despite the fact that other theories ofhelp-seeking have shown that psychosocial factors play an important role indecision-making processes (Bradley et al., 2002). To address this limitation, thepresent study expanded the set of predisposing factors to include social-cognitivefactors; specifically self-efficacy to change substance use which is associatedwith help-seeking in the substance abuse treatment literature (Broyles, Narine, &Robertson, 2004).2.1.2. The enabling variable domainThe BHSU defines enabling factors as resources that facilitate (or restrict) theindividual’s use of substance abuse treatment services when services arerequired (Andersen, 1995). These factors represent the actual ability of anindividual to obtain health services (Andersen, 1995; Booth et al., 2001; Wallaceet al., 2004) and are mutable by interventions (Andersen, 1995). The modelassumes that as enabling resources increase, the likelihood of accessing care16

when needed becomes greater (Andersen, 1995). The BHSU postulates that theenabling domain includes personal, community and organizational resourceswhich interact to influence service utilization (Andersen, 1995). Personal enabling resourcesThese include individuals’ knowledge and awareness of services and their meansof using services. These resources are indicated by factors such as income,medical insurance coverage, having a regular source of care, language, andawareness of services (Andersen, 1995; Rew, 1998) as well as functioning inareas such as employment, social relationships and physical and mental health(Tucker et al., 2004). This study expanded these core personal enablingresources to include competing needs. This variable refers to difficulties inmeeting subsistence needs and has been identified as an important enablingvariable among vulnerable populations, including impoverished communities(Gelberg et al., 2000; Wenzel et al., 2001). Community & organizational enabling resourcesThese include attributes of the community where the individual lives andorganizational attributes of the health provider that enable the individual to obtainservices (e.g. convenience, availability of services, affordability of services,spatial distribution of services, accessibility of services, perceived acceptability ofservices, and adequacy of supply to meet needs) (Andersen, 1995; Rew, 1998).In addition, this study examines the following community enabling resources:social capital, community social support, and community stigma. These variableshave been shown to strongly influence help-seeking for substance use disorders(Brown et al., 2004). In addition, the qualitative component of this study providesan in-depth analysis of the role of organizational and community factors inshaping access to substance abuse treatment services.2.1.3. Need for health servicesThe BHSU assumes that need variables reflect illness levels that are sufficientlysevere enough to warrant access to treatment services. According to the BHSU,17

need for services is the most immediate determinant of health service utilization(Andersen, 1995), with the model assuming that some health service need mustalways be present for service utilization to occur (Andersen, 1995; Thind &Andersen, 2003). More specifically, the BHSU distinguishes between perceivedand evaluated need for health services (Andersen, 1995; Wallace et al., 2004). Perceived needThis refers to how people view their own health and functionality (Andersen,1995; Rew, 1998). Perceptions of need are based on self-assessments of healthstatus and the extent to which symptom severity impairs functioning and qualityof life. These judgements can be made by the individual, family caregivers, orthe larger community (Andersen, 1995; Andersen & Thind, 2003). As individualswith substance use disorders often have low levels of perceived need and mayaccess treatment due to external pressures from family, employers, or thecriminal justice system (Booth et al., 2001; Hser et al., 1998), this study examinespersonal perceptions of treatment need as well as perceptions by others aboutan individual’s need for treatment. In this study, variables such as problemrecognition, treatment motivation and desire for help reflect personal perceptionsof need. Evaluated needThis refers to professional judgements and clinical evaluations about anindividual’s health status and their need for health services (Andersen, 1995;Thind & Andersen, 2003). This model recognizes that as utilization may occurindependently of objectively assessed need, perceived need must be present forservice utilization to occur (Andersen, 1995; Thind & Andersen, 2003).2.2. THE CONTEXTUAL / ENVIRONMENT DOMAINThe BHSU identifies two types of societal determinants of health serviceutilization: factors at the level of the health care system (Andersen & Newman,1973) and external environmental influences (Andersen, 1995). These societaldeterminants are thought to interact to influence individual-level determinants of18

health service utilization, and consequently the use of health services (Andersen,1995; Andersen & Newman, 1973).2.2.1. Health care system factorsFactors at the level of the health care system are also seen as determinants ofaccess to services (Andersen, 1995), primarily because the health systemstructures the provision of health services in society. The BHSU proposes thatthe health care system consists of three dimensions: health policy, health-relatedresources and health care organization (Andersen, 1995). Together thesedimensions shape health service delivery and influence the extent to whichenabling resources are present in society, the degree to which health-relatedneeds are perceived, and the use of services (Phillips et al., 1998).More specifically, health (and social welfare) policies are understood to influencelegislation and social norms concerning the structure and functioning of thehealth system, including resource allocation, training of health workers, andhealth priorities (Andersen, 1995; Andersen & Newman, 1973). Health systemresources are defined in terms of the financial and personnel resources allocatedfor health care (Andersen & Newman, 1973). These resources include personnelresponsible for service delivery, health care facilities, as well as technology,equipment and materials used to provide services (Andersen & Newman, 1973).The BHSU defines the organizational dimension in terms of the distribution ofhealth resources, including the co-ordination and regulation of personnel andfacilities (Andersen & Newman, 1973). This dimension is comprised of twoelements; access and structure. Access refers to the way in which a persongains entry into the system and is indicated by eligibility requirements and systembarriers such as waiting times, referral processes, and gatekeepers. In contrast,structure refers to factors that determine the type of services received once aperson enters the system.19

This study focuses specifically on health care system factors as they apply tosubstance abuse treatment services. The choice of substance abuse treatmentsystem factors is based on findings from national research (Myers, 2004). Asindicators of resource allocation and system organization are largely unavailablefor the South African substance abuse treatment system, this study usesqualitative methods to examine these variables.2.2.2. Factors within the external environmentAccording to the BHSU, other contextual factors that influence an individual’sability to access health care include external environmental influences, such asthe economic, political, and social milieu, and prevailing social norms (Andersen,1995; Litaker & Love, 2005; Phillips et al., 1998; Rew, 1998). This group of interrelatedcharacteristics represents several basic influences that shape theopportunities available to individuals independently of their personalcharacteristics (Litaker & Love, 2005), by providing a context for health servicedelivery (Rew, 1998).This study weaves an understanding of the socio-cultural context within which theSouth African substance abuse treatment system is located throughout itsconceptual framework; particularly in the qualitative component of the studywhich explicitly explores the influence of contextual factors on realized access.The inclusion of these factors is based on the understanding that substanceabuse outcomes, the use of substance abuse services, and the structure andfunctioning of the substance abuse treatment system are shaped by political andeconomic ideologies, power relations and socially constructed roles inherent inany given society (Morgan et al., 2004; Zurayk, 2001).2.3. THE HEALTH BEHAVIOUR DOMAIN: UTILIZATIONThe conceptual model in this study focuses on one aspect of the BHSU’s healthbehaviour domain, namely health services utilization. This is viewed as animmediate outcome of access to health care (Andersen, 1995). The BHSUdefines health service utilization as obtaining health care provision in the form of20

a health care contact (Andersen, 1995). Studies using the BHSU have used thefollowing indicators of health service utilization: type of visit, location and site ofvisit, frequency of visits, and intensity of care received (Andersen, 1995;Andersen & Thind, 2003). This study focuses specifically on the use ofsubstance abuse treatment services.2.4. WHEN IS ACCESS EQUITABLE?For the purposes of this study, it is also important to distinguish betweenequitable and inequitable access. While the concept of equality refers to equalopportunities to use a facility or service, equity involves the just distribution ofservices in relation to need (Aday, Begley, Lairson et al., 1999). According to theBHSU, equitable access occurs when services are distributed according to healthcare needs and that inequitable access occurs when social structural variables,health belief factors, and/or barriers to service use determine who receives care(Andersen, 1995). Access is therefore inequitable when predisposing factorsand/or enabling resources are the main predictors of utilization.The following section describes the specific aims of the study and how the BHSUis used to achieve these aims.21

METHOD3.1. STUDY AIMS & OBJECTIVESAim 1: To identify factors that predict access to substance abuse treatmentservices for people from historically underserved communities in the Cape Townmetropole.Objectives:• To identify predisposing factors associated with substance abusetreatment utilization.• To identify enabling/ restricting factors associated with substance abusetreatment utilization.• To examine the need for treatment variables associated with substanceabuse treatment utilization.• To identify and describe the socio-contextual factors associated withsubstance abuse treatment utilization.Aim 2: To examine whether access to substance abuse treatment in SouthAfrica is equitable.Objectives:• To identify which variable domain is the strongest predictor of access totreatment.Aim 3: To describe socio-demographic differences on predisposing, enabling andneed for treatment variable domains among subjects who do not accesssubstance abuse treatment.Objectives:• To identify gender differences on predisposing, enabling and need fortreatment variable domains among subjects who do not access substanceabuse treatment.22

• To identify race differences on predisposing, enabling and need fortreatment variable domains among subjects who do not access substanceabuse treatment.Aim 4: To identify variables associated with predictors of substance abusetreatment utilization among subjects who did not access treatment.Aim 5: To describe the challenges of delivering substance abuse treatmentservices in a resource-poor setting with historically underserved anddisadvantaged communities.Aim 6: Based on the study’s overall findings, to make recommendations andinform intervention efforts to improve access to treatment for historicallydisadvantaged communities in the Cape Town metropole.3.2. STUDY DESIGNWe used a multi-level mixed model research design that consisted of a crosssectionalcase-control study (phase 1), followed by a separate qualitative study(phase 2). This mixed methods design allowed the researcher to gain insightsinto aspects of access to substance abuse treatment at different levels; withphase 1 focusing on intra and inter-personal factors associated with access totreatment and phase 2 focusing on contextual influences on access to treatment.While the knowledge generated by these studies is level-specific, the use of theBHSU model (Andersen, 1995) as a guiding framework for both studies allowsresults from each phase to be integrated so that global inferences about accessto substance abuse treatment for historically disadvantaged communities in theCape Town metropole can be made.The case-control study compared substance abusers from historicallydisadvantaged communities who accessed treatment (cases) with substanceabusers from historically disadvantaged communities who did not accesstreatment (controls) on a range of population-based predisposing, enabling andneed variables thought to be associated with access to treatment. This allowed23

the researcher to explore possible causes and factors associated with access. Tominimize the risk of bias, this study obtained a response rate of 98.3% -well overthe recommended 70%. Recall bias was limited by using time-line follow back(TLFB) procedures to collect retrospective data. TLFB procedures improve theaccuracy of historical substance abuse data collection.In contrast, the qualitative case study examined contextual and substance abusetreatment system influences on access to treatment for substance abusers fromhistorically disadvantaged communities. This part of the study examined theinfluence of multiple variables on access to treatment, specifically communitylevelinfluences, substance abuse treatment system organization and resources,and broader contextual influences such as the role of government and the healthcare system. This component of the study also integrated multiple perspectiveson access, including the voices of treatment service providers and localcommunities. The inclusion of these multiple variables and multiple perspectivesallowed us to examine how the substance abuse treatment system andindividuals seeking care interact with each other.There are several advantages to examining the access phenomenon throughboth quantitative and qualitative lenses, including allowing for a morecomprehensive understanding of access to treatment to be gained than would befrom using a single approach (Stufflemean, 2001). Phase 2 also helps improvethe explanatory power of phase 1 by identifying factors within the treatmentsystem that clarify and help interpret findings from this phase. In addition, asquantitative and qualitative methods have their own set of strengths andweaknesses, combining methods (and triangulating different data sources)enhances the validity, reliability and usefulness of the full set of findings(Stufflemean, 2001; Teddlie & Tashakkori, 2003). This allows for many of thelimitations of a single approach to be overcome (Teddlie & Tashakkori, 2003).The following sub-sections describe each phase of the study separately.24

3.3. PHASE 1: CASE-CONTROL STUDY3.3.1. Sample characteristics3.3.1.1. Eligibility criteriaSubjects had to meet the following eligibility criteria: they had to be at least 18years old; self-identify as either Black/African or Coloured; earn less than R1500per month from legal sources; have a lifetime substance dependence diagnosis(either treated or untreated); and provide written, informed consent to participate. Sampling methodAs the target population consisted of a hard-to-reach population for which limitedinformation was available, snowball sampling techniques were used to identifysubjects (Babbie & Mouton, 2001). During the data collection period, cases wereidentified at non-profit substance abuse treatment facilities in the Cape Townmetropole, with which the researcher had well-established relationships. Thesecentres were identified as starting points for sampling as compared to the forprofittreatment sector; they are more likely to serve clients from historicallydisadvantaged communities. In addition, community contacts were used toidentify controls in each of the 12 recruitment areas. These cases and controlsserved as starting points for snowball sampling by referring the researcher toother potential subjects. This chain referral process continued until the cases andcontrols adequately represented recruitment areas and the desired sample sizehad been obtained.As race and gender were identified as potential confounders of access totreatment, equal proportions of male and female as well as Black/African andColoured subjects were sampled and frequency matching was used to ensurethat the cases and controls were matched on these dimensions. Race andgender were also controlled for in statistical analyses. Recruitment areasTo ensure that controls represented the population of substance abusers fromhistorically disadvantaged communities (HDCs) in the Cape Town metropole, two25

esidential areas from each of the six sub-structures of the Cape Town metropolewere selected as key focus areas for sampling. To be selected, the area had toconsistently appear in SACENDU’s list of top ten residential areas for substanceuse or be identified by key informants as an area with high levels of substanceuse. Selected areas also had to be classified as “Black” or “Coloured” residentialareas under the apartheid regime; have high levels of health and socialproblems; have limited infrastructure to support service delivery; and be lowincomeareas.For this study, recruitment areas included: Atlantis and Dunoon in theBlaauwberg/ Northern sub-structure, Delft and Khayelitsha in the Tygerberg substructure,Eersterivier and Wallacedene in the Oostenberg/Eastern sub-structure,Macassar and Lowandle in the Helderberg sub-structure, Langa and Retreat inthe Southern Peninsula sub-structure, and Mitchell’s Plain and Gugulethu in theCentral sub-structure of the Cape Town metropole. Characteristics of the final sampleA non-random, snowball sample of 989 participants was drawn from the selectedrecruitment areas. The final sample consisted of 434 cases and 555 controls. Ofthese controls, approximately 46 were selected from each recruitment area. Chisquaretests of association reveal that cases and controls did not differ bygender, or race. Demographic data for this study are shown in Table Procedures3.3.2.1. Pilot testingPrior to initiating phase 1, the Access to Treatment Survey Questionnaire (ATQ)was pilot-tested among 40 substance users from two historically disadvantagedcommunities in Cape Town. Feedback from the pilot-testing allowed researchersto refine the ATQ and change problematically worded items prior to the mainstudy. Pilot-testing also allowed the reliability of the scales that comprise the ATQto be established for a South African substance-using population. As feedbackfrom fieldworkers, key informants and participants revealed that most individuals26

in the urbanized communities of the Cape Town metropole had a good grasp ofEnglish, the researchers decided not to translate the ATQ and instead employedtrained fieldworkers, who were fluent in at least two of the three official languagesof the region and could translate items where needed. FieldworkersAll fieldworkers employed in the study had extensive experience in conductingcommunity surveys related to substance use and had close ties to the targetrecruitment areas. This facilitated entry into these communities. Fieldworkersalso completed 40 hours of training in data collection procedures, such asrecruitment, quality assurance, screening and interview administration; researchethics; and alcohol and drug-related issues. In order to maintain data quality,fieldworkers were closely monitored by a fieldwork manager and by theresearchers. Data collection: casesResearchers contacted all inpatient and outpatient non-profit substance abusetreatment facilities in the Cape Town and described the study. Having obtainedthe support of these service providers, counselling staff were trained to identifyclients that met the study’s selection criteria. Prior to screening potential casesfor eligibility, counsellors obtained written informed consent from theseindividuals. All 440 persons screened met the study’s eligibility criteria. Onceeligibility had been established, locator information (e.g. residential address andcontact telephone numbers) was obtained so that fieldworkers could contactrecruits to arrange for an interview. Fieldworkers contacted recruits to obtainwritten informed consent to conduct an interview during which the ATQ would beadministered. Only 6 recruits refused to participate. This interview tookapproximately 90 minutes to complete and was generally conducted in recruits’place of residence.27 Data collection: controlsFieldworkers entered target communities by contacting community organizations,community leaders, and individuals in the community known to have interests inthe substance abuse field. Having explained the study’s goals and obtained thesupport of these community contacts, fieldworkers asked these key contacts toidentify potential recruits for the study. Key contacts were easily able to identifysubstance users within their communities- this is partly due to the social andpolitical structure of poorer South African communities where people live togetherin close confines and often depend on each other for financial survival. In suchcommunities, keeping issues such as drug use private is often a challenge.Fieldworkers contacted these potential controls and after explaining the aims ofthe study, obtained written informed consent to screen them for eligibility toparticipate in the study. The interviewer-administered brief screener tookapproximately five minutes to complete. Participants were given feedback fromthe results of the screener and those who did not meet the study’s eligibilitycriteria were thanked for their participation and given a resource list of substanceabuse-related services. Of the 559 participants screened, only 4 did not meet thestudy’s eligibility criteria. For the eligible participants, fieldworkers obtainedwritten consent to conduct a full interview. A time and place was arranged whereparticipants could complete the interviewer-administered ATQ in private. Thisinterview took approximately 90 minutes to complete. Although participants didnot receive financial incentives; fieldworkers did provide participants withrefreshments as well as feedback from their interview and referrals to substanceabuse treatment, mental health and social welfare-related services.3.3.3. Data collection tools3.3.3.1. The brief screenerThis tool determined eligibility to participate in the study. The screener collectsinformation on socio-demographic variables such as area of residence, gender,age, race, and legal income in the last 30 days. Controls were screened forcurrent substance use disorders (SUDS) using the Texas Christian University28

Drug Screen (TCUDS-II, Knight et al., 2002). As cases were known to have alifetime diagnosis of substance dependence, they were not screened for SUDS.The TCUDS had good internal reliability, with this study obtaining a coefficientalpha of . The Access to Treatment Survey Questionnaire (ATQ)The ATQ, designed to examine access to substance abuse treatment amongSouth African populations, is a 45-page questionnaire that collects self-reportinformation on several domains, including factors thought to predispose personsto seeking treatment, factors thought to enable or restrict access, need fortreatment variables, and utilization of substance abuse services. The ATQconsists of scales that were constructed for the purposes of this study andexisting standard questionnaires. The following sub-sections summarise thedomains and measures comprising the ATQ in more detail (see Table 1).• Utilization of substance abuse treatment servicesThe dependent variable for this study is realized access or utilization oftreatment. This was assessed by the question: “Have you ever gone anywhereor seen anyone for help with alcohol and/or drug-related problems? “• Need for substance abuse treatmentThe ATQ assesses perceived and evaluated need for substance abuse treatmentas well as severity of SUDS - with greater severity indicative of more treatmentneed. Perceived need is examined by the following questions: “Do you think youhave an alcohol or drug problem?”, “Do you think you need help to change youralcohol and/or drug use?”, and “Have other people suggested that you need helpto change your use of alcohol/drugs?” The Substance Use Disorders module ofthe Structured Clinical Interview for DSM-IV-TR (SCID-I, First et al., 1997) isused to objectively evaluate need for treatment. The following scales alsoexamine perceived need:29

o Problem recognition, Desire for help and Treatment readinessThe 9-item Problem Recognition (PR) scale measures the extent to whichparticipants’ perceive problems related to their substance use. The 6-item Desirefor Help (DH) scale examines intrinsic need for change and interest in gettinghelp. The 8-item Treatment Readiness (TR) scale assesses commitment levelsand expectations about how helpful substance abuse treatment will be (Knight,Holcom & Simpson, 1994). This study obtained Cronbach alpha coefficientsof.86 for the PR scale,.86 for the DH scale, and .68 for the TR scale.o Readiness to changeThe Stages of Change, Readiness and Treatment Eagerness Scale(SOCRATES, Miller & Tonigan, 1996) measures readiness to change substanceuse; with higher scores indicating greater readiness to change. This scale hasgood internal reliability, with alpha coefficients of .91 and .95 being obtained forthe pilot and main study, respectively.• Predisposing factors for access to treatmentThe ATQ contains several variables thought to be predisposing factors for accessto substance abuse treatment. These include demographic and social structuralfactors; beliefs and attitudes related to substance abuse treatment; and socialcognitive factors including readiness to change substance use, self-efficacy,problem recognition, desire for help, and treatment readiness.o Demographic and social-structural factorsThe ATQ includes the following socio-demographic variables: age, gender,race/ethnicity, education, marital status, employment status and deprivation. Arelative deprivation index was constructed for the study, with higher scoresindicating relatively less socio-economic deprivation.o Beliefs about substance abuse treatmentThe 12-item “Community beliefs about substance abuse treatment” scalemeasures community beliefs about the effectiveness of substance abuse30

treatment, with higher scores reflecting more negative beliefs. This scale hasgood internal reliability, with Cronbach alpha coefficients of .74 and .81 obtainedin the pilot and main study, respectively.o Social cognitive factors.• Self-efficacyThe Alcohol and Drug Use Self-efficacy Scale, Confidence version (ADUSE-C,Brown et al., 2002) is a 20-item scale that assesses self-efficacy as it applies toalcohol and drug abstinence. Good internal reliability was obtained for thismeasure (Cronbach alpha coefficient = .97).• Enabling and restricting factors for access to treatmento Affordability barriersSeveral items examine the affordability of substance abuse treatment services,including questions about monthly income and access to medical insurance.o Awareness barriersIn the ATQ, a single-item question asks participants if they know where to go forsubstance abuse treatment. Participants are also asked to list the number ofsubstance abuse treatment facilities that they are aware of.o Availability and accessibility of treatment servicesTwo items examine the availability of alcohol and drug services withincommunities. Two questions also examine the geographical accessibility ofservices in terms of distance to treatment and travelling time to treatment. A 3-item “Delays in accessing treatment scale” examines delays in accessingtreatment due to distance, gatekeepers and waiting lists. This study obtained aCronbach alpha coefficient of .72 for this scale.o Perceived appropriateness of treatment servicesA 5-item “Culture and gender barrier scale” examines the extent to which a lackof culture and gender appropriateness within treatment services serves as abarrier to seeking treatment.31

Table 1.Domains and measures comprising the ATQDomain Variables Scale and indicatorsUtilization Use of treatment Use; type, frequency & amount of treatment; treatment completionPredisposing SociodemographicAge, education, gender, raceNeighbourhood environment NES; safety, substance use, and crime in communitiesRelative deprivationRelative deprivation indexBeliefs/attitudes to treatment Beliefs about treatment effectiveness, perceptions about access, treatment concernsSelf-efficacyADUCE-C, self-efficacy to stop AOD use for one month and > 1 monthNeed Evaluated needDrug severity scale based on SCIDPerceived need- internal Perceived AOD problem, perceived need for treatmentPerceived need- external Others suggest need for treatmentReadiness to change SOCRATES scaleTreatment motivation TCU problem recognition, desire for help & treatment readiness scalesEnabling AffordabilityMedical Aid, income, employment status, affordability barrier scaleCompeting prioritiesCompeting priorities: money for food and need to care for othersAwarenessAwareness of services (Yes/No), Number of facilities aware ofAvailabilityExtent to which alcohol and/or drug treatment availableGeographic accessDistance and time to treatment, Delays in accessing treatmentTreatment appropriateness Treatment utility scale, Culture and gender appropriateness scaleStigmaStigma consciousness and stigma towards substance abusers scalesPsychological functioning TCU depression, anxiety, and self esteem scalesSocial supportRAND- MOS social support scale, TCU abstinence support scaleSocial capitalNeighbourhood trust scale, Social cohesion scale32

In addition, a 2-item “Utility barrier scale” examines the extent to which treatmentservices are perceived to be effective and useful. This study obtained Cronbachalpha coefficients of .81 and .78 for the culture/gender scale and the utility scale,respectively.o Competing prioritiesThe ATQ includes two questions about whether the need to take care of othersand/or the need to pay for food and shelter limits access to treatment.o Barriers related to psychological functioningThe ATQ includes self-esteem, depression and anxiety scales. These scales havegood reliability, with Cronbach alpha coefficients of .93, .85, and .92 beingobtained for the self-esteem, depression and anxiety scales during the mainphase of the study.o Stigma-related barriersThe 10-item Stigma Consciousness Scale measures expectations of being judgedon the basis of one’s substance abuse (Ross et al., 2005), with higher scoresreflecting greater degrees of internalized stigma. Cronbach alpha coefficients of.90 and .84 were obtained for the pilot and implementation phases, respectively.The 16-item Stigma towards Substance Abusers Scale measures communitybasedstigma towards substance users, with higher scores reflecting moreperceived stigma. A Cronbach alpha coefficient of.84 was obtained in this study.o Barriers associated with neighbourhood environmentThe Neighbourhood Environment Scale (NES, Crum et al., 1996) measuresneighbourhood disadvantage. This scale has good internal reliability, with thisstudy obtaining a Cronbach alpha coefficient of .82. The ATQ also includesquestions that examine perceived levels of crime, poverty, alcohol and drug use inparticipants’ neighbourhoods.o Barriers related to social support• RAND MOS-SSS (Sherbourne & Stewart, 1991)33

The 19-item MOS-SSS measures functional dimensions of perceived socialsupport. The MOS-SSS consists of 4 subscales: the emotional and informationalsupport subscale measures the extent to which others are perceived to expressunderstanding and offer advice and information, the tangible support subscaleassesses the extent to which others are perceived to provide material aid, thepositive social interaction subscale measures the extent to which others areperceived to be available to do fun things with, and the affectionate supportsubscale measures the extent to which others are perceived to express feelings ofaffection for the respondent. The MOS-SSS has good internal reliability, withCronbach alpha coefficients of.97 being obtained for the composite score. Morespecifically, the pilot and main study obtained subscale alpha coefficients thatranged between .80 and .96.• TCU Social Support ScaleThe 9-item TCU Social Support scale measures the extent to which others act asexternal supports for treatment and abstinence from substance use, specifically.Higher composite scores indicate greater levels of support for treatment andabstinence. This study obtained a Cronbach alpha coefficient of .77.o Barriers related to social capitalThe ATQ included two indicators of social capital: interpersonal trust and socialcohesion. The 17-item Neighbourhood Trust Scale measures the extent to whichparticipants trust others, with higher scores reflecting greater social trust. Thisscale has good internal reliability, with the main study obtaining an alphacoefficients of.86. The 5-item Social Cohesion Scale (Sampson et al., 1997) is aneighborhood-level measure of social cohesion, with higher scores reflectinggreater levels of cohesion. A Cronbach alpha coefficient of .83 was obtained forthe main study.3.3.4. Data analysisAll quantitative data were analysed using the Statistical Package for the SocialSciences (SPSS, Norusis, 1999). To examine significant differences between34

participants who accessed and those who did not access treatment on bivariateanalyses consisting of Chi-squared tests and t-tests of means were conducted oneach of the variable domains. Multiple Logistical Regression analyses wereperformed to identify factors that predict “access to treatment” versus “no access”,and to determine whether access was equitable. For subjects who did not accesstreatment, bivariate analyses such as chi-squared analyses and t-tests wereconducted to compare each of the variable domains by socio-demographicvariables and other predisposing, enabling and/or restricting and treatment needfactors. Regression analyses were also performed to identify factors thatdifferentiated between race and gender for subjects who did not access services.Finally, a multiple correlation matrix was used to compare significant relationshipsamong the study variables. Following this regression analyses were conducted toidentify factors associated with significant predictors of access to treatment.3.4. PHASE 2: QUALITATIVE CASE STUDY3.4.1. Sample characteristicsFor this phase, data were collected from multiple informants and multiple sourcesto improve confidence in the reliability of findings (Babbie & Mouton, 2001). Asample frame was constructed from the contact list of the Western Cape DrugForum, a body that is comprised of community-based local drug actioncommittees, treatment service providers (TSPs), researchers and policy-makers.Local drug action committees (LDACs) are community-based bodies tasked withcoordinating all substance abuse prevention and treatment activities at a locallevel. LDACs consist of community representatives concerned with substanceabuse as well as substance abuse agencies operating in the community. Thedevelopment and initiation of LDACs is the responsibility of the ProvincialDepartment of Social Services and Poverty Alleviation, which has electedsubstance abuse coordinators (SACs) in each of the six social service districtoffices to fulfill this mandate. As LDACs, their SACs, and non-profit treatmentcentres focus on coordinating and providing substance abuse treatment servicesfor HDCs, the researcher thought that these would be the best sources of35

information on the accessibility of treatment services and the functioning of thetreatment system in these communities.As data collection only continued until saturation of new themes and informationoccurred, the final sample consisted of 20 key informants. Some of the keyinformants playing multiple roles: 7 were TSPs, 4 were involved in LDACs, 5worked in the substance abuse policy arena, and 5 were SACs in district socialservice offices located in the recruitment areas.3.4.2. ProceduresIn this phase, the researcher contacted the identified key informants, informedthem about the study, and obtained their written informed consent to participate insemi-structured in-depth interviews. The interview was conducted in private bythe principal investigator and a research assistant. As all the key informants spokeEnglish fluently, interviews were conducted in this language. The interviews tookapproximately 90 minutes to complete. Each interview was audio-taped andtranscribed verbatim using professional transcription services.3.4.3. The Access to Treatment Interview ScheduleThe interviews covered broad themes that include perceptions of access totreatment and contextual influences on access in HDCs. More specifically, theinterview explored (i) the structure and functioning of the substance abusetreatment system in the Cape Town metropole, (ii) the process of accessingsubstance abuse treatment for persons from HDCs, and (iii) factors that enableand restrict access to services for persons from HDCS. Interviews were looselyguided by an interview schedule based on these themes.3.4.4. Data analysisQualitative data were analyzed using the Analysis Software for Word-BasedRecords programme, version 6.4 (AnSWR, Centre for Disease Control, 2004).More specifically, content and thematic analysis techniques were used to analyzethe textual data (Strauss & Corbin, 1990). Deductive category application (based36

on the broad themes of interest) was used to develop an initial coding scheme(Strauss & Corbin, 1990). An iterative process of coding and analysis was thenfollowed: as coding progressed and new dimensions of meaning emerged in theanalysis, new categories of codes were added to the coding scheme. Followingthe development of a coding scheme, axial coding was used to order and makelinkages between codes.3.5. ETHICSEthical approval for this study was granted by the Ethics Review Board of theFaculty of Humanities at the University of Cape Town.37

RESULTS: PHASE ONE4.1. VARIABLES ASSOCIATED WITH ACCESS TO SUBSTANCE ABUSETREATMENT: BIVARIATE ANALYSESIn order to identify predisposing, enabling and need for treatment variablessignificantly associated with access to substance abuse treatment, Chi-squaretests of association were conducted on all categorical variables and independentsample t tests were performed to compare differences between cases andcontrols on all continuous variables.4.1.1. Predisposing variables associated with access to treatmentLevel of education and place of residence were the only categorical predisposingvariables significantly associated with access to treatment (Table 2).Table 2. Chi-square analyses of predisposing variables by accessPredisposing variablesNo access Access P 2 df OR (95%CI)% (n) % (n)GenderFemale 49.7 (276) 45.6 (198) 1.65 1 1.18 (0.92-1.52)Male 50.3 (279) 54.4 (236)RaceBlack 50.3 (279) 50.9 (221) 0.04 1 0.97 (0.76-1.25)Coloured 49.7 (276) 49.1 (213)Level of education < Std 8 24.3 (135) 23.0 (100) 6.12* 2Std 8-9 46.3 (257) 40.3 (175)≥ Std 10 29.4 (163) 36.6 (159)HousingOwn home 16.0 (89) 5.3 (23) 34.80*** 4arrangements Family home 58.0 (322) 65.7(285)Someone else 105 (58) 16.1 (70)Outbuilding 132 (73) 10.4 (45)Other place 2.3 (13) 2.5 (11)Family: AOD abuse No 52.6 (292) 50.5 (219) 0.45 1 1.09 (0.85-1.40)Yes 47.4 (263) 49.5 (434)* " < .05; ** " < .01; *** " < .00138

For both of these variables, each response category was transformed into adummy variable and further Chi-square tests were conducted. Results show thathaving a high school diploma was significantly associated with access totreatment, with subjects who completed high school being 1.39 times more likelyto access services than those who had not completed high school (Table 3).However, this effect size is small (Rosenthal, 1994).Table 3. Chi-square analyses of education and housing by access totreatmentDummy variables No access % Access P 2 df OR (95%CI)(n)% (n)≥ Std 10No 70.6 (392) 63.4 (275) 5.86* 1 1.39 (1.06-1.82)Yes 29.4 (163) 36.6 (159)Live in own home No 84.0 (466) 94.7 (411) 27.96*** 1 0.29 (0.18-0.47)Yes 16.0 (89) 5.3 (23)Live in family’s No 42.0 (233) 34.3 (149) 6.01* 1 1.38 (1.07-1.80)home Yes 58.0 (322) 65.7 (285)Live in someone No 89.5 (497) 83.9 (364) 6.97** 1 1.65 (1.13-2.39)else’s home Yes 10.5 (58) 16.1 (70)* " < .05; ** " < .01; *** " < .001For housing arrangements, the variables “living in own home”, “living in family’shome” and “living in somebody else’s home” were significantly associated withaccess to treatment (Table 3). Although subjects who lived in their family’s homeor who lived in somebody else’s home were 1.38 and 1.65 times more likely toaccess treatment compared to subjects who lived elsewhere, these effect sizesare small (Rosenthal, 1994). In contrast, a moderately strong effect size wasobtained for “living in one’s own home”, with the inverted odds ratio indicating thatsubjects living in their own home were 3.4 times more likely to not accesstreatment compared to those living elsewhere.For continuous predisposing variables, significant differences were found betweencases and controls for “self-efficacy to stop using drugs for one month” and “self-39

efficacy to stop using drugs for more than one month” (Table 4), with casesreporting more self-efficacy for abstinence than controls. However, these findingsshould be interpreted with caution given the small effect sizes obtained. 3Table 4. Independent sample t tests for continuous predisposing variablesPredisposing variablesControls(N= 555)Cases(N = 434)t value df Effectsize (d)Mean (SD) Mean (SD)Beliefs about the treatment effectiveness 31.95 (6.83) 35.98 (8.29) -8.03*** 655 0.51Treatment concerns 26.43 (8.54) 29.70 (7.71) -6.23*** 987 0.40Community views about access to treatment 3.87 (0.33) 3.64 (0.57) 8.39*** 832 0.79Neighbourhood safety 1.71 (0.70) 2.13 (1.07) -7.10*** 708 0.48Neighbourhood crime 1.52 (0.64) 1.83 (0.91) -5.91*** 745 0.40Neighbourhood alcohol 1.41 (0.56) 1.75 (0.83) -7.44*** 723 0.49Neighbourhood drug 1.39 (0.57) 1.60 (0.84) -4.45*** 727 0.30Neighbourhood poverty 1.49 (0.59) 1.94 (0.98) -8.40*** 672 0.57Neighbourhood environment scale (NES) 42.36 (3.43) 41.42 (5.07) -7.93*** 658 0.22Self-efficacy to stop using for one month 2.19 (0.95) 2.42 (1.20) -3.26*** 807 0.22Self-efficacy to stop using > 1 month 2.02 (0.99) 2.34 (1.22) -4.37*** 828 0.29* " < .05; ** " < .01; *** " < .001Cases also had significantly higher scores on the “Beliefs about treatmenteffectiveness”, and “Treatment concerns” scales than controls. This suggests thatpeople who access treatment hold more negative beliefs and have more concernsabout treatment than people who do not access services. In contrast, controls hadsignificantly higher mean scores on the “Community Views about Access toTreatment” scale than cases; reflecting more negative perceptions about theavailability and accessibility of treatment. This finding may be particularlyimportant given its large effect size.Compared to cases, controls report significantly lower mean scores (indicatinggreater problems) on neighbourhood safety, crime, alcohol and drug use, andpoverty. These findings suggest that subjects who do not access treatment3 Cohen (1988) noted that effect sizes for d of .20 are small; .50 are medium, and .80 are large40

experience more neighbourhood-related problems than those who do accesstreatment. The finding that cases have significantly lower mean scores on theNES than controls (reflecting lower levels of neighbourhood disadvantage)provides further support for this claim. However, given the small to moderateeffect sizes, neighbourhood factors are probably only weakly associated withaccess to treatment.4.1.2. Need for treatment variables associated with access to treatmentResults from Chi-square analyses reflect significant associations between accessand perceived need for treatment, self-recognition of an alcohol or drug (AOD)problem, and others suggesting the need for AOD-related help (Table 5). Subjectswho thought they had an AOD problem were 2.8 times more likely to accesstreatment than those who thought they did not have a problem. Similarly, theodds of accessing treatment were 2.8 times greater for subjects who reported aneed for treatment compared to subjects who reported no need for treatment.These are moderate to strong effects (Rosenthal, 1994). Finally, the odds ofaccessing treatment were almost 4 times greater for subjects where others hadsuggested they need AOD-related help compared to subjects where others hadnot suggested they need help. This is a strong effect (Rosenthal, 1994).Table 5. Chi-square analyses of need for treatment variables by accessNeed variables No access Access P 2 df OR (95%CI)% (n) % (n)Think have No 34.8 (193) 15.9 (69) 44.56*** 1 2.82 (2.07-3.85)AOD problem Yes 65.2 (362) 84.1 (365)Others suggest No 29.0 (161) 9.7 (42) 55.80*** 1 3.81 (2.64-5.51)you need help Yes 71.0 (394) 90.3 (392)Need AOD No 42.3 (235) 21.0 (91) 50.36*** 1 2.77 (2.08-3.68)treatment Yes 57.7 (320) 79.0 (343)*** " < .001Cases also had significantly higher mean scores on the drug dependence severityscale and on the perceived drug problem severity scale, compared to controls41

(Table 6). Effect sizes were large for these scales. This suggests that individualswho access treatment have more severe drug problems than those who do notaccess services.Table 6. T tests for continuous need for treatment variablesNeed for treatment variables Controls(N= 555)Cases(N = 434)t value df Effectsize (d)Mean (SD) Mean (SD)SCID drug dependence severity 10.09 (1.47) 11.51 (1.49) -14.82*** 895 0.96Perceived AOD problem severity 2.79 (1.38) 3.93 (1.36) -13.09*** 987 0.83Socrates-composite 52.99 (13.80) 67.76 (13.92) -16.63*** 987 1.07TCU PR 29.97 (8.21) 36.88 (6.24) -15.04*** 986 0.93TCU DH 32.15 (8.76) 37.71 (7.66) -10.62*** 975 0.67TCU TR 33.19 (5.65) 32.52 (5.89) 1.817 987 0.12* " < .05; ** " < .01; *** " < .001Cases also had significantly higher mean scores on the SOCRATES scale(indicating greater motivation and readiness to change) than controls. A verylarge effect size was obtained for this scale (Cohen, 1988). Compared to controls,cases also obtained higher mean scores for two of treatment motivation scales:problem recognition (PR) and desire for help (DH). Effect sizes for these scaleswere strong and moderate, respectively (Cohen, 1988). This suggests that peoplewho access treatment have greater AOD problem recognition and greater desirefor AOD-related help than people who do not access treatment.4.1.3. Enabling and restricting variables associated with accessAlmost all cases and controls reported limited availability of both alcohol and drugrelatedtreatment services in their communities. Availability was thus notsignificantly associated with access. A very large effect was found for awarenessof where to go for AOD-related help, with the odds of accessing treatment beingmore than 15 times greater for subjects who were aware of where to go for helpcompared to those who were unaware (Table 7). Competing monetary needs andthe need to take care of others were also strongly associated with access. Strong42

associations were also found between access to treatment and access to medicalinsurance, with the odds of accessing treatment being more than 4 times greaterfor those with medical insurance.Table 6. Chi-square analyses of enabling and restricting variables by accessEnabling/restrictingNo access Access P 2 df OR (95%CI)variables% (n) % (n)Medical No 97.8 (543) 91.5 (397) 20.94*** 1 4.22insurance Yes 2.2 (12) 8.5 (37)(2.17-8.19)Legal income < 500 43.4 (241) 49.8 (216) 41.70*** 3(Rands) 501-1000 36.8 (204) 19.6 (85)1001-2500 19.8 (110) 30.6 (133)Awareness of No 37.5 (208) 3.7 (16) 158.73*** 1 15.66where to go Yes 62.5 (347) 96.3 (418)(9.24-26.55)Enough No 99.8 (554) 98.6 (428) 5.01* 1 7.77alcohol tx Yes 0.2 (1) 1.4 (6)(0.93-64.75)Enough drug No 99.8 (554) 98.6 (428) 5.01* 1 7.77treatment Yes 0.2 (1) 1.4 (6)(0.93- 64.75)Competing No 26.5 (147) 59.9 (260) 112.33*** 1 0.24needs: money Yes 73.5 (408) 40.1 (174)(0.18-0.31)Competing No 48.5 (269) 68.9 (299) 41.56*** 1 0.43needs- care Yes 51.5 (286) 31.1 (135)(0.33-0.55)* " < .05; *** " < .001In addition, access to treatment was significantly associated with legal income(Table 7). For this variable, each response category was transformed into adummy variable and further Chi-square tests were conducted. A weak tomoderate effect was found for monthly income greater than R1000, with subjectswho earned more than R1000 per month being 1.8 times more likely to accesstreatment than subjects who did not earn this amount (Table 8). The effect size foraccessing treatment when earning between R500 and R1000 per month wasmoderate, with the inverted odds ratio indicating that subjects earning this amount43

were 2.4 times more likely to not access treatment than those who did not earnwithin in this range.Table 8. Chi-square analyses of dummy enabling variables by accessVariablesNo access% (n)Access% (n)Income

Table 9. T tests for continuous enabling variables by access to treatmentEnabling variablesControls(N= 555)Cases(N = 434)t value df Effectsize (d)Mean (SD) Mean (SD)Affordability barriers 38.76 (6.23) 27.91 (9.46) 20.66*** 854 1.39Number of treatment centres aware of 1.06 (0.97) 4.00 (1.84) -30.27*** 619 2.07Delays in treatment 37.63 (5.80) 31.90 (9.76) 10.83*** 664 0.73Distance to treatment (km) 3.66 (0.55) 2.72 (0.75) 17.36*** 766 1.15Time to treatment (min) 3.63 (0.58) 2.84 (0.80) 21.95*** 769 1.46Culture/gender barriers 22.63 (7.83) 21.93 (7.48) 1.45 949 0.09Perceived utility scale 24.73 (9.56) 28.80 (11.13) -6.07*** 854 0.40Social trust 46.74 (8.94) 44.28 (12.34) 3.49*** 761 0.23Social cohesion 2.71 (0.62) 2.75 (0.74) -1.10*** 842 0.06Community stigma 55.30 (7.56) 62.33 (8.89) -13.17*** 849 0.86Stigma consciousness 7.63 (1.53) 8.59 (1.64) -9.44*** 898 0.61TCU Abstinence support 35.28 (5.56) 37.43 (4.66) -6.62*** 982 0.41Tangible support 3.38 (0.87) 3.58 (0.82) -3.65*** 987 0.24Affectionate support 3.29 (0.92) 3.53 (0.89) -4.15*** 987 0.26Positive social interaction 3.43 (0.86) 3.64 (0.83) -3.96*** 987 0.25RAND social support 3.34 (0.72) 3.47 (0.74) -2.80** 987 0.18TCU Self esteem 31.69 (9.39) 37.47 (9.29) -9.66*** 935 0.62TCU Depression 32.51 (7.35) 38.31 (7.85) -11.94*** 987 0.77TCU Anxiety 34.12 (8.66) 39.19 (7.90) -9.61*** 964 0.61* " < .05; ** " < .01; *** " < .001While significant differences were found between cases and controls for indicatorsof social capital and generic social support, the effect sizes were too small to drawmeaningful conclusions. Cases also differed significantly from controls onmeasures of abstinence support, suggesting that subjects who accessedtreatment had higher levels of abstinence support than those who did not accessservices.Cases also differed from controls on measures of psychological functioning; withcases obtaining significantly higher mean scores on depression, anxiety and self-45

esteem scales (Table 9). Stigma also differentiated cases and controls, withcases reporting significantly higher mean scores on the “Stigma towardsSubstance Abusers” scale and on the “Stigma Consciousness” scale thancontrols. Contrary to expectations, greater stigma may be associated withaccess to treatment, especially given the strong effects obtained for these scales.4.2. PREDICTORS OF ACCESS TO SUBSTANCE ABUSE TREATMENTA stepwise multiple logistic regression procedure was performed with access totreatment as the dependent variable and significant need for treatment,predisposing, and enabling/restricting variables (see Tables 2-9) hierarchicallyentered as block variables. This allowed the extent to which each variable domaincontributed to predicting access to be examined, while controlling for the influenceof other variable domains.Gender and race were entered as covariates in Block 1 to control for theirinfluence on access to treatment. Following this, three logistic regression modelswere evaluated in hierarchical fashion, beginning only with the need for treatmentvariables as predictors (Model 1) and culminating in a multifactorial model thatincluded need for treatment, predisposing and enabling variable domains (seeTable 9 for test statistics, p-values, and odds ratios). More specifically, need fortreatment variables were entered in Block 2. These were entered as the first blockof predictor variables as the BHSU model (Andersen, 1995) suggests that thesevariables are more strongly associated with access than predisposing andenabling variables. In Block 3, a predisposing variable block was addedhierarchically and sequentially to the need for treatment block (Model 2). Finally, afourth block of enabling/restricting variables was added hierarchically andsequentially to the first three blocks (Model 3).4.2.1. Model 1: Need for treatment variablesFor model 1, the addition of the block of need for treatment variables substantiallyimproved the predictive utility of the model (Δχ 2 (7; N = 989) = 450.49, p < .001)compared to the intercept-only model. However, this model did not demonstrate46

adequate fit to the data (Hosmer-Lemeshow χ 2 (8; N= 989) = 64.46, D < .001),even though this model predicted approximately 49% of the variation in access totreatment (Nagelkerke R 2 = .490).For this model, results show that the drug dependence severity scale,SOCRATES scale, TCU PR scale, TCU DH scale, others suggesting the need fortreatment, self-perceived AOD problem recognition, and the age at which drugswere first used all had significant partial effects. A one-unit increase in the drugdependence severity scale resulted in a 2.2 increase in the odds of accessingtreatment. This shows that as drug problem severity increases, the chances ofindividuals accessing treatment increases significantly. Although significant, theeffects of the SOCRATES scale and the TCU problem recognition scale weremuch smaller, with a one-point increase in these scales being associated with theodds of accessing treatment increasing by a multiplicative factor of 1.1. A smalleffect was found for the TCU desire for help scale and the age at which drugswere first used, with a one-unit increase in these variables resulting in the odds ofaccessing treatment decreasing by a multiplicative factor of 0.9. The only otherneed for treatment variables that moderately predicted access to treatment whenthe influence of other variables was controlled for, were “self-perceived AODproblem” and “others suggesting the need for help”, which were both associatedwith almost a tripling of the odds of accessing treatment. These findings suggestthat having a self-perceived AOD problem and have others suggest the need forhelp are stronger predictors of treatment use than readiness to change, treatmentmotivation, and drug dependence severity (Table 10).47

Table 10.Logistic regression coefficients with need for treatment, predisposing and enabling/restricting variables aspredictors and access as the dependent variablePredictor variablesModel 1 Model 2 Model 3WaldOR (95% CI)WaldOR (95% CI)WaldOR (95% CI)(df=1)(df=1)(df=1)Need for treatment variablesDrug dependence severity 93.00*** 2.23(1.89-2.62) 86.28*** 2.46 (2.04-2.98) 13.36*** 1.79 (1.31-2.45)SOCRATES composite 62.94*** 1.09 (1.07-1.11) 25.93*** 1.06 (1.04-1.09) 1.92 1.03 (0.99-1.08)TCU problem recognition 9.74** 1.06(1.02-1.10) 5.91* 1.06 (1.01-1.11) 2.63 1.10 (0.98-1.26)TCU desire for help 20.17*** 0.92 (0.89-0.96) 4.27* 0.96 (0.92-0.99) 0.13 0.98 (0.88-1.09)Others suggest help (Yes) 19.93*** 2.89(1.81-4.60) 15.94*** 3.00 (1.75-5.15) 1.24 2.07 (0.58-7.40)Perceived AOD problem (Yes) 17.56*** 3.12(1.83-5.32) 10.14** 2.71 (1.47-5.01) 0.00 0.96 (0.21-4.37)Age first used drugs 7.31** 0.94(0.89-0.98) 4.33* 0.95 (0.90-0.99) 6.31* 0.85 (0.74-0.96)Predisposing variablesLiving in own home (Yes) - - 12.26*** 0.30 (0.15-0.59) 3.54 0.18 (0.03-1.07)Community views - - 53.89*** 0.16 (0.10-0.26) 8.57*** 0.17 (0.05-0.55)Beliefs: treatment efficacy - - 34.17*** 1.09 (1.06-1.12) 0.43 1.02 (0.96-1.09)48

Treatment concerns - - 29.84*** 1.07 (1.05-1.10) 16.69*** 1.15 (1.08-1.24)Neighbourhood poverty - - 45.16*** 2.68 (2.01-3.57) 2.62 1.88 (0.88-4.02)Enabling/restricting variablesAware of treatment (Yes) - - - - 10.28*** 10.46 (2.49-43.92)Number of known tx centres - - - - 47.95*** 5.39 (3.33-8.68)Affordability barriers - - - - 14.35*** 0.88 (0.83-0.94)Delays to treatment - - - - 8.61** 0.91 (0.85-0.97)Income =R500-R1000 (Yes) - - - - 7.70** 0.28 (0.16-0.69)Time to treatment - - - - 37.65*** 0.09 (0.04-0.20)Social trust composite - - - - 5.72* 0.95 (0.92-0.99)Competing needs- money (Y) - - - - 9.88** 0.24 (0.10-0.59)Perceived utility scale - - - - 7.76** 1.07 (1.02-1.13)Community stigma - - - - 20.66*** 1.16 (1.09-1.23)* " < .05; ** " < .01 ***; " < .00149

4.2.2. Model 2: Predisposing variables and need variablesThe addition of a block of predisposing variables in Model 2, while controlling forthe effects of need for treatment variables, significantly increased the predictivevalue of the model; P 2 (5; N = 989) = 196.16, D < .001. When compared to theintercept-only model, Model 2 was better able to predict access to treatment (ΔP 2(12; N = 989) = 646.65, D < .001). Although Model 2 predicted a greaterproportion of the estimated variance (64%) in access to treatment than Model 1(Nagelkerke R 2 = .643), the general fit of the model to the data remained poor(Hosmer–Lemeshow χ 2 (8; N= 989) = 60.57, p < .001).For this model, findings from the hierarchical logistic regression show that “selfperceivedproblem recognition” and “others suggesting the need for help”continue to be associated with almost a tripling of the odds of accessingtreatment (Table 10). Similarly, increases in readiness to change drug use, druguse severity, age at which first used drugs, problem recognition and desire forhelp remained associated with an increased likelihood of accessing treatment,although these associations are weak.For predisposing variables, living in own home, community views about accessto treatment, beliefs about treatment effectiveness, treatment concerns, andneighbourhood poverty all had significant partial effects on access to treatment.“Living in one’s own home” strongly predicted access to treatment when theinfluence of other predisposing and need variables were controlled for, with theinverted odds ratio indicating that subjects living in their own home were 3.3times more likely to not access treatment compared to subjects living elsewhere.Inverting the odds ratio for community views about access to treatment revealsthat a one-unit increase in the 5-point scale resulted in a 6.3 times increase in theodds of not accessing treatment. This shows that as community perceptionsabout the inaccessibility of treatment increase, the chances of individualsaccessing treatment decrease. In contrast, although significant, the effects oftreatment effectiveness beliefs and treatment concerns were much smaller, with50

a one-point increase in these scales associated with the odds of accessingtreatment increasing by a multiplicative factor of 1.1. For neighbourhood poverty,a one-unit increase in this scale (indicating less poverty) more than doubled theodds of accessing treatment.4.2.3. Model 3: Need for treatment, predisposing, and enabling variablesModel 3 involved the addition of a block of enabling/restricting variables whilecontrolling for the effects of need for treatment and predisposing variables. Theaddition of these enabling variables significantly increased the predictive value ofthe model; P 2 (10; N = 989) = 521.92, D < .001. When compared to the interceptonlymodel, Model 3 was better able to predict access to treatment (ΔP 2 (22; N =989) = 1168.57, D < .001). In addition, Model 3 predicted a greater proportion ofthe estimated variance in access to treatment than Model 2 and Model 1(Nagelkerke R 2 = .929). The Hosmer and Lemeshow goodness-of-fit test alsodemonstrated that the addition of enabling/restricting predictor variables resultedin the model becoming an adequate fit for the data for the first time (χ 2 (8; N=989) = 1.07, p = 0.99). The full model had a sensitivity of 94.5%, a specificity of95.9% and overall classified 95.2% of the cases correctly. Thus this model issufficiently accurate to be considered a useful model.For this model, the only need for treatment variables that significantly predictedaccess to treatment were age at which drugs were first used (which re-enteredthe model) and drug use severity - both of which had relatively weak effects onaccess. For predisposing variables, only community views about accessibilityand treatment concerns remained significantly associated with access totreatment. The inverted odds ratio for negative community perceptions aboutaccess to treatment indicates that a one-unit increase in this scale wasassociated with more than a six-fold increase in the odds of not accessingtreatment. Although an increase in treatment concerns was still associated withan increased likelihood of accessing treatment, this association was very weak.In contrast, the “beliefs about treatment effectiveness” scale, neighbourhood51

poverty scale, and the variable “living in own home” were no longer significantpredictors of access to treatment in this equation.Ten enabling variables had significant partial effects on access to treatment inmodel 3 (Table 10): social trust, community stigma, awareness of where to go forAOD help, number of known treatment centres, competing needs for money,affordability barriers, delays in seeking treatment, perceived utility of treatment,income between R500 and R1000, and travelling time to nearest treatmentcentre. More specifically, for the number of known treatment centres, a one-unitincrease in the 8-point scale increased the odds of accessing treatment morethan five-fold, when the influence of other variables was controlled for. Similarly,when holding other variables constant, the odds of accessing treatment weremore than ten times greater for subjects who knew where to go for AOD helpthan for subjects who were unaware of where to seek help. These findings pointtowards a strong effect of awareness factors on access to treatmentThe effect of affordability barriers on access was much smaller, with a one-pointincrease in this scale resulting in the odds of not accessing treatment increasingby a multiplicative factor of 1.1. When holding all other variables constant, theodds of accessing treatment for those without competing monetary needs ismore than 4 times greater than for subjects with competing monetary needs.The inverted odds ratio for subjects earning between R500 and R1000 per monthin legal income indicates that the odds of not accessing treatment for subjects inthis income bracket is 3.6 times greater than for subjects in other incomebrackets. These findings suggest that affordability barriers and financialconcerns do impact on access to treatment.Travelling time to treatment also impacts on access, with the inverted odds ratiofor this variable indicating that every one-unit increase in this scale is associatedwith the odds of not accessing treatment increasing with a multiplicative factor of11.1. This finding points to the importance of geographical accessibility issues.Although significant, the effects found for social trust, community stigma, delays52

in accessing treatment, and perceived utility of treatment on the odds ofaccessing treatment were much weaker. Although social support factors wereassociated with treatment access in bivariate analyses, they were no longerassociated with access when controlling for the influence of other variables. Thischallenges the study hypothesis that social support is positively associated withtreatment utilization.In summary, this final model suggests that when controlling for gender and race,enabling variables (particularly the five variables: travelling time to treatment,awareness of AOD help, number of known treatment centres, competingmonetary needs, and income) are stronger predictors of access to treatment thanneed or predisposing variables. Only one predisposing variable remainedstrongly associated with access to treatment: community views about access.Despite a few need for treatment variables being significant predictors of access;contrary to previous research findings, none of these need for treatmentvariables had strong effects on access when considered together with othervariable domains.4.2.4. A more parsimonious model of access to treatment: Model 4Although Model 3 accounted for a very large proportion of the variance, itincluded many variables, several of which were weak predictors of access. Inorder to create a more parsimonious model that could predict whether individualswould access services or not, only those predictors in Model 3 with strong effectson access were entered into the logistic regression equation. More specifically,gender and race were controlled for by entering these variables as covariates inBlock 1. In Block 2, the following variables were entered: community views aboutaccess, awareness of treatment centres, number of known treatment centres,competing monetary needs, income (R500-R1000), and travelling time totreatment.A test of the full model versus the model with the intercept only was statisticallysignificant P 2 (6; N = 989) = 890.89, D < .001; indicating that the predictive value53

of the model increased significantly when these variables were added. The fullmodel accounted for approximately 80% of the variance in access to treatment(Nagelkerke R 2 = .796). In addition, the Hosmer and Lemeshow test revealedthat the data were a good fit for the model; P 2 (8; N = 989) = 4.85, D = .774. Thefull model was able to correctly classify 85.5% of those who accessed treatmentand 92.3% of those who did not access treatment, with an overall success rate of89.3% (Table 11).Table 11. Logistic regression coefficients for Model 4, with access as thedependent variablePredictor variables # Wald OR (95% CI)(df =1)Awareness of AOD treatment centres (Yes) 1.65 14.29*** 5.21 (2.21-12.27)Number of known treatment centres 1.41 143.15*** 4.08 (3.24-5.14)Competing needs: money (Yes) -1.73 83.14*** 0.18 (0.12-0.26)Income =R500-R1000 (Yes) -1.42 32.82*** 0.24 (0.15-0.39)Time to treatment -0.84 10.19** 0.43 (0.26-0.73)Community views about access -0.64 4.98* 0.53 (0.30-0.93)* " < .05; ** " < .01 ***; " < .001To test the utility of the more parsimonious Model 4 with that of the morecomprehensive Model 3 (as well as Models 1-2), we used a Receiver–OperatorCharacteristic (ROC) curve to examine the extent to which these modelscorrectly classified subjects as having accessed treatment (see figure 1). All themodels had better than chance diagnostic performance, with area under thecurve (AUC) quantities for Models 1 (AUC = .86; CI = .83-.88), and 2 (AUC = .91;CI= .89-.93) being “moderate to high” and for Model 3 and 4 being “very high”(AUC = .99; CI =.98-.99 and AUC = .96; CI =.95-.97, respectively) (Swets, 1988).Findings suggest that Model 1 and 2 are not as good as Model 3 and 4 inpredicting access to treatment, especially as the AUC confidence intervals forModels 3 and 4 lie above the other models. Compared to Model 4, Model 3 isstill better at classifying subject correctly. However, as the difference betweenthese models is not large and because Model 4 is not only more parsimonious54

ut also predicts a large percentage of cases correctly, a strong argument can bemade for using this model rather than that of Model 3.Figure 2. ROC curves for Regression Models 1-4.1.0Sensitivity 0.8Source of the CurveModel 1Model 2Model 3Model 4Reference Line0. - Specificity4.3. SOCIODEMOGRAPHIC DIFFERENCES ON PREDISPOSING, NEEDFOR TREATMENT AND ENABLING VARIABLE DOMAINSTo refine possible interventions, we explored potential gender and racedifferences on predictors of access to treatment among control subjects (N =555). Chi-square tests of association or independent sample t tests wereconducted on all variables that were significantly associated with access in initialbivariate analyses by gender and race.4.3.1. Gender differences on predictors of access among individuals whodid not access treatment4.3.1.1. Predisposing factorsFor control subjects, the only gender differences found among predisposingpredictors of access to treatment, was on “housing arrangements”, particularly“living in own home” (see Table 11) and self-efficacy (Table 12), where male55

controls had greater self-efficacy to remain abstinent in risky situations for onemonth and for more than 1 month compared to their female counterparts. Theeffect sizes for these variables were, however weak. Need for treatment factorsAmongst the categorical need for treatment variables, significant associationswere found only between gender and “perceived AOD problem” and “perceivedneed for treatment”. For the former, the inverted odds ratio revealed that malecontrols had double the odds of perceiving an AOD problem compared to theirfemale counterparts. For the latter, the inverted odds ratio revealed that malecontrols had 1.7 times the odds of perceiving a need for treatment compared totheir female counterparts (Table 12). In contrast, gender differences were foundon all of the continuous need for treatment variables associated with access, withmale controls again showing greater need for treatment than their femalecounterparts (Table 13). Male respondents who did not access treatment hadsignificantly higher levels of drug severity (both perceived and evaluated),readiness and motivation to change drug use, problem recognition and desire forhelp, and had started using drugs at an earlier age than their female counterparts(Table 13). Apart from readiness and motivation to change, effect sizes for theother need variables were small, indicating weak associations with gender. Enabling/restricting factorsThe only categorical enabling variables significantly associated with gender werelegal income, competing needs for money, and competing needs to care forothers (Table 11). For legal income, each response category was transformedinto a dummy variable and more Chi-square tests conducted.56

Table 12. Chi-square analyses of categorical predictor variables by genderVariablesMale Female P 2 df OR (95%CI)% (n) % (n)Predisposing variablesHousingown home 21.1 (59) 10.9 (30) 25.31*** 4 -family’s home 58.4 (163) 57.6 (159)someone else 8.2 (23) 12.7 (35)outbuilding 12.2 (34) 14.1 (39)Other place 0.0 (0) 4.7 (13)Live own home No 78.9 (220) 89.1 (246) 10.88** 1 0.46 (0.28-0.73)Yes 21.1 (59) 10.9 (30)Need for treatment variablesThink you need No 36.2 (101) 48.6 (134) 8.67** 1 0.60 (0.43-0.84)treatment Yes 63.8 (178) 51.4 (142)Think have AOD No 27.2 (76) 42.4 (117) 14.04*** 1 0.50 (0.36-0.73)problem Yes 72.8 (203) 57.6 (159)Enabling variablesLegal income < 500 37.3 (104) 49.6 (137) 9.67** 2 -(Rands)501-1000 42.3 (118) 31.2 (86)1001-2500 20.4 (57) 19.2 (53)Income

and R1000 per month than their female counterparts. For competing needs,female control subjects had more than double the odds of reporting additionalfinancial demands (that took priority over the need for treatment) than their malecounterparts. Similarly, females who did not access treatment had 1.6 times theodds of reporting demands to care for others (that took priority over theirtreatment entry) than their male counterparts (Table 12).Similarly, only a few gender differences were found on continuousenabling/restricting variables significantly associated with access (Table 13).Compared to male controls, women reported significantly higher levels of barriersrelated to perceived utility and appropriateness of treatment services (includingcultural and gender appropriateness of services). Women also reported moregeographic accessibility barriers (including longer travelling times and distancesto treatment) than men. In contrast, male subjects who had not accessedtreatment reported lower levels of social trust and social cohesion (indicators ofsocial capital) than their female counterparts. However, these variables areprobably only weakly associated with gender, given the small effects obtained.4.3.2. Factors that differentiate between male and female subjects that didnot access treatmentTo identify factors associated with access that differentiate between male andfemale substance abusers who do not access treatment, a multivariate logisticregression analyses were performed with gender as the dependent variable.This allowed us to evaluate the independent contribution of variables associatedwith being a female substance abuser and not accessing treatment compared tobeing a male, while controlling for the influence of all other variables (Table 14).58

Table 13. Independent sample t tests for continuous variables by genderVariablesMale(N = 279)Female(N = 276)t value df Effectsize (d)Mean (SD) Mean (SD)Predisposing variablesNeighbourhood poverty 1.42 (0.58) 1.57 (0.60) -2.99** 551 0.25Self-efficacy- 1 month 2.30 (0.95) 2.08 (0.94) 2.77** 553 0.25Self-efficacy > 1 month 2.11 (1.00) 1.94 (0.98) 2.00* 553 0.17ADUSE-C 2.66 (0.70) 2.49 (0.76) 2.83** 553 0.25Need for treatment variablesDrug dependence severity 10.25 (1.32) 9.97 (1.52) 2.35** 541 0.20Perceived AOD severity 3.01 (1.25) 2.54 (1.46) 4.06*** 553 0.35Socrates-composite 55.93 (12.65) 50.00 (14.30) 5.15*** 543 0.44TCU- PR 30.94 (8.22) 29.00 (8.10) 2.79** 553 0.24TCU-DH 33.37 (7.93) 30.92 (9.38) 3.33** 553 0.28Age first used drugs 18.57 (3.06) 19.92 (4.31) -4.25*** 496 0.36Enabling/restricting variablesDistance to rehab 3.54 (0.65) 3.72 (0.49) -3.61*** 517 0.31Time to treatment 3.57 (0.61) 3.76 (0.46) -4.23*** 516 0.35Perceived utility barriers 23.53 (9.20) 25.94 (9.77) -2.99** 550 0.25Social trust 45.28 (8.72) 48.21 (8.92) -3.91*** 553 0.33Social cohesion 2.65 (0.51) 2.76 (0.71) -2.21* 498 0.18Culture/gender barriers 21.69 (7.20) 23.59 (8.32) -2.87** 540 0.24* " < .05; ** " < .01; *** " < .001Social trust, travelling time to treatment, competing financial needs, age at whichfirst used drugs, motivation to change (SOCRATES), desire for help,culture/gender barriers, income (less than R500),and neighbourhood poverty allhad significant partial effects on gender group membership. The factors that moststrong differentiated between female and male controls were the enablingvariables of competing needs (monetary), income less than R500 per month, andtravelling time to treatment. The inverted odds ratio shows that subjects who hadcompeting monetary needs had almost triple the odds of being female. Similarly,the odds of controls being female increased by a multiplicative factor of 2.2 for59

subjects earning less than R500 per month. For travelling time to treatment, aone-unit increase in the scale was associated with almost a doubling of the oddsof being female and not accessing treatment (Table 14).Table 14. Logistic regression with significant variables as predictors andgender as the dependent variablePredictor variables # Wald (df)) OR (95% CI)Neighbourhood poverty 0.54 8.90 (1)** 1.71 (1.20-2.44)Age at which first used drugs 0.12 17.00 (1)*** 1.13 (1.07-1.20)SOCRATES -0.05 15.52 (1)*** 0.95 (0.93-0.98)AOD problem recognition (No) 0.05 6.23 (1)* 1.05 (1.01-1.10)Income (reference >R1000) 17.54(2)***Income

the continuous need-for-treatment variables, the effect sizes for all theseassociations were small and the differences between the race groups on thesevariables are probably weak and not clinically meaningful (Table 16).Nonetheless, Black/African respondents who did not access treatment hadsignificantly higher levels of drug severity (both perceived and evaluated),readiness and motivation to change drug use, and desire for help, and hadstarted using drugs at an earlier age than their Coloured counterparts. Predisposing factorsFor predisposing variables associated with access to treatment, a significantrelationship was found between race and “housing arrangements”. For thisvariable, each response category was transformed into a dummy variable andfurther Chi-square tests were conducted. Only one of these dummy variableswas significantly associated with race among controls: Coloured controls hadalmost 3 times greater odds of living in someone else’s home compared to theirBlack counterparts (Table 15).In addition, compared to their Black/African counterparts, Coloured controls hadsignificantly higher mean scores on the “Community views about access totreatment”, “treatment concerns” and the “Beliefs about treatment effectiveness”scales (Table 16). These findings suggest that Coloured controls have morenegative perceptions about the availability and accessibility of treatment, havemore negative beliefs about treatment effectiveness, and more concerns aboutthe process of treatment than their Black/African counterparts. Effect sizes forthese variables were moderate.Finally, race differences were also found on neighbourhood factors, withColoured controls reporting significantly higher mean scores on the NES(indicating higher levels of neighbourhood disadvantage) and significantly lowermean scores (indicating more problems) for neighbourhood drug use than theirBlack/African counterparts. Large effect sizes were obtained for theseassociations between neighbourhood disadvantage, neighbourhood drug use,61

and race (Table 16). This indicates that Coloured individuals who do not accesstreatment experience higher levels of neighbourhood dysfunction thanBlack/Africans who do not access treatment.Table 15. Chi-square analyses of categorical variables by raceVariablesBlack Coloured P 2 df OR (95%CI)% (n) % (n)Predisposing variablesHousingown home 15.1 (42) 17.0 (47) 38.72*** 4 -arrangements family’s home 55.2 (154) 60.9 (168)someone else 6.1 (17) 14.9 (41)outbuilding 19.0 (53) 7.2 (20)other place 4.7 (13) 0.0 (0)Live- someone else No 93.9 (262) 85.1 (235) 11.38** 1 2.69Yes 6.1 (17) 14.9 (41)(1.49-4.86)Need for treatment variablesThink you needNo 31.2 (87) 53.6 (148) 28.62*** 1 0.39 (0.28-treatment Yes 15.7 (192) 26.7 (128)0.55)Enabling variablesLegal income

Table 16. Independent sample t tests for continuous variables by raceVariablesBlack/African(N = 279)Coloured(N = 276)t value df Effectsize (d)Mean (SD) Mean (SD)Predisposing variablesNeighbourhood drug abuse 1.54 (0.62) 1.24 (0.46) 6.68*** 511 0.55NES 40.96 (2.72) 43.78 (3.49) -10.59*** 519 0.90Treatment concerns 27.86 (8.65) 31.61 (6.05) -5.41*** 522 0.50Community views: access to tx 3.55 (0.59) 3.73 (0.53) -9.36*** 483 0.32Treatment effectiveness beliefs 34.02 (8.87) 38.02 (7.10) -3.83*** 547 0.50Need for treatment variablesDrug dependence severity 10.26 (1.19) 9.97 (1.63) 2.40* 503 0.20Perceived AOD severity 2.96 (1.39) 2.60 (1.34) 3.10** 553 0.26Socrates-composite 54.14 (10.56) 51.84 (16.38) 1.97* 469 0.17TCU DH 33.53 (6.79) 30.76 (10.20) 3.77*** 478 0.32Age first used drugs 18.59 (3.81) 19.91 (3.67) -4.14*** 553 0.35Enabling/restricting variablesSocial trust 47.91 (8.750 45.55 (8.98) 3.13** 553 0.27Number of tx centres aware of 0.65 (0.68) 1.47 (1.05) -10.86*** 469 0.93Affordability barriers 39.81 (5.81) 37.70 (6.48) 4.03*** 553 0.34Distance to treatment 3.74 (0.49) 3.99 (0.36) 4.54*** 511 0.58Delays in treatment 35.32 (4.77) 39.96 (5.79) -10.32*** 553 0.87Perceived utility 23.69 (9.12) 25.78 (9.89) -2.58** 548 0.22Community stigma 53.23 (6.55) 57.38(7.94) -6.72*** 531 0.61Stigma consciousness 7.31 (1.48) 7.95 (1.51) -5.07*** 552 0.43Depression 30.38 (6.45) 34.67 (7.57) -7.20*** 553 0.57Anxiety 30.25 (8.12) 38.02 (7.33) -11.84*** 548 1.00* " < .05; ** " < .01; *** " < .0014.3.3.3. Enabling/restricting factorsLegal income was the only categorical enabling variable significantly associatedwith race (Table 15). For this variable, each response category was transformedinto a dummy variable and further Chi-square tests were conducted. Two ofthese variables were significantly associated with race: Black/African controls63

were 3 times more likely to earn less than R500 per month than Colouredcontrols. In contrast, Coloured controls had almost 3 times greater odds ofearning between R501 and R1000 per month than Black/African controls.For continuous enabling variables that predicted access to treatment,Black/African controls reported significantly higher affordability and awarenessbarriers than their Coloured counterparts (Table 16). A very large effect wasfound for the association between race and number of known treatment centres,with Black/Africans knowing significantly fewer facilities than Coloured controls.In contrast, Coloured respondents who did not access services reportedsignificantly more barriers related to delays in accessing care (due togatekeepers and waiting times), barriers related to perceived utility andappropriateness of services, and higher levels of community (external) stigmatowards drug users and internalized stigma (stigma consciousness) than theirBlack/African counterparts. Coloured respondents who did not access servicesalso reported significantly higher levels of anxiety and depression than theirBlack/African counterparts. The effect sizes for these associations were strongand moderate, respectively. Coloured controls also reported significantly lowerlevels of social trust (an indicator of social capital) than their Colouredcounterparts (Table 16).Given that larger effect sizes were found on predisposing and enabling variablesthan need for treatment variables, it seems that greater differences between therace groups occur on predisposing and enabling variables compared to treatmentneed variables. This implies that interventions need to be targeted to specificcommunities.4.3.4. Factors that differentiate between Black/African and Colouredsubjects that did not access treatmentTo identify factors associated with access that differentiate betweenBlack/African and Coloured substance abusers who do not access treatment, a64

multivariate logistic regression analyses were performed with race as thedependent variable. This allowed us to evaluate the independent contribution ofvariables associated with being a Black/African substance abuser and notaccessing treatment compared to being Coloured, while controlling for theinfluence of all other variables.Factors which strongly distinguish between Black/African and Coloured controlsinclude “Community views about access to treatment” scale, “living in someoneelse’s home”, “income less than R500 per month”, “number of known treatmentcentres”, and “distance to treatment” (Table 17). More specifically, an invertedodds ratio indicates that a one-unit increase on the “Community views aboutaccess to treatment” scale was associated with the odds of being Colouredincreasing by a multiplicative factor of 8.3. Compared to Black/Africancounterparts, Coloured controls thus seem to have more negative perceptionsabout access to treatment when other variables are controlled for. Similarly, aninverted odds ratio shows that controls living in someone else’s home were morethan 4 times more likely to be Coloured than those living elsewhere.In contrast, Black/African controls were more likely to have affordability,awareness, and geographical accessibility barriers than their Colouredcounterparts, when the influence of other variables was controlled for.Specifically, compared to controls earning more than R1000 per month, controlsearning less than R500 per month had five-fold greater odds of beingBlack/African. In addition, for number of known treatment centres, the invertedodds ratio shows that a one-unit increase in the scale was associated with theodds of being Black/African decreasing by a multiplicative factor of 3.4. Similarly,the odds of controls being Black/African increased by a multiplicative factor of 3.4with every one-unit increase in the “distance to rehab” scale (Table 17).The main factors that distinguish Black/African and Coloured controls thus seemto be awareness barriers, financial concerns, and geographical access barriers65

(which are higher for Black/Africans) as well as attitudes and beliefs aboutsubstance abuse treatment (which are more negative for Coloured controls).Table 17. Logistic regression with significant variables as predictors; and raceas the dependent variablePredictor variables # Wald (df) OR (95% CI)Income (Reference: R1000) 24.26 (2)***Income

4.4.1. Relationships between predisposing variables and predictors ofaccess to treatment among controlsThe variables “Awareness of where to go for AOD help” and “number of knowntreatment centres” were significantly positively correlated with self efficacy to stopAOD use for more than one month and negatively correlated with NES. It seemsthat subjects who have more self-efficacy to change their AOD use and lessneighbourhood disadvantage, are more aware of where to seek treatmentservices. “Number of treatment centres” was also positively correlated with therelative deprivation scale, with higher scores indicating less deprivation.Table 18. Predisposing variables significantly correlated with predictors ofaccess to substance abuse treatment among control subjectsPredictor Variables Variables correlated with predictorvariablesCorrelationCoefficientAwareness of AOD help Self efficacy >1 month .170***NES -.125***Number of known treatmentRelative deprivation .269***centresNES -.125***Legal employment .166***Treatment concerns .135***Self efficacy >1 month .172***Competing needs (money) Self efficacy >1 month -.180***Time to treatmentSelf efficacy >1 month -.196***ADUSE-C -.166***Community views aboutRelative deprivation .159***accessNES .394***Self efficacy >1 month -.209***ADUSE-C -.324**** " < .05; ** " < .01; *** " < .001In contrast, competing needs, time to treatment and community views aboutaccess were all negatively correlated with self-efficacy to change AOD useand/or abstinence self-efficacy. This suggests that as self-efficacy to change67

substance use or remain abstinent decreases; time to treatment increases,competing financial needs rise, and community views about access becomemore negative. Finally, the “Community views about access” scale waspositively correlated with NES, suggesting that neighbourhood advantageincreases, community perceptions about the availability and accessibility ofservices become more negative (Table 18).4.4.2. Relationships between need for treatment variables and predictors ofaccess among respondents who did not access treatmentThe predictor variable “Awareness of where to go for AOD help” was positivelycorrelated with “Others suggesting the need for AOD help.” This implies thatother individuals play a role in increasing awareness of where to seekassistance. Similarly, the predictor variable “Number of known treatmentcentres” was positively correlated with “AOD problem recognition” scalesuggesting that as problem recognition increases, subjects become aware ofmore facilities where they can receive substance abuse treatment. This predictorvariable is also positively correlated with age at which first used drugs, anindicator of drug use severity. This suggests that increases in drug use severityare associated with decreasing awareness of treatment facilities (Table 19).Table 19. Need for treatment variables significantly correlated with predictorsof access to substance abuse treatment among control subjectsPredictor Variables Variables correlated with predictorvariablesCorrelationCoefficientAwareness of AOD help Others suggest AOD help .137**Number of known treatmentTCU DH -.241***centresThink have problem .136**Age first used drugs .173***Time to treatment SOCRATES -.138**Community views aboutThink have AOD problem -.131**access Age first used drugs .133*** " < .05; ** " < .01; *** " < .00168

The predictor variable “Time to treatment” was negatively correlated with theSOCRATES scale, indicating that as travelling time to treatment increases,readiness and motivation to change substance use decreases. Finally, thepredictor variable “Community views about access to treatment” was negativelycorrelated with “perceived AOD problem” and positively correlated with “age atwhich first used drugs”. This suggests that as age of drug use initiation rises,community views about access to services becomes more negative (increases).In addition, as community views about access to treatment become morenegative, self-recognition of AOD problems decreases. The predictor variable“Competing needs” was not significantly correlated with any of the need fortreatment variables (Table 19).4.4.3. Relationships between enabling variables and predictors of accessamong respondents who did not access treatmentThe predictor variable “Awareness of where to go for AOD help” was positivelycorrelated with number of known treatment centres, social trust, abstinencesupport and the RAND social support scale. In contrast, this variable as well asthe predictor variable “Number of known treatment centres” were negativelycorrelated with travelling time and distance to nearest treatment centre,competing needs, and affordability barriers. This indicates that as time anddistance to treatment, competing needs, and affordability barriers increase,awareness of where to go for AOD help decreases. “Number of known treatmentcentres” was positively correlated with depression and anxiety scales, the RANDsocial support scale, income, and social trust. These findings suggest that higherlevels of support and income, higher levels of social trust, and lower levels ofpsychological functioning are associated with greater awareness of where to gofor AOD treatment (Table 20).The predictor variable “Competing needs” was positively correlated withaffordability barriers, and negatively correlated with social support, abstinencesupport, social trust and stigma consciousness. This indicates that as competing69

monetary needs rise, subjects report lower levels of social and abstinencesupport and lower levels of social trust (an indicator of social capital). In addition,the predictor variable “travelling time to treatment” was positively correlated withaffordability barriers and travelling distance to treatment, and negativelycorrelated with awareness of AOD help and number of known treatment centres.Finally, “community views about access to treatment” was positively correlatedwith delays in accessing treatment, community stigma and stigma consciousnessand negatively correlated with social support. This suggests that as delays inaccessing treatment as well as stigma towards drug users increases, communityviews about access to services becomes more negative (Table 20).Table 20. Enabling/restricting variables significantly correlated with predictorsof access to substance abuse treatment among control subjectsVariablesPredictor variablesAwareness Numberof knowntx centresCompetingneedsTime totreatmentCommunityviews:accessIncome - .136*** - - -Social trust .265*** .316*** -.149*** - -Awareness AOD help - .331*** -.136** -.165** -Number of tx centres .331*** - -.157*** -.235*** -Affordability barriers -.149*** -.250*** .152*** .194*** -Delays in treatment - - - - .254***Time to treatment -.165*** -.235*** - - -Distance to treatment -.123** -.214*** - .787*** -Competing needs -.136** -.157*** - - -Community stigma - - - - .325***Stigma consciousness - - -.125** - .182***Depression - .132** - - -Anxiety - .315*** - - -Abstinence support .117** - -.140*** - -RAND social support .111** .257*** -.157*** - -.151**** " < .05; ** " < .01; *** " < .00170

4.4.4. Predictors of awareness, competing needs, travelling time totreatment, and community views about treatment accessA series of multiple regression analyses were performed to identify predisposing,need for treatment and enabling variables that predict awareness of AODservices, number of known treatment centres, competing needs, travelling time totreatment, and community views about access to treatment, amongst subjectswho had not accessed treatment services (N = 555). This allowed the researcherto evaluate the independent contribution of variables associated with each ofthese dependent variables and to identify factors that could be targeted ininterventions to maximize factors that facilitate access. Predictors of awareness of AOD servicesNES, social trust, travelling distance to treatment, others suggesting the need forhelp, social support, abstinence support, and self-efficacy to stop AOD use formore than 1 month had significant partial effects on awareness. The strongestpredictors were others suggesting the need for help and number of knowntreatment centres. Subjects for whom others suggested the need for help hadalmost double the odds of being aware of AOD services compared to those forwhom others did not suggest the need for help. Similarly, for every one-unitincrease in the number of number of known treatment centres scale, the odds ofbeing aware of services increased by a multiplicative factor of 1.9.For distance to treatment, the inverted odds ratio revealed that a one-unitincrease in the scale was associated with the odds of not being aware of AODservices increasing by a multiplicative factor of 1.5. Similarly, the inverted oddsratio for the RAND social support scale found that a one-unit increase in thescale was associated with the odds of not being aware of AOD servicesincreasing by a multiplicative factor of 1.5. In contrast, a one-unit increase in theTCU abstinence support scale was associated with the odds of being aware ofservices increasing by a multiplicative factor of 1.1. This suggests that genericsupport decreases awareness whilst abstinence-specific support is associated71

with improved awareness of services. The remaining variables, althoughsignificant, had very weak effects on awareness (Table 21)Table 21. Logistic regression with awareness as the dependent variablePredictor variables # Wald (df =1) OR (95% CI)NES -0.08 8.08** 0.92 (0.87-0.98)Social trust 0.06 20.20*** 1.06 (1.03-1.09)Others suggest need help (Yes) 0.66 9.58** 1.93 (1.27-2.93)Self efficacy stop AOD use >1month 0.26 6.14* 1.30 (1.06-1.30)RAND Social support composite -0.43 6.48* 0.65 (0.47-0.91)TCU Abstinence support 0.06 9.79** 1.07 (1.02-1.11)No. of known treatment centres 0.66 25.79*** 1.93 (1.50-2.49)Distance to treatment -0.38 4.76* 0.68 (0.48-0.96)* " < .05; ** " < .01; *** " < .0014.4.4.2. Predictors of “number of known treatment centres”A stepwise multiple linear regression analysis was performed with number ofknown treatment centres as the dependent variable and all variables significantlycorrelated with this variable in earlier analyses entered as independent variables.Several variables emerged as significant predictors of number of knowntreatment centres, namely: TCU DH, TCU anxiety, awareness of AOD help,travelling time, legal employment, relative deprivation, trust, and social support.The stepwise procedure entered TCU desire for help as the best predictor ofnumber of known treatment centres, with this variable accounting for 10.5% ofthe variance. TCU anxiety was the second strongest predictor of number ofknown treatment centres, accounting for an additional 12.6% of the variance.Higher scores on the following variables predicted knowing more treatmentcentres: anxiety, social trust, social support, employment, and relative deprivation(where higher scores indicate less deprivation) (Table 22).72

Table 22. Linear regression with number of known treatment centres as thedependent variablePredictor variables Beta T (df =1)TCU DH -0.32 -8.74***TCU anxiety 0.28 7.55***Awareness of where to go for help 0.19 5.16***Travelling time to treatment -0.14 -3.98***Legal employment 0.14 3.98***Relative deprivation 0.15 4.04***Trust 0.08 2.14*Social support 0.08 2.08** " < .05; ** " < .01; *** " < .0014.4.4.3. Predictors of “travelling time to treatment”A stepwise multiple linear regression analysis was performed with travelling timeto treatment as the dependent variable and all variables significantly correlatedwith this variable entered as independent variables. The variables that emergedas significant predictors of travelling time to treatment were: distance totreatment, ADUSE-C scale, number of known treatment centres, and affordabilitybarriers. The stepwise procedure entered distance to treatment as the bestpredictor, with this variable accounting for 69% of the variance. Greater distancesto treatment predicted longer travelling times. More affordability barriers alsopredicted longer travelling times to treatment. In contrast, higher levels ofabstinence self-efficacy and greater number of known treatment centrespredicted shorter travelling times (Table 23). These variables were however,weaker predictors of travelling time to treatment.Table 23. Linear regression with time to treatment as the dependent variablePredictor variables Beta t (df =1)Distance to treatment 0.81 34.01***ADUSE-C composite -0.10 -4.00***Number of known treatment centres -0.06 -2.27*Affordability barriers 0.05 1.98** " < .05; ** " < .01; *** " < .00173 Predictors of “community views about access to treatment”A stepwise multiple linear regression analysis was performed with communityviews about access to treatment as the dependent variable and all variablessignificantly correlated with this variable entered as independent variables. Thevariables that emerged as significant predictors of community views aboutaccess to treatment were NES, community stigma and stigma consciousness,the ADUSE-C scale, social support, barriers related to delays in accessingtreatment, and perceived AOD problem (Table 24).Table 24. Linear regression with community views about access to treatmentas the dependent variablePredictor variables Beta t (df =1)NES 0.23 5.83***Community stigma 0.28 7.43***ADUSE-C -0.18 -4.64***RAND social support composite -0.14 -3.97***Barriers related to delays in accessing treatment 0.11 2.77**Stigma consciousness 0.12 3.23**Think have an AOD problem -0.09 -2.33** " < .05; ** " < .01; *** " < .001The stepwise procedure entered NES as the best predictor, with this variableaccounting for 16% of the variance. Lower neighbourhood advantage predictedmore negative community perceptions about access to treatment. In addition,greater community stigma, more stigma consciousness and more delays inaccessing treatment due to waiting lists and gatekeepers predicted morenegative perceptions about access. In contrast, higher levels of abstinence selfefficacy,social support and self-perceived AOD problems predicted morepositive perceptions about access to treatment. Apart from community stigma,these variables were much weaker predictors of community views about accessto treatment (Table 24).74 Predictors of “competing monetary needs”A stepwise multiple logistic regression analysis was performed with competingneeds as the dependent variable and variables significantly correlated with thisvariable entered as independent variables. The variables that emerged assignificant predictors of “competing needs” were self efficacy to stop AOD use formore than 1 month, social support, and awareness of where to go for AOD help.Table 25. Logistic regression with competing needs as the dependent variablePredictor variables # Wald (df =1) OR (95% CI)Self-efficacy stop AOD use > 1month -0.37 14.40*** 0.69 (0.57-0.84)RAND social support -0.42 8.84** 0.66 (0.50-0.87)Know where to go for AOD help (No) 0.50 5.18* 1.65 (1.07-2.53)* " < .05; ** " < .01; *** " < .001Inverted odds ratio shows that for every one-unit increase in the self-efficacyscale, the odds of not having competing needs increased by a multiplicativefactor of 1.5. Similarly, the inverted odds ratio for social support revealed that forevery one-unit increase in this scale, the odds of not having competing needsincreased by a multiplicative factor of 1.5. Self-efficacy and social support thusseem to be associated with fewer competing monetary needs. In contrast,subjects who were not aware of where to go for AOD-related services had 1.7times greater odds of having competing monetary needs than subjects who wereaware of where to go for AOD-related services. The effects of these predictorson competing needs are relatively weak (Table 25).4.5. SUMMARY OF FINDINGS• All subjects commented on the limited availability of substance abusetreatment facilitiesPredictors of access• When controlling for gender and race, enabling variables are more powerfulpredictors of access to substance abuse treatment than need for treatmentand/or predisposing variables.75

• In historically disadvantaged communities in the Cape Town metropole, thefollowing enabling factors are especially significant influences on access totreatment: awareness barriers (indicated by awareness of treatment services& number of known treatment centres), geographical accessibility factors(indicated by traveling time to treatment), affordability barriers (income andcompeting financial needs).• When the influence of need for treatment and enabling variables arecontrolled for, only one predisposing factor remains a significant influence onaccess to treatment: community perceptions about access. More negativeperceptions about access and service availability are associated with lesstreatment utilization.• When the influence of predisposing and enabling variables are controlled for,the only need for treatment factors that remain significant influences onaccess to treatment are drug use severity and age at which first used drugs.However, these are weak influences on access.Gender and race differences on predictors of access• Female substance abusers who do not access treatment are more likely tohave competing financial needs and other affordability barriers as well aslonger traveling times to treatment than their male counterparts• Black/African substance abusers who do not access treatment are more likelyto have longer traveling distances to treatment (accessibility issues), lowerawareness of existing treatment services and more financial concerns thantheir Coloured counterparts.• In contrast, Coloured substance abusers who do not access treatment aremore likely to have negative perceptions about treatment and more treatmentthan their Black/African counterparts.Factors underpinning key predictors of access to treatment• Awareness: The most powerful factors underpinning awareness of where toget help included the role of others (“others suggest the need for help”) and76

number of known treatment centres. Weaker influences included support forabstinence, self efficacy and distance to treatment• Number of known treatment centres: The strongest influences on numberof known treatment centres are desire for help and anxiety. Other significantfactors include social trust, social support, and relative deprivation, withhigher levels of social trust and social support and lower levels of deprivationpredicting more known treatment centres• Competing needs: Improvements in self-efficacy and social support seemassociated with reductions in competing financial needs. Competing financialneeds are also associated with barriers relating to awareness of services.• Time to treatment (Geographical accessibility): The most powerful factorsunderpinning travelling time to treatment include distance to treatment,followed by affordability barriers; with higher levels of these variablespredicting longer travelling times. In contrast, greater levels of abstinence selfefficacy and greater number of known treatment centres predicted shortertravelling times.• Community views about access: The most powerful factors underpinningnegative perceptions about access and availability of treatment includegreater neighbourhood disadvantage, greater community stigma, and barriersrelated to delays in accessing treatment due to gatekeepers. In contrast,greater social support and abstinence self-efficacy predicted more positiveperceptions about the availability of treatment.77

RESULTS: PHASE TWODuring qualitative data analysis, three themes were identified: political andsystemic influences on access to treatment, treatment system dynamics, andcommunity dynamics. The first two themes relate primarily to theexternal/contextual environmental domain, while the third relates to thepredisposing and enabling variable domains of the BHSU.5.1. THEMES RELATED TO BROAD SYSTEM DYNAMICSWe identified two broad systemic influences on substance abuse treatmentutilization: provincial government’s responses to substance use and theprovincial government’s allocation of resources to substance abuse treatment.5.1.1. Provincial government’s responses to substance abuseProvincial government’s responses to substance use indirectly hamper treatmentutilization by shaping the organization of the treatment sector and communityresponses to government initiatives. The first influence on government’s responses to substanceabuse revolves around information.More specifically, government tends to develop strategic plans and responseswithout assessing the needs of HDCs and gaps in current service delivery:“You (government) say research is not available, so how do you make yourdecisions?” [LDAC]“…even to identify needs and gaps (in service delivery) because often, thedepartment will take the initiative and say, okay they want some training here orthey identify certain needs but I know they don't have very good needs analysisin the province…” [TSP]This hampers government’s ability to appropriately allocate resources fortreatment. For instance, it has contributed to an uneven dispersion of resources;with some communities being relatively over-served while others remainunderserved, despite similar needs. In addition, it has led to service duplication,78

with government and NGOs often providing similar services in the samecommunities:“Somebody, somewhere, some person or persons need to take the role of coordinatingservices within areas and identifying gaps, as … has mentioned nowthere is another treatment centre in Community Y. I know Community Y is a bigarea and there is a need, but then who will serve the other areas where theservice is nonexistent?” [TSP]“I have been really amazed to see that within Community A, the department hasagreed to also offer treatment centre X posts in Community A, when there arevarious other suburbs which there is no service…I am just saying that there is anuneven spread of resources.” [TSP] Secondly, government’s failure to consult with otherstakeholders impacts on the quality of their responsesIn part, government’s lack of information about needs and service gaps stemsfrom their failure to consult with TSPs:“….Never, as far as I know have they come to anyone of us and said, listen let'sjust plan together. They decide, the minister or whoever, they have got x amountto spend and they want to do a project.” [TSP]“The department will strategise and they will have their own agenda, and thenthey will decide, okay this year we have got x amount we would like to spend onsubstance abuse, and that is normally when they want to make some kind ofpublic press release or statement- but that is without any consultation with peoplein the field. They could say, listen, let's just sort of get ideas together. So thereis no partnership; that there is kind of an opportunity for us to also give input tothe department, say listen we think that will work or let's try it this way…all I wantto say is it is without any consultation with anyone in the NGO sector.” [TSP]79 Government’s responses to substance abuse are adverselyaffected by a lack of intersectoral collaborationThere is a lack of intersectoral collaboration between government departmentson substance-related issues which hinders government’s ability to developadequate responses to substance abuse issues:“There's complete fragmentation. Nobody is collaborating with anybody else atall.” [LDAC]“You don't see anything really materialising on the ground level, where the 3departments (health, education, social services) actually say okay, this is howtogether we are going to address the problem practically.” [TSP]Government departments’ inability to work together on substance abuse issuesalso reduces the perceived competency of government in HDCs, thus increasingcommunity resistance to government-run substance abuse interventions anddecreasing social trust in government-run institutions such as state “rehabs”.This reflects how broad systemic factors influence community responses totreatment utilization. As a SAC commented:“And also they (community) can see the different departments are not workingtogether. You get the education department going to X and whatever, but they'renot actually working together to help in this. So that's already a negative thingfrom government's side.” Government’s responses to substance abuse are adverselyaffected by the “leadership deficit”Provincial government seems to have a “leadership deficit”, characterized byfailure to take responsibility for substance abuse programme planning andimplementation. This is partly due to substance abuse’s waxing and waningpolitical popularity, where at times no government department is willing to acceptresponsibility for substance-related issues. As one key informant remarked:“It's an odd thing, because with substance abuse it tends to go in cycles whereno government department wants it. And then every now and again all thegovernment departments will be fighting to play the lead in it.” [TSP]80

This lack of leadership entrenches community resistance to governmentinterventions by perpetuating community beliefs that the state is not heldaccountable for service delivery outcomes:“The lack of (government) leadership and the inability to implement effectiveinterventions in communities has actually made the community quite resistant.It's made them resistant and very angry. It's made them resistant to effectivetreatment, because it's coming from outside the community.” [LDAC]“At the end of the day, what is really needed is a person or a single person ordepartment, where the buck stops. Yes, somebody needs to be accountable,because it is public money; it is funding that is involved.” [TSP] Ideologies & political agendas at the cost of community needsGovernment’s responses to substance-related issues are also hampered bypolitical agendas; which sometimes take precedence over community needs.This is reflected in government’s tendency to seek “quick fixes” rather than“sustainable solutions” to substance abuse problems in HDCs:“Peoples frustration is just, if you look at the past 2 years, the amount of moneythat went from the various departments to training people without any properfollow up plan, or to make things sustainable…. And sometimes, I feel thedepartment is very short sighted and they try and look at quick fixes and there isno way you can do that in this field.” [TSP]“If you think in terms of community development, in one area that was identified,they want us to change the community within 6 months and we said no… it isnothing to have all those projects in place and it can be completed within 6months, but there is no sustainability. So they don't have a sustainable plan inplace and that is why the impact is lacking.” [TSP]These political agendas are also reflected in (i) reports that the governmentplaces more importance on “being seen to be acting in communities’ bestinterests” instead of service outcomes and (ii) claims that the government onlytakes swift action when it is politically opportune to do so. These politicalpositions tend to increase community resistance to external interventions:81

“Part of the government's agenda is definitely to make an impact in communities.But part of the agenda is also to be seen to be making an impact, and there'sless of an emphasis on the impact being made as opposed to being seen.” [TSP]“I think a lot of the time there's a bit of an Elastoplast attitude where you just wantto cover it up or you just want to be seen to be doing something. And a lot ofmoney goes down the drain that way. That you don't tender properly for it, thenthe tender goes to the cheapest person without evaluating the actual quality ofthe training and what approach people are taking to the training. And sometimesits pure political being seen to be doing something about substance abusebecause it's a major community thing and it's had lots of publicity.” [TSP]There also appears to be a relationship between government’s responses tosubstance abuse and their allocation of resources to substance abuse treatment.5.1.2. Allocation of resources to the social welfare and health sectorsGovernment’s allocation of financial and personnel resources for substanceabuse intervention seems to hinder treatment utilization by limiting (i) serviceproviders’ capacity to provide substance abuse-related services; (ii) theavailability of affordable, publicly-funded substance abuse treatment; and (iii) theavailability of ancillary health services. Allocation of personnel resourcesLack of personnel within district social service offices limits state social workers’capacity to provide substance-related services by restricting the number ofpeople that can be served, service coverage, and service quality:“Understand that really there is a shortage of staff and this area we findourselves in is overpopulated, there is a lot of people here… I don't know howmany social workers; there is one social worker for whatever. But you will findthat ….the population of community Z is increasing… So it becomes really verydifficult. At times you can see our waiting room here is full, full and these peoplethey need to be served by today and they must be at home by the time we knockoff. So do you think really that we are producing quality service, I doubt it.” [SAC]82

“I think we don't have the infrastructure. We don't have the capacity. We knowwhat we're supposed to do but we don't have the people, the manpower. We justdon't have it. I mean, we've started now the substance abuse coordinators, andthe reality is we're using the same people in the department…they haven't addedextra staff to this project. So we don't have the capacity... Although we want tohelp the community outside there and be effective with regards to intervention,we don't have the capacity.” [SAC]An unintended consequence of this limited manpower is that SACs performmultiple activities unrelated to substance abuse. These competing demandsfurther reduce their capacity to provide substance-related services:“At times it becomes very difficult, especially the support from your supervisorand the rest of the office. If I can give an example, I need to go out and do drugand substance abuse training, my supervisor is going to growl and say; how canyou go, you are the only crisis worker, how are we going to cope without you, youcan't go and stuff like that because there is not enough staff. So the moment thatyou are not there then there is a gap”. [SAC]“You know, this substance abuse is actually a secondary function. It's not myprimary function. Just to find a balance between the two is nerve-wracking... Andbesides that your managers also say, look you have to focus on your primarywork as well. Substance abuse is not the alpha and omega.” [SAC]Limited manpower not only restricts service capacity, which affects access tocare; but also contributes to low morale and work-related stress among statesocial workers:“It's difficult for me. The expectation from head office is to just do substanceabuse, and the manager also expects you to do your primary work. I also feel Ineed to focus on what my job description is actually saying. That's difficult for me,finding the balance.” [SAC]“I still have my case load and I'm the coordinator of substance abuse. I had ameeting last night till half past nine. Monday night till nine o'clock in the evening,because you have to do it outside of your normal duties and office hours. And it's83

putting extra strain and pressure on you. There's no-one extra to help us andsupport us and that for me is really a weakness”. [SAC]Limited knowledge about SUDS also contributes to work-related stress bydiminishing SACs’ capacity to provide effective services:“So I was sort of forced to work in substance abuse, and it's not my passion. Youneed to be equipped and in university you get generic social work training. Youfocus more on child abuse and all that stuff. So I'd feel more confident in thatfield.” [SAC]“For me it's just I'm not confident in terms of even running a drug group, becauseI don't have that knowledge.” [SAC]The state’s limited allocation of personnel resources thus seems to impede thecapacity of state social workers to deliver substance-related services. Thislimited capacity restricts access to substance abuse services and is, to somedegree, underpinned by the state’s limited allocation of financial resources forsubstance abuse. Allocation of financial resourcesThe state’s limited allocation of financial resources also hinders access totreatment by restricting (i) the availability of affordable, publicly-funded substanceabuse services in the social welfare sector and (ii) constraining the availability ofdetoxification and mental health services in the health sector.• Resource allocation to the social welfare sectorAll key informants commented on the limited availability of registered treatmentfacilities in the social welfare sector:“See substance abuse is one of thethe biggest problems in our society. And it'sgetting worse. And the thing is, since the beginning up till now, there's only beenthese few [treatment centres]. You don't see them grow, you don't see themexpand, getting to take more children. But really when you look at the problem inwhole, the rehab centres it's too little.” [TSP]84

“If all the addicts had to decide, I want to go for rehabilitation, out of my own and Iwant to come clean, then by all means we have a problem because now, howmany rehabs have we got? Not enough.” [LDAC]Even where services are available, they have limited capacity to provideaffordable (i.e. free or low-cost) services to clients from HDCs. TSPs reportedpressure to remain financially viable while serving poor clients – this sometimesresulted in indigent clients being refused treatment. For the poor, this hindersaccess to services:“Financially we're restricted. How do you say no? You can't. And then whathappens to us, because we've got overheads that need to be covered? So I thinkthat's one of our main constraints. We've had meetings with government. We'vebeen through the mill. All they did was say we're doing great work. We don't needthat. If we wanted we could have patted ourselves on the back. We need to knowhow government can assist organisations like ourselves. Other organisations arestruggling which are also catering for the under-privileged.” [TSP]In many cases, limited capacity to meet the demand for low-cost services leadsto lengthy waiting periods for affordable treatment slots. These lengthy waitingperiods often act as a barrier to treatment utilization, by diminishing motivation:“Yes there are State facilities that are free but the problem is, the disadvantage isthis, they have to wait for a long time. They are being put on a waiting list.” [TSP]“It was in November and they were saying they're not going to take on anybodynow until February the first. That makes people think where to now?” [LDAC]“For a state patient you will get in, in three months or so. (By that time) they'veoften relapsed in such a state that they're unwilling to come for treatment. Weoften say that when we get an application there's a therapeutic window ofopportunity. And it's so sad when that window passes.” [TSP]“You try and tell that lady that... it is going to take you at least 3 or 4 monthsbefore they will be able to admit him free of charge. He would have been put ona waiting list, by which time what's the point? He'll have committed more crimes,he may have overdosed.” [LDAC]85

The impact of availability and affordability on access is particularly salient amongindividuals requiring inpatient services. As outpatient TSPs commented:“Then looking at the need, I think the problem that we have is to get inpatientfacilities. We are really struggling to get places.” [TSP]“We still experience difficulty in getting people from under-resourced areas intoinpatient treatment.” [TSP]• Resource allocation to the health sectorKey informants also commented on the limited availability of ancillary healthservices for substance-abusing clients, including detoxification services in statehospitals:“(Hospitals and clinics)will assess and see whether there's a need for detoxthere, and then they will arrange the detox. Whether its happening is anotherquestion. People still do have difficulties…” [SAC]“We have experienced problems with detox, access to detox. Although there isa good partnership with us and the various health clinics, it is still difficult toaccess detox.” [TSP]This is partly because detoxification services compete with other, moreprioritized, medical conditions for scarce health resources such as bed space,staff time, and medical supplies:“One of the issues, briefly, is detox. There is an instruction that every hospitalhad to have detox beds. Now that is fine, except that I have to sit in the hospitalin a high trauma area, where they have to decide whether to give this bed todetox or whether to give this to a casualty that has just walked in, that is wherethe problem lies. That's one of the things for those who can't pay. People whocan pay we say go straight to the medi-clinic or the clinic, whatever it is, and getyourself detoxed. That is one of the big issues.” [TSP]“The subject's first reaction might be to go to casualty. They're not going to seeyou straight away because you're not a casualty. It's not like your arm is severedand there's blood. So you are actually the last person that they will assist if86

someone else needs the bed or needs to be assisted. So that person sits thereand waits until somebody can help them.” [TSP]For poor clients, the limited availability of state detoxification services acts as abarrier to treatment, particularly because inpatient facilities generally requireclients to be detoxified prior to admission:“Because the inpatient treatment requires us to have detox. They don't acceptthe person without it. So when you get to the rehab centre they turn the personaway if they get there and they’re still withdrawing. Because they don't have amedical team to look after the person.” [TSP]Similarly, many treatment facilities require clients with co-occurring psychiatricdisorders to be stabilized prior to admission. However, state mental healthservices are often unwilling or unable to treat drug-induced psychiatric problems.Clients thus fall through the cracks of the health system, with neither mentalhealth nor substance abuse services accepting responsibility for clients with cooccurringdisorders:“I have this guy now; he's a psychiatric patient of ten years at X communityhealth care. So his family brought him, and I'm waiting for …treatment centre tolet him be admitted. But at one stage he got so berserk man, he did strangethings. And I thought to myself, no man, he was a psychiatric patient and he's stillgetting medication. So I phoned the psychiatric nurse and she said the personcan come in for assessment. But they sent that person back home and said nothere's nothing wrong. I'm so convinced there is something wrong… The whole ofthe interview he was like fiddling and staring and gnashing on his teeth, and Ithought no this man needs some psychiatric intervention. But they just say it's nota psychiatric case, it's because of the alcohol. They say its withdrawalsymptoms...and you can see there's something wrong with this person but fromtheir perspective there's nothing wrong.” [SAC]The state’s allocation of personnel and financial resources to the health andsocial welfare sectors also hinders access to substance abuse treatmentindirectly by shaping the way in which the substance abuse treatment system isorganised. For instance, the state’s allocation of resources impacts on the87

availability of affordable services, and shape the organization of the treatmentsystem. This is discussed in the following section.5.2. THEMES RELATED TO TREATMENT SYSTEM DYNAMICSThe organization of the substance abuse treatment system and resourceallocation within the treatment system also emerged as influences on access tosubstance abuse treatment. As already mentioned, these factors are influencedby broad systemic and political factors.5.2.1. Organisation of the substance abuse treatment systemAccording to key informants, there are several organisational barriers thatimpede access to treatment, including: complex referral pathways, the presenceof gatekeepers, complex eligibility requirements, and waiting lists for treatment. Complex referral pathwaysKey informants agreed that the lengthy process of accessing treatment and thepresence of “bureaucratic red tape” hampers access to services:“The process is so long.” [TSP]“There's some red tape things and bureaucracy. It seems excessive from thestart.” [SAC]As the process of accessing non-profit treatment involves multiple steps (withgatekeepers controlling access at each step); clients may encounter severalobstacles in their attempts to access services:• Lack of referral pathwayFirstly, there is no structured referral pathway. As the referral pathway isunclear, people are often referred to several organizations before they are able toobtain assistance:“…By the time they come here they have been sent by various organisations. SoNICRO sent them here or the court sent them to social services who sent them tothe day hospital who sent them here. So they get sent from pillar to post.” [TSP]88

“So it's being sent from this place to this place to this place, nowhere tohelp…From point A to B and land up to Z and back again to point A.” [TSP]• Social worker reportsFor clients requiring state-funded inpatient treatment, a further obstacle is theneed for referral from a state social worker. This necessitates the production ofreports on the client’s medical status, need for treatment, and financial status.When combined with caseloads and staff shortages in social work offices, thiscontributes to the referral process taking several weeks to complete:“There are the gatekeepers. There's a process they have to go through. So whathappens there is they then go to social services or to their local hospital whorefers them to social services. Social services then need to dig up reports. Ifsomebody says I am a drug addict please help me, then the social worker has towrite a report, they have to consult doctors and the dominee (Reverend) andeverybody in the area to see whether that person is.” [LDAC]“… you cannot just accept a person who say, place me at D…, I have got thisproblem. You have to check what efforts did the person undertake…. If a personhas done nothing then normally we refer it back to an outpatient centre. If theoutpatient centre feels, no we have done our part and there has been no change,they are supposed to be doing a formal referral to us. After this, if a personcomes for placement then that person will see the intake social worker and thenit takes the social worker not even a day to get the referral through thesupervisor. At times it gets stuck… it all depends on the number of cases theperson does have. If it is so urgent, then the supervisor has to write on yourallocation to attend to this urgently. It takes a month or more than a month,depending on who is doing what. At times you will find that the cases get stuckwhen it comes to supervisor, the supervisor is on leave. And then it is going totake some time to be allocated once the supervisor is back.” [SAC]• Access to detoxification and mental health servicesShould a person obtain a referral to an inpatient facility, the next obstacle s/heencounters is the need for detoxification and/or mental health services. Asmentioned previously, many facilities will not accept clients unless they have89

completed a hospital-based detoxification and unless they are psychiatricallystabilized (should this be required). As the availability of detoxification andpsychiatric services is limited, entry into the treatment system is often delayed:“Detox becomes a problem. That's the first thing he encounters, detox… Nextproblem… Even if we shortcut everything and said bring him in and have aninterview, we have to be careful that he is in fact psychiatrically stabilised tocome in for treatment…And that is the sad part abut the fact that we can't say'bring him in, we'll put him in detox for a week and we'll work the processthrough.' We can't do that. That is the saddest fact of all. If only we had somefacility like that. He may find after detox that he needs primary care in a medicalinstitution; he needs to be psychiatrically stabilised. But unfortunately all this isnot possible in this facility.” [TSP] Complex eligibility requirementsEligibility requirements also hamper access to treatment. For example, mostfacilities do not accept court-referred clients due to concerns about their motives:“And another barrier to treatment is that they're not allowed to go into treatment ifthey've got a court case pending. A lot of places like …won't take people in ifthey've got a pending court case. And their justification for this is that the personis not there for the right motives. Nobody knows what anybody's motives are… Ithink it's very, very short sighted. It seems very short sighted not to take peoplewho are on court cases, because that may very well be the thing that jolts themto pay attention to treatment.” [LDAC, policymaker] Waiting listsEven if the person is accepted into an inpatient facility, they still encounter awaiting period for their admission date:“From there we refer you to D…, because that's the only available statetreatment centre. Depending on their waiting list, which is about a month to twomonths, then the person will get an answer to go in.” [outpatient TSP]“When they do get here for help, what is maybe discouraging for them is perhapsthe waiting list.” [TSP]90

This process of accessing treatment impacts negatively on treatment utilization;with individuals often abandoning attempts to access treatment services:“Ja. Yes, it's true. They just ran away. When you come there then they are notthere. Because it takes so long.” [SAC]“People fall by the wayside.” [TSP]“That that poor guy out there, as willing as he is to stand for treatment, he's upagainst it. And what can he do?” [TSP]These organizational barriers to treatment utilization are not only influenced bythe allocation of financial resources to the health and social welfare sectors, butalso by the allocation and distribution of resources within the treatment system.5.2.2. Resource allocation within the treatment systemKey informants noted that limited financial resources within treatment facilitiesaffect treatment utilization by restricting treatment facilities’ capacity to provideservices and by contributing to low morale within the treatment team. Resource allocation and treatment capacityLimited financial resources affect treatment facilities’ capacity to provide servicesby (i) contributing to staff shortages, (ii) jeopardizing sustainability, and (iii)hampering skills development. Taken together, these factors hamper access toservices.• Staff shortages and treatment capacityLimited resources restrict the number of personnel within facilities, hamperingtreatment capacity and TSPs’ ability to expand their services to meet theincreased demand for services in HDCs:“I think staff shortages is one of the major areas of concern, because with limitedfunding, you cannot really expand or get hold of the necessary resources thatyou would like.” [TSP]91

“I have thirty beds that are unused completely simply because I can't afford to…And of course I can't open those beds up unless I've got staff. Paid staff. Andthat's the whole story of the situation.” [TSP]Coupled with a growing treatment demand, staff shortages have increased thecaseloads of already overburdened counsellors. This restricts the number ofpeople who can be served; thus limiting access to care.“But the thing is person power… And we are only two social workers, Xhosaspeaking social workers, here. For the whole of K community.” [TSP]“So on average we see about six people per day. But because of the otherclients we do see, if they have a crisis, they also tend to be here as well. Or otherpeople that want information. And if the person is crying or needs to be seen to,then you have to see them. So it might be more than that. That's just theaverage… Plus you have your cases that is running already.” [TSP]These shortages also contribute to counsellors having competing demands fortheir time - apart from their treatment duties. This further diminishes theircapacity to provide treatment services:“I was the only one, the only person that was here, then I was supposed to helpwith the community and the case work. That was a difficulty for me.” [TSP]“Because even if you want to train people, it means from our side, it is our seniorstaff that already do have a lot of other responsibilities which need to shift someof the responsibilities to do that and we don't have the time still to go and followup and supervising those kinds of counsellors.” [TSP]• Financial sustainability and treatment capacityLimited financial resources also affect TSPs’ financial sustainability and ability toafford basic materials needed to deliver treatment services:“The premises are quite small as you can see, so it's not actually fit for groupwork. And also (drug) testing. Its not equipped for testing, the space. There'sactually a lack in terms of, say you want to do intervention, just basic stuff likestationery. There's a huge problem. Like paper for pamphlets. Newsprint forworkshops, koki's, just basic stuff. So there isn't basic stuff. Even like our92

computer, it's old and it freezes. You do a report and the thing freezes and thereare other workers that also want to use it.” [TSP]“How do you feed twenty people and still cover your water and electricity and allthose things?” [TSP]“With all our bills we're living on hope and fear. How are we going to cover this?”[TSP]Concerns about financial sustainability often result in TSPs competing forfunding. In some instances, this leads to unhealthy competition and “infighting”:“There's definitely infighting among service providers. They do sometimes seeeach other as competing for the same funding. I think that's in general for NGO'sbut in particular in the field of substance abuse. ” [TSP]“…there is a very unhealthy competitive kind of environment. For some reason,people think that there is money in terms of rendering substance abuse servicesand there are very limited resources. So people are very ... there is resistance toreally work together, because everyone is trying to protect themselves, trying toprotect the resources, and there is not always a willingness to share…” [TSP]According to key informants, “unhealthy competition” makes it difficult fororganisations to pool knowledge, experience and other resources and find jointsolutions to SUDS in HDCs. In addition, as “infighting” damages the reputation oforganizations, HDCs are less likely to utilize existing treatment services:“It does affect the service delivery because some of the organisations will notrefer. Because if I'm in rivalry with you or I don't think you're using your budget ormoney that you have effectively, why must I refer to you? …It affectsorganisations' reputations and it affects their service delivery as well. Andreferral. So ja. And resources. Because we could have used each other'sresources but now we have to struggle on our own.” [TSP]This competition is most salient among unregistered, community-basedorganizations (CBOs), which are particularly prevalent in HDCs:93

“I don't see it amongst the bona fide service providers. I think there's probablyhealthy commercial competition. It's amongst the people who are not capacitatedwho are wanting money to render services that aren't regulated. It's the “Momand Pop” treatment centres who are wanting money who are fighting with people.(For them) it's a way of making an income.” [TSP]These CBOs emerged to address the limited availability of substance abusetreatment in HDCs. While these organizations provide counselling and aftercareservices, they have little knowledge of and few skills to treat SUDS:“So there is other smaller organisations that do provide drug treatment but I don'tthink they have the necessary skills for what we deal with…” [TSP]“And whether they do it for money or out of the best of intentions, they don'teducate themselves in terms of best practise or what we've learnt from researchsince the 1950's. And I think they do a lot of harm. They're using approacheswhich research indicates runs the risk of increasing drug abuse instead ofdecreasing it. We've got people counselling, and their only qualification is thatthey're recovering addicts. Which I think is problematic.” [TSP, policy maker]• Knowledge capacity and skills developmentThis lack of knowledge capacity is partly due to limited financial resources; withCBOs employing “lay counsellors” or “recovering addicts” instead of costlyprofessionals. This impedes service quality and treatment capacity:“So I took on F… that worked in Pick 'n Pay, and I trained her in correctiontherapy, she is battling and I took Aunty F… that was doing community work overthe years. She is battling. I have got all these people, I have trained so manypeople, but none of them are really professional, and they are battling.” [TSP]“People come to us because others have failed, and they will say to us, listen Ineed professional treatment because where I was they treated me like a dog; orit was just lectures; or it was just talk, talk, talk, and I learned nothing.” [TSP]“Quality is really very variable. And it sounds like there are services where as infact there aren't. Because you've this little Aunty Fatima that wants to helpbecause of her nephew, and sets herself up as a treatment expert.” [LDAC]94

Lack of knowledge capacity also sometimes results in unethical practices:“There are some adamant religious approaches which are extremely harsh andare unethical, and place patients or clients' lives at risk.” [TSP, policymaker]“When you hear the stories that is going on within the treatment centres. There isa will power and there is commitment to do something right but I think they lackthe relevant necessary training. Like the story of yesterday when the guys came.They reported yesterday that they actually beat their heads to the ground andthen they had to say “I'm not going to go to the shebeens, I'm not going to go buydrugs”. That kind of stories. Punitive…the only conclusion that I can get to ismaybe a lack of training.” [SAC]Punitive approaches not only impact on the effectiveness of services, but alsoindirectly affect treatment utilization by increasing negative beliefs abouttreatment in HDCs. For example, TSPs commented on “concerns about a lack ofcontrol over yourself and what’s going to happen to you once men in white coatstake over the whole process”, client beliefs that “it’s a jail and you cannot go out”,and concerns that they were going “to be controlled, these people (were) going tohit me.” These perceptions increase resistance to seeking treatment. Resource allocation and low moraleLimited financial resources also contribute to low morale, feelings ofineffectiveness and burnout among TSPs. These feelings impact on serviceprovision and ultimately, communities’ responses to treatment services.According to key informants, treatment staff often struggle to cope with theoverwhelming nature of the work:“It is also with the use, there's the same pattern. The person uses, steals, sleepsout and doesn't come home, comes back Tuesday. So there's this pattern of thechild missing and the child coming home. So there's that pattern, and where do Irefer him to? So it is quite overwhelming having to deal with.” [TSP]“Where do I leave my feelings when I really feel kak (awful). By the time I get tothis gate, there are already 15 guys standing outside waiting for my positiveness.There is a whole staff that is waiting for me to smile, so that I can say today is95

going to be a good day. So, yes it is very, very tough. It is extremely tough. Andto deal with all the horrific things that come in here.” [TSP]The perception that TSPs cannot meet the need for treatment in HDCs alsocontributes to feelings of ineffectiveness:“Because of who we are we sit with huge guilt. I walk here to my house, get intobed and I hear the people on the other end of the phone calls, and it's actuallysoul destroying. I sit up and night and… I sit here and try to work out thesewonderful schemes of how I can connect this all together.” [TSP]“I hate the part of telling the mother that does not have money, that we can't help”[TSP]In several facilities, burnout and low levels of remuneration contribute to lowlevels of staff retention. TSPs reported difficulties in retaining experiencedcounsellors, who are often replaced with new graduates:“In the experience of the X treatment centre as an NGO, our salaries aren't veryhigh. As a result we tend to get social workers straight out of Varsity. They spendtwo or three years here during which we train them up, and then we lose them.We lose them either to private inpatient clinics who pay a good three times whatwe pay our counsellors, or we lose them to Britain. So it's more about difficulty instaff retention. We're very lucky that we've got a set of core staff that is like thespine of the organisation. But around that we have a high staff turnover and partof it is due to the nature of the work - that it is demanding work with a high rate ofburnout - but part of it is definitely just issues around remuneration.” [TSP]As high levels of staff turnover erode the treatment team’s body of skills andexperience, this has a negative effect on service delivery and contributes tocommunity perceptions that treatment is ineffective. For instance, several keyinformants expressed concern about the quality of treatment services provided:“And really, my experience with rehabs or our traditional rehabs we send ourclients to, the success rate is very minimum. They're coming back for two days,for one week and then they relapse again. It's really scary to send the people and96

then they come back and that happens. So I have my own doubts regarding therehab centres.” [SAC]“So that's the experience that people do have. Either it's not successful,ineffective, or they have an approach that is not evidence-based.” [SAC]Treatment system resources thus hinder access to treatment both directly (viatheir impact on treatment capacity and morale), and indirectly by shapingcommunity responses to existing services. These community dynamics arediscussed below.5.3. THEMES RELATED TO COMMUNITY DYNAMICSSeveral community factors emerged as influences on treatment utilization.These include unrealistic expectations about treatment (a predisposing factor),as well as two community enabling factors: community awareness of treatmentservices and social capital within HDCs.5.3.1. Community expectations about treatmentWithin HDCs, unrealistic expectations of existing treatment facilities hampertreatment utilization by shaping community beliefs that available treatmentoptions are ineffective.• Expectations of a quick-fixThese unrealistic expectations seem predicated upon limited awareness oftreatment and recovery. For example, communities do not understand thatsubstance dependence is a relapsing illness. This leads to expectations that asingle treatment episode will “cure” the individual:“So that is the problem, people don't understand that relapses are part ofrecovery. And people might relapse about 1, 2, 3 times before actually reallyrecovering…” [LDAC]“I think they have unrealistic expectations of treatment. That the person comeshere once and they're fine. So when the person perhaps comes three times and97

in the fourth week they relapse, it's like, but we expected you to be ok and you'renot. So that is the misconception about treatment, it doesn't work.” [TSP]These unmet expectations of a “quick-fix” shape community beliefs thatsubstance abuse treatment is ineffective and that “it doesn’t really help to go torehab.” This hampers treatment utilization as communities do not see the valueof treatment for SUDS:“A lot of people are looking for a quick fix and if they don't find one then they thinkthat the service is not good enough.”“When people hear that you are going to rehab they say ‘Why do you want togo, rehabs don’t work’.”• Expectations regarding inpatient servicesLimited knowledge about the treatment process also informs community beliefsthat inpatient treatment is more effective than outpatient services:“Our people, obviously due to lack of understanding of addiction, believe theyshould have an inpatient clinic...let's just make it someone else's problem for awhile, and when he is cured, then bring him back.” [TSP]“They also have the belief that people have to go away for treatment.” [LDAC]Taken together with the limited availability of inpatient treatment, this viewcreates a perception that effective treatment is not available:“I think often there's a tendency in the community to say that there's no help outthere. When it's just not help to their liking. So I think there is in reality a lack oftreatment capacity, but at the same time there'll always be to some extent aperception in the community that there's not enough treatment.” [TSP]• Expectations regarding roles and responsibilitiesLimited knowledge about treatment also shapes community expectations ofTSPs’ roles and responsibilities. According to key informants, communitiesunrealistically expect TSPs to assume full responsibility for the recovery process:98

“I'm bringing the problem to you, you need to fix it. And it's not on. It's their child;they need to take ownership of the problem at the end of the day.” [SAC]“Because, the parents’ perception is, here is my child with a problem, I amputting it on the institution’s lap. And once that problem comes back to me, Iexpect my child to be clean.” [TSP]“Our community, they just want to pass the buck and give you the responsibility.They don't want to take ownership” [SAC]As a result, communities often fail to fulfill their supportive function, which isintegral to successful recovery. Key informants identified two reasons for thisdynamic. Firstly, communities and families are sometimes unaware that theyneed to provide a supportive environment to assist in the recovery process:“The parents don't understand that he is playing an integral part in that child'srecovery process. Because he needs to be the support structure…” [LDAC]“I think total unrealistic expectations. They need to be part of the recoveryprocess, because they have been part of the problem and they also need to gothrough certain changes as a family system…and all of a sudden they expect thisperson to change and be completely recovered and without also realising howthey can form part of the supporting network afterwards.” [TSP]Secondly, communities may transfer responsibility to TSPs due to high levels ofdisempowerment in HDCs - indicated by the desire to be rescued:“Once the child is here then the parents will stand back. Now it is no more myproblem it is the social workers problem. Because they feel, what can I do?”[TSP]“There's desire for rescuing. And we still will every year see people who willcome into the centre and ask for a pill. They want a pill which will make themstop. And if you can't provide that service then they get very irate.” [TSP]The relationship between unrealistic expectations about treatment, communitydisempowerment, and knowledge of treatment suggests that community99

esponses to treatment, in part, are shaped by community enabling resources.These enabling resources are discussed in the following section.5.3.2. Community enabling/restricting resources5.3.2.1. Community awareness of treatment servicesLimited awareness of where, when, and how to seek substance abuse treatmentas well as what comprises appropriate treatment serves as a barrier to treatmentutilization.• Awareness of where to seek helpAlmost all key informants noted that awareness of where to seek help hampersaccess to treatment within HDCs:“Lack of information and knowledge - that's also a constraint. People are sittingthere, hopeless and in a situation of despair. It's unnecessary; if they can onlycome to us we will assist and can assist in some way or another.”This lack of awareness is not, however, uniform. Compared to Colouredcommunities, Black/African communities are relatively less aware of substanceabuse treatment services:“Many people who live in informal settlements are completely ignorant that thereis treatment available. There's a huge problem out there. And not only that, theunderstanding in the communities that this is a disease is non-existent.” [TSP]“And in the Black communities they have no idea about treatment at all. Whenwe were doing our community development work there, they were really pleasedto hear about the support groups and they wanted to know how they could getthem started in their communities. They were fascinated to know that it was anillness.” [LDAC]• Awareness of when to seek helpIn contrast, both Black/African and Coloured communities struggle to recognizewhen substance abuse treatment is necessary. Rather than seeking treatment inthe early stages of the illness, communities tend to seek treatment only once theproblem has become severe:100

“I think when you talk to these people, when they really get worried is whenpsychotic things…Or criminal activity. You know with tik (methamphetamine), forexample, it was fine with the family when he used. It's not fine anymore when hesees things coming out of the walls…Or he's stealing…I think it's about a seriouslack of early intervention.”As a result, communities tend to demand access to inpatient treatment and aredissatisfied when treatment slots are not immediately available:“The other thing is that people by that time are so desperate they want somethingto be done. They don't want (outpatient) counselling, they want this person to besent away.” [SAC]“What you find is that people normally wait until the last moment to come here,when the problem is now out of…out of…do you see? Then they come and thenthey want the child to be sent away immediately because they can't take it anylonger.” [SAC]“I also think by the time when the parent comes and complains about the childthen the situation is already very, very bad. She says I have had enough! Justdo something; just send him away”. [TSP]This interaction between awareness of when to seek help and service availability(a treatment system factor) is shown in this comment by a TSP:“Part of it is also possibly not knowing when to get help, or not defining it assubstance abuse. I also think its simple things like providing treatment servicesin……those areas.”• Awareness of how to seek helpHDCs also do not know how to access treatment, especially the procedures thatneed to be followed to access help:“The way I assess it, they do want their children to go to rehab but the only thingthey don't know is the procedure. If a parent experience that a child has got aproblem and they are sick and tired of all those things they come to us and,please I want to take my children to this place but they don't know andunderstand the procedure…” [SAC]101

• Awareness of appropriate treatmentIn addition, communities do not seem to be aware of what constitutes appropriatetreatment for SUDS. For example, they do not seem to recognize that substancedependence requires professional intervention. According to one SAC: “It’speople's misunderstanding about what rehab is about.”“And very often they don't go because they don't know where to go seek help.And they've heard about Mrs So and So who's heard this about that place... Sothey're not understanding that if you're on heroin you need a detox. They're notunderstanding that if you're on meth you need this process.” [LDAC] Social capitalAnother barrier to treatment utilization is low levels of social capital, indicated bylow levels of collective efficacy and social trust.• Collective efficacy in HDCsLearned helplessness and disempowerment around substance abuse issuessuggest that HDCs have low levels of collective efficacy (i.e. ability to act jointlyto address substance-related problems):“I do believe that our parents in our community they don't know what to do whena child has a problem with the substance abuse. They don't know what to dobecause these children are too much for parents, they carry guns… ” [SAC]“Some parents say to me 'we know there's a place that is selling drugs to ourchildren, but there's nothing we can do.’” [SAC]“Complete disempowerment, this is the way life is going to be.Absolute hopelessness about the future.” [LDAC]When missing, this component of social capital hinders treatment utilization::“And if she is using drugs, what would the parents do? If she is, so what? Well,not 'so what' but rather not go there because then the parents got to take somesort of action.” [LDAC]“Families don't know what to do; the school doesn't know how to deal with it.102

So it's easier just to be quiet about it and silent about it than saying this isunacceptable, because the next step would be, what do we do now?” [TSP]Traditionally Black/African communities seem to have higher levels of collectiveefficacy than their Coloured counterparts. Key informants noted thatBlack/African communities seem willing to work together to resolve socialproblems, while Coloured communities have low levels of social cohesion:“In our Black communities, if you invite them over they can come togetheragainst whatever. I think the community is also willing to come to board to helpwith what we are trying to do now.” [SAC]“In the community you get the different community organizations working againstone another, but they're both working for drugs. You know? With the drugproblem at the end of the day. So this competition is also happening in thecommunity now.” [SAC serving predominantly Coloured communities]One of the contributing factors to low levels of collective efficacy isneighbourhood environment, a community predisposing variable. All keyinformants noted that poverty, lack of recreational facilities, and other socioeconomicproblems foster widespread drug use; with drugs being viewed as acoping mechanism in these communities:“There are a host of socioeconomic problems. And that, with a lot of peopletogether, and then here comes the drug lord, because there is a lot of people,there is nothing to do. We don't earn enough money, but we can fix you up witha hit or two. And you can get high on something, and at least you are going to dosomething that is going to be nice, for the start, until addiction strikes…” [LDAC]“It's a way of coping. It's a way of coping. Everybody uses drugs, everybody getshigh.” [TSP]In addition, drug dealing is viewed as a means of surviving financially in HDCs:“Every second house there's drug merchants. That is what the problem is.Because there is more and more dealers going out, it's a quick way of makingmoney. Selling this heroin, selling this tik.” [LDAC]103

This perception is prevalent in Coloured communities, where drug merchants areseen as a financial resource. This diminishes collective efficacy aroundtreatment-seeking:“Those specific merchants support maybe the aunty next door. They'redependent on them. They get bread or money or whatever. I don't know, it'smore a cycle, the whole poverty thing in the community contributing to peoplebeing dependent on drug merchants.” [SAC]“And the of course, why must I go to rehab when the merchant is paying mymom's bills? It happens and drug pushers are actually doing that, to the extentwhere they hand out groceries. If you're living in a poor area and somebody isgoing to offer you groceries, why would you bother? Why would I send my son(to rehab)?” [TSP]The normalization of drug use is another aspect of the environment thatcontributes to low levels of collective efficacy in Coloured communities. Keyinformants from these communities reported that drug use is part of communityculture and is viewed as “part of life”. In contrast, drug use is not normalized intraditionally Black/African communities:“It was part of the culture in the Cape Flats.” [TSP]“I find that…it's different from our (Black) areas. In our areas it's not accepted.It's really not accepted, especially with young people. But in Coloured areas itseems as though it's something that's not so bad in the community. In one familyyou will find the grandmother is abusing liquor, the mother, the father, thechildren, everybody here. At one stage I was shocked to find that almost thewhole family is using drugs.” [SAC]This not only reduces collective efficacy, but also diminishes the value thatcommunities’ attach to treatment. This hinders treatment utilization:“What I find especially with the use is that it has become something that just 'is' inthe community. I think the idea is that its part of life. So if it’s part of life, why areyou people going on like that? Why is my mother finding a problem with it? Sothat is I think a common belief...Why must I be here (in rehab) when a whole104

neighbourhood is using? So what difference can you make if I am coming here?So because of normalisation it does become a problem for them to be at atreatment centre.” [TSP]• Social trust in HDCsSocial trust, another component of social capital, also appears to affect treatmentutilization. This is most salient in Coloured communities, where there is distrusttowards “outsiders” who provide substance abuse services:“There're still people who’re saying why are you coming now? …and you get allthe recognition at the end of the day. You know, so you're coming from outside,you weren't here from the beginning.” [SAC]“They are seen as outsiders… then the people still ask who the social workersare? We don't see them in M…. community. Things like that. That is where thehostility comes from.” [SAC]In part, this “insider/outsider” perspective emerges from the provision ofineffective and poor quality services by “external” organizations. This hasresulted in communities being less receptive to “outside” interventions, includingthe provision of treatment services by professional facilities:“So we have had an organisation, for example, they've advocated vitamins whichcan cure substance abuse. Obviously this is problematic and I think thatcommunities are therefore less receptive after that, when they've received thatkind of thing and have been let down to that degree. I think that's part of theproblem.” [TSP]“But that's because they've had so many people come in and tell them what todo. Government started the tik task team. That fell apart. They had Xorganization in, they had Y organisation in. They've had all sorts of differentpeople in and nothing's happened.” [LDAC, policy maker]This “insider/outsider” perspective hampers treatment utilization, as services runby “outsiders” are often not supported or given “buy-in into the community.”Instead, several communities are attempting to find their own solutions to the105

substance abuse problem - without assistance from TSPs. This is cause forconcern given the limited capacity to provide treatment in HDCs::“They don't respect…they think very little of them coming in the community. Theythink they're better equipped than anybody else to do the job because they'refrom the community and all that stuff.” [SAC]“(Communities) feel they're better equipped to deal with the problem in the area.For example if people come to them in the evening for drug counselling, thenthey want to do it.” [SAC]This lack of social trust extends beyond TSPs to include governmentdepartments responsible for the co-ordination and management of substanceabuse services. According to key informants from these communities,government raised expectations that substance abuse would be effectivelyaddressed. As this has not happened, communities feel “let down” and“betrayed”:“But it is not impacting…and the department is saying look, we are going to havethis and that glamorous thing that is going to take place, that is going to ease theimpact (of drugs) and will create work. Look at the day hospital and look at thepolice station and look at the courts, mothers sitting outside and you see theguys appearing in the Magistrate’s Court. 95% of those people that is beingcharged, somehow or the other are linked to drugs, or to get their hands ondrugs…So did it impact? No.” [LDAC]“They are raising expectations in the community…Hulle maak 'n klomp promises.And that is it. Now you ask yourself what has happened ever since after that.What has happened? Did it impact that problem?” [TSP]The lack of social trust in government is also due to government’s top-downapproach to interacting with HDCs, with communities feeling that their voices arenot being heard and that “they just hear what they want to hear”:“…things work a lot better if needs are identified by the community and it's abottom-up process…The problem happens when an area is identified bygovernment, even by national departments, as one where there is a need. And106

money is given for people to go and do work in that area. But it's very much atop-down approach and your outcomes are a lot less in that scenario.”According to key informants, this has implications for the implementation and useof public substance abuse services, with community willingness to supportsubstance abuse initiatives diminishing:“Well I think that is important… It's to start with your community, to start with theirneed, to identify who the community leaders are and to involve them right fromthe very beginning, and not just coming in with your own plans and ideas… Ithink that is very important, otherwise you will not get the buy-in and the supportfrom the community and you cannot change a community without thecommunity's own taking partnership, taking ownership of any project.” [TSP]This reflects how social capital, particularly social trust, is informed by broadersystemic influences. Community barriers to treatment utilization thus interactwith political and treatment system factors to influence substance abusetreatment utilization in HDCs.5.4. SUMMARY• Both political and treatment system factors influence access to care.o Political strategies for addressing substance abuse in HDCs interactwith the state’s allocation of resources for substance abuse to affectthe availability of substance-related services, treatment systemdynamics, and community responses to both state and TSPinterventions.o The organization of, and resource distribution within, thetreatment system affects access to care directly and indirectly byhindering treatment capacity and by shaping communityperceptions about the effectiveness of services.o The lengthy process of accessing treatment (specifically unclearreferral pathways and multiple gatekeepers) hampers access toservices.• Community dynamics directly influence access to treatment.107

o These community influences are located within both the predisposingand enabling variable domain of the BHSU.o Awareness of when, where and how to access treatment impedestreatment utilizationo Unrealistic expectations of TSPs creates negative perceptions oftreatment services and hampers service use.o Social capital (specifically collective efficacy and social trust)negatively affect treatment utilization.o Low levels of social capital are underpinned by neighbourhooddisadvantage, poverty and the normalization of drug use withinHDCso Socio-demographic differences were found on community enablingresources; with Black/African communities being less aware oftreatment than Coloured communities, and Coloured communitieshaving lower levels of social capital than Black/African communities.• Contextual/environmental factors influence both predisposing andenabling resources- suggesting that access to substance abuse treatment ismultiply determined.o These multiple influences on access, together with constraints ontreatment capacity in the substance abuse treatment system, highlightthe challenges of delivering substance abuse treatment in resourcepoorsettings.108

DISCUSSION AND RECOMMENDATIONS6.1. IS ACCESS TO SUBSTANCE ABUSE TREATMENT EQUITABLE?Findings show that access to substance abuse treatment for historicallydisadvantaged communities in the Cape Town metropole is not equitable. Morespecifically, when substance abuse treatment need is considered in the light ofpredisposing and enabling/restricting variables, findings show that access isdetermined predominantly by the extent to which barriers to treatment areexperienced and negative views about treatment are held, with need fortreatment having little effect on treatment utilization. This highlights the need forinterventions that address barriers to accessing substance abuse treatment aswell as negative perceptions about treatment services.6.2. FACTORS THAT PREDICT ACCESS TO SERVICESAlthough a range of variables were significantly associated with access tosubstance abuse treatment for people from historically disadvantagedcommunities in the Cape Town metropole, many of these were weak predictorsof access to treatment. For instance, while some indicators of perceived andevaluated need for substance abuse treatment significantly predicted treatmentutilization, when considered together with indicators on the enabling andpredisposing variable domains, their effect on treatment utilization was relativelyweak.In contrast, the strongest predictors of access were located in theenabling/restricting variable domain. These predictors included: awareness oftreatment, geographical accessibility of treatment (indicated by travelling time totreatment) and affordability of treatment (indicated by competing financialpriorities and income). Negative perceptions about access to treatment, anattitudinal-belief variable located in the predisposing variable domain, wasanother strong predictor of whether persons accessed treatment. The followingsub-sections describe these predictors.109

6.2.1. Awareness of substance abuse treatmentOne of the strongest predictors of access to substance abuse treatment isawareness of substance abuse treatment services. Findings from the qualitativephase of this study not only confirm this finding, but also suggest that awarenessof substance abuse treatment is often multidimensional, with several dimensionsneeding to be present to facilitate access to treatment. More specifically, keyinformants noted that for access to occur, persons need to be aware of where toseek help, to know when help is needed, and to know how to access services.Furthermore, persons also need to know what constitutes appropriate treatmentfor substance use disorders. This study found that knowing how to accessservices is strongly related to the organisation and functioning of the substanceabuse treatment system, a factor that predicts access to services (discussed insection 6.3). In contrast, knowing what constitutes appropriate treatment forsubstance use disorders seems to underpin HDCs’ perceptions of treatmentanotherfactor strongly associated with access to services (see section 6.2.4).During the quantitative phase of the study, this first dimension, knowing where toseek help, was indicated by two variables: awareness of alcohol and drugtreatment services, and number of known treatment centres. For the former,findings indicate that the odds of accessing treatment were ten times greater forpersons who knew where to go for alcohol and drug-related help compared topersons who were not aware of where to go for help. In addition, the odds ofaccessing treatment were greater for individuals who knew of more treatmentfacilities; with every one unit increase on the “number of known treatmentcentres” scale resulting in a five-fold increase in the odds of accessing treatment.These findings from the quantitative component of the study highlight the strongeffect that awareness of where to seek help has on substance abuse treatmentutilization. Socio-demographic differences on awareness barriersRelated to this, both qualitative and quantitative findings suggest that personsfrom Black/African communities are significantly less likely to know where to110

access substance abuse treatment services compared to their Colouredcounterparts. For instance, for every one unit increase in the “Number of knowntreatment centres” scale, the odds of participants being Black/African decreased3.4 times. This indicates that awareness of where to access treatment issignificantly lower in Black/African communities compared to traditionallyColoured communities in the Cape Town metropole. As awareness of services isnot uniform across communities, it is important to design interventions thatrecognise these differences among HDCs and target community-specific needs.In contrast, no socio-demographic differences emerged for the other awarenessdimensions. Specifically, both Black/African and Coloured communities had lowlevels of awareness of when to seek help. According to key informants, personsfrom HDCs often recognised that a person needed help only when the substanceabuse had become relatively severe. This claim appears to be confirmed byfindings (from phase one) that greater levels of problem severity and need fortreatment were significantly associated with higher levels of awareness ofsubstance abuse treatment services. This hampers timely access to services, assubstance use disorders of greater severity often require inpatient services whichare relatively less available, more expensive, and have longer waiting lists thanlow intensity outpatient treatment services. Low levels of awareness of when toseek help thus may contribute to delays in accessing treatment. Factors underpinning awareness barriersFindings also reveal the important role that others play in increasing awarenessof when, where, and how to access substance abuse treatment. Morespecifically, findings from the quantitative phase of the study show that greaterawareness of substance abuse treatment services is strong associated withsignificant others suggesting the need for help as well as higher levels of genericsocial support and social support for abstinence and treatment. The vital role thatfamily members play in providing information about services (including whereand how to access help) and supporting treatment processes is alsocorroborated by findings from the qualitative phase of the study. It seems that111

informational support can improve awareness of where to seek services, whileemotional support can improve awareness of the need to seek treatment. Thistends to confirm findings from previous studies which suggest that the provisionof informational and emotional support by significant others may buffer againstpoor substance-related problem recognition by providing health information thatenables people to recognize the need for health care, may motivate treatmentseekingbehaviour, and may address awareness-related barriers by providingtreatment service information (Appel et al., 2004; Brown et al., 2004; Tucker etal., 2004). Based on these findings, we recommend that interventions to addressawareness barriers should provide information on the signs and symptoms ofsubstance use disorders, provide information on various treatment options, andhighlight the importance of social support for facilitating treatment-seekingbehaviour.Community and environmental factors also appear to contribute to awareness ofwhen and where to seek substance abuse treatment. More specifically, findingsfrom the quantitative phase of the study show that greater awareness ofsubstance abuse treatment services is strongly associated with lower levels ofrelative deprivation and less neighbourhood disadvantage. In other words,environments characterised by better access to basic services, moreinfrastructure, and less disadvantage seem to enable awareness of substanceabuse treatment services. This could be due to less disadvantagedneighbourhoods having better access to material and informational resources ontreatment for substance use disorders; including basic health, social welfare andtransport services.Another possible explanation could lie in the relationship between social supportand awareness. Neighbourhood disorder may have disruptive effects on socialsupport by eroding social networks (Schulz et al., 2006), with residents of sociallydisordered neighbourhoods finding it difficult to develop and maintain supportiveinterpersonal relationships (Silver et al., 2002). This may limit awareness ofsubstance abuse treatment services and consequently hamper access to112

services. Environmental factors thus seem to shape barriers to accessingsubstance abuse treatment, including awareness of services.6.2.2. Geographical accessibilityGeographical accessibility of treatment services is another strong predictor ofwhether persons from HDCS utilize substance abuse treatment. During thequantitative phase of the study, this factor was indicated by two variables:travelling time to treatment and distance to nearest treatment centre. These twovariables were strongly correlated with each other, suggesting that travelling timeto treatment may be a proxy indicator of distance to treatment services. Morespecifically, findings indicate that the odds of accessing treatment were greaterfor persons who reported less travelling time to the nearest treatment facility; withevery one unit increase on the “travelling time to treatment” scale resulting in aneleven-fold increase in the odds of not accessing treatment. In addition, longertravelling times to treatment were associated with more delays in accessingtreatment services. These findings suggest that geographical accessibilitybarriers are strong impediments to substance abuse treatment utilization amongHDCs. Socio-demographic differences on geographical accessibilityFindings suggest that female substance abusers from HDCs experience greaterbarriers relating to the geographical accessibility of treatment services comparedto their male counterparts. For example, for every one unit increase in the“Travelling time to treatment” scale, the odds of being female doubled. A possibleexplanation for this lies in the finding that female substance abusers havesignificantly lower incomes and higher levels of competing financial needs thantheir male counterparts. This may limit women’s ability to afford public transportto substance abuse treatment and may increase the time it takes for women totravel to treatment. This explanation is supported by the finding that affordabilitybarriers were strongly associated with travelling time to treatment. Findings fromthe international literature that geographical access barriers are particularly113

salient for low-income groups who have less access to private transportation(Allard, Tolman, & Rosen, 2003) also corroborate this claim.Similarly, findings suggest that persons from Black/African communities havesignificantly longer travelling times and distances to travel to treatment comparedto their Coloured counterparts. For instance, for every one unit increase in the“Distance to nearest treatment centre” scale, the odds of participants beingBlack/African increased by a multiplicative factor of 3.4. This suggests thatgeographical accessibility barriers are significantly higher in Black/Africancommunities than Coloured communities in the Cape Town metropole. Thesesocio-demographic differences highlight the need for interventions that addressgeographical accessibility barriers among women and Black/African persons withsubstance use disorders especially. Factors underpinning geographical access barriersPolitical and systemic factors appear to contribute to these geographicalaccessibility barriers. More specifically, findings from the qualitative phase of thestudy suggest that the state’s failure to assess the substance abuse treatmentneeds of HDCs and gaps in treatment service coverage has led to an unevendispersion of treatment resources; with Black/African communities beingparticularly underserved. This has resulted in persons from Black/Africancommunities having greater distances to travel to treatment than theircounterparts from other communities. This reveals one way in which the politicalcontext informs the dispersion of treatment resources and consequentlygeographical barriers to accessing care.Given these findings, a starting point for developing interventions that addressgeographical accessibility barriers would be a mapping of treatment need andexisting treatment services in the Cape Town metropole. Other innovative lowcostinterventions could include the use of mobile outpatient clinics located withinBlack/African communities. These mobile units would reduce both the distances114

equired to travel and the costs associated with travelling to treatment serviceslocated at permanent facilities.6.2.3. Availability of affordable treatmentThe availability of affordable treatment options also emerged as a significantpredictor of access to substance abuse treatment for people from HDCs. Duringthe quantitative phase of the study, the affordability of treatment services wasindicated by three variables: barriers relating to the affordability of treatment,monthly income, and competing financial needs. While only a weak effect wasfound for the former, stronger effects were found for the latter two variables. Forexample, individuals without competing financial needs were four times morelikely to access services than persons with competing financial needs. Thesefindings suggest that affordability considerations inform whether persons fromHDCS utilize substance abuse treatment services. Factors underpinning affordability barriersThe manner in which affordability considerations impact on access to substanceabuse treatment is revealed through findings from the qualitative phase of thestudy. In part, affordability barriers seem to be underpinned by contextual factors,such as the limited allocation of financial resources to the social welfare sectorresponsible for the provision of substance abuse treatment. While these limitedfinancial resources restrict the number of non-profit treatment facilities that areavailable; for non-profit treatment services that do exist, it also limits theircapacity to provide affordable (free or low-cost) services to clients from HDCs.This is partly due to the need for non-profit facilities to cross-subsidize freetreatment slots with paying clients, in order to remain financially sustainable.For substance abusers from HDCs, this limits the availability of substance abusetreatment by contributing to lengthy waiting periods for affordable treatmentservices. This is cause for concern as many substance abusers are ambivalentabout seeking treatment and may have little tolerance for waiting (Kaplan & Johri,2000). These lengthy waiting periods act as a barrier to treatment utilization by115

diminishing self-efficacy and motivation for treatment. Additional support for thisexplanation arises from findings (from the quantitative phase of the study) thataffordability barriers and competing financial needs are significantly associatedwith reductions in self-efficacy and motivation for treatment. Political decisionsregarding the allocation of resources to substance abuse treatment thus informthe organisation of substance abuse treatment resources (such as waitingperiods for treatment and the affordability of available treatment options) andconsequently substance abuse treatment utilization among HDCs. Socio-demographic differences on affordability of treatmentIn addition, female substance abusers from HDCs seem to have more barriersrelating to the affordability of treatment than their male counterparts. Forexample, substance abusers earning less than R500 per month were more thantwice as likely to be female than male. In addition, compared to males, the oddsof having competing financial needs tripled for female substance abusers. Thesefindings suggest that compared to men, women’s ability to afford substanceabuse treatment is significantly lower. Interventions that address barriers totreatment among women should therefore focus not only on the provision ofaffordable treatment options, but should also address factors that compete withwomen’s ability to pay for treatment, such as the provision of food and shelter fordependents.Interventions that enhance the provision of social support, particularly tangiblesupport provision (such as food, clothing or other basic necessities) for womenmay reduce the impact of competing financial priorities on substance abusetreatment utilization. The finding that higher levels of social support aresignificantly associated with fewer competing financial needs provides support forthis suggestion. Further support for this suggestion arises from previousresearch which has identified a lack of tangible support as an important barrier totreatment for substance abusers (Appel et al., 2004; Brown et al., 2004; Tuckeret al., 2004). Access to treatment could therefore be facilitated by the provisionof tangible support in the form of transport or economic assistance.116

Similarly, findings suggest that persons from Black/African communities havesignificantly more affordability concerns than their Coloured counterparts. Forinstance, substance abusers earning less than R500 per month were five timesmore likely to be Black African than Coloured. In addition, Black Africansubstance abusers reported significantly more barriers relating to the affordabilityof treatment than their Coloured counterparts. While the affordability of treatmentwas a concern for all persons from HDCs, these findings highlight the need forinterventions that specifically target barriers relating to affordability amongwomen and Black/African persons with substance use disorders.6.2.4. Negative perceptions of treatmentAnother strong predictor of access to substance abuse treatment for HDCs iscommunity perceptions about existing substance abuse treatment services. Thisattitudinal-belief factor was indicated by the following variables: negativeperceptions of treatment effectiveness, concerns about treatment (i.e. whathappens within treatment facilities) and negative beliefs about the accessibility oftreatment.While only a weak effect was found for the former two variables, communityperceptions about the accessibility of treatment appears to have a strong effecton access to substance abuse treatment. For example, a one unit increase in the“community beliefs about access to treatment scale” was associated with a sixfoldincrease in the odds of not accessing treatment. In addition, increases in thisscale were associated with more delays in accessing treatment services. Whenconsidered together, these findings suggest that as negative beliefs about theaccessibility and availability of substance abuse treatment services increase,substance abusers are less disposed to seek and utilize these services. Factors underpinning negative perceptions of treatmentA possible reason for the relationship between realised access and negativeperceptions of treatment services may lie in the significant association between117

self-efficacy and negative perceptions about access to treatment. This studyfound that increases in the extent to which access to treatment services isnegatively perceived are associated with reductions in self-efficacy. Perceptionsthat existing treatment services are relatively inaccessible may result insubstance abusers having less confidence in their ability (i.e. self-efficacy) toaccess treatment; which may hamper treatment-seeking behaviour. The role ofself-efficacy in facilitating treatment-seeking behaviour has been welldocumentedby previous research (Appel et al., 2004).Findings (from the qualitative phase of the study) suggest that community beliefsthat treatment is inaccessible seem to relate to the accessibility of effectivetreatment services and appear to be underpinned by a limited awareness of whatconstitutes appropriate and effective treatment (an enabling factor). Morespecifically, HDCs tend to believe that only inpatient/residential substance abusetreatment services of a lengthy duration are effective - despite evidence to thecontrary (NIDA, 2000). These beliefs contribute to the perception that there are“no effective services available” and consequently hamper treatment utilizationas communities do not see the value of using existing treatment services whichare often outpatient programmes of limited duration. These claims are supportedby findings from international research which identified concerns about privacyand confidentiality in treatment and beliefs that treatment would be ineffective asconditions that interfered with linkage to substance abuse treatment (Appel et al.,2004; Grant, 1997; Simpson & Tucker, 2002; Tucker et al., 2004).In addition, findings from both phases of the study suggest that social supportand stigma contribute to negative perceptions about access to treatment; withthese variables being significant predictors of negative perceptions about accessto treatment. More specifically, low levels of social support and higher levels ofstigma towards substance abusers may contribute to views that treatment isinaccessible for persons from HDCs. These low levels of social support may beunderpinned by HDCs’ desire to transfer responsibility for supporting thesubstance abuser to the treatment system. This attempt to “transfer118

esponsibility” may arise from (i) limited awareness of the role that communitiescan play in facilitating access to treatment and positive treatment outcomes and(ii) from limited capacity to provide a supportive community environment.Interventions that address these negative perceptions as a means of improvingtreatment utilization should focus not only on addressing these perceptionsdirectly, but also focus on factors that contribute to these perceptions. Forinstance, interventions could attempt to (i) increase awareness of the value ofcreating a drug-free community environment that is supportive of abstinence and(ii) improve social capital and community capacity so that environments can beprovided. These interventions would enhance social support for and reducestigma towards substance abuse treatment-seeking behaviour in HDCs. Socio-demographic differencesSubstance abusers from traditionally Coloured communities seem to have morenegative perceptions about treatment than their Black/African counterparts. Forexample, a one unit increase in the “Community views about access totreatment” scale resulted in the odds of respondents being Coloured increasingmore than eight-fold. In addition, Coloured respondents reported significantlyhigher levels of “treatment concerns” and more negative beliefs about theeffectiveness of existing treatment services than their Black/African counterparts.These findings suggest that compared to Black/African respondents, Colouredrespondents hold more negative views about access to and availability oftreatment facilities, are more concerned about what happens in treatment, andare more likely to believe that treatment is ineffective.These findings highlight the need for interventions that target negative beliefsabout treatment and the availability of services among Coloured persons,specifically. Given these negative beliefs and concerns about treatment, it is notsurprising that many respondents do not attempt to access treatment.119

6.3. TREATMENT SYSTEM FACTORS ASSOCIATED WITH ACCESS TOSUBSTANCE ABUSE TREATMENTAlthough treatment system factors were not examined during the quantitativephase of the study, these factors emerged as significantly associated withtreatment utilization during qualitative data analysis. Key informants highlightedthe way in which both organizational barriers and resource allocation within thetreatment system limit access to treatment in HDCs.6.3.1. Organisational barriers to accessing substance abuse treatmentFindings suggest that there are several organisational factors within thesubstance abuse treatment system that act as barriers to accessing treatment forpeople from HDCs. These barriers all relate to the process of accessing nonprofittreatment. One such barrier is the lack of a clear, structured referralpathway; with persons from HDCs often referred to several non-profit treatmentservices before they are able to obtain help. For persons from HDCs this oftendelays entry into the treatment system. Administrative requirements forobtaining a free or low-cost bed at a non-profit treatment facility also delay theprocess of accessing treatment. In order to access affordable treatmentservices, persons from HDCs often need reports from social workers and healthprofessionals that document their need for treatment, their levels of motivation,and their medical and psychiatric history. Given that many of the agenciesresponsible for collating these reports have high caseloads and staff shortages,these administrative requirements often take several weeks to complete.Complex eligibility requirements (such as the need for adequate levels ofmotivation and the need for detoxification to have occurred prior to admission)also delay entry into the treatment system for persons from HDCs. For example,many non-profit facilities do not admit clients into their treatment programmeunless they have completed a hospital-based detoxification programme.Although this eligibility criertia arises from facilities’ lack of capacity to providedetoxification services, an unintended consequence is that treatment entry isoften delayed due to the limited availability of detoxification services in state120

hospitals. These findings are in keeping with prior research which also reportsthat complex programme admission and eligibility criteria may hamper access tosubstance abuse treatment (Appel et al., 2004; Hser et al., 1998).Taken together, these barriers contribute to delays in accessing care, indicatedby lengthy waiting periods for affordable treatment slots. As mentionedpreviously, these waiting periods negatively affect access to treatment; withindividuals often abandoning attempts to access treatment services (Grant, 1997;Hser et al., 1998; Tucker et al., 2004). In addition, delays in accessing care alsocontribute to perceptions that treatment services are relatively inaccessible forpeople from HDCs - a factor which has been shown to limit access to treatment.These findings highlight the need for interventions that streamline the processof accessing treatment for persons from HDCs. These interventions shouldattempt to reduce delays in accessing treatment, not only by increasing theavailability of affordable treatment services but also by increasing the availabilityof affordable detoxification and psychiatric services. In addition, interventionstargeting delays in accessing treatment should attempt to develop a structuredreferral algorithm for individuals from HDCs that includes patient placementcriteria. Finally, interventions should also attempt to reduce the administrativerequirements for admission to non-profit treatment facilities. This could beachieved by limiting the number of reports required prior to patient placement.6.3.2. Resource-related barriers within the treatment systemFindings also suggest that resource-related factors limit the extent to whichsubstance abuse treatment facilities can provide affordable services to clientsfrom HDCs. More specifically, the state’s limited allocation of financial resourcesto non-profit substance abuse treatment facilities restricts the capacity of thesefacilities to provide affordable treatment services, by contributing to staffshortages, jeopardizing the sustainability of treatment, and hampering skillsdevelopment within treatment facilities.121

This study found that limited resources hamper treatment facilities’ capacity toexpand their staff contingent to meet the increased demand for services inHDCs. This negatively impacts on access to care by restricting the availability ofservices. The increased demand for treatment services coupled with staffshortages have also restricted the breadth of services that can be offered toclients, with detoxification and aftercare services generally not being provided.This negatively impacts on access to care by contributing to delays in accessingservices (due to the need for detoxification services) and by fueling communityperceptions that effective treatment services are generally not available.Limited financial resources also affect the financial sustainability of non-profittreatment services. As mentioned previously, concerns about financialsustainability often result in TSPs limiting the number of free and low costtreatment slots. This further restricts the availability of affordable treatment andtherefore access to care for persons from HDCs. Related to this, as many nonprofittreatment facilities end up competing for scarce financial resources, it isdifficult for treatment service providers to pool their resources and maximize theircapacity to deliver services to HDCs.Limited financial resources also affect the capacity of non-profit treatmentservices to provide effective treatment services by restricting the skillsdevelopment of the treatment team. Low levels of remuneration for treatmentstaff often lead to high levels of staff turnover, with treatment facilities strugglingto retain experienced counsellors. This erodes the treatment team’s body ofskills and experience and impacts negatively on treatment capacity.The impact of financial constraints on the knowledge and skills set of treatmentstaff is most obvious among small, community-based organizations (CBOs)which have emerged to meet the growing demand for substance abuse treatmentin HDCs. In these sectors of the substance abuse treatment system, there arefew resources for staff training and development and few resources to invest inup-to-date treatment models. In addition, as these organizations are often122

unregistered and unfunded, they tend to employ “lay counsellors” or “recoveringaddicts” instead of costly professional staff. These addiction counselors areoften only qualified by experience and have limited knowledge of evidence-basedpractice and few counselling skills. This is cause for concern, as many of theseCBOs engage in ineffective (and sometimes punitive) approaches to treatment.This hampers treatment service utilization among HDCs by contributing tocommunity perceptions that effective services are not available.These findings suggest that interventions to improve access to effective,affordable services for people from HDCs should also focus on capacity issueswithin the non-profit substance abuse treatment sector. Treatment serviceproviders and community groups should mobilise and advocate for increasedfunding for both new and existing non-profit treatment facilities. However, theallocation of increased financial resources to TSPs should be contingent onthese facilities providing evidence-based treatment services by appropriatelyqualified staff. Funding should also be earmarked for capacity developmentinitiatives within CBOs. These initiatives may include providing addictionscounsellors with counselling skills that lead to accreditation by a professionalbody as well as ongoing supervision by professionally trained staff. The statemay also wish to consider introducing tighter regulations regarding theregistration of treatment facilities including the requirement that facilities onlyemploy staff with some form of counselling qualification. Funding also needs tobe allocated to the development and management of a professional body thataccredits and regulates both professionals and addiction counsellors working inthe substance abuse treatment field. International guidelines that exist for theaccreditation of addiction counsellors may serve as a useful framework for similarinitiatives in South Africa. Such interventions would go some distance towardsboth improving capacity within treatment services and addressing communityperceptions that existing treatment services are ineffective.123

6.4. RECOMMENDATIONSBased on study findings, a number of recommendations for interventions thataddress barriers to accessing substance abuse treatment services within HDCscan be made. Some of these recommendations are described below:6.4.1. Recommendations for interventions that address awareness-relatedbarriersBased on the finding that awareness of when and where to seek help is a strongpredictor of substance abuse treatment utilization, we make severalrecommendations for improving awareness of existing substance abusetreatment services:• Community-based programmes to improve access to substance abusetreatment within HDCs should focus on increasing community awarenessof existing resources for substance abuse treatment and related services.o These awareness programmes should be multi-faceted and shouldinclude information on where to go for help, when to go for help(including information on how to recognise when help is needed fora substance use disorder), and how to access help (that is,information on the process of accessing detoxification andtreatment services for substance use disorders).• Findings suggest that awareness of where to access treatment issignificantly lower in Black/African communities compared to traditionallyColoured communities in the Cape Town metropole. As awareness ofservices is not uniform across communities, it is important to designinterventions that recognise these differences among HDCs and targetcommunity-specific needs.• Findings also reveal the important role that others play in increasingawareness of when, where, and how to access substance abusetreatment. Interventions to improve awareness of substance abuse124

treatment should attempt to enhance social support for treatment withinfamilies and communities. Families and concerned community membersshould be provided with and encouraged to share information relating tothe signs and symptoms of substance use disorders and treatment optionswith individuals who have substance use disorders.• Findings also point to the impact of community and environmental factorson awareness of when and where to seek substance abuse treatment. Asenvironments characterised by better access to basic services, moreinfrastructure, and less disadvantage seem to enable awareness ofsubstance abuse treatment services, interventions should:o Focus on providing more informational and tangible support interms of resource materials to more disadvantaged and deprivedneighbourhoods.o Attempt to strengthen positive social networks in neighbourhoodscharacterised by high levels of disorder and disruption. Thesesupportive networks can act as an informational resource foraccessing substance abuse treatment services.6.4.2. Recommendations for interventions that address geographicalaccessibility barriersBased on the finding that the geographical accessibility of treatment services is astrong predictor of whether persons from HDCS utilize substance abusetreatment, we make several recommendations for improving the accessibility ofexisting services:• Given that the state’s failure to assess the substance abuse treatmentneeds of HDCs and gaps in treatment service coverage has led to anuneven dispersion of treatment resources; a starting point for developinginterventions that address geographical accessibility barriers would be amapping of treatment need and existing treatment services in the CapeTown metropole.125

• As findings suggest that female substance abusers from HDCs experiencegreater barriers relating to the geographical accessibility of treatmentservices than males, interventions to reduce distance to nearest treatmentcentre and lengthy travelling times to treatment should focus especially onpoor women.o These interventions should address the underlying factors thatcontribute to this gender difference such as women having morecompeting financial needs, lower incomes and more affordabilitybarriers. These income issues impact on women’s ability to affordpublic transport to treatment and leads to more difficult commutes.o Interventions should consider providing women with vouchers forpublic transport to treatment facilitieso As an alternative, treatment facilities may wish to considertransporting female clients to and from the facility in order toaddress this barrier to treatment engagement.• Findings also suggest that geographical accessibility barriers aresignificantly higher in Black/African communities than Colouredcommunities in the Cape Town metropole. These socio-demographicdifferences highlight the need for interventions that target geographicalaccessibility barriers amongst women and Black/African persons withsubstance use disorders specifically.• Innovative low-cost, geographically accessible interventions could includethe use of mobile outpatient clinics located within Black/Africancommunities.o These clinics could be moved within and between communities ona regular basis, and as such would reduce both the distancesrequired to travel and the costs associated with travelling totreatment services located at permanent facilities.126

6.4.3. Recommendations for interventions that address affordabilitybarriersBased on the study’s findings, we also make recommendations for interventionsthat target the availability of affordable treatment options for people from HDCs.This is important as affordability considerations seem to inform whether personsfrom HDCS utilize substance abuse treatment services. More specifically, thefollowing recommendations are made:• The availability of affordable treatment options, including the number offree or low-cost treatment slots, needs to increase for people from HDCsin the Cape Town metropole.• In addition, interventions that address affordability concerns as a means ofimproving treatment utilization should focus not only on addressing theseconcerns directly, but also on factors that contribute to affordabilitybarriers, such as the limited allocation of financial resources to the socialwelfare sector responsible for the provision of substance abuse treatment.The increased allocation of financial resources will allow facilities toexpand their services to meet the growing demand for treatment in HDCs.• Findings suggest that female substance abusers from HDCs have morebarriers relating to the affordability of treatment and more competingfinancial priorities than males. Interventions that address barriers totreatment among women should therefore address factors that competewith women’s ability to pay for treatment, such as the need to providedependent children and families with food and shelter.o Interventions that enhance the provision of tangible support (suchas providing food, clothing or other basic necessities such astransport or economic assistance) for women may reduce theimpact of competing financial priorities on substance abusetreatment utilization.127

• While the affordability of treatment was a concern for all persons fromHDCs, findings that persons from Black/African communities havesignificantly more affordability concerns than their Coloured counterpartshighlight the need for interventions that target barriers relating to theaffordability of substance abuse treatment among Black/African personsspecifically.6.4.4. Recommendations for interventions that address negativeperceptions about treatmentIn order to improve access to treatment among persons from HDCs,interventions should also target negative community perceptions about theaccessibility of treatment and the effectiveness of existing treatment services.More specifically, we recommend that:• Interventions that attempt to change negative perceptions about theaccessibility of treatment services should also attempt to enhance selfefficacyto seek treatment, due to the deleterious effect that negativebeliefs have on substance abusers’ confidence to use treatment servicesand the impact this has on access to services.• As findings suggest that beliefs that effective treatment is inaccessible areunderpinned by a limited awareness of what constitutes appropriate andeffective treatment, interventions that target these negative perceptionsshould attempt to enhance community awareness of what constituteseffective treatment. Such interventions should provide information onevidence-based treatment approaches, treatment approaches for whichthere is limited support, the process of treatment and recovery, and patientoutcomes that can be anticipated over the course of recovery.• In addition, interventions should focus not only on addressing theseperceptions directly, but also on factors that contribute to theseperceptions including limited social support for treatment-seeking128

ehaviour, the provision of a supportive community environment, andstigma toward treatment-seeking in HDCs.o Interventions are required that attempt to increase awareness ofthe importance of creating a drug-free community environment thatis supportive of abstinence and treatment-seeking for substancerelatedproblemso Interventions that attempt to improve social capital are alsorequired. These interventions should focus on improving social trusttowards external treatment service providers as this wouldencourage treatment utilization. In addition interventions shouldattempt to increase collective efficacy and community mobilisationaround drug availability and treatment resources within HDCS in anattempt to create an environment that is supportive of interventionefforts.• As findings show that substance abusers from traditionally Colouredcommunities seem to have more negative perceptions about treatmentthan their Black/African counterparts, interventions that target negativebeliefs about treatment and the availability of services should focus onColoured communities specifically.6.4.5. Recommendations for interventions within the treatment system:In order to improve access to treatment for people from HDCs, interventions arealso required at the level of the treatment system. Interventions targeting organisational barriers to accessOrganisational barriers to accessing treatment need to be addressed in the nonprofittreatment sector as these barriers often delay access to treatment. This iscause for concern as delays in accessing care often result in personsabandoning attempts to enter the treatment system and also contribute tocommunity perceptions that treatment is inaccessible.129

To address these barriers, we argue for interventions that streamline the processof accessing non-profit treatment services:• The availability of affordable substance abuse treatment services needs tobe drastically improved. Increased availability will reduce waiting times foraffordable treatment slots, and consequently delays in accessing care.• To reduce waiting times for non-profit treatment slots, the availability ofdetoxification and mental health services needs to be improved in thestate health sector.o The availability of these services can also be improved byincreasing the capacity of the non-profit substance abuse treatmentsector to provide these services.o This can be achieved by providing funding to agencies that is earmarkedfor this purpose. This funding should be used to developdetoxification services and to employ suitably trained and qualifiedmedical personnel to oversee these services.• Interventions targeting delays in accessing treatment should develop astructured referral pathway for clients from HDCs. This referral pathwayshould describe:o Stages in the referral process (e.g. initial assessment, referral fordetoxification, referral to outpatient/inpatient services, referral topsychiatric services, aftercare and follow-up)o Agencies responsible for activities that need to be conducted ateach referral stageo Activities that need to occur at each referral stage (e.g. medicalreports for admission into inpatient treatment)o Patient placement criteria for each step in the referral chain. Thiswould include guidelines specifying when the need fordetoxification, outpatient and/or inpatient services is indicated; andrecommended combinations of services for substance usedisorders of varying severity.130

• At the point of entry into the treatment system, all clients should beassigned to a case manager responsible for ensuring that clients are ableto access services at each step in the referral process, without fallingthrough the cracks.• Interventions targeting delays in accessing treatment should attempt toreduce the administrative and bureaucratic requirements for admissioninto non-profit treatment settings. Such interventions should attempt toreduce waiting periods for social work reports, the number of reportsrequired from professionals and complex eligibility requirements that arenot evidence-based. Interventions targeting resource-related barriersResource-related barriers (particularly capacity issues) need to be addressed inthe non-profit treatment sector as these contribute to perceptions that effectivetreatment services are not available as well as fears about treatment – both ofwhich have been shown to restrict treatment utilization. To address thesecapacity issues, we argue for:1. Increased funding for the non-profit substance abuse treatment sector• In order to expand capacity to provide treatment services to HDCs,treatment service providers and community groups should mobilize andadvocate both the state, private foundations, and donor agencies forincreased funding for both new and existing non-profit substance abusetreatment facilitieso The development of new facilities and the expansion of existingfacilities should be developed based on a proper assessment ofsubstance-related treatment needs in the Cape Town metropoleo A thorough substance-related treatment needs assessment inHDCs needs to be conducted in order to avoid duplication ofservices and to ensure adequate service coverage across themetropole.131

o To ensure objectivity, this needs analysis should be conducted byan organization or individuals without vested interests in specificcommunities or treatment-related organizations.• The allocation of increased funding for the provision of substance abusetreatment services should be contingent on the following:o A percentage of the funding should be ear-marked for free beds ortreatment slots for indigent clientso Funding should only be allocated to facilities/organizations thatcomply with state regulations regarding substance abuse treatmentfacilities (see below), including minimum norms and standards fortreatment services.o Funding should only be allocated to facilities/organizations thatemploy appropriately qualified staffo Funding allocation should be guided by the extent to whichtreatment facilities use evidence-based treatment models andtreatment outcomes• Increased funding also needs to be allocated to capacity developmentinitiatives for CBOs and other treatment service providers who areunregistered and/or employ unqualified “addiction counsellors”, and/or donot yet meet current standards governing treatment service provision.Funding for capacity development initiatives should be contingent on thefollowing:o Capacity-development activities should only be provided by suitablyqualified individualso All training courses should by accredited with the HealthProfessions Council and provide attendees with continuousprofessional development pointso Training courses should also be accredited with SAQA132

o For nonprofessional “addictions counsellors”, training initiativesshould include a practical component, supervision by anexperienced professional, and should lead towards a recognizedqualificationo All capacity development initiatives should be monitored andevaluated in terms of their impact on treatment practice.• Funding should also be ear-marked for other capacity developmentinitiatives including the development of a national training framework forsubstance use disorders that outlines the skills development of health andsocial work professionals providing substance-related interventionservices. This framework would include a:o Critical review of the training and continued professionaldevelopment of health and social work professionals in themanagement of patients with substance abuse problems.o Overview of state social workers’ current capacity developmentneeds with regards to substance use disorders. These wouldinclude an assessment of current assessment, early interventionand referral skills. In addition, it should include specificrecommendations on how to address potential skills deficits.2. Tighter regulation of treatment facilities and individuals providing“addiction counseling” services by the state• The state should introduce tighter regulation for all treatment facilities(whether they provide inpatient or outpatient services). These regulationsshould ensure that service providers are compliant with South Africanlegislation governing the provision of health and social services, humanrights, and occupational health and safety.• The state should ensure that all treatment facilities (whether providinginpatient or outpatient services) care) are registered with the Departmentof Social Development as a substance abuse treatment facility. This133

egistration process should gather information on the following aspects ofthe programme: philosophy, goals and objectives of the treatmentprogramme; admission procedures, including duration of treatment;treatment models and activities; discharge policies; follow-up policies; aswell as information about the organizational structure of the programme(including management policies and programme staffing)• The state should ensure that no clients receive services at facilities thatare unregistered, until registration at these facilities has been approved.• As part of the registration process, the state should ensure that theorganisation employs competent individuals as part of their treatmentteam.o Should these individuals have professional qualifications, theyshould be registered and of good standing with their professionalbodies, such as the Health Professions Council and or the SocialWorkers Council.o “Addiction counsellors” who are not registered with the SouthAfrican Health Professions or other relevant Councils, should betrained, accredited and work under the supervision of professionalstaff.o Registration with international bodies governing “addictioncounsellors” in the UK, USA or elsewhere does not automaticallyafford the counsellor South African registration.o “Counsellors” and registered professionals who have had their ownsubstance abuse problems should follow the guidelines set byinternational agencies regarding minimum periods of uninterruptedsobriety. These periods range between two and five years.• The state should allocate funding and support for the development andmaintenance of a South African national body for the registration, trainingand continuing professional development, and regulation of “addiction134

counsellors” and other professionals working in the substance abusetreatment field. This body would also be responsible for the certification of“addiction counsellors.”o Such a body should be staffed by competent individuals withsuitable counseling qualifications and adequate experience in thesubstance abuse treatment fieldo This Board should have statutory powers and should be guided byevidence-based practice and ethical principles.• All staff should remain current in their knowledge and training by attendingcourses and training workshops. This should be a requirement of ongoingregistration and accreditation.135

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