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

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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
4.4.4.4. 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
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Access to substance abuse treatment
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CONTENTSINTRODUCTION ..............
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5.4. SUMMARY.......................
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al., 2004; Reddy et al., 2003; Shis
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1.3. IS ACCESS TO SUBSTANCE ABUSE T
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1.4.2. Racial disparities in the ne
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illegally and are unregulated by th
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CONCEPTUAL MODELThis study’s conc
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presenting problems and ability to
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need for services is the most immed
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This study focuses specifically on
Page 23 and 24: METHOD3.1. STUDY AIMS & OBJECTIVESA
Page 25 and 26: the researcher to explore possible
Page 27 and 28: esidential areas from each of the s
Page 29 and 30: 3.3.2.4. Data collection: controlsF
Page 31 and 32: o Problem recognition, Desire for h
Page 33 and 34: Table 1.Domains and measures compri
Page 35 and 36: The 19-item MOS-SSS measures functi
Page 37 and 38: information on the accessibility of
Page 39 and 40: RESULTS: PHASE ONE4.1. VARIABLES AS
Page 41 and 42: efficacy to stop using drugs for mo
Page 43 and 44: (Table 6). Effect sizes were large
Page 45 and 46: were 2.4 times more likely to not a
Page 47 and 48: esteem scales (Table 9). Stigma als
Page 49 and 50: Table 10.Logistic regression coeffi
Page 51 and 52: 4.2.2. Model 2: Predisposing variab
Page 53 and 54: poverty scale, and the variable “
Page 55 and 56: of the model increased significantl
Page 57 and 58: controls had greater self-efficacy
Page 59 and 60: and R1000 per month than their fema
Page 61 and 62: subjects earning less than R500 per
Page 63 and 64: and race (Table 16). This indicates
Page 65 and 66: were 3 times more likely to earn le
Page 67 and 68: (which are higher for Black/African
Page 69 and 70: substance use or remain abstinent d
Page 71 and 72: monetary needs rise, subjects repor
Page 73: with improved awareness of services
Page 77 and 78: • In historically disadvantaged c
Page 79 and 80: RESULTS: PHASE TWODuring qualitativ
Page 81 and 82: 5.1.1.3. Government’s responses t
Page 83 and 84: “Part of the government's agenda
Page 85 and 86: putting extra strain and pressure o
Page 87 and 88: The impact of availability and affo
Page 89 and 90: availability of affordable services
Page 91 and 92: completed a hospital-based detoxifi
Page 93 and 94: “I have thirty beds that are unus
Page 95 and 96: “I don't see it amongst the bona
Page 97 and 98: going to be a good day. So, yes it
Page 99 and 100: in the fourth week they relapse, it
Page 101 and 102: esponses to treatment, in part, are
Page 103 and 104: • Awareness of appropriate treatm
Page 105 and 106: This perception is prevalent in Col
Page 107 and 108: substance abuse problem - without a
Page 109 and 110: o These community influences are lo
Page 111 and 112: 6.2.1. Awareness of substance abuse
Page 113 and 114: informational support can improve a
Page 115 and 116: salient for low-income groups who h
Page 117 and 118: diminishing self-efficacy and motiv
Page 119 and 120: self-efficacy and negative percepti
Page 121 and 122: 6.3. TREATMENT SYSTEM FACTORS ASSOC
Page 123 and 124: This study found that limited resou
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6.4. RECOMMENDATIONSBased on study
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• As findings suggest that female
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• While the affordability of trea
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To address these barriers, we argue
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o To ensure objectivity, this needs
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egistration process should gather i
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REFERENCESAday, L.A., & Awe, W.C. (
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First, MB; Spitzer, RL; Gibbon, M;
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Myers, B., & Parry, C.D.H. (2005).
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Ross, M.W., Williams, M.L., Timpson
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