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

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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
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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
Page 9 and 10: 1.3. IS ACCESS TO SUBSTANCE ABUSE T
Page 11 and 12: 1.4.2. Racial disparities in the ne
Page 13 and 14: illegally and are unregulated by th
Page 15 and 16: CONCEPTUAL MODELThis study’s conc
Page 17 and 18: presenting problems and ability to
Page 19 and 20: need for services is the most immed
Page 21 and 22: 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 R1000 per month than their fema
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 and 74: with improved awareness of services
Page 75 and 76: 4.4.4.4. Predictors of “community
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
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6.2.1. Awareness of substance abuse
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informational support can improve a
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salient for low-income groups who h
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diminishing self-efficacy and motiv
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self-efficacy and negative percepti
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6.3. TREATMENT SYSTEM FACTORS ASSOC
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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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