Contingency management (CM) interventions are efficacious in treating cocaine abusing methadone patients, but few studies have examined the effect of age on treatment outcomes in this population. This study evaluated the impact of age on treatment outcomes in cocaine abusing methadone patients.
Data were analyzed from 189 patients enrolled in one of three randomized studies that evaluated the efficacy of CM versus standard care (SC) treatment.
Age was associated with some demographics and drug use characteristics including racial composition, education, and methadone dose. Primary drug abuse treatment outcomes did not vary across age groups, but CM had a greater benefit for engendering longer durations of abstinence in the middle/older and older age groups compared to the younger age groups. At the 6-month follow-up, submission of a cocaine positive urine sample was predicted by submission of a cocaine positive sample at intake, higher methadone doses, and assignment to SC rather than CM treatment.
As substance abusers are living longer, examination of the efficacy of pharmacological and psychosocial treatments specifically within older age groups may lead to a better understanding of subpopulations for whom enhanced treatments such as CM are warranted. (Am J Addict 2013;22:119-126).
"The primary independent variable of interest was reporting being forced to pay a bribe to police in the previous six months (i.e., participants were asked whether they had been stopped by law enforcement in the previous six months, and if so, whether they paid a bribe). Potential confounders previously identified in the literature included: age (Dürsteler-MacFarland et al., 2011; Weiss and Petry, 2013), gender (Kelly et al., 2011), any use of heroin (Mattick et al., 2009), cocaine (Castells et al., 2010; Weiss and Petry, 2013), or methamphetamine (including crystal methamphetamine; Shekarchizadeh et al., 2012), reported frequency of injection drug use (i.e., daily vs. non-daily/none; Amato et al., 2002; Ferri et al., 2010), follow-up visit (Kelly et al., 2011), self-perceived need for addiction treatment (none or some need vs. a great or urgent need), and a visit-by-bribe interaction term. This last variable was included because changes to discretionary policing practices may have evolved over the study period given the ongoing implementation of the drug policy reform (Syvertsen et al., 2010). "
[Show abstract][Hide abstract] ABSTRACT: Aims:
In 2009, Mexico passed legislation to decriminalize drug possession and improve access to addiction treatment. We undertook research to assess the implementation of the reform among a cohort of people who inject drugs (PWID) in Tijuana. This study specifically sought to determine whether discretionary policing practices like extortion impact access to methadone maintenance therapy (MMT) in Tijuana, a city characterized by high levels of drug-related harms.
Generalized estimating equation analyses were used to construct longitudinal confounding models to determine the association between paying a police bribe and MMT enrolment among PWID in Tijuana enrolled in a prospective cohort study. Outcome of interest was MMT enrolment in the past six months. Data on police interactions and MMT enrolment were also obtained.
Between October, 2011 and September, 2013, 637 participants provided 1825 observations, with 143 (7.8%) reports of MMT enrolment during the study period. In a final confounding model, recently reporting being forced to pay a bribe to police was significantly associated with an increased likelihood of accessing MMT (adjusted odds ratio=1.69, 95% confidence interval: 1.02-2.81, p=0.043). However, in 56 (39.2%) cases, MMT enrolment ceased within six months. The majority of participant responses cited the fact that MMT was too expensive (69.1%).
Levels of MMT access were low. PWID who experienced police extortion were more likely to access MMT at baseline, though this association decreased during the study period. Coupled with the costs of MMT, this may compromise MMT retention among PWID.
Drug and Alcohol Dependence 01/2015; 148. DOI:10.1016/j.drugalcdep.2015.01.011 · 3.42 Impact Factor
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