Predictors of treatment retention in a major methadone maintenance treatment program in Iran: a survival analysis

To identify correlates related to retention time of a cohort study of the opioid-dependent patients participating in the Methadone Maintenance Treatment [MMT] program offered by a major addiction treatment clinic in Tehran, Iran between April 2007 and March 2011. Several parametric Survival models assuming Weibull, Log-normal and Log-logistic distributions were compared to search for association between covariates and risk of relapse and dropping out of treatment among 198 patient participants. According to Akaike Information Criterion [AIC], Log-normal model had the best fitting. Estimates of this model indicated that increase in average methadone dosage was associated with longer retention time. Correlates associated with shorter retention time were suffering from mental disorders, using stimulant drugs, being poly-substance dependents and having prior treatments. Findings of this study provide support for giving more attention to patients who are poly-substance or stimulant-drug dependents, have non-substance psychiatric comorbidity and the ones with addiction treatment history. Independent of patient characteristics, retention improved as the dose of methadone increased

Stated time preferences for health: a systematic review and meta analysis of private and social discount rates

The present study aimed to provide better insight on methodological issues related to time preference studies, and to estimate private and social discount rates, using a rigorous systematic review and meta-analysis. We searched PubMed, EMBASE and Proquest databases in June 2013. All studies had estimated private and social time preference rates for health outcomes through stated preference approach, recognized eligible for inclusion. We conducted both fixed and random effect meta-analyses using mean discount rate and standard deviation of the included studies. I-square statistics was used for testing heterogeneity of the studies. Private and social discount rates were estimated separately via Stata11 software. Out of 44 screened full texts, 8 population-based empirical studies were included in qualitative synthesis. Reported time preference rates for own health were from 0.036 to 0.07 and for social health from 0.04 to 0.2. Private and social discount rates were estimated at 0.056 [95% CI: 0.038, 0.074] and 0.066 [95% CI: 0.064, 0.068], respectively. Considering the impact of time preference on healthy behaviors and because of timing issues, individual's time preference as a key determinant of policy making should be taken into account. Direct translation of elicited discount rates to the official discount rates has been remained questionable. Decisions about the proper discount rate for health context, may need a cross-party consensus among health economists and policy makers