Search

Background Despite harmful drinking causing a significant burden on global health, there is a large treatment gap, especially in low- and middle-income countries. A major barrier to care is the lack of adequately skilled human resources to deliver contextually appropriate treatments. This paper describes the systematic process used to develop Counselling for Alcohol Problems ( CAP), a brief psychological treatment (PT) for delivery by lay counselors in routine primary care settings to men with harmful drinking in India. Methods CAP was developed using a methodology involving 3 sequential steps: (i) identifying potential treatment strategies; (ii) developing a theoretical framework for the treatment; and (iii) evaluating the acceptability and feasibility of the treatment. Results CAP is a 3-phase treatment delivered over 1 to 4 sessions based on a motivational interviewing ( MI) stance and involves the following strategies: assessment and personalized feedback, family engagement, drink refusal skills, skills to address drinking urges, problem-solving skills and handling difficult emotions, and relapse prevention and management. Data from a case series were used to inform several adaptations to enhance the acceptability of CAP to the recipients and feasibility of delivery by lay counselors of the treatment, for example expansion of the target group to include alcohol-dependent patients and the extension of the delivery settings to include home-based delivery. There was preliminary evidence of the effectiveness of CAP. Conclusions CAP is an acceptable brief PT for harmful drinking delivered by lay counselors in primary care whose effectiveness is currently being tested in a randomized controlled trial based in primary care in Goa, India. [ABSTRACT FROM AUTHOR]

ABSTRACT Aims Smoking cessation trials generally record information on daily smoking behavior, but base analyses on measures of smoking status at the end of treatment (EOT). We present an alternative approach that analyzes the entire sequence of daily smoking status observations. Methods We analyzed daily abstinence data from a smoking cessation trial, using two longitudinal logistic regression methods: a mixed-effects (ME) model and a generalized estimating equations (GEE) model. We compared results to a standard analysis that takes abstinence status at EOT as outcome. We evaluated time-varying covariates (smoking history and time-varying drug effect) in the longitudinal analysis and compared ME and GEE approaches. Results We observed some differences in the estimated treatment effect odds ratios across models, with narrower confidence intervals under the longitudinal models. GEE yields similar results to ME when only baseline factors appear in the model, but gives biased results when one includes time-varying covariates. The longitudinal models indicate that the quit probability declines and the drug effect varies over time. Both the previous day's smoking status and recent smoking history predict quit probability, independently of the drug effect. Conclusion When analysing outcomes of studies from smoking cessation interventions, longitudinal models with multiple outcome data points, rather than just end of treatment, can makes efficient use of the data and incorporate time-varying covariates. The generalized estimating equations approach should be avoided when using time-varying predictors. [ABSTRACT FROM AUTHOR]