Key considerations for choosing a statistical method to deal with incomplete treatment adherence in pragmatic trials

Pragmatic trials offer practical means of obtaining real-world evidence to help improve decision-making in comparative effectiveness settings. Unfortunately, incomplete adherence is a common problem in pragmatic trials. The commonly used methods in randomized control trials often cannot handle the added complexity imposed by incomplete adherence, resulting in biased estimates. Several naive methods and advanced causal inference methods (e.g., inverse probability weighting and instrumental variable-based approaches) have been used in the literature to deal with incomplete adherence. Practitioners and applied researchers are often confused about which method to consider under a given setting. This current work is aimed to review commonly used statistical methods to deal with non-adherence along with their key assumptions, advantages, and limitations, with a particular focus on pragmatic trials. We have listed the applicable settings for these methods and provided a summary of available software. All methods were applied to two hypothetical datasets to demonstrate how these methods perform in a given scenario, along with the R codes. The key considerations include the type of intervention strategy (point treatment settings, where treatment is administered only once versus sustained treatment settings, where treatment has to be continued over time) and availability of data (e.g., the extent of measured or unmeasured covariates that are associated with adherence, dependent confounding impacted by past treatment, and potential violation of assumptions). This study will guide practitioners and applied researchers to use the appropriate statistical method to address incomplete adherence in pragmatic trial settings for both the point and sustained treatment strategies.

Individual and social factors associated with participation in treatment programs for drug users

Since only about one third of people who are dependent on drugs are in treatment, there is a need to promote both treatment entry and retention. Previous research has described the role of individual and social characteristics in drug user treatment participation, but little is known about the interaction of individual and social factors. Injecting and noninjecting drug users (2002-2004; N = 581) were recruited, as part of Self-Help in Eliminating Life-Threatening Diseases (SHIELD) study, in Baltimore, MD, and were administered a structured questionnaire. The mean age of participants was 43.6 years, out of which 41% were female, 50% had high school education, and 16% self-reported being HIV infected. Logistic regression analyses of interaction terms revealed that compared to those with no plans to stop and no friends encouraging them to enter treatment those who planned to cease drug use or whose friends encouraged treatment were more likely to attend a 12-step program. Furthermore, compared to those with no problems with drug use and no friends encouraging them to enter treatment those with greater perceived drug problem severity or with friends encouraging treatment were more likely to attend methadone maintenance, as were those who did not receive free drugs from others. The influence of friends may have a crucial modifying effect by getting into treatment less addicted individuals who have higher chances of successful recovery.