Implementation and Analysis of Respondent Driven Sampling: Lessons Learned from the Field

Those who engage in illegal or stigmatized behaviors, which put them at risk of HIV infection, are largely concentrated in urban centers. Owing to their illegal and/ or stigmatized behaviors, they are difficult to reach with public health surveillance and prevention programs. 1 These populations include illicit drug users, sex workers and men who have sex with men. Development and implementation of adequate prevention services targeting hidden populations requires data on risk behaviors and disease prevalence from non-biased samples. In the last two decades, a number of sampling methods have been used to collect risk behavior and disease prevalence data from highly at-risk populations and to direct survey participants to prevention services. These include venue-based time–space sampling, targeted sampling, and snowball sampling. Time–space (also called time–location or venue–day–time) and targeted sampling provide coverage limited to population members who are readily accessible; those who are missed may differ from those who are Bcaptured[. 2 Targeted sampling fares well when compared to other forms of convenienc

Process evaluation for complex interventions in primary care: understanding trials using the normalization process model

Background: the Normalization Process Model is a conceptual tool intended to assist in understanding the factors that affect implementation processes in clinical trials and other evaluations of complex interventions. It focuses on the ways that the implementation of complex interventions is shaped by problems of workability and integration.Method: in this paper the model is applied to two different complex trials: (i) the delivery of problem solving therapies for psychosocial distress, and (ii) the delivery of nurse-led clinics for heart failure treatment in primary care.Results: application of the model shows how process evaluations need to focus on more than the immediate contexts in which trial outcomes are generated. Problems relating to intervention workability and integration also need to be understood. The model may be used effectively to explain the implementation process in trials of complex interventions.Conclusion: the model invites evaluators to attend equally to considering how a complex intervention interacts with existing patterns of service organization, professional practice, and professional-patient interaction. The justification for this may be found in the abundance of reports of clinical effectiveness for interventions that have little hope of being implemented in real healthcare setting