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Standardized screening, brief intervention, and referral to treatment (SBIRT) is effective when used by health care professionals to assess, educate, and intervene to address risky alcohol use. To accelerate SBIRT training within academic settings, the Substance Abuse and Mental Health Services Administration funded implementation of its SBIRT curriculum to promote its use by future health care professionals. We report on how SBIRT content was implemented within nursing, social work, psychology, and family medicine residency programs at a state university. The reach, effectiveness, adoption, implementation, and maintenance (RE-AIM) evaluation framework was used to compare delivery of SBIRT curriculum across health professions. Survey data measured changes in student knowledge, confidence, and responsibility to use SBIRT for alcohol and drugs, pre- and post-SBIRT training. Twelve months postgraduation follow-up surveys examined maintenance of outcomes and SBIRT use in practice. Observational data explored fidelity and adaptations made to curriculum content and delivery logistics. Results indicated that instructor adoption, fidelity, and format varied across health professional training programs, with adaptations made to improve fit, role alignment, and cultural relevance. Despite variation in curriculum delivery, students demonstrated significant gains in knowledge and confidence, ( p < .001). Key implementation and maintenance challenges included time constraints, instructor buy-in, competing accreditation requirements, and costs for using the university simulation laboratory to practice SBIRT. Strengths supporting maintenance included flexibility to adapt curriculum, department champions, and electronic resources to support curriculum delivery. Results suggest that adaptations maximizing the feasibility and fit of SBIRT within existing courses enhanced its adoption and maintenance potential without sacrificing effectiveness.

Background. Efforts to predict success in chronic disease management programs have been generally unsuccessful. Objective. To identify patient subgroups associated with success at each of 6 steps in a diabetes self-management (DSM) program. Design. Using data from a randomized trial, recursive partitioning with signal detection analysis was used to identify subgroups associated with 6 sequential steps of program success: agreement to participate, completion of baseline, initial website engagement, 4-month behavior change, later engagement, and longer-term maintenance. Setting. The study was conducted in 5 primary care clinics within Kaiser Permanente Colorado. Patients. Different numbers of patients participated in each step, including 2076, 544, 270, 219, 127, and 89. All measures available were used to address success at each step. Intervention. Participants were randomized to receive either enhanced usual care or 1 of 2 Internet-based DSM programs: 1) self-administered, computer-assisted self-management and 2) the self-administered program with the addition of enhanced social support. Measurements. Two sets of potential predictor variables and 6 dichotomous outcomes were created. Results. Signal detection analysis differentiated successful and unsuccessful subgroups at all but the final step. Different patient subgroups were associated with success at these different steps. Demographic factors (education, ethnicity, income) were associated with initial participation but not with later steps, and the converse was true of health behavior variables. Limitations. Analyses were limited to one setting, and the sample sizes for some of the steps were modest. Conclusions. Signal detection and recursive partitioning methods may be useful for identifying subgroups that are more or less successful at different steps of intervention and may aid in understanding variability in outcomes.

Objective: There is a need for practical, efficient and broad-reaching diabetes self-management interventions that can produce changes in lifestyle behaviours such as healthy eating and weight loss. The objective of this study was to evaluate such a computer-assisted intervention. Methods: Type 2 diabetes primary care patients ( n=335) from fee-for-service and health maintenance organization settings were randomized to social cognitive theory-based tailored self-management (TSM) or computer-aided enhanced usual care (UC). Intervention consisted of computer-assisted self-management assessment and feedback, tailored goal-setting, barrier identification, and problem-solving, followed by health counsellor interaction and follow-up calls. Outcomes were changes in dietary behaviours (fat and fruit/vegetable intake), haemoglobin A1c (HbA1c), lipids, weight, quality of life, and depression. Results: TSM patients reduced dietary fat intake and weight significantly more than UC patients at the 2-month follow-up. Among patients having elevated levels of HbA1c, lipids or depression at baseline, there were consistent directional trends favouring intervention, but these differences did not reach significance. The intervention proved feasible and was implemented successfully by a variety of staff. Conclusions: This relatively low-intensity intervention appealed to a large, generally representative sample of patients, was well implemented, and produced improvement in targeted behaviours. Implications of this practical clinical trial for dissemination are discussed.

PURPOSE this study reports on methods and strategies employed to increase participation rates in diabetes interventions and discusses the reach and representativeness of the Diabetes Priority Program. METHODS A passive mail-out procedure was used to contact patients of participating primary care physicians. Patients who did not return the refusal postcard were contacted. Several attempts were made to contact potential participants. Brochures, "wrong number" postcards, posters, and reports for clinic staff were strategies used to increase participation. RESULTS The recruitment process resulted in a participation rate of 83% among patients who were contacted and eligible. These participants appeared to be representative of both nonparticipants and persons with diabetes in Colorado. In contrast, a low percentage of primary care physicians, estimated at 3%, took part in the program despite efforts to make the program brief, nonintrusive, and compatible with usual care. CONCLUSIONS Recruitment is currently challenging and will become even more difficult with the privacy regulations that affect healthcare research and the public distrust of solicitations. To increase participation rates, it is important that the clinic staff promotes and supports the program, and that participant lists are accurate and adequate in size.