Suchergebnisse

Purpose. To assess tobacco screening and counseling in student health clinics, including facilitators, barriers, and associations with campus- and state-level variables. Design. We conducted a mixed-methods study with an online survey and qualitative interviews. Setting. Study setting was student health clinics on college campuses. Subjects. Subjects included 71 clinic directors or designees from 10 Southeastern states (quantitative survey) and 8 directors or designees from 4 Southeastern states (qualitative interviews). Measures. Quantitative measures included demographics, screening and counseling practices, clinic-level supports for such practices, perceptions of tobacco on campus, institution size, public/private status, state tobacco farming revenue, and state tobacco control funding. Qualitative measures included barriers and facilitators of tobacco screening and counseling practices. Analysis. Logistic and linear regression models assessed correlates of screening and counseling. Qualitative data were analyzed using multistage interpretive thematic analysis. Results. A total of 55% of online survey respondents reported that their clinics screen for tobacco at every visit, whereas 80% reported their clinics offer counseling and pharmacotherapy. Barriers included lack of the following: time with patients, relevance to chief complaint, student self-identification as a tobacco user, access to pharmacotherapy, and interest in quitting among smokers. In multivariable models, more efforts to reduce tobacco use, student enrollment, and state-level cash receipts for tobacco were positively associated with clinic-level supports. Conclusion. This study highlights missed opportunities for screening. Although reports of counseling were higher, providers identified many barriers.

Random digit dialing (RDD) telephone sampling, although experiencing declining response rates, remains one of the most accurate and cost-effective data collection methods for generating national population-based estimates. Such methods, however, are inefficient when sampling hard-to-reach populations because the costs of recruiting sufficient sample sizes to produce reliable estimates tend to be cost prohibitive. The authors implemented a novel respondent-driven sampling (RDS) approach to oversample cigarette smokers and lesbian, gay, bisexual, and transgender (LGBT) people. The new methodology selects RDS referrals or seeds from a probability-based RDD sampling frame and treats the social networks as clusters in the weighting and analysis, thus eliminating the intricate assumptions of RDS. The authors refer to this approach as RDD+RDS. In 2016 and 2017, a telephone survey was conducted on tobacco-related topics with a national sample of 4,208 U.S. adults, as well as 756 referral-based respondents. The RDD+RDS estimates were comparable with stand-alone RDD estimates, suggesting that the addition of RDS responses from social networks improved the precision of the estimates without introducing significant bias. The authors also conducted an experiment to determine whether the number of recruits would vary on the basis of how the RDS recruitment question specified the recruitment population (closeness of relationship, time since last contact, and LGBT vs. tobacco user), and significant differences were found in the number of referrals provided on the basis of question wording. The RDD+RDS sampling approach, as an adaptation of standard RDD methodology, is a practical tool for survey methodologists that provides an efficient strategy for oversampling rare or elusive populations.