Screening, brief intervention, and referral to treatment for tobacco consumption, alcohol misuse, and physical inactivity: an equity-informed rapid review
Bibliographic record
Abstract
OBJECTIVE: This rapid review systematically synthesizes evidence of the effectiveness of the Screening, Brief Intervention, and Referral (SBIR/T) approach for tobacco use, alcohol misuse, and physical inactivity. STUDY DESIGN: This was a rapid review. METHODS: We searched primary studies between 2012 and 2022 in seven electronic databases. The search strategy used concepts related to alcohol-related disorders, intoxication, cigarette, nicotine, physical activity, exercise, sedentary, screening, therapy, and referral. We reviewed both title/abstract and full-text using a priori set inclusion and exclusion criteria to identify the eligible studies. We appraised study quality, extracted data, and summarized the characteristics of the included studies. We applied health equity lenses in the synthesis. RESULTS: Of the 44 included studies, most focused on alcohol misuse. SBIR/T improved patients' attitudes toward alcohol behavior change, improved readiness and referral initiation for change, and effectively reduced alcohol consumption. Few studies pertained to smoking and physical inactivity. Most studies on smoking demonstrated effectiveness pertaining to patients' acceptance of referral recommendations, improved readiness and attempts to quitting smoking, and reduced or cessation of smoking. Findings were mixed about the effectiveness of SBIR/T in improving physical activity. Minimal studies exist on the impacts of SBIR/T for these three risk factors on healthcare resource use or costs. Studies considering diverse population characteristics in the design and effectiveness assessment of the SBIR/T intervention are lacking. CONCLUSIONS: More research on the impacts of SBIR/T on tobacco use, alcohol misuse, and physical inactivity is required to inform the planning and delivery of SBIR/T for general and disadvantaged populations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".