Stigma related to screening, brief intervention, and referral intervention for behavioral health risk factors in healthcare settings: A systematic review
Bibliographic record
Abstract
Introduction This systematic review aimed to synthesize existing studies on stigma (patient or provider’s perspective) related to screening, brief intervention, and referral (SBIR) for tobacco use, alcohol use, and insufficient physical activity Methods We conducted a systematic review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). We systematically searched articles in MEDLINE, CINAHL, EMBASE, and Web of Science databases using predetermined keywords. We reviewed both the title/abstract and full text using an a priori set of inclusion and exclusion criteria to identify the eligible studies. We appraised study quality, extracted data, and summarized the characteristics of intervention design and study findings from the included studies. Results No published studies were found pertaining to SBIR related to stigma for tobacco use or insufficient physical activity. Five studies were included in the review; all focused on SBIR-related stigma for alcohol use. The studies reported that patients perceive stigma in accessing treatment for alcohol use in healthcare settings. Our review identified that patients who consume alcohol fear being judged or stigmatized by their provider, which may lead patients to provide dishonest answers and hide their alcohol use status. We identified that patients are concerned about the confidentiality of the information collected on alcohol use and its impacts on their employment and housing. Conclusions Patients’ fear of being judged or stigmatized prevents them from getting treatment for alcohol use and reduces providers’ ability to engage and support patients. More studies are needed to explore stigma related to SBIR for risk factors (including tobacco use and physical activity) using standardized stigma measurement tools.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.084 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.012 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".