Electronic Screening and Brief Intervention for Unhealthy Alcohol use in Primary Care Waiting Rooms – a Pilot Project
Bibliographic record
Abstract
Background: In primary care, electronic self-administered screening and brief interventions for unhealthy alcohol may overcome some of the implementation barriers of face-to-face intervention. We developed an anonymous electronic self-administered screening brief intervention device for unhealthy alcohol use and assessed its feasibility and acceptability in primary care practice waiting rooms. Two modes of delivery were compared: with or without the presence of a research assistant (RA) to make patients aware of the device's presence and help users. Using the device was optional. Methods: The devices were placed in 10 participating primary care practices waiting rooms for 6 weeks, and were accessible on a voluntary basis. Number of appointments by each practice during the course of the study was recorded. Access to the electronic brief intervention was voluntary among those who screened positive. Screening and brief intervention rates and characteristics of users were compared across the modes of delivery. Results: During the study, there were 7270 appointments and 1511 individuals used the device (20.8%). Mean age of users was 45.3 (19.5), and 57.9% screened positive for unhealthy alcohol use. Of them, 53.8% accessed the brief intervention content. The presence of the RA had a major impact on the device's usage (59.6% vs 17.4% when absent). When the RA was present, participants were less likely to screen positive (49.4% vs 60.7%, P = 0.0003) but more likely to access the intervention (62.7% vs 51.4%, P = 0.009). Results from the satisfaction survey indicated that users found the device easy to use (93.5%), questions useful (89–95%) and 77.2% reported that their friends would be willing to use it. Conclusions: This pilot project indicates that the implementation of an electronic screening and brief intervention device for unhealthy alcohol is feasible and acceptable in primary care practices but that, without human support, its use is rather limited.
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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 | 0.011 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".