Alcohol brief intervention delivered in UK community pharmacies: customers’ experiences
Bibliographic record
Abstract
Pharmacy-based alcohol brief intervention (BI) has the potential to identify risky drinkers in the general population, but the opinions of users regarding the service remain relatively unexplored. Alcohol BI was offered to customers by trained pharmacists (n = 29) at 28 London, UK, community pharmacies between February and July 2010. Customers requiring alcohol-use related medication and/or advice were targeted. The Alcohol Use Disorders Identification Test-Consumption (AUDIT-C), a drinking diary, and a readiness to change assessment were used by pharmacists to assess and provide appropriate feedback regarding alcohol use. Customers also received written information, including a UK Department of Health “Units and You” booklet. Following BI, customers were given a confidential service evaluation questionnaire to complete and return to the project team using a prepaid envelope. This invited responses to closed- and open-format questions regarding their initial reason for visiting the pharmacy, why they took up the BI service, and their levels of satisfaction with the service delivery and environment. Of the 134 customers who received a BI, 58% (n = 78) returned the questionnaire. Bringing a prescription for dispensing was the most common reason for the pharmacy visit (55%, n = 43). Wishing to find out about alcohol use and concerns for personal health were the two most reported reasons for taking up the service. Almost one-quarter of customers (n = 18) reported that they liked having increased their alcohol-related awareness, and 18% (n = 14) indicated that they liked the informative written information. The privacy (74%, n = 57), confidentiality (77%, n = 59), and quietness (70%, n = 54) of consulting rooms was rated as good, with 77% (n = 60) of customers reporting they would recommend this service to others. In line with past primary care BI studies, customers were generally positive about the experience of receiving BI in community pharmacies and would recommend it to others.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".