Enhancing alcohol screening and brief intervention among people receiving opioid agonist treatment: qualitative study in primary care
Bibliographic record
Abstract
Purpose Problem alcohol use (PAU) is common and associated with considerable adverse outcomes among patients receiving opioid agonist treatment (OAT). The purpose of this paper is to describe a qualitative feasibility assessment of a primary care-based complex intervention to promote screening and brief intervention for PAU, which also aims to examine acceptability and potential effectiveness. Design/methodology/approach Semi-structured interviews were conducted with 14 patients and eight general practitioners (GPs) who had been purposively sampled from practices that had participated in the feasibility study. The interviews were transcribed verbatim and analysed thematically. Findings Six key themes were identified. While all GPs found the intervention informative and feasible, most considered it challenging to incorporate into practice. Barriers included time constraints, and overlooking and underestimating PAU among this cohort of patients. However, the intervention was considered potentially deliverable and acceptable in practice. Patients reported that (in the absence of the intervention) their use of alcohol was rarely discussed with their GP, and were reticent to initiate conversations on their alcohol use for fear of having their methadone dose reduced. Research limitations/impelications Although a complex intervention to enhance alcohol screening and brief intervention among primary care patients attending for OAT is likely to be feasible and acceptable, time constraints and patients’ reticence to discuss alcohol as well as GPs underestimating patients’ alcohol problems is a barrier to consistent, regular and accurate screening by GPs. Future research by way of a definitive efficacy trial informed by the findings of this study and the Psychosocial INTerventions for Alcohol quantitative data is a priority. Originality/value To the best of the knowledge, this is the first qualitative study to examine the capability of primary care to address PAU among patients receiving OAT.
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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 | 0.015 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".