Integration of early identification and brief intervention in frontline health services: the case of Quebec
Bibliographic record
Abstract
In 2006, the Quebec provincial government committed itself to developing capacity for evidence-based alcohol and other drug screening and brief intervention (SBI) in frontline health-service delivery settings. Two studies were conducted prior to province-wide deployment to inform decision makers as to possible implementation challenges. Study 1 evaluated the efficacy of implementing a model of SBI, adapted from the World Health Organization, in three frontline public health services. Sixty-two clinicians were trained in systematic detection of substance use and brief motivational intervention. Chart review of new admissions (N = 453) prior and following training assessed clinician conformity to SBI guidelines. Forty percent of patients endorsed at least one item on the four-question CAGE-AID (Cut Down, Annoyed, Guilty, Eye Opener screen Adapted to Include Drugs). Systematic screening among new admissions peaked at 70% and decreased to pre-training levels seven months after training. However, more than half of all new patients were assessed with validated questionnaires rather than informal questioning. Implementation of motivational interviewing techniques led to modest changes in clinician interventions. A second qualitative study was conducted to document possible organizational barriers to SBI implementation. Interviews were conducted with 24 clinicians and program administrators from frontline services of the six main health regions of Quebec province. Choice of vocabulary used in public policy documents and program material and sequence of delivery of services created confusion among clinicians as to what constituted alcohol and other drug SBI. Many resources developed for other SBI health programs in these frontline services seemed to be transferable to alcohol and drug SBI. Lessons learned were as follows: complexity in the SBI program is inversely related to the subsequent integrity of program deployment; clarity as to what constitutes SBI is paramount; and integration of parallel competencies/related programs could facilitate deployment of alcohol and other drug SBI.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".