Stages of Change Assessments in Alcohol Problems: Agreement across Self– and Clinician–Reports
Bibliographic record
Abstract
A number of self-report scales and "algorithms" have been developed to measure stage of change in alcohol problems. These methods rely on client self-reports, but an alternative approach is to use clinician judgments. The purpose of this investigation was to compare approaches including a newly developed Readiness to Change Questionnaire - Clinician Version (RCQ-CV). Clients being assessed for alcohol treatment (N = 64) completed SOCRATES, the Readiness to Change Questionnaire (RCQ), a social desirability scale, and a stage of change algorithm. Clinicians completed the RCQ-CV and provided a simple assessment of stage of change. The agreement among the alternative methods was generally good with the continuous measures, including agreement between scales, between clients and clinicians, and between experienced clinicians and trainees. Agreement among categorical stage assignments was poor. The RCQ-CV shows promise as a clinical and research tool.
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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 | 0.053 | 0.101 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".