Bibliographic record
Abstract
Summary Routine use of Health of the Nation Outcome Scales (HoNOS) has not produced the anticipated benefits for people using mental health services. Four HoNOS-specific reasons for this are: low relevance to clinical decision-making; not reflecting service user priorities; being staff-rated; and having a focus on deficits. More generally, the imposition of a centrally chosen measure on the mental health system leads to a clash of cultures, since frontline workers do not need a standardised measure to treat individuals. A better approach might be to use research from the emerging academic discipline of implementation science to inform the routine use of a standardised measure that is chosen by the people who will use it and hence is more concordant with existing clinical processes. This is illustrated using a case study of successful implementation of the Camberwell Assessment of Need (CAN) in community mental health services across Ontario, Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.626 | 0.704 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.018 | 0.013 |
| Bibliometrics | 0.041 | 0.021 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.028 | 0.012 |
| Open science | 0.016 | 0.015 |
| Research integrity | 0.013 | 0.018 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".