Canadian Schizophrenia Guidelines: Introduction and Guideline Development Process
Bibliographic record
Abstract
INTRODUCTION: The aim of the Canadian Schizophrenia Guidelines is to provide evidence-based recommendations for the treatment of schizophrenia and schizophrenia spectrum disorders. The target users are health care professionals. Recommendations are provided as guidance to physicians and patients, with the goal of improving the overall standard of care of individuals with schizophrenia. METHODS: The guidelines were developed using the ADAPTE process, a systematic approach and alternative to de novo guideline development, in which an existing guideline is customised to suit the local context. We assembled a multidisciplinary team of experts, patients, and family carers from across Canada with the goal of involving individuals with diverse areas of expertise and offering different perspectives. RESULTS: We identified 6 guidelines that were suitable for adaptation. Recommendations from each guideline were extracted and, based on content, were reviewed by the relevant working group. Each working group examined the evidence from which the recommendation was derived and the acceptability and applicability of the recommendation to the Canadian context. Working groups also made decisions on modifications to recommendations when language or terms differed between the source guideline and the Canadian context. Each working group presented selected recommendations to the guideline panel at an in-person consensus meeting. Once the consensus process was completed, each working group created a manuscript with the recommendations adapted from the included guidelines, with the rationale for each recommendation. CONCLUSIONS: The process yielded an up-to-date list of evidence-based recommendations that are relevant and applicable in 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 | 0.048 | 0.162 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.018 | 0.018 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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".