Psychiatric diagnosis: what the recovery movement can offer the DSM-5 revision process
Bibliographic record
Abstract
Many developments in the understanding of mental disorders are reflected in the ways in which the DSM has evolved through its different editions over the years. Within the context of the upcoming publishing of the DSM-5, and particularly in relation to people diagnosed with schizophrenia and psychosis, the purposes of the present paper are to: (a) briefly review the central developments of the DSM over time; (b) challenge the current role of the DSM as a classification manual in light of recent developments in psychiatric rehabilitation; (c) discuss the role of personal experience and subjectivity in the diagnostic process; and (d) offer suggestions as to how the DSM-5 can benefit from the recent tenets and findings of psychiatric rehabilitation. We claim that developments in the field of psychiatric rehabilitation, and its vision of recovery, do not yet find expression in the current DSM edition. We believe that it is important to update future versions of the manual with the findings and developments which have occurred in this field over the last several decades in order to improve diagnosis, treatment, and patient outcomes in mental health.
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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 | 0.090 | 0.144 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.004 | 0.023 |
| Scholarly communication | 0.010 | 0.025 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.010 | 0.021 |
| Insufficient payload (model declined to judge) | 0.006 | 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".