The reality of at risk mental state services: a response to recent criticisms
Bibliographic record
Abstract
BACKGROUND: In the 1990s criteria were developed to detect individuals at high and imminent risk of developing a psychotic disorder. These are known as the at risk mental state, ultra high risk or clinical high risk criteria. Individuals meeting these criteria are symptomatic and help-seeking. Services for such individuals are now found worldwide. Recently Psychological Medicine published two articles that criticise these services and suggest that they should be dismantled or restructured. One paper also provides recommendations on how ARMS services should be operate. METHODS: In this paper we draw on the existing literature in the field and present the perspective of some ARMS clinicians and researchers. RESULTS: Many of the critics' arguments are refuted. Most of the recommendations included in the Moritz et al. paper are already occurring. CONCLUSIONS: ARMS services provide management of current problems, treatment to reduce risk of onset of psychotic disorder and monitoring of mental state, including attenuated psychotic symptoms. These symptoms are associated with a range of poor outcomes. It is important to assess them and track their trajectory over time. A new approach to detection of ARMS individuals can be considered that harnesses broad youth mental health services, such as headspace in Australia, Jigsaw in Ireland and ACCESS Open Minds in Canada. Attention should also be paid to the physical health of ARMS individuals. Far from needing to be dismantled we feel that the ARMS approach has much to offer to improve the health of young people.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".