Early interventions for people with psychotic disorders
Bibliographic record
Abstract
Abstract Early intervention (EI) in psychosis has established itself as a cornerstone of service provision in psychosis over the last two decades. It is the latest in a line of key developments in the management of psychotic disorders over the last 60 years, following the introduction of antipsychotic medication, de-institutionalization, community care, and more effective psychosocial interventions. It borrows from principles that have emerged over the last few decades in other areas of medicine, social care, and education. Its focus is on early detection, prevention, and intervention in young people with emerging first-episode psychosis. It has become a social movement in its own right, developing its own national and international associations (e.g. the International Early Psychosis Association) World Health Organization-endorsed principles (Bertolote and McGorry, 2005), and attracting considerable political, media, and community support. This explosion of interest in EI over the past two decades has prompted governments in many developed countries to adopt the EI model, with some promoting it as a top priority for mental health service planning (Appleby, 2009). Countries such as United Kingdom, Canada, Australia, and New Zealand have committed to national roll-outs of these services. This has been further supported by recent economic evaluations highlighting the substantial health savings involved (McCrone et al., 2008; Mihalopoulos et al., 2009). The field is now moving into other forms of serious mental illness, not only in conditions typically affecting young people but even into old age psychiatry (Naismith et al., 2009). However, questions remain regarding the long-term benefits of a focus on early intervention (Bertelsen et al., 2008; Craig, 2003; Gafoor et al., 2010; Pelosi, 2009) and there is much to discover about the true extent of its merits. There is still uncertainty about the ideal model. EI services wrestle with the dilemma of whether they are for all age groups or specifically for young people, whether they are extensions of child and adolescent mental health services, or young adult services, or both, whether they are limited to non-affective psychoses or all forms of serious mental illness, and whether they are best provided independently of generic services or embedded as subcomponents of these services.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".