From Social Experience to Illness Experience: Reviewing the Psychological Mechanisms Linking Psychosis with Social Context
Bibliographic record
Abstract
This review was undertaken to describe the psychological processes that are associated with the social experiences and behaviours of people with psychosis. A systematic search was conducted using MEDLINE and PsycINFO search engines. In each of the major topic domains, the search was comprised of review articles published from 2004 to present, and individual article searches for papers published from 2010 to present. The key psychological mechanisms in this context are social cognition, self-concept, emotion, and communication. While diverse in content, there were several cross-cutting themes in these literatures. These include evidence of the presence of social processing difficulties in high-risk and psychosis populations that have both state and trait characteristics, are related to, but not fully accounted for by, neurocognition and symptomatology, and have significant implications for social functioning. There are numerous established and promising treatments linked to our understanding of social cognition. Limitations cutting across these literatures include a substantial reliance on cross-sectional studies that use control groups comprised of people who have not experienced significant psychological or social adversity. There is also limited inquiry into how psychological mechanisms may differ owing to sex, ethnicity, and race. Despite these issues, this line of inquiry is very promising as part of the larger movement toward an integrative model of psychosis that is able to account for the complex interactions of social, biological, and psychological risks.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".