Keys to their Kingdom: Preliminary Evidence to Support the Role of Positive Beliefs in Recovery-Oriented Cognitive Therapy for Negative Symptoms and Community Participation
Bibliographic record
Abstract
BACKGROUND AND HYPOTHESIS: Review studies find negative beliefs account for a small amount of the variance in negative symptoms and functioning. Recovery-Oriented Cognitive Therapy (CT-R) theory postulates positive beliefs as an additional causal factor. STUDY DESIGN: Two convenience datasets-including indices of beliefs, negative symptoms, positive symptoms, and community functioning-were utilized: a test-retest database (Study 1 and Study 2, n = 285); the CT-R condition of an RCT (Study 3, n = 31). STUDY RESULTS: Study 1 finds that positive and negative beliefs are independent and not highly correlated with each other at baseline (r = -0.4); an exploratory factor analysis also suggests this 2 factor solution. Study 2 finds significant prediction of positive beliefs at baseline with negative symptoms (β = -0.21; P = .001), and community functioning (β = 0.29; P = .002) 6 months later. Study 3 finds a significant correlation between increase in positive belief endorsement and improvement in community functioning in the CT-R condition across 24-months (r = 0.39, P < .05). The correlation between positive belief endorsement and negative symptom improvement was not statistically significant but showed a medium effect size (r = -0.26; P > .05). Change in positive beliefs were not significantly associated with positive symptom improvement. Negative beliefs were not significantly associated with change in any of the RCT outcomes. CONCLUSIONS: The hypothesis that positive beliefs are related in the predicted direction to negative symptoms and functioning is supported, adding to an emerging literature. We point out the treatment implications of this result, utilizing CT-R theory, and discuss future research directions.
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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 | 0.008 | 0.064 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.048 | 0.005 |
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".