Do personality traits matter when choosing a group therapy for early psychosis?
Bibliographic record
Abstract
OBJECTIVES: This study aimed at determining the predictive value of personality traits, based on the Five Factor Model (FFM) of personality, on therapeutic outcomes according to specific group treatments for first episode psychosis: cognitive-behavioural therapy (CBT) or skills training for symptom management (SM). METHODS: Individuals experiencing early psychosis were recruited to participate in a randomized- controlled trial (RCT). Participants were randomized to one of two group treatments or to a wait-list control group. Measures included a personality inventory (NEO-FFI) and outcome measures of symptomatology (BPRS-E) and coping strategies (CCS). Pearson correlation analyses were conducted on 78 individuals and linear regression analyses on 66. RESULTS: Links were found between personality traits, symptoms, and coping outcome measures, according to specific group treatments. Personality traits were particularly linked to therapeutic changes in active coping strategies, with Conscientiousness accounting for 14% of the variance in the CBT group, Extraversion accounting for 41% of the variance in the SM group, and Openness to experience accounting for 22% of the variance in the control group. CONCLUSIONS: Individual differences in personality traits for people experiencing early psychosis should be considered when offering psychosocial treatments, since it appears that those with specific traits might benefit more than others in specific group interventions, particularly for interventions that do not solely aim at improving symptoms.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".