Cognitive Behavioural Therapy for Unusual Experiences in Children: A Case Series
Bibliographic record
Abstract
BACKGROUND: Over half of children in the general population report unusual or "psychotic-like" experiences (PLEs). The development of a later at-risk mental state is associated with persistent, distressing, PLEs, which are appraised negatively and hard to cope with. We have designed a novel, manualized, cognitive behavioural intervention for children aged 9 to 14 years, which aims to reduce emotional problems, improve coping and resilience, and help children manage PLEs, before an identifiable psychosis risk develops. We report on the feasibility, acceptability and clinical impact of the intervention. METHOD: Four children who reported PLEs and emotional problems in a community survey completed the intervention, and gave detailed feedback. Clinical outcomes were assessed before, during, and after therapy. RESULTS: Emotional problems, PLE frequency, and PLE impact all decreased during the intervention. Child and therapist satisfaction with the treatment was high. CONCLUSIONS: It is feasible, acceptable and helpful to offer psychological interventions to children who report emotional distress and PLEs, prior to the emergence of clear risk factors. Our intervention has the potential to increase resilience to the development of future mental health problems. A larger, randomized controlled evaluation is underway.
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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 | 0.000 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".