Parental expressed emotion in depressed adolescents: prediction of clinical course and relationship to comorbid disorders and social functioning
Bibliographic record
Abstract
BACKGROUND: High expressed emotion (EE) predicts worse clinical course for a number of disorders. High EE is more frequent in parents of disordered children than normal controls. It is uncertain whether EE and its components are disorder-specific, whether EE is more closely related to parent characteristics or child characteristics, and whether EE predicts clinical course independently of clinical variables that reflect severity of disorder. EE has not been investigated in adolescent depression. METHOD: The 57 participants in this study were a sub-sample of a longitudinal study of the clinical course of depression. Adolescents and parents were recruited from consecutive referrals to all psychiatric outpatient clinics and inpatient units in a geographic catchment area. The association between EE and one-year clinical outcome of major depressive disorder was tested and associations between EE and characteristics of the adolescent, the parent, and the family were examined. RESULTS: EE was independent of socio-demographic characteristics, comorbid diagnoses, and parental depression. High EE was associated with worse adolescent social functioning according to either adolescent or parent report. High EE was associated with the presence of more depression symptoms. Low EE predicted major depression remission in participants without comorbid attention-deficit/hyperactivity disorder (ADHD), but this association was not independent of the association between social functioning and depression remission. CONCLUSIONS: The findings indicate a need to examine possible protective effects of low EE. Relationships between EE, social functioning, and depression persistence and remission require further examination.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".