Assessing for Mood and Anxiety Disorders in Parents of Clinically-Referred Children: Laying the Foundation for a Family-Based Approach to Mental Health in Singapore
Bibliographic record
Abstract
INTRODUCTION: Family history of psychopathology is a risk factor for mood and anxiety disorders in children, but little is known about rates of parental psychopathology among treatment-seeking youth with affective disorders in the Asia Pacific region. This study examined patterns of emotional and behavioural problems in parents of clinically-referred youth in Singapore. We hypothesised that parents would have higher rates of affective disorders compared to the Singapore national prevalence rate of 12%. MATERIALS AND METHODS: In this cross-sectional study, 47 families were recruited from affective disorders and community-based psychiatry programmes run by a tertiary child psychiatry clinic. All children had a confirmed primary clinical diagnosis of depression or an anxiety disorder. Parents completed the Mini International Neuropsychiatric Interview (MINI) to assess for lifetime mood and anxiety disorders. They also completed the Adult Self Report (ASR) and Adult Behavior Checklist (ABCL) to assess current internalising and externalising symptoms. RESULTS: Consistent with our hypothesis, 38.5% of mothers and 10.5% of fathers reported a lifetime mood and anxiety disorder. Nearly 1/3 of mothers had clinical/subclinical scores on current internalising and externalising problems. A similar pattern was found for internalising problems among fathers, with a slightly lower rate of clinical/subclinical externalising problems. CONCLUSION: Our findings are consistent with previous overseas studies showing elevated rates of affective disorders among parents - particularly mothers - of children seeking outpatient psychiatric care. Routine screening in this population may help to close the current treatment gap for adults with mood and anxiety disorders.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".