Reliability, Validity, and Clinical Use of the Dominic Interactive: A DSM-Based, Self-Report Screen for School-Aged Children
Bibliographic record
Abstract
OBJECTIVES: As no single informant can be considered the gold standard of child psychopathology, interviewing of children regarding their own symptoms is necessary. Our study focused on the reliability, validity, and clinical use of the Dominic Interactive (DI), a multimedia self-report screen to assess symptoms for the most frequent Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision, mental disorders in school-aged children. METHODS: A sample of 585 children aged 6 to 11 years from the community and psychiatric clinics was used to analyze the internal consistency, the test-retest estimate of reliability, and the criterion-related validity of the DI against the referral status. In addition, cross-informant correlation coefficients between this instrument (child report) and the Child Symptom Inventory (parent report) were explored in a subsample of 292 participants. RESULTS: For the total sample, Cronbach alpha coefficients ranged from 0.63 to 0.91. Test-retest kappas varied from 0.42 to 0.62 for categories based on cut-off points, except for specific phobias. Intraclass correlation coefficients ranged from 0.70 to 0.81 for symptom scales. The DI discriminated between referred and non-referred children in psychiatric clinics for all symptom scales. Significant cross-informant correlation coefficients were higher for the externalizing symptoms (0.35 to 0.48) than the internalizing symptoms (0.14 to 0.27). CONCLUSIONS: Findings of our study reasonably support adequate psychometric properties of the DI. This instrument offers a developmentally sensitive screening method to obtain unique information from young children about their mental health problems in front-line services, psychiatric clinics, and research settings.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".