The comparability of mother‐report structured interviews and checklists for the quantification of youth externalizing symptoms
Bibliographic record
Abstract
BACKGROUND: Although structured interviews are assumed to be scientifically superior to checklists for measuring youth psychopathology, few studies have tested this hypothesis. Interviews place a much greater burden on respondents, making it critical to determine their added value when quantifying psychiatric symptoms. METHODS: Confirmatory factor analysis was used to compare interviews and checklists in community (N = 251) and clinically referred (N = 406) samples of youth aged 5 to 17 years. We examined the associations between mother-reported externalizing symptoms assessed by interview versus checklist against (a) teacher-reported externalizing symptoms, and (b) child's gender, academic performance, single- versus two-parent family, and family income. Models in which associations were estimated freely were contrasted to models in which the interview and the checklist were constrained to have equal associations with the variables. Finding these models fit comparably would suggest no difference between interviews and checklists. RESULTS: In the community sample, both the constrained and unconstrained models provided comparable fit to the data, suggesting no marked differences between interviews and checklists. In the clinical sample, associations with the interview were generally stronger. Reducing the number of items on the interview to match those on the 6-item checklist eliminated these differences, suggesting that the increased reliability of the interview scales, afforded by additional items, enhanced their quantification of psychopathology. CONCLUSIONS: Consistent with previous studies, interviews were not notably superior to checklists for the measurement of externalizing symptoms. When only a few items are used, small performance differences between checklists and interviews may be due to scale length.
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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 | 0.104 | 0.263 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 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".