Research Review: Test–retest reliability of standardized diagnostic interviews to assess child and adolescent psychiatric disorders: a systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND: A better understanding of factors contributing to the observed variability in estimates of test-retest reliability in published studies on standardized diagnostic interviews (SDI) is needed. The objectives of this systematic review and meta-analysis were to estimate the pooled test-retest reliability for parent and youth assessments of seven common disorders, and to examine sources of between-study heterogeneity in reliability. METHODS: Following a systematic review of the literature, multilevel random effects meta-analyses were used to analyse 202 reliability estimates (Cohen's kappa = ҡ) from 31 eligible studies and 5,369 assessments of 3,344 children and youth. RESULTS: = 79%). In subgroup analysis, reliability varied across informants for specific types of psychiatric disorder (ҡ = .53-.69 for parent vs. ҡ = .39-.68 for youth) with estimates significantly higher for parents on attention deficit hyperactivity disorder, oppositional defiant disorder and the broad groupings of externalizing and any disorder. Reliability was also significantly higher in studies with indicators of poor or fair study methodology quality (sample size <50, retest interval <7 days). CONCLUSIONS: Our findings raise important questions about the meaningfulness of published evidence on the test-retest reliability of SDIs and the usefulness of these tools in both clinical and research contexts. Potential remedies include the introduction of standardized study and reporting requirements for reliability studies, and exploration of other approaches to assessing and classifying child and adolescent psychiatric disorder.
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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 | 0.039 | 0.116 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.031 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".