Development and Reliability of a Pictorial Mental Disorders Screen for Young Adolescents
Bibliographic record
Abstract
OBJECTIVE: To report psychometric data from preliminary studies of the Adolescent Dominic (AD), a pictorial screen for the most frequent Axis I youth mental disorders. METHODS: We created 113 picture items based on DSM-III-R diagnostic criteria and assessed them for comprehension (sample 1, n = 114; sample 2, n = 40) and reliability (sample 3, n = 128) in a group of adolescents aged 12 to 16 years living in the community. We used the kappa statistic to estimate test-retest reliability of symptoms, criteria and diagnoses, and intraclass correlation coefficients (ICCs) for symptom and criterion scores. We assessed internal consistency of symptom scores with the alpha coefficient. RESULTS: For symptoms, 54.4% of kappas were higher than 0.60, while only 2% were poor. ICCs for symptom scores yielded higher values (0.81 to 0.89) than for criterion scores (0.51 to 0.86). Internal consistency of symptom scores ranged from 0.52 to 0.83. Kappas for diagnoses ranged from 0.52 to 0.76. CONCLUSIONS: Symptom reliability compared favourably with data from other assessment interviews of youth mental disorders. Following these positive results, a computerized DSM-IV version of the AD has focused on the assessment of symptoms and is currently being tested for reliability and criterion validity.
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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 | 0.006 | 0.016 |
| 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 | 0.001 |
| 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".