Psychometric Qualities of the Dimensional Assessment of Personality Pathology – Short Form for Adolescents
Bibliographic record
Abstract
Abstract Background: A growing body of research recognizes the occurrence and validity of personality pathology during adolescence as well as its relevance as a developmental precursor of adult personality pathology. Objective: The present study recognizes the need for a comprehensive and concise instrument to assess the dimensions of personality pathology in adolescents. Therefore, the psychometric qualities of an abbreviated version of the Dimensional Assessment of Personality Pathology - Basic Questionnaire for Adolescents (DAPP-BQ-A), which has been denoted as the DAPP - Short Form for Adolescents (DAPP-SF-A), were examined. Method: The factorial structure, internal consistency, test-retest reliability, discriminative validity, and classification accuracy of the DAPP-SF-A scales were examined in three samples: 1596 non-referred adolescents; 166 adolescents referred to inpatient and outpatient mental health services; and 58 referred and general population adolescents. Results: Despite a reduction in the number of items by 50% (from 290 to 144 items), the promising psychometric qualities established for the DAPP-BQ-A were replicated for the DAPP-SF-A. Conclusions: The results of this study are promising regarding the qualities of the DAPP-SF-A and its utility in both clinical and research settings. In addition, the equivalence of the instruments for adolescents and (young) adults enables the investigation of developmental trajectories across different life stages.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".