Measuring adolescent dating violence: Development of ‘conflict in adolescent dating relationships inventory’ short form
Bibliographic record
Abstract
Given the high prevalence of dating violence among adolescent and the signifi cant consequences associated with adolescent dating violence, including its co-occurrence with other problematic behaviors such as alcohol and substance abuse, standardized measures to assess adolescent dating violence are essential. The objective of the present studies was to develop and validate a 10-item short form of the Confl ict in Adolescent Dating Relationships Inventory (CADRI; Wolfe et al., 2001), a 46-item self-report questionnaire of dating violence among youth dating partners. In study one, the short form (CADRI-S) was derived from a sample of 277 high school students, and its psychometric properties were analyzed. In study two, the CADRI-S was validated on a sample of 365 at-risk youth involved with child protective services (CPS). The new short form was composed of two items for each subscale (physical abuse, threatening behavior, sexual abuse, relational abuse, and verbal/emotional abuse). Results showed acceptable reliability indices and confi rmatory factor analyses revealed a good model fi t. Indicators of convergent, concurrent and predictive validity are also provided. Although the sensitivity of the new short form was lower than that of the full scale, fi ndings provided initial evidence of the validity of the CADRI-S and its potential applications are discussed. Future studies should evaluate its psychometric properties using an independent administration of the short and full form to the same participants.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".