Development and validation of the Relational Skills Inventory for Adolescents
Bibliographic record
Abstract
INTRODUCTION: Dating violence prevention initiatives are intended, not only to reduce the occurrence of violent behaviors, but also to promote the development of positive dating relational skills starting in adolescence. However, despite the growing interest in examining adolescent relational skills in adolescents, no specific measure is yet available to assess post program gains relative to dating violence prevention and intervention. The current study addressed this important gap in dating relationships research by developing and validating a new measure of relational skills for adolescents. METHODS: = 687). RESULTS: Exploratory factor analysis revealed a three-factor structure reflecting constructs of Assertiveness, Support and Individuality (α = 0.69-0.81). Results also support evidence of convergent validity with related measures. The three-factor structure was cross-validated among a second sample (α = 0.74-0.79). Two-way ANCOVAs were also conducted to examine differences in levels of relational skills as a function of sex and previous dating violence perpetration. Results indicated that girls reported higher levels of assertiveness than boys, and that adolescents who reported the use of dating violence also reported lower levels of all relational skills. CONCLUSION: The validation of the Relational Skills Inventory for Adolescents (RSI-A) will help researchers assess the effectiveness of interventions aimed at promoting the development of positive dating relationships during adolescence.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".