Longitudinal Associations Between Teen Dating Violence Victimization and Adverse Health Outcomes
Bibliographic record
Abstract
OBJECTIVE: To determine the longitudinal association between teen dating violence victimization and selected adverse health outcomes. METHODS: Secondary analysis of Waves 1 (1994-1995), 2 (1996), and 3 (2001-2002) of the National Longitudinal Study of Adolescent Health, a nationally representative sample of US high schools and middle schools. Participants were 5681 12- to 18-year-old adolescents who reported heterosexual dating experiences at Wave 2. These participants were followed-up ~5 years later (Wave 3) when they were aged 18 to 25. Physical and psychological dating violence victimization was assessed at Wave 2. Outcome measures were reported at Wave 3, and included depressive symptomatology, self-esteem, antisocial behaviors, sexual risk behaviors, extreme weight control behaviors, suicidal ideation and attempt, substance use (smoking, heavy episodic drinking, marijuana, other drugs), and adult intimate partner violence (IPV) victimization. Data were analyzed by using multivariate linear and logistic regression models. RESULTS: Compared with participants reporting no teen dating violence victimization at Wave 2, female participants experiencing victimization reported increased heavy episodic drinking, depressive symptomatology, suicidal ideation, smoking, and IPV victimization at Wave 3, whereas male participants experiencing victimization reported increased antisocial behaviors, suicidal ideation, marijuana use, and IPV victimization at Wave 3, controlling for sociodemographics, child maltreatment, and pubertal status. CONCLUSIONS: The results from the present analyses suggest that dating violence experienced during adolescence is related to adverse health outcomes in young adulthood. Findings from this study emphasize the importance of screening and offering secondary prevention programs to both male and female victims.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".