What makes them last? Predicting time to relationship dissolution in adolescent women’s intimate relationships with male partners
Bibliographic record
Abstract
Adolescents acquire important intimacy and communication skills in their relationships that contribute to relationship longevity. Yet we know relatively little about which factors help relationships endure. Objective: This study tracked adolescent women’s ( N = 387; 14–17 years) relationships from onset to dissolution to assess factors that contribute to relationship length. Prior relationship experience, relationship characteristics, and current relationship behaviors were assessed as contributors. Method: A sample of 387 female adolescents (89% African American) were recruited from three primary care adolescent health clinics serving lower- to middle-income families in a large Midwestern city. All were interviewed every 3 months about ongoing relationships. The main outcome measure was time to dissolution. Results: The average relationship lasted 5.87 months ( SD = 11.76). Greater numbers and more time spent in prior relationships were associated with longer duration of the current relationship. Being older, having more status changes during the relationship (promotions and demotions), and reporting greater relationship quality, sexual communication, and sexual autonomy were associated with significantly longer time to breakup. Conclusions: Research to date has not tracked specific relationship timelines. In line with a developmental tasks perspective, this study provides new insights into the value of adolescent women’s past relationship experiences, measures of aging and accrued experience, as well as current relationship characteristics and behaviors to the development of relationship maintenance skills. These findings have educational and clinical implications as they inform programming initiatives designed to help young people establish healthy, consensual intimate relationships.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".