Is skills training necessary for the primary prevention of marital distress and dissolution? A 3-year experimental study of three interventions.
Bibliographic record
Abstract
OBJECTIVE: Evidence in support of skill-based programs for preventing marital discord and dissolution, while promising, comes mainly from studies using single treatment conditions, passive assessment-only control conditions, and short-term follow-up assessments of relationship outcomes. This study overcomes these limitations and further evaluates the efficacy of skill-based programs. METHOD: Engaged and newlywed couples (N = 174) were randomly assigned to a 4-session, 15-hr small-group intervention designed to teach them skills in managing conflict and problem resolution (PREP) or skills in acceptance, support, and empathy (CARE). These couples were compared to each other, to couples receiving a 1-session relationship awareness (RA) intervention with no skill training, and to couples receiving no treatment on 3-year rates of dissolution and 3-year trajectories of self-reported relationship functioning. RESULTS: Couples in the no-treatment condition dissolved their relationships at a higher rate (24%) than couples completing PREP, CARE, and RA, who did not differ on rates of dissolution (11%). PREP and CARE yielded unintended effects on 3-year changes in reported relationship behaviors. For example, wives receiving PREP showed slower declines in hostile conflict than wives receiving CARE, and husbands and wives receiving CARE showed faster declines in positive behaviors than husbands and wives receiving PREP. CONCLUSIONS: These findings highlight the potential value of cost-effective interventions such as RA, cast doubt on the unique benefits of skill-based interventions for primary prevention of relationship dysfunction, and raise the possibility that skill-based interventions may inadvertently sensitize couples to skill deficits in their 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".