Spillover effects on the relationship with the partner of a mentalization‐based intervention for pregnant women
Bibliographic record
Abstract
The birth of a child has been associated with a decline in couple satisfaction, which has implications for the child's social-emotional development. This study investigated the potential spillover effect on pregnant women's perceptions of their relationships with their partners of the Supporting the Transition to and Engagement in Parenthood (STEP) program, a brief trauma-informed mentalization-based prenatal group intervention. Participants (94% White) were recruited in prenatal clinics and through online advertisements in Quebec, Canada. Both quantitative and qualitative data were collected from participants assigned to the STEP program (n = 42) and those receiving treatment-as-usual (TAU; n = 125). Women participating in STEP reported significant improvements in their relationships with their partners compared to those assigned to TAU. More precisely, they reported higher couple satisfaction, enhanced communication, and increased interest in their partners' emotional experience. The qualitative analysis further substantiated these results, with participants reporting having involved their partners in their pregnancy, shared their insights about themselves with their partners and gained fresh perspectives on their relationships. Participants in STEP also expressed sharing program materials with their partners and considered that such interventions should be extended to expecting fathers. This study underscores the potential of mentalization-based interventions to indirectly contribute to couple relationships, which may have positive implications for parenting and the infant.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".