Pathways between self-esteem and depression in couples.
Bibliographic record
Abstract
Guided by concepts from a relational developmental perspective, this study examined intra- and interpersonal associations between self-esteem and depressive symptoms in a sample of 1,407 couples surveyed annually across 6 years in the Panel Analysis of Intimate Relations and Family Dynamics (pairfam) study. Autoregressive cross-lagged model results demonstrated that self-esteem predicted future depressive symptoms for male partners at all times, replicating the vulnerability model for men (low self-esteem is a risk factor for future depression). Additionally, a cross-partner association emerged between symptoms of depression: Higher depressive symptoms in one partner were associated with higher levels of depression in the other partner one year later. Finally, supportive dyadic coping, the support that partners reported providing to one another in times of stress, was tested as a potential interpersonal mediator of pathways between self-esteem and depression. Female partners' higher initial levels of self-esteem predicted male partners' subsequent reports of increased supportive dyadic coping, which, in turn, predicted higher self-esteem and fewer symptoms of depression among female partners in the future. Male partners' initially higher symptoms of depression predicted less frequent supportive dyadic coping subsequently reported by female partners, which was associated with increased feelings of depression in the future. Couple relations represent an important contextual factor that may be implicated in the developmental pathways connecting self-esteem and symptoms of depression. (PsycINFO Database Record
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".