Daily interpersonal tensions as predictors of threats to communion and agency, coping, and perceived coping efficacy: role of adverse childhood experiences
Bibliographic record
Abstract
BACKGROUND: Daily interpersonal tensions, common sources of stress, have well-established links to adverse psychological and physiological health outcomes. This study examined whether daily interpersonal tensions differ from other stressors in their relations to threat appraisals and coping, and how adverse childhood experiences (ACEs) contribute to this process. METHODS: Community-dwelling adults (N = 233, aged 25-87 years) reported ACEs and completed four mobile surveys per day for 14 days about stressors, threat appraisals for communion and agency, coping, and perceived coping efficacy. RESULTS: Multilevel models found greater communal, but not agentic, threat appraisals on days with interpersonal tensions (vs. days with other stressors). On such days, there was less support seeking, more avoidance, and lower perceived coping efficacy, but no differences in problem solving or reappraisal. The within-person relationship between interpersonal tensions and avoidance (but not other coping approaches) was more pronounced in individuals with more ACEs. CONCLUSION: Compared to other daily stressors, interpersonal tensions were associated with greater communal threat appraisals, and engagement in less effective coping responses. People with more ACEs tended to disengage more from interpersonal tensions than from other stressors.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".