The More We Are in Control, the Merrier? Partner Perceived Control and Negative Affect in the Daily Lives of Older Couples
Bibliographic record
Abstract
OBJECTIVES: It is well established that daily perceived control is closely associated with lower negative affect (NA) among older adults. However, it is an open question whether control perceptions of one's partner are also uniquely associated with one's own NA. METHOD: To examine such associations in dyads of older long-term partners, we make use of data obtained 6 times a day over 7 consecutive days as participants went about their everyday lives (N = 87 couples; mean age = 75 years; mean relationship length = 46 years). Our multilevel actor-partner models for dyadic data analyses covary for relevant individual and couple differences in sociodemographic characteristics, self-reported physical health, and cognitive functioning. RESULTS: Corroborating and extending earlier reports, results reveal that higher momentary perceived control was associated with lower NA. Most importantly, we found that higher momentary perceived control of the partner is additionally and uniquely associated with lower NA of the actor. DISCUSSION: We discuss possible mechanisms and underlying pathways of how perceived control may help both partners downregulate their negative emotions in daily life. We close by considering conceptual and practical implications.
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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 | 0.007 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".