The Impact of Self- and Relation-Inferred Efficacy on Physical Activity in Older Adult Couples
Bibliographic record
Abstract
Abstract Previous research has indicated that physical activity (PA) is a health-promoting behavior that is closely linked in couples. However, few studies have examined how PA is intertwined among couples in their everyday lives. For example, relation-inferred efficacy (RIE) is an individual perception that captures whether a close other believes in one’s own abilities to perform specific behaviours; it originates from the sports literature on coach-athlete dyads and has been shown to shape athlete performance. Applying a repeated daily life assessment design, the current study targets self-efficacy (SE) and relation-inferred efficacy (RIE) as predictors of PA in older adult couples, as well as potential moderators when obstacles occur. We hypothesized that: (a.) There is a main effect of SE and RIE on PA. (b.) PA is lower on days when people anticipate barriers (c.) SE and RIE moderate the time-varying relationship between PA and barriers. Heterosexual couples (N=108 couples, Mage=70.5 years, SD=6.70) rated their SE and REI, completed daily electronic questionnaires asking about barriers and wore an accelerometer to capture indices of PA across seven days. In line with past work, SE (r(2438)=.13, p=<.001) and RIE (r(2438)=.14, p=<.001) were significantly related to total moderate-to-vigorous PA (MVPA) and step counts. A series of multilevel models were fit to examine the hypotheses. Preliminary analyses indicated that RIE (estimate=3.93, SE=1.49, p=.009) is a stronger predictor of MVPA than SE (estimate=2.83, SE=2.02, p=.16). Further analysis will be conducted to unpack daily life circumstances that create barriers to PA, including daily pain, anxiety, and tiredness.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".