Relational effects on physical activity: A dyadic approach to the theory of planned behavior.
Bibliographic record
Abstract
(see record 2016-36139-020). In the article, NIAAA Grant 5T32-AA07290 provided funding support for manuscript preparation but was omitted from the author note.] Objective: Despite growing appreciation of how close relationships affect health outcomes, there remains a need to explicate the influence romantic partners have on health behavior. In this paper, we demonstrate how an established model of behavior change-the theory of planned behavior (TPB)- can be extended from an individual level to a dyadic (couple) model to test the influence that relationship partners have on a key determinant of health behavior-behavioral intentions. METHODS: Two hundred romantic couples (400 individuals) completed TPB measures regarding physical activity for themselves and their romantic partner as well as a measure of relationship quality. RESULTS: Above and beyond the individual-level TPB predictors of behavioral intentions (i.e., attitudes, subjective norms, and perceived behavioral control), the romantic partner's perceived behavioral control (PBC) regarding physical activity predicted each individual's behavioral intentions and moderated the influence of each individual's PBC on his or her own behavioral intentions. Additionally, the romantic partner's perceptions of each individual's TPB measures predicted each individual's behavioral intentions to be physically active. Quality of the relationship also moderated some partner influences on individuals' intentions. CONCLUSIONS: This paper provides a roadmap for integrating a dyadic framework into individual-level models of behavior change. The findings suggest that data from both partners and relationship quality are important to consider when trying to understand and change health-related behavior such as physical activity. The results broaden the potential applications of the TPB as well as our understanding of how romantic partners might influence important health-related practices. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".