Physical activity, well-being and the basic psychological needs in cardiac rehabilitation graduates: A path analysis
Bibliographic record
Abstract
Both physical activity and well-being have been shown to be related to cardiovascular disease; however, the relationship between these variables is not well understood in this population. According to Ryan, Huta and Deci's (2008) empirical model, eudaimonic living (as a motive) fosters well-being through the satisfaction of the basic psychological needs. The purpose of this study was to first test the empirical model proposed by Ryan, Huta & Deci (2008) in cardiac rehabilitation graduates and second to examine if physical activity is best served as a predictor or an outcome of the model. Participants (N=52, Mage = 62.9 [SD =14.85]; 79% male) wore an Actigraph GT3X accelerometer for 9 days to objectively assess moderate-to-vigorous physical activity. Participants completed questionnaires on eudaimonic and hedonic motives, eudaimonic and hedonic well-being, and the basic psychological needs of autonomy, relatedness and competence. Separate path analyses in MPlus were conducted to examine (a) the empirical eudaimonic model and physical activity as a (b) predictor and (c) outcome of the model. The empirical eudaimonic model was supported as both motives strongly predicted the basic psychological needs (β>.64) and the basic psychological needs were strongly related with eudaimonic well-being (β=.63). A small to moderate relationship was found with physical activity as a predictor of eudaimonic motives (β=.26) and as an outcome of eudaimonic well-being (β=.23). The empirical eudaimonic model appears to hold in a cardiac sample but the role of physical activity remains unclear. A longitudinal study testing alternative models would provide additional insight for future physical activity and well-being interventions.Acknowledgments: CS was supported by the Social Sciences and Humanities Research Council of Canada (SSHRC). This research was funded by the Fonds de recherche du Quebec - Santé (FRQS).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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 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".