Self-regulation as a Mediator of Mindfulness and Physical Activity: A Narrative Review
Bibliographic record
Abstract
Mindfulness is gaining increased attention as a means of increasing physical activity (PA) participation. Given that only 15.4% of adult Canadians currently meet the Canadian Physical Activity Guidelines (Colley et al., 2011), it is imperative to find ways to increase PA among adults. One way to do this is to promote self-regulation skills as self-regulation is among the top predictors of PA participation (Teixeira et al., 2015). The purpose of this narrative review was to further understand the role of self-regulation as a potential mechanism by which mindfulness may be related to PA participation. Initially, 160 papers were identified by title for this review. After reading abstracts, 37 papers were identified as possibly relating to the topic of interest. Following full readings, 26 papers were included in the final review. Likely due to the novelty of this topic, there is limited research on the mechanisms by which mindfulness may be related to physical activity. Review of the literature suggests that self-regulation appears to be a promising mechanism by which mindfulness could improve physical activity participation (Shapiro et al., 2006; Samdal et al., 2017), as self-regulation has been shown to play an important role in behaviour change, however, other alternative mechanisms include improved self-efficacy, as well as improved satisfaction (Neace et al., 2020; Tsafou et al., 2016). The authors conclude that more research on the mechanisms of mindfulness on PA, specifically self-regulation as a mechanism, could foster more knowledgeable intervention practices, and consequently improve mindfulness-based interventions efficacy.
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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".