How can sport help those with Type 2 diabetes? A look at coping
Bibliographic record
Abstract
Organized sport is a staple activity in the lives of many Canadians. Sport brings people together and provides a fun and unique form of physical activity. One skill that is said to come from organized sport is the ability to learn coping strategies to manage stress and adversity. If this is indeed the case, then participation in organized sport should be especially beneficial for individuals who rely on coping skills on a daily basis. People living with Type 2 diabetes are indeed such a group. People living with diabetes have to cope with managing their illness which includes blood glucose monitoring, diet, exercise, attending medical appointments, and other related activities. In this research, I examined whether people living with Type 2 diabetes who have a history of participating in organized sport implement different types of coping strategies to manage their illness, thereby improving their quality of life. Participants (n = 455) living with Type 2 diabetes completed online surveys that assessed (a) past participation in organized sport; (b) the extent to which they engage in problem-focused, emotion-focused, and avoidant coping strategies to manage their illness; and (c) health-related quality of life. Responses were analyzed using mediation analysis to test whether having a history of participation in organized sport predicted higher quality of life indirectly via specific coping strategies. Having a history of participation in organized sport was associated with greater self-rated general health and mental health, more use of problem-focused and emotion-focused coping strategies, and less use of avoidance coping strategies. As an individual’s level of avoidance coping increased, they generally had lower levels of self-reported general, mental, and physical health. In contrast, emotion-focused coping predicted greater levels of general and mental health. Finally, emotion-focused coping mediated the relationship between hours spent playing organized sport and both general health and mental health. The findings of this study suggest that participants may learn skills associated with problem-focused and emotion-focused coping strategies to manage stress through engagement in organized sport, which may facilitate better quality of life outcomes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| 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".