The Impact of Gender on Physical Activity Preferences and Barriers in Adults With Type 1 Diabetes: A Qualitative Study
Bibliographic record
Abstract
OBJECTIVES: Current exercise recommendations for people with type 1 diabetes (T1D) are based on research involving primarily young, fit male participants. Recent studies have shown possible differences between male and female blood glucose response to exercise, but little is known about whether these differences are sex-related (due to physiological differences between male and female participants) or gender-related (behavioural differences between men and women). METHODS: To better understand gender-based behavioural differences surrounding physical activity (PA), we asked men and women (n=10 each) with T1D to participate in semistructured interviews. Topics discussed included motivation and barriers to exercise, diabetes management strategies, and PA preferences (type, frequency, duration of exercise, etc). Interview transcripts were coded by 2 analysts before being grouped into themes. RESULTS: Six themes were identified impacting participants' PA experience: motivation, fear of hypoglycemia, time lost to T1D management, medical support for PA, the role of technology in PA accessibility, and desire for more community. Gender differences were found in motivations, medical support, and desire for more community. Women were more motivated by directional weight dissatisfaction, and men were more motivated to stay in shape. Men felt less supported by their health-care providers than women. Women more often preferred to exercise in groups, and sought more community surrounding T1D and PA. CONCLUSION: Although men and women with T1D experience similar barriers around PA, there are differences in motivation, desire for community, and perceived support from medical providers.
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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".