545-P: The Impact of Gender on Physical Activity Preferences and Barriers in Adults with Type 1 Diabetes: A Qualitative Study
Bibliographic record
Abstract
Exercise studies involving people with type 1 diabetes (T1D) have tested young, fit, men. As such, current insulin adjustment and carbohydrate intake advice may not work for women. A recent secondary analysis found different blood glucose (BG) responses to a weight lifting protocol between male and female T1D participants. It is unclear whether these differences were physiological (i.e., hormones, muscle mass, etc.) or behavioural (i.e., insulin adjustments, carbohydrate intake, etc.) . To explore gender-related differences in physical activity (PA) behaviours and preferences, we recruited men and women with T1D to take part in semi-structured interviews. Questions included demographics, perceived differences between genders (preferred type of PA, motivation, and barriers) , diabetes management strategies (i.e., insulin adjustments, carbohydrate intake, high intensity exercise, etc.) , and PA preferences (frequency, type, motivations, etc.) . Two analysts coded interview transcripts using a framework approach, through open coding of emergent themes. The most common themes were:1) Impact of support on PA success. Both men and women made statements about support, or lack of support, from family members, medical providers, and group exercise. Women reported receiving support from their healthcare team, while men did not.2) Strategies for BG management. This included reducing insulin pre-exercise and consuming extra carbohydrates. Few participants reported using intense exercise.3) Barriers to PA. Men and women reported similar barriers, including hypoglycemia, time limitations, and lack of motivation. Women reported more concerns about dysglycemia.4) Reasons to exercise. The main differences between genders were the importance of enjoyment for men and weight management for women. Overall, men and women with T1D possess similar barriers, sources of support, and BG management strategies around PA, despite differences in motivation. Disclosure J.E.Logan: None. M.Prevost: None. A.Brazeau: Research Support; Eli Lilly and Company, Novo Nordisk, Sanofi. S.Hart: None. M.Maldaner: None. J.E.Yardley: Research Support; Abbott, Dexcom, Inc., LifeScan, Speaker's Bureau; Abbott Diabetes. Funding Heart and Stroke Foundation of Canada, University of Alberta Undergraduate Research Initiative
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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 | 0.015 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".