Self-management experiences among men and women with type 2 diabetes mellitus: a qualitative analysis
Bibliographic record
Abstract
BACKGROUND: The purpose of this study is to better understand differences in diabetes self-management, specifically needs, barriers and challenges among men and women living with type 2 diabetes mellitus (T2DM). METHODS: 35 participants were recruited from a diabetes education center (DEC) in Toronto, Canada. Five focus groups and nine individual interviews were conducted to explore men and women's diabetes self-management experiences. RESULTS: The average age of participants was 57 years and just over half (51.4%) were female. Analyses revealed five themes: disclosure and identity as a person living with diabetes; self-monitoring of blood glucose (SMBG); diet struggles across varying contexts; utilization of diabetes resources; and social support. Women disclosed their diabetes more readily and integrated management into their daily lives, whereas men were more reluctant to tell friends and family about their diabetes and were less observant of self-management practices in social settings. Men focused on practical aspects of SMBG and experimented with various aspects of management to reduce reliance on medications whereas women focused on affective components of SMBG. Women restricted foods from their diets perceived as prohibited whereas many men moderated their intake of perceived unhealthy foods, except in social situations. Women used socially interactive resources, like education classes and support groups whereas men relied more on self-directed learning but also described wanting more guidance to help navigate the healthcare system. Finally, men and women reported wanting physician support for both affective and practical aspects of self-management. CONCLUSIONS: Our findings highlight the differences in needs and challenges of diabetes self-management among men and women, which may inform gender-sensitive diabetes, care, counseling and support.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".