Association of Fatigue with Physical Functioning, Postural Balance, and Fall Efficacy in Women with and without Type 2 Diabetes Mellitus
Bibliographic record
Abstract
Background: Type 2 diabetes mellitus significantly impacts patients' health-related quality of life (HRQoL), affecting physical, psychological, social, and emotional well-being. This study examined the differences in fatigue, postural balance, fall efficacy, and HRQoL among patients with and without type 2 diabetes across these critical domains. Methods: This cross-sectional study involved 37 females with type 2 diabetes (mean age 52.9 ± 7.3 years) who were recruited from a diabetes clinic, along with 16 healthy female participants. Fatigue, postural balance, fall efficacy, and HRQoL were measured using the Fatigue Severity Scale, Berg Balance Scale, the International Fall Efficacy Scale, and the 36-item Short-Form Survey questionnaire, respectively. Results: Fatigue scores were significantly higher in people with type 2 diabetes than healthy participants (d= 0.457; p= -0.01). No statistically significant differences in HRQoL were found between the groups, except for role limitations due to emotional problems (d = 0.36, p = 0.013) and social functioning (d = 0.51, p < 0.01). Participants with type 2 diabetes showed no significant differences in postural balance and fall efficacy compared to healthy subjects (p > 0.05). However, fatigue emerged as a significant predictor of physical functioning in individuals with type 2 diabetes but not in healthy participants. Conclusion: In conclusion, individuals with type 2 diabetes experience significantly higher fatigue levels, which predict physical functioning, while reporting greater limitations in social functioning and emotional health compared to healthy participants. Identifying these differences guides healthcare professionals in designing more personalized care strategies for individuals with type 2 diabetes.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".