The Effects of a Low-Intensity Aerobic Exercise Program to Enhance Occupational Performance and Quality of Life in Diabetic Patients
Bibliographic record
Abstract
Globally, diabetes mellitus (DM) is a prevalent chronic condition many people encounter. DM is one of the primary causes of mortality due to individuals struggling to manage or prevent the condition. The healthcare field is also failing to provide sufficient education on DM. Individuals with this condition may begin to experience co-morbidities and depressive symptoms, which make it difficult for them to engage in meaningful occupations, in addition to decreased quality of life (QOL). This project examines the effectiveness of a low-intensity aerobic exercise (LIAE) program to enhance occupational performance (OP) and QOL in those diagnosed with the condition or at-risk, which was guided by the occupational performance process model and the problem-based learning theory. The objectives were to enhance engagement in desired occupations, provide guidance and resources to better manage or prevent DM, and increase awareness in the occupational therapy program. This project utilized a quasi-experimental, pretest-posttest design. Assessments utilized the Canadian Occupational Performance Measure (COPM) and the Perceived Quality of Life (PQOL) scale. These assessments incorporated a 10-point Likert scale to determine performance and satisfaction rates. Three participants from Encompass Health Rehabilitation Hospital in Henderson, Nevada took part in a one-week LIAE program lasting approximately 15-30 minutes per session. Each participant began their program during different weeks. The exercise program consisted of yoga, tai chi, boxing, and upper extremity strengthening. The results indicated a correlation between LIAE, OP, and QOL. It was concluded that LIAE can have beneficial impacts on OP and QOL in DM patients or those at-risk. However, the outcomes did not demonstrate statistical significance.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".