The Effects of Repeated Thermal Therapy on Quality of Life in Patients with Type II Diabetes Mellitus
Bibliographic record
Abstract
OBJECTIVES: Decreased quality of life in diabetes is associated with poor health outcomes. Far-infrared sauna treatments improve the quality of life for those with chronic pain, chronic fatigue syndrome, depression, and congestive heart failure. The objective of this study is to determine whether far-infrared saunas have a beneficial effect on quality of life in those with type II diabetes. DESIGN: This was a sequential, longitudinal, interrupted time series design study. SETTING/LOCATION: The setting was Fraser Lake BC, a rural village in central British Columbia, Canada. SUBJECTS: All patients of the Fraser Lake Community Health Center with type II diabetes were invited to participate in this study. INTERVENTIONS: The study consisted of 20-minute, 3 times weekly infrared sauna sessions, over a period of 3 months. OUTCOME MEASURES: To assess quality of life, subjects completed the 36-item Short-form Health Survey Version 2 (SF-36v2) questionnaire as well as "Zero-to-Ten" Visual Analogue Scales. Baseline study parameters were measured within 1 week prior to commencing sauna sessions. Postintervention measurements were collected between 1 and 3 days after the last sauna session. RESULTS: Physical health, general health, and social functioning indices of the SF-36v2 improved. Visual Analogue Scales for stress and fatigue improved. CONCLUSIONS: Far-infrared sauna use maybe associated with improved quality of life in people with type II diabetes mellitus. Uptake of infrared saunas use is greater than the uptake of other lifestyle interventions.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".