Specific Impact of Kinesiologist in Lifestyle Intervention Outcomes for Prediabetic Adults
Bibliographic record
Abstract
Lifestyle intervention for prediabetic adults aims to delay or avoid type 2 diabetes by increasing physical activity and decreasing body weight. However, the optimal team composition to reach different outcomes is not well known. PURPOSE: To determine the independent effect of each healthcare professional and the frequency of contacts on changes in anthropometric measures, physical activity level, energy intake and functional capacity. METHODS: A 12-month interdisciplinary lifestyle intervention was performed in 49 pre-diabetic adults. Patients were randomly assigned to two different groups: 1- individual counselling + proposed weekly group seminars (IN+SE) or 2- proposed weekly group seminars (SE). Individual counselling consisted of nine contacts (every six weeks) by a physician, a nurse and a dietician. Weekly group seminars were given by a physician, a dietician, a kinesiologist or a psychologist. Anthropometric measures, physical activity level, energy intake, and physical capacity (6-minute walk test) were studied. RESULTS: The IN+SE group improved anthropometric measures, physical capacity and decreased energy intake (all P≤0.05). The SE group only significantly improved physical capacity (P≤0.01) No physical capacity improvement between groups as observed groups (P=.35). Total frequency of contacts was associated with changes in body weight, BMI, and waist circumference (all P≤0.05) while no specific professional contacts was associated with studied outcomes. However, changes in physical capacity was significantly greater in patients who attended at least two group sessions with the kinesiologist (P=0.02) while no such observation was observed for other specific health professional or outcomes. CONCLUSION: This study suggests that total contact frequency and / or individual counselling are important to achieve a significant change in anthropometric measures. However, two contacts with a kinesiologist may be enough to improve physical capacity in prediabetics adults. Supported by Lawson Foundation
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".