It's Not Too Hard! Perceived Enjoyment for High-intensity Interval Training in Type 2 Diabetes
Bibliographic record
Abstract
Despite accumulating evidence that high-intensity interval training (HIT) can improve physical fitness, the feasibility of encouraging sedentary individuals to engage in such vigorous training is unclear. Although a negative relationship between exercise intensity and perceived enjoyment has been suggested, the reduced time commitment and rest periods built into interval training may make HIT more appealing than traditional continuous endurance-oriented training. PURPOSE: To explore the receptiveness to HIT in individuals with prediabetes and type 2 diabetes before and after a 2 wk HIT intervention. METHODS: Four patients with type 2 diabetes and three prediabetics (fasting blood glucose >6.1 mmol/L) performed six sessions of HIT over 2 wk. Each session consisted of 10 × 1-min cycling intervals at ∼90% maximal heart rate separated by 1 min recovery. Perceived enjoyment of engaging in 20 min of HIT (HIT), 30 min of continuous moderate intensity exercise (30CON), and 60 min of continuous moderate intensity exercise (60CON) was assessed before and after the 2 wk training period. Self-efficacy for adhering to each exercise modality as a means of controlling diabetes was also assessed. Perceived differences in enjoyment and self-efficacy between HIT, 30CON, and 60CON were compared using ANOVA pre- and post-training. RESULTS: Perceived enjoyment pre-training tended to favor 30CON (p =.09). Post-training, however, participants rated HIT as more enjoyable (8.3±.0.3) than engaging in 30CON (7.6±0.4) or 60CON(5.0±0.5; p <.001). Differences between self-efficacy scores post-training approached significance (p =.07). Specifically, self-efficacy to perform HIT (91.4±2.6) was greater than efficacy to perform either 30CON (88.6±4.0) or 60CON (80.0±5.3) over the next month. CONCLUSION: These preliminary findings suggest that HIT can be perceived as enjoyable in individuals with type 2 diabetes and prediabetes, and a short-term intervention can increase self-efficacy to engage in HIT in the future.
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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 | 0.003 |
| 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 | 0.001 | 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".