Unpacking the debate: A qualitative investigation of first-time experiences with high-intensity and sprint interval exercise among men and women who are inactive
Bibliographic record
Abstract
Objective: There has been compelling debate about whether interval exercise should be promoted in public health strategies to increase physical activity participation, particularly among inactive populations. Despite a rapidly growing body of quantitative research, there is a notable absence of qualitative research on the topic. This study used a series of interviews conducted over time to develop a richer understanding of (1) inactive adults' experiences during and following moderate-intensity continuous training (MICT), high-intensity interval training (HIIT), and sprint interval training (SIT) trials completed in the laboratory; (2) how their perceptions of MICT, HIIT, and SIT changed over time and with experience; and (3) factors that may influence their ability to engage in real-world MICT, HIIT, and SIT. Methods: Thirty inactive young adults completed three trials of cycling exercise in a random order on separate days: MICT, HIIT, and SIT, and subsequently logged their free-living exercise over four weeks. Interviews were conducted at five timepoints and were subjected to a thematic analysis. Results: Three overarching themes were identified: (1) thoughts and beliefs about exercise, (2) physiological and psychological exercise experiences, (3) challenges with real-world exercise behaviour. Conclusions: The findings emphasize that people respond differently to different forms of exercise and their decisions to participate in interval or continuous exercise are far more complex than can be captured by quantitative methodologies alone. It appears that there is indeed a place for interval exercise in exercise plans and programs for the general population and interval exercise can be used concurrently with continuous exercise.
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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 | 0.015 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.013 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".