A qualitative exploration of affective experiences during exercise in an insufficiently active population
Bibliographic record
Abstract
Most Canadians are not sufficiently physically active to achieve health benefits. Retrospective and quantitative studies show that negative affective responses to exercise can have a negative influence on exercise participation and adherence. The dual-mode model states that affective responses are a result of two modes; (1) cognitive processes (e.g., self-efficacy) and (2) interoceptive cues elicited as a result of physiological responses; however, little is known about what (e.g., symptoms and emotions) exactly affects one's exercise experience. Therefore, the purpose of this study was to explore insufficiently active adults' experiences during an exercise bout with the use of a think-aloud protocol. Nine women (Mage = 21.11 years, SD = 1.83) participated in two sessions, one week apart. Session 1 involved a graded maximal exercise treadmill test to determine the work rate associated with the ventilatory threshold and session 2 involved exercising on a treadmill at three intensities for 6 minutes each while saying all of their thoughts aloud. The think aloud data were recorded and transcribed verbatim and analyzed using thematic content analysis. In line with the dual-mode model, our qualitative data showed that participants experienced more physiological symptoms (e.g., muscular, ventilation), above the ventilatory threshold, and expressed more exercise enjoyment and greater exercise self-efficacy below the ventilatory threshold. These findings provide rich insight into what insufficiently active individuals experience during exercise and how they perceive them. These findings could be used to educate new exercisers about what kind of symptoms one can experience during different exercise intensities, which could potentially help increase physical activity adherence.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".