Explaining the Aerobic Exercise Intention-behavior Gap in Cancer Survivors
Bibliographic record
Abstract
OBJECTIVES: We sought to quantify the aerobic exercise intention-behavior gap in hematologic cancer survivors (HCS), and examine the correlates of intention formation and translation using the multi-process action control framework. METHODS: HCS (N = 606) completed a survey reporting their aerobic exercise motivation and behavior. The correlates of intention formation and translation were analyzed using separate logistic regressions. RESULTS: Overall, 71% (N = 428/606) of HCS intended to do aerobic exercise, 44% (N = 267/606) met aerobic exercise guidelines, and 60% of intenders (N = 256/428) translated their intention into aerobic exercise. Attitude (OR = 1.9), perceived control (OR = 1.5), younger age (OR = 2.0), and higher education (OR = 2.1) explained intention formation (all ps ≤ .001). A sense of obligation/regret (OR = 2.8), self-regulation over alternative activities (OR = 1.6), attitude (OR = 2.0), perceived control (OR = 1.7), planning (OR = 1.7), being female (OR = 2.0), and younger (OR = 3.0) explained intention translation (all ps < .005). CONCLUSIONS: Forming an intention is insufficient for many HCS to meet aerobic exercise guidelines. Interventions targeting the determinants of both intention formation and translation may be most effective in promoting aerobic exercise in cancer survivors.
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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 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".