Examining the utility of exercise-related cognitive errors in predicting physical activity across 12-week fitness programmes
Bibliographic record
Abstract
Social cognitive theories often assume that information is acted upon in a rational manner. While theorists acknowledge biased perceptions exist, their theories do not include factors representing these inaccurate perceptions. Exercise-related cognitive errors (ECEs) may be such a factor that is associated with physical activity adherence beyond established predictors, like self-efficacy or past behaviour. The purpose of this study was to examine whether ECEs change across participants’ 12-week fitness programmes and examine whether ECEs predicted moderate-to-vigorous physical activity (MVPA) and self-regulatory efficacy (SRE). A sample of N = 93 adults (Mage = 54.8, SD = 12.8 years; 86% female, 14% male) who signed up for various group fitness classes were recruited to participate in this study. ECEs did not change across the 12-week fitness programmes (p > .05). Mid-programme ECEs significantly predicted post-programme SRE and MVPA beyond pre-programme SRE and MVPA (R2MVPA = 0.44, p < .001, R2 self-efficacy = 0.65, p < .001). The path model fit the data, further supporting these associations (CFI = .994, Χ2 = 7.74, p = .17). Those who missed at least one class reported higher ECEs (M = 4.58, SD = 1.49) compared to those who did not miss any classes (M = 3.55, SD = 1.50; t = 2.35, p < .05, Cohen’s d = 0.69). While certain analyses were limited by a small sample size, ECEs might be a useful concept that represents biased or inaccurate thinking useful in understanding physical activity attendance. Findings implicate ECEs as a factor that may predict non-adherence in physical activity interventions, highlighting biased thinking as a potential mechanism to target in interventions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".