Validation Of A Brief Stages Of Change Instrument For The Goal Of 10,000 Steps Daily
Bibliographic record
Abstract
Maintaining a physically active lifestyle offers numerous benefits to health and well-being, but most adults are not sufficiently physically active. Various interventions have promoted adults’ physical activity levels, and the 10,000 steps campaign has been a popular and effective approach. Such interventions are often tailored for individuals, but few validated assessment instruments are currently available for determining Stages of Change according to the Transtheoretical Model. PURPOSE: To assess the criterion-related validity of a brief 10,000 steps per day Stages of Change instrument, using baseline data from the Walk 2.0 Study, a 3-arm RCT investigating the effects of Web 2.0 applications on engagement, retention, and physical activity behavior change. METHODS: The dataset (N=506 adults; 176 males, 330 females, mean age = 50.8±13.0 years) included 7-day accelerometry (Actigraph GT3X), and self-reported intention and Stages of Change relative to achieving 10,000 steps per day. Validity of the Stages of Change physical activity component was assessed in comparison to mean Actigraph step counts via ANOVA and logistic regression. Validity of the intention component was assessed in relation to a separate 2-item intention scale via ANOVA and Spearman correlation. RESULTS: Accelerometer-measured daily steps significantly differed among stages (F4,462 = 4.2; p = 0.001), and stages significantly predicted meeting the 10,000 steps per day goal (OR=1.51; 95%CI=1.18-1.93; ptrend = 0.001). Participants classified in action or maintenance stage were more than three times as likely to achieve ≥10,000 steps per day (OR=3.53; 95%CI=1.92-6.51) compared to those in pre-contemplation, contemplation, or preparation. Self-reported intention also differed significantly among stages (F4,501 = 36.6; p < 0.001), and there was a significant correlation between self-reported stage and intention to achieve 10,000 steps daily (rho = 0.371, p < 0.001). CONCLUSION: Participants in the action and maintenance stages showed highest accelerometer-based physical activity levels, and the intention to achieve 10,000 steps significantly differed by stage of change classification. This brief instrument appears to have suitable validity for determining Stages of Change related to the public health goal of 10,000 steps. This study was funded by the National Health and Medical Research Council (Project Grant number 589903).
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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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".