Move More Mommy: A postnatal ehealth physical activity intervention (pilot study)
Bibliographic record
Abstract
The purpose of this study was to assess the feasibility of a theory-based cognitive behavioural skills training eHealth physical activity intervention.. Twenty (n=20) postnatal women were recruited to participate in an 8-week pilot study. All participants met once a week for a 45-minute bootcamp-style group exercise class (n=10 per class) taught by a certified instructor. The cognitive behavioural skills training aspect of the intervention was delivered to all participants through a purpose-built website, www.movemoremommy.com. Participants were asked to log into the website each week to view a short video, make action plans and track their physical activity. Furthermore, participants had access to a discussion board and were prompted to post a message each week. Intervention feasibility was assessed using an-11 item feedback questionnaire as well as monitoring website use (e.g, action planning calendar, self-monitoring calendar and the discussion board). A self-report measure of physical activity was collected at baseline and post intervention (week 8). Overall, intervention feedback was extremely positive, (M=1.35, SD=36, Range = -2 to 2). On average, participants used the online action planning calendar 78% of time and the self-monitoring calendar 69% of the time. Over the 8-week intervention, the average number of discussion board posts was 6.5. Total MVPA significantly increased by 76.89 minutes per week (SD=120.1) from baseline to post intervention, t=-2.63, p=.018. These results indicate that delivering a theory-based intervention via website is a feasible and effective method of increasing physical activity in the postnatal population.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".