Barriers and facilitators impacting the experiences of adults participating in an internet-facilitated pedometer intervention
Bibliographic record
Abstract
Objectives Internet-facilitated physical activity interventions are becoming more common. A better understanding about the barriers and facilitators experienced by participants is needed to improve the delivery and effectiveness of these types of interventions. Our study explored perceived individual, social, and physical environment characteristics that hinder or facilitate physical activity among previously “inactive” adults during a 12-week internet-facilitated pedometer intervention. Design Qualitative Study (qualitative description). Method Twenty-three participants (82.6% women; ages 24–68 years) who registered for the 12-week internet-facilitated pedometer intervention (UWALK) participated in telephone-administered semi-structured interviews. Interview questions explored perceived barriers and facilitators to physical activity during the UWALK intervention. Participants were purposefully sampled to represent various levels of engagement with UWALK. Results The experiences shared by participants were represented by four themes including: creating (in)activity awareness; commitment to physical activity; incorporating activity for transportation, and; importance of nature and changing scenery. Wearing the pedometer and recording their daily steps made participants more aware about time being sedentary. Moreover, participants developed strategies to help achieve their step goals. Active transportation was frequently mentioned as an effective way of increasing daily steps, and access to nature or beautiful scenery encouraged more physical activity. Conclusions Perceived individual and environmental factors contribute to participants’ ability to engage in UWALK and physical activity. Providing participants enrolled in internet-facilitated pedometer interventions with strategies for overcoming barriers, instructions for exploring their local environments, and approaches for incorporating active transportation into daily routines, may improve adherence and, ultimately, increase physical activity.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| 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".