Age and Attitudes Towards an Internet-Mediated, Pedometer-Based Physical Activity Intervention for Chronic Obstructive Pulmonary Disease: Secondary Analysis
Bibliographic record
Abstract
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is prevalent among older adults. Promoting physical activity and increasing exercise capacity are recommended for all individuals with COPD. Pulmonary rehabilitation is the standard of care to improve exercise capacity, although there are barriers that hinder accessibility. Technology has the potential to overcome some of these barriers, but it is unclear how aging adults with a chronic disease like COPD perceive technology-based platforms to support their disease self-management. OBJECTIVE: Guided by the unified theory of acceptance and use of technology, the current retrospective secondary analysis explores if age moderates multiple factors that influence an individual with COPD's openness toward an internet-mediated, pedometer-based physical activity intervention. METHODS: As part of an efficacy study, participants with COPD (N=59) were randomly assigned to use an internet-mediated, pedometer-based physical activity intervention for 12 weeks. At completion, they were asked about their experience with the intervention using a survey, including their performance expectancy and effort expectancy, facilitating conditions (ie, internet use frequency and ability), and use of the intervention technology. Logistic regression and general linear modeling examined the associations between age and these factors. RESULTS: Participants ranged in age from 49 to 89 years (mean 68.66, SD 8.93). Disease severity was measured by forced expiratory volume in the first second percent predicted (mean 60.01, SD 20.86). Nearly all participants (54/59) believed the intervention was useful. Regarding effort expectancy, increasing age was associated with reporting that it was easy to find the time to engage in the intervention. Regarding facilitating conditions, approximately half of the participants believed the automated step count goals were too high (23/59) and many did not feel comfortable reaching their goals (22/59). The probability of these perceptions increased with age, even after accounting for disease severity. Age was not associated with other facilitating conditions or use of the technology. CONCLUSIONS: Age does not influence performance expectancy or use of technology with an internet-mediated, pedometer-based physical activity intervention. Age is associated with certain expectations of effort and facilitating conditions. Consideration of age of the user is needed when personalizing step count goals and time needed to log in to the website. TRIAL REGISTRATION: ClinicalTrials.gov NCT01772082; https://clinicaltrials.gov/ct2/show/NCT01772082.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".