Demographic and clinical correlates of accelerometer assessed physical activity and sedentary time in lung cancer survivors
Bibliographic record
Abstract
OBJECTIVE: To determine demographic and clinical correlates of accelerometer assessed physical activity and sedentary time among a population-based sample of lung cancer survivors. METHODS: Lung cancer survivors in Southern Alberta, Canada (N = 527) were invited to complete a mailed survey assessing socio-demographics and wear an Actigraph® GT3X+ accelerometer for 7 days. Average daily minutes of physical activity and sedentary time were derived from the accelerometer data. Accelerometer data were processed using standard Freedson cutpoints, and correlates of physical activity and sedentary time were determined with linear regression. RESULTS: A total of 127 lung cancer survivors participated (mean age = 71 years), for a 24% response rate. Moderate-to-vigorous physical activity was negatively associated with being >60 years of age (β = -7.4, CI: -14.7, -0.10). Moderate-to-vigorous physical activity accumulated in 10-minute bouts was associated with receiving surgery and adjuvant chemotherapy (β = 9.1, CI: 2.1, 16.1). Sedentary time was associated with being >60 years of age (β = 32.4, CI: 3.1, 61.7), smoking (β = 63.9, CI: 22.5, 105.4), and being overweight/obese (β = 28.6, CI: 6.4, 50.1). CONCLUSION: Age, smoking history, and body mass index emerged as correlates of accelerometer assessed light, moderate, and vigorous physical activity, and sedentary time among lung cancer survivors. IMPLICATIONS FOR CANCER SURVIVORS: Identifying correlates of physical activity and sedentary time may aid in the development of targeted behavioral interventions for this population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.000 |
| 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".