Correlates Of Exercise Behavior In Korean Cancer Patients: KNHANES 2014-2016
Bibliographic record
Abstract
PURPOSE: Most Korean cancer patients do not participate in sufficient physical activity. Understanding the determinants of exercise behavior is important to improve their physical activity level. The purpose of this study was to examine the correlates of meeting exercise guidelines in Korean cancer patients. METHODS: Data were obtained from the Korea National Health and Nutrition Examination Survey 2014-2016. We included 640 cancer patients who had been diagnosed with any type of cancer. Moderate and vigorous physical activity time and frequency of resistance exercise were assessed. Participants were categorized as meeting (1) aerobic only, (2) resistance only, (3) combined, or (4) neither exercise guideline based on the American College of Sports Medicine’s aerobic and resistance exercise guidelines for cancer survivors. Correlates included demographic, medical, and health-related fitness/quality of life variables. Univariate and stepwise multinomial logistic regression were used for statistical analyses. RESULTS: The percentage of participants meeting the combined, aerobic only, resistance only, and neither guideline were 7.5%, 11.4%, 13.0%, and 68.1%, respectively. In univariate analyses, age (p<0.001), sex (p=0.030), region (p=0.011), marital status (p=0.003), education level (p<0.001), and income (p<0.001) were associated with meeting the exercise guidelines among demographic variables. Time since cancer diagnosis (p=0.027) and the number of comorbidities (p=0.030) were associated with meeting the exercise guidelines among medical variables. Hand-grip strength (p<0.001), quality of life for mobility (p<0.001), quality of life for self-care (p=0.047), quality of life for pain/discomfort (p=0.004), and total quality of life index (p<0.001) were associated with meeting exercises guidelines among health-related fitness/quality of life variables. In stepwise multivariate multinomial logistic regression, younger age, higher education level, more hand-grip strength, and better quality of life for mobility independently predicted exercise behaviors. CONCLUSION: Physical activity level is insufficient in Korean cancer patients and their exercise behaviors were correlated with age, education level, muscular strength, and quality of life.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".