Direct and Indirect Relationships Between Physical Activity, Fitness Level, Kinesiophobia, and Health-Related Quality of Life in Patients with Rheumatic and Musculoskeletal Diseases: A Network Analysis
Bibliographic record
Abstract
INTRODUCTION: Using a network analysis, the present study investigated the extent to which physical activity (PA), objective fitness level, kinesiophobia, and health-related quality of life (HRQoL) interact in patients with rheumatic and musculoskeletal diseases. The objectives were twofold: 1) to clarify the direct and indirect relationships between these variables while controlling for the shared variance between them, and 2) to establish a potential ranking of influence among them. METHODS: This cross-sectional design study involved patients recruited from a rheumatology unit. One hundred and twenty patients completed self-reported measures of PA, the Tampa scale of kinesiophobia and the 36-item Short-Form Health Survey, and ninety-seven of those patients performed the six-minute walking test and the thirty-second sit-to-stand test. Network analyses were conducted using bootnet and qgraph packages. RESULTS: Weekly time spent on PA, as well as physical fitness measures, were directly linked to kinesiophobia and the HRQoL physical dimension, but indirectly linked to HRQoL mental dimension through the mediation of kinesiophobia. Specifically, weekly PA time had direct relationships to physical functioning, vitality, and role limitations due to physical and emotional problems. Fitness measures had direct relationships with physical functioning, bodily pain, and mental health. The analyses did not clearly highlight one variable as the most influential in the network. DISCUSSION: The study highlights the complexities of direct and indirect biopsychosocial relationships that are at the core of patients' daily functioning. Measurement of PA, use of a longitudinal design, and interventions are discussed.
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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 | 0.015 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".