Indirect associations of pain resilience and kinesiophobia with the relationship between physical activity and chronic pain
Bibliographic record
Abstract
BACKGROUND: Pain is associated with a decrease in physical activity for most individuals. Nevertheless, some individuals manage to maintain physical activity levels despite pain. While the exact psychological mechanisms behind this are unknown, it may possibly be due to low kinesiophobia and high pain resilience levels. This study aimed to examine the direct and indirect associations of pain resilience and kinesiophobia with the relationship between pain and physical activity. METHODS: In this cross-sectional study data were collected from 172 participants suffering from chronic pain. Three path models were fitted to assess the indirect associations between pain resilience and kinesiophobia in the relationship between physical activity and musculoskeletal pain individually and simultaneously. Additionally, a linear regression model was fitted to examine the impact of psychological predictors of physical activity while accounting for musculoskeletal pain. RESULTS: Significant proportions of the association between musculoskeletal pain on physical activity occurred through both pain resilience and kinesiophobia. Nevertheless, when examined simultaneously, only the indirect associations via pain resilience remained significant. Similarly, when predicting physical activity levels, only high levels of pain resilience and male gender were associated with increased physical activity levels, whereas kinesiophobia was not. CONCLUSIONS: This highlights the central role pain resilience plays in retaining physical activity levels when faced with chronic pain. It also implies that pain resilience predicts physical activity levels beyond pain intensity, kinesiophobia, pain duration, and pain spread. It is, therefore, imperative to examine avenues of increasing pain resilience among individuals suffering from chronic pain, not only to improve their pain, but also their overall health and well-being. This possibly bears implications for clinical practice and may inform treatment approaches, whereby pain resilience may be boosted to increase physical activity levels. Nevertheless, given the cross-sectional design, longitudinal and experimental studies are needed to confirm the causal pathways.
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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".