Approach-Avoidance Tendencies Moderate the Relationship Between Fear of Movement and Physical Activity in Osteoarthritis
Bibliographic record
Abstract
Research Question: Do psychological processes, such as explicit attitudes and approach-avoidance tendencies toward physical activity, mediate or moderate the relationship between fear of movement and usual physical activity levels among people with osteoarthritis? Method: We conducted an online observational study with 197 participants, including 68 with osteoarthritis. Using questionnaires, we assessed arthritis, fear of movement, usual physical activity level, and explicit attitudes. Approach-avoidance tendencies, an indicator of automatic attitudes, were derived from reaction times in an approach-avoidance task. Results: Results showed that higher fear of movement was associated with lower physical activity levels among participants with osteoarthritis. This association was moderated by approach-avoidance tendencies toward physical activity, with a significant effect only among participants with an automatic tendency to avoid physical activity or a weak tendency to approach it. Conclusions: This study suggests that, among adults with osteoarthritis, the detrimental effect of fear of movement on usual physical activity levels may be mitigated by strong automatic tendencies to approach physical activity. Because these tendencies result from the automatic activation of affective memories, health professionals should consider not only promoting physical activity but also ensuring its association with positive emotional experiences.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".