A proof-of-concept study on the impact of a chronic pain and physical activity training workshop for exercise professionals
Bibliographic record
Abstract
OBJECTIVES: Physical activity is essential for long-term chronic pain management, yet individuals struggle to participate. Exercise professionals, including fitness instructors, and personal trainers, are preferred delivery agents for education and instruction on chronic pain, physical activity, and strategies to use adherence-promoting behavioral skills. However, exercise professionals receive no relevant training during certification or continuing education opportunities to effectively support their participants living with chronic pain. Based on the ORBIT model for early pre-efficacy phases of development and testing of new behavioral treatments, the present Phase IIa proof-of-concept study was conducted. The purpose was to examine the impacts of a newly developed chronic pain and physical activity training workshop on psychosocial outcomes among exercise professionals. Outcomes included knowledge and attitudes regarding chronic pain, attitudes and beliefs about the relationship between pain and impairment, and self-efficacy to educate and instruct participants with chronic pain. METHODS: =44.4±11.0 years) participated in a three-hour, in-person workshop that was offered at one of four different locations. Participants completed pre- and post-workshop outcome assessment surveys. RESULTS: 's<0.001), demonstrating large effect sizes (partial eta-squared values ranging from 0.45 to 0.59). CONCLUSIONS: Findings offer early phase preliminary support for the effectiveness of the chronic pain and physical activity training workshop for exercise professionals. Based on ORBIT model recommendations, findings warrant future phased testing via a pilot randomized clinical trial as well as testing for impacts that trained professionals have on activity adherence among their clients living with chronic pain. Eventual workshop adoption by exercise professional certification organizations would ensure widespread and sustainable access to qualified exercise professionals to help individuals engage in physical activity. By increasing the capacity of available exercise professionals to deliver effective support, active individuals could better manage their chronic pain and live well.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".