Sustained Benefits of Exercise-based Motivational Interviewing, but Only among Nonusers of Opioids in Patients with Fibromyalgia
Bibliographic record
Abstract
OBJECTIVE: Given the known side effects of opioids and their potential effects on cognition, we sought to evaluate the benefits of motivational interviewing (MI) to promote physical activity on 2 subsets of participants with fibromyalgia (FM): nonusers and users of opioids. METHODS: This was a secondary data analysis of a 36-week randomized controlled trial to assess the efficacy of MI to promote physical activity among participants with FM. Participants were randomized to 1 of 2 treatment arms: 6 phone-based MI sessions (n = 107) or 6 sessions of FM self-management instructions [attention control (AC), n = 109]. The primary outcomes were changes in physical function (Medical Outcomes Study Short Form-36), pain severity (Brief Pain Inventory), global FM symptom severity (Fibromyalgia Impact Questionnaire), and the amount of light to moderate physical activity (LMPA) from baseline to each followup visit. At study entry, subjects were categorized as opioid nonusers versus users. Repeated measures ANOVA was used to assess treatment effects adjusting for potential confounders. RESULTS: Of the 216 participants, 145 (67%) were nonusers and 71 (33%) were opioid users. Among nonusers, MI was associated with improved physical function, reduced pain severity, and global FM severity, and increased LMPA at 6-month followup. Among opioid users, there were no significant differences in any outcome measures between the MI and AC groups. CONCLUSION: Exercise-based MI was associated with sustained clinical benefits 6 months after completion of therapy, but only for those who were not taking opioids.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".