Expectancy Reduces Symptoms but not Functional Impairment Following Exercise-induced Musculoskeletal Injury
Bibliographic record
Abstract
OBJECTIVES: To quantify the extent to which the participant-provider interaction influences the response to sham treatment following exercised-induced acute musculoskeletal pain. MATERIALS AND METHODS: In total, 40 participants between the ages of 18 and 35 volunteered for the study. Participants came to the laboratory for 3 test sessions 48-hour apart (day 1, 3, and 5). During the initial session, baseline measures were assessed and participants underwent a fatigue protocol for the biceps brachii. Participants were then assigned to a positive expectation or a no-expectation condition before receiving a sham laser therapy treatment. The positive expectation group received symptom improvement priming before their sham treatment. Participants allocated to the no-expectation condition received no feedback before the sham treatment. Maximum voluntary isometric contraction; relaxed elbow angle; visual analog scale; and the QuickDash questionnaire were used as outcome measures. RESULTS: The positive expectation group had a significant reduction in perceived pain compared with the no-expectation group at day 3 follow-up, with the mean scores being 34.65 mm (SE=4.44) compared with 49.4 mm (SE=5.79), respectively. There were no between-group differences with respect to maximum voluntary isometric contraction, QuickDash, or relaxed elbow angle outcomes. In addition, there were no significant between-group differences observed with expected pain on follow-up visits, the effect sizes were d=0.26 on day 1 for day 3 and d=0.51 on day for day 5. DISCUSSION: Positive expectations before a sham treatment enhanced reduction in pain intensity but did not improve functional impairments following exercise-induced acute musculoskeletal injury.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.003 | 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".