Expectancy after the first treatment and response to acupuncture for menopausal hot flashes
Bibliographic record
Abstract
BACKGROUND: Evidence on the impact of expectancy on acupuncture treatment response is conflicting. OBJECTIVES: This secondary analysis of a randomized sham-controlled trial on acupuncture for menopausal hot flashes investigated whether treatment expectancy score was associated with hot flash score at end-of-treatment. Secondary analyses investigated whether there were associations between other pre-specified factors and hot flash score. STUDY DESIGN: Women experiencing moderately-severe hot flashes were randomized to receive 10 sessions of real or sham acupuncture over eight weeks. Hot flash score was collected using a seven-day hot flash diary, and expectancy using the modified Credibility and Expectancy Questionnaire immediately after the first treatment. Linear mixed-effects models with random intercepts were used to identify associations between expectancy score and hot flash score at end-of-treatment. Regression was also used to identify associations between pre-specified factors of interest and hot flash score. Because there was no difference between real and sham acupuncture for the primary outcome of hot flash score, both arms were combined in the analysis. RESULTS: 285 women returned the Credibility and Expectancy Questionnaire, and 283 women completed both expectancy measures. We found no evidence for an association between expectancy and hot flash score at end-of-treatment for individual cases in either acupuncture or sham group. Hot flash scores at end-of-treatment were 8.1 (95%CI, 3.0 to 13.2; P = 0.002) points lower in regular smokers compared to those who had never smoked, equivalent to four fewer moderate hot flashes a day. CONCLUSION: In our study of acupuncture for menopausal hot flashes, higher expectancy after the first treatment did not predict better treatment outcomes. Future research may focus on other determinants of outcomes in acupuncture such as therapist attention. The relationship between smoking and hot flashes is poorly understood and needs further exploration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 teacher head, 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".