A Comparison of the Characteristics of Acupuncture- and Non–Acupuncture-Preferred Consumers: A Secondary Analysis of NHIS 2012 Data
Bibliographic record
Abstract
OBJECTIVES: To determine whether acupuncture use, sociodemographic characteristics, and existing health conditions differ between acupuncture-preferred consumers (i.e., those who deem acupuncture to be one of the three most important complementary and alternative medicine [CAM] modalities used) and non-acupuncture-preferred consumers who used acupuncture in the past 12 months METHODS: This is a secondary analysis of the National Health Interview Survey Sample Adult File and Adult Alternative Medicine datasets collected by the Centers for Disease Control and Prevention during 2012. The sample was drawn from the noninstitutionalized civilian population of the United States. The datasets yielded 34,525 respondents aged 18 years and older. Measures included in the analysis were acupuncture use in the past 12 months, sociodemographic characteristics, and existing health conditions. Analyses were performed by using Stata software, version 9.0 (Stata Corp., College Station, TX). RESULTS: Of the 10,158 adults who responded to the question regarding the "three most important" CAM modalities used, 572 (5.6%) had used acupuncture in the past 12 months. Of these, 456 (79.7%) chose acupuncture as one of the top three CAM modalities most important to their health. Acupuncture-preferred consumers reported significantly more visits to acupuncturists (7.46 versus 3.99 visits; p < 0.001), as well as higher out-of-pocket costs ($342.8 versus $246.4; p < 0.001), compared with non-acupuncture-preferred consumers. The logistic regression model revealed that with every additional CAM modality used, the likelihood of deeming acupuncture as one of the three CAM modalities most important to one's health decreased by 39% (odds ratio, 0.61; 95% confidence interval, 0.52-0.71; p < 0.001). Health conditions were not statistically significant predictors. CONCLUSIONS: A consumer's preference for acupuncture appeared not to be driven by health conditions but rather was related to sociodemographic factors. This suggests that health education regarding acupuncture may need to be tailored to certain consumer groups, such as those residing in the South, and could provide more information on the comparative effectiveness of acupuncture for various health conditions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".