P05.66 . “It’s a regular part of my schedule, just like brushing my teeth”: the perceived fit of complementary and alternative medicine among young adults
Bibliographic record
Abstract
Undergraduate students (N = 359, mean age = 21.2, 86 % female) completed a survey about their use of CAM, self-perceptions of being health-minded, and how CAM fit into their health routine. Forty-four percent were currently using one or more CAM. CAM consumers (N=159) were significantly more health-minded than non-consumers, t(357) = 3.89. The CAM consumer responses to the open-ended question “Where does CAM use fit in with the things that you do to take care of your health issues, and/or things that you do to maximize your health and wellness?” were inductively tagged using qualitative content analysis and placed into categories reflecting common themes. Several key themes emerged from the responses. CAM was viewed as a means to deal with athletic injuries, to supplement other health promotion activities, to take care of body and mind, to prevent illness, and as a natural and holistic method for promoting health and well-being. These findings echo those of previous research indicating a growing role for CAM in promoting health and well-being and further suggest the ways in which this next generation of CAM consumers integrate CAM use into their lifestyle.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".