Assessing Efficacy of Complementary Medicine: Adding Qualitative Research Methods to the "Gold Standard"
Bibliographic record
Abstract
Randomized controlled trials (RCTs) have an important place in the assessment of the efficacy of complementary and alternative medicine (CAM). However, they address only one, limited, question, namely whether an intervention has-statistically-an effect. They do not address why the intervention works, how participants are experiencing the intervention, and/or how they give meaning to these experiences. Therefore, we argue that the addition of qualitative research methods to RCTs can greatly enhance understanding of CAM interventions. Qualitative research can assist in understanding the meaning of an intervention to patients as well as patients' beliefs about the treatment and expectations of the outcome. Qualitative research also assists in understanding the impact of the context and the process of the intervention. Finally, qualitative research is helpful in developing appropriate outcome measures for CAM interventions. Greater understanding of CAM interventions has the potential to improve health care delivery.
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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 | 0.466 | 0.487 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.020 | 0.013 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.014 | 0.028 |
| Open science | 0.007 | 0.017 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".