Evaluating complementary and alternative medicine interventions: in search of appropriate patient-centered outcome measures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Central to the development of a sound evidence base for Complementary and Alternative Medicine (CAM) interventions is the need for valid, reliable and relevant outcome measures to assess whether the interventions work. We assessed the specific needs for a database that would cover a wide range of outcomes measures for CAM research and considered a framework for such a database. METHODS: The study was a survey of CAM researchers, practitioners and students. An online questionnaire was emailed to the members of the Canadian Interdisciplinary Network for CAM Research (IN-CAM) and the CAM Education and Research Network of Alberta (CAMera). The majority of survey questions were open-ended and asked about outcome measures currently used, outcome measures' assessment criteria, sources of information, perceived barriers to finding outcome measures and outcome domains of importance. Descriptive quantitative analysis and qualitative content analysis were used. RESULTS: One hundred and sixty-four completed surveys were received. Of these, 62 respondents reported using outcome measures in their CAM research and identified 92 different specific outcomes. The most important barriers were the fact that, for many health concepts, outcome measures do not yet exist, as well as issues related to accessibility of instruments. Important outcome domains identified included physical, psychological, social, spiritual, quality of life and holistic measures. Participants also mentioned the importance of individualized measures that assess unique patient-centered outcomes for each research participant, and measures to assess the context of healing and the process of healing. CONCLUSION: We have developed a preliminary framework that includes all components of health-related outcomes. The framework provides a foundation for a larger, comprehensive collection of CAM outcomes. It fits very well in a whole systems perspective, which requires an expanded set of outcome measures, such as individualized and holistic measures, with attention to issues of process and context.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it