Integrative Health Care: How Can We Determine Whether Patients Benefit?
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
OBJECTIVE: Evaluation of integrative health care (IHC) models is becoming increasingly important. One of the areas that requires further attention is the development of an appropriate set of outcome measures. The purpose of this study was: (1) to identify how cancer patients phrase and frame the beneficial outcomes they experienced from IHC, and (2) to develop recommendations for an appropriate outcome measures package for evaluation of IHC. DESIGN: This study involved two different parts: (1) a secondary analysis of qualitative data consisting of transcripts from 42 personal interviews and three focus groups from previous studies related to IHC use by cancer patients; and (2) a content analysis of goal-setting data collected from patients attending an IHC clinic to categorize the type and range of their treatment goals. RESULTS: Six types of benefits were identified: physical well-being, change in physiological indicators, improved emotional well-being, personal transformation, feeling connected, global state of well-being, and cure. Types of goals identified by patients confirmed these benefits and include: to improve state of being, to be cancer free, to have more energy, more effective pain management, and improved quality of life. CONCLUSIONS: A patient's perspective is crucial in understanding the process and outcomes of intentional selfhealing. Assessing self-identified goals suggests the need for patient empowerment through participation in outcome evaluation. We present recommendations for an appropriate outcomes package that is relevant, practical, and based on patient experiences.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 it