Integrative health care – What are the relevant health outcomes from a practice perspective? A survey
Bibliographic record
Abstract
BACKGROUND: Integrative health care (IHC) is an innovative approach to health care delivery. There is increasing focus on and demand for the evaluation of IHC practices. To ensure such evaluations capture their full scope, a clear understanding of the types of outcomes relevant to an IHC approach is needed. The objective was to describe the health domains and health outcomes relevant to IHC practices in Canada. METHODS: An online survey of Canadian IHC clinics. Survey questions were informed by the IN-CAM Health Outcomes Database. Descriptive statistics were used to summarize the data. Chi square tests were used to compare responses between clinic types and patient groups served. RESULTS: Surveys were completed by 21 clinics (response rate: 50%). Physical, psychological, social, individualized and holistic were identified as applicable health domains by more than 90% of the clinics. Spiritual domain was the least relevant (70% of clinics). A number of relevant outcomes within each domain were identified. A core set of outcomes were identified and included: fatigue, anxiety, stress, and patient-provider relationship, and quality of life. Clinics with primarily conventional health practitioners were less likely to address overall well-being (p = 0.04), while clinics that provided care to a specialized patient population (i.e. cancer patients) or a mix of general and specialized patients were less likely to address religious practices (p = 0.04) or spiritual experiences (p = 0.007). CONCLUSIONS: Outcomes across health domains should be considered in the evaluation of IHC models to generate an understanding of the full scope of effectiveness of IHC approaches. The core set of outcomes identified may facilitate this task. Ethics approval (Ethics ID REB14-0495) was received from the Conjoint Health Research Ethics Board at the University of Calgary.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 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".