Provider Support in Complementary and Alternative Medicine: Exploring the Role of Patient Empowerment
Bibliographic record
Abstract
BACKGROUND: The quality of the patient-provider relationship is well-recognized as having a key role in therapeutic outcomes irrespective of treatment effects. Yet there is a lack of scales to assess aspects of complementary and alternative medicine (CAM) provider support. OBJECTIVES: The objectives of this study were to develop and psychometrically evaluate scales to measure patients' perceptions of provider support, patient-centered care, and empowerment as predictors of health outcomes. METHODS: Based on five focus groups with CAM clients, we developed the following three scales: Perceived Provider Support, Patient-Centered Care (PCC), and Empowerment. The scales were cognitively tested with 6 CAM users and then pilot-tested with 216 respondents. Confirmatory factor analyses, item response theory analyses, and Cronbach's alphas were conducted to evaluate their psychometric properties. Bootstrapping techniques and structural equation modeling were used to evaluate Empowerment as a mediator of the relationship of Perceived Provider Support and PCC with symptom relief. RESULTS: All three scales demonstrated high internal consistency with Cronbach's alphas of 0.85 to 0.90 and confirmatory factor analyses supported a one-factor solution for each scale. Controlling for demographics, presenting problem, and main CAM provider used in the past 12 months, each of the scales had a positive and significant relationship with overall symptom relief for the patient's primary presenting problem (p < .01). Bootstrapped Sobel tests were significant (p < .01), supporting the role of empowerment as a mediator of the impact of PCC and provider support on symptom relief. A structural equation model combining PCC and provider support into a single latent variable representing quality of patient-provider interactions and including empowerment as a mediator fit well. CONCLUSIONS: From a holistic perspective, CAM treatment effects can arise in part from sources related to the therapeutic relationship, as well as the philosophy of healing and specific techniques designed to reduce symptoms. This analysis provides conceptual support for this perspective, a means to evaluate aspects of the therapeutic relationship and to measure its impact on outcomes of CAM treatment across conditions and therapies.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 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".