Practitioners' validation of framework of team-oriented practice models in integrative health care: a mixed methods study
Bibliographic record
Abstract
BACKGROUND: Biomedical and Complementary and Alternative Medicine (CAM) academic and clinical communities have yet to arrive at a common understanding of what Integrative healthcare (IHC) is and how it is practiced. The Models of Team Health Care Practice (MTHP) framework is a conceptual representation of seven possible practice models of health care within which teams of practitioners could elect to practice IHC, from an organizational perspective. The models range from parallel practice at one end to integrative practice at the other end. Models differ theoretically, based on a series of hypotheses. To date, this framework has not been empirically validated. This paper aims to test nine hypotheses in an attempt to validate the MTHP framework. METHODS: Secondary analysis of two studies carried out by the same research team was conducted, using a mixed methods approach. Data were collected from both biomedical and CAM practitioners working in Canadian IHC clinics. The secondary analysis is based on 21 participants in the qualitative study and 87 in the quantitative study. RESULTS: We identified three groups among the initial seven models in the MTHP framework. Differences between practitioners working in different practice models were found chiefly between those who thought that their clinics represented an integrative model, versus those who perceived their clinics to represent a parallel or consultative model. Of the scales used in the analysis, only the process of information sharing varied significantly across all three groups of models. CONCLUSIONS: The MTHP framework should be used with caution to guide the evaluation of the impact of team-oriented practice models on both subjective and objective outcomes of IHC. Groups of models may be more useful, because clinics may not "fit" under a single model when more than one model of collaboration occurs at a single site. The addition of a hypothesis regarding power relationships between practitioners should be considered. Further validation is required so that integrative practice models are well described with appropriate terminology, thus facilitating the work of health care practitioners, managers, policy makers and researchers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".