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Record W2006717422 · doi:10.3109/13561820902886287

Integrative health care in a hospital setting: Communication patterns between CAM and biomedical practitioners

2009· article· en· W2006717422 on OpenAlexaff
Sophie Soklaridis, Merrijoy Kelner, Rhonda Love, J. David Cassidy

Bibliographic record

VenueJournal of Interprofessional Care · 2009
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsUniversity of TorontoToronto Western HospitalUniversity Health Network
Fundersnot available
KeywordsScope (computer science)Scope of practiceHealth careIntegrative medicineNursingFocus groupQualitative researchMedicineMedical educationAlternative medicineSociology

Abstract

fetched live from OpenAlex

Research in the area of collaboration between complementary and alternative medicine (CAM) and biomedical practitioners often describes their relationships as fraught with power struggles. This paper explores communication among the various stakeholders at an integrative health clinic for artists located in a university hospital. Qualitative research methods were used, in-depth interviews and semi-structured focus groups, to facilitate the gathering of information about patterns of communication among stakeholders involved at the clinic. The findings describe the challenges to communication and integration at the clinic. The lack of communication is described as a scheduling issue, or lack of consistent presence of CAM practitioners, and a lack of formal methods of communication (patient charting). The consequences of these gaps were felt mostly by the CAM practitioners, as their scope of practice was not well understood by other practitioners. CAM practitioners stated that this had a direct effect on their confidence levels. CAM practitioners were relegated to the periphery of the hospital in their role as part-time, contract employees. Their lack of consistent presence at the clinic lead to a lack of understanding of their scope of practice, hence, a lack of referrals from other health-care practitioners, particularly those who were biomedically-oriented.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score0.349

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.391
Teacher spread0.377 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations29
Published2009
Admission routes1
Has abstractyes

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