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Record W2891455677 · doi:10.1089/acm.2018.0255

Naturopathic Approaches to Irritable Bowel Syndrome—A Delphi Study

2018· article· en· W2891455677 on OpenAlexaff
Joshua Z. Goldenberg, Lesley Ward, Andrew S. Day, Kieran Cooley

Bibliographic record

VenueThe Journal of Alternative and Complementary Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsCanadian Forces CollegeCanadian College of Naturopathic Medicine
Fundersnot available
KeywordsMedicineNaturopathyIrritable bowel syndromeAlternative medicineDelphi methodPsychological interventionDelphiPopulationIntegrative medicineRandomized controlled trialFunctional gastrointestinal disorderTraditional medicineFamily medicinePsychiatrySurgeryEnvironmental health

Abstract

fetched live from OpenAlex

INTRODUCTION: Irritable bowel syndrome (IBS) affects 11% of the population, and up to 50% of patients report using complementary and alternative medicines (CAM) for it. To date, there is no research describing how providers of naturopathic medicine in North America, a well-defined CAM profession, approach IBS. METHODS: A Delphi study was conducted over a 17-month period in 4 rounds with 15 North American naturopathic medicine experts in IBS. Consensus was defined as a median value of 75% or greater agreement with the relevant statement. RESULTS: Consensus was met with 45 statements describing a "reasonable naturopathic approach" to IBS. These statements covered the domains of general, office visits, tracking progress, testing, interventions, and resources. CONCLUSION: These results represent the beginning of an evidence base depicting naturopathic interventions for IBS and should inform future randomized controlled clinical trials in this area. Future research should look to reflect on and revise these guidance consensus statements particularly extending to other stakeholders as well as geographic and regulatory jurisdictions in the naturopathic profession.

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)0.002
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 score0.105
Threshold uncertainty score0.726

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.226
GPT teacher head0.359
Teacher spread0.134 · 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

Citations9
Published2018
Admission routes1
Has abstractyes

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