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Record W1561479070

Attitudes of clinicians at the Canadian Memorial Chiropractic College towards the chiropractic management of non-musculoskeletal conditions.

2011· article· en· W1561479070 on OpenAlexaffabout
Jodi Parkinson, Jennifer D. Lau, Sandeep Kalirah, Brian J Gleberzon

Bibliographic record

VenuePubMed · 2011
Typearticle
Languageen
FieldHealth Professions
TopicInfant Health and Development
Canadian institutionsCanadian Memorial Chiropractic College
Fundersnot available
KeywordsChiropracticAlternative medicineMedicineFamily medicinePhysical therapyMedical educationPathology
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of this study was to determine the attitudes of clinical faculty during the 2009-2010 academic year at the Canadian Memorial Chiropractic College towards the treatment of various non-musculoskeletal disorders. METHODS: A confidential survey was distributed to the clinical faculty via email. It consisted of several questions polling the demographic of the respondent such as years in clinical practice, and a list of 29 non-musculoskeletal conditions. Clinicians were asked to indicate their opinions on each condition on rating scale ranging from strongly agree to strongly disagree. RESULTS: Twenty of 22 clinicians responded. The conditions garnering the greatest positive ratings include: asthma, constipation, chronic pelvic pain, dysmenorrhea, infantile colic, and vertigo. The options regarding vertigo and asthma, while demonstrating an overall positive attitude towards the benefits of chiropractic care, were stratified amongst clinicians with varying years in clinical practice. CONCLUSION: This study suggests clinicians at this college are moderately open towards the chiropractic treatment of some non-musculoskeletal disorders.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.502
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.119
GPT teacher head0.392
Teacher spread0.274 · 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.

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

Citations3
Published2011
Admission routes2
Has abstractyes

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