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Record W4317866231 · doi:10.7899/jce-21-47

An investigation into chiropractic intern adherence to radiographic guidelines in clinical decisions with a descriptive comparison to clinical practitioners

2023· article· en· W4317866231 on OpenAlexaboutno aff
David N. Taylor, Cheryl Hawk

Bibliographic record

VenueJournal of Chiropractic Education · 2023
Typearticle
Languageen
FieldMedicine
TopicRadiology practices and education
Canadian institutionsnot available
Fundersnot available
KeywordsChiropracticMedicineReferralFamily medicineVignetteClinical PracticeRadiographyClinical decision makingAlternative medicineMedical physicsPhysical therapyPathologyPsychologyRadiology

Abstract

fetched live from OpenAlex

OBJECTIVE: The purpose of this study was to assess chiropractic interns' knowledge and adherence to radiographic clinical practice guidelines (CPGs) and compare their clinical decisions to previous surveys of established practitioners in Canada and Australia. METHODS: A clinical decision-making survey was administered to 88 interns. The survey contained clinical scenarios and vignettes with inquiries regarding indications for radiographic referral, the likelihood of referral, and the application of CPGs. RESULTS: Forty-four percent (43.75%) of the interns were aware of CPGs, 38.75% were unsure, and 17.5% were not aware. When asked specific questions about the appropriateness of diagnostic imaging, the interns' responses were similar to those of practitioners in Canada and Australia. When interns evaluated a clinical vignette, there was lower compliance with CPGs. CONCLUSION: The interns' clinical decisions regarding the use of diagnostic radiography did not significantly differ from those of practitioners who were surveyed in other related studies. Interns were inconsistent in applying their decision making in clinical cases. Notwithstanding the similarities with practitioners, some deviation from the guidelines indicates the need for further intern education to improve the implementation of CPGs for optimal cost-effective and clinically appropriate care.

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)0.007
metaresearch head score (Gemma)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.252
GPT teacher head0.531
Teacher spread0.280 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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