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Record W2109464452 · doi:10.1016/j.jmpt.2003.12.021

Implementing Evidence-Based Guidelines for Radiography in Acute Low Back Pain: A Pilot Study in a Chiropractic Community

2004· article· en· W2109464452 on OpenAlexaffabout
Carlo Ammendolia, Sheilah Hogg‐Johnson, Claire Bombardier, Victoria Pennick, Richard H. Glazier

Bibliographic record

VenueJournal of Manipulative and Physiological Therapeutics · 2004
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsInstitute for Work & HealthUniversity of TorontoCanadian Memorial Chiropractic College
Fundersnot available
KeywordsChiropracticMedicinePhysical therapyRadiographyLow back painBack painAlternative medicinePhysical medicine and rehabilitationRadiologyPathology

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the ability of a systematic educational intervention strategy to change the plain radiography ordering behavior of chiropractors toward evidence-based practice for patients with acute low back pain (LBP). DESIGN: A quasi-experimental method was used comparing outcomes before and after the intervention with those of a control community. SETTING: Two communities in southern Ontario. DATA SOURCE: Mailed survey data on the management of acute LBP. Outcome Measures Plain radiography use rates for acute LBP based on responses to mailed surveys. RESULTS: Following the intervention, there was a 42% reduction in the self-report need for plain radiography for uncomplicated acute LBP (P <.025) and a 50% reduction for patients with acute LBP < 1 month (P <.025) in the intervention community. There was no significant change in the self-report need for plain radiography in the control community (P >.05). CONCLUSIONS: The educational intervention strategy used in this study appeared to have an effect in reducing the perceived need for plain radiography in acute LBP.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.992
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.566
GPT teacher head0.470
Teacher spread0.096 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designNon-randomized trial
DomainMethods
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

Citations45
Published2004
Admission routes2
Has abstractyes

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