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Record W2125784740

Physicians' knowledge of the epidemiology, diagnosis, and management of otitis media: design of a survey instrument.

2009· article· en· W2125784740 on OpenAlexaboutno aff
Ambrose Lee, Gordon Flowerdew, Mary Delaney

Bibliographic record

VenuePubMed · 2009
Typearticle
Languageen
FieldMedicine
TopicEar Surgery and Otitis Media
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOtitisInternal consistencyNova scotiaReliability (semiconductor)Family medicineTest (biology)EpidemiologyConstruct validityPhysical therapyPsychometricsClinical psychologySurgeryInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To develop a survey instrument with good internal consistency and test-retest reliability to explore the level of knowledge among Nova Scotia family physicians concerning the risk factors, signs and symptoms, and treatment of otitis media and the use of pneumatic otoscopy. DESIGN: Prospective cohort design. SETTING: Fee-for-service family practices in Nova Scotia. PARTICIPANTS: A convenience sample of 25 family physicians. MAIN OUTCOME MEASURES: Test-retest reliability and internal consistency of the survey. RESULTS: The constructs including "signs and symptoms of otitis media with effusion" and "comprehensive knowledge scores" showed excellent internal consistency with Kuder-Richardson 20 scores greater than 0.7 whereas the construct "signs and symptoms of acute otitis media" has a Kuder-Richardson 20 score of 0.54 after deletion of several items. The Cohen kappa and Spearman rho tests showed the survey has very good test-retest reliability. CONCLUSION: The questionnaire that we developed proved to have very good internal consistency and test-retest reliability. We hope to use this questionnaire to explore the practice patterns of family physicians in managing otitis media disease.

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)0.015
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.101
GPT teacher head0.282
Teacher spread0.180 · 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.

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

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

Citations6
Published2009
Admission routes1
Has abstractyes

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