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Record W2149358561 · doi:10.1177/154405910808700701

Changing Clinicians’ Behavior: a Randomized Controlled Trial of Fees and Education

2008· article· en· W2149358561 on OpenAlexaff
Jan Clarkson, Stephen Turner, Jeremy Grimshaw, Craig Ramsay, Marie Johnston, Anthony Scott, Debbie Bonetti, Colin Tilley, Graeme MacLennan, Richard Ibbetson, L.M.D. Macpherson, Nigel Pitts

Bibliographic record

VenueJournal of Dental Research · 2008
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsRemunerationRandomized controlled trialIncentiveMedicineIntervention (counseling)Health careEvidence-based practiceFamily medicineTreatment and control groupsDentistryNursingAlternative medicineFinanceBusinessSurgery

Abstract

fetched live from OpenAlex

The fissure-sealing of newly erupted molars is an effective caries prevention treatment, but remains underutilized. Two plausible reasons are the financial disincentive produced by the dental remuneration system, and dentists' lack of awareness of evidence-based practice. The primary hypothesis was that implementation strategies based on remuneration or training in evidence-based healthcare would produce a higher proportion of children receiving sealed second permanent molars than standard care. The four study arms were: fee per sealant treatment, education in evidence-based practice, fee plus education, and control. A cost-effectiveness analysis was conducted. Analysis was based on 133 dentists and 2833 children. After adjustment for baseline differences, the primary outcome was 9.8% higher when a fee was offered. The education intervention had no statistically significant effect. 'Fee only' was the most cost-effective intervention. The study contributes to the incentives in health care provision debate, and led to the introduction of a direct fee for this treatment.

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.255

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.082
GPT teacher head0.469
Teacher spread0.387 · 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 designRandomized trial
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

Citations88
Published2008
Admission routes1
Has abstractyes

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