MétaCan
Menu
Back to cohort
Record W2025478975 · doi:10.1186/1748-5908-2-39

Testing a TheoRY-inspired MEssage ('TRY-ME'): a sub-trial within the Ontario Printed Educational Message (OPEM) trial

2007· article· en· W2025478975 on OpenAlexafffundabout
Jill Francis, Jeremy Grimshaw, Merrick Zwarenstein, Martin Eccles, Susan K Shiller, Gaston Godin, Marie Johnston, Keith O’Rourke, Justin Presseau, Jacqueline Tetroe

Bibliographic record

VenueImplementation Science · 2007
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsCanadian Institutes of Health ResearchUniversité LavalSunnybrook HospitalSt. Michael's HospitalInstitute for Clinical Evaluative SciencesUniversity of TorontoInstitute of Population and Public HealthUniversity of Ottawa
FundersCanadian Institutes of Health ResearchCanada Research ChairsScottish Government
KeywordsDirectiveTest (biology)MedicineProtocol (science)Medical educationClinical trialRandomized controlled trialAlternative medicineComputer scienceSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: A challenge for implementation researchers is to develop principles that could generate testable hypotheses that apply across a range of clinical contexts, thus leading to generalisability of findings. Such principles may be provided by systematically developed theories. The opportunity has arisen to test some of these theoretical principles in the Ontario Printed Educational Materials (OPEM) trial by conducting a sub-trial within the existing trial structure. OPEM is a large factorial cluster-randomised trial evaluating the effects of short directive and long discursive educational messages embedded into informed, an evidence-based newsletter produced in Canada by the Institute for Clinical Evaluative Sciences (ICES) and mailed to all primary care physicians in Ontario. The content of educational messages in the sub-trial will be constructed using both standard methods and methods inspired by psychological theory. The aim of this study is to test the effectiveness of the TheoRY-inspired MEssage ('TRY-ME') compared with the 'standard' message in changing prescribing behaviour. METHODS: The OPEM trial participants randomised to receive the short directive message attached to the outside of informed (an 'outsert') will be sub-randomised to receive either a standard message or a message informed by the theory of planned behaviour (TPB) using a two (long insert or no insert) by three (theory-based outsert or standard outsert or no outsert) design. The messages will relate to prescription of thiazide diuretics as first line drug treatment for hypertension (described in the accompanying protocol, "The Ontario Printed Educational Materials trial"). The short messages will be developed independently by two research teams.The primary outcome is prescription of thiazide diuretics, measured by routinely collected data available within ICES. The study is designed to answer the question, is there any difference in guideline adherence (i.e., thiazide prescription rates) between physicians in the six groups? A process evaluation survey instrument based on the TPB will be administered pre- and post-intervention (described in the accompanying protocol, "Looking inside the black box"). The second research question concerns processes that may underlie observed differences in prescribing behaviour. We expect that effects of the messages on prescribing behaviour will be mediated through changes in physicians' cognitions.

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)0.046
metaresearch head score (Gemma)0.109
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.945
Threshold uncertainty score0.243

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0460.109
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0080.001

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 head0.550
GPT teacher head0.659
Teacher spread0.109 · 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 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

Citations14
Published2007
Admission routes3
Has abstractyes

Explore more

Same venueImplementation ScienceSame topicHealth Policy Implementation ScienceFrench-language works237,207