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Record W4406125005 · doi:10.1177/26334895241307638

Changing or validating physician opioid prescribing behaviors through audit and feedback and academic detailing interventions in primary care

2025· article· en· W4406125005 on OpenAlex
Celia Laur, Natasha Kithulegoda, Nicola McCleary, Emily Nicholas Angl, Michael Strange, Barbara Sklar, Thivja Sribaskaran, Gail Dobell, Sharon Gushue, Jonathan Lam, Lindsay Bevan, Victoria J. Burton, Lena Salach, Justin Presseau, Laura Desveaux, Noah Ivers

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueImplementation Research and Practice · 2025
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsTrillium Health CentreCentre for Social InnovationOttawa HospitalUniversity of OttawaPublic Health OntarioWomen's College HospitalUniversity of Toronto
FundersStrategy for Patient-Oriented Research
KeywordsPsychological interventionAcademic detailingAuditContext (archaeology)ReceiptPsychologyMedical educationMedicineBehavior changeNursingSocial psychology

Abstract

fetched live from OpenAlex

Background In Ontario, Canada, province-wide initiatives supporting safer opioid prescribing in primary care include voluntary audit and feedback reports and academic detailing. In this process evaluation, we aimed to determine the fidelity of delivery and receipt of the interventions, the observed change strategies used by physicians, potential mechanisms of action, and how complementary the initiatives can be to each other. Method Semi-structured interviews were conducted with academic detailers and with physicians who received both interventions. Academic detailer interviews were coded using the Behavior Change Technique Taxonomy; physician interviews were coded to the Theoretical Domain Framework. Change strategies were summarized based on academic detailer intentions and physician-reported practice changes. Potential mechanisms of action were identified using the Theories and Techniques Tool and the literature. Patient partners informed the interpretation of results through ongoing group discussions of preliminary findings. Results Interviews were conducted with eight academic detailers and 12 physicians. Change strategies described by academic detailers to support physicians’ opioid prescribing included problem solving, instructions on how to perform the behavior, adding objects to the environment, credible source, shaping knowledge, and social support. Physicians mentioned that academic detailing validated current opioid practices or increased their belief about capabilities and their intentions, mediated by increased skills and the impact of environmental context and resources. Potential mechanisms of action included behavioral regulation, behavioral cueing, and general attitudes/beliefs. On its own, receiving the audit and feedback report did not lead to changes in beliefs about prescribing practices; however, for some physicians, it provided validation and reassurance. Physicians saw unrealized potential for complementarity. Conclusions New interventions are often implemented in a complex ecosystem with other competing interventions. In this study, we show how examining the fidelity of the intervention from initial design through to delivery can identify opportunities for potential optimization.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.681
Threshold uncertainty score0.426

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.172
GPT teacher head0.525
Teacher spread0.353 · 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