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Record W7117700838 · doi:10.2196/80199

Effect of an Online Continuing Professional Development Course on Physicians’ Intention to Approach a Colleague in Difficulty: Mixed Methods Convergent Study

2025· article· en· W7117700838 on OpenAlexaffvenue
Florence Lizotte, Martin Tremblay, C. Biron, Éloi Lachance, Souleymane Gadio, Roberta de Carvalho Corôa, Claude Bernard Uwizeye, Sam J. Daniel, F. Légaré

Bibliographic record

VenueJMIR Medical Education · 2025
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsMcGill UniversityFédération des Maisons D'Hébergement pour FemmesUniversité Laval
Fundersnot available
KeywordsCourse (navigation)Online courseHealth careContinuing professional developmentHealth professionalsProfessional developmentOnline learningKey (lock)

Abstract

fetched live from OpenAlex

BACKGROUND: Burnout and psychological distress are prevalent among physicians. Peer support appears to play a protective role, yet little is known about training interventions that motivate physicians to approach peers in difficulty, as such effects are often overlooked or assessed using nonvalidated tools. OBJECTIVE: We evaluated the effects of an online continuing professional development (CPD) course designed to increase physicians' intention to approach a colleague in difficulty. METHODS: Physicians who completed a 1-hour asynchronous online CPD course between March 2022 and May 2024 were invited to participate in this mixed methods convergent study. The e-learning course aimed to increase physicians' confidence in approaching colleagues in difficulty by recognizing signs of psychological distress, offering support, and referring them to appropriate resources. Participant characteristics were collected, and behavioral intention to approach a colleague in difficulty along with its determinants were measured pre- and postcourse using the validated CPD-REACTION tool. Differences in mean pre-post intention scores were assessed using 2-tailed paired t tests (n=466) and generalized estimating equations. Factors associated with postcourse intention were examined using multivariate analysis (n=466). Four months later, the proportion of physicians reporting adoption of the behavior was calculated (n=61). Qualitative responses to open-ended questions were analyzed thematically using behavior change models, and behavior change techniques used in the course were identified. Quantitative and qualitative results were triangulated. We reported results following STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) and SRQR (Standards for Reporting Qualitative Research) guidelines for quantitative and qualitative analyses, respectively. RESULTS: =0.22). Four months later, 41% (25/61; 95% CI 28.6%-54.3%) of participants reported having approached a colleague in difficulty. Frequently reported reasons for intention to adopt behavior were beliefs about capabilities, beliefs about consequences, and knowledge. Quantitative and qualitative results converged on beliefs about capabilities but diverged regarding beliefs about consequences. A total of 7 behavioral change techniques were identified in the CPD course: goal setting, increasing competence, planning, persuasive communication, behavior-related information, modeling, and behavioral experiments. CONCLUSIONS: This online CPD course increased physicians' intention to approach a colleague in difficulty. The results highlight beliefs about capabilities as a key determinant of this behavioral intention. The study suggests that online learning has strong potential to raise awareness about peer support and ultimately build a culture of care among health care workers.

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)0.018
metaresearch head score (Gemma)0.040
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.040
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.016
GPT teacher head0.452
Teacher spread0.435 · 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
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".

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Citations0
Published2025
Admission routes2
Has abstractyes

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