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Record W4413298878 · doi:10.1177/01632787251368457

Factors Influencing the Reporting of Notifiable Conduct in Health Professionals in Australia

2025· article· en· W4413298878 on OpenAlexaff
D. Bhasin, Karl Kilian Konrad Wiener

Bibliographic record

VenueEvaluation & the Health Professions · 2025
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsChild, Adolescent and Family Mental Health
Fundersnot available
KeywordsMisconductSexual misconductHealth careTheory of planned behaviorMedicinePsychologyHealth professionalsProfessional conductAgency (philosophy)Family medicineControl (management)Criminology

Abstract

fetched live from OpenAlex

Objective: Notification of misconduct is a requirement by the Australian Health Practitioner Regulatory Agency. The study focuses on examining the factors that influence the intention to report misconduct by applying the Theory of planned behavior model. Method: The quantitative online survey study using vignettes and questionnaires examined one hundred and seventy-two regulated health professionals on factors that may impact the willingness to report on notifiable conduct. Results: The findings indicate that clinicians were more inclined to report on sexual misconduct and alcohol misuse conduct, however, they did not report on clinicians’ competencies. Perceived behavior control, descriptive norms, and subjective norms predicted intention to report notifiable conduct, while attitude was not a predictor. Clinicians with a higher reporting intention were more likely to engage in actual reporting behavior. The behavioral pattern of reporting notifiable conduct did not differ among the three health professional groups. Conclusion: The findings identify important factors that assist clinicians in their decision-making when reporting observed misconduct. Awareness of these factors reduces health care related misconduct. That is, organizations are encouraged to develop specific programs that facilitate clinicians’ decision making by educating and refreshing their knowledge of the factors impacting their intention to report misconducts.

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)0.070
metaresearch head score (Gemma)0.036
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.264
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0700.036
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.559
GPT teacher head0.638
Teacher spread0.080 · 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; both teacher heads agree on what is shown here.

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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