Prevention and management of unprofessional behaviour among adults in the workplace: A scoping review
Bibliographic record
Abstract
BACKGROUND: Unprofessional behaviour is a challenge in academic medicine. Given that faculty are role models for trainees, it is critical to identify strategies to manage these behaviours. A scoping review was conducted to identify interventions to prevent and manage unprofessional behaviour in any workplace or professional setting. METHODS: A search of 14 electronic databases was conducted in March 2016, reference lists of relevant systematic reviews were scanned, and grey literature was searched to identify relevant studies. Experimental and quasi-experimental studies that reported on interventions to prevent or manage unprofessional behaviours were included. Studies that reported impact on any outcome were eligible. Two reviewers independently screened articles and completed data abstraction. Qualitative analysis of the definitions of unprofessional behaviour was conducted. Data were charted to describe the study, participant, intervention and outcome characteristics. RESULTS: 12,482 citations were retrieved; 23 studies with 11,025 participants were included. The studies were 12 uncontrolled before and after studies, 6 controlled before and after studies, 2 cluster-randomised controlled trials (RCTs), 1 RCT, 1 non-randomised controlled trial and 1 quasi-RCT. Four constructs were identified in the definitions of unprofessional behaviour: verbal and/or non-verbal acts, repeated acts, power imbalance, and unwelcome behaviour. Interventions most commonly targeted individuals (22 studies, 95.7%) rather than organisations (4 studies, 17.4%). Most studies (21 studies, 91.3%) focused on increasing awareness. The most frequently targeted behaviour change was sexual harassment (4 of 7 studies). DISCUSSION: Several interventions appear promising in addressing unprofessional behaviour. Most of the studies included single component, in-person education sessions targeting individuals and increasing awareness of unprofessional behaviour. Fewer studies targeted the institutional culture or addressed behaviour change.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.077 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.016 | 0.012 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".