Comparing an In-Person and Online Continuing Education Intervention to Improve Professional Decision-Making: A Mixed Methods Study
Bibliographic record
Abstract
Purpose: This paper compares two iterations (in-person and online) of a multi-stage continuing education program for improving high-risk decision-making among mental health workers. Methods: The mixed-methods study analyzed the following: (1) physiological and psychological arousal during simulated patient interviews; (2) physiological and psychological arousal recorded during real-time decision-making over four months; and (3) thoughts on the process and outcomes of the intervention raised in reflective interviews. Findings: Quantitatively, there were no statistical differences in stress measures between in-person and online simulated interviews or decision-making logs, suggesting they were effective in eliciting reactions commonly found in challenging clinical situations. Qualitatively, participants in both iterations indicated that the intervention caused them to reflect on practice, consider a wider range of factors related to the decisions, and enact approaches to improve decision-making. Conclusions: A carefully constructed online continuing education experience can result in outcomes for experienced social workers that are equivalent to an in-person iteration.
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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 | 0.016 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".