Internal determinants of change readiness: implications for the continuing education of health professionals
Bibliographic record
Abstract
Continuing professional education events do not often result in behaviour change in the learner, even when satisfaction with the event is high and evidence of knowledge acquisition in the learner is present. One important variable that might help explain the relationship between continuing health educational and subsequent change is the degree to which the learner feels ready to change his or her behaviour. While much is known about how physicians learn and change, the cognitive and affective determinants of readiness to change have not been extensively researched in the applied health professions. This study used a mixed methodology, one-group retrospective pre-test, post-test design to investigate the value of readiness to change in predicting behaviour change and to determine if the value of an educational event is dependent on the state of learner "readiness." A readiness to change questionnaire was administered to 84 health professionals registered in the University of Toronto's International Interdisciplinary Wound Care Course in May, 2005. Responses were scored and summed to arrive at a numerical indicator of the degree of readiness to change both at the beginning and at the end of the course. Three regression analyses were conducted to examine the significance of a model in which the three internal determinants predicted learner readiness before, during, and after the course. To examine how the educational event influenced learner readiness, 20 semi-structured interviews were conducted 3 months after the course. Interpretation of quantitative and qualitative data supported that change readiness is a fluid cognitive state comprised of determinants that vary depending upon the temporal proximity to behaviour change. Data further supported a relationship between change readiness and subsequent behaviour change that discriminates across wound care skills. However, behaviour change might be best predicted by a comprehensive examination of factors both internal and external to the individual. Furthermore, the educational event did appear to influence the state of learner readiness. These findings supported the measurement of change readiness both during the program development phase and as an indicator of program success.
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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 | 0.017 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".