Motivational interview training improves self-efficacy of GP interns in vaccination consultations: A study using the Pro-VC-Be to measure vaccine confidence determinants
Bibliographic record
Abstract
Immunization-specific motivational interviewing (MI), a patient-centered communication style used to encourage internal motivation for attitudinal and behavioral change, can provide healthcare professionals (HCPs) with the skills and practice required to respond to patients’ doubts and concerns related to vaccines. We sought to assess the impact of an MI-training of General Practitioner (GP) interns on the psychosocial determinants of their vaccine confidence and behaviors. French GP interns participated in a virtual three-day MI-workshop in southeastern France. We used the validated Pro-VC-Be questionnaire – before and after the MI-workshop spanning over three months – to measure the evolution of these determinants. Scores before and after workshop trainings were compared in pairs. Participants’ scores for commitment to vaccination (+10.5 ± 20.5, P = .001), perceived self-efficacy (+36.0 ± 25.8, P < .0001), openness to patients (+18.7 ± 17.0, P < .0001), and trust in authorities (+9.5 ± 17.2, P = 0.01) significantly increased after the training sessions, but not the score for confidence in vaccines (+1.5 ± 11.9, P = .14). The effect sizes of the four score improvements were moderate to large, with self-efficacy and openness to patients having the largest effect sizes (P = .83 and 0.78, respectively). This study provides evidence that certain determinants of overall vaccine confidence in HCPs, reflected respectively in the openness to patients and self-efficacy scores of the Pro-VC-Be, improve after immunization MI-training workshops. Incorporating immunization-specific MI-training in the curriculum for HCPs could improve several necessary skills to improve HCP-patient relationships and be useful for vaccination and other healthcare services.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".