Development of motivational interviewing skills in immunization (MISI): a questionnaire to assess MI learning, knowledge and skills for vaccination promotion
Bibliographic record
Abstract
Objective: Vaccine hesitancy is a complex problem. We previously demonstrated that motivational interviewing (MI) could be helpful to enhance parents’ motivation to vaccinate their child. The aim of this study is to develop a new, simple and robust evaluation tool that is suitable for evaluating MI learning of vaccination health professionals.Methods: We designed the Motivational Interviewing Skills in Immunization (MISI), a short written questionnaire to evaluate the MI knowledge and skills of participants in an immunization context. It covers three key areas: knowledge of MI, ability to apply MI-related skills, participant self-confidence in using MI. Questionnaire content and face validity were assessed by MI experts and internal consistency, reliability and effect size were analyzed using a multiple pretest-posttest design.Results: Psychometric measures showed good to excellent internal consistency of the questionnaire for all three areas (Cronbach’s and KR coefficient: 0.70 to 0.88). Test-retest reliability showed good measurement stability (ICC: 0.53). Good sensitivity to change was also obtained (Cohen’s d: 0.80 to 1.66).Conclusion: The MISI questionnaire is the first paper/pencil evaluation method to assess MI training specific to immunization. Psychometric measures showed high reliability.Practice implications: This questionnaire could provide a convenient and inexpensive method to evaluate knowledge and competencies following immunization-specific MI training.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".