Physiotherapy students enhance awareness of motivational interviewing skills needed in health promotion
Bibliographic record
Abstract
Background Health professionals who are skilled at communicating are a prerequisite for providing services of high quality. Physiotherapists work within health promotion and support people in change of lifestyle. The aim of this project was to gain insight into physiotherapy students’ motivation to train their practical communication skills and what students learned after a training session. The theory of motivational interviewing and the Calgary Cambridge guide served as a basic framework. Methods Training was undergone as an audiovisual training session with an actor. 5th semester physiotherapy students with an average age of 27,4 years (range 21-40) brought forward cases from self-experienced communication challenges from internships. Students answered an online 16 item questionnaire concerning their motivation and self-perceived learning outcome. 50 students had access to the online questionnaire. 23 students completed the questionnaire (46%). A content analysis of data was made, themes categorized and developed. Findings Students expressed personal development and working with own cases as important motivational factors for coming to class. 83 % had read all or parts of the literature suggested by the teachers. Students emphasized the importance of the learning environment being safe, appreciative and inclusive. All 23 students stated that they learned from playing, observing and/or giving feedback. Learnings were focused around personal issues such as seeing one self and others from without, the impact of silence and how it takes courage to give patients time to reflect and answer, and the impact of body language. Students found that they gained skills around active listening, setting an agenda, being non-judgmental and allowing the patient to be the expert on their own lives. 91 % of students evaluated that they acquired more skills - training in the audiovisual setting than they would in an ordinary lecture. Discussion Findings comprise important issues related to learning; based on involvement, peer learning, feedback and responsibility for own and others’ learning processes. In the light of the present focus on communication as an important skill for health professionals, we hope the project can contribute to further didactic discussions around how to train communication skills in health professional education. Keywords: Communication. Motivational interviewing. Physiotherapy. Skills 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) | 0.001 | 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".