The Knowledge, Attitudes, and Practices of Canadian Master of Physical Therapy Students Regarding Peer Mentorship
Bibliographic record
Abstract
PURPOSE: To describe Canadian Master of Physical Therapy (MPT) students' knowledge, attitudes, and practices regarding peer mentorship. METHODS: A quantitative cross-sectional survey study was conducted. An online questionnaire was sent to 945 MPT students via e-mail, using a modified Dillman approach. Data were analyzed using descriptive statistics to describe the knowledge, attitudes, and practices of Canadian MPT students. RESULTS: A total of 260 MPT students (27.5%) responded to the questionnaire. Most respondents (68.7%) did not have any experience in a peer mentorship relationship during their MPT programme. A few respondents (5.4%) reported having received formal training on peer mentorship as part of their PT curriculum. Respondents generally held positive attitudes toward peer mentorship: 65.9% agreed that including peer mentorship is important, 89.5% agreed that peer mentorship can assist with learning in clinical internships, and 84.1% agreed that peer mentorship can help the transition from student to professional. Most respondents (52.5%) did not participate in a peer mentorship relationship during a typical month. CONCLUSIONS: MPT students' attitudes toward peer mentorship are positive, yet their knowledge of and resources for peer mentorship are limited, and few students have been involved in peer mentorship practices. The findings highlight the importance of university programme support to provide a nurturing environment and structure to overcome barriers, promote commitment, and facilitate successful participation. The evidence from this study provides a rationale to support and guide peer mentorship programming for Canadian MPT students.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".