Impact of Self- and Peer Assessment on the Clinical Performance of Physiotherapists in Primary Care: A Cohort Study
Bibliographic record
Abstract
Purpose: This study evaluated the impact of a quality improvement programme based on self- and peer assessment to justify nationwide implementation. Method: Four professional networks of physiotherapists in The Netherlands (n = 379) participated in the programme, which consisted of two cycles of online self-assessment and peer assessment using video recordings of client communication and clinical records. Assessment was based on performance indicators that could be scored on a 5-point Likert scale, and online assessment was followed by face-to-face feedback discussions. After cycle 1, participants developed personal learning goals. These goals were analyzed thematically, and goal attainment was measured using a questionnaire. Improvement in performance was tested with multilevel regression analyses, comparing the self-assessment and peer-assessment scores in cycles 1 and 2. Results: In total, 364 (96%) of the participants were active in online self-assessment and peer assessment. However, online activities varied between cycle 1 and cycle 2 and between client communication and recordkeeping. Personal goals addressed client-centred communication (54%), recordkeeping (24%), performance and outcome measurement (15%), and other (7%). Goals were completely attained (29%), partly attained (64%), or not attained at all (7%). Self-assessment and peer-assessment scores improved significantly for both client communication (self-assessment = 11%; peer assessment = 8%) and recordkeeping (self-assessment = 7%; peer assessment = 4%). Conclusions: Self-assessment and peer assessment are effective in enhancing commitment to change and improving clinical performance. Nationwide implementation of the programme is justified. Future studies should address the impact on client outcomes.
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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".