Physiotherapy students' perceptions of how the Cervical Framework influences their clinical reasoning: A qualitative single case study of a Canadian university
Bibliographic record
Abstract
BACKGROUND: Neck pain and headaches are highly prevalent, often presenting a challenge for physiotherapists when considering differential diagnoses. For guidance, the International Federation of Manual and Musculoskeletal Physical Therapists (IFOMPT) created the International IFOMPT Cervical Framework. Its purpose is to improve clinical reasoning through various functional objectives and design principles. Although the Cervical Framework supports clinical reasoning among physiotherapy students, how this is achieved is unexplored. OBJECTIVES: 1. To explore physiotherapy students' perceptions of how the Cervical Framework's functional objectives influence their clinical reasoning. 2. To explore physiotherapy students' perceptions of how the Cervical Framework's design principles influence their clinical reasoning. DESIGN: Qualitative, constructivist, exploratory, single-case study. METHOD: Semi-structured interviews of physiotherapy students enrolled in one of three educational programs at one university were conducted. Directed qualitative content analysis informed by the Cervical Frameworks' functional objectives and design principles was used to interpret data. FINDINGS: From eighteen participants, meaningful data were found for all functional objectives, with particular value when informing clinical reasoning during assessment and improving understanding of risk. Students showed mixed perceived value in informing clinical reasoning during treatment and facilitating patient-centred practice. Physiotherapy students' perceptions of the Cervical Framework align with most of its design principles, especially its informative, simple, and non-prescriptive nature. Students also perceived the Cervical Framework as long and this may have affected engagement. CONCLUSION: Physiotherapy students in this case study perceive the Cervical Framework to influence their clinical reasoning by achieving its functional objectives and by successfully adhering to its design principles.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.022 | 0.010 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".