The Efficacy of a Cadaver‐based Online Teaching Resource on Improving Physiotherapists' Anatomical Knowledge: A Pelvic Health Perspective
Bibliographic record
Abstract
Neuromuscular dysfunction of the pelvic floor and perineum can negatively impact several populations including the elderly, parous women, and athletes. Pelvic health physiotherapists assess and treat neuromuscular dysfunction of the perineal and pelvic diaphragmatic regions using targeted physical therapy techniques. Consequently, they must rely on their understanding of the complex anatomy of the pelvic floor to guide them during the assessment and treatment of their patients. In Canada, physiotherapists who choose to specialize in pelvic health enroll in continuing education courses to learn clinical concepts and techniques associated with the specialty. However, an initial pilot study revealed that the majority of physiotherapists attending these entry‐level pelvic health courses had limited prior knowledge of the anatomy relevant to the specialty. Since pelvic anatomy is foundational to the pelvic health specialty, entering the course with insufficient anatomical knowledge may limit the physiotherapists' abilities to learn and execute more advanced clinical procedures. To improve baseline pelvic anatomy knowledge, a cadaver‐based online teaching resource, the Pelvic Health Anatomy Module (PHAM), was created and evaluated in the present study. The study was conducted to assess: (1) the efficacy of the PHAM to enhance physiotherapists' anatomical knowledge before entering a pelvic health course, and (2) if having stronger anatomical knowledge prior to the onset of the course impacted their understanding of the course concepts. Physiotherapists (n = 23) were given one of two anatomy education resources to review before the beginning of an entry‐level pelvic health certification course – the experimental group received the novel PHAM resource, while the control groups reviewed a traditionally‐used online video resource. Participants who received the PHAM perceived it as “very useful”, while the control group perceived the traditional videos as “useful”. The average for the group who reviewed the PHAM was higher for the anatomy scores at the beginning, end, and one week after completion of the course than the group who reviewed the control resource. Furthermore, the average for the group who reviewed the PHAM was higher on evaluations of course concepts compared to the groups who reviewed the control resource. The initial results of this study support the development and use of comprehensive and purposeful anatomy resources for continuing education courses in healthcare, particularly physiotherapy, to enhance foundational knowledge and facilitate better application of course concepts. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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 | 0.010 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".