Physical and occupational therapists' learning needs and preferences for education on functional electrical stimulation: A qualitative descriptive study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Functional electrical stimulation (FES) is an evidence-based intervention that is rarely used by Canadian physical therapists (PTs) and occupational therapists (OTs). A common barrier to FES implementation is a lack of knowledge and training. FES learning resources that meet therapists' learning needs and preferences may address this barrier. OBJECTIVE: To explore OTs' and PTs' perspectives on the utility of FES e-learning resources, including whether the resources met their learning needs and preferences. METHODS: Through this qualitative descriptive study, feedback on FES e-learning resources was solicited from 5 PTs and 18 OTs who work clinically, but do not use FES. Participants reviewed ≥3 prerecorded lectures on FES topics and then completed a semi-structured interview. Participants were asked about the lectures' content, delivery, ease of use and comprehensibility, and were asked to suggest modifications to facilitate self-directed learning about FES. Interviews were analyzed using conventional content analysis. RESULTS: Three themes were identified. (1) Feedback on FES e-learning: the content and delivery of the prerecorded lectures facilitated participants' learning, although opportunities to improve content and delivery were identified. (2) Factors influencing FES learning needs and preferences: Participants identified internal (i.e., baseline knowledge, learning style) and external (i.e., learning with colleagues, practice setting) factors that affected learning. Themes 1 and 2 impacted (3) the effects of FES e-learning: Participants described the outcomes of their FES e-learning, including increases in FES knowledge, confidence, and use in clinical practice. CONCLUSION: Therapists' perceived the FES e-learning resources to be useful and to address their learning needs and preferences.
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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 | 0.000 | 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 it