The Psychological Impacts of Taking Physiotherapy Teaching Online in 2020: What Did We Learn?
Bibliographic record
Abstract
INTRODUCTION: The rapid shift to online learning due to the COVID-19 pandemic presented challenges for physical therapy (PT) education worldwide. This article aims to explore the factors influencing the well-being of the PT faculty and department chairs involved in delivering PT programs during the initial stages of the COVID-19 pandemic. REVIEW OF LITERATURE: The literature has focused on the pedagogical impacts of the rapid shift to online learning. Little is known about the social and psychological impacts of this rapid transition on the well-being of the faculty involved in implementing PT programs. SUBJECTS: Physical therapy faculty and department chairs at 3 universities in metropolitan Sydney, Australia who taught into or led PT programs in 2020. METHODS: Focus group methodology was used to explore the experiences of PT faculty and department chairs during the initial stages of the COVID pandemic. The focus groups were digitally recorded and transcribed verbatim and the transcripts analyzed thematically. RESULTS: The main finding of this study was the extent of stress experienced by PT program faculty and chairs during this period. Both work-related institutional and faculty factors and non-work-related personal factors contributed to perceived high levels of stress. Overall, there was a feeling that the stressors had not improved over the duration of the pandemic and that this had left the faculty and chairs feeling more fatigued, less collegiate, and may have ongoing impacts on their mental health. DISCUSSION: The pandemic created stresses for faculty and program chairs over and above the usual stress of faculty and college work. The reality of taking steps to reduce the stressors in the current climate is very difficult. CONCLUSION: Moving forward, it is vital to secure increased institutional support, including the support for creating realistic boundaries without the risk of penalty, to address the psychological health and well-being of PT faculty and chairs to enable high-quality education in the future.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".