Canadian Respiratory Therapists During the COVID-19 Pandemic
Bibliographic record
Abstract
Despite pre-COVID-19 pandemic evidence to suggest that respiratory therapists (RTs) may experience elevated symptoms of anxiety and distress due to the nature of their occupation, the extant literature on healthcare providers (HCPs’) experiences during the pandemic is largely limited to other HCP groups, such as nurses and physicians. Global reports demonstrate widespread adverse psychological impacts to HCPs during the pandemic, including symptoms of depression, anxiety, burnout, moral distress and post- traumatic stress disorder (PTSD). Furthermore, occupational impacts, namely turnover intention, are increasingly reported as the pandemic persists. This Master’s thesis investigated the psychological and occupational impacts associated with COVID-19 pandemic service among Canadian RTs during the Spring of 2021. A review of the relevant literature on HCPs' experiences during the pandemic is presented in Chapter 1, along with a synthesis of knowledge on RTs. An exploration of psychological and functional outcomes among RTs during the COVID-19 pandemic is presented in Chapter 2. Here, almost half of the sample reported clinically relevant symptoms of depression, anxiety and stress, and one in three RTs screened positively for likely PTSD. In Chapter 3, we investigated consideration of position departure, finding that one in four RTs were considering leaving. Despite over half of those considering leaving screening positive for likely PTSD, adverse psychological experiences contributed little to the predictive model of departure consideration compared to past consideration to leave. We posit that longstanding organizational issues may play an important role in RTs’ consideration to leave. Overall, these studies expand the literature investigating the impact of COVID-19 pandemic service among HCPs and advance knowledge on the impacts of pandemic service among RTs who have, up until recently, been neglected. Altogether, the evidence presented in this thesis suggests that RTs require adequate mental health supports and resources alongside their HCP colleagues during and beyond the COVID-19 pandemic.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.012 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".