Characterizing the mental health and functioning of Canadian respiratory therapists during the COVID-19 pandemic
Bibliographic record
Abstract
Introduction: Healthcare professionals (HCPs) appear to be at increased risk for negative psychological outcomes [e.g. depression, anxiety, post-traumatic stress disorder (PTSD), moral distress] and associated impacts on functioning throughout the COVID-19 pandemic. HCPs working on designated COVID-19 units may be further impacted than their colleagues not on these units given added demands of patient care and risk of contracting COVID-19. Little is known, however, about the mental health and functioning of specific professional groups beyond nurses and physicians, including respiratory therapists (RTs), over the course of the pandemic. Accordingly, the purpose of the present study was to characterize the mental health and functioning of Canadian RTs and compare profiles between RTs working on and off designated COVID-19 units.Methods: Canadian RTs completed an online survey between February and June 2021, including demographic information (e.g. age, sex, gender,) and measures of depression, anxiety, stress, PTSD, moral distress and functional impairment. Descriptive statistics, correlation analyses and between-groups comparisons were conducted to characterize RTs and compare profiles between those on and off COVID-19 units.Results: Two hundred and eighteen (N = 218) RTs participated in this study. The estimated response rate was relatively low (6.2%) Approximately half of the sample endorsed clinically relevant symptoms of depression (52%), anxiety (51%) and stress (54%) and one in three (33%) screened positively for potential PTSD. All symptoms correlated positively with functional impairment (p's < .05). RTs working on COVID-19 units reported significantly greater patient-related moral distress compared to those not on these units (p < .05).Conclusion: Moral distress and symptoms of depression, anxiety, stress and PTSD were prevalent among Canadian RTs and were associated with functional impacts. These results must be interpreted with caution given a low response rate, yet raise concern regarding the long-term impacts of pandemic service among RTs.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".