Canadian respiratory therapists who considered leaving their clinical position experienced elevated moral distress and adverse psychological and functional outcomes during the COVID-19 pandemic
Bibliographic record
Abstract
INTRODUCTION: Respiratory therapists (RTs) faced morally distressing situations throughout the COVID-19 pandemic, including working with limited resources and facilitating video calls for families of dying patients. Moral distress is associated with a host of adverse psychological and functional outcomes (e.g. depression, anxiety, symptoms of posttraumatic stress disorder [PTSD] and functional impairment) and consideration of position departure. The purpose of this study was to understand the impact of moral distress and its associated psychological and functional outcomes on consideration to leave a clinical position among Canadian RTs during the COVID-19 pandemic. METHODS: Canadian RTs (N = 213) completed an online survey between February and June 2021. Basic demographic information (e.g. age, sex, gender) and psychometrically validated measures of moral distress, depression, anxiety, stress, PTSD, dissociation, functional impairment, resilience and adverse childhood experiences were collected. RESULTS: One in four RTs reported considering leaving their position. RTs considering leaving reported elevated levels of moral distress and adverse psychological and functional outcomes compared to RTs not considering leaving. Over half (54.5%) of those considering leaving scored above the cut-off for potential diagnosis of PTSD. Previous consideration to leave a position and having left a position in the past each significantly increased the odds of currently considering leaving, along with system-related moral distress and symptoms of PTSD, but the contribution of these latter factors was small. CONCLUSIONS: Canadian RTs considering leaving their position reported elevated levels of distress and adverse psychological and functional outcomes, yet these individual-level factors appear unlikely to be the primary factors underlying RTs' consideration to leave, because their effects were small. Further research is required to identify broader, organizational factors that may contribute to consideration of position departure among Canadian RTs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".