1330 The Effects of SARS-CoV2 (COVID-19) on NICU health care providers
Bibliographic record
Abstract
Background The Neonatal Intensive Care Unit (NICU) has risks of burnout and psychological morbidity for health care providers. The COVID-19 pandemic has required the rapid adaptation of work practices to accommodate social distancing and Personal Protective Equipment (PPE) policy changes. Many departments have recognized the wellbeing implications to staff and made changes to try and mitigate this risk. Objectives In this study, we aim to begin to understand how COVID-19 and its associated workplace practice changes have impacted the existing situation. Methods An online survey was distributed to tertiary NICU physicians, nurses, nurse practitioners, respiratory therapists and allied health professionals in British Columbia and Alberta (table 1). We employed a combination of closed- and open-ended questions to understand the participants’ views on work in the NICU during the pandemic and how this has impacted their wellbeing. Results 142 replies of which 121 were complete. 93 were from Alberta, 45 from British Columbia, and 4 did not provide their province. Of the respondents, 33 (22.7%) had cared for a patient with COVID-19. 98.3% reported a major change as a result of COVID-19. These included homeschooling children (40, 33.3%), caring for vulnerable relatives (19, 15.8%), shielding vulnerable relatives (107, 89.2%), changes to a family member’s employment (36, 30%) and being unable to connect with friends and family outside their city/province (101, 84.2%) Respondents also cited themes of personal isolation, delayed care for their or their family’s non-COVID-19 physical and mental health conditions, anxiety at working on multiple sites and a lack of access to their usual daily coping strategies such as sports. There were a series of Likert-scale question, with 0 = ‘Completely disagree’ and 100 = ‘Completely agree’. Conclusions All NICUs have made significant adaptions to their operating procedures and sought to support their staff through the pandemic, and these data suggest that this is recognised by the majority of participants. This is necessary but not sufficient. The successes we can demonstrate in the logistical response must be taken in context of a global change affecting staff’s physical, psychological and social circumstances which changes their relationship with the NICU. In future work, we aim to use quantitative and qualitative analysis from this survey in order to better understand the current state of staff wellbeing, the nature of the difficulties experienced by staff and their perception of the interventions used to support them.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".