Midwives’ experiences with PPE during the COVID-19 pandemic: The Birth in the Time of COVID (BITTOC) study
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic resulted in rapid changes aimed at reducing disease transmission in maternity services in Australia. An increase in personal protective equipment (PPE) in the clinical and community setting was a key strategy. There was variation in the type of PPE and when it was to be worn in clincial practice. AIM: This paper reports on Australian midwives' experiences of PPE during the pandemic. METHODS: This sequential mixed methods study was part of the Birth in the Time of COVID-19 (BITTOC 2020) study. Data were obtained from in-depth semi-structured interviews with midwives in 2020 followed by a national survey undertaken at two time points (2020 and 2021). Qualitative open-text survey responses and interview data were analysed using content analysis. FINDINGS: 16 midwives were interviewed and 687 midwives provided survey responses (2020 n = 477, 2021 n = 210). Whilst midwives largley understood the need for increased PPE, and were mainly happy with this, as it was protective, they reported a number of concerns. These included: inconsistency with PPE type, use, availability, quality, fit and policy; the impact of PPE on the physical and psychological comfort of midwives; and the barriers PPE use placed on communication and woman centred care. This at times resulted in midwives working outside of policy. CONCLUSION: These findings highlight the need for future comprehensive pandemic preparedness that ensures policy and procedure recommendations are consistent and PPE is available, of approriate quality, and individually fitted in order to ensure that Australian maternity services are well placed to manage future pandemics.
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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 | 0.012 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".