Human factors considerations in designing for infection prevention and control in neonatal care – findings from a pre-design inquiry
Bibliographic record
Abstract
Qualitative data collection methods drawn from the early stages of human-centred design frameworks combined with thematic analysis were used to develop an understanding of infection prevention practice within an existing neonatal intensive care unit. Findings were used to generate a framework of understanding which in turn helped inform a baseline approach for future research and design development. The study revealed that a lack of clarity between infection transmission zones and a lack of design attributes needed to uphold infection prevention measures may be undermining healthcare workers' understanding and application of good practice. The issue may be further complicated by well-intentioned behavioural attitudes to meeting work objectives; undue influences from spatial constraints; the influence of inadvertent and excessive touch-based interactions; physical and/or cognitive exertion to maintain transmission barriers; and the impact of expanding job design and increased workload to supplement for lack of effective barriers. Practitioner Summary: Despite high hand hygiene compliance within a neonatal intensive care unit, healthcare workers expressed concerns about the unit design and infection prevention practice. Early inquiry methods from human-centred design and thematic analysis helped develop a framework to understand how design can be used to aid infection prevention.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".