MétaCan
Menu
Back to cohort
Record W2487681406 · doi:10.1177/2327857916051011

Disconnects in design and infection prevention and control – how the design of products and the environment in neonatal intensive care may be undermining infection prevention practice

2016· article· en· W2487681406 on OpenAlex
Chantal Trudel, Sue Cobb, Kathryn Momtahan, Janet Brintnell, Ann M. Mitchell

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProceedings of the International Symposium on Human Factors and Ergonomics in Health Care · 2016
Typearticle
Languageen
FieldMedicine
TopicInfection Control in Healthcare
Canadian institutionsOttawa HospitalCarleton University
Fundersnot available
KeywordsInfection controlThematic analysisStakeholderHealth careMedicineNeonatal intensive care unitBest practiceRisk analysis (engineering)NursingBusinessIntensive care medicinePublic relationsQualitative researchPediatrics

Abstract

fetched live from OpenAlex

This study examined the role design plays in infection prevention and control within an existing neonatal intensive care unit. Methods from human-centred design such as planning, stakeholder meetings and naturalistic observation were used to obtain infection prevention information related to the existing unit design, interactions with products and the environment, and perspectives of front-line staff on design. Thematic analysis was used to categorize and structure the issues that were identified. The analysis revealed that the design of products and the environment may be undermining best practice in infection prevention. Health care workers experience a variety of difficulties in maintaining the recommended barriers to infection transmission, difficulties which stem from deficiencies in products and the environment. Various aspects of the neonatal care design lack the feedback or supports needed to help health care workers differentiate or work between infection transmission zones making the design challenging to use or maintain in a manner that supports best practice in infection prevention. Identifying issues in the design of products and the environment related to infection prevention practice led to the development of a ‘Design Exploration Guide’. The guide outlines issues and strategies for remediation based on feasibility within the project constraints.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.043
GPT teacher head0.312
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it