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Record W3073234728 · doi:10.1093/pch/pxaa068.028

29 Using Simulation in a Clinical Care Setting to Evaluate a Novel Medical Device with Families and Bedside Staff – Phase 1: Perceptions of the NeoVest under a Family Integrated Care (FICare) Model

2020· article· en· W3073234728 on OpenAlexaffabout
Avery Longmore, Kathleen Hollamby, Jeanne Zielonka, Douglas M. Campbell

Bibliographic record

VenuePaediatrics & Child Health · 2020
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineContinuous positive airway pressureRespiratory therapistRespiratory distressRespiratory careIntensive careMechanical ventilationNursingIntensive care medicinePsychiatry

Abstract

fetched live from OpenAlex

Abstract Background Newborn infants are at increased risk of requiring respiratory support with a mechanical ventilator. Nasal continuous positive airway pressure (nCPAP) is the most commonly used non-invasive respiratory support. Current nCPAP support is not synchronized to an infant’s breathing efforts, and can contribute to patient discomfort, skin breakdown, and interference with mother-infant bonding. An alternative to nCPAP is negative pressure ventilation. Our NeoVest was developed as a wearable vest that utilizes Neurally Adjusted Ventilator Assist (NAVA) technology to synchronize with the infant’s own respiratory drive and control. NeoVest and NAVA have demonstrated efficacy/feasibility in preliminary experiments emulating neonatal respiratory distress in animal models. Before implementation of this new technology in NICUs, it is important to assess the perspectives of NICU multi-disciplinary staff and parents to optimize design and understand its impact. Objectives The objective was to assess both clinicians’ and NICU parents’ perceptions of the NeoVest as compared with traditional nCPAP devices. Design/Methods Nurses, respiratory therapists and NICU parents at St. Michael’s Hospital in Toronto, Canada were invited to participate in the study. Research Ethics Board approval was obtained for this study. Parents were approached if their baby has previously been on CPAP. After consent, participants attended simulations that demonstrated the utility of the NeoVest. After the simulation, participants completed a survey that assessed their satisfaction and stress level regarding use of the NeoVest in a clinical setting. Numeric Likert scale responses and free text comments were collected from participants and analyzed. Free text comments were assessed using the principles of thematic analysis. Results Thirty clinicians (16 nurses, and 14 RTs), and 4 parents answered the survey. Almost all respondents were excited by the new technology and believed the use of simulation in the NICU was beneficial. Respondents reported that the NeoVest would not add stress to their roles in the NICU, and the majority of clinicians also believed that the NeoVest will improve care of the infant patient. Parents and clinicians both suggested that nCPAP can cause stress, and that the NeoVest would be preferred. One of the major themes regarding how the NeoVest may improve care from the perspective of both parents and clinicians was improved parent-child bonding through improved eye contact. Clinicians also believed it would reduce irritation, maintain skin integrity and have less complications as compared to nCPAP. The major themes with respect to clinician concerns about the NeoVest included: examining the neonate, umbilical line access, and the learning curve for new technology. The major themes with respect to parental concerns included: interference with skin to skin and holding their child. Conclusion Survey responses were overall favourable for introduction of new NICU technology, in this case a novel breathing device: the NeoVest. Although small, this cohort provided invaluable insight regarding the NeoVest’s impact on future patient populations. This highlights the importance of patient feedback in innovation. Next steps include a pilot study assessing the feasibility and efficacy of the NeoVest in the clinical setting, with re-administration of the questionnaires to compare reality and simulation.

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 imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.057
GPT teacher head0.385
Teacher spread0.328 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes2
Has abstractyes

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