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Record W4289526318 · doi:10.1177/10748407221114326

The Impact of Parental Presence Restrictions on Canadian Parents in the NICU During COVID-19: A National Survey

2022· article· en· W4289526318 on OpenAlexaffabout
Marsha Campbell‐Yeo, Justine Dol, Holly McCulloch, Brianna Hughes, Amos Hundert, Fabiana Bacchini, Leah Whitehead, Jehier Afifi, Lynsey Alcock, Tanya Bishop, Jon Dorling, Rebecca Earle, Annette Elliott Rose, Darlene Inglis, Carye Leighton, Gail MacRae, Andrea Melanson, Christy Simpson, Michael Smit

Bibliographic record

VenueJournal of Family Nursing · 2022
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsIzaak Walton Killam Health CentreDalhousie University
Fundersnot available
KeywordsIntensive careCoronavirus disease 2019 (COVID-19)PandemicFamily centered careMedicineMental health2019-20 coronavirus outbreakHealth careFamily medicineSurvey researchNursingPsychologyPsychiatryPolitical scienceApplied psychology

Abstract

fetched live from OpenAlex

The purpose of this research was to explore parental perspectives on the impact of parent restrictions imposed in response to the COVID-19 pandemic across Canadian Neonatal Intensive Care Units (NICUs). A co-designed online survey was conducted targeting parents ( n = 235) of infants admitted to a Canadian NICU from March 1, 2020, until March 5, 2021. Parents completed the survey from 38 Canadian NICUs. Large variation in the severity of policies regarding parental presence was reported. Most respondents (68.9%) were classified as experiencing high restrictions, with one or no support people allowed in the NICU, and felt that policies were less easy to understand, felt less valued and respected, and found it more challenging to access medicine or health care. Parents reported gaps in care related to self-care, accessibility, and mental health outcomes. There is significant variation in parental restrictions implemented across Canadian NICUs. National guidelines are needed to support consistent and equitable care practices.

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 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 score0.020
Threshold uncertainty score0.992

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 studies0.0010.000
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 head0.070
GPT teacher head0.374
Teacher spread0.303 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations14
Published2022
Admission routes2
Has abstractyes

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