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Record W4313312503 · doi:10.1111/nhs.13012

Organizational support and <scp>Nurse–Physician</scp> collaboration during <scp>SARS‐CoV</scp>‐2 pandemic: A qualitative study

2022· article· en· W4313312503 on OpenAlexaff
Hussan Zeb, Shahzad Inayat, Ahtisham Younas

Bibliographic record

VenueNursing and Health Sciences · 2022
Typearticle
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsThematic analysisNursingWorkforcePandemicQualitative researchHealth carePsychologyOrganizational cultureMedicinePublic relationsSociologyCoronavirus disease 2019 (COVID-19)Political science

Abstract

fetched live from OpenAlex

Health care professionals experienced multiple uncertainties during the pandemic. Exploring health care professionals' views about collaboration and organizational support can offer insights into organizational processes and issues during the pandemic. This research explored the perspectives of nurses and physicians about organizational support and nurse-physician collaboration during the SARS-CoV-2 pandemic. Using a qualitative descriptive design, interviews were conducted with nurses and physicians working in hospital settings. The interviews lasted for 24-61 min. Reflexive thematic analysis was used for data analysis. Nurses and physicians were disappointed with the organizational support, but they were satisfied with nurse-physician collaboration. The theme "Management Abusing Authority and Blaming the Victimized Workforce" included organizational nepotism, unethical managerial actions, and neglecting frontline workforce. Nurses and physicians supported each other in tackling the intensive and complex demands of the pandemic. The theme "Demonstrating Professional Humility and Overcoming Patient Care Issues at Hand" entailed subthemes - negotiating conflicts and prioritizing patient care, practicing kindness, and jointly managing conflicts with patients' families. Nurses and physicians reported frustrations with limited organizational support and abusive practices of managers. Still, they prioritized patient care needs and family-related conflicts over interprofessional tensions.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0060.000
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 head0.109
GPT teacher head0.492
Teacher spread0.382 · 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.

Study designQualitative
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

Citations5
Published2022
Admission routes1
Has abstractyes

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