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Record W4285394076 · doi:10.1177/19375867221111530

Hospital Outdoor Spaces as Respite Areas for Healthcare Staff During the COVID-19 Pandemic

2022· article· en· W4285394076 on OpenAlexaff
Saad Arslan Iqbal, Ismaila Rimi Abubakar

Bibliographic record

VenueHERD Health Environments Research & Design Journal · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRespite carePandemicHealth careAnxietyDistressBurnoutNursingCoping (psychology)Mental healthGovernment (linguistics)PsychologyMedicineCoronavirus disease 2019 (COVID-19)PsychiatryPolitical scienceClinical psychologyDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

The COVID-19 pandemic has created considerable implications for healthcare staff around the globe. During the pandemic, the frontline healthcare workers experience intense anxiety, stress, burnout, and psychological breakdown, with severe implications on their mental and physical well-being. In addition to these implications, anxiety and stress can hinder their productivity and ability to perform their duties efficiently. The literature indicates that hospital gardens and contact with nature can help alleviate psychological distress among hospital staff. However, few studies investigated the role of outdoor spaces as areas for respite and work breaks in healthcare facilities during the pandemic. The present opinion paper highlights the challenges of job stress and psychological distress health workers face during the pandemic. This article also underscores the role of hospital outdoor spaces and garden facilities in coping with the challenges. While other measures to reduce stress among hospital staff and ensure their health and safety are important, hospital administrators and relevant government agencies should also emphasize the provision of gardens and open spaces in healthcare facilities. These spaces can act as potential areas for respite for hospital staff to help them cope with the stress and anxiety accumulated through working under crises.

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)0.015
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.645
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0100.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0060.000

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 head0.160
GPT teacher head0.414
Teacher spread0.253 · 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 designNot applicable
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

Citations25
Published2022
Admission routes1
Has abstractyes

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