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Mental Health and Health-Related Quality of Life Among Nephrology Nurses: A Survey-Based Cross-Sectional Study

2021· article· en· W3211551063 on OpenAlex

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

VenueNephrology Nursing Journal · 2021
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsGroup for Research in Decision Analysis
Fundersnot available
KeywordsMedicineAnxietyNephrologyDepression (economics)Patient Health QuestionnairePandemicCoronavirus disease 2019 (COVID-19)BurnoutCross-sectional studyMental healthFeelingStressorWorkloadQuality of life (healthcare)Internal medicineClinical psychologyFamily medicinePsychiatryDepressive symptomsPsychologyNursingDisease

Abstract

fetched live from OpenAlex

Nephrology nurses face health and wellness challenges due to significant work-related stressors. This survey, conducted online between July 24 and August 17, 2020, assessed the psychological well-being of nephrology nurses in the United States during the COVID-19 pandemic (n = 393). Respondents reported feeling burned out from work (62%), symptoms of anxiety (47% with Generalized Anxiety Disorder-7 [GAD-7] scores ≥ 5), and major depressive episodes (16% with Patient Health Questionnaire-2 [PHQ-2] scores ≥ 3). Fifty-six percent (56%) of survey respondents reported caring for COVID-19 patients, and 62% were somewhat or very worried about COVID-19. Factors, including high workload, age, race, and the COVID-19 pandemic, may partially explain the high proportion of nephrology nurses who reported symptoms of burnout, anxiety, and depression.

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)0.012
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0040.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.140
GPT teacher head0.497
Teacher spread0.357 · 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