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Record W4389132032 · doi:10.55016/ojs/tsw.v1i1.77694

Impacts of the COVID-19 pandemic on nephrology social work: Perspectives of social workers

2023· article· en· W4389132032 on OpenAlexaffabout
Andrew Mantulak, David Nicholas, Hilary Nelson, Julisa Crocker

Bibliographic record

VenueTransformative Social Work · 2023
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of CalgaryThe King's UniversityWestern University
Fundersnot available
KeywordsPandemicSocial workPsychosocialNephrologyMedicineFocus groupCoronavirus disease 2019 (COVID-19)Public relationsNursingInternal medicinePolitical scienceSociologyPsychiatry

Abstract

fetched live from OpenAlex

A mixed method study utilized surveys and focus groups to explore the perceptions of nephrology social workers in Canada regarding the impact of the COVID-19 pandemic on their practice with patients and their families. As part of this larger study, participants were invited to focus groups which elicited pandemic experiences, personally and professionally, and to offer post-pandemic recommendations for nephrology social work. The sample comprised 15 nephrology social workers from several Canadian provinces, who provided in-depth reflections regarding the impact of the pandemic on professional practice. Study results reflect COVID-19 pandemic-related experiences of Canadian nephrology social workers, including psychosocial impacts as well as practice and infrastructure shifts. In providing service to patients and families, nephrology social workers were forced to confront personal, professional and organizational landscapes altered by hospital and broader societal public health guidelines aimed at decreasing the spread of COVID-19. Although an inherently challenging experience, participating social workers concurrently noted areas of growth that resulted from pandemic circumstances..

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)0.000
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 score0.295
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.003
Science and technology studies0.0050.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.093
GPT teacher head0.439
Teacher spread0.346 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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