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Record W4307343840 · doi:10.1080/01634372.2022.2139321

Exploring the COVID-19 Practice Experiences of Social Workers Working in Long Term Care

2022· article· en· W4307343840 on OpenAlexaffabout
Joann Schneider, Teigan Tsoukalas, Rosslynn Zulla, David Nicholas, Jennifer Hewson

Bibliographic record

VenueJournal of Gerontological Social Work · 2022
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversity of CalgaryAlberta Health Services
Fundersnot available
KeywordsPandemicPreparednessSocial workLong-term careNursingPsychologyWork (physics)Coronavirus disease 2019 (COVID-19)Qualitative researchPublic relationsMedicineSociologyPolitical science

Abstract

fetched live from OpenAlex

The COVID-19 pandemic ushered in multiple public health protocols that shaped the service delivery system supporting older adults, their family caregivers and their formal care providers. In this qualitative study, sixteen social workers employed in long term care facilities in a western province of Canada shared their perspectives about the impacts of the COVID-19 pandemic on their practice early in the pandemic. Participants responded to nine open-ended online survey questions about their practice and experiences. Four themes were identified: (1) a changing and demanding work environment, (2) witnessing transitions in residents' quality of life, (3) impacts on relationships and work climate, and (4) personal impacts on social workers. Recommendations for enhancing capacity in the system were identified. Implications of findings illuminate a need for proactive preparedness approaches in order for social workers to address emergent and changing needs of residents and their families during a pandemic.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.097
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.230
GPT teacher head0.453
Teacher spread0.223 · 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

Citations2
Published2022
Admission routes2
Has abstractyes

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