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Record W2140690193 · doi:10.1093/intqhc/mzs047

Types and patterns of safety concerns in home care: staff perspectives

2012· article· en· W2140690193 on OpenAlexafffundabout
Catherine K. Craven, Kerry Byrne, Joanie Sims‐Gould, Anne Martin-Matthews

Bibliographic record

VenueInternational Journal for Quality in Health Care · 2012
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsVancouver Coastal HealthUniversity of British ColumbiaVancouver Coastal Health Research InstitutePositive Living Society of British ColumbiaUniversity of British Columbia Hospital
FundersCanadian Institutes of Health Research
KeywordsNursingPatient safetyMedicineMedical emergencyHealth carePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Quality health care in the home is dependent on having a safe environment to provide care. This analysis is based on the data from a larger study aimed at understanding key issues in the delivery and receipt of home support services from the perspectives of home support workers (HSWs), older adult clients and family members. This analysis focuses on HSWs perspectives of safety. OBJECTIVE: To explore the types and patterns of safety concerns staff encountered in home care settings. DESIGN: In-depth, semi-structured interviews were conducted with HSWs. The analysis included topic and analytical coding of workers' verbatim accounts. SETTING: Interviews were completed in British Columbia, Canada. PARTICIPANTS: A total of 115 HSWs participated. The average age was 50 years, and the average tenure in this sector was 11.5 years. Fully, 71% of workers had completed at least some college-level education, and 69% of workers were born outside of Canada. RESULTS: Workers identified four types of safety concerns: physical, spatial, interpersonal and temporal. We developed a conceptual model of HSW safety that demonstrates the: types of safety concerns; the multi-dimensional and intersectional nature of safety concerns and the factors that intensify or mitigate safety concerns. CONCLUSIONS: Our study identifies numerous HSW safety concerns, each requiring tailored interventions and strategies. Where multiple concerns intersect, the complexity and precarious nature of the home care workspace is revealed. The identification of mitigating and intensifying factors points to future interventions.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.135
Threshold uncertainty score0.706

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.079
GPT teacher head0.508
Teacher spread0.429 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations58
Published2012
Admission routes3
Has abstractyes

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