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Record W1899819662 · doi:10.3233/wor-2012-0127-1

New working conditions and consequences on activity of home healthcare workers

2012· article· en· W1899819662 on OpenAlexaff
Corinne van de Weerdt, René Baratta

Bibliographic record

VenueWork · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicEmotional Labor in Professions
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsHealth careJob satisfactionWork (physics)Coping (psychology)Occupational stressHealthcare serviceOccupational safety and healthEmotional laborNursingVariety (cybernetics)BusinessCare workPreferencePsychologyMedicineSocial psychologyEngineeringPolitical science

Abstract

fetched live from OpenAlex

Home healthcare is steadily growing in Europe. There are a number of reasons for this development: aging population, rising hospital costs, preference to stay in one's own home. Nevertheless, it has been known that home healthcare workers are frequently exposed to a variety of potentially serious occupational hazards. Furthermore, emotional labor is frequently high in this profession. This paper describes an ergonomic study conducted at a home healthcare service. The research focuses on analyzing working conditions of home healthcare aides and nurses, as well as the impacts of their work in terms of job satisfaction, well-being, emotions at work, relationships with the others and occupational stress. The study show that employee strategies are specifically centered around preserving the relationship between patients and workers and coping with the job demands. This paper also shows that home healthcare workers express emotions and conceal them from others. Finally, recommendations discussed with the manager and workers to improve working conditions in this sector led to practical proposals: for example, implementing certain equipment items better suited to difficult care, encouraging assistance between healthcare workers when operations require this through adequate organizational measures, extending work emotion-focused discussion groups with management involvement.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score0.383

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.073
GPT teacher head0.384
Teacher spread0.312 · 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

Citations11
Published2012
Admission routes1
Has abstractyes

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