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Record W2986055497 · doi:10.18192/riss-ijhs.v9i1.3579

Expériences de préposées aux bénéficiaires sur l'utilisation d'un système informatisé de gestion des soins en résidences pour personnes âgéees

2019· article· en· W2986055497 on OpenAlexvenueaboutno aff
Antonia Arnaert, Norma Ponzoni, Zoumanan Debe, France Morisette

Bibliographic record

VenueRevue interdisciplinaire des sciences de la santé - Interdisciplinary Journal of Health Sciences · 2019
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsnot available
Fundersnot available
KeywordsDocumentationWorkflowFocus groupAutonomyAsset (computer security)PsychologyNursingSociologyMedicineComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Despite the increasing use of computerized care management systems in residences for older adults, there is very little evidence on the perceptions of caregivers regarding this technology, specifically the perceptions of orderlies. The purpose of this qualitative study is to explore the experiences of 17 orderlies vis-à-vis the use of the software “Soins Organisation Facilité Intérêt” (SOFI) in two senior residences in Quebec. Transcripts from four focus groups were analyzed using an inductive approach. All attendants agreed that the software was a positive asset that allowed them to better organize their tasks and documentation. In addition, they expressed the desire to use SOFI in their workflow to improve communication between themselves and with other professionals within the institution to participate in decision-making around quality of care. Finally, they insisted on the absolute necessity of having this technology be adapted to the working environment, both in its digital presentation and in its physical form, in order for it to be easy to access and use. The presence of software meeting the identified criteria enabled them to improve their performance through increased autonomy and their commitment to daily practice.

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)0.022
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0080.005
Scholarly communication0.0000.003
Open science0.0020.001
Research integrity0.0000.001
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 head0.063
GPT teacher head0.438
Teacher spread0.375 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2019
Admission routes2
Has abstractyes

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Same venueRevue interdisciplinaire des sciences de la santé - Interdisciplinary Journal of Health SciencesSame topicGeriatric Care and Nursing HomesFrench-language works237,207