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Record W2980629121 · doi:10.1017/ice.2019.269

Adoption of infection prevention and control practices by healthcare workers in Québec: A qualitative study

2019· article· en· W2980629121 on OpenAlexaffabout
Ève Dubé, Armelle Lorcy, Nathalie Audy, Nadia Desmarais, Patrice Savard, Chantal Soucy, Samuel Bassetto, Mathilde Rajon, Fabrice Brunet, Caroline Barbir, Caroline Quach

Bibliographic record

VenueInfection Control and Hospital Epidemiology · 2019
Typearticle
Languageen
FieldMedicine
TopicInfection Control in Healthcare
Canadian institutionsPolytechnique MontréalUniversité LavalUniversité de MontréalCentre Hospitalier Universitaire Sainte-JustineCentre hospitalier de l'Université LavalInstitut National de Santé Publique du Québec
Fundersnot available
KeywordsFacilitatorSafety cultureProactivityHealth careNursingContext (archaeology)Infection controlOrganizational cultureQualitative researchMedicinePatient safetyFamily medicinePsychologyPublic relationsSocial psychologyManagement

Abstract

fetched live from OpenAlex

OBJECTIVE: To describe barriers and facilitators to the adoption of recommended infection prevention and control (IPC) practices among healthcare workers (HCWs). METHODS: A qualitative research design was used. Individual semistructured interviews with HCWs and observations of clinical practices were conducted from February to May 2018 in 8 care units of 2 large tertiary-care hospitals in Montreal (Québec, Canada). RESULTS: We interviewed 13 managers, 4 nurses, 2 physicians, 3 housekeepers, and 2 medical laboratory technologists. We conducted 7 observations by following IPC nurses (n = 3), nurses (n = 2), or patient attendants (n = 2) in their work routines. Barriers to IPC adoption were related to the context of care, workplace environment issues, and communication issues. The main facilitator of the IPC adoption by HCWs was the "development of an IPC culture or safety culture." The "IPC culture" relied upon leadership support by managers committed to IPC, shared belief in the importance of IPC measures to limit healthcare-associated infections (HAIs), collaboration and good communication among staff, as well as proactivity and ownership of IPC measures (ie, development of local solutions to reduce HAIs and "working together" toward common goals). CONCLUSIONS: Adoption of recommended IPC measures by HCWs is strongly influenced by the "IPC culture." The IPC culture was not uniform within hospital and differences in IPC culture were identified between care units.

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)0.004
metaresearch head score (Gemma)0.004
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 score0.146
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.039
GPT teacher head0.418
Teacher spread0.380 · 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

Citations7
Published2019
Admission routes2
Has abstractyes

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