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Record W2801342114 · doi:10.1186/s13756-018-0312-6

Mixed methods evaluation of the impact of a short term training program on sterile processing knowledge, practice, and attitude in three hospitals in Benin

2018· article· en· W2801342114 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAntimicrobial Resistance and Infection Control · 2018
Typearticle
Languageen
FieldMedicine
TopicSurgical site infection prevention
Canadian institutionsMount Royal University
FundersMount Royal University
KeywordsWork (physics)MedicineNursingHealth careQuality (philosophy)Medical educationBest practiceManagementEngineering

Abstract

fetched live from OpenAlex

Background: Proper sterile processing is fundamental to safe surgical practice and optimal patient outcomes. Sterile processing practices in low and middle-income countries often fall short of recommended standards. The impact of education and training on sterile processing practices in low and middle-income countries is unknown. We designed a sterile processing education course, including mentoring, and aimed to evaluate the impact on participants' personal knowledge, skills, and practices. We also aimed to identify institutional changes in sterile processing practices at participants' work places. Methods: A mixed methods design study was conducted using a Hospital Sterile Processing Assessment Tool, knowledge tests, and open-ended interviews. Results: Education and mentoring improved how workers understood and approached their work and to what they paid attention. Sterile processing workers were also better able to identify resources available to do their work and showed improved understanding of the impact of their work on patient safety. Conclusions: Health care organizations seeking to improve surgical outcomes can find easy wins requiring minimal cost expenditures by paying attention to sterile processing practices. Investing in education and low-cost resources, such as cleaning detergents and brushes, must be part of any quality improvement initiative aimed at providing safe surgery in low and middle-income countries.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.690
Threshold uncertainty score0.358

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.045
GPT teacher head0.426
Teacher spread0.381 · 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