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Record W4205373836 · doi:10.47723/kcmj.v17i3.297

Knowledge, Attitude, and Practice of Nurseries' Workers toward Infection Prevention among the Children

2021· article· en· W4205373836 on OpenAlexaff
Sahar Abdul Hassan Al-Shatari, Tayser Salah Ghafouri

Bibliographic record

VenueAL-Kindy College Medical Journal · 2021
Typearticle
Languageen
FieldHealth Professions
TopicPediatric health and respiratory diseases
Canadian institutionsCentre for Family Medicine
Fundersnot available
KeywordsMedicinePsychological interventionInfection controlFamily medicineDisease controlGood practiceChild careKnowledge levelEnvironmental healthNursingPsychologyIntensive care medicine

Abstract

fetched live from OpenAlex

Background: Infections are common in the children attending daycare centers how act as predisposes to it. Hygienic interventions have a fundamental role in infection control and disease prevention in child care settings. Objective: - To evaluate the knowledge, attitude, and practice of nurseries workers in infection prevention and control among the children. Subjects and Methods: A cross-sectional study using the researcher-developed questionnaire validated by two experts and piloted and 100 nurseries-workers had participated in it. Result: the mean age of participants was 37.5 years±12.1, (37%) aged 18-30 yrs, 58% married, and 57% with higher education, 54% of nurseries the participant take care of 11-20 children. 67 (67%) had correct knowledge about infection control, (91%) had the corrected practice, but unfortunately, 47 (47%) had low-attitude. Education level has significantly associated with the knowledge, attitude, and practice of the child care workers. Conclusion: the majority of the nurseries workers had good knowledge and correct practice and less about their attitude in infection prevention.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
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)0.0020.000

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 head0.038
GPT teacher head0.435
Teacher spread0.397 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2021
Admission routes1
Has abstractyes

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