Evidence map›Paper›PMID 41280979›Full record

ArticleCureus2025

Data Analysis of Infection Control Awareness and Practices Among Healthcare Workers: A Cross-Sectional Study in a Tertiary-Care Hospital in Kashmir, India.

Fatima Abeer, Aasim Ayaz Wani, Shoaib M Khan, Anjum Farhana

Abstract read
In one paragraph

Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Fatima AbeerMicrobiology, Government Medical College, Srinagar, IND.
Aasim Ayaz WaniChemical and Biomolecular Engineering, Cornell University, New York, USA.
Shoaib M KhanMicrobiology, Government Medical College, Srinagar, IND.
Anjum FarhanaMicrobiology, Government Medical College, Srinagar, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Healthcare-associated infections (HAIs) pose a significant threat to patient and healthcare worker (HCW) safety, particularly in low-resource settings. While infection prevention and control (IPC) measures can effectively reduce HAIs, adherence among HCWs often varies. This study assessed IPC awareness and practices among HCWs in a tertiary-care hospital in Kashmir, India, aiming to identify areas for targeted intervention. A cross-sectional study was conducted among 300 HCWs at Government Medical College (GMC), Srinagar, and its associated hospitals using an online questionnaire to assess demographics, comorbidities, IPC knowledge, and self-reported adherence to key practices. While the majority of respondents (93%) reported awareness of IPC measures, adherence to key practices was suboptimal. Regular handwashing was practiced by only 56% of HCWs, while mask use stood at 17% and hand-sanitizer use at 20%. Needlestick injuries were reported by 16% of HCWs, highlighting gaps in standard precautions. Despite substantial IPC awareness, consistent application remains a challenge in this tertiary-care setting. Strengthening training programs, ensuring resource availability, and promoting a culture of safety are crucial to improve compliance, reduce HAIs, and protect both patients and HCWs. These findings underscore the need for targeted interventions to bridge the knowledge-practice gap and enhance IPC effectiveness in similar settings.

Indexed as

cross-sectional studyhealthcare-acquired infectionhealthcare-associated infections (hcais)healthcare workersinfection prevention and control practicespromoting infectious disease control

Identifiers

PMID41280979
PMCPMC12638001

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.