Evidence map›Paper›PMID 33603416›Full record

ArticleInfection and drug resistance2021

Knowledge, Attitudes, and Practices of Antimicrobial Uses and Resistance Among Public University Students in Bangladesh.

Mahfuza Marzan, Dewan Zubaer Islam, Halyna Lugova, Ambigga Krishnapillai, Mainul Haque, Salequl Islam

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Infection and drug resistance, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05100407 (Evaluation of the Prevalence and Antibiotic Susceptibility Pattern of Multidrug Resistance Bacteria and Its Association With Patients' Predictive Factors), which is not on this map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
5.7field-weighted citation impact, top 4% of its field
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.

NCT05100407 completednot on this mapstarted 2022, after this paper: background citation

Evaluation of the Prevalence and Antibiotic Susceptibility Pattern of Multidrug Resistance Bacteria and Its Association With Patients' Predictive Factors

TypeobservationalSponsorKufa UniversityRan2022 to 2022Enrolled400ConditionsMulti-antibiotic Resistance
3 · Its place in the literature

Who cites it

36 citing papers in PubMed, 65 citations in OpenAlex.

  1. Article
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  6. A pill for every ill? Unpacking antibiotic misuse among Bangladeshi university students.International journal of qualitative studies on health and well-being · 2025
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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

6 authors at 2 institutions in 2 countries.

Mahfuza MarzanDepartment of Microbiology, Jahangirnagar University, Savar, Dhaka, 1342, Bangladesh.ORCID 0000-0003-4568-412X
Dewan Zubaer IslamDepartment of Microbiology, Jahangirnagar University, Savar, Dhaka, 1342, Bangladesh.ORCID 0000-0003-0023-1733
Halyna LugovaThe Unit of Community Medicine, Faculty of Medicine and Defence Health, National Defence University of Malaysia, Kuala Lumpur, 57000, Malaysia.ORCID 0000-0001-8052-0580
Ambigga KrishnapillaiThe Unit of Family Medicine, Faculty of Medicine and Defence Health, National Defence University of Malaysia, Kuala Lumpur, 57000, Malaysia.ORCID 0000-0003-3485-2079
Mainul HaqueThe Unit of Pharmacology, Faculty of Medicine and Defence Health, Universiti Pertahanan Nasional Malaysia (National Defence University of Malaysia), Kuala Lumpur, 57000, Malaysia.ORCID 0000-0002-6124-7993
Salequl IslamDepartment of Microbiology, Jahangirnagar University, Savar, Dhaka, 1342, Bangladesh.ORCID 0000-0001-6131-4132
Jahangirnagar University · BDNational Defence University of Malaysia · MY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAntibiotics are lifesaving drugs, and inappropriate uses lead to the resistance that renders them ineffective. This study aims to understand knowledge, attitude, and practice (KAP) concerning antibiotic use and resistance among university students in Bangladesh.

methodsA cross-sectional study was performed from January to April 2020 among students at Jahangirnagar University (JU), Bangladesh. Purposive sampling was conducted through an in-person interview using a structured questionnaire. Students from the faculties of biological sciences and non-biology background were included. The univariate ordinal regression technique was used to analyze the relationship between predictors and good knowledge about the antibiotics. A two-tailed p-value was calculated to determine statistical association.

resultsOut of 205 study participants, 92 and 113 responders were from biological science faculty and non-biology disciplines, respectively. Less than half of the students (42.4%) showed a good knowledge level (scores higher than 80%). Biology-background students possess better knowledge than non-biology students [odds ratio (OR) = 4.44, 95% confidence level (CL) (2.56, 7.70), p < 0.001]. A better attitude was noticed among all students. The self-medication rate was quite low, and more than 90% of students were found to consume antibiotics according to the physician's prescription. Lack of treatment adherence was recorded, and students admitted to stop-taking antibiotics when symptoms disappeared (48.67% biology and 36.26% non-biology). Multivariate regression analysis was unable to detect any significant association between self-medication and gender, student category or the level of knowledge about antibiotics.

conclusionStudents of biological science background possessed better knowledge indicating the importance of appropriate curriculum imparted in knowledge buildup. Introducing a short course about the risk and development of antibiotic resistance will grow the students' awareness to avoid the resistance phenomenon.

Indexed as

anti-bacterial agentsantibioticBangladeshdrug resistanceknowledgestate-owneduniversity students

Identifiers

PMID33603416
PMCPMC7886243
OpenAlexW3128353153

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

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.