Evidence map›Paper›PMID 42026635›Full record

ArticleBMC women's health2026

Digital addiction among female university students: a cross-sectional study in Dhaka, Bangladesh.

Abu Bakkar Siddique, Tafhimur Rahman, Md Mustafizur Rahman, Md Saiful Islam, Lakshmi Rani Kundu

Abstract read
In one paragraph

Article in BMC women's health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

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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

5 authors.

Abu Bakkar SiddiqueDepartment of Public Health and Informatics, Jahangirnagar University, Savar, Dhaka, 1342, Bangladesh. abubakkarsamrat1010@gmail.com.ORCID 0000-0002-1573-8281
Tafhimur RahmanCollege of Communication & Information Sciences, The University of Alabama, Tuscaloosa, AL, 35487, USA.
Md Mustafizur RahmanDepartment of Biochemistry and Molecular Biology, Jahangirnagar University, Savar, Dhaka, 1342, Bangladesh.
Md Saiful IslamDepartment of Public Health and Informatics, Jahangirnagar University, Savar, Dhaka, 1342, Bangladesh.
Lakshmi Rani KunduDepartment of Public Health and Informatics, Jahangirnagar University, Savar, Dhaka, 1342, Bangladesh. lakshmi@juniv.edu.ORCID 0000-0002-3528-0108

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDigital addiction is becoming increasingly prevalent, especially among university students in developing countries like Bangladesh. This study primarily aimed to understand digital addiction among female university students in Bangladesh and to identify the factors associated with it.

methodsA descript type of cross-sectional survey was conducted among 614 female university students (mean age: 21.65 ± 1.49 years) in Mirpur, Azimpur, Uttara, and Savar areas of the Dhaka district in Bangladesh between September 2 and October 15, 2023. The survey comprised a semi-structured questionnaire encompassing sections on informed consent, socio-demographic details, and the evaluation of digital addiction (i.e., Digital Addiction Scale [DAS]). Data were analyzed using Stata (Version 15.0) and SPSS (Version 26.0).

resultsThe digital addiction score averaged 59.47 ± 18.33 out of 95 indicates the increasing level of digital addiction based on assumption. Factors such as higher education level, unmarried status, lack of physical exercise, poor self-perception of physical and mental health, and over 4 h of daily social media use were positively associated with digital addiction, while higher family income was linked to a lower likelihood of experiencing it.

conclusionsThis study provides new insights into the factors associated with digital addiction among female university students in Dhaka, Bangladesh. It highlighted that lifestyle habits, mental health perceptions, and social media use contribute to digital addiction. The findings emphasize the need for targeted interventions, including mental health support, awareness programs, and strategies to promote balanced digital engagement among students.

Indexed as

Behavior, AddictiveInternet Addiction DisorderSocial MediaStudentsAdultBangladeshCross-Sectional StudiesDigital MediaFemaleHumansSurveys and QuestionnairesUniversitiesYoung AdultAssociated factorsBangladeshDigital addictionFemale university studentsInternet use

Identifiers

PMID42026635
PMCPMC13248244

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.