Evidence map›Paper›PMID 34298222›Full record

ArticleJournal of affective disorders2021

The mental impact of digital divide due to COVID-19 pandemic induced emergency online learning at undergraduate level: Evidence from undergraduate students from Dhaka City.

Avijit Saha, Arpita Dutta, Ridwan Islam Sifat

Abstract read
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Article in Journal of affective disorders, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
–field-weighted citation impact
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

The trial behind it

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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

24 citing papers in PubMed.

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  18. Impact of Parents' Attitudes on Learning Ineffectiveness: The Mediating Role of Parental Self-Efficacy.International journal of environmental research and public health · 2022
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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

3 authors.

Avijit SahaDepartment of Development Studies, Bangladesh University of Professionals; Dhaka, Bangladesh.
Arpita DuttaDepartment of Development Studies, Bangladesh University of Professionals; Dhaka, Bangladesh.
Ridwan Islam SifatDepartment of Development Studies, Bangladesh University of Professionals; Dhaka, Bangladesh. Electronic address: ridwanislamsifat@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCOVID-19 outbreak has drawn out institutions to closure with several challenges for university students of undergraduate level in Dhaka city including an emergency shift from traditional learning to online learning, which associated digital divide, left several arguments in response to technological inefficiency, pedagogic inefficiency of teachers, inappropriate study environment and so on. Previous literature shows that the COVID-19 is imposing a threat to mental health all over the nation since its spread. This study intended to evaluate the emerging reasons for psychological distress among university students of undergraduate level in Dhaka, also assess the execution methods, barriers of online learning, and lastly, the attitudes of students regarding online learning throughout the pandemic.

methodsA mixed methodology was used to conduct the research. Primary data has been collected using simple purposive sampling on 180 undergraduate students, 9 interviews were taken including 6 in-depth interviews of different university undergraduates from Dhaka city and also 3 (KIIs) from specialists of pedagogy and medical anthropology, and a high official from Bangladesh Telecommunication Regulatory Commission (BTRC).

resultsBased on the Kessler K-10 distress scale, the study found that the prevalence of no psychological distress (16.67%) followed by mild (40%), moderate (30.56%), and severe psychological distress (12.78%).

conclusionThe results concluded considering several reasons for mild to severe psychological distress. The findings suggest some recommendations to accumulate the process of online learning effectively and also strategies to regulate the preferred mode of learning in future.

Indexed as

COVID-19Digital DivideEducation, DistanceBangladeshHumansPandemicsSARS-CoV-2StudentsCOVID-19Digital divideMental healthOnline learningUniversity students

Identifiers

PMID34298222
PMCPMC8433598

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.