Multidimensional Poverty as a Determinant of Techno-Distress in Online Education

Evidence from the Post-Pandemic Era

Bibliographic Data

ID15499887
AuthorsAlejandro Cataldo (0000-0002-8183-591X, University of Talca), Natalia Bravo-Adasme (0000-0001-8612-6170, University of Talca, corresponding author), Andrés Riquelme (0000-0003-1220-0926, University of Talca), Abiguey Vásquez (0009-0004-2856-3494, University of Talca), Ariela Vásquez (University of Talca), Sebastián Joaquín Ocampo Rojas (0000-0003-4183-4960, University of Talca), Sebastián Rojas (0000-0002-6206-8436, University of Talca), Mario Arias-Oliva (0000-0002-6874-4036, Universidad Complutense de Madrid)
Year2025
Volume22
Issue7
Pages986-986
Publication date2025-06-23
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph22070986
PMID40724053
OpenAlexW4411605824
LanguageEN
Citations received1
References cited48

The rapid shift to online education during the COVID-19 pandemic exacerbated mental health risks for students, particularly those experiencing multidimensional poverty-a potential contributor to psychological distress in digital learning environments. This study examines how poverty-driven techno-distress (technology-related stress) impacts university students' mental health, focusing on 202 Chilean learners engaged in remote classes. Using partial least squares structural equation modeling (PLS-SEM), we analyzed multidimensional poverty and its association with techno-distress, measured through validated scales. The results suggest that poverty conditions are associated with 32.5% of technostress variance (R 2 = 0.325), while techno-distress may indirectly relate to 18.7% of students' dissatisfaction with academic life-a proxy for emerging mental health risks. Importance-performance map analysis (IPMA) identified housing habitability (e.g., overcrowding, inadequate study spaces) and healthcare access as priority intervention targets, surpassing purely digital factors. These findings indicate that techno-distress in online education may function as a systemic stressor, potentially amplifying pre-existing inequities linked to poverty. For educators and policymakers, this highlights the urgency of early interventions addressing students' physical environments alongside pedagogical strategies. By framing techno-distress as a public health challenge rooted in socioeconomic disparities, this work advances preventive approaches to safeguard student well-being in increasingly hybrid educational landscapes

Coronavirus disease 2019 (COVID-19 · Disease · Distress · Economic growth · Economics · Environmental health · Mental health · Pandemic · Population · Poverty · Psychiatry · Psychological intervention · Public health · Socioeconomic status · Clinical Psychology · COVID-19 and Mental Health · Impact of Technology on Adolescents · Medicine · Nursing · Psychology · Technostress in Professional Settings

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