Digital device usage and psychological well-being in the post-COVID-19 era: insights from a cross-sectional survey

Abstract The COVID-19 pandemic accelerated digital technology adoption worldwide, yet limited evidence links post-pandemic multi-purpose online behavior with health outcomes and psychological well-being (PWB) in a single, integrated analysis. This study examines how digital device usage, breadth of online activity and self-reported Health Complaints relate to PWB across pre-COVID, during-COVID, and post-2023 periods. A cross-sectional survey of 622 respondents (collected in two pooled recruitment waves: Wave 1, $$n{=}323$$ ; Wave 2, $$n{=}299$$ ) assessed device usage across three temporal periods, online purpose diversity, Health Complaints (12 indicators), and PWB (Ryff’s 18-item scale). Spearman correlations with permutation-based p -values and Benjamini–Hochberg FDR correction were used. Group comparisons employed permutation tests with Cohen’s d effect sizes and bootstrap 95% confidence intervals. K -means clustering ( $$k{=}3$$ ) identified behavioral segments. PWB was negatively associated with Health Complaints count ( $$\rho =-0.319$$ , $$p_{\text {FDR}}<0.05$$ ). Broader online purpose use correlated with more health effects ( $$\rho =0.202$$ , $$p_{\text {FDR}}<0.05$$ ). High online-purpose users (top quartile) reported significantly more Health Complaints than low users ( $$\Delta =+1.55$$ , $$d=0.54$$ , $$p_{\text {FDR}}<0.001$$ ). A partial Spearman correlation confirmed that this association persisted after controlling for total screen time ( $$\rho _{\text {partial}}{=}0.154$$ , $$p_{\text {perm}}{<}0.001$$ , 95% CI [0.07, 0.23]), though the effect size was modest. Retrospective group-level estimates were higher for the during-COVID period than the pre-COVID baseline, with a lower estimate in Wave 2; these reflect between-wave, not within-person, comparisons. Three behavioral clusters emerged: low-usage/minimal-effects ( $$n{=}142$$ ), high multi-device users ( $$n{=}291$$ ), and higher health-effects/lower-PWB users ( $$n{=}189$$ ). Among young, educated, urban adults, breadth of online activity was cross-sectionally associated with more self-reported adverse Health Complaints; both factors independently and collectively accounted for significant variance in PWB. These findings highlight the urgent need for digital wellness strategies that address activity diversity — not only total screen time — among young, educated, urban adults who represent the heaviest users of multi-purpose internet services in post-pandemic settings.

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Journal
BMC Psychology
Published
2026-08-03
DOI
https://doi.org/10.1186/s40359-026-05205-x
Primary Topic
Technology Adoption and User Behaviour
Type
article
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article

Digital device usage and psychological well-being in the post-COVID-19 era: insights from a cross-sectional survey

Annajiat Alim Rasel, Razoana Ayshee, Umme Nusrat Jahan, Mohammad Quamruzzaman et al.
BMC Psychology
Technology Adoption and User Behaviour
article

Digital device usage and psychological well-being in the post-COVID-19 era: insights from a cross-sectional survey

Annajiat Alim Rasel, Razoana Ayshee, Umme Nusrat Jahan, Mohammad Quamruzzaman, Md Jafrin Hossain, Ariful Hasan Shuvo, Munima Haque, Md. Shohag Hossain
article en

Abstract

Abstract The COVID-19 pandemic accelerated digital technology adoption worldwide, yet limited evidence links post-pandemic multi-purpose online behavior with health outcomes and psychological well-being (PWB) in a single, integrated analysis. This study examines how digital device usage, breadth of online activity and self-reported Health Complaints relate to PWB across pre-COVID, during-COVID, and post-2023 periods. A cross-sectional survey of 622 respondents (collected in two pooled recruitment waves: Wave 1, $$n{=}323$$ ; Wave 2, $$n{=}299$$ ) assessed device usage across three temporal periods, online purpose diversity, Health Complaints (12 indicators), and PWB (Ryff’s 18-item scale). Spearman correlations with permutation-based p -values and Benjamini–Hochberg FDR correction were used. Group comparisons employed permutation tests with Cohen’s d effect sizes and bootstrap 95% confidence intervals. K -means clustering ( $$k{=}3$$ ) identified behavioral segments. PWB was negatively associated with Health Complaints count ( $$\rho =-0.319$$ , $$p_{\text {FDR}}<0.05$$ ). Broader online purpose use correlated with more health effects ( $$\rho =0.202$$ , $$p_{\text {FDR}}<0.05$$ ). High online-purpose users (top quartile) reported significantly more Health Complaints than low users ( $$\Delta =+1.55$$ , $$d=0.54$$ , $$p_{\text {FDR}}<0.001$$ ). A partial Spearman correlation confirmed that this association persisted after controlling for total screen time ( $$\rho _{\text {partial}}{=}0.154$$ , $$p_{\text {perm}}{<}0.001$$ , 95% CI [0.07, 0.23]), though the effect size was modest. Retrospective group-level estimates were higher for the during-COVID period than the pre-COVID baseline, with a lower estimate in Wave 2; these reflect between-wave, not within-person, comparisons. Three behavioral clusters emerged: low-usage/minimal-effects ( $$n{=}142$$ ), high multi-device users ( $$n{=}291$$ ), and higher health-effects/lower-PWB users ( $$n{=}189$$ ). Among young, educated, urban adults, breadth of online activity was cross-sectionally associated with more self-reported adverse Health Complaints; both factors independently and collectively accounted for significant variance in PWB. These findings highlight the urgent need for digital wellness strategies that address activity diversity — not only total screen time — among young, educated, urban adults who represent the heaviest users of multi-purpose internet services in post-pandemic settings.

BMC Psychology
Shahjalal University of Science and Technology (BD), Florida International University (US), Daffodil International University (BD), World University of Bangladesh (BD), BRAC University (BD), East West University (BD)
Good health and well-being
Openalex Percentile: Top 5%
Technology Adoption and User Behaviour
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