Psychometric properties of the Arabic Perceived Digital Well-Being Scale (PDWS) in Saudi young adults

Rapid digital transformation in Saudi Arabia has intensified young adults' day-to-day reliance on smartphones, increasing the need for balanced, culturally appropriate measures of perceived digital well-being. This study aimed to psychometrically validate the Arabic version of the Perceived Digital Well-Being Scale (PDWS) among Saudi young adults aged (18-25). A cross-sectional instrument-validation study was conducted with (N = 450) participants. The full sample was randomly split into two independent analytic subsamples: Sample (1) for exploratory factor analysis (EFA) (n = 225) and Sample (2) for confirmatory factor analysis (CFA) (n = 225); convergent validity was examined in both subsamples. EFA supported a clear three-factor structure (Emotional, Social, Cognitive). CFA confirmed a second-order model with excellent fit: χ²(116)=133.275, p = .130, χ²/df=(1.149), CFI=(.986), TLI=(.983), RMSEA=(.026), and SRMR=(.055). Convergent validity was supported by positive associations with life satisfaction (SWLS) and negative associations with fear of missing out (FoMO), with the same pattern observed across both subsamples (Sample (2): SWLS r=(.416-.550), p < .01; FoMO r=(-.321--.254), p < .01). Internal consistency was acceptable across subsamples (Cronbach's α=(.759-.886); McDonald's ω=(.761-.889)). Overall, the Arabic PDWS demonstrates strong initial evidence of structural validity, theoretically consistent convergent validity, and adequate reliability, supporting its use as a multidimensional measure of perceived smartphone-related digital well-being among Saudi emerging adults.

Authors

Institutions

Publication Details

Journal
PLoS ONE
Published
2026-07-30
DOI
https://doi.org/10.1371/journal.pone.0354474
Primary Topic
Impact of Technology on Adolescents
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Psychometric properties of the Arabic Perceived Digital Well-Being Scale (PDWS) in Saudi young adults

Emadeldin M. Elsokkary
PLoS ONE
Impact of Technology on Adolescents
article

Psychometric properties of the Arabic Perceived Digital Well-Being Scale (PDWS) in Saudi young adults

Emadeldin M. Elsokkary
article en

Abstract

Rapid digital transformation in Saudi Arabia has intensified young adults' day-to-day reliance on smartphones, increasing the need for balanced, culturally appropriate measures of perceived digital well-being. This study aimed to psychometrically validate the Arabic version of the Perceived Digital Well-Being Scale (PDWS) among Saudi young adults aged (18-25). A cross-sectional instrument-validation study was conducted with (N = 450) participants. The full sample was randomly split into two independent analytic subsamples: Sample (1) for exploratory factor analysis (EFA) (n = 225) and Sample (2) for confirmatory factor analysis (CFA) (n = 225); convergent validity was examined in both subsamples. EFA supported a clear three-factor structure (Emotional, Social, Cognitive). CFA confirmed a second-order model with excellent fit: χ²(116)=133.275, p = .130, χ²/df=(1.149), CFI=(.986), TLI=(.983), RMSEA=(.026), and SRMR=(.055). Convergent validity was supported by positive associations with life satisfaction (SWLS) and negative associations with fear of missing out (FoMO), with the same pattern observed across both subsamples (Sample (2): SWLS r=(.416-.550), p < .01; FoMO r=(-.321--.254), p < .01). Internal consistency was acceptable across subsamples (Cronbach's α=(.759-.886); McDonald's ω=(.761-.889)). Overall, the Arabic PDWS demonstrates strong initial evidence of structural validity, theoretically consistent convergent validity, and adequate reliability, supporting its use as a multidimensional measure of perceived smartphone-related digital well-being among Saudi emerging adults.

PLoS ONEVol. 21(7)
Imam Mohammad ibn Saud Islamic University (SA)
American Educational Research Association
Openalex Percentile: Top 4%
Impact of Technology on Adolescents
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.