作者
Germano Vera Cruz,Magdalena Liberacka-Dwojak,Monika Wiłkość-Dębczyńska,Merve Aktaş Terzioğlu,Todd J. Farchione,Tania Lecomte,Sandy Ingram,Riaz Khan,Yasser Khazaal
摘要
Abstract Background Digital well-being encourages balanced mobile use. The Perceived Digital Well-Being in Adolescence Scale measures this in adolescents but has been validated only in Slovenia, raising questions about its relevance for other age groups and cultural contexts. Objective This study had three primary objectives: (1) confirm the 3-factor structure of an English version of the Perceived Digital Well-Being in Adolescence Scale, renamed the Perceived Digital Well-Being Scale (PDWS), in samples of young adults from the United States and the United Kingdom; (2) examine the associations between PDWS dimensions and participants’ sociodemographic characteristics; and (3) explore the relationships between PDWS scores and patterns of smartphone use. Methods A total of 1854 young adults from the United States and the United Kingdom (ages 18‐25 years; mean 22.4, SD 2.1; 892, 48.1% female, 872, 47.0% male, 90, 4.9% nonbinary) participated in an online survey including the PDWS, digital flourishing, and digital stress measures. Data were analyzed using descriptive statistics, confirmatory factor analysis, correlations, t tests, chi-squared tests, and moderation-mediation analysis. Results Smartphone screen time and smartphone time for nonessential activities were statistically higher in the US sample than in the UK sample (mean 6.95 vs mean 6.13; t 1852 =4.97; P <.001; d =0.27 and mean 3.62 vs mean 3.29; t 1852 =5.57; P <.001; d =0.25, respectively). The digital well-being total score was statistically higher among US participants when compared with the UK counterparts (mean 3.49 vs mean 3.38; t 1852 =3.33; P <.001; d =0.15). Male participants were significantly more represented among the group with higher PDWB scores ( χ 2 136 =478.45; P <.001). Confirmatory factor analysis supported the adequacy of the 3-factor model (emotional, social, and cognitive), indicating strong model fit (critical indices ≥0.90). Evidence of convergent validity was established through significant associations between PDWS scores and measures of digital flourishing and digital stress (most correlation coefficients being significant at P <.001). Measurement invariance testing confirmed the scale’s equivalence across US and UK samples ( χ 2 246 change=17.90; P =.21); however, strict invariance across gender (male vs female) was not supported ( χ 2 246 change=200.91; P <.001). Gender, sexual orientation, relationship status, ethnicity, socioeconomic status, and education level significantly influenced PDWS scores. Gender and socioeconomic status also moderated the relationship between smartphone use or screen time and PDWS scores ( b =0.048; P =.03 and b =0.020; P =.03, respectively), indicating that these factors affect how smartphone usage relates to psychological distress or well-being in different demographic groups. Conclusions The PDWS showed good psychometric properties in the US and UK samples. The scale offers a promising tool for identifying individuals at risk of adverse outcomes associated with digital connectivity.