Perceived Digital Well-Being Scale in the United States and United Kingdom: Psychometric Validation Study
Bibliographic record
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; t1852=4.97; P<.001; d=0.27 and mean 3.62 vs mean 3.29; t1852=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; t1852=3.33; P<.001; d=0.15). Male participants were significantly more represented among the group with higher PDWB scores (χ2136=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 (χ2246 change=17.90; P=.21); however, strict invariance across gender (male vs female) was not supported (χ2246 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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".