Bedtime smart device usage and accelerometer-measured sleep outcomes in children and adolescents

Purpose: we analyzed the association between bedtime smart device usage habits and accelerometer-measured sleep outcomes (total sleeping time, sleep efficiency, and wake after sleep onset) in Hong Kong children and adolescents aged 8–14. Methods: a total of 467 students in Hong Kong participated in this study from 2016 to 2017. They self-reported their bedtime smart device usage habits. The primary caregiver of each participant was also invited to complete a self-administered questionnaire about the family’s social-economic status and bedtime smart device usage habits. An ActiGraph GT3X accelerometer was used to assess participants’ 7-day sleep outcomes. Results: the mean age of the participants was 10.3 (SD 1.9), and 54% were girls. Among the participants, 27% (n = 139) used a smart device before sleep, and 33% (n = 170) kept the smart device on before sleep. In total, 27% (n = 128) placed the smart device within reach before sleep, 23% (n = 107) would wake up when notifications were received, and 25% (n = 117) immediately checked the device after being awakened by a notification. Multiple regression controlling for age, sex, socio-economic status, and other confounders showed that those who woke up after receiving a notification had a statistically longer sleeping time (19.7 min, 95% CI: 0.3, 39.1, p = 0.046), lower sleep efficiency (− 0.71%, 95% CI − 1.40, − 0.02, p = 0.04), and a longer wake after sleep onset (2.6 min, 95% CI: 0.1, 5.1, p = 0.045) than those who did not. Nonetheless, all primary caregivers’ bedtime smart device habits were insignificantly associated with all sleep outcomes of their children. Conclusion: those who woke up after receiving smart device notifications had lower sleep efficiency and longer wake after sleep onset than those who did not, and they compensated for their sleep loss by lengthening their total sleep time.</p

Psychometric properties and demographic correlates of the smartphone addiction scale-short version among Chinese children and adolescents in Hong Kong

Nearly all children and teens in Hong Kong own a smartphone. There is currently no validated instrument that measures whether they use their phone too much. This study tested the psychometric properties of a translated Chinese version of the Smartphone Addiction Scale-Short Version (SAS-SV) and examined the demographic correlates of smartphone addiction among Hong Kong children and adolescents. A total of 1,901 primary school children and secondary school pupils were recruited from 15 Hong Kong schools. Furthermore, 1,797 primary caregivers were asked to complete a self-administered questionnaire on their socioeconomic status and educational attainment. The study used exploratory factor analysis (EFA) to identify the factor structure of SAS-SV for half the participants (n = 951), while confirmatory factor analysis (CFA) was used to assess the goodness-of-fit of EFA models for the remaining half (n = 951). Spearman correlations were used to assess the convergent validity of the SAS-SV, taking account of time spent by subjects on phones per day, the Smart Device Addiction Screening Tool (SDAST), the Pittsburgh Sleep Quality Index (PSQI), the Multidimensional Scale of Perceived Social Support (MSPSS), and the Center for Epidemiological Studies Depression Scale for Children (CES-DC). EFA generated a three-factor model (with factors labeled "dependency," the incidence of a "problem," and "time spent"). CFA confirmed this model yielded an acceptable goodness-of-fit (Comparative Fit Index = 0.96, Tucker Lewis Index = 0.95, and root-mean-square error of approximation = 0.06). SAS-SV was positively correlated with SDAST (ρ = 0.59), PSQI (ρ = 0.29), and CES-D (ρ = 0.35), and negatively correlated with MSPSS (ρ = -0.10). A linear regression model showed that female adolescents, those with highly educated caregivers and those who spent more time using smartphones on their holidays, had on average higher SAS-SV scores, meaning they showed greater vulnerability to becoming addicted. The study found that SAS-SV is a valid scale for estimating excessive smartphone use among Hong Kong children and adolescents

Association between time spent on smart devices and change in refractive error: a 1-year prospective observational study among Hong Kong children and adolescents

This study examined the association between smart device usage and the 1-year change in refractive error among a representative sample of Hong Kong children and adolescents aged 8–14 years. A total of 1597 participants (49.9% male, mean age 10.9, SD 2.0) who completed both baseline (2017–2018) and 1-year follow-up (2018–2019) eye examinations were included in the present study. The non-cycloplegic auto-refractive error was measured and the average spherical equivalent refraction (SER) was analyzed. The participants also self-reported their smart device usage at baseline. Multivariate regression adjusted for age, sex, baseline SER, parents’ short-sightedness, BMI, time spent on moderate-to-vigorous physical activity (MVPA), and caregiver-reported socio-economic status showed that, compared with the reference group (&lt;2 h per day on both smartphone and tablet usages), those who spent ≥2 h per day using a smartphone and &lt;2 h per day using a tablet had a significantly negative shift in refractive error (1-year change in SER −0.25 vs. −0.09 D, p = 0.01) for the right eye, while the level of significance was marginal (1-year change −0.28 vs. −0.15 D, p = 0.055) for the left eye. To conclude, our data suggested spending at most 2 h per day on both smartphones and tablets