Effect of Electronic Device Addiction on Sleep Quality and Academic Performance Among Health Care Students: Cross-sectional Study

Validity and reliability of the Korean version of the Digital Burnout Scale

Objectives

To investigate the factor structure and verify the validity and reliability of the Korean version of the Digital Burnout Scale (DBS) among Generation Z university students.

Methodology

The World Health Organization guidelines were employed in the forward and back translation, synthesis, cross-cultural adaptation, and pre-survey phases to result in the Korean version of the DBS. The Korean version was then used to collect data from 330 university students online. Construct, convergent, discriminant, and concurrent validity, and internal consistency were assessed.

Findings

The Korean version of the DBS had three subscales (digital aging, digital deprivation, and emotional exhaustion) and included 24 items. The results of the confirmatory factor analysis indicated adequate model fit indices. Convergent, discriminant, and concurrent validity were satisfactory. The Cronbach's ⍺ for the overall scale was 0.95.

Conclusion

The Korean version of the DBS has good reliability and validity and can be used as a tool to assess the level of risk of digital burnout and provide appropriate support and intervention.

Implications

The Korean version of the DBS will serve as a framework for developing healthy digital education by grasping individual characteristics. Longitudinal research is recommended to identify factors that cause digital usage and burnout for various age groups.

Digital Addiction and Related Factors among College Students

(1) Background: Digital addiction has been a global concern, with college students becoming increasingly vulnerable to it. The detrimental psycho-physiological effects of digital addiction have raised concerns regarding college students' health. This descriptive correlational study was conducted to evaluate the prevalence of digital addiction and identify influencing factors among college students, such as body shape satisfaction, time management, and psychological health. (2) Methods: Data were collected from 199 students at a university in Seoul, South Korea, from 30 May to 13 June 2023. The Digital Addiction Scale (DAS), Time Structure Questionnaire (TSQ), General Health Questionnaire (GHQ), and Body Shape Questionnaire (BSQ) were used for the assessment. Data (N = 199) were analyzed using descriptive statistics, one-way ANOVA, Pearson's correlation coefficient, and stepwise multiple regression. (3) Results: The mean score for digital addiction was 54 ± 12, with scores ranging from 23.0 to 89.0. Digital addiction had a significant positive correlation with body shape satisfaction (r = 0.156, p = 0.028) and a negative correlation with time management (r = -0.500, p < 0.001). In the stepwise multiple regression model of digital addiction (adjusted R2 = 0.285, p < 0.001), subfactors of body shape satisfaction (fear of fatness β = -0.280, body dissatisfaction β = 0.401) and time management (effective organization β = -0.211, persistence β = -0.209, past orientation β = -0.165) were statistically significant. (4) Conclusions: Body shape satisfaction and time management are important factors influencing digital addiction among college students. However, it does not establish a direct causal relationship. The findings indicate that there is a statistical association or connection between these factors, but they do not definitively state that body shape satisfaction or time management directly cause digital addiction. To decrease digital addiction in this population, interventions should aim to improve body shape satisfaction and time management.

Dose-response analysis of smartphone usage and self-reported sleep quality: a systematic review and meta-analysis of observational studies

STUDY OBJECTIVES

Several studies have recently reported on the association between smartphone usage and self-reported sleep quality. However, no systematic review or meta-analysis has yet been performed. We aimed to analyze the association between smartphone usage time and self-reported sleep quality.

METHODS

We searched for articles published up to January 13, 2022, using the Embase and Medline databases. All observational studies were eligible for inclusion. The Newcastle-Ottawa scale was used to evaluate the risk of bias within studies. We used restricted cubic spline analysis to perform a dose-response analysis.

RESULTS

Seventeen studies with a total of 36,485 participants were included. The pooled odds ratio was 2.28 (confidence interval [CI]: 1.81-2.89; P < .001) and heterogeneity was 80%. In the dose-response analysis conducted on 5 studies, the regression coefficient between daily smartphone usage time (hours/day) and poor sleep quality was 1.042 (1.027-1.058), which confirmed a significantly positive association.

CONCLUSIONS

Smartphone overuse was closely associated with poor self-reported sleep quality, sleep deprivation, and sleep latency prolongation. Further studies using a more structured method and high-quality evidence (cohort or case-control) should be conducted.

SYSTEMATIC REVIEW REGISTRATION

CRD42022303371.

CITATION

Chu Y, Oh Y, Gwon M, et al. Dose-response analysis of smartphone usage and self-reported sleep quality: a systematic review and meta-analysis of observational studies. J Clin Sleep Med. 2023;19(3):621-630.

The impact of sleep–wake problems on health-related quality of life among Japanese nursing college students: a cross sectional survey

Aim

This study was conducted to examine the impact of sleep–wake problems on health-related quality of life of Japanese nursing college students. 

Methods

This cross-sectional study was conducted in 2019 on 150 third and fourth-year nursing college students from two locations in Japan. Insomnia severity was assessed using the Insomnia Severity Index (ISI) and health-related quality of life using the SF-8 questionnaire. The total sleep time (TST) was divided into 3 groups: < 6 h, 6–7 h (reference), and ≥ 7 h. The total ISI score was divided into 2 groups: ≥ 8 points and < 8 points (reference). Logistic regression analysis was performed to evaluate sleep–wake problems related to decline in mental health.

Results

The median mental health indicated in the SF-8 questionnaire was divided into two groups, and the factors causing decline in mental health were investigated. The odds ratios (95% confidence interval) for adjusted ISI ≥ 8 and TST on weekdays < 6 h was 6.51 (2.96–14.30) and 3.38 (1.40–8.17), respectively. Mental health status was significantly lower when ISI ≥ 8 and even lower when TST < 6 h.

Conclusion

Insomnia and short sleep duration are associated with decreased mental health status in nursing college students. Many tended to lack sleep on weekdays. Sleep–wake problems identified while in university should be comprehensively dealt with.