This study was designed to investigate the revised and short version of the smartphone addiction scale and the proof of its validity in adolescents. In addition, it suggested cutting off the values by gender in order to determine smartphone addiction and elaborate the characteristics of smartphone usage in adolescents. A set of questionnaires were provided to a total of 540 selected participants from April to May of 2013. The participants consisted of 343 boys and 197 girls, and their average age was 14.5 years old. The content validity was performed on a selection of shortened items, while an internal-consistency test was conducted for the verification of its reliability. The concurrent validity was confirmed using SAS, SAPS and KS-scale. Receiver operating characteristics analysis was conducted to suggest cut-off. The 10 final questions were selected using content validity. The internal consistency and concurrent validity of SAS were verified with a Cronbach's alpha of 0.911. The SAS-SV was significantly correlated with the SAS, SAPS and KS-scale. The SAS-SV scores of gender (p<.001) and self-evaluation of smartphone addiction (p<.001) showed significant difference. The ROC analysis results showed an area under a curve (AUC) value of 0.963(0.888–1.000), a cut-off value of 31, sensitivity value of 0.867 and specificity value of 0.893 in boys while an AUC value of 0.947(0.887–1.000), a cut-off value of 33, sensitivity value of 0.875, and a specificity value of 0.886 in girls. The SAS-SV showed good reliability and validity for the assessment of smartphone addiction. The smartphone addiction scale short version, which was developed and validated in this study, could be used efficiently for the evaluation of smartphone addiction in community and research areas.

Background and Aims: Smartphone addiction, its association with smartphone use, and its predictors have not yet been studied in a European sample. This study investigated indicators of smartphone use, smartphone addiction, and their associations with demographic and health behaviour-related variables in young people. Methods: A convenience sample of 1,519 students from 127 Swiss vocational school classes participated in a survey assessing demographic and health-related characteristics as well as indicators of smartphone use and addiction. Smartphone addiction was assessed using a short version of the Smartphone Addiction Scale for Adolescents (SAS-SV). Logistic regression analyses were conducted to investigate demographic and health-related predictors of smartphone addiction. Results: Smartphone addiction occurred in 256 (16.9%) of the 1,519 students. Longer duration of smartphone use on a typical day, a shorter time period until first smartphone use in the morning, and reporting that social networking was the most personally relevant smartphone function were associated with smartphone addiction. Smartphone addiction was more prevalent in younger adolescents (15–16 years) compared with young adults (19 years and older), students with both parents born outside Switzerland, persons reporting lower physical activity, and those reporting higher stress. Alcohol and tobacco consumption were unrelated to smartphone addiction. Discussion: Different indicators of smartphone use are associated with smartphone addiction and subgroups of young people have a higher prevalence of smartphone addiction. Conclusions: The study provides the first insights into smartphone use, smartphone addiction, and predictors of smartphone addiction in young people from a European country, which should be extended in further studies.

Kim SM, et al. J Korean Neuropsychiatr Assoc. 2014 Jul;53(4):214-220. http://dx.doi.org/10.4306/jknpa.2014.53.4.214

The female-headed household is a new vulnerable group associated with health inequality. The purpose of this study was to analyze psychological well-being and related factors among Korean female-headed households based on age stratification. This was a secondary analysis of data extracted from the fifth Korean Working Conditions Survey (2017), which included a total of 9084 female-headed households. Their psychological well-being was measured by the WHO-5 well-being index. A total of 39.8% of female-headed household workers were psychologically unhealthy. Among them, 2.2% of those aged 15–30 years old, 8.1% aged 30–50 years old, and 29.5% over aged 50 years old were unhealthy. In the age group of 15–30 years old, depression/anxiety was negatively associated with psychological well-being. In the age group of 30–50 years old, living alone, musculoskeletal pain, fatigue, and depression/anxiety were negatively associated with psychological well-being. In the age group over 50 years old, low education level, living alone, low income, musculoskeletal pain, fatigue, and depression/anxiety were negatively associated with psychological well-being. The psychological well-being perceived by female households is complex and goes beyond economic poverty and dependent burdens. Therefore, a multidimensional support strategy should be included in the concept of social deprivation, and a preventive approach is needed to establish a support system.