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Too much screen time? – perception and actual smartphone usage, gender differences and academic success
Abstract
The number of hours spent using mobile phones has been increasing over the years and is especially visible in younger generations. Interestingly, the body of research on this emerging topic is mainly based on self-assessment measures of screen time. There are few studies on mobile phones in Croatia. Therefore the aim of this study was to examine how many hours Croatian high school students spend on mobile phones and see if there is a discrepancy in self-estimates of high-school students’ screen time compared to the objective measure obtained through an application for screen time tracking. Moreover, gender differences in screen time were analysed, as well as differences between different levels of students’ academic achievement. This study included 156 high-school pupils aged 14 to 18. They were asked to fill out a questionnaire about their smartphone usage habits and attitudes, while their smartphone usage was tracked for one week using the Screen Time application. The analysis was done based on data collected from 130 participants. Most of the students reported that they spend 2 to 4 hours a day using their smartphones, while their actual screen time is, on average, 5 hours and 29 minutes per day. 64.6% of the students underestimated the time spent on their smartphones. Moreover, most of the students believe that it is recommended to spend 1-2 hours a day using a smartphone, while addiction is formed when a phone is used for 2-4 hours a day. There were no significant differences in screen time between students with different school achievements, as well as between male and female students. However, when gender differences were examined for different categories of mobile phone applications, the results showed that female students spent more time on social media applications while male students spent more time using multimedia applications.
... In the same way, another study highlights that most research analysing the degree of adherence to the Mediterranean diet among Spanish adolescents and adolescents from different countries has not found significant differences between sexes either (Tapia- . Regarding other variables, there are studies such as the one by Maljur et al. (2022) that have observed no significant differences in screen time between students of both sexes. Another example is the study by Gómez-Mármol et al. (2013), which states that no significant differences were found in body image dissatisfaction between boys and girls. ...
The decline in quality of life in recent decades in Spain and how it is related to health factors highlight the importance of considering health-related quality of life (HRQOL) as a key indicator in the assessment of well-being. Marked by physical, hormonal and social changes, adolescence is a critical period when lifestyle habits are consolidated, including physical activity and diet, which affect HRQOL. There are growing concerns that body image, especially in a context of increased sedentarism and screen use, is associated with low self-esteem and mental health problems. The promotion of healthy habits and a positive body image during this age is essential to improve overall well-being and prevent psychological disorders. This study examines differences in screen time, Mediterranean diet adherence, health-related quality of life and body image self-concept in children and adolescents, considering gender and educational level. A cross-sectional analysis was conducted with 305 students (ages 11–14) from primary and secondary schools. The instruments used to measure the different variables were the KIDMED questionnaire for adherence to the Mediterranean diet, the Screen-time Sedentary Behaviour Questionnaire (SSBQ) for screen time, the KIDSCREEN for health-related quality of life and the Body Size Guides (BSGs) for body image perception. The results showed significant differences by educational stage in screen time, health-related quality of life and body image, with secondary school students reporting higher values. No significant differences were found based on sex. The originality of this study lies in its holistic approach to identify patterns of behaviour and well-being, influenced by sociocultural and demographic factors, and in the detailed analysis of variations by age and gender that affect physical and mental health during critical stages of development. The findings highlight the need for educational strategies to promote healthy lifestyles, involving students, families and their environments, to enhance well-being and self-esteem.
Relationships between multiple sleep outcomes, obesity and adiposity across childhood and adolescence have been previously reported. Health‐promoting interventions to improve sleep and reduce adolescent obesity could target shared determinants of sleep and obesity. The aim of this systematic review was to systematically identify and examine research that investigated the shared determinants of poor sleep and increased adiposity or obesity in adolescents. A systematic literature search covering publications up to April 2024 was conducted across 10 bibliographic databases. Search terms included objective and subjective sleep/circadian rhythm measurements, objective adiposity measurements and adolescents aged 8–18 years. Eighty studies were included in the final review. Determinants were categorised into three different domains: socioenvironmental determinants, behavioural determinants and health determinants. Shared determinants of poor sleep and increased adiposity or obesity in adolescents aged 8–18 years included: socioenvironmental determinants (gender, ethnicity, pubertal status, academic attainment), behavioural determinants (timing of moderate‐to‐vigorous physical activity (MVPA), unhealthy diet choices and timing of consumption and screen time and videogaming quantity and timing) and health determinants (wellbeing). These findings suggest that sleep hygiene and the modifiable shared behavioural determinants should be targeted in health‐promoting interventions, and statistical analyses should be adjusted for socioenvironmental determinants and wellbeing.
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