Digital obesity in adolescents and adults

The research encompasses the examination of health problems arising from digital obesity, digital game addiction, social media addiction, device addiction, internet addiction, binge-watching, and health issues related to technological devices. Since these concepts are presumed to cause digital obesity and result in its consequences, the aim of the study is to investigate these concepts. In the process, there was a need to develop a scale to understand individuals' levels of digital obesity. As existing research did not yield a digital obesity scale, one was developed after corrections based on expert opinions, resulting in a draft scale comprising 46 items. Following validity, reliability, and exploratory factor analyses, a digital obesity scale consisting of 25 items was developed. The developed scale comprises five factors named digital game addiction, social media addiction, device internet addiction, binge-watching, and health problems. These factors consist of items designed to measure the respective dependencies. The developed scale is a valid and reliable instrument capable of measuring digital obesity levels with five factors. Data were collected from 223 participants through Google Forms, including 108 females and 105 males. Participants were distributed across age groups, with 25% in the 14-21 age range, 42% in the 22-29 age range, and approximately 33% aged 30 and above. In addition to scale items, a personal information form was created and added to the scale to determine participants' demographic characteristics. The research comprises one main problem and 12 sub-problems. The main problem focuses on participants' digital obesity levels, while sub-problems address variations in participants' digital obesity levels based on factors such as age, education level, place of residence, mother's education level, father's education level, internet access status, age of starting to use a phone, age of starting to use social media, age of starting to play digital games, daily average screen time, daily average digital game playing time, and daily internet-connected status. Analysis results for each sub-problem were determined based on scale sub-dimensions and discussed in comparison with existing literature.