Objective:

Individuals' digital consumption habits have changed as a result of the rapid advances in information and communication technology and the pandemic. Although digitalization facilitates the fulfillment of many needs including educational, social, practical, and entertainment; it exposes individuals to a variety of risks depending on the intensity, area and purpose of use. Digital obesity, a current concept, can be defined as individuals having easy access to digital content and becoming addicted to it by consuming it in large quantities. It is associated with the desire to consume a large amount of content in a short period of time, with technological tools becoming human limbs and leaving one feeling incomplete without them. However, there is conflict about who is "digitally obese" and what the boundaries should be. Students who have just started university are one of the groups that use technology extensively and are vulnerable to a variety of risks due to the developmental stage they are in. In this context the aim of this study is to conceptualize digital obesity and reveal the consequences of digital obesity on young people.

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Methodology:

This is a correlational study, consisting of two parts: First, by using FoMo, binge-watching and screen use types variables, a norm for digital obesity will be developed. Secondly, using this norm, (digital obese and non-obese) participants will be compared on sleep quality, depression, negative self-perception, somatization, hostility.

Data collection process is still ongoing, however study group is aimed to be consist of approximately 500 participants. Data collection tools are demographic information form, screen use information form, FoMo scale, binge-watching engagement and symptoms questionnaire, sleep quality scale, and brief symptom inventory. A norm development study will be conducted based on the cutoff score in measuring the concept of digital obesity. In line with the second objective of the study, MANOVA analysis will be performed to compare the "digital obese" and "non-digital obese" groups, in terms of low sleep quality, depression, anxiety, negative self-perception, somatization and hostility levels.

Expected Results:

In this study it is expected that digital obesity have significant effect on outcomes such as sleep quality, depression, anxiety, negative self-perception, somatization and hostility. Individuals in the digital obese group are expected to have lower sleep quality and higher levels of depression, anxiety, negative self- perception, somatization, and hostility than those in the other group.

Conclusion:

In conclusion, digital obesity is expected to have significant negative effects on young people’s mental health and sleep quality. However, this study has limitations as well. Future studies may take a more ecological approach and measure screen use prospectively.