Screen Time
Conditions
Keywords
smartphone, problematic digital use, depression, academic motivation, young adult, adolescent, digital phenotyping
Brief summary
The goal of this observational study is to describe how adolescents and young adults use screens in their daily lives and to identify different profiles of screen use ranging from low to excessive. The study also aims to understand how screen-use behaviors relate to health, motivation, and sociodemographic factors. The main questions it aims to answer are: What are the objective and self-reported patterns of screen use (e.g., frequency of use, types of apps, daily time spent, usage periods)? Do distinct screen-use profiles emerge (low, moderate, intensive/excessive) when taking into account: Age, gender, educational track (general, technological, vocational), Parents' socioeconomic status, Health variables (sleep quality, physical activity/sedentary behavior, well-being), Cognitive and conative variables (self-regulation capacity, academic motivation)? Are excessive users characterized by specific patterns, such as intensive use of social media, video platforms, or video games combined with mood problems, sleep difficulties, or motivational issues? Do screen-use profiles vary depending on age group (middle school, high school, university) and gender? Are there mediating mechanisms explaining excessive use? Specifically: Does poor self-regulation mediate the link between screen-use intensity and well-being? Do sleep problems mediate the link between excessive nighttime use and mood disturbances (anxiety, depression)? Do academic motivation and cognitive factors mediate differences between moderate and excessive users? If groups differ, researchers will compare low-use, moderate-use, and excessive-use profiles to determine whether they show meaningful differences in health, motivation, and sociodemographic characteristics. Participants will: Install a smartphone application that passively records daily screen-use indicators (e.g., usage time, app categories, frequency of openings, time windows of use). Complete questionnaires assessing: Self-reported screen use, Sleep, physical activity, well-being, Mood variables (anxiety, depression), Self-regulation, Academic motivation, Sociodemographic factors (age, gender, parents' SES, educational track).
Interventions
DEVICEPhonixDiag Smartphone Monitoring Tool
PhonixDiag is a passive smartphone-based monitoring tool designed to collect objective digital behavior indicators in real time. The tool runs in the background of the participant's smartphone and records daily screen-use patterns, including frequency of app openings, time spent on recreational applications, usage periods throughout the day, and nighttime phone activity. PhonixDiag does not modify the participant's phone use or deliver any behavioral intervention. It functions solely as a data collection system to objectively assess screen-use behaviors and identify usage profiles (low, moderate, excessive). The tool is distinct from other digital interventions because it does not provide feedback, warnings, or recommendations, and operates exclusively for passive monitoring purposes.
Sponsors
Phonix Health
Study design
Observational model
COHORT
Time perspective
CROSS_SECTIONAL
Eligibility
Sex/Gender
ALL
Age
12 Years to 25 Years
Healthy volunteers
Yes
Inclusion criteria
* Own an Android smartphone * Have at least 200 MB of storage on your smartphone * Be in middle school, high school, or university * Be enrolled in a school within the Grenoble academy district
Exclusion criteria
* Own an iPhone * Participate in an interventional study in the field within the last six months * Not sign the consent form
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Objective Screen Use Time (Daily Median Over Monitoring Period) | From enrollment to the end of treatment at 4 weeks | Objective screen-use time will be measured using the PhonixDiag smartphone monitoring tool. The outcome corresponds to the median daily duration (in minutes) spent on smartphone applications across the full monitoring period. This includes all app categories and reflects real-world behavioral engagement with digital media. The measure will be used to classify participants into usage profiles (low, moderate, excessive) and to examine associations with age, gender, socioeconomic status, sleep, physical activity, well-being, self-regulation, and academic motivation. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Sleep Quality (Self-Reported Index) | 7 days | Participants will complete a self-reported measure of sleep quality, including sleep duration, bedtime regularity, and perceived sleep disturbances. This outcome will be explored in relation to objective nighttime digital activity and mood variables. |
| Physical Activity and Sedentary Behavior (Self-Reported Levels) | 7 days | Participants will report their weekly physical activity, sitting time, and sedentary behaviors using standardized self-report questionnaires. These variables will be examined as predictors or correlates of screen-use profiles. |
| Well-Being (Self-Reported Score) | 1 day | Participants will complete a validated well-being questionnaire assessing positive mental health, life satisfaction, and emotional balance. Scores will be compared across screen-use profiles and related to objective digital behaviors. |
| Self-Reported Screen Use (Questionnaire Score) | 1 day | Participants will self-report their perceived daily screen time and frequency of use across app categories. Questionnaire responses will be used to compare subjective and objective measures of screen use and to explore potential biases in self-estimation. |
| Depressive Symptoms (Self-Reported Score) | 1 day | Participants will complete a validated depression questionnaire. Scores will be examined in relation to objective smartphone use indicators and will support analyses of risk factors for problematic digital use. |
| Self-Regulation Capacity (Self-Reported Score) | 1 day | Self-regulation will be assessed using a validated questionnaire measuring planning, inhibition, and control. This measure will help characterize screen-use profiles and explore cognitive factors associated with excessive use. |
| Academic Motivation (Self-Reported Score) | 1 day | Participants will complete a validated measure of academic motivation covering intrinsic, identified, introjected, and external regulation. Motivation scores will be analyzed across usage profiles to investigate potential conative differences between groups. |
| Anxiety (Self-Reported Symptom Score) | 1 day | Anxiety symptoms will be assessed using a standard validated questionnaire. This outcome will be used to examine associations with objective digital behaviors. |
Countries
France
Outcome results
None listed