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The goal of this study is to understand how children's mobile device usage (smartphones or tablets), including social media use and online games, are related to their mental wellness and mental health, as well as some aspects of their physical activity and sleep. This study is available to all children between the ages of 8 and 17 years and a parent/caregiver.
Researchers will compare participant mobile device usage with their survey responses on sleep, stress, mental health, and physical activity, as well as their parent/caregiver's survey responses.
Participants will:
The study is fully virtual. Duration is 3 months.
Once enrolled, child participants will use their mobile devices as usual, and Aura will collect data on on-line and off-line activity, app usage, social interaction, sleep, location and activity levels.
The child participant will complete surveys on a monthly basis, including:
In parallel, the parent participant will complete monthly surveys about the child, including:
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Children 8-17 years old | Over 84% of children ages 8 and up have access to a mobile device (smartphone, tablet) and are active on social media. This study focuses on children ages 8-17 to better understand social media usage and how it relates to their mental well-being. |
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| Measure | Description | Time Frame |
|---|---|---|
| Assess ongoing technology use to explore children's online behaviors and derived health behaviors. | Assess ongoing technology use via the Aura app, including social media and other online behaviors, as well as other smartphone derived health behaviors, such as sleep, location, and activity levels. | December 2025 |
| Measure | Description | Time Frame |
|---|---|---|
| Examine bivariate associations between technology use features and mental wellness and mental health outcomes | Given the wide range of variables that can be derived from the Aura app, and the number of assessments that will be collected, all analyses should be considered exploratory. As an initial exploration of this objective, we will conduct simple bivariate analyses between technology use variables and mental health outcomes. Example questions include:
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Inclusion Criteria:
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US-based, English-speaking, parents and children who use mobile devices for social media and online games.
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| Name | Affiliation | Role |
|---|---|---|
| Scott Kollins, Doctorate in Psychology | Aura | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Aura | Boston | Massachusetts | 02210 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 40424191 | Derived | Kollins SH, Flannery J, Goetz K, Akre-Bhide S. Technology Effects and Child Health: Wellness Impact and Social Effects (TECHWISE): Protocol for a Prospective, Observational, Real-World Study. JMIR Res Protoc. 2025 Jun 19;14:e69358. doi: 10.2196/69358. |
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| ID | Term |
|---|---|
| D001008 | Anxiety Disorders |
| D001068 | Feeding and Eating Disorders |
| D009043 | Motor Activity |
| ID | Term |
|---|---|
| D001523 | Mental Disorders |
| D012817 | Signs and Symptoms, Digestive |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
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| December 2025 |
| Develop preliminary predictive models that use technology use and smartphone-derived parameters to predict point-in-time mental health outcomes | Develop preliminary predictive models that use technology use and smartphone-derived parameters to predict point-in-time mental health outcomes, as well as change over time. A wide range of analytic techniques will be used to develop and evaluate predictive models to determine whether mental health related outcomes and their change over time can be reliably predicted from device usage data. Example prediction models that may be evaluated but are not limited to the following: Do patterns/changes in device-mediated social interactions predict presence/severity of loneliness? Are there specific patterns of keyboard data (specific search terms, text messaging sentiment, etc.) that predict changes in mood or anxiety outcomes? Related, do patterns of keyboard activity map onto daily ratings of mood/stress/anxiety? Can patterns of device usage predict changes in health care utilization over time? | December 2025 |
| D001519 | Behavior |