Screen Time Exposure
Conditions
Keywords
teenagers, young adults, warning labels, social media
Brief summary
The primary objective of this study is to evaluate whether social media warnings are perceived as more effective than control labels among teens and young adults, and to identify the most promising topics for social media warnings for these age groups. A secondary objective is to compare perceived message effectiveness of warnings refined using artificial intelligence (AI) vs. those not refined using AI.
Detailed description
Participants will complete a within-subjects online randomized experiment in which they will view and rate messages on the risk of social media use. Participants will view messages about 9 topics: 8 warning topics and 1 control topic. The 8 warning topics include 7 potential mandatory warnings (depression and anxiety, body image, addiction, sleep, mental health harms to children, not been proven safe, and California's proposed warning) and 1 voluntary warning (similar to a message used on TikTok to encourage users to take breaks). For each topic, participants will view 1-2 messages and respond to survey items about that message. All messages will be shown in random order.
Interventions
BEHAVIORALHuman-developed negative body image warning
Participants will view a message about the risk of social media use contributing to negative body. The message was developed by humans without using artificial intelligence.
BEHAVIORALVoluntary warning
Participants will view a message suggesting user take a break from scrolling on social media. The message was developed by humans without using artificial intelligence.
BEHAVIORALHuman-developed depression and anxiety warning
Participants will view a message about the risk of social media use contributing to depression and anxiety. The message was developed by humans without using artificial intelligence.
BEHAVIORALHuman-developed addiction warning
Participants will view a message warning that social media can be addictive. The message was developed by humans without using artificial intelligence.
BEHAVIORALHuman-developed sleep warning
Participants will view a message that social media use can contribute to poor sleep quality. The message was developed by humans without using artificial intelligence.
BEHAVIORALHuman-developed mental health harms to young people warning
Participants will view a message about the risk of social media use contributing to mental health harms for some young people. The message was developed by humans without using artificial intelligence.
BEHAVIORALHuman-developed warning that social media has not been proven safe
Participants will view a message warning that the use of social media has not been proven safe for young people. The message was developed by humans without using artificial intelligence.
BEHAVIORALControl message
Participants will view a message about encouraging seatbelt use while traveling in a vehicle.
BEHAVIORALCalifornia's proposed social media warning
Participants will view a message warning about the harms of social media use that mirrors the language the state of California has proposed for mandatory social media warnings.
BEHAVIORALArtificial-intelligence-developed depression and anxiety warning
Participants will view a message about the risk of social media use contributing to depression and anxiety. The message was developed using artificial intelligence.
BEHAVIORALArtificial-intelligence-developed negative body image warning
Participants will view a message about the risk of social media use contributing to negative body. The message was developed using artificial intelligence
BEHAVIORALArtificial-intelligence-developed addiction warning
Participants will view a message warning that social media can be addictive. The message was developed using artificial intelligence.
BEHAVIORALArtificial-intelligence-developed sleep warning
Participants will view a message that social media use can contribute to poor sleep quality. The message was developed using artificial intelligence.
BEHAVIORALArtificial-intelligence-developed mental health harms to young people warning
Participants will view a message about the risk of social media use contributing to mental health harms for some young people. The message was developed using artificial intelligence.
BEHAVIORALArtificial-intelligence-developed warning that social media has not been proven safe
Participants will view a message warning that the use of social media has not been proven safe for young people. The message was developed using artificial intelligence.
Sponsors
Stanford University
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
PREVENTION
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
13 Years to 29 Years
Healthy volunteers
Yes
Inclusion criteria
* Age between 13-29 years * Reside in the United States * Able to complete a survey in English * Access to the internet
Exclusion criteria
* Younger than 13 or older than 29 years * Reside outside of the United States * Unable to complete a survey in English * Lacks access to the internet
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Perceived message effectiveness for discouraging social media use | The survey will measure perceived message effectiveness immediately after participants are exposed to the message. | The study will assess perceived message effectiveness for discouraging social media use with 1 item: "How much does this message discourage you from wanting to use social media?" Response options will range from "Not at all" (coded as 1) to "A great deal" (coded as 5). Higher scores indicate higher perceived message effectiveness. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Awareness of the harms of social media use | The survey will measure awareness of the harms of social media use immediately after participants are exposed to the message. | The study will assess awareness of the harms of social media use with 1 item: "How much does this message increase your awareness of the harms of using social media?" Response options will range from "Not at all" (coded as 1) to "A great deal" (coded as 5). Higher scores indicate greater awareness. |
Countries
United States
Contacts
PRINCIPAL_INVESTIGATORAnna H. Grummon, PhD
Stanford School of Medicine
Outcome results
None listed