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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.
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Warning labels | Experimental | Participants view 15 messages in random order: 6 warning messages about social media developed by a team of human experts (1 each about 6 different topics), 6 warning messages about social media developed by artificial intelligence (1 each about the same 6 topics as the human-developed messages), an additional 1 warning message that mirrors the language proposed by the state of California, 1 voluntary warning message developed by human experts, and 1 control message. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Human-developed negative body image warning | Behavioral | 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. |
| Measure | Description | Time Frame |
|---|---|---|
| Perceived message effectiveness for discouraging social media use | 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. | The survey will measure perceived message effectiveness immediately after participants are exposed to the message. |
| Measure | Description | Time Frame |
|---|---|---|
| Awareness of the harms of social media use | 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. | The survey will measure awareness of the harms of social media use immediately after participants are exposed to the message. |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Anna H. Grummon, PhD | Stanford School of Medicine | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Stanford School of Medicine | Palo Alto | California | 94304 | United States |
Investigators will post de-identified individual participant data in a publicly available repository.
Investigators will post IDP upon acceptance of any manuscripts associated with the data generated in this study.
Data and code will be publicly available.
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| SAP | No | Yes | No | Statistical Analysis Plan | Aug 1, 2025 | Oct 21, 2025 |
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| Voluntary warning | Behavioral | 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. |
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| Human-developed depression and anxiety warning | Behavioral | 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. |
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| Human-developed addiction warning | Behavioral | Participants will view a message warning that social media can be addictive. The message was developed by humans without using artificial intelligence. |
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| Human-developed sleep warning | Behavioral | 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. |
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| Human-developed mental health harms to young people warning | Behavioral | 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. |
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| Human-developed warning that social media has not been proven safe | Behavioral | 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. |
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| Control message | Behavioral | Participants will view a message about encouraging seatbelt use while traveling in a vehicle. |
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| California's proposed social media warning | Behavioral | 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. |
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| Artificial-intelligence-developed depression and anxiety warning | Behavioral | Participants will view a message about the risk of social media use contributing to depression and anxiety. The message was developed using artificial intelligence. |
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| Artificial-intelligence-developed negative body image warning | Behavioral | Participants will view a message about the risk of social media use contributing to negative body. The message was developed using artificial intelligence |
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| Artificial-intelligence-developed addiction warning | Behavioral | Participants will view a message warning that social media can be addictive. The message was developed using artificial intelligence. |
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| Artificial-intelligence-developed sleep warning | Behavioral | Participants will view a message that social media use can contribute to poor sleep quality. The message was developed using artificial intelligence. |
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| Artificial-intelligence-developed mental health harms to young people warning | Behavioral | 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. |
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| Artificial-intelligence-developed warning that social media has not been proven safe | Behavioral | 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. |
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| SAP_000.pdf |