What doomscrolling is
Doomscrolling started as slang for continuing to scroll through bad news on social-media feeds, and it has since become something researchers measure. Sharma, Lee & Johnson (2022) developed and validated a scale for it: 15 items, with a 4-item short form. Two details in their data matter. Doomscrolling turned out to be distinct from general social-media use, so it isn't simply "using your phone a lot". And it went with lower well-being.
Satici et al. (2023) tested a version of the scale in three Turkish samples (378, 419 and 460 people). It held together as a single factor, and higher scores went with fear of missing out, problematic social-media use, lower life satisfaction and lower well-being, with psychological distress linking them.
So the word now points at something specific: a pattern of continuing to scroll past the point where it feels good, not the total hours you spend online.
What the research says about it
Most of what's known is correlational. That's worth stating up front, because headlines often turn "goes with" into "causes".
Price et al. (2022) tracked people with daily diaries during the COVID-19 pandemic. On days with more social and traditional media consumption, people reported more symptoms of post-traumatic stress and depression that same day. That fits the idea that heavy news feeds take a toll, and it also fits the reverse: people who feel worse may scroll more. A daily diary can't tell those apart.
The intervention studies are more useful, because they change something and watch what happens.
Friction is the clearest result. The Danish Competition and Consumer Authority (2025) ran a six-week field experiment with 269 teenagers aged 13 to 17, who averaged 3 hours 19 minutes a day on social media at the start. Small frictions cut daily social-media activity by 31 to 36% across the different versions tested. A six-second wait with a calming animation before an app opened cut use by more than a third on its own. Teens' satisfaction with social media didn't drop. The limits: it's a government report, not peer-reviewed, and it reports no follow-up after the interventions stopped, so nobody knows yet whether the change outlasts the friction.
Notification timing matters too. In a two-week randomized trial with 237 people, Fitz et al. (2019) found that delivering notifications in three batches a day improved attention, mood, productivity and sense of control, and lowered stress. Hourly batches did little. Switching notifications off completely raised anxiety and fear of missing out. The pull to check, in other words, is shaped by when rewards arrive, and the best result came from making that timing predictable rather than removing it.
Breaks are the weakest lever over time. In a pilot trial, Sullivan, Cairney & Henderson (2026) randomized 82 UK adolescents to a 21-day smartphone and social-media detox or to a control group. At 21 days the detox groups showed tentative improvements in sleep, stress and mood, but those were not maintained at the two-month follow-up. Pieh et al. (2025) found something similar in 111 students who capped screen time at two hours a day for three weeks: small to medium gains that were partly fading by the six-week follow-up. A short break helps while it lasts. The habit is still there when it ends.
Read together, the evidence points one way. Changing the structure of the feed, through friction and predictable timing, works better than relying on willpower or a heroic break.
Why feeds are hard to stop
Feeds pay out on an unpredictable schedule, one of the schedules that builds the most persistent checking in the reinforcement literature (how variable-ratio reinforcement works). The reward arrives for almost no effort, and effortless reward behaves differently from rewards you work for. Repetition also changes the experience itself: the opponent process explains why each session hits a little less and the after-effect grows, and wanting can grow while liking doesn't, which is why you keep reaching for something you no longer enjoy. None of this is a willpower problem. It's what the schedule is built to do.
A reading map
Each note on this site answers one question. Start with the one closest to yours.
- "How do I actually stop?" Start with the practical guide to stopping doomscrolling: move the phone, add friction where the pull is strongest, and fill the slot with something that pays off.
- "Why is it so hard to put down?" Variable-ratio reinforcement covers the schedule, and wanting vs liking explains craving without enjoyment.
- "Why does everything feel flat afterwards?" Everything feels boring after scrolling is about the hour after, and the opponent process is about why it stops hitting.
- "Should I just quit for 30 days?" Why 30-day challenges fail looks at what happens when the break ends, and is dopamine fasting real looks at the term itself.
- "Has it changed my baseline?" What a dopamine baseline is, and what a self-check can and can't tell you.
- "Nothing feels enjoyable, even away from the phone." That's a broader question than doomscrolling. The feeling flat guide and how to enjoy things again are the right places, and if it has lasted weeks, a doctor is the right next step.
If you'd rather start from your own data, the 60-second audit names the single change most likely to move your day, and the science page shows how Myo's model weighs each input.
Sources
- Danish Competition and Consumer Authority (KFST). (2025). Disrupting social media habits: A field experiment with young Danish consumers. https://en.kfst.dk/analyses/2025/20250619-disrupting-social-media-habits-a-field-experiment-with-young-danish-consumers
- Fitz, N., Kushlev, K., Jagannathan, R., Lewis, T., Paliwal, D., & Ariely, D. (2019). Batching smartphone notifications can improve well-being. Computers in Human Behavior, 101, 84 to 94. https://doi.org/10.1016/j.chb.2019.07.016
- Pieh, C., Humer, E., Hoenigl, A., Schwab, J., Mayerhofer, D., Dale, R., & Haider, K. (2025). Smartphone screen time reduction improves mental health: a randomized controlled trial. BMC Medicine, 23, 107. https://doi.org/10.1186/s12916-025-03944-z
- Price, M., Legrand, A. C., Brier, Z. M. F., van Stolk-Cooke, K., Peck, K., Dodds, P. S., Danforth, C. M., & Adams, Z. W. (2022). Doomscrolling during COVID-19. Psychological Trauma: Theory, Research, Practice, and Policy. https://doi.org/10.1037/tra0001202
- Satici, S. A., Gocet Tekin, E., Deniz, M. E., & Satici, B. (2023). Doomscrolling Scale: Its association with personality traits, psychological distress, social media use, and wellbeing. Applied Research in Quality of Life, 18(2), 833 to 847. https://doi.org/10.1007/s11482-022-10110-7
- Sharma, B., Lee, S. S., & Johnson, B. K. (2022). The dark at the end of the tunnel: Doomscrolling on social media newsfeeds. Technology, Mind, and Behavior, 3(1). https://doi.org/10.1037/tmb0000059
- Sullivan, Cairney & Henderson (2026). A pilot randomised trial on smartphone and social media abstinence: effects on sleep quality and psychological wellbeing in adolescents. Child and Adolescent Mental Health. https://doi.org/10.1111/camh.70118