The research behind Anchored.
Anchored rests on three ideas: phones in private rooms cost sleep, willpower alone doesn’t change a habit, and screen time is a family matter, not just a kids’ one. This page collects the peer-reviewed studies and national surveys behind each, and the ones that cut the other way.
Four numbers.
How each part of Anchored lines up with the research
Strength of the evidence behind each design choice, from strong to untested
| What Anchored does | What the research says | Evidence |
|---|---|---|
| Phones locked out of bedrooms | Meta-analyses and multi-year cohorts link bedroom phones to shorter, worse sleep, even unused. | Strong |
| Limits you can’t dismiss yourself | Randomized trials: commitment limits cut use; soft nudges faded once they stopped. | Good |
| Phone-free table | A field experiment found meals less enjoyable with phones out; pediatric guidance recommends media-free meals. | Moderate |
| Rules that apply to parents too | Parents’ screen time predicts kids’; kids follow rules parents also follow. Mostly surveys. | Moderate |
| Someone else approves extra time | Commitment devices work but few opt in; group limits worked in one field study. Not tested directly. | Early |
| Everyone sees everyone’s usage | Kids reject one-way monitoring apps. Shared, two-way visibility hasn’t been studied. | Untested |
Sources for each row are in the sections below. “Untested” means no published study has looked at it yet.
A phone in the bedroom costs sleep, even when it isn’t used.
This is the best-studied part of the case. Across meta-analyses, long-term cohorts and small trials, bedtime phone use goes with shorter, worse sleep, and so does simply having the device in the room. It holds for adults as well as teens.
How a bedroom phone costs a night’s sleep
Each step is backed by the study shown. Most are associations, not proof of cause.
- A phone in the bedroomEven unused: 1.79× the odds of inadequate sleep.Carter et al. 2016, meta-analysis
- Scrolling and alerts at nightWoken by the phone monthly: 5.66× the odds of new restless sleep a year later.Foerster et al. 2019, cohort
- Shorter, worse sleepBedtime use: 2.17× the odds of inadequate sleep. Frequent night interruptions: about 48 minutes less.Carter 2016; Rod et al. 2018
- A worse next day2.72× the odds of daytime sleepiness; over four years, lost sleep carried the link to low mood.Carter 2016; Vernon et al. 2018
Odds ratios compare children with and without bedroom device access or use.
- Device in the bedroom, not used → inadequate sleep Carter 2016 1.79×
- Bedtime use → inadequate sleep Carter 2016 2.17×
- Bedtime use → poor sleep quality Carter 2016 1.46×
- Bedtime use → daytime sleepiness Carter 2016 2.72×
- Night-time phone use → insufficient sleep Mireku 2019 1.82×
- Woken by phone → new restless sleep Foerster 2019 5.66×
- Woken by phone → trouble falling asleep Foerster 2019 3.51×
-
Carter, Rees, Hale, Bhattacharjee & Paradkar (2016) JAMA Pediatrics 170(12):1202–1208 · 20 studies, n = 125,198, ages 6–19
Bedtime device use: inadequate sleep OR 2.17, poor quality OR 1.46, daytime sleepiness OR 2.72. A device in the bedroom without use: inadequate sleep OR 1.79.
-
Hale & Guan (2015) Sleep Medicine Reviews 21:50–58 · 67 studies
Screen time was adversely associated with sleep (later bedtime, shorter sleep) in 90% of studies.
-
Bartel, Gradisar & Williamson (2015) Sleep Medicine Reviews 21:72–85 · 41 studies, n = 85,561, ages 12–18
Evening light and computer use were risk factors for shorter sleep; parent-set bedtimes were protective.
-
Brautsch et al. (2023) Sleep Medicine Reviews 68:101742 · 60 studies, ages 16–25
Mobile phone, internet and social media use were associated with shorter, poorer sleep; TV and consoles were not.
-
He, Tu, Xiao, Su & Tang (2020) PLoS ONE 15(2):e0228756 · Pilot RCT, n = 38 students
No phone for 30 minutes before bed for 4 weeks shortened sleep latency and improved sleep duration, quality, mood and working memory.
-
Chang, Aeschbach, Duffy & Czeisler (2015) PNAS 112(4):1232–1237 · Crossover, n = 12 adults
Reading on an iPad before bed suppressed melatonin, delayed the body clock by over an hour and reduced next-morning alertness compared with a printed book.
-
Perrault et al. (2019) Sleep 42(9) · Adolescents 12–19, 2 weeks, actigraphy
Stopping screens after 9 pm on school nights brought sleep earlier, lengthened it and improved daytime vigilance.
-
Bowler & Bourke (2019) British Journal of Psychology 110(3) · Lab experiment
Blue-light filtering alone didn’t improve sleep after Facebook use; social content itself was arousing.
-
Vernon, Modecki & Barber (2018) Child Development 89(1):66–77 · 4 years, n = 1,101, ages 13–16
Night-time phone use rose with poorer sleep, and sleep changes carried its link to later depressed mood, externalizing behavior and lower self-esteem.
-
Foerster, Henneke, Chetty-Mhlanga & Röösli (2019) IJERPH 16(3):518 · 1-year cohort, n = 843, grades 7–9
Being woken by one’s phone at least monthly predicted new restless sleep (OR 5.66) and trouble falling asleep (OR 3.51).
-
Nagata et al. (2024) Journal of Adolescent Health 75(4) · ABCD Study cohort, early adolescents
Leaving the ringer on overnight, and social media, calls or music at bedtime, predicted worse sleep a year later; a bedroom device predicted shorter sleep.
-
Mireku et al. (2019) Environment International 124:66–78 · n = 6,616, ages 11–12
71.5% used a device in the hour before sleep. Night-time phone use was linked to insufficient weekday sleep (OR 1.82), more so in a dark room.
-
Hysing et al. (2015) BMJ Open 5(1):e006748 · ~9,800 Norwegians aged 16–19
Nearly all used devices in the hour before bed; phone use before bed raised the odds of a 2+ hour sleep deficit by about 35%.
-
Rod, Dissing, Clark, Gerds & Lund (2018) PLoS ONE 13(10):e0204811 · Objective phone logs, n = 815 young adults
12% had phone activity 3–5 hours after bedtime; frequent interrupters slept about 48 minutes less.
-
Garrett et al. (2023) J. Clinical Child & Adolescent Psychology · n = 59 teens, Fitbit + iOS Screen Time
Hours with more screen time or pickups had longer night-time wake events; notifications alone did not.
-
Exelmans & Van den Bulck (2016) Social Science & Medicine 148:93–101 · n = 844 adults aged 18–94
60% took their phone to bed; using it after lights out predicted worse sleep quality, more insomnia and fatigue.
-
Woods & Scott (2016) Journal of Adolescence 51:41–49 · n = 467 teens
Night-time social media use predicted poorer sleep quality after controlling for anxiety, depression and self-esteem.
-
Kroese, De Ridder, Evers & Adriaanse (2014) Frontiers in Psychology 5:611 · n = 177
Bedtime procrastination is common and tied to low self-regulation and insufficient sleep.
-
Correa-Iriarte, Hidalgo-Fuentes & Martí-Vilar (2023) Behavioral Sciences 13(10):839 · n = 313 adults
Problematic smartphone use hurt sleep quality through bedtime procrastination.
-
Gradisar et al. (2013) J. Clinical Sleep Medicine 9(12) · NSF Sleep in America poll, n = 1,508, ages 13–64
95% used electronics in the hour before bed a few nights a week or more; interactive devices were most linked to sleep complaints.
-
Common Sense Media (2019) The New Normal: Parents, Teens, Screens, and Sleep · 1,000 parent–teen pairs
29% of teens sleep with a device in bed; 36% of teens and 26% of parents wake at night to check their phone; 70% of teens and 61% of parents check it within 30 minutes of bed.
-
American Academy of Sleep Medicine (2022) Sleep Prioritization Survey · n = 2,010 adults
80% of adults and 93% of Gen Z stayed up past bedtime because of social media.
-
American Academy of Sleep Medicine (2023) Phones in the bedroom survey · US adults
87% regularly sleep with their phone in the bedroom.
aasm.org/wp-content/uploads/2023/11/sleep-prioritization-survey-2023-phones-in-the-bedroom.pdf
Willpower loses to habit and place.
Phone checking is a habit triggered by context, and resisting in the moment often fails. Self-control research consistently finds that changing the situation works better than relying on resolve. That is the idea behind rules attached to rooms.
Of every 100 US adults who tried to cut back on their phone last year
How successful they say they were
- 25 very or extremely successful
- 52 somewhat successful
- 23 not successful
Pew Research Center, Sep 2026 (9,750 US adults; 45% tried to cut back in the past year).
Where in the moment a strategy works
Self-control research ranks strategies by when they act. The earlier, the less willpower they need.
Process model of self-control from Duckworth, Gendler & Gross 2016, Perspectives on Psychological Science.
-
Duckworth, Gendler & Gross (2016) Perspectives on Psychological Science 11(1):35–55 · Theory and review
Strategies that choose or change the situation beat resisting temptation in the moment, and are underused.
-
Hofmann, Baumeister, Förster & Vohs (2012) JPSP 102(6):1318–1335 · n = 205 adults, 7,827 desires
About half of everyday desires conflicted with goals; resistance often failed, and the situation mattered more than personality.
-
Wood & Neal (2007) Psychological Review 114(4):843–863 · Theory and review
Habits are triggered by context cues and persist even when goals change.
-
Oulasvirta, Rattenbury, Ma & Raita (2012) Personal and Ubiquitous Computing 16(1):105–114 · Three studies, logs + field experiment
Brief, repetitive checking habits form and drive up overall smartphone use.
-
Lally, van Jaarsveld, Potts & Wardle (2010) European Journal of Social Psychology 40(6):998–1009 · n = 96, 84 days
Habits took a median of 66 days to become automatic (range 18–254).
-
Verplanken & Roy (2016) Journal of Environmental Psychology 45:127–134 · n ≈ 800
Behavior-change interventions worked better for people who had recently moved home.
-
Pew Research Center (2026) About half of Americans say they spend too much time on their smartphone · n = 9,750 adults
53% say they spend too much time on their phone; 45% tried to cut back in the past year; 25% of those were very or extremely successful.
Limits people can’t switch off reduce use.
In randomized trials, limits that couldn’t be immediately overridden and enforced breaks reduced use. Some also improved wellbeing modestly. Soft nudges faded once they stopped, and very strict lockouts frustrated people, which is why Anchored pairs hard blocks with a way to ask someone else for more time.
From gentle nudges to hard blocks: what each did in studies
Ordered from softest to strictest
- A reflective messageShowing a “do you really want to?” message on its own. (Grüning et al. 2023)No measurable effect
- A buzz past your limitVibration once over a daily limit. Use returned to normal when it stopped. (Okeke et al. 2018)−20%, then faded
- Friction before openingA delay plus a chance to back out before the app opens. (Grüning et al. 2023)−57% app opens
- Limits you can’t overrideLimits set in advance that can’t be switched off in the moment, in a 2,000-person RCT. (Allcott et al. 2022)−17% app use
- Full lockoutCut use the most, but frustrated people the most. (Kim et al. 2019)Most effective, least liked
- AnchoredA hard block only in set rooms, with extra time granted by someone else instead of yourself. Not yet tested directly.Field test in 2027
Outcomes are measured differently in each study (minutes of use, app opens, time on one app), so compare direction, not size.
-
Allcott, Gentzkow & Song (2022) American Economic Review 112(7):2424–2463 · RCT, ~2,000 users
Limits that couldn’t be immediately overridden cut targeted app use by 22 min/day (17%); people underestimated their own self-control problems.
-
Allcott, Braghieri, Eichmeyer & Gentzkow (2020) American Economic Review 110(3):629–676 · RCT, n = 2,844, 4 weeks
Verified Facebook deactivation produced small well-being gains, more offline time with family and friends, and lower use afterwards.
-
Hunt, Marx, Lipson & Young (2018) J. Social and Clinical Psychology 37(10):751–768 · RCT, n = 143, 3 weeks
Limiting social media to ~30 min/day reduced loneliness and depression compared with controls.
-
Brailovskaia et al. (2022) J. Experimental Psychology: Applied · RCT, n = 619, 4-month follow-up
Using the phone one hour less per day improved life satisfaction and lowered depression and anxiety; the group used ~45 min/day less at 4 months.
-
Thai et al. (2023) Psychology of Popular Media · RCT, n = 220, ages 17–25
Capping social media at 1 hour/day for 3 weeks improved appearance and weight esteem.
-
Grüning, Riedel & Lorenz-Spreen (2023) PNAS 120(8) · n = 280 over 6 weeks + online experiment n = 500
Adding friction cut attempts to open target apps by 57%; the reflective message alone had no effect. One author is linked to the app studied.
-
Okeke, Sobolev, Dell & Estrin (2018) MobileHCI ’18 · n = 50
A vibration nudge past a limit cut Facebook time by 20%+, but use returned to baseline when it stopped.
-
Kim, Jung, Ko & Lee (2019) Proc. ACM IMWUT 3(1):16 (GoalKeeper) · Field study of lockout strengths
Strong lockouts cut use most but caused frustration; moderate lockouts balanced the two.
-
Ko, Choi, Yatani & Lee (2016) CHI ’16 (Lock n’ LoL), Best Paper · Field trials n = 20 and 28; campus campaign 1,000+
Groups limited phone use together with shared awareness; an early version required permission to use the phone.
-
Burnell et al. (2025) SSM – Mental Health · 32 RCTs
Restricting social media improved well-being, g = 0.17 [0.08, 0.27]; limiting worked about as well as quitting.
-
Monge Roffarello & De Russis (2023) ACM TOCHI 30(4):53 · Systematic review + meta-analysis
Digital self-control tools cut device time in the short term but don’t build lasting habits.
-
Lyngs et al. (2019) CHI ’19 · 367 apps and extensions
Maps digital self-control tools onto dual-systems self-regulation and finds underused mechanisms.
-
Giné, Karlan & Zinman (2010) AEJ: Applied 2(4):213–235 · RCT, smokers in the Philippines
Only 11% took up a commitment contract; those offered it were 3 points more likely to quit at 6 and 12 months.
-
Rogers, Milkman & Volpp (2014) JAMA 311(20):2065–2066 · Viewpoint
Commitment devices are cheap and effective but uptake is often low.
-
Gallup (2023) Teens spend average of 4.8 hours on social media per day · n ≈ 1,591 teens
Teens average 4.8 hours/day on social media; those whose parents restrict use spend about 1.7 hours less.
news.gallup.com/poll/512576/teens-spend-average-hours-social-media-day.aspx
Parents’ phones are part of the picture.
Children’s screen time tracks their parents’, and parents’ distraction by their phone is linked to children’s behavior. Pediatric and federal guidance already recommends family media plans, phone-free meals and no devices in bedrooms at night, for everyone.
Overuse runs both ways
Share of US teens and parents saying each about themselves
TeensParents
Row 1: Pew Research Center 2024 (1,453 parent–teen pairs). Rows 2–3: Common Sense Media 2019 (1,000 parent–teen pairs), figures from the published summary.
Parents notice it more in their teens
Share of parents of teens who say each is at least sometimes distracted by a phone during conversations
Pew Research Center 2024.
-
McDaniel & Radesky (2018) Child Development 89(1):100–109 · n = 170 two-parent families
Parents’ problematic phone use predicted more interruptions of parent–child time, which predicted more child behavior problems.
-
Radesky et al. (2014) Pediatrics 133(4):e843–e849 · 55 caregivers observed
40 of 55 caregivers used a device during the meal; highly absorbed ones responded more harshly to children.
-
Lauricella, Wartella & Rideout (2015) J. Applied Developmental Psychology 36:11–17 · ~2,300 parents of children 0–8
Parents’ own screen time was the strongest predictor of children’s screen time.
-
Leonova et al. (2025) European Psychiatry · 26 studies, 22,833 children
Parental phubbing was associated with children’s affective symptoms (r = 0.32) and lower self-esteem (r = −0.23).
-
Pew Research Center (2024) How Teens and Parents Approach Screen Time · 1,453 parent–teen pairs
47% of parents say they spend too much time on their phone (38% of teens say so); about half of teens say a parent is at least sometimes distracted when they talk.
www.pewresearch.org/internet/2024/03/11/how-teens-and-parents-approach-screen-time
-
Pew Research Center (2020) Parenting Children in the Age of Screens · US parents
68% of parents say they are at least sometimes distracted by their phone when with their kids.
-
AAP Council on Communications and Media (2016) Pediatrics 138(5):e20162591 (Media and Young Minds) · Policy statement
Recommends a family media plan, media-free mealtimes and no devices in bedrooms at night; names parents’ own use.
-
US Surgeon General (2023) Social Media and Youth Mental Health advisory · Advisory
Recommends tech-free zones and family media plans; cites a cohort where 3+ hours/day doubled the risk of depression and anxiety symptoms.
www.hhs.gov/surgeongeneral/reports-and-publications/youth-mental-health/social-media/index.html
-
American Psychological Association (2023) Health Advisory on Social Media Use in Adolescence · Advisory
Adults’ own use shapes teens’; limit use that displaces sleep. Also says social media is neither inherently harmful nor beneficial.
Shared rules work better than one-way control.
Kids follow rules they helped make and see their parents follow. They reject apps that only watch them. The hard part, according to the families studied, is enforcing rules tied to a place like the dinner table. That is the gap Anchored is designed to close.
Parental-control apps are built for watching, not shared rules
Features of 75 safety apps, and how kids rate the apps
Rows 1–2: Wisniewski et al. 2017 (CSCW). Row 3: Ghosh et al. 2018 (CHI), 736 reviews of 37 apps.
-
Hiniker, Schoenebeck & Kientz (2016) CSCW ’16 (Not at the dinner table) · 249 parent–child pairs, children 10–17
Children followed rules better when they helped make them and parents followed them too. Context rules like “not at dinner” were harder to enforce than outright bans.
-
Wisniewski et al. (2017) CSCW ’17 · 75 Android safety apps
About 89% of features supported parental control and 11% supported teen self-regulation.
-
Ghosh et al. (2018) CHI ’18 (Safety vs. Surveillance) · 736 reviews of 37 apps
79% of children’s reviews of parental-control apps gave 2 stars or fewer; kids saw them as invasive.
-
Ghosh et al. (2018) CHI ’18 (A matter of control or safety?) · Parent–teen pairs
Monitoring apps were used most by authoritarian parents and were linked to more teen online risk, not less.
-
Chen & Shi (2019) Journalism & Mass Communication Quarterly 96(1):173–193 · 52 studies, n = 74,159
Restrictive mediation worked better for reducing time; active mediation and co-use worked better for reducing risks.
-
Collier, Coyne et al. (2016) Developmental Psychology 52(5):798–812 · Meta-analysis
Parental mediation effects were small (restrictive r = −.06).
Phones at the table and between partners.
Phones at meals reduce how much people enjoy each other’s company, and being snubbed for a partner’s phone is linked to more conflict and lower relationship satisfaction.
Phones between partners
Share of partnered US adults
Rows 1–2: Pew Research Center 2020. Rows 3–4: Roberts & David 2016 (453 US adults).
Caregivers on a device during a family meal
55 caregivers observed eating with children at fast-food restaurants
40 of 55 used a phone or other device during the meal. The most absorbed responded more harshly to their children.
Radesky et al. 2014, Pediatrics (observational).
-
Roberts & David (2016) Computers in Human Behavior 54:134–141 · n = 453 US adults
46% said their partner had snubbed them for a phone; 23% said it caused conflict, which lowered relationship and life satisfaction.
-
McDaniel & Coyne (2016) Psychology of Popular Media Culture 5(1):85–98 · n = 143 women
62% said a partner checked their phone during couple time at least daily; more interference meant more conflict and lower satisfaction.
-
Ni, Ahrari, Zaremohzzabieh, Zarean & Roslan (2025) Frontiers in Psychology · 52 studies, n = 19,698
Partner phubbing was linked to lower satisfaction and intimacy and more conflict (r ≈ .12–.31).
-
Wang, Xie, Wang, Wang & Lei (2017) Personality and Individual Differences 110:12–17 · Married adults, China
Partner phubbing was linked to depression through lower relationship satisfaction.
-
Dwyer, Kushlev & Dunn (2018) J. Experimental Social Psychology 78:233–239 · Restaurant experiment, n = 304
People enjoyed meals with friends and family less, and felt more distracted, when phones were out.
-
Przybylski & Weinstein (2013) J. Social and Personal Relationships 30(3):237–246 · Two lab experiments
A visible phone lowered closeness and conversation quality. A 2021 replication found the effect harder to reproduce.
-
Pew Research Center (2020) Dating and Relationships in the Digital Age · US adults, fielded Oct 2019
51% of partnered adults say their partner is at least sometimes distracted by their phone when they try to talk; 40% are bothered by it.
www.pewresearch.org/internet/2020/05/08/dating-and-relationships-in-the-digital-age
People are asking for help.
Teens, young adults and parents all say they use their phones more than they want to, and existing parental controls are underused.
Teens are turning on social media
Share of US teens, 2022 vs 2024
Say social media harms people their ageSay they spend too much time on it
Pew Research Center, “Teens, Social Media and Mental Health,” April 2025. Axis starts at 25%.
Young adults want fewer apps, not no phone
Share of Gen Z adults (18–27) who wish each had never been invented
The Harris Poll with Haidt & Rausch, Aug 2024 (1,006 adults aged 18–27), figures from the published release. Anchored blocks apps, not the phone.
-
Pew Research Center (2025) Teens, Social Media and Mental Health · Teens and parents, fielded fall 2024
45% of teens say they spend too much time on social media (36% in 2022); 44% have cut back on their phone.
-
Harris Poll with Haidt & Rausch (2024) Gen Z survey · n = 1,006, ages 18–27
47% wish TikTok had never been invented and 50% say so of X, but only 21% say so of the smartphone.
-
Common Sense Media & University of Michigan (2023) Constant Companion · ~200 young people aged 11–17, phone tracking
Median 237 notifications a day; over half used their phone between midnight and 5 am on school nights.
-
Common Sense Media (2022) Common Sense Census: Media Use by Tweens and Teens, 2021 · National survey
Teens averaged 8h39m a day of entertainment screen use, up 17% since 2019.
-
FOSI / Ipsos (2025) Parental controls study · 1,000 parents of 10–17-year-olds
Only 47% of parents use parental controls on smartphones.
fosi.org/parental-controls-for-online-safety-are-underutilized-new-study-finds
-
Sohn, Rees, Wildridge, Kalk & Carter (2019) BMC Psychiatry 19:356 · 41 studies, n = 41,871
About 23% of young people show problematic smartphone use, associated with depression (OR 3.17), anxiety (OR 3.05) and poor sleep.
What the research doesn’t show.
The case for Anchored is about sleep, focus and rules that hold. It isn’t a claim that phones cause depression or that cutting back cures it. Most studies above are correlational. Effects on wellbeing are small and disputed. No study has yet tested blocking apps by room, or adults approving each other’s screen time.
-
Orben & Przybylski (2019) Nature Human Behaviour 3:173–182 · n > 300,000
Digital technology use explains at most 0.4% of the variation in adolescent well-being.
-
Przybylski (2019) Journal of Pediatrics 205:218–223 · ~50,000 children, preregistered
Screen time explained under 1.9% of the variance in sleep, roughly 3–8 minutes less sleep per hour of screen time.
-
Orben & Przybylski (2020) PeerJ 8:e8427 · n = 11,884, time-use diaries
Little evidence that use in the 30 minutes before bed was linked to sleep.
-
Duraccio et al. (2021) Sleep Health · Small RCT
No sleep difference between phone with Night Shift, without it, or no phone.
-
Lemahieu et al. (2025) Scientific Reports 15:7581 · 10 studies, n = 4,674
Social media abstinence had no significant effect on affect or life satisfaction.
-
Ferguson (2024) Psychology of Popular Media · 27 experiments, preregistered
No average effect of social media experiments on mental health (coding disputed by Haidt & Rausch).
-
Radtke, Apel, Schenkel, Keller & von Lindern (2022) Mobile Media & Communication 10(2):190–215 · 21 studies
Digital detox effects on well-being, relationships and self-control were mixed.
-
Ward, Duke, Gneezy & Bos (2017) and replications J. Assoc. for Consumer Research 2(2); Ruiz Pardo & Minda 2022; Böttger et al. 2023 · ~800; replication; meta-analysis of 22 studies
A phone in the room seemed to reduce cognitive capacity, but a direct replication failed and a meta-analysis finds a small, inconsistent effect.
-
Odgers (2024) Nature 628:29–30 · Book review of The Anxious Generation
Argues the research shows “no, small and mixed associations,” not an epidemic caused by phones.
What Anchored will test itself.
- Does room-level blocking hold up in real homes? The detection study measures how often the phone picks the right room, then adds sleep and usage outcomes for families who use it.
- Does someone else approving extra time help? No published study has tested it. Approval requests, grants and uninstalls will show whether the circle makes hard blocks easier to live with.
- Do parents change too? The family dashboard records every member’s use, so a pilot can measure parents’ screen time as well as kids’.
How this list was built: sources were found through searches of journals, PubMed records and research centers in November 2026, and each was confirmed through its abstract or publisher record. Entries marked “From summary” take their figures from coverage of the study rather than the study itself. Follow the DOI links for the original papers.