Almost everyone writing about this has something to sell — an app, a programme, a book, a treatment centre. So the research gets reported selectively: the encouraging trials get quoted, the null results get left out, and the effect sizes disappear entirely.
I have nothing to sell you. The course on this site is free and always will be. So here is all of it, including the studies that make my own course look less impressive.
The short answer
Yes, with two important qualifications.
Several randomised trials have found short-term improvements in mental health, wellbeing or attention after people reduced selected screen use. Other studies found small effects or no clear improvement, especially when they examined broad population averages. The evidence supports testing a defined reduction; it does not support promising that every digital detox will work.
One 2025 trial reported a depression-symptom effect size larger than the meta-analytic average the authors cited for antidepressants. The authors explicitly warned that their participants and intervention were very different from clinical treatment studies. It is an effect-size comparison, not evidence that blocking mobile internet should replace medication or therapy.
The first qualification is that adherence was difficult. In that study, only about a quarter of participants kept the block running for ten days out of fourteen — even though they had volunteered for the trial. That is a strong reason to plan the environment and involve another person instead of relying on a promise made in frustration.
The second is that almost nobody has measured what happens afterwards. The trials run for two or three weeks. Whether the benefit survives six months depends entirely on what filled the space, and that is the part the research has not yet caught up with.
The studies, in plain English
Blocking the mobile internet for two weeks
- What they did
- 467 people installed a blocker that cut off all mobile internet on their phone for two weeks. Calls and texts still worked; laptops still worked. Attention was measured with a lab task, not self-report.
- What they found
- Screen time fell from 314 minutes a day to 161. The depression-symptom effect size was 0.56. The authors noted that this was larger than the meta-analytic average they cited for antidepressants, while warning that the samples and interventions were not directly comparable. Sustained attention and wellbeing also improved.
- What it does not show
- Only about a quarter of participants kept the block running for ten or more of the fourteen days. This was not a direct comparison with clinical treatment and does not show that blocking mobile internet can replace medication or therapy.
Castelo, Kushlev, Ward, Esterman & Reiner — PNAS Nexus 4(2), pgaf017 (2025)
Cutting screen time to two hours a day
- What they did
- 111 young adults were randomly assigned either to limit their phone to two hours a day for three weeks, or to carry on as normal. Baseline use was 276 minutes a day.
- What they found
- Depressive symptoms fell 27%. Stress fell 16%. Insomnia severity fell 18%. Wellbeing rose 14%. All statistically significant.
- What it does not show
- Small sample, young participants, three weeks. It shows the direction clearly; it does not tell you how long the effect lasts.
Pieh, Humer, Hoenigl, Schwab, Mayerhofer, Dale & Haider — BMC Medicine 23:107 (2025)
Taking the screens off a whole family for two weeks
- What they did
- 89 Danish families — 181 children — were randomly assigned to hand over smartphones and tablets and cut leisure screen use to under three hours a week per person, for two weeks. Basic phones were supplied.
- What they found
- Children's behavioural difficulties fell by a moderate amount (Cohen's d = 0.53), internalising symptoms fell, and prosocial behaviour rose.
- What it does not show
- Two weeks, small sample, no long-term follow-up, and a far more drastic intervention than most families would sustain. It is the best experimental signal we have — and it is still a small one.
Schmidt-Persson et al. — JAMA Network Open 7(7):e2419881 (2024)
A breath before the app opens
- What they did
- Researchers tested a short, deliberate delay — a breathing prompt — inserted before a chosen app would open, in a live field study rather than a lab.
- What they found
- The friction meaningfully reduced how often people opened the app, and the effect persisted rather than washing out after a few days.
- What it does not show
- It reduces use of the specific apps you choose. It does not treat the underlying reason you reach for them.
Social media and depression in early adolescence
- What they did
- 11,876 American children were followed from ages 9–10 through to 12–13, with four annual measurements, comparing each child against their own earlier self rather than against other children.
- What they found
- A year-on-year increase in a child's own social media use predicted more depressive symptoms the following year. The reverse was not true: depressive symptoms did not predict later increases in use. Average daily use rose from 7 minutes to 73 minutes over the study.
- What it does not show
- Observational, so unmeasured factors could still explain it — the authors themselves call social media a “potential contributing factor”, not a proven cause.
The study that argues the other way
- What they did
- A specification-curve analysis ran essentially every reasonable statistical model across three large datasets, instead of picking the one that gave the desired answer.
- What they found
- Technology use explained at most 0.4% of the variation in adolescent wellbeing — about the same as regularly eating potatoes, and less than wearing glasses.
- What it does not show
- This measures the average across a whole population. A small average effect can still hide a large effect on a smaller group of heavy or vulnerable users — which is what the more recent within-person work suggests.
What happens when schools ban phones
- What they did
- An English study compared 1,227 pupils across 30 secondary schools with restrictive and permissive phone policies. Separately, an American study used Florida's statewide ban as a natural experiment.
- What they found
- The English study found no difference in wellbeing, and no difference in overall phone use outside school hours — the phones simply moved. The Florida study found small but real gains in test scores and a significant fall in unexplained absence.
- What it does not show
- The Florida study also found suspensions rose about 12% in the first year, with a larger rise for Black students, before settling by year two. It is a working paper and has not yet been peer reviewed.
Goodyear et al. — Lancet Regional Health Europe 51 (2025); Figlio & Özek — NBER 34388 (2025)
Do parental controls protect children?
- What they did
- 515 British adolescents and their caregivers were surveyed about internet filtering at home and about seven categories of unpleasant online experience.
- What they found
- No statistically significant protective effect on any of the seven. Follow-up work estimated that between 17 and 77 households would need to use filters to prevent one young person encountering sexual content.
- What it does not show
- Filtering is not useless — it buys time and signals a family value. But it is not the safety net most parents believe they have bought.
What families can actually do that works
- What they did
- A meta-analysis pooled 88 studies published between 2008 and 2024 on digital parenting and children's wellbeing.
- What they found
- Co-use — being in the room, watching together, talking about what you are both seeing — showed the strongest protective effect against harm, ahead of both encouragement and restriction.
- What it does not show
- The effects are modest and the underlying studies are correlational. The authors conclude there is no one-size-fits-all approach.
Questions the research does not answer
Four questions people ask me constantly, answered without pretending to more certainty than exists.
Is phone addiction a real diagnosis?
Not formally. Gaming Disorder is in the World Health Organization's ICD-11. “Smartphone addiction” and “social media addiction” are in neither ICD-11 nor the DSM-5-TR. This is why prevalence estimates range from 23% to 37% — different researchers use different questionnaires with different cut-off points. That does not mean the suffering is imaginary. It means the measurement is not yet standardised, and anyone quoting a single confident number is overreaching.
Are phones causing the teen mental health crisis?
This is genuinely contested by serious people. Jonathan Haidt argues yes, forcefully, in The Anxious Generation. Candice Odgers, Andrew Przybylski and Amy Orben argue the effect sizes are far too small to carry that weight and that other causes are being ignored. The US National Academies concluded in 2023 that the published literature “did not support the conclusion that social media causes changes in adolescent health at the population level”, and the Surgeon General's advisory says we do not yet have enough evidence to call it safe either. When 120+ researchers were surveyed, 97.6% agreed heavy use can cause sleep problems — and more than 93% agreed the evidence is still too preliminary to say whether delaying smartphones or banning social media for under-16s would actually help.
Does a digital detox work?
For reducing screen time and improving mood over days and weeks: yes, the trials above are reasonably clear. For lasting change after the detox ends: much less clear, because almost nobody has measured it. The honest position is that a detox reliably shows you what your relationship with the screen actually is, and reliably improves how you feel while you are doing it. Whether it changes your life depends entirely on what you put in the space — which is why every part of the free course here spends more time on what replaces the screen than on the screen itself.
Is problematic use different from heavy use?
Yes, and this is the most useful distinction in the whole field. A 2026 umbrella review found that problematic social media use — compulsion, distress, loss of control — was consistently linked to poorer wellbeing, while general use measured in hours showed much weaker associations. Hours are a bad measure. How it feels to try to stop is a much better one.
What I think this means
That the mechanism matters more than the hours. Counting screen time is a poor measure and a miserable way to live; the better question is whether stopping feels free or feels frightening. The research bears this out — problematic use predicts poor wellbeing far better than duration does.
That a detox is diagnostic before it is curative. Its first job is not to fix you but to show you, unmistakably, what the screen has been standing in for. Almost everyone who does a serious one discovers something they were not expecting, and it is rarely about technology.
And that doing it alone is the most common reason it fails. This is the finding I would most like people to take seriously, because it is the one that contradicts how these things are usually sold. The free meetings at Media Addicts Anonymous and ITAA exist for exactly this reason, they run every day, and they cost nothing.
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Michael has spent much of his working life online—and much of the rest of it trying to stop that technology taking over. He has thrown a phone into a lake, locked devices in boxes and experimented with long periods offline. He writes about what helped, what failed and how to keep the useful parts of digital life.
Last updated 9 August 2026. This page is checked and corrected as new research comes out. If you spot something out of date or wrong, tell me and I will fix it.