testflight

social media syndrome

not a diagnosis

thirteen signs. nobody has checked whether they turn up in the same person.

There is already a scale. It is called Social Media Disorder, and it counts how much you use: nine questions; answer yes to five of them and you qualify. It is not an official diagnosis anywhere. And it measures only how much — not what the use does to you. This page is the other half.

observed. 1 — van den Eijnden, Lemmens & Valkenburg (2016).

If any of this frightens you, talk to a doctor. Each sign carries the grade its evidence has earned:

counted
Hospital records, exam results, minutes — the strongest evidence.
randomised
A real experiment, on a small group.
observed
People said so; nobody measured it.
direction
The link is real; which causes which is not known.

01 the thirteen

one at a time

the mind, the body, the day, the edges — and the paper each one stands on.

depression, anxiety, self‑harm, substance use

All four rose in the same Italian hospital records — the one place the signs were seen together. Fast internet reached the towns at different times. Those who got it before age twenty went to hospital more often. Those born ten years earlier: no change. Same country, same hospitals, same years — so this is not just every generation panicking about a new machine.

An American study of one social network’s college rollout — 430,000 responses — found the first two: severe depression up 7%, anxiety up 20%.

counted. 2 · 3 — Donati et al. (2025); Braghieri, Levy & Makarin (2022).

sleep

When fast internet reached Spain, teenagers slept less. Almost all of the loss was among girls.

counted. 4 — Arenas‑Arroyo, Fernández‑Kranz & Nollenberger (2025).

your face stops being enough

A trial split 144 girls into groups at random. Looking at filtered photos lowered how they felt about their own bodies, on the spot.

randomised. 5 — Kleemans, Daalmans, Carbaat & Anschütz (2018).

and then you ask a surgeon

Among facial plastic surgeons, 55% say patients ask to look better in their selfies. Two years earlier it was 42%. This is an opinion piece, not a study, and the numbers come from a surgeons’ association asking its own members — the weakest row here, and the one closest to the writer’s own former trade.

observed. 6 — Rajanala, Maymone & Vashi (2018).

time you did not choose

Offered a daily limit they could set themselves, people used much less. The authors estimate that 31% of all social media use is time people did not actually choose.

counted. 7 — Allcott, Gentzkow & Song (2022).

falling behind

Schools that banned phones saw scores rise. The bottom quarter gained twice the average; the top gained nothing.

counted. 8 — Beland & Murphy (2016).

the phone only has to be there

Face down and silent, your own phone still costs you a little memory. Memory only — the effect on attention did not hold up. A review of 22 studies found the same: only memory, and only clearly in the studies from Asia. So the overall number rests on one part of the world.

randomised. 9 · 10 — Ward, Duke, Gneezy & Bos (2017); Böttger, Poschik & Zierer (2023).

pulling away

Less time with family. Less with friends.

counted. 4 — Arenas‑Arroyo, Fernández‑Kranz & Nollenberger (2025).

money, through the same door

The more someone spends on loot boxes — paid random rewards inside games — the more gambling problems they report. Fifteen studies found a small‑to‑moderate link, but none could say which causes which. One study looked at a game that removed loot boxes: problem gamblers then spent much less. It was 112 players, before and after, and the author calls the pattern complicated.

direction. 11 · 12 — Garea et al. (2021); Zendle (2019).

identity that will not settle

Across 32 studies and nearly 20,000 teenagers, what you do online matters more than how long you stay — and comparing yourself to others raises both self‑searching and distress. One study followed the same teenagers over time: low self‑esteem led to more use, while more use barely changed self‑esteem. That is the opposite direction from the one this page would want.

direction. 13 — Avci, Baams & Kretschmer (2025).

02 the case against

potatoes

the strongest paper on the other side, in full.

bullied –0.212 binge-drinking –0.144 asthma –0.066 technology –0.049 potatoes –0.042 breakfast +0.116 sleep +0.150
how much each thing explains about wellbeing — Orben & Przybylski, 2019

The researchers tried 600 million reasonable ways of analysing three national surveys. Screen time explained at most 0.4% of a teenager’s wellbeing — between having asthma and eating potatoes. Being bullied was four times worse. Getting enough sleep helped three times more than screens hurt. But those surveys used hours that people guessed. The strongest rows above measure a hospital admission, an exam result, a counted minute — and the weakest rows are exactly the ones this paper dissolves.

Odgers and Jensen go further: most of this research only shows that two things go together, not that one causes the other; the results point both ways; and the most careful large studies find effects too small to matter in a clinic. Guessed screen time matches measured screen time only weakly — and of the 29 studies they list, just two measured it at all.

observed. 14 · 15 — Orben & Przybylski (2019); Odgers & Jensen (2020).

03 the honest ending

until one does

every study above counted its sign alone. none looked for two in the same person.

the other binge

In adults, binge‑watching TV and loneliness go together. The same emptiness shows up in people who never opened the apps. The substance can be swapped. The shape stays the same — and this one is not one of the thirteen.

observed. 16 — Sun & Chang (2021).

the same person

Nobody has asked whether the one who lost the sleep is the one who edited the selfie, who bought the loot box, who stopped seeing friends. Until a study measures two signs in the same person, this is a suspicion, not a finding.

a suspicion you can check is worth more than a certainty you cannot.

04 sources

sixteen papers

no name on this page, on purpose. every number on it has a source you can check.

  1. van den Eijnden, R. J. J. M., Lemmens, J. S. & Valkenburg, P. M. (2016). The Social Media Disorder Scale. Computers in Human Behavior, 61, 478–⁠487.
  2. Donati, D., Durante, R., Sobbrio, F. & Zejcirovic, D. (2025). Lost in the net? Broadband internet and youth mental health. Journal of Health Economics, 103, 103017.
  3. Braghieri, L., Levy, R. & Makarin, A. (2022). Social Media and Mental Health. American Economic Review, 112(11), 3660–⁠3693.
  4. Arenas‑Arroyo, E., Fernández‑Kranz, D. & Nollenberger, N. (2025). High speed internet and the widening gender gap in adolescent mental health: Evidence from Spanish hospital records. Journal of Health Economics, 102, 103014.
  5. Kleemans, M., Daalmans, S., Carbaat, I. & Anschütz, D. (2018). Picture Perfect: The Direct Effect of Manipulated Instagram Photos on Body Image in Adolescent Girls. Media Psychology, 21(1), 93–⁠110.
  6. Rajanala, S., Maymone, M. B. C. & Vashi, N. A. (2018). Selfies — Living in the Era of Filtered Photographs. JAMA Facial Plastic Surgery, 20(6), 443–⁠444.
  7. Allcott, H., Gentzkow, M. & Song, L. (2022). Digital Addiction. American Economic Review, 112(7), 2424–⁠2463.
  8. Beland, L.‑P. & Murphy, R. (2016). Ill Communication: Technology, distraction & student performance. Labour Economics, 41, 61–⁠76.
  9. Ward, A. F., Duke, K., Gneezy, A. & Bos, M. W. (2017). Brain Drain: The Mere Presence of One’s Own Smartphone Reduces Available Cognitive Capacity. Journal of the Association for Consumer Research, 2(2), 140–⁠154.
  10. Böttger, T., Poschik, M. & Zierer, K. (2023). Does the Brain Drain Effect Really Exist? A Meta‑Analysis. Behavioral Sciences, 13(9), 751.
  11. Garea, S. S., Drummond, A., Sauer, J. D., Hall, L. C. & Williams, M. N. (2021). Meta‑analysis of the relationship between problem gambling, excessive gaming and loot box spending. International Gambling Studies, 21(3), 460–⁠479.
  12. Zendle, D. (2019). Problem gamblers spend less money when loot boxes are removed from a game: a before and after study of Heroes of the Storm. PeerJ, 7, e7700.
  13. Avci, H., Baams, L. & Kretschmer, T. (2025). A Systematic Review of Social Media Use and Adolescent Identity Development. Adolescent Research Review, 10(2), 219–⁠236.
  14. Orben, A. & Przybylski, A. K. (2019). The association between adolescent well‑being and digital technology use. Nature Human Behaviour, 3(2), 173–⁠182.
  15. Odgers, C. L. & Jensen, M. R. (2020). Annual Research Review: Adolescent mental health in the digital age — facts, fears, and future directions. Journal of Child Psychology and Psychiatry, 61(3), 336–⁠348.
  16. Sun, J. J. & Chang, Y. J. (2021). Associations of Problematic Binge‑Watching with Depression, Social Interaction Anxiety, and Loneliness. International Journal of Environmental Research and Public Health, 18(3), 1168.

This is the case love&truth was built on.