Across 355,358 adolescents, screen time explained at most 0.4 percent of the differences in well-being
Orben and Przybylski ran every defensible analysis on three big surveys. Technology use was linked to lower well-being, but the link was tiny: eating potatoes was nearly as bad, and wearing glasses was worse.
Reasonable evidence with real limitations. how we score evidence
Caveat on this rating: Correlational self-report surveys with broad screen-time items from 2007 to 2016; a small average can hide larger effects for some young people or uses. One author discloses unpaid advisory roles to Facebook and Google. The opposite reading of similar data (Twenge) remains contested.
The paper that puts the screens and teen mental health alarm to scale, and its own limits.
Significant findings
Orben and Przybylski applied specification curve analysis, which runs every reasonable version of an analysis rather than the one that produces the wanted result, to three large datasets: the US Monitoring the Future and Youth Risk Behavior surveys and the UK Millennium Cohort Study, 355,358 adolescents in total, surveyed between 2007 and 2016. The association between digital technology use and well-being was "negative but small, explaining at most 0.4% of the variation in well-being". For comparison in the same data, being bullied and smoking marijuana had much larger negative associations (4.3 and 2.7 times larger in the YRBS). Eating potatoes (median standardised beta -0.042) was nearly as negative as technology use; in the Millennium Cohort, wearing glasses (-0.061) was more negative. Getting enough sleep and eating breakfast had larger positive associations. The authors conclude the effects "are too small to warrant policy change".
The other direction
All three datasets are correlational and self-reported. A small average could hide larger harms for some young people or from particular uses, which broad screen-time items cannot separate, and the data predate TikTok. One author, Przybylski, declares unpaid advisory roles in the previous five years to Facebook, Google, the OECD and ParentZone; the funders (EU Horizon 2020 and the ESRC) had no role. The opposite reading of this kind of data, that teen depression rose as smartphones spread (Twenge and colleagues), is contested, and the two camps have argued since.
What this does not show
It does not show that heavy use is harmless for a given teenager, or that limiting screens does nothing; the Facebook deactivation trial in this library found a small benefit from stepping away. Nothing here concerns medication.
Worth asking
Is it the hours on the screen, or what the hours replace?
Source
The association between adolescent well-being and digital technology use — Orben A, Przybylski AK (2019)
Top-tier peer-reviewed journal
Read the source: https://doi.org/10.1038/s41562-018-0506-1
DOI: 10.1038/s41562-018-0506-1
How this was scored
- Study design
- Cross-sectional study / survey
- Funding
- Independently funded
- Published in
- Top-tier peer-reviewed journal
- Sample size
- 355,358
- Preregistered
- not recorded
- Conflicts disclosed
- Yes
- Independent of proponent
- not recorded
- Retracted
- No
Read the full scoring rubric, including what it can't tell you.
Published October 7, 2026.
Questions
How strong is the evidence behind this?
veisund rates this source "moderate evidence". Reasonable evidence with real limitations. It scores 66 out of 100 on our published rubric. One caveat travels with that badge: Correlational self-report surveys with broad screen-time items from 2007 to 2016; a small average can hide larger effects for some young people or uses. One author discloses unpaid advisory roles to Facebook and Google. The opposite reading of similar data (Twenge) remains contested. The score is calculated from recorded facts about the source — study design, funding, publication venue, sample size, preregistration — not typed in by an editor.
What is the source for this?
The association between adolescent well-being and digital technology use — Orben A, Przybylski AK (2019). Published in: Top-tier peer-reviewed journal. DOI: 10.1038/s41562-018-0506-1. The full source is linked on this page so you can read it yourself.
Who paid for this research, and does that matter?
Study design: Cross-sectional study / survey. Funding: Independently funded. Independence from the proponent is not recorded. Industry sponsorship is one of the most reliably measured biases in medicine, which is why funding carries real weight in the score rather than sitting in a footnote.
Is this medical advice?
This is information to bring to your prescriber, not medical advice and not a reason to change anything on your own. Nothing here is an instruction to stop or reduce a medication. If you are in crisis, call or text 988.
This is information to bring to your prescriber, not medical advice and not a reason to change anything on your own. Nothing here is an instruction to stop or reduce a medication. If you are in crisis, call or text 988.