Specification-curve analyses (Orben & Przybylski 2019 and successors) systematically vary analytic choices across thousands of plausible model specifications and find that the median association between adolescent digital technology use and well-being explains less than half a percent of variance — comparable in magnitude to associations with eating potatoes or wearing glasses.

Anonymous

Argument·Showcase: Smartphones, social media, and adolescent mental health

Conclusion

Specification-curve analyses (Orben & Przybylski 2019 and successors) systematically vary analytic choices across thousands of plausible model specifications and find that the median association between adolescent digital technology use and well-being explains less than half a percent of variance — comparable in magnitude to associations with eating potatoes or wearing glasses.

Argument

TODO: explain what specification-curve analysis is, what it is designed to detect, and why the consistent ~0.4% variance result across thousands of specifications is the methodologically correct way to read the cross-sectional well-being literature.

⟨ ⟩Argument from Witness TestimonyReasoning based on direct observation by someone present at an event

Supporting evidence for the conclusion (10)

Orben & Przybylski — Adolescent well-being and digital tech use (Nat Hum Behav 2019)

https://www.nature.com/articles/s41562-018-0506-1

Orben & Przybylski — Adolescent well-being and digital tech use (Nat Hum Behav 2019)

https://www.nature.com/articles/s41562-018-0506-1

Orben & Przybylski — Adolescent well-being and digital tech use (Nat Hum Behav 2019)

https://www.nature.com/articles/s41562-018-0506-1

Orben & Przybylski — Adolescent well-being and digital tech use (Nat Hum Behav 2019)

https://www.nature.com/articles/s41562-018-0506-1

Orben & Przybylski — Adolescent well-being and digital tech use (Nat Hum Behav 2019)

https://www.nature.com/articles/s41562-018-0506-1

Orben & Przybylski — Adolescent well-being and digital tech use (Nat Hum Behav 2019)

https://www.nature.com/articles/s41562-018-0506-1

Orben & Przybylski — Adolescent well-being and digital tech use (Nat Hum Behav 2019)

https://www.nature.com/articles/s41562-018-0506-1

Orben & Przybylski — Adolescent well-being and digital tech use (Nat Hum Behav 2019)

https://www.nature.com/articles/s41562-018-0506-1

Orben & Przybylski — Adolescent well-being and digital tech use (Nat Hum Behav 2019)

https://www.nature.com/articles/s41562-018-0506-1

Orben & Przybylski — Adolescent well-being and digital tech use (Nat Hum Behav 2019)

https://www.nature.com/articles/s41562-018-0506-1

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Is the testimony corroborated by evidence?Open
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Odgers and her co-authors have spent more than a decade working directly with the kind of datasets and analytic methods this debate hinges on, and they keep arriving at the same conclusion: the associations are real but small, the methods are more fragile than the popular synthesis lets on, and the cross-national timing pattern looks cleaner from a distance than it does once you break it apart by country and metric. The expert_opinion scheme licenses giving weight to that judgment in the specific sub-area where she has done primary methodological work. Her position isn't dismissive — she takes the rise in adolescent distress seriously and isn't denying it's happened — it's about what the existing data can and can't carry. Specification-curve analysis, which runs the same association across thousands of plausible model choices and looks at the distribution rather than picking one specification to publish, returns effects in the range of 0.4% of variance: not nothing, but not the kind of effect size that typically supports a "principal cause" claim. And several drivers that co-vary with smartphone adoption — declining sleep, less unsupervised face-to-face time, changes in clinical screening practice — can't be cleanly separated from social media in the available studies.
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Anonymous. (2026). Specification-curve analyses (Orben & Przybylski 2019 and successors) systematically vary analytic choices across thousands of plausible model specifications and find that the median association between adolescent digital technology use and well-being explains less than half a percent of variance — comparable in magnitude to associations with eating potatoes or wearing glasses. Isonomia. https://www.isonomia.app/a/9pSbtMcQ@bda0466ff64a4254d8e3197964b1a37b166a7e777c4777b583c6eb683a685065

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