The association between adolescent well-being and digital technology use



The widespread use of digital technologies by young people has spurred speculation that their regular use negatively impacts psychological well-being. Current empirical evidence supporting this idea is largely based on secondary analyses of large-scale social datasets. Though these datasets provide a valuable resource for highly powered investigations, their many variables and observations are often explored with an analytical flexibility that marks small effects as statistically significant, thereby leading to potential false positives and conflicting results. Here we address these methodological challenges by applying specification curve analysis (SCA) across three large-scale social datasets (total n = 355,358) to rigorously examine correlational evidence for the effects of digital technology on adolescents. The association we find between digital technology use and adolescent well-being is negative but small, explaining at most 0.4% of the variation in well-being. Taking the broader context of the data into account suggests that these effects are too small to warrant policy change.

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Fig. 1: Results of SCA of the YBRS.
Fig. 2: Results of SCA for MTF.
Fig. 3: Results of SCA for MCS.
Fig. 4: Results of SCA for MCS, split by whether controls are included in the analysis.
Fig. 5: Comparison specifications for MCS.

Data availability

The data that support the findings of this study are available from the Centre for Disease Control and Prevention (YRBS), Monitoring the Future (MTF) and the UK data service (MCS), but restrictions apply regarding the availability of these data, which were used under licence for the current study and so are not publicly available. Data are, however, available from the relevant third-party repository after agreement to their terms of usage. Information about data collection and questionnaires can be found on the OSF website (


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The National Institute on Drug Abuse provided funding for the MTF conducted at the Survey Research Centre in the Institute for Social Research, University of Michigan. The YRBS was collected by the Centres for Disease Control and Prevention. The Centre for Longitudinal Studies, UCL Institute of Education collected the MCS and the UK Data Archive/UK Data Service provided the data. They bear no responsibility for its aggregation, analysis or interpretation. A.O. was supported by a EU Horizon 2020 IBSEN grant. A.K.P. was supported by an Understanding Society Policy Fellowship funded by the Economic and Social Research Council. A.O. and A.K.P.’s funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Thanks are extended to U. Simonsohn, N.K. Reimer and N. Weinstein for their valuable input, and to J.M. Rohrer, U. Simonsohn, J.P. Simmons and L.D. Nelson for code provision. We also acknowledge the use of the University of Oxford Advanced Research Computing facility in carrying out this research: The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information




A.O. conceptualized the study, with regular guidance from A.K.P. A.O. completed the statistical analyses and drafted the manuscript. A.K.P. gave integral feedback in the process.

Corresponding author

Correspondence to Amy Orben.

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Competing interests

A.O. has no competing interests. A.K.P. has no competing financial interests; in the last five years A.K.P. has served in an unpaid advisory capacity with the Organization for Economic Co-operation and Development, Facebook Inc., Google Inc. and the ParentZone.

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Supplementary information

Supplementary Information

Supplementary Methods, Supplementary Figures 1–12, Supplementary Tables 1, 2, 5, 6, Supplementary Note, and Supplementary References

Reporting Summary

Supplementary Table 3

The MTF questionnaire contains different questionnaire types that are completed by different subsets of participants. Different numbers of participants, therefore, completed different combinations of questions, the details of which are displayed in this table. DS, depressive symptoms, SE, self-esteem; LO, loneliness.

Supplementary Table 4

In both the MTF and YRBS datasets questions were added and changed over the course of the study. This table outlines these alterations, showing both when questions were added and when they were modified.

Supplementary Software

R code and .run scripts to reproduce the analyses presented in the manuscript. A life version of this code can be found on the Open Science Framework:

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Orben, A., Przybylski, A.K. The association between adolescent well-being and digital technology use. Nat Hum Behav 3, 173–182 (2019).

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