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      Does Objectively Measured Social-Media or Smartphone Use Predict Depression, Anxiety, or Social Isolation Among Young Adults?

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          Abstract

          Despite a plethora of research, the link between digital-technology use and psychological distress among young adults remains inconclusive. Findings in this area are typically undermined by methodological limitations related to measurement, study design, and statistical analysis. Addressing these limitations, we examined the prospective, within-persons associations between three aspects of objectively measured digital-technology use (duration and frequency of smartphone use, duration of social-media use) and three aspects of psychological distress (depression, anxiety, and social isolation) among a sample of young adults ( N = 384). Across 81 different model specifications, we found that most within-persons prospective effects between digital-technology use and psychological distress were statistically nonsignificant, and all were very small—even the largest effects were unlikely to register a meaningful impact on a person’s psychological distress. In post hoc subgroup analyses, we found scant evidence for the claim that digital-technology use is more harmful for women and/or younger people.

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          Most cited references61

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          Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives

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            False-positive psychology: undisclosed flexibility in data collection and analysis allows presenting anything as significant.

            In this article, we accomplish two things. First, we show that despite empirical psychologists' nominal endorsement of a low rate of false-positive findings (≤ .05), flexibility in data collection, analysis, and reporting dramatically increases actual false-positive rates. In many cases, a researcher is more likely to falsely find evidence that an effect exists than to correctly find evidence that it does not. We present computer simulations and a pair of actual experiments that demonstrate how unacceptably easy it is to accumulate (and report) statistically significant evidence for a false hypothesis. Second, we suggest a simple, low-cost, and straightforwardly effective disclosure-based solution to this problem. The solution involves six concrete requirements for authors and four guidelines for reviewers, all of which impose a minimal burden on the publication process.
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              Evaluating Effect Size in Psychological Research: Sense and Nonsense

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                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                Clinical Psychological Science
                Clinical Psychological Science
                SAGE Publications
                2167-7026
                2167-7034
                September 2022
                March 25 2022
                September 2022
                : 10
                : 5
                : 997-1014
                Affiliations
                [1 ]Department of Psychiatry, University of Pittsburgh
                [2 ]Department of Psychology, University of Pittsburgh
                [3 ]School of Social Work, University of Pittsburgh
                Article
                10.1177/21677026221078309
                36406004
                1974064e-bebf-449d-9f91-a2406a8a858d
                © 2022

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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