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      Attention Training Improves the Self-Reported Focus and Emotional Regulation of High School Students

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          Abstract

          Previous research points to digital attention training as a potential remedy for the growing levels of distraction and emotional distress that adolescents experience. However, no studies with a comparison group have been conducted in high school settings to assess the feasibility and efficacy of digital attention training. Using a two-group, pretest/posttest design, this study examined the effect of an online course called Finding Focus. Across three U.S. high schools, N = 197, classrooms were assigned to either continue with school-as-usual or to complete 2.5 hr of attention training over the course of 22 days. At pretest, data collection via online surveys showed that 77% of students reported focusing less often during class than they believed they ideally should. Compared to those in the control condition, students in the intervention condition reported at posttest adopting a stronger growth mindset regarding their ability to focus (Cohen’s d = .42) and greater confidence that they knew how to train that ability ( d = .89). At posttest, those in the intervention condition also self-reported less mind-wandering during class ( d = .31) and daily life ( d = .42), as well as higher classroom focus ( d = .29). The intervention also led to improvements in perceived emotional regulation ( d = .37). Collectively, these results suggest that digital interventions may be a promising and scalable avenue for improving adolescents’ attention and emotional well-being.

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          A power primer.

          One possible reason for the continued neglect of statistical power analysis in research in the behavioral sciences is the inaccessibility of or difficulty with the standard material. A convenient, although not comprehensive, presentation of required sample sizes is provided here. Effect-size indexes and conventional values for these are given for operationally defined small, medium, and large effects. The sample sizes necessary for .80 power to detect effects at these levels are tabled for eight standard statistical tests: (a) the difference between independent means, (b) the significance of a product-moment correlation, (c) the difference between independent rs, (d) the sign test, (e) the difference between independent proportions, (f) chi-square tests for goodness of fit and contingency tables, (g) one-way analysis of variance, and (h) the significance of a multiple or multiple partial correlation.
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            Individual differences in two emotion regulation processes: Implications for affect, relationships, and well-being.

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              Emotion Regulation: Current Status and Future Prospects

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                Author and article information

                Journal
                Technology, Mind, and Behavior
                American Psychological Association
                2689-0208
                November 2, 2022
                : 3
                : 4
                Affiliations
                [1]Department of Psychology, The University of Texas at Austin
                [2]Department of Psychological and Brain Sciences, University of California Santa Barbara
                Author notes
                Action Editor: Danielle S. McNamara was the action editor for this article.
                Funding: This research was supported by the Institute of Education Sciences Grant R305A110277 awarded to Jonathan W. Schooler. The content does not necessarily reflect the position or policy of the U.S. government and the funding source had no other role than financial support.
                Disclosures: The authors have no conflicts of interest to declare that are relevant to the content of this article.
                Data Availability: Data connected to this study are available at the Open Science Foundation ( https://osf.io/rfq2v/).
                Open Science Disclosures:

                The data are available at https://osf.io/5pfr9/.

                The experimental materials are available at https://osf.io/cx3tu/.

                The preregistered design is available at https://osf.io/gb6ac/.

                [*] Alissa J. Mrazek, Department of Psychology, The University of Texas at Austin, 108 East Dean Keeton Street, Austin, TX 78712, United States mrazek@utexas.edu
                [*] Michael D. Mrazek, Department of Psychological and Brain Sciences, University of California Santa Barbara, Building 251, Santa Barbara, CA 93106, United States mrazek@ucsb.edu
                Author information
                https://orcid.org/0000-0003-3178-1789
                Article
                2023-14755-001
                10.1037/tmb0000092
                23dee6ab-0b82-40df-9330-7777a56f7a9f
                © 2022 The Author(s)

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC-BY-NC-ND). This license permits copying and redistributing the work in any medium or format for noncommercial use provided the original authors and source are credited and a link to the license is included in attribution. No derivative works are permitted under this license.

                History

                Education,Psychology,Vocational technology,Engineering,Clinical Psychology & Psychiatry
                mindfulness,focus,attention training,emotion regulation,digital intervention

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