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      Testing the Multi-Theory Model (MTM) to Predict the Use of New Technology for Social Connectedness in the COVID-19 Pandemic

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          Abstract

          Loneliness or social isolation, recently described as a “behavioral epidemic,” remains a long-standing public health issue, which has worsened during the COVID-19 pandemic. The use of technology has been suggested to enhance social connectedness and to decrease the negative health outcomes associated with social isolation. However, till today, no theory-based studies were performed to examine the determinants of technology use. Therefore, the current study aims to test theory-based determinants in explaining the adoption of new technology in a nationally representative sample during the COVID-19 pandemic ( n = 382). A psychometrically reliable and valid instrument based on the multi-theory model (MTM) of health behavior change was administered electronically using a cross-sectional study design. A total of 47.1% of the respondents reported high levels of social isolation, and 40.6% did not use any new technology. Among technology users (59.4%), the three initiation constructs participatory dialogue (b = 0.054, p < 0.05), behavioral confidence (b = 0.184, p < 0.001), and changes in the physical environment (b= 0.053, p < 0.05) were significant and accounted for 38.3% of the variance in the initiation of new technologies. Concerning sustenance in technology users, all three constructs emotional transformation (b = 0.115, p < 0.001), practice for change (b = 0.086, p < 0.001), and changes in the social environment (b = 0.061, p < 0.001) were significant and accounted for 42.6% of the variance in maintaining the use of new technology. MTM offers a powerful framework to design health promotion interventions encouraging the use of new technologies to foster greater social connectedness amid the COVID-19 pandemic and beyond it.

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          Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.

          G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.
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            Loneliness and social isolation as risk factors for mortality: a meta-analytic review.

            Actual and perceived social isolation are both associated with increased risk for early mortality. In this meta-analytic review, our objective is to establish the overall and relative magnitude of social isolation and loneliness and to examine possible moderators. We conducted a literature search of studies (January 1980 to February 2014) using MEDLINE, CINAHL, PsycINFO, Social Work Abstracts, and Google Scholar. The included studies provided quantitative data on mortality as affected by loneliness, social isolation, or living alone. Across studies in which several possible confounds were statistically controlled for, the weighted average effect sizes were as follows: social isolation odds ratio (OR) = 1.29, loneliness OR = 1.26, and living alone OR = 1.32, corresponding to an average of 29%, 26%, and 32% increased likelihood of mortality, respectively. We found no differences between measures of objective and subjective social isolation. Results remain consistent across gender, length of follow-up, and world region, but initial health status has an influence on the findings. Results also differ across participant age, with social deficits being more predictive of death in samples with an average age younger than 65 years. Overall, the influence of both objective and subjective social isolation on risk for mortality is comparable with well-established risk factors for mortality.
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              An index of factorial simplicity

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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Healthcare (Basel)
                Healthcare (Basel)
                healthcare
                Healthcare
                MDPI
                2227-9032
                01 July 2021
                July 2021
                : 9
                : 7
                : 838
                Affiliations
                [1 ]Department of Environmental and Occupational Health, University of Nevada, Las Vegas, NV 89119, USA; Manoj.Sharma@ 123456unlv.edu (M.S.); Jason.flatt@ 123456unlv.edu (J.F.)
                [2 ]Office of Research, Kirk Kerkorian School of Medicine, University of Nevada, Las Vegas, NV 89102, USA
                Author notes
                [* ]Correspondence: Kavita.batra@ 123456unlv.edu
                Author information
                https://orcid.org/0000-0002-4624-2414
                https://orcid.org/0000-0002-0722-0191
                Article
                healthcare-09-00838
                10.3390/healthcare9070838
                8303357
                bce2fe4b-bfbf-4cd5-9cf8-d1162abfbef7
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 06 June 2021
                : 28 June 2021
                Categories
                Article

                social isolation,social connectedness,loneliness,depression,technology,internet,smartphones,m-health,covid-19,pandemic

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