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      Sleep Quality and Self-Stigma Mediate the Association Between Problematic Use of Social Media and Quality of Life Among People With Schizophrenia in Taiwan: A Longitudinal Study

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          Abstract

          Objective

          Problematic use of social media (PUSM) may affect sleep quality and self-stigma in people with schizophrenia and consequently reduce their quality of life (QoL). This longitudinal study investigated if sleep quality and self-stigma mediated relationships between PUSM and QoL.

          Methods

          One-hundred-and-ninety-three outpatients with schizophrenia were recruited from a psychiatric center in Taiwan from April 2019 to August 2021 and participated in a longitudinal study at intervals of three months between measurements. QoL was assessed using the World Health Organization Quality of Life Questionnaire Brief Version; sleep quality using the Pittsburgh Sleep Quality Index; self-stigma using the Self-Stigma Scale-Short; and PUSM using the Bergen Social Media Addiction Scale. Via SPSS 20.0, general estimating equation models assessed temporal associations between variables. Via R software, mediating effects of self-stigma and sleep quality were examined through Monte Carlo simulations with 20,000 repetitions.

          Results

          Mean scores of physical, psychological, social and environmental QoL ranged from 11.86 to 13.02. Mean scores of sleep quality and self-stigma were 9.1±4.5 and 2.2±0.8, respectively. Sleep quality and self-stigma were directly related to QoL (p<0.001) and mediated indirect relationships between PUSM and all components of QoL with a range of 95% confidence intervals spanning from -0.0591 to -0.0107 for physical QoL; -0.0564 to -0.0095 for psychological QoL; -0.0292 to -0.0035 for social QoL; and -0.0357 to -0.0052 for environmental QoL.

          Conclusion

          Sleep quality and self-stigma mediated relationships between PUSM and QoL in people with schizophrenia. Developing interventions targeting PUSM, sleep, and self-stigma may help improve QoL in people with schizophrenia.

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          Most cited references73

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          The Pittsburgh sleep quality index: A new instrument for psychiatric practice and research

          Despite the prevalence of sleep complaints among psychiatric patients, few questionnaires have been specifically designed to measure sleep quality in clinical populations. The Pittsburgh Sleep Quality Index (PSQI) is a self-rated questionnaire which assesses sleep quality and disturbances over a 1-month time interval. Nineteen individual items generate seven "component" scores: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. The sum of scores for these seven components yields one global score. Clinical and clinimetric properties of the PSQI were assessed over an 18-month period with "good" sleepers (healthy subjects, n = 52) and "poor" sleepers (depressed patients, n = 54; sleep-disorder patients, n = 62). Acceptable measures of internal homogeneity, consistency (test-retest reliability), and validity were obtained. A global PSQI score greater than 5 yielded a diagnostic sensitivity of 89.6% and specificity of 86.5% (kappa = 0.75, p less than 0.001) in distinguishing good and poor sleepers. The clinimetric and clinical properties of the PSQI suggest its utility both in psychiatric clinical practice and research activities.
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            Development of the World Health Organization WHOQOL-BREF Quality of Life Assessment

            (1998)
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              The relationship between addictive use of social media and video games and symptoms of psychiatric disorders: A large-scale cross-sectional study.

              Over the last decade, research into "addictive technological behaviors" has substantially increased. Research has also demonstrated strong associations between addictive use of technology and comorbid psychiatric disorders. In the present study, 23,533 adults (mean age 35.8 years, ranging from 16 to 88 years) participated in an online cross-sectional survey examining whether demographic variables, symptoms of attention-deficit/hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), anxiety, and depression could explain variance in addictive use (i.e., compulsive and excessive use associated with negative outcomes) of two types of modern online technologies: social media and video games. Correlations between symptoms of addictive technology use and mental disorder symptoms were all positive and significant, including the weak interrelationship between the two addictive technological behaviors. Age appeared to be inversely related to the addictive use of these technologies. Being male was significantly associated with addictive use of video games, whereas being female was significantly associated with addictive use of social media. Being single was positively related to both addictive social networking and video gaming. Hierarchical regression analyses showed that demographic factors explained between 11 and 12% of the variance in addictive technology use. The mental health variables explained between 7 and 15% of the variance. The study significantly adds to our understanding of mental health symptoms and their role in addictive use of modern technology, and suggests that the concept of Internet use disorder (i.e., "Internet addiction") as a unified construct is not warranted.
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                Author and article information

                Journal
                Psychiatry Investig
                Psychiatry Investig
                PI
                Psychiatry Investigation
                Korean Neuropsychiatric Association
                1738-3684
                1976-3026
                November 2023
                21 November 2023
                : 20
                : 11
                : 1034-1044
                Affiliations
                [1 ]Health Research Center, Life Style Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
                [2 ]Health Education Department, Faculty of Health, Baqiyatallah University of Medical Sciences, Tehran, Iran
                [3 ]Department of General Psychiatry, Jianan Psychiatric Center, Ministry of Health and Welfare, Tainan, Taiwan
                [4 ]Department of Psychiatry, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
                [5 ]Department of Medical Research, E-Da Hospital, I-Shou University, Kaohsiung, Taiwan
                [6 ]Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
                [7 ]Connecticut Mental Health Center, New Haven, CT, USA
                [8 ]Connecticut Council on Problem Gambling, Wethersfield, CT, USA
                [9 ]Child Study Center, Yale School of Medicine, New Haven, CT, USA
                [10 ]Department of Neuroscience, Yale University, New Haven, CT, USA
                [11 ]Wu Tsai Institute, Yale University, New Haven, CT, USA
                [12 ]Department of Psychiatry, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
                [13 ]Department of Psychiatry, School of Medicine and Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
                [14 ]College of Professional Studies, National Pingtung University of Science and Technology, Pingtung, Taiwan
                [15 ]Graduate Institute of Social Work, National Taiwan Normal University, Taipei, Taiwan
                [16 ]Institute of Allied Health Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan
                [17 ]Department of Psychiatry, School of Medicine, Tzu Chi University, Hualien, Taiwan
                [18 ]Department of Psychiatry, Tzu Chi General Hospital, Hualien, Taiwan
                [19 ]University of Religions and Denominations, Qom, Iran
                [20 ]Department of Public Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan
                [21 ]Department of Occupational Therapy, College of Medicine, National Cheng Kung University, Tainan, Taiwan
                [22 ]Biostatistics Consulting Center, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
                Author notes
                Correspondence: Chung-Ying Lin, PhD Institute of Allied Health Sciences, College of Medicine, National Cheng Kung University, 1 University Rd, Tainan 701401, Taiwan Tel: +886-6-2353535, Fax: +886-6-2367981, E-mail: cylin36933@ 123456gmail.com
                Correspondence: Hsin-Chi Tsai, MD, PhD Department of Psychiatry, Tzu Chi General Hospital, 701 Zhongyang Rd., Sec. 3, Hualien 970374, Taiwan Tel: +886-3-8561825, Fax: +886-3-8560977, E-mail: cssbmw45@ 123456gmail.com
                [*]

                These authors contributed equally to this work.

                Author information
                http://orcid.org/0000-0001-7590-9516
                http://orcid.org/0000-0002-0551-1999
                http://orcid.org/0000-0003-3187-9479
                http://orcid.org/0000-0002-6323-1354
                http://orcid.org/0000-0003-1156-4939
                http://orcid.org/0000-0002-9132-3539
                http://orcid.org/0000-0002-2047-2246
                http://orcid.org/0000-0003-1015-8728
                http://orcid.org/0000-0002-2129-4242
                Article
                pi-2023-0169
                10.30773/pi.2023.0169
                10678148
                37997331
                730851a1-8c39-4a46-a958-3f6a5bf973e4
                Copyright © 2023 Korean Neuropsychiatric Association

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 19 May 2023
                : 10 July 2023
                : 28 August 2023
                Categories
                Original Article

                Clinical Psychology & Psychiatry
                addictive behaviors,internet addiction disorder,technology addiction,social media addictions,schizophrenia,stereotyping

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