Depression and associated factors among elderly using social media
Keywords:
social media, older adults, depression, addiction, internetAbstract
Objective: Previous studies have found that long-term use of social media is associated with depression in adolescents and young adults, but studies in the elderly are limited. This study aimed to study depression and associated factors among elderly using social media.
Methods: The study was a cross-sectional study of 300 elderly people at Rajavithi Hospital, collected data during January 2023 to April 2023. The questionnaire was conducted using the Social Media Addict Test (SMAT) and Thai Geriatric Depression Scales (TGDS-15). The data were analyzed using descriptive statistics, chi-square statistics and logistical regression.
Results: The age of the participants was 66.4±5.25 years with 3 percent depression. Social media usage period was 69.8±32.056 month and social media access was 240.8±128.8 minutes per day. The participants with social media addiction were 4.30 percent. The factors associated with depression showed significant (p<0.05) were monthly income less than 15,000 baht (p=0.001), social media usage period (p=0.007) and following the news (p=0.010). The monthly income less than 15,000 baht was associated with depression when combined all factors. (Adj. OR 12.3 95%CI 1.46-102.6, p=0.021)
Conclusions: The depression of the elderly using social media was slightly. Monthly income was associated with depression in elderly using social media.
References
Roser M, Ritchie H, Ortiz-Ospina E. Internet. Our World in Data [Internet]. 2015 [cited 2022 Jun 10]. Available from: https://ourworldindata.org/internet.
Johnson J. Internet. Internet usage worldwide [Internet]. 2021 [cited 2022 Jun 10]. Available from: https://www.statista.com/statistics/273018/number-of-internet-users-worldwide/
Lotrakul M, Sukanich P. Psychology Ramathibodi, 4th ed. Department of Psyshology, Faculty of Medicine, Ramathibodi Hospital, Mahidol University; 2015.
Department of Strategy, Electronic Transactions Development Agency, Ministry of Digital Economy and Society. Report on the survey of internet user behavior in Thailand. Bangkok: Electronic Transactions Development Agency, Ministry of Digital Economy and Society; 2020.
Hemmin A. Social media consumption behaviors and opinion towards results of experiencing social media in Bangkok metropolitan [Thesis]. Master of Science (Applied Statistic): National Institute of Development Administration; 2556.
Dullaphan K. Social networking usage behavior and mental factor as a predictor of depression [Thesis]. Master of Arts (communication Arts and Innovation): National Institute of Development Administration; 2561.
Liu YL, Jaime SE, Shensa A, Radovic A, Miller E, Jason CB, et al. Association between social media use and depression among U.S. young adults. Depression and anxiety. 2016; 33: 323-31.
Heather CW, Scott H. Social media use in adolescence is associated with poor sleep quality, anxiety, depression and low self-esteem. J. Adolesc. 2016; 51: 41-49.
Social Statistics Division, National Statistics Office. Executive summary of the survey on Thai elderly in 2021. Bangkok: Statistical Forecasting Division, 2022.
Foundation of Thai Gerontology Research and Development institute (TGRI). Situation of the Thai older persons 2021. Bangkok: Amarin Corporations Public Company Limited; 2022.
Rattana M. Prevalence and factors related to depression among elderly in Phra Nakorn Sri Ayuttaya province [Thesis]. Master of Public Health: Thammasat University; 2559.
Sadock BJ, Sadock AV, Ruiz P. Synopsis of psychiatry. 11th ed. Philadelphia: Wolters Kluwer; 2015.
Changthong T, Laeheem K. Psychosocial Affecting the Depression among the Elderly in Nakhon Si Thammarat Province. J Soc Sci Law Politics. 2021; 5: 53-70.
Setapura P, Chaisongkram N. Prevalence and Associated Factors of Depressive Disorder among the Elderly in Thailand, 2021. Reg Health Promot Center 9 J. 2022; 16: 1070-1084.
Thumcharoen W, Chalernngam N, Chotedelok Y, et al. Factors Related to Depression of the Elderly. Rajabhat Rambhai Barni Res J. 2021; 15: 52-62.
Djernes JK. Prevalence and predictors of depression in populations of elderly. Acta Psychiatr Scand 2006; 113: 372-387.
Wayne WD. Biostatistics: A foundation of analysis in the health sciences. 6th ed. New York: John Wiley and Sons; 1995.
Phantong W, Khammathi A, Saengthong W, et al. Prevalence and Factors Related to Depression among Elderly People in Community Hospitals. S Coll Network J Nurs Publ Health. 2563; 7: 114-126.
Pernsungnern P, Pornnoppadol C, Sitdhiraksa N, Buntub D. Social media addiction: prevalence and association with depression among 7th-12th Grade Students in Bangkok. Graduate Research Conference 2014; 2014 Mar 28; Khon Kaen, Thailand. Khon Kaen: Khon Kaen University; 2014: 1132-9.
Wongpakaran N, Wongpakaran T, Reekum VR. The use of GDS-15 in detecting MDD: A comparison between residents in a Thai long-term care home and geriatric outpatients. J. Clin. Med. Res. 2013; 5: 101–111.
Siriwankulthon I, Jiraporncharoen W, Pinyopornpanish K, et al. Prevalence and factors associated with depression in elderly patients in family medicine outpatient clinic, Chiang Mai University. J Ment Health Thai. 2564; 29: 1-11.
Phanichsiri K, Tuntasood B. Social Media Addiction and Attention Deficit and Hyperactivity Symptoms in High School Students in Bangkok. J Psychiatr Assoc Thailand. 2559; 61: 191-204.
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