The psychological impact of COVID-19 and the subsequent social isolation on the general population of Karnataka, India
Notice bibliographique
Résumé
Background: The COVID-19 pandemic has various unfavorable effects on individuals and the community. This study aims to assess the psychological impact of the COVID-19 epidemic and the subsequent social isolation on the general population of Karnataka, India. Methods: A web-based cross-sectional survey was conducted in Karnataka from 8 to 14 April 2020 using the snowball technique. The psychological impact was assessed with the help of the nine-item Patient Health Questionnaire-9 (PHQ-9) and seven-item General Anxiety Disorder-7 (GAD-7) questionnaires. IBM SPSS Statistics Subscription version 16.0 was recruited to analyze the data. Descriptive (Mean + Standard Deviation) and bivariate (Pearson chi-square and ANOVA tests) analysis used to present data with the significance level set at less than 0.05. Results: This study included 1537 participants from 26 cities in Karnataka. About two-thirds of the respondents were undergraduate students (951, 61.9%), females (768, 50.0%), and 40.1% stayed about 15-20 days in social isolation. The prevalence of depression was 47.0%, and anxiety was 41.5%, respectively, among the surveyed sample. After the analysis, the age group 21-30 year old (P < 0.001), females P < 0.001), urban residents (P = 0.021), and the students (P p < 0.001) were significant for depression. However, only the age group 31-40 years was found to be more susceptible to anxiety. Conclusion: As important as addressing the psychological effects, knowing people at risk of developing mental illnesses will contribute effectively to providing appropriate psychological rehabilitation programs at the right time. References World Health Organization, Novel Coronavirus (2019-nCoV) Situation Report –1, 21 January 2020. Available from: https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200121-sitrep-1-2019-ncov.pdf, [Accessed on 30 August 2020]. Wang C, Pan R, Wan X, Tan Y, Xu L, Ho CS, Ho RC. Immediate Psychological Responses and Associated Factors during the Initial Stage of the 2019 Coronavirus Disease (COVID-19) Epidemic among the General Population in China. Int J Environ Res Public Health. 2020 Mar 6;17(5):1729. https://doi.org/10.3390/ijerph17051729. World Health Organization, WHO Director-General's opening remarks at the media briefing on COVID-19 - 11 March 2020. Available from: https://www.who.int/dg/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---11-march-2020 [Accessed on 13 April 2020] Coronavirus in India: Latest Map and Case Count. Available from: https://www.covid19india.org/ [Accessed 13 April 2020]. Arakal RA. First COVID-19 case in Karnataka: Techie who returned to Bengaluru from US tests positive, (9 March2020). Available from: https://indianexpress.com/article/cities/bangalore/coronavirus-karnataka-first-case-covid-19-bengaluru-6307223/ [Accessed on 13 April 2020] India Today on 24 March 2020. Modi announces lockdown Updates: No panic buying please. Stay indoors, tweets PM. Available from: https://www.indiatoday.in/india/story/pm-modi-address-the-nation-at-8-pm-today-speech-covid-19-coronavirus-live-updates-1659215-2020-03-24 [Accessed on 13 April 2020] Ali Jadoo SA. Was the world ready to face a crisis like COVID-19? Journal of Ideas in Health2020;3(1):123-4. https://doi.org/10.47108/jidhealth.Vol3.Iss1.45 Steptoe A, Shankar A, Demakakos P, Wardle J. Social isolation, loneliness, and all-cause mortality in older men and women. Proc Natl Acad Sci U S A. 2013;110(15):5797-5801. https://doi.org/10.1073/pnas.1219686110 Cao W, Fang Z, Hou G, Han M, Xu X, Dong J, et al. The psychological impact of the COVID-19 epidemic on college students in China. Psychiatry Res. 2020; 287:112934. https://doi.org/10.1016/j.psychres.2020.112934 Taylor HO, Taylor RJ, Nguyen AW, Chatters L. Social Isolation, Depression, and Psychological Distress Among Older Adults. Journal of Aging and Health2018; 30(2): 229–246. https://doi.org/10.1177/0898264316673511 Sim K, Huak Chan Y, Chong PN, Chua HC, Wen Soon S. Psychosocial and coping responses within the community health care setting towards a national outbreak of an infectious disease. J Psychosom Res. 2010;68(2):195-202. https://doi.org/10.1016/j.jpsychores.2009.04.004 Roy D, Tripathy S, Kar SK, Sharma N, Verma SK, Kaushal V. Study of knowledge, attitude, anxiety & perceived mental healthcare need in Indian population during COVID-19 pandemic. Asian J Psychiatr. 2020; 51:102083. https://doi.org/10.1016/j.ajp.2020.102083. Karnataka Population. Available from: http://www.populationu.com/in/karnataka-population [Accessed on 8 April 2020] Sample Size Calculator: Understanding Sample Sizes. Available from: https://www.surveymonkey.com/mp/sample-size-calculator/ [Accessed on 5 March 2020] Toussaint A, Hüsing P, Gumz A, Wingenfeld K, Härter M, Schramm E, Löwe B. Sensitivity to change and minimal clinically important difference of the 7-item generalized anxiety disorder questionnaire (GAD-7). J Affect Disord. 2020; 265:395–401. https://doi.org/10.1016/j.jad.2020.01.032 Williams N. The GAD-7 Questionnaire [Review of the test Generalized anxiety disorder (gad-7) Questionnaire, by R. L. Spitzer]. Occupational Medicine2014; 64(3): 224. https://doi.org/10.1093/occmed/kqt161 Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16(9):606–613. https://doi.org/10.1046/j.1525-1497.2001.016009606. Albert PR. Why is depression more prevalent in women? J Psychiatry Neurosci. 2015;40(4):219-221. https://doi.org/10.1503/jpn.150205 Patten SB, Wang JL, Williams JV, Wang JL, McDonald K, Bulloch ACM. Descriptive epidemiology of major depression in Canada. Can J Psychiatry. 2006; 51:84–90. https://doi.org/10.1177/070674371506000106 Jones C. Student anxiety, depression increasing during school closures, survey finds. EdSorce, 13 May 2020. Available from: https://edsource.org/2020/student-anxiety-depression-increasing-during-school-closures-survey-finds/631224 [Accessed on 29 August 2020]. Frasquilho D, Matos MG, Salonna F, Guerreiro D, Storti CC, Gaspar T, Caldas-de-Almeida JM. Mental health outcomes in times of economic recession: a systematic literature review. BMC Public Health2015; 16:115. https://doi.org/10.1186/s12889-016-2720-y. Ali Jadoo SA. COVID -19 pandemic is a worldwide typical Biopsychosocial crisis. Journal of Ideas in Health2020;3(2):152-4. https://doi.org/10.47108/jidhealth.Vol3.Iss2.58 Prabhu N. Bengaluru urban tops state in per capita income, Kalaburagi last, (20 March 2016). Available from: https://www.thehindu.com/news/cities/bangalore/bengaluru-urban-tops-state-in-per-capita-income-kalaburagi-last/article8376124.ece [Accessed 13 April 2020].
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».