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Vo TKN, Skokauskas N, Cheslack-Postava K, Hoven CW. The relationship between safety measures, preparedness, and mental health outcomes in New York City during the COVID-19 pandemic. Front Psychiatry 2025; 16:1547178. [PMID: 40270571 PMCID: PMC12014668 DOI: 10.3389/fpsyt.2025.1547178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2024] [Accepted: 03/21/2025] [Indexed: 04/25/2025] Open
Abstract
Background The COVID-19 pandemic necessitated strict safety measures and preparedness, potentially influencing mental well-being worldwide. This study investigated the impact of safety measures and preparedness levels on mental health outcomes during the COVID-19 pandemic in New York City, USA examining how sociodemographic characteristics modified these associations. Method A longitudinal study of 1,227 participants from three ongoing cohorts, provided data through telephone interviews across three waves from March 2020 to August 2021. Depression and anxiety were measured using Patient Health Questionnaire 8 (PHQ-8) and Generalized Anxiety Disorder 7 (GAD-7). Logistic regression models were used to investigate associations between safety measures, preparedness, and mental health outcomes over time, adjusting for potential confounders and assessing the modification effect of demographic factors. Results At Wave 1, 18% of participants reported moderate to severe depression, while 20% had moderate to severe anxiety. Over time, these rates declined significantly, with depression dropping to 9% and anxiety to 10% by Wave 3. Safety measures practiced at Wave 1 showed a protective effect on depression at Wave 3 (OR=0.45, 95% CI: 0.22, 0.91). Higher preparedness levels were significantly associated with reduced odds of anxiety (aOR=0.72, 95% CI: 0.55, 0.93) in the concurrent wave. Age specific analysis revealed that individuals aged 26-35 experienced stronger protective effects from higher preparedness levels (OR=0.43, 95% CI: 0.2, 0.92) compared to younger age groups. Conclusion This study highlights the importance of safety measures and preparedness in mitigating mental health challenges during crises. Addressing age specific factors and preparedness levels can guide the public health strategies to better support diverse populations.
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Affiliation(s)
- Thi Kim Ngan Vo
- Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Norbert Skokauskas
- Regional Centre for Child and Youth Mental Health and Child Welfare, Department of Mental Health (IPH), NTNU, Trondheim, Norway
| | - Keely Cheslack-Postava
- Global Psychiatric Epidemiology Group, Division of Child and Adolescent Psychiatry, Department of Psychiatry, Columbia University-New York State Psychiatric Institute, New York, NY, United States
| | - Christina W. Hoven
- Global Psychiatric Epidemiology Group, Division of Child and Adolescent Psychiatry, Department of Psychiatry, Columbia University-New York State Psychiatric Institute, New York, NY, United States
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, United States
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van Kessel R, Seghers LE, Anderson M, Schutte NM, Monti G, Haig M, Schmidt J, Wharton G, Roman-Urrestarazu A, Larrain B, Sapanel Y, Stüwe L, Bourbonneux A, Yoon J, Lee M, Paccoud I, Borga L, Ndili N, Sutherland E, Görgens M, Weicken E, Coder M, de Fatima Marin H, Val E, Profili MC, Kosinska M, Browne CE, Marcelo A, Agarwal S, Mrazek MF, Eskandar H, Chestnov R, Smelyanskaya M, Källander K, Buttigieg S, Ramesh K, Holly L, Rys A, Azzopardi-Muscat N, de Barros J, Quintana Y, Spina A, Hyder AA, Labrique A, Kamel Boulos MN, Chen W, Agrawal A, Cho J, Klucken J, Prainsack B, Balicer R, Kickbusch I, Novillo-Ortiz D, Mossialos E. A scoping review and expert consensus on digital determinants of health. Bull World Health Organ 2025; 103:110-125H. [PMID: 39882497 PMCID: PMC11774227 DOI: 10.2471/blt.24.292057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2024] [Revised: 10/01/2024] [Accepted: 10/02/2024] [Indexed: 01/31/2025] Open
Abstract
Objective To map how social, commercial, political and digital determinants of health have changed or emerged during the recent digital transformation of society and to identify priority areas for policy action. Methods We systematically searched MEDLINE, Embase and Web of Science on 24 September 2023, to identify eligible reviews published in 2018 and later. To ensure we included the most recent literature, we supplemented our review with non-systematic searches in PubMed® and Google Scholar, along with records identified by subject matter experts. Using thematic analysis, we clustered the extracted data into five societal domains affected by digitalization. The clustering also informed a novel framework, which the authors and contributors reviewed for comprehensiveness and accuracy. Using a two-round consensus process, we rated the identified determinants into high, moderate and low urgency for policy actions. Findings We identified 13 804 records, of which 204 met the inclusion criteria. A total of 127 health determinants were found to have emerged or changed during the digital transformation of society (37 digital, 33 social, 33 commercial and economic and 24 political determinants). Of these, 30 determinants (23.6%) were considered particularly urgent for policy action. Conclusion This review offers a comprehensive overview of health determinants across digital, social, commercial and economic, and political domains, highlighting how policy decisions, individual behaviours and broader factors influence health by digitalization. The findings deepen our understanding of how health outcomes manifest within a digital ecosystem and inform strategies for addressing the complex and evolving networks of health determinants.
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Affiliation(s)
- Robin van Kessel
- LSE Health, Department of Health Policy, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, London, England
| | - Laure-Elise Seghers
- LSE Health, Department of Health Policy, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, London, England
| | - Michael Anderson
- LSE Health, Department of Health Policy, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, London, England
| | - Nienke M Schutte
- Innovation in Health Information Systems Unit, Sciensano, Brussels, Belgium
| | - Giovanni Monti
- LSE Health, Department of Health Policy, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, London, England
| | - Madeleine Haig
- LSE Health, Department of Health Policy, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, London, England
| | - Jelena Schmidt
- Department of International Health, Maastricht University, Maastricht, Kingdom of the Netherlands
| | - George Wharton
- LSE Health, Department of Health Policy, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, London, England
| | | | - Blanca Larrain
- Department of Psychiatry, University of Cambridge, Cambridge, England
| | - Yoann Sapanel
- Institute of Digital Medicine, National University of Singapore, Singapore
| | - Louisa Stüwe
- Digital Health Delegation for Digital Health, Ministry of Labour, Health and Solidarities, Paris, France
| | - Agathe Bourbonneux
- Digital Health Delegation for Digital Health, Ministry of Labour, Health and Solidarities, Paris, France
| | - Junghee Yoon
- Department of Clinical Research Design and Evaluation, Sungkyunkwan University, Seoul, Republic of Korea
| | - Mangyeong Lee
- Department of Clinical Research Design and Evaluation, Sungkyunkwan University, Seoul, Republic of Korea
| | - Ivana Paccoud
- Luxembourg Centre for Systems Biomedicine, Université du Luxembourg, Belvaux, Luxembourg
| | - Liyousew Borga
- Luxembourg Centre for Systems Biomedicine, Université du Luxembourg, Belvaux, Luxembourg
| | - Njide Ndili
- PharmAccess Foundation Nigeria, Lagos, Nigeria
| | | | - Marelize Görgens
- Health, Nutrition and Population Global Practice, World Bank Group, WashingtonDC, United States of America (USA)
| | - Eva Weicken
- Fraunhofer Institute for Telecommunications, Heinrich Hertz Institut, Berlin, Germany
| | | | - Heimar de Fatima Marin
- Department of Biomedical and Data Science, Yale University School of Medicine, New Haven, USA
| | - Elena Val
- Migration Health Division, International Organization for Migration Regional Office for the European Economic Area, the EU and NATO, Brussels, Belgium
| | - Maria Cristina Profili
- Migration Health Division, International Organization for Migration Regional Office for the European Economic Area, the EU and NATO, Brussels, Belgium
| | - Monika Kosinska
- Department of Social Determinants of Health, World Health Organization, Geneva, Switzerland
| | | | - Alvin Marcelo
- Medical Informatics Unit, University of the Philippines, Manila, Philippines
| | - Smisha Agarwal
- Department of International Health, The Johns Hopkins University Bloomberg School of Public Health, Baltimore, USA
| | - Monique F. Mrazek
- International Finance Corporation, World Bank Group, WashingtonDC, USA
| | - Hani Eskandar
- Digital Services Division, International Telecommunications Union, Geneva, Switzerland
| | - Roman Chestnov
- Digital Services Division, International Telecommunications Union, Geneva, Switzerland
| | - Marina Smelyanskaya
- HIV and Health Group, United Nations Development Programme Europe and Central Asia, Istanbul, Türkiye
| | | | | | | | - Louise Holly
- Digital Transformations for Health Lab, Geneva, Switzerland
| | - Andrzej Rys
- Health Systems, Medical Products and Innovation, European Commission, Brussels, Belgium
| | - Natasha Azzopardi-Muscat
- LSE Health, Department of Health Policy, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, London, England
- Innovation in Health Information Systems Unit, Sciensano, Brussels, Belgium
| | - Jerome de Barros
- LSE Health, Department of Health Policy, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, London, England
- Department of International Health, Maastricht University, Maastricht, Kingdom of the Netherlands
| | - Yuri Quintana
- LSE Health, Department of Health Policy, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, London, England
- Department of Psychiatry, University of Cambridge, Cambridge, England
| | - Antonio Spina
- LSE Health, Department of Health Policy, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, London, England
- Institute of Digital Medicine, National University of Singapore, Singapore
| | - Adnan A Hyder
- LSE Health, Department of Health Policy, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, London, England
- Digital Health Delegation for Digital Health, Ministry of Labour, Health and Solidarities, Paris, France
| | - Alain Labrique
- LSE Health, Department of Health Policy, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, London, England
- Department of Clinical Research Design and Evaluation, Sungkyunkwan University, Seoul, Republic of Korea
| | - Maged N Kamel Boulos
- LSE Health, Department of Health Policy, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, London, England
- Luxembourg Centre for Systems Biomedicine, Université du Luxembourg, Belvaux, Luxembourg
| | - Wen Chen
- LSE Health, Department of Health Policy, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, London, England
- PharmAccess Foundation Nigeria, Lagos, Nigeria
| | - Anurag Agrawal
- LSE Health, Department of Health Policy, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, London, England
- Paris, France
| | - Juhee Cho
- Department of Clinical Research Design and Evaluation, Sungkyunkwan University, Seoul, Republic of Korea
| | - Jochen Klucken
- Luxembourg Centre for Systems Biomedicine, Université du Luxembourg, Belvaux, Luxembourg
| | - Barbara Prainsack
- LSE Health, Department of Health Policy, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, London, England
- Health, Nutrition and Population Global Practice, World Bank Group, WashingtonDC, United States of America (USA)
| | - Ran Balicer
- LSE Health, Department of Health Policy, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, London, England
- Fraunhofer Institute for Telecommunications, Heinrich Hertz Institut, Berlin, Germany
| | | | - David Novillo-Ortiz
- LSE Health, Department of Health Policy, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, London, England
- Innovation in Health Information Systems Unit, Sciensano, Brussels, Belgium
| | - Elias Mossialos
- LSE Health, Department of Health Policy, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, London, England
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Basu S, Desai M, Karan A, Bhardwaj S, Negandhi H, Jadhav N, Maske A, Zodpey S. COVID-19 Resilience and Risk Reduction Intervention in Rural Populations of Western India: Retrospective Evaluation. JMIR Public Health Surveill 2024; 10:e47520. [PMID: 39073851 PMCID: PMC11319881 DOI: 10.2196/47520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 04/28/2024] [Accepted: 05/28/2024] [Indexed: 07/30/2024] Open
Abstract
BACKGROUND Globally, especially in the low- and middle-income countries (LMICs), rural populations were more susceptible to the negative impact of the COVID-19 pandemic due to lower levels of community awareness, poor hygiene, and health literacy accompanying pre-existing weak public health systems. Consequently, various community-based interventions were engineered in rural regions worldwide to mitigate the COVID-19 pandemic by empowering people to mount both individual and collective public health responses against the pandemic. However, to date, there is paucity of information on the effectiveness of any large-scale community intervention in controlling and mitigating the effects of COVID-19, especially from the perspective of LMICs. OBJECTIVE This retrospective impact evaluation study was conducted to evaluate the effect of a large-scale rural community-based intervention, the COVID-Free Village Program (CFVP), on COVID-19 resilience and control in rural populations in Maharashtra, India. METHODS The intervention site was the rural areas of the Pune district where CFVP was implemented from August 2021 to February 2022, while the adjoining district, Satara, represented the control district where the COVID-Free Village Scheme was implemented. Data were collected during April-May 2022 from 3500 sample households in villages across intervention and comparison arms by using the 2-stage stratified random sampling through face-to-face interviews followed by developing a matched sample using propensity score matching methods. RESULTS The participants in Pune had a significantly higher combined COVID-19 awareness index by 0.43 (95% CI 0.29-0.58) points than those in Satara. Furthermore, the adherence to COVID-appropriate behaviors, including handwashing, was 23% (95% CI 3%-45%) and masking was 17% (0%-38%) higher in Pune compared to those in Satara. The probability of perception of COVID as a serious illness in patients with heart disease was 22% (95% CI 1.036-1.439) higher in Pune compared to that in Satara. The awareness index of COVID-19 variants and preventive measures were also higher in Pune by 0.88 (95% CI 0.674-1.089) points. In the subgroup analysis, when the highest household educational level was restricted to middle school, the awareness about the COVID-control program was 0.69 (95% CI 0.36-1.021) points higher in Pune, while the awareness index of COVID-19 variants and preventive measures was higher by 0.45 (95% CI 0.236-0.671) points. We did not observe any significant changes in the overall COVID-19 vaccination coverage due to CFVP implementation. Furthermore, the number of COVID-19 deaths in both the sampled populations were very low. The probability of observing COVID-19-related stigma or discrimination in Pune was 68% (95% CI 0.133-0.191) lower than that in Satara. CONCLUSIONS CFVP contributed to improved awareness and sustainability of COVID-appropriate behaviors in a large population although there was no evidence of higher COVID-19 vaccination coverage or reduction in mortality, signifying potential applicability in future pandemic preparedness, especially in resource-constrained settings.
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Affiliation(s)
- Saurav Basu
- Indian Institute of Public Health-Delhi, Public Health Foundation of India, Gurugram, India
| | - Meghana Desai
- Department of Monitoring, Evaluation, and Learning, Bharatiya Jain Sangathana, Shantilal Muttha Foundation, Pune, India
| | - Anup Karan
- Indian Institute of Public Health-Delhi, Public Health Foundation of India, Gurugram, India
| | - Surbhi Bhardwaj
- Indian Institute of Public Health-Delhi, Public Health Foundation of India, Gurugram, India
| | - Himanshu Negandhi
- Indian Institute of Public Health-Delhi, Public Health Foundation of India, Gurugram, India
| | - Nitin Jadhav
- Department of Monitoring, Evaluation, and Learning, Bharatiya Jain Sangathana, Shantilal Muttha Foundation, Pune, India
| | - Amar Maske
- Department of Monitoring, Evaluation, and Learning, Bharatiya Jain Sangathana, Shantilal Muttha Foundation, Pune, India
| | - Sanjay Zodpey
- Indian Institute of Public Health-Delhi, Public Health Foundation of India, Gurugram, India
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