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Tancredi S, van der Linden BWA, Chiolero A, Cullati S, Imboden M, Probst-Hensch N, Keidel D, Witzig M, Dratva J, Michel G, Harju E, Frank I, Lorthe E, Baysson H, Stringhini S, Kahlert CR, Bardoczi JB, Haller ML, Chocano-Bedoya PO, Rodondi N, Amati R, Albanese E, Corna L, Crivelli L, Kaufmann M, Frei A, von Wyl V. Socioeconomic Status and Adherence to Preventive Measures During the COVID-19 Pandemic in Switzerland: A Population Based Digital Cohort Analysis. Int J Public Health 2024; 69:1606861. [PMID: 39022447 PMCID: PMC11251880 DOI: 10.3389/ijph.2024.1606861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 06/12/2024] [Indexed: 07/20/2024] Open
Abstract
Objectives To assess the association between socioeconomic status (SES) and self-reported adherence to preventive measures in Switzerland during the COVID-19 pandemic. Methods 4,299 participants from a digital cohort were followed between September 2020 and November 2021. Baseline equivalised disposable income and education were used as SES proxies. Adherence was assessed over time. We investigated the association between SES and adherence using multivariable mixed logistic regression, stratifying by age (below/above 65 years) and two periods (before/after June 2021, to account for changes in vaccine coverage and epidemiological situation). Results Adherence was high across all SES strata before June 2021. After, participants with higher equivalised disposable income were less likely to adhere to preventive measures compared to participants in the first (low) quartile [second (Adj.OR, 95% CI) (0.56, 0.37-0.85), third (0.38, 0.23-0.64), fourth (0.60, 0.36-0.98)]. We observed similar results for education. Conclusion No differences by SES were found during the period with high SARS-CoV-2 incidence rates and stringent measures. Following the broad availability of vaccines, lower incidence, and eased measures, differences by SES started to emerge. Our study highlights the need for contextual interpretation when assessing SES impact on adherence to preventive measures.
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Affiliation(s)
- Stefano Tancredi
- Population Health Laboratory (#PopHealthLab), University of Fribourg, Fribourg, Switzerland
| | | | - Arnaud Chiolero
- Population Health Laboratory (#PopHealthLab), University of Fribourg, Fribourg, Switzerland
- School of Population and Global Health, Faculty of Medicine and Health Sciences, McGill University, Montreal, Canada
- Institute of Primary Healthcare (BIHAM), University of Bern, Bern, Switzerland
| | - Stéphane Cullati
- Population Health Laboratory (#PopHealthLab), University of Fribourg, Fribourg, Switzerland
- Quality of Care Service, Geneva University Hospitals, Geneva, Switzerland
| | - Medea Imboden
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Nicole Probst-Hensch
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Dirk Keidel
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Melissa Witzig
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Julia Dratva
- University of Basel, Basel, Switzerland
- Zurich University of Applied Sciences, Winterthur, Switzerland
| | - Gisela Michel
- Faculty of Health Sciences and Medicine, University of Lucerne, Lucerne, Switzerland
| | - Erika Harju
- Faculty of Health Sciences and Medicine, University of Lucerne, Lucerne, Switzerland
- School of Health Sciences, ZHAW Zurich University of Applied Sciences, Winterthur, Switzerland
| | - Irene Frank
- Clinical Trial Unit, Cantonal Hospital Lucerne, Lucerne, Switzerland
| | - Elsa Lorthe
- Unit of Population Epidemiology, Division of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland
- Université Paris Cité, INSERM, INRAE, Centre for Research in Epidemiology and Statistics Paris (CRESS), Paris, France
| | - Hélène Baysson
- Unit of Population Epidemiology, Division of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Silvia Stringhini
- Unit of Population Epidemiology, Division of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland
- Department of Health and Community Medicine, Faculty of Medicine, University of Geneva, Geneva, Switzerland
- University Center of General Medicine and Public Health, Lausanne, Switzerland
- School of Population and Public Health, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - Christian R. Kahlert
- Cantonal Hospital St Gallen, Division of Infectious Diseases and Hospital Epidemiology, St Gallen, Switzerland
- Children’s Hospital of Eastern Switzerland, Department of Infectious Diseases and Hospital Epidemiology, St Gallen, Switzerland
| | - Julia B. Bardoczi
- Institute of Primary Healthcare (BIHAM), University of Bern, Bern, Switzerland
- Department of General Internal Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Moa Lina Haller
- Institute of Primary Healthcare (BIHAM), University of Bern, Bern, Switzerland
| | | | - Nicolas Rodondi
- Institute of Primary Healthcare (BIHAM), University of Bern, Bern, Switzerland
- Department of General Internal Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Rebecca Amati
- Institute of Public Health, Faculty of Biomedical Sciences, Università della Svizzera italiana, Lugano, Switzerland
| | - Emiliano Albanese
- Institute of Public Health, Faculty of Biomedical Sciences, Università della Svizzera italiana, Lugano, Switzerland
| | - Laurie Corna
- Department of Business Economics, Health and Social Care, University of Applied Sciences and Arts of Southern Switzerland, Manno, Switzerland
| | - Luca Crivelli
- Institute of Public Health, Faculty of Biomedical Sciences, Università della Svizzera italiana, Lugano, Switzerland
- Department of Business Economics, Health and Social Care, University of Applied Sciences and Arts of Southern Switzerland, Manno, Switzerland
| | - Marco Kaufmann
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Anja Frei
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Viktor von Wyl
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
- Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
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Lee N, Kim HR. Nursing Students' Perceptions of Factors Influencing Nursing Intentions toward COVID-19 Patients. Healthcare (Basel) 2024; 12:285. [PMID: 38338170 PMCID: PMC10855262 DOI: 10.3390/healthcare12030285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 01/08/2024] [Accepted: 01/21/2024] [Indexed: 02/12/2024] Open
Abstract
Coronavirus disease (COVID-19) is a pandemic to which nursing students are particularly susceptible. This study aims to comprehensively examine nursing students' knowledge, attitudes, risk perceptions, preventive behaviors related to COVID-19, and nursing intentions toward patients with the virus. A questionnaire was administered to 149 nursing students from two universities. Data on the respondents' general characteristics, knowledge levels, attitudes, perceived risk, preventive behaviors toward COVID-19, and nursing intentions toward COVID-19 patients were collected. The collected data were statistically analyzed using SPSS software (version 26.0). This involved descriptive statistics, independent t-tests, one-way ANOVA, Pearson's correlation coefficient, and stepwise multiple regression analyses. The analyses of the factors affecting nursing students' nursing intentions for COVID-19 patients showed that the most predictive factor was perceived risk (β = -0.38, p < 0.001), followed by attitudes (β = 0.29, p < 0.001) and preventive behaviors (β = 0.17, p = 0.017), which explained 26% of the variance in nursing intentions. Lowering the perceived risk of infectious diseases and cultivating positive attitudes and preventive behaviors can increase nursing students' intentions toward COVID-19 patients. Finally, infection management education programs and research on interventions for nursing students are necessary to enhance the quality of nursing care provided to patients with novel infectious diseases.
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Affiliation(s)
- Nari Lee
- Chosun University Hospital, Gwangju 61453, Republic of Korea;
| | - Hae Ran Kim
- Department of Nursing, College of Medicine, Chosun University, Gwangju 61452, Republic of Korea
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