Comparison of networks of loneliness, depressive symptoms, and anxiety symptoms in at-risk community-dwelling older adults before and during COVID-19.
Sci Rep
; 14(1): 14737, 2024 06 26.
Article
en En
| MEDLINE
| ID: mdl-38926445
ABSTRACT
Network analysis provides an innovative approach to examining symptom-to-symptom interactions in mental health, and adverse external conditions may change the network structures. This study compared the networks of common risk factors and mental health problems (loneliness, depressive symptoms, and anxiety symptoms) in community-dwelling older people before and during COVID-19. Older adults (aged ≥ 60) at risk for depression were recruited through non-governmental organizations. Loneliness, depressive symptoms and anxiety symptoms were measured using the three-item Loneliness Scale (UCLA-3), nine-item Patient Health Questionnaire (PHQ-9), and seven-item Generalized Anxiety Disorder Scale (GAD-7), respectively. Data from 2549 (before) and 3506 (during COVID-19) respondents were included using propensity score matching. Being restless (GAD-7-item5) was most central, indicated by Expected Influence, in both pre and during COVID-19 networks despite low severity (mean score). The network during COVID-19 had higher global strength and edge variability than the pre-pandemic network, suggesting easier symptom spread and potentially more complex symptom presentation. In addition, feeling isolated from others (UCLA-3-item3) had stronger connections with feeling worthless/guilty (PHQ-9-item6) and anticipatory anxiety (GAD-7-item7) during COVID-19 than before. These findings may enhance our knowledge of the symptom structure of common mental health problems and the impacts of the pandemic. Targeting central symptoms may offer novel preventive strategies for older people.
Texto completo:
1
Base de datos:
MEDLINE
Asunto principal:
Ansiedad
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Depresión
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Vida Independiente
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COVID-19
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Soledad
Límite:
Aged
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Aged80
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Revista:
Sci Rep
Año:
2024
Tipo del documento:
Article
País de afiliación:
China