A New Social Network Scale for Detecting Depressive Symptoms in Older Japanese Adults.
Int J Environ Res Public Health
; 17(23)2020 11 29.
Article
in English
| MEDLINE | ID: covidwho-948963
ABSTRACT
Social engagement and networking deter depression among older adults. During the COVID-19 pandemic, older adults are especially at risk of isolation from face-to-face and non-face-to-face interactions. We developed the National Center for Geriatrics and Gerontology Social Network Scale (NCGG-SNS) to assess frequency of, and satisfaction with, social interactions. The NCGG-SNS consists of four domains face-to-face/non-face-to-face interactions with family/friends. Each domain score is obtained by multiplying frequency ratings by satisfaction ratings for each item; all scores were summed to obtain a total NCGG-SNS score (range 0-64). Additionally, face-to-face and non-face-to-face subscores were calculated. Higher scores indicated satisfactory social networking. A cohort of 2445 older Japanese adults completed the NCGG-SNS and the Geriatrics Depression Scale-Short form. Receiver Operating Characteristic (ROC) analysis and logistic regression determined predictive validity for depressive symptoms. Depressive symptoms were reported by 284 participants (11.6%). The optimal NCGG-SNS cut-off value to identify depressive symptoms was 26.5 points. In logistic regression analysis adjusted for potential confounders, lower NCGG-SNS values were significantly associated with greater prevalence of depressive symptoms. Face-to-face and non-face-to-face subscores were associated with depressive symptoms. The NCGG-SNS is a valid and useful indicator of multidimensional social networking enabling identification of depressive symptoms in older adults.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Depression
/
Social Networking
Type of study:
Cohort study
/
Diagnostic study
/
Observational study
/
Prognostic study
Limits:
Aged
/
Humans
Country/Region as subject:
Asia
Language:
English
Year:
2020
Document Type:
Article
Affiliation country:
Ijerph17238874
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