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Article: Sad Mood Bridges Depressive Symptoms and Cognitive Performance in Community-Dwelling Older Adults: A Network Approach
Title | Sad Mood Bridges Depressive Symptoms and Cognitive Performance in Community-Dwelling Older Adults: A Network Approach |
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Authors | |
Keywords | Cognition Depressive symptoms Mental health Network analysis Quantitative research methods |
Issue Date | 29-Dec-2023 |
Publisher | Oxford University Press |
Citation | Innovation in Aging, 2023, v. 8, n. 1 How to Cite? |
Abstract | Background and Objectives: Depression and cognitive impairment are common and often coexist in older adults. The network theory of mental disorders provides a novel approach to understanding the pathways between depressive symptoms and cognitive domains and the potential "bridge"that links and perpetuates both conditions. This study aimed to identify pathways and bridge symptoms between depressive symptoms and cognitive domains in older adults. Research Design and Methods: Data were derived from 2,792 older adults aged 60 years and older with mild and more severe depressive symptoms from the community in Hong Kong. Depressive symptoms were assessed using the Patient Health Questionnaire (PHQ-9) and cognition using the Montreal Cognitive Assessment 5-minute protocol (MoCA-5min). Summary descriptive statistics were calculated, followed by network estimation using graphical LASSO, community detection, centrality analysis using bridge expected influence (BEI), and network stability analyses to assess the structure of the PHQ-9 and MoCA-5min items network, the pathways, and the bridge symptoms. Results: Participants (mean age = 77.3 years, SD = 8.5) scored 8.2 (SD = 3.4) on PHQ-9 and 20.3 (SD = 5.4) on MoCA-5min. Three independent communities were identified in PHQ-9 and MoCA-5min items, suggesting that depression is not a uniform entity (2 communities) and has differential connections with cognition. The network estimation results suggested that the 2 most prominent connections between depressive symptoms and cognitive domains were: (1) anhedonia with executive functions/language and (2) sad mood with memory. Among all depressive symptoms, sad mood had the highest BEI, bridging depressive symptoms and cognitive domains. Discussion and Implications: Sad mood seems to be the pathway between depression and cognition in this sample of older Chinese. This finding highlights the importance of sad mood as a potential mechanism for the co-occurrence of depression and cognitive impairment, implying that intervention targeting sad mood might have rippling effects on cognitive health. |
Persistent Identifier | http://hdl.handle.net/10722/345888 |
ISSN | 2023 Impact Factor: 4.9 2023 SCImago Journal Rankings: 1.052 |
DC Field | Value | Language |
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dc.contributor.author | Zhang, Wen | - |
dc.contributor.author | Liu, Tianyin | - |
dc.contributor.author | Leung, Dara Kiu Yi | - |
dc.contributor.author | Chan, Stephen | - |
dc.contributor.author | Wong, Gloria | - |
dc.contributor.author | Lum, Terry | - |
dc.date.accessioned | 2024-09-04T07:06:16Z | - |
dc.date.available | 2024-09-04T07:06:16Z | - |
dc.date.issued | 2023-12-29 | - |
dc.identifier.citation | Innovation in Aging, 2023, v. 8, n. 1 | - |
dc.identifier.issn | 2399-5300 | - |
dc.identifier.uri | http://hdl.handle.net/10722/345888 | - |
dc.description.abstract | Background and Objectives: Depression and cognitive impairment are common and often coexist in older adults. The network theory of mental disorders provides a novel approach to understanding the pathways between depressive symptoms and cognitive domains and the potential "bridge"that links and perpetuates both conditions. This study aimed to identify pathways and bridge symptoms between depressive symptoms and cognitive domains in older adults. Research Design and Methods: Data were derived from 2,792 older adults aged 60 years and older with mild and more severe depressive symptoms from the community in Hong Kong. Depressive symptoms were assessed using the Patient Health Questionnaire (PHQ-9) and cognition using the Montreal Cognitive Assessment 5-minute protocol (MoCA-5min). Summary descriptive statistics were calculated, followed by network estimation using graphical LASSO, community detection, centrality analysis using bridge expected influence (BEI), and network stability analyses to assess the structure of the PHQ-9 and MoCA-5min items network, the pathways, and the bridge symptoms. Results: Participants (mean age = 77.3 years, SD = 8.5) scored 8.2 (SD = 3.4) on PHQ-9 and 20.3 (SD = 5.4) on MoCA-5min. Three independent communities were identified in PHQ-9 and MoCA-5min items, suggesting that depression is not a uniform entity (2 communities) and has differential connections with cognition. The network estimation results suggested that the 2 most prominent connections between depressive symptoms and cognitive domains were: (1) anhedonia with executive functions/language and (2) sad mood with memory. Among all depressive symptoms, sad mood had the highest BEI, bridging depressive symptoms and cognitive domains. Discussion and Implications: Sad mood seems to be the pathway between depression and cognition in this sample of older Chinese. This finding highlights the importance of sad mood as a potential mechanism for the co-occurrence of depression and cognitive impairment, implying that intervention targeting sad mood might have rippling effects on cognitive health. | - |
dc.language | eng | - |
dc.publisher | Oxford University Press | - |
dc.relation.ispartof | Innovation in Aging | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Cognition | - |
dc.subject | Depressive symptoms | - |
dc.subject | Mental health | - |
dc.subject | Network analysis | - |
dc.subject | Quantitative research methods | - |
dc.title | Sad Mood Bridges Depressive Symptoms and Cognitive Performance in Community-Dwelling Older Adults: A Network Approach | - |
dc.type | Article | - |
dc.identifier.doi | 10.1093/geroni/igad139 | - |
dc.identifier.scopus | eid_2-s2.0-85187263720 | - |
dc.identifier.volume | 8 | - |
dc.identifier.issue | 1 | - |
dc.identifier.eissn | 2399-5300 | - |
dc.identifier.issnl | 2399-5300 | - |