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Network of positive affect and depression in older adults

Title: Network of positive affect and depression in older adults
Authors: Hopkins, EG; Leman, PJ; Cervin, M; Numbers, K; Brodaty, H; Sachdev, PS; Medvedev, ON
Contributors: Patrick J. Leman 0000-0003-1708-029X
Publisher Information: Elsevier
Publication Year: 2025
Collection: Brunel University London: Brunel University Research Archive (BURA)
Subject Terms: positive affect; depression; network analysis; older adults; mental health
Description: Data availability: The data that support the findings of this study are available from the Centre for Healthy Brain Ageing (CHeBA) Research Bank following a standardized request process. Access requests can be directed to CHebaData@unsw.edu.au or to the corresponding author. Data access is restricted due to participant consent terms requiring Older Australian Twins Study (OATS) investigators' review and approval of proposed secondary uses, regardless of data de-identification status. Analysis code in R is available in the supplemental materials at the end of the manuscript. We report all data exclusions, manipulations, measures, and sample size determinations in the Method section. ; Supplementary data are available online at: https://www.sciencedirect.com/science/article/pii/S0165032725019718?via%3Dihub#s0080 . ; Background: Depression in older adults poses significant health challenges, yet the protective role of positive affect remains understudied. This research examined the complex network of positive affect and depression in older adults using advanced network analysis techniques to identify potential targets for intervention. Methods: Bayesian Gaussian Graphical Models and Directed Acyclic Graph modelling were used to analyse associations between ten positive affect variables and depression. Exploratory and confirmatory network analyses ensured stability and node predictability quantified variable influence. Stepwise linear regression confirmed whether specific positive affective variables identified in the networks predicted lower depression scores. Results: Enthusiasm emerged as a key ancestral node with the highest predictability (R2 = 0.65), initiating cascades of positive affect. A primary pathway to depression was identified through feeling active (strength = 1.00, direction = 0.79), with an indirect pathway from feeling enthusiastic via active (strength = 0.98, direction = 0.79) to depression (strength = 1.00, direction = 0.79). Confirmatory longitudinal analysis showed that feeling active and ...
Document Type: article in journal/newspaper
File Description: 1 - 9; Print-Electronic
Language: English
Relation: Journal of Affective Disorders; Article number: 120529; https://bura.brunel.ac.uk/handle/2438/32470; https://doi.org/10.1016/j.jad.2025.120529
DOI: 10.1016/j.jad.2025.120529
Availability: https://bura.brunel.ac.uk/handle/2438/32470; https://doi.org/10.1016/j.jad.2025.120529
Rights: Creative Commons Attribution 4.0 International ; https://creativecommons.org/licenses/by/4.0/ ; https://creativecommons.org/licenses/by/4.0/legalcode.en ; The Authors
Accession Number: edsbas.217C803B
Database: BASE