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Assessing the relative importance of correlates of loneliness in later life. Gaining insight using recursive partitioning

Ejlskov, L; Wulff, J; Bøggild, H; Kuh, D; Stafford, M; (2017) Assessing the relative importance of correlates of loneliness in later life. Gaining insight using recursive partitioning. Aging & Mental Health pp. 1-8. 10.1080/13607863.2017.1370690. (In press). Green open access

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Abstract

OBJECTIVES: Improving the design and targeting of interventions is important for alleviating loneliness among older adults. This requires identifying which correlates are the most important predictors of loneliness. This study demonstrates the use of recursive partitioning in exploring the characteristics and assessing the relative importance of correlates of loneliness in older adults. METHOD: Using exploratory regression trees and random forests, we examined combinations and the relative importance of 42 correlates in relation to loneliness at age 68 among 2453 participants from the birth cohort study the MRC National Survey of Health and Development. RESULTS: Positive mental well-being, personal mastery, identifying the spouse as the closest confidant, being extrovert and informal social contact were the most important correlates of lower loneliness levels. Participation in organised groups and demographic correlates were poor identifiers of loneliness. The regression tree suggested that loneliness was not raised among those with poor mental wellbeing if they identified their partner as closest confidante and had frequent social contact. CONCLUSION: Recursive partitioning can identify which combinations of experiences and circumstances characterise high-risk groups. Poor mental wellbeing and sparse social contact emerged as especially important and classical demographic factors as insufficient in identifying high loneliness levels among older adults.

Type: Article
Title: Assessing the relative importance of correlates of loneliness in later life. Gaining insight using recursive partitioning
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1080/13607863.2017.1370690
Publisher version: http://dx.doi.org/10.1080/13607863.2017.1370690
Language: English
Additional information: © 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.
Keywords: Loneliness, psycho-social interventions, random forest, recursive partitioning, regression trees
UCL classification: UCL > School of Life and Medical Sciences
UCL > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science
URI: http://discovery.ucl.ac.uk/id/eprint/1573274
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