Using a loneliness measure to screen for risk of mental health problems:: A replication in two nationally-representative cohorts

Timothy Matthews; Bridget Bryan; Andrea Danese; Alan Meehan; Poulton Richie; Louise Arseneault

doi:10.3390/ijerph19031641

Original language	English
Article number	1641
Number of pages	14
Journal	International Journal of Environmental Research and Public Health
Volume	19
Issue number	3
DOIs	https://doi.org/10.3390/ijerph19031641
Accepted/In press	24 Jan 2022
Published	1 Feb 2022
Additional links	Link to publication in Scopus

Bibliographical note

Funding Information: Funding: The E-Risk Study is funded by the UK Medical Research Council (grant G1002190). Additional support was provided by National Institute of Child Health and Human Development (grant HD077482) and by the Jacobs Foundation. The Dunedin Study was supported by the National Institute on Aging (grants AG032282, AG049789, and AG028716) and by the UK Medical Research Council (grant MR/P005918/1). The Dunedin Multidisciplinary Health and Development Research Unit was supported by the New Zealand Health Research Council and New Zealand Ministry of Business, Innovation, and Employment. Timothy Matthews is a British Academy Postdoctoral Fellow. Bridget T. Bryan is supported by a Colt Foundation PhD Fellowship. Andrea Danese is funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. Louise Arseneault is the Mental Health Leadership Fellow for the UK Economic and Social Research Council (ESRC). Our thanks to Professors Terrie E. Moffitt and Avshalom Caspi for providing access to the data used in this study. Funding Information: The E-Risk Study is funded by the UK Medical Research Council (grant G1002190). Additional support was provided by National Institute of Child Health and Human Development (grant HD077482) and by the Jacobs Foundation. The Dunedin Study was supported by the National Institute on Aging (grants AG032282, AG049789, and AG028716) and by the UK Medical Research Council (grant MR/P005918/1). The Dunedin Multidisciplinary Health and Development Research Unit was supported by the New Zealand Health Research Council and New Zealand Ministry of Business, Innovation, and Employment. Timothy Matthews is a British Academy Postdoctoral Fellow. Bridget T. Bryan is supported by a Colt Foundation PhD Fellowship. Andrea Danese is funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. Louise Arseneault is the Mental Health Leadership Fellow for the UK Economic and Social Research Council (ESRC). Our thanks to Professors Terrie E. Moffitt and Avshalom Caspi for providing access to the data used in this study. Publisher Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Abstract

Background: Loneliness co-occurs alongside many mental health problems and is associated with poorer treatment outcomes. It could therefore be a phenomenon of interest to clinicians as an indicator of generalised risk for psychopathology. The present study tested whether a short measure of loneliness can accurately classify individuals who are at increased risk of common mental health problems. Methods: Data were drawn from two nationally representative cohorts: the age-18 wave of the UK-based Environmental Risk (E-Risk) Longitudinal Twin Study and the age-38 wave of the New Zealand-based Dunedin Multidisciplinary Health and Development Study. In both cohorts, loneliness was assessed using the three-item UCLA Loneliness Scale, plus two standalone items about feeling alone and feeling lonely. Outcome measures consisted of diagnoses of depression and anxiety and self-reports of self-harm/suicide attempts, assessed via a structured interview. Results: ROC curve analysis showed that the Loneliness Scale had fair accuracy in classifying individuals meeting criteria for all three outcomes, with a cut-off score of 5 (on a scale from 3 to 9) having the strongest empirical support. Both of the stand-alone items showed modest sensitivity and specificity but were more limited in their flexibility. The findings were replicated across the two cohorts, indicating that they are applicable both to younger and older adults. In addition, the accuracy of the loneliness scale in detecting mental health problems was comparable to a measure of poor sleep quality, a phenomenon which is often included in screening tools for depression and anxiety. Conclusions: These findings indicate that a loneliness measure could have utility in mental health screening contexts, as well as in research.

King's College London

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