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Published on: February 22, 2018
[Loneliness in unemployed individuals diagnosed with mental illness]
Felix S Hussenoeder1, Maria Koschig2, Ines Conrad2
1Institut für Sozialmedizin, Arbeitsmedizin und Public Health, Medizinische Fakultät, Universität Leipzig, Philipp-Rosenthal-Str. 55, 04103, Leipzig, Deutschland. Felix.Hussenoeder@medizin.uni-leipzig.de.
Background:
Loneliness is a widespread phenomenon, and it is associated with a variety of health problems and diseases. Unemployed individuals diagnosed with a mental illness (UMIs) are at a high risk of experiencing loneliness, with serious repercussions for their health and vocational rehabilitation. With this study we wanted to better understand the associations between sociodemographic variables, mental health, and loneliness in UMIs.
Methods:
We analyzed the data of 526 unemployed individuals that received means-tested benefits as well as at least one psychiatric diagnosis. Data were collected between September 2020 and September 2023. We conducted two robust regressions with loneliness (University of California, Los Angeles, Loneliness Scale, UCLA) as an outcome (N = 526). In the first regression, we used social network as a predictor (Lubben Social Network Scale, LSNS-6); in the second regression we included the additional predictors personal debt (yes/no), depression (Patient Health Questionnaire, PHQ-9), anxiety (Mini-Symptom-Checklist,MSCL), and somatization (MSCL) as well as age, gender, education, and living with a partner as control variables.
Results:
We found a significant negative association between social network and loneliness, and a significant positive association between a high level of education, depression, anxiety, and loneliness.
Conclusions:
Unemployed individuals diagnosed with a mental illness in our sample exhibited high levels of depression, anxiety, somatization, and loneliness. The associations between social network, mental health, and loneliness that we found emphasize the importance of psychological screening and/or diagnostics, and they highlight areas for prevention.
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