Abstract
High risk of mental health problems is associated with loneliness resulting from social distancing measures and “lockdowns” that have been imposed globally due to the COVID‐19 pandemic. This study explores the interconnectedness of loneliness, anxiety and depression on a symptom level using network analysis. A representative sample of participants (N = 1041), who were of at least 18 years of age, was recruited from the Republic of Ireland (ROI). Loneliness, anxiety and depression were assessed using validated instruments. Network analysis was used to identify the network structure of loneliness, anxiety and depression. Loneliness was found to be largely isolated from anxiety and depression nodes in the network. Anxiety and depression were largely interconnected. “Trouble relaxing,” “feeling bad about oneself” and “not being able to stop or control worrying” were suggested as the most influential nodes of the network. Despite the expectation that loneliness would be implicated more robustly in the anxiety and depression network of symptoms, the results suggest loneliness as a distinct construct that is not interwoven with anxiety and depression.
| Original language | English |
|---|---|
| Pages (from-to) | 585-596 |
| Number of pages | 12 |
| Journal | International Journal of Psychology |
| Volume | 57 |
| Issue number | 5 |
| Early online date | 6 May 2022 |
| DOIs | |
| Publication status | Published (in print/issue) - 31 Oct 2022 |
Bibliographical note
Funding Information:The results of this study found that loneliness existed as a distinct construct that is more distant to anxiety and depression than the two disorders are to each other. This has been supported by the results from the Clique Percolation, by examining closeness centrality and by examining bridge centrality. Studies have demonstrated that bridge symptoms are implicated in the emergence of comorbidity structures between mental disorders (Cramer et al., 2010 ). Targeting central and bridge symptoms might constitute a focal point of therapies, as they are suggested to accelerate the development of network interactions between symptoms (Borsboom, 2017 ). Jones et al. ( 2019 ) found that deactivating bridging symptoms was more effective for preventing symptom activation, suggesting that bridging symptoms are implicated in the cascade of symptom activation. Bridge centrality for loneliness was low, there was no indication of significant “bridge symptoms” from loneliness to anxiety or depression in the network analysis—meaning symptoms of loneliness did not have strong direct connections to other neighbouring symptoms or clusters of anxiety and depression. This suggests that loneliness symptoms do not share any common symptoms with anxiety or depression, nor affect these disorders strongly, thus is a distinct disorder (Borsboom, 2017 ). Further examining bridge EI suggests that GAD6 (“Becoming easily annoyed or irritable”) and PHQ2 (“Feeling down depressed or hopeless”) were highly influential. Given that, one has to consider that the psychological interventions are not “surgical” tools being able to affect only one of the symptoms in a network. Rather, these interventions are performed using verbal communication or visual and auditory stimuli and as such, and in the foreseeable future, affecting only one psychological symptom is unrealistic (Eronen, 2020 ). However, the present study can be used as a guide when considering the impact and trajectory of these changes. If an intervention was to be planned—this study suggests that loneliness, anxiety and depression while distinct, are interconnected phenomena that affects change and development of the other. Furthermore, there are some reports of utilising network analysis in predicting future onset of psychological ailments (Boschloo et al., 2016 ) and as such, there exists initial support for examining highly central symptoms in the light of having high prognostic impact on the risk of developing a disorder. As such, while longitudinal research is needed, the present study supports loneliness being a worse predictor of anxiety and depression than the other two constructs are to each other.
Publisher Copyright:
© 2022 The Authors. International Journal of Psychology published by John Wiley & Sons Ltd on behalf of International Union of Psychological Science.
Keywords
- Regular Empirical Article
- Regular Empirical Articles
- Anxiety
- Depression
- Loneliness
- Arts and Humanities (miscellaneous)
- General Psychology
- General Medicine
- Pandemics
- Humans
- Loneliness/psychology
- Communicable Disease Control
- COVID-19/epidemiology
- Anxiety/psychology
- Depression/psychology
