A new study finds that regardless of how loneliness is defined, by how often, how distressing, or how long it lasts, it leaves a consistent psychological footprint, with common patterns like low self-esteem and heightened social sensitivity.
Study: Revisiting the cognitive and behavioral aspects of loneliness: Insights from different measurement approaches. Image Credit: Jorm Sangsorn / Shutterstock
In a recent study published in the journal PLOS ONE, researchers in Austria and Switzerland investigated the cognitive and behavioral differences between participants with low and high loneliness using three independent classification methods: frequency, distress, and chronicity. The study aimed to assess the agreement between these classification methods, informing future research and treatment interventions for this growing public health concern.
Study findings demonstrated a fair to substantial classification agreement, but also revealed the considerable impact of cognitive and behavioral traits, such as interpretation bias, participant self-esteem, and social avoidance, on participant group differences across classification methods. These results highlight the complexity of loneliness and call for future treatments to carefully consider the several dimensions of loneliness across both cognitive and behavioral axes.
Background
Loneliness is a distressing emotional state characterized by a subjective gap between desires and perceived social connection. While exceedingly common (almost everyone experiences periods of loneliness across their lifetimes), today's fast-paced world and reductions in sufficient social interaction have exacerbated chronic loneliness to a globally relevant public health concern, affecting between 5.3–12.7% of all people and causing significant negative mental and physical health outcomes.
Previous research on loneliness has distinguished between adaptive and maladaptive forms of loneliness. While the former is an evolutionary cue that encourages increased social connections, the latter results from cognitive biases and behavioral tendencies and can trigger or exacerbate mental health issues, as outlined in Cacioppo and Hawkley's cognitive loneliness model.
"This model suggests that loneliness triggers a cascade of cognitive processes that heighten awareness of social disconnection. These processes include heightened sensitivity to subjective social threats, negative attributions, and biased social information processing, which can lead to maladaptive behaviors such as social withdrawal and increased vigilance toward potential social threats and thereafter maintain or increase feelings of loneliness."
A distinct yet often overlooked difference between adaptive and maladaptive loneliness is its persistence. Current measures of loneliness, including the UCLA Loneliness Scale (UCLA-LS) and the Rasch-Type Loneliness Scale (RTLS), may not sufficiently account for the persistence and other dimensions of maladaptive loneliness's complexity, thereby compromising their ability to classify patients accurately and inform subsequent treatment. It is essential to note that while this study explores the distinction between adaptive and maladaptive loneliness, its primary focus is on the maladaptive aspects and does not directly investigate adaptive loneliness in practice.
About the study
The present study revisits the evaluation of loneliness through the lens of the cognitive model of loneliness. It evaluates cognitive and behavioral differences between individuals across the loneliness spectrum by first classifying them via three distinct classification methodologies (frequency, distress, and chronicity), subsequently evaluating the degree of agreement between these methodologies, and finally elucidating the impacts of these psychological variables as dependent outcomes (rejection sensitivity, interpretation bias, self-esteem, etc.) among individuals grouped as lonely or not lonely.
Study data was obtained via an online survey hosted on SurveyCircle, internet forums, and social media. Target participants were German-speaking adults aged 18 years or older. Additional participant information included age, sex, education level, employment status, and relationship status.
Loneliness frequency was evaluated using the UCLA Loneliness Scale (short version). Loneliness distress was measured using a 2-item custom query ('Do you feel lonely?' in combination with 'extent of distress due to loneliness'). Loneliness chronicity was evaluated via participant-reported loneliness duration, with a 24-month cutoff.
Additionally, interpretation bias was recorded using the Interpretation and Judgmental Questionnaire (IJQ), social avoidance behavior using the Cognitive-Behavioral Avoidance Scale (CBAS), rejection sensitivity using the Rejection Sensitivity Questionnaire (A-RSQ), comfort of self-disclosure using the Distress Disclosure Index (DDI), self-esteem using the Rosenberg Self-Esteem Scale (RSES), and avoidance goal intensity using the Inventory of Approach and Avoidance Goals (IAAM) scale.
To account for confounds introduced by overlaps with anxiety and depression, psychopathological symptoms were assessed using the Patient Health Questionnaire (PHQ-9) and the Social Interaction Anxiety Subscale (SIAS-6).
Study findings
Of the 1,389 individuals who participated in the online survey, 553 did not complete it, and 44 participants failed data integrity checks, resulting in a final study cohort of 790 participants (mean age = 31.86, 81% female). Loneliness classification methodologies classified 15.95%, 29.75%, and 19.49% of participants as 'lonely' based on frequency, distress, and chronicity criteria, respectively.
Agreement analyses between classification methodologies revealed moderate agreement between frequency and distress criteria (78.10%, Cohen's κ = 0.40), fair agreement between frequency and chronicity (79.74%, Cohen's κ = 0.31), and substantial agreement between distress and chronicity (86.96%, Cohen's κ = 0.65).
"…these results indicate that while there is some overlap between different loneliness classification methods, they are not entirely interchangeable. The varying levels of agreement across measures suggest that each method captures a distinct aspect of loneliness, with distress and chronicity showing the highest alignment and frequency showing lower agreement with the other methods."
Analysis of variance (ANOVA) analyses revealed that individuals classified as lonely using frequency classification were more likely to experience rejection sensitivity and lower self-esteem (large effects), interpretation bias, social avoidance behavior, and lower distress disclosure (medium effects), as well as avoidance goal intensity (small effects). Notably, similar cognitive and behavioral differences were observed across all three classification methods. However, the effect sizes varied, with distress-based classifications showing the strongest associations and chronicity-based classifications showing similar but sometimes smaller effects.
Limitations
The authors note several limitations to their findings. The cross-sectional design of the study does not permit conclusions about causality; therefore, it remains unclear whether cognitive biases and behavioral tendencies cause persistent loneliness or result from it. There is also a potential for self-selection bias, as individuals experiencing loneliness may have been more inclined to participate in a study explicitly advertised as focusing on loneliness, potentially inflating prevalence rates. The sample was predominantly female (81%) and relatively young, which may limit the generalizability of the results to broader or different populations. Additionally, the study relied solely on self-report measures, which can introduce response biases such as underreporting or overreporting feelings due to social desirability or recall issues. The assessment of chronic loneliness overlapped with the COVID-19 pandemic, which may have influenced participants' perceptions of the duration of their loneliness. Furthermore, the study was not pre-registered, which limits transparency regarding hypothesis testing.
Conclusions
The present study reveals that while classifications of loneliness patients according to differing criteria (frequency versus distress versus chronicity) may display fair to substantial agreements, nuanced evaluations of these patients highlight stark differences in their dimensions and experiences of loneliness. At the same time, the cognitive and behavioral correlates associated with loneliness were consistent across classification methods, suggesting a shared profile of maladaptive traits among those identified as lonely by any of the three approaches. This is indicative and cautionary as it underscores the complexity of the behavioral and emotional response to feelings of loneliness, emphasizing the need for a broader understanding of patient needs when initiating interventions against the condition.
"Further research, particularly longitudinal studies, is needed to build on these findings, further to investigate the distinction between adaptive and maladaptive loneliness, and develop effective strategies to combat loneliness."