Owner of a lonely heart: The stability of loneliness across the life span.

Abstract

Individuals feel lonely when they perceive a discrepancy between their aspired and their actually experienced amount of closeness and intimacy in social relationships. In the present study, we disentangled developmental constancy factors, time-varying factors such as person-environment transactions, and stochastic mechanisms as sources of interindividual differences in loneliness by applying STARTS models in nationally representative samples from Germany (n = 13,397), Switzerland (n = 6,599), Australia (n = 30,496), and The Netherlands (n = 12,810). Across the 4 studies, we found trait-like sources reflecting developmental constancy factors and the influence of time-varying factors to account for 19–43% and 23–30% of interindividual differences in loneliness, respectively. Depending on the type of measurement instrument, state-like stochastic mechanisms accounted for 30% to 55% of interindividual differences, whereby multi-item measures were less affected by stochastic mechanisms. We found gradual sex differences but considerable differences between age groups regarding the amount of interindividual differences in loneliness accounted for by the three sources. Taken together, the results demonstrate that interindividual differences in loneliness are to a large degree trait-like. Based on these findings, we discuss implications for theory and measurement.

A Bayesian Approach to Estimating Reciprocal Effects with the Bivariate STARTS Model using Markov Chain Monte Carlo

“…We set the stable trait variances for both variables to 0.25, autoregressive trait variances to 0.55, and occasion-specific state variances to 0.2. These variance proportions are in line with findings from longitudinal research that applied the univariate STARTS model (Jansen et al, 2020;Mund et al, 2020; see also Usami, Todo, & Murayama, 2019). The total variance of the manifest variables was set to 1.…”

“…This has been applied to constructs such as life satisfaction (Lucas & Donellan, 2007;Schimmack et al, 2010), academic self-concept (Jansen et al, 2020), self-esteem (Alessandri et al, 2016;Donellan et al, 2012;Wagner et al, 2016), loneliness (Mund et al, 2020), and personality traits (Anusic et al, 2012;Anusic & Schimmack, 2016).…”

Would the Real Loneliness Please Stand Up? The Validity of Loneliness Measures and the Reliability of Single Items

“…Moreover, it seems that the individuals who are classified as "lonely" based on cut-off scores on multi-item scales are not the same individuals who are classified as "lonely" based on the same cut-off score applied to single-item measures (Eccles et al, 2020;Shiovitz-Ezra & Ayalon, 2012). Apart from prevalence rates, however, the results obtained with single-item measures converge very well with those obtained with multi-item scales with regard to demographic aspects (Shiovitz-Ezra & Ayalon, 2012;von Soest et al, 2020), aspects of mean-level and rank-order stability (Mund, Freuding, et al, 2020;Mund, Lüdtke, et al, 2020), interpersonal dynamics (Mund & Johnson, 2021;Mund et al, in press), personality correlates (Buecker et al, 2020), and health outcomes (Beutel et al, 2017;Eccles et al, 2020), including early mortality (Holt-Lunstad et al, 2015;Shiovitz-Ezra & Ayalon, 2010).…”

“…Russell, 1982). In line with this reasoning, a study employing STARTS models (Kenny & Zautra, 2001) found that single item measures capture more (potentially unreliable) state variance (≈ 50% state variance) than longer scales such as a 6-item version of the RTLS (≈ 25% state variance; Mund, Lüdtke, et al, 2020). However, it has been shown for single-item measures of subjective well-being that state variance can contain a substantial amount of reliable variance (Lucas & Donnellan, 2012).…”

Is personality stable in adolescence? Disentangling time‐invariant and time‐varying factors of personality in a trait–state–occasion model

“…The occasion-specific factor displays the time-varying part of agreeableness at any specific assessment point. Time-varying factors could be internal (e.g., changing genetic effects), external (e.g., environmental effects) or consequence from interactions between internal and external factors (Mund et al, 2020). The autoregressive coefficient indicates sustainability between consecutive occasion factors over time, reflecting relative influences of prior occasion factors on inter-individual differences in agreeableness at the next wave.…”