Measuring Loneliness in Different Age Groups: The Measurement Invariance of the UCLA Loneliness Scale

Psychometric properties of the variants of the Chinese UCLA Loneliness Scales and their associations with mental health in adolescents

Loneliness is a pervasive and distressing emotional experience that affects individuals of all ages and can have significant consequences for both physical and mental health. The UCLA Loneliness Scale (UCLA-LS) is widely used to assess the subjective feelings of loneliness, but concerns have been raised about its structure and applicability in diverse cultural contexts. This study analysed the reliability and validity of the five Chinese versions of the UCLA-LS in a representative sample of 2,643 adolescents and young adults with Chinese as their first language in Hong Kong. The results showed high internal consistency across all versions and content validity for most items. Factor analysis revealed a two-factor structure for the longer versions and a unidimensional structure for the shorter versions. However, the fit statistics suggested that the models did not meet good fit criteria, indicating item loading or model specification requires further review. The scales demonstrated strong associations with mental health conditions such as depression and anxiety, as well as psychosocial factors like hopelessness and aggression. Notably, the 8-item version's total scores were associated with mental health and psychological attributes comparable to those of the 20-item version, suggesting its potential suitability as a screening tool in population settings. Future research is needed to improve the generalisability of these scales to other Chinese populations, particularly for items with lower content validity.

Modelling nonlinear moderation effects with local structural equation modelling (LSEM): A non-technical introduction

Understanding the differential strength of effects in the presence of a third variable, known as a moderation effect, is a common research goal in many psychological and behavioural science fields. If structural equation modelling is applied to test effects of interest, the investigation of differential strength of effects will typically ask how parameters of a latent variable model are influenced by categorical or continuous moderators, such as age, socio-economic status, personality traits, etc. Traditional approaches to continuous moderators in SEMs predominantly address linear moderation effects, risking the oversight of nonlinear effects. Moreover, some approaches have methodological limitations, for example, the need to categorise moderators or to pre-specify parametric forms of moderation. This tutorial introduces local structural equation modelling (LSEM) in a non-technical way. LSEM is a nonparametric approach that allows the analysis of nonlinear moderation effects without the above-mentioned limitations. Using an empirical dataset, we demonstrate the implementation of LSEM through the R-sirt package, emphasising its versatility in both exploratory analysis of nonlinear moderation without prior knowledge and confirmatory testing of hypothesised moderation functions. The tutorial also addresses common modelling issues and extends the discussion to different application scenarios, demonstrating its flexibility.

Addressing loneliness and social isolation in 52 countries: a scoping review of National policies

BACKGROUND

Even prior to the advent of the COVID-19 pandemic, there was ample evidence that loneliness and social isolation negatively impacted physical and mental health, employability, and are a financial burden on the state. In response, there has been significant policy-level attention on tackling loneliness. The objective of this scoping review was to conduct a loneliness policy landscape analysis across 52 countries of the UN European country groups. Our policy analysis sought to highlight commonalities and differences between the different national approaches to manage loneliness, with the goal to provide actionable recommendations for the consideration of policymakers wishing to develop, expand or review existing loneliness policies.

METHODS

We searched governmental websites using the Google search engine for publicly available documents related to loneliness and social isolation. Seventy-eight documents were identified in total, from which 23 documents were retained. Exclusion of documents was based on predetermined criteria. A structured content analysis approach was used to capture key information from the policy documents. Contextual data were captured in a configuration matrix to highlight common and unique themes.

RESULTS

We could show that most policies describe loneliness as a phenomenon that was addressed to varying degrees in different domains such as social, health, geographical, economic and political. Limited evidence was found regarding funding for suggested interventions. We synthesised actionable recommendations for the consideration of policy makers focusing on the use of language, prioritisation of interventions, revisiting previous campaigns, sharing best practice across borders, setting out a vision, evaluating interventions, and the need for the rapid and sustainable scalability of interventions.

CONCLUSIONS

Our study provides the first overview of the national loneliness policy landscape, highlighting the increasing prioritisation of loneliness and social isolation as a major public health and societal issue. Our findings suggest that policymakers can sustain this momentum and strengthen their strategies by incorporating rigorous, evidence-based intervention evaluations and fostering international collaborations for knowledge sharing. We believe that policymakers can more effectively address loneliness by directing funds to develop and implement interventions that impact the individual, the community and society.

Pathways from Men's Shed engagement to wellbeing, health-related quality of life, and lower loneliness

Extensive qualitative evidence, but limited quantitative evidence, indicates that mutual aid organizations such as Men's Sheds have positive impacts on wellbeing, health-related quality of life, and loneliness. A recently developed theoretical model proposes that Men's Sheds may have these impacts via mediating factors such as broadening social networks, increasing behavioural activation and physical activity, reducing alcohol use, and providing meaning in life. The aim of this study was to quantitatively test a model whereby psychological safety (feeling safe, accepted, and valued) is associated with Men's Shed engagement (frequency of attendance, duration of membership, diversity of activities), which is associated with the hypothesized mediators, which, in turn, are associated with wellbeing, health-related quality of life, and loneliness. Men's Shed members (N = 333, Mage = 70.90 years, SD = 10.34, 98% male) completed a survey assessing the factors in the model. The hypothesized path model provided an excellent fit to the data. Findings indicated that higher psychological safety was associated with higher engagement, which, in turn, was associated with larger social networks and more meaning in life, which were associated with higher wellbeing and lower loneliness. Higher behavioural activation and less alcohol use were also associated with higher wellbeing. Higher Men's Shed engagement was not associated with higher behavioural activation and physical activity, or less alcohol use, but behavioural activation and alcohol use were directly associated with health-related quality of life. Implications for optimizing health outcomes within Men's Sheds are discussed.

Perspectives on interpersonal touch are related to subjective sleep quality

Affective touch has been reported for its calming effects; however, it is less clear whether touch is associated with sleep. Here, the relationship between different touch variables and self-reported sleep indicators was investigated. Data were extracted from the Touch Test, a cross-sectional survey conducted in 2020. Data from a sample of 15,049 healthy adults from the UK (mean age = 56.13, SD = 13.8; 75.4% female) were analysed. Participants were asked to attribute positive, negative, or no effects on sleep to hugs, strokes, massages, intimate touch, and sleep onset with and without touch. The time since last intentional touch, touch amount satisfaction, and childhood bed routine with hugs and kisses were assessed. Sleep quality, duration, latency, wake after sleep onset and diurnal preference were measured. Data were analysed using chi-square tests and logistic regressions. Affective touch before sleep was perceived to have positive effects on sleep. Touch recency emerged as a significant predictor for some sleep variables, with a longer timespan since the last intentional touch relating to improved sleep quality, longer sleep duration, and shorter and fewer instances of waking up after sleep onset in some participants. Experiencing too much touch was related to lower sleep quality and higher instances of waking up after sleep onset. These findings highlight the importance of interpersonal touch for subjective sleep quality.

How (Not) to Measure Loneliness: A Review of the Eight Most Commonly Used Scales

Loneliness affects well-being and has long-term negative impacts on physical and mental health, educational outcomes, and employability. Because of those current and long-term impacts, loneliness is a significant issue for which we need reliable and appropriate measurement scales. In the current paper, psychometric properties of the eight most commonly used loneliness scales are reviewed both descriptively and meta-analytically. Results suggest that for many of the scales, the psychometric properties are promising. However, for some psychometric features, especially test-retest reliability and measurement invariance, evidence is rather scarce. Most striking, however, is the fact that all of the scales included items that do not measure loneliness. Surprisingly, for many (sub)scales, this was even the case for about half of the items. Because our measures are the foundation of our research work, it is crucial to improve the way loneliness is being measured.