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A Meta-Analysis of Interventions to Reduce Loneliness:

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TLDR
An integrative meta-analysis of loneliness reduction interventions was conducted to quantify the effects of each strategy and to examine the potential role of moderator variables, and revealed that single-group pre-post and nonrandomized comparison studies yielded larger mean effect sizes relative to randomized comparison studies.
Abstract
Social and demographic trends are placing an increasing number of adults at risk for loneliness, an established risk factor for physical and mental illness. The growing costs of loneliness have led to a number of loneliness reduction interventions. Qualitative reviews have identified four primary intervention strategies: (a) improving social skills, (b) enhancing social support, (c) increasing opportunities for social contact, and (d) addressing maladaptive social cognition. An integrative meta-analysis of loneliness reduction interventions was conducted to quantify the effects of each strategy and to examine the potential role of moderator variables. Results revealed that single-group pre-post and nonrandomized comparison studies yielded larger mean effect sizes relative to randomized comparison studies. Among studies that used the latter design, the most successful interventions addressed maladaptive social cognition. This is consistent with current theories regarding loneliness and its etiology. Theoretical and methodological issues associated with designing new loneliness reduction interventions are discussed.

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Journal ArticleDOI

Lonely young adults in modern Britain: findings from an epidemiological cohort study.

TL;DR: Young adults’ experience of loneliness co-occurs with a diverse range of problems, with potential implications for health in later life, and underscores the importance of early intervention to prevent lonely young adults from being trapped in loneliness.
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Loneliness over time: the crucial role of social anxiety

TL;DR: It is suggested that loneliness may be a potential antecedent to emerging mental health symptoms and that identifying and treating co-occurring social anxiety symptoms may reduce the severity of loneliness.
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Can Digital Technology Enhance Social Connectedness Among Older Adults? A Feasibility Study:

TL;DR: The technology was a feasible communication tool, although requiring an adaptation period, and sense of well-being and confidence with technology was enhanced, but negative effects were also observed.
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Interventions targeting loneliness and social isolation among the older people: An update systematic review.

TL;DR: It is suggested that new technologies and community engaged arts might be seen as a promising tool for tackling social isolation and loneliness among the older individuals.
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Mental Health During the First Year of the COVID-19 Pandemic: A Review and Recommendations for Moving Forward

TL;DR: A review of the evidence indicates that anxiety, depression, and distress increased in the early months of the COVID-19 pandemic, while suicide rates, life satisfaction, and loneliness remained largely stable throughout the first year of the pandemic.
References
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The need to belong: Desire for interpersonal attachments as a fundamental human motivation.

TL;DR: Existing evidence supports the hypothesis that the need to belong is a powerful, fundamental, and extremely pervasive motivation, and people form social attachments readily under most conditions and resist the dissolution of existing bonds.
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Clinical significance: a statistical approach to defining meaningful change in psychotherapy research.

TL;DR: In this paper, the authors defined clinically significant change as the extent to which therapy moves someone outside the range of the dysfunctional population or within the ranges of the functional population, and proposed a reliable change index (RC) to determine whether the magnitude of change for a given client is statistically reliable.
Book

Practical Meta-Analysis

TL;DR: This paper presents a meta-analysis procedure called “Meta-Analysis Interpretation for Meta-Analysis Selecting, Computing and Coding the Effect Size Statistic and its applications to Data Management Analysis Issues and Strategies.
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