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: 1) improving social skills, 2) enhancing social support, 3) increasing opportunities for social contact, and 4) 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 non-randomized 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.

Objectives The objective of this study was to test a conceptual model of loneliness in which social structural factors are posited to operate through proximal factors to influence perceptions of relationship quality and loneliness. Methods We used a population-based sample of 225 White, Black, and Hispanic men and women aged 50 through 68 from the Chicago Health, Aging, and Social Relations Study to examine the extent to which associations between sociodemographic factors and loneliness were explained by socioeconomic status, physical health, social roles, stress exposure, and, ultimately, by network size and subjective relationship quality. Results Education and income were negatively associated with loneliness and explained racial/ethnic differences in loneliness. Being married largely explained the association between income and loneliness, with positive marital relationships offering the greatest degree of protection against loneliness. Independent risk factors for loneliness included male gender, physical health symptoms, chronic work and/or social stress, small social network, lack of a spousal confidant, and poor-quality social relationships. Discussion Longitudinal research is needed to evaluate the causal role of social structural and proximal factors in explaining changes in loneliness.

Loneliness is a prevalent social problem with serious physiological and health implications. However, much of the research to date is based on cross-sectional data, including our own earlier finding that loneliness was associated with elevated blood pressure. In this study, we tested the hypothesis that the effect of loneliness accumulates to produce greater increases in SBP over a fouryear period than are observed in less lonely individuals. A population-based sample of 229 50-68 year-old White, Black, and Hispanic men and women in the Chicago Health, Aging, and Social Relations Study was tested annually for each of five consecutive years. Cross-lagged panel analyses revealed that loneliness at study onset predicted increases in SBP 2, 3, and 4 years later (B = 0.152, SE = 0.091, p < .05, one-tailed). These increases were cumulative such that higher initial levels of loneliness were associated with greater increases in SBP over a 4-year period. The effect of loneliness on SBP was independent of age, gender, race/ethnicity, cardiovascular risk factors, medications, health conditions, and the effects of depressive symptoms, social support, perceived stress, and hostility. Keywordsloneliness; blood pressure; aging; social isolation Loneliness is a prevalent and serious social and public health problem (Cacioppo & Patrick, 2008). At any given time, up to thirty-two percent of adults over the age of 55 report feeling lonely (De Jong Gierveld & Van Tilburg, 1999), and from five to seven percent report feeling intense or persistent loneliness (Steffick, 2000;Victor, Scambler, Bowling, & Bond, 2005). Socially isolated individuals tend to feel lonely, but loneliness is not synonymous with being socially isolated. Loneliness is more accurately defined as the distressing feeling that accompanies discrepancies between one's desired and actual social relationships. Number of Direct correspondence to the first author at the Department of Psychology, University of Chicago, 940 E. 57 th St., Chicago, IL 60637, by fax to 773-702-6898, by telephone to 773-834-9152, or by hawkley@uchicago.edu. Publisher's Disclaimer: The following manuscript is the final accepted manuscript. It has not been subjected to the final copyediting, fact-checking, and proofreading required for formal publication. It is not the definitive, publisher-authenticated version. The American Psychological Association and its Council of Editors disclaim any responsibility or liabilities for errors or omissions of this manuscript version, any version derived from this manuscript by NIH, or other third parties. The published version is available at www.apa.org/journals/pag NIH Public Access NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript relationships can be important, but perceived shortcomings in the quality of one's relationships are particularly closely linked to loneliness (Hawkley et al., 2008;Peplau & Perlman, 1982;Pinquart & Sőrensen, 2003). Prospective studies have shown that feelings of loneliness predict depressive sym...

A population-based sample of Caucasians, African Americans, and Latino Americans, 50-68 years of age (M = 57.5), from Cook County, Illinois (N = 229), was tested to examine how loneliness and co-occurring psychosocial factors (depressive symptoms, perceived stress, social support, and hostility) were related to indices of cardiovascular and endocrine functioning. Extending prior research, the authors found that loneliness was associated with elevated systolic blood pressure (SBP) and age-related increases in SBP, net of demographic variables, health behavior variables, and the remaining psychosocial factors. Loneliness was not associated with differences in autonomic or endocrine functioning. Although the results are limited by the cross-sectional methods used, they are consistent with the hypothesis that cardiovascular disease contributes to increased morbidity and mortality among lonely individuals.

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Meta-analyses are becoming increasingly popular, especially in the fields of cardiovascular disease prevention and treatment. They are often considered to be a reliable source of evidence for making healthcare decisions. Unfortunately, problems among meta-analyses such as the misapplication and misinterpretation of statistical methods and tests are long-standing and widespread. The purposes of this statement are to review key steps in the development of a metaanalysis and to provide recommendations that will be useful for carrying out meta-analyses and for readers and journal editors, who must interpret the findings and gauge methodological quality. To make the statement practical and accessible, detailed descriptions of statistical methods have been omitted. Based on a survey of cardiovascular metaanalyses, published literature on methodology, expert consultation, and consensus among the writing group, key recommendations are provided. Recommendations reinforce several current practices, including protocol registration; comprehensive search strategies; methods for data extraction and abstraction; methods for identifying, measuring, and dealing with heterogeneity; and statistical methods for pooling results. Other practices should be discontinued, including the use of levels of evidence and evidence hierarchies to gauge the value and impact of different study designs (including meta-analyses) and the use of structured tools to assess the quality of studies to be included in a metaanalysis. We also recommend choosing a pooling model for conventional meta-analyses (fixed effect or random effects) on the basis of clinical and methodological similarities among studies to be included, rather than the results of a test for statistical heterogeneity. CLINICAL STATEMENTS AND GUIDELINES D espite the increasing popularity of meta-analyses and systematic reviews in general, problems with methodology are widespread and frequently undermine the credibility of the results. New guidance is needed for both researchers who carry out meta-analyses and systematic reviews in general and the consumers who read them and rely on the results. The term meta-analysis was coined in 1976 by the American statistician Gene Glass, who wrote, "I use it to refer to the statistical analysis of a large collection of results from individual studies for the purpose of integrating findings. It connotes a rigorous alternative to the casual, narrative discussions of research studies which typify our attempts to make sense of the rapidly expanding literature."1 Meta-analyses are a subcategory of the broader category of studies known as systematic reviews.Qualitative systematic reviews include explicit and detailed methods for identification, selection, and grading the quality of individual studies and overall evidence but do not pool results across studies. Meta-analysis is synonymous with the term quantitative systematic review and by definition includes pooling of results across studies. The emphasis in this statement is on metaanalysis bec...

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Breast cancer is the most common noncutaneous malignancy and the second most lethal form of cancer among women in the United States. Mortality from breast cancer has declined since the late 1980s, but this decline has been steeper among white women compared with black women. As a result, the black:white mortality rate ratio has increased over the last two decades. Other ethnic minorities also suffer from disproportionately high breast cancer mortality rates. This review discusses the causes of racial and ethnic disparities in breast cancer mortality and describes the most common approaches to reducing these disparities. The literature suggests that outcome disparities are related to patient-, provider-, and health system-level factors. Lack of insurance, fear of testing, delay in seeking care, and unfavorable tumor characteristics all contribute to disparities at the patient level. At the provider level, insufficient screening, poor follow-up of abnormal screening tests, and nonadherence to guideline-based treatments add to outcome disparities. High copayment requirements, lack of a usual source of care, fragmentation of care, and uneven distribution of screening and treatment resources exacerbate disparities at the health system level. Although pilot programs have increased breast cancer screening among select populations, persistent disparities in mortality suggest that changes are needed at the policy level to address the root causes of these disparities.