Table of ContentsMeta-Analytic ReviewArticle PantellCapable TrialConclusionReferencesExtensive research over the past several decades shows the extreme harm that social isolation causes to individuals of all ages; The association between social isolation and health was found to be as strong as the evidence linking smoking to health. Social isolation can be defined as “the absence of social interactions, contacts and relationships” with family, friends, neighbors and with society as a whole. The impact of social isolation on communities is profound: study after study shows a significant link to poorer health outcomes and a host of other problems. Isolation is more common today than before, in part because of the baby boomer generation's lower birth rate and higher divorce rate. Say no to plagiarism. Get a tailor-made essay on “Why violent video games should not be banned”?Get an original essaySocial isolation of older people is particularly difficult due to the special needs of older people; social isolation can either exacerbate or be exacerbated by mental illness, physical disorders, and decreased cognitive function. Holt-Lunstad et al. also found that those with social connections have a 50% reduced risk of dying prematurely. One in six baby boomers lives alone, and about one in 11 Americans age 50 or older does not have a spouse, romantic relationship or children. A socially isolated older person is more likely to suffer from depression or commit suicide. Suicide deaths among older adults are considered a significant public health problem, and the aging baby boomer generation has consistently experienced higher suicide rates than any other cohort. The Centers for Disease Control found that a key strategy for preventing suicide is “promoting and strengthening connections at the personal, family, and community levels.” Addressing social isolation – and depression – among older adults will not only increase overall well-being, but will also impact the suicide rate in this population. A review of Ventura County's current environment regarding its homebound seniors provides additional insight into why the proposed project is both important and innovative. The number of county residents aged 75 and older is expected to double to more than 90,000 over the next decade (250,000 aged 60 and older). Programs aimed at meeting the needs of these residents fall far short of what is needed. To achieve real, large-scale change, there needs to be greater acceptance of the need to tackle social isolation as well as a greater commitment to supporting our homebound older people. Thus, a comprehensive strategy that goes beyond program implementation is imperative. The Ventura County Senior Social Isolation Project (VCESIP) is a comprehensive strategy to improve countywide services for low-income, homebound older adults. In addition to forming a coalition, VCESIP will work to develop and/or implement therapeutic home programs throughout the county. There are evidence-based programs that could be replicated in Ventura County. For example, the Community Aging in Place, Advancing Better Living for Elders (CAPABLE) program developed at Johns Hopkins University combines occupational therapy, nursing, and handyman support and offers up to10 home visits over 6 months. The Positive Solutions program, which has been running in San Diego County for ten years now, has been successful in identifying and treating socially isolated older adults suffering from depression. The Positive Solutions program uses the Program to Encourage Active Rewarding Lives (PEARLS), a national evidence-based program treating late-life depression in older adults. Given the challenges homebound frail older adults face in accessing programs that can help them, in-home supportive/therapeutic services are an optimal solution for many. Meta-analytic review This meta-analytic review focuses on determining the extent to which social relationships influence mortality risk as well as factors that may moderate risk. This analysis ultimately included data from 148 studies, involving 308,849 participants. Several techniques were used to find studies to include in this analysis. Studies were searched from January 1900 to January 2007 using several databases, including HealthSTAR, Medline, Mental Health Abstracts, PsycINFO, Social Sciences Abstracts, Sociological Abstracts, Academic Search Premier, ERIC, and Family & Society Studies Worldwide. Several search terms were cross-referenced with words related to social relationships. To reduce unintentional omissions, databases with the most citations were searched twice more. The researchers also manually examined the reference sections of reviews of previous studies to find articles that had not been identified during database searches. Finally, letters were sent to authors who had published three or more articles in this area to ensure that appropriate studies were all included. Coding and data entry. The researchers laid out many details and requirements in order to capture the data they wanted to focus on. For example, mortality from suicide or injury was not included, while baseline health status and pre-existing health conditions were included. The OR (odds ratio) data cannot be meaningfully aggregated, so it was put into natural log OR form for analysis and then converted back to OR for interpretation. Random effects modeling was undertaken to calculate the average effect size of the studies (the average OR was 1.5) Results. Results indicate that there is a 50% increased likelihood of survival for participants with stronger social relationships, a finding that remains consistent regardless of age, gender, baseline health status, cause of death and the follow-up period. This particular finding from this study has been used prolifically in academic and other publications focused on the impact of social relationships (and/or social isolation) on health. The research literature on social isolation provides strong evidence that social isolation is truly a health epidemic in this country, and well-supported statistics such as this link between social relationships and mortality are helpful in understanding the severity of the problem. For the purposes of this synthesis project, this finding is useful in strengthening the argument for the existence of the problem and the need for intervention. Bias. Although this meta-analysis is well structured and respected in the research literature, there are some areas of potential bias to explore. The authors of this article report that this meta-analysis may underestimate the effect of social relationships on mortality. This is because most studies includedsimple single-item measures of social isolation rather than complex measures (research indicates that effect sizes tend to be larger when multiple measures of social relationships are used in a study). Additionally, there is the fact that proving causality between lack of social relationships and poor health/mortality presents some inherent challenges to overcome. Definitions of social relationships are heterogeneous in nature, and Howick et al argue that the term "social relationship" is a "synthesized construct relating to specific contexts that change over time." Finally, an aspect not addressed in this or other meta-analytic reviews is that certain social relationships can shorten lifespan (gang affiliation/membership is one example). Article by Pantell This study is a quantitative study exploring the relationship between social isolation and mortality using a nationally representative US sample. Social isolation is compared to traditional clinical factors in predicting mortality. Sampling. The sample consisted of 16,849 adults using data from the National Health and Nutrition Examination Survey and the National Mortality Index. Sampling weights were already included so that the sample was representative of the non-institutionalized civilian population. Some participants in the original dataset were excluded due to their low mortality/young age and incomplete mortality follow-up data. There were 8,974 women and 7,875 men, with the average age being 48.4 years for women and 46.5 years for men. The study population was predominantly white and non-Hispanic, had 12 years of education or more, average income, and good baseline health. Data collection and analysis. Four predictors of social isolation (marital status, frequency of contact with other people, participation in religious activities, and participation in another club/organization) were compared with four comparison predictors (smoking, obesity, blood pressure high blood pressure and high cholesterol). The Berkman-Syme Social Network Index (SNI) was used to measure the level of social isolation. Kaplan-Meier life tables and Cox proportional hazards models were used to predict mortality based on social isolation, clinical risk factors, and covariates (age, race/ethnicity, education, income and basic health status). All models were stratified by sex because previous studies have shown sex differences in the influence of social isolation on mortality. Results. Study finds increased risk of death among socially isolated men and women. Social isolation also predicts mortality at a higher level than some of the standard clinical risk factors (smoking and high blood pressure). These results are consistent with the many other studies that support the need for innovative solutions to combat social isolation, such as my capstone project.Bias. The authors of this study acknowledge several limitations, which could indicate potential areas of bias. Most of the data included in this study were self-reported data by participants. Thus, true levels of social activity may not have been accurately captured. The researchers controlled for a number of potential confounding factors, but acknowledge that there may have been unmeasured confounding factors that would then have affected the relationship between social relationships and mortality. As is the case with many studies examining the relationship between isolationsocial and health, it is difficult to control for reverse causality in all cases. There are probably many cases where health problems have led to social isolation rather than the other way around. Capable TrialA paper by John Hopkins researchers (from various John Hopkins schools) describes the rationale and design of the first clinical trial of a program called CAPABLE. (Community Aging in Place, Advancing Better Living for Elders) (Szanton, et. al., 2014). This article does not discuss the results but rather provides an in-depth analysis of the study design. The aim of the trial study was to evaluate the effectiveness of CAPABLE in reducing disability in participants. This is a randomized, two-group, single-blind controlled trial. Sampling and recruitment. The target population is low-income older adults living in the community who have difficulty caring for themselves. Participants had to be functionally limited but medically stable and have a sufficiently high cognitive level to actively participate in the intervention. Participants were divided into an experimental group (n = 150), whose members received ten at-home sessions (6 with the occupational therapist, up to 4 with a registered nurse and up to $1,200 in safe repairs and functional at home by a handyman). These sessions took place over a period of four months. The control group (n = 150) also received 10 in-home sessions over a four-month period, but the intervention was different from that received by the experimental group. Participant recruitment is described as a “multi-faceted community effort.” Study coordinators worked with agencies serving older adults, such as senior centers and Meals on Wheels, to find potential participants. Targeted mailings were also sent to low-income neighborhoods with large numbers of seniors. Participants were then stratified by gender and then randomized into two groups using a computer program. A pilot trial had been conducted prior to this larger trial, and in order to determine the sample size of this trial, calculations were made based on the effect size of the pilot. Data collection. A prolific number of measurement tools are included in this study and are administered at different times before, during, and after intervention implementation: Measurement Tool Objective Portable Short Mental State Questionnaire Assesses cognitive level Battery short physical performance test (SPPB) Three objective tests of physical function. The SPPB has been shown to have high reliability.End-of-life Function and Disability InstrumentA self-report measure of disabilities and is correlated with the SPPB and self-report function questions.Sociodemographic QuestionnaireAuto -assessment of baseline characteristics.Patient Activation ScaleMeasures patient activation in relation to medical visits. Patient Health Questionnaire-9Assesses depression. Validated to diagnose depression and determine severity level. Brief Pain Inventory Measures intensity, stress, and interference with life due to pain. Test-retest reliability and inter-rater reliability are strong according to the authors of the articleCC Home Safety Checklist43 item checklist developed as part of the CDC.EuroQol (EQ-5D)Health-related quality of life questionnaire . 5 items.Control-oriented strategyMeasures behavioral and cognitive processes that facilitate adaptation to life challenges.Results. Although this article does not include the results of the trial, this study and other studies evaluating the effectiveness of2352-8273..2014.03.005