Laurie A. Theeke

Predictors of Loneliness in U.S. Adults Over Age Sixty-Five

The purpose of this study was to examine sociodemographic and health-related risks for loneliness among older adults using Health and Retirement Study Data. Overall prevalence of loneliness was 19.3%. Marital status, self-report of health, number of chronic illnesses, gross motor impairment, fine motor impairment, and living alone were predictors of loneliness. Age, female gender, use of home care, and frequency of healthcare visits were not predictive. Loneliness is a prevalent problem for older adults in the United States with its own health-related risks. Future research of interventions targeting identified risks would enhance the evidence base for nursing and the problem of loneliness.

Loneliness, Depression, Social Support, and Quality of Life in Older Chronically Ill Appalachians

ABSTRACT This studys purpose was to describe loneliness and to examine the relationships between loneliness, depression, social support, and QOL in chronically ill, older Appalachians. In-person interviews were conducted with a convenience sample of 60 older, chronically ill, community-dwelling, and rural adults. Those with dementia or active grief were excluded. The UCLA Loneliness Scale (Russell, Peplau, & Cutrona, 1985), Geriatric Depression Scale (Shiekh & Yesavage, 1986), Katz ADL scale (Katz, Down, & Cash, 1970), MOS Social Support Scale (Sherbourne & Stewart, 1991), and a visual analog scale for Quality of Life (Spitzer et al., 1981) scale were used. Diagnoses were obtained through chart reviews. SPSS was used for data analyses. The majority of the 65% female sample (M age = 75 years) were married and impoverished. Participants’ number of chronic illnesses averaged more than 3. Over 88% of participants reported at least 1 area of functional impairment. Loneliness was prevalent with UCLA loneliness scores indicating moderate to high loneliness, ranging from 39 to 62 (possible scores were 20−80). Higher loneliness scores correlated with depression, lower Qol, and lower social support, particularly lower emotional support. This study provides evidence that loneliness is a significant problem for older chronically ill Appalachian adults and that it may be related to low emotional support. Further, it provides evidence that this population may be significantly lonely and may not self-identify as lonely. Screening for loneliness and designing interventions that target the emotional aspects of loneliness could be important in this population.

A Systematic Review of Loneliness and Common Chronic Physical Conditions in Adults

Loneliness is a prevalent and global problem for adult populations and has been linked to multiple chronic conditions in quantitative studies. This paper presents a systematic review of quantitative studies that examined the links between loneliness and common chronic conditions including: heart disease, hypertension, stroke, lung disease, and metabolic disorders. A comprehensive literature search process guided by the PRISMA statement led to the inclusion of 33 articles that measure loneliness in chronic illness populations. Loneliness is a significant biopsychosocial stressor that is prevalent in adults with heart disease, hypertension, stroke, and lung disease. The relationships among loneliness, obesity, and metabolic disorders are understudied but current research indicates that loneliness is associated with obesity and with psychological stress in obese persons. Limited interventions have demonstrated long-term effectiveness for reducing loneliness in adults with these same chronic conditions. Future longitudinal randomized trials that enhance knowledge of how diminishing loneliness can lead to improved health outcomes in persons with common chronic conditions would continue to build evidence to support the translation of findings to recommendations for clinical care.

C-reactive protein and long-term ischemic stroke prognosis.

C-reactive protein (CRP) is an inflammatory biomarker of inflammation and may reflect progression of vascular disease. Conflicting evidence suggests CRP may be a prognostic biomarker of ischemic stroke outcome. Most studies that have examined the relationship between CRP and ischemic stroke outcome have used mortality or subsequent vascular event as the primary outcome measure. Given that nearly half of stroke patients experience moderate to severe functional impairments, using a biomarker like CRP to predict functional recovery rather than mortality may have clinical utility for guiding acute stroke treatments. The primary aim of this study was to systematically and critically review the relationship between CRP and long-term functional outcome in ischemic stroke patients to evaluate the current state of the literature. PubMed and MEDLINE databases were searched for original studies which assessed the relationship between acute CRP levels measured within 24 hours of symptom onset and long-term functional outcome. The search yielded articles published between 1989 and 2012. Included studies used neuroimaging to confirm ischemic stroke diagnosis, high-sensitivity CRP assay, and a functional outcome scale to assess prognosis beyond 30 days after stroke. Study quality was assessed using the REMARK recommendations. Five studies met all inclusion criteria. Results indicate a significant association between elevated baseline high sensitivity CRP and unfavorable long-term functional outcome. Our results emphasize the need for additional research to characterize the relationship between acute inflammatory markers and long-term functional outcome using well-defined diagnostic criteria. Additional studies are warranted to prospectively examine the relationship between high sensitivity CRP measures and long-term outcome.

Original Research: Loneliness and Quality of Life in Chronically Ill Rural Older Adults

The nursing literature has long recognized loneliness as a health priority. In 1955, Hildegard Peplau wrote about loneliness for this journal, calling it an “unbearable” condition and describing it as a psychological problem that results from deprivation of some social or emotional need.1 She also noted that being alone, often a chosen and useful state, isn’t the same as being lonely, which is not a chosen state; a distinction that is now well established. Historically, loneliness was first thought of as primarily a social phenomenon, and many of the instruments developed and used to measure it have been based on its social components. More recently, loneliness has been conceptualized in psychological terms, albeit at first as a construct embedded within depression. Currently the health and social sciences literature recognizes loneliness as a unique phenomenon, separate from depression, with emotional and social components.2, 3 This view of loneliness calls for a transdisciplinary approach, one that acknowledges that loneliness can be a significant biopsychosocial stressor and may adversely affect health.BackgroundLoneliness is a contributing factor to various health problems in older adults, including complex chronic illness, functional decline, and increased risk of mortality. ObjectivesA pilot study was conducted to learn more about the prevalence of loneliness in rural older adults with chronic illness and how it affects their quality of life. The purposes of the data analysis reported here were twofold: to describe loneliness, chronic illness diagnoses, chronic illness control measures, prescription medication use, and quality of life in a sample of rural older adults; and to examine the relationships among these elements. MethodsA convenience sample of 60 chronically ill older adults who were community dwelling and living in Appalachia was assessed during face-to-face interviews for loneliness and quality of life, using the University of California, Los Angeles (UCLA) Loneliness Scale (version 3) and the CASP-12 quality of life scale. Chronic illness diagnoses, chronic illness control measures, and medication use data were collected through review of participants’ electronic medical records. ResultsOverall mean loneliness scores indicated significant loneliness. Participants with a mood disorder such as anxiety or depression had the highest mean loneliness scores, followed by those with lung disease and those with heart disease. Furthermore, participants with mood disorders, lung disease, or heart disease had significantly higher loneliness scores than those without these conditions. Loneliness was significantly related to total number of chronic illnesses and use of benzodiazepines. Use of benzodiazepines, diuretics, nitrates, and bronchodilators were each associated with a lower quality of life. ConclusionsNurses should assess for loneliness as part of their comprehensive assessment of patients with chronic illness. Further research is needed to design and test interventions for loneliness.

Quality of life and loneliness in stroke survivors living in Appalachia.

ABSTRACT Background and Purpose: Negative outcomes of stroke are associated with poorer quality of life (QoL) and impact stroke recovery. The purpose of this study was to characterize QoL and loneliness in a sample of rural Appalachian stroke survivors within 1 year of stroke. Methods: Using mail survey methodology, survey data were collected from 121 ischemic and hemorrhagic stroke survivors living in West Virginia using 13 subscales from the Neuro-QOL survey and the three-item UCLA Loneliness Scale. Statistical Package for Social Sciences v. 20 was used to conduct descriptive, comparative, and predictive analyses. Multiple linear regression models were used to assess explanatory value of loneliness for QoL domains while controlling for comorbidities. Results: Participants who were discharged to a nursing home had poorer QoL when compared with those who were discharged to home. Stroke survivors who continued to smoke were less satisfied with social roles and reported higher mean loneliness and depression scores. History of psychological problems negatively correlated with all QoL domains and loneliness scores. Loneliness predicted poorer QoL even when controlling for age, gender, and significant comorbidities. Conclusion: Nurses need to assess for loneliness, include loneliness in care planning, and implement smoking cessation and cognitive behavioral interventions. Interventions that target loneliness for stroke survivors could potentially diminish psychological sequelae after stroke and enhance QoL.

Psychosocial variables and self-rated health in young adult obese women

AIM The aim of this study is to describe relationships among self-rated health, stress, sleep quality, loneliness, and self-esteem, in obese young adult women. BACKGROUND Obesity has steadily increased among young adults and is a major predictor of self-rated health. METHODS A sample of 68 obese (BMI 30 or higher, mean 35), young (18-34 years, mean 22) adult women were recruited from a health center. Survey data were gathered and analyzed using descriptive and bivariate procedures to assess relationships and group differences. RESULTS Scores reflected stress, loneliness, poor sleep quality, and poor self-esteem. There were positive correlations among stress, loneliness, and sleep quality and, a high inverse correlation between loneliness and self-esteem. Those who ranked their health as poor differed on stress, loneliness, and self-esteem when compared to those with rankings of good/very good. CONCLUSIONS Assessing and addressing stress, loneliness, sleep quality and self-esteem could lead to improved health outcomes in obese young women.

Free Care Is Not Enough: Barriers to Attending Free Clinic Visits in a Sample of Uninsured Individuals with Diabetes

Free care does not always lead to improved outcomes. Attendance at free clinic appointments is unpredictable. Understanding barriers to care could identify innovative interventions. The purpose of this study was to examine patient characteristics, biophysical outcomes, and health care utilization in uninsured persons with diabetes at a free clinic. A sample of 3139 patients with at least one chronic condition was identified and comparisons were made between two groups: those who attended all scheduled appointments and those who did not. Geographic distance to clinic and multiple chronic conditions were identified as barriers to attendance. After one year, missing more than one visit had a positive correlation with increased weight, A1C, and lipids. Additionally, patients who missed visits had higher blood pressure, depression scores, and numbers of medications. Future research should further enhance understanding of barriers to care, build knowledge of how social and behavioral determinants contribute to negative outcomes in the context of rurality. Innovative methods to deliver more frequent and intensive interventions will not be successful if they are not accessible to patients.

Study protocol: mobile improvement of self-management ability through rural technology (mI SMART)

AbstractBackgroundThere are 62 million Americans currently residing in rural areas who are more likely to have multiple chronic conditions and be economically disadvantaged, and in poor health, receive less recommended preventive services and attend fewer visits to health care providers. Recent advances in mobile healthcare (mHealth) offer a promising new approach to solving health disparities and improving chronic illness care. It is now possible and affordable to transmit health information, including values from glucometers, automated blood pressure monitors, and scales, through Bluetooth-enabled devices. Additionally, audio and video communications technologies can allow healthcare providers to conduct many parts of a physical exam remotely from varied settings. These technologies could remove geographical distance as a barrier to care and diminish the access to care issues faced by patients who live rurally. However, currently there is lack of studies that provide evidence of feasibility, acceptability, and effectiveness of mHealth initiatives on improved outcomes of care, a needed step to make the translation to implementation studies in healthcare systems. The purpose of this paper is to present the protocol for the first study of mI SMART (mobile Improvement of Self-Management Ability through Rural Technology), a new integrated mHealth intervention.MethodsOur objective is to provide evidence of feasibility and acceptability for the use of mI SMART in an underserved population and establish evidence for the refinement of mI SMART. The proposed study will take place at Milan Puskar Health Right, a free primary care clinic in the state of West Virginia. The clinic provides health care at no cost to uninsured, low income; adults aged 18–64 living in West Virginia. We will enroll 30 participants into this feasibility study with plans of implementing a longitudinal randomized, comparative effectiveness design in the future. Data collection will include tracking of barriers and facilitators to using mI SMART on patient and provider feedback surveys, tracking of patient-provider communications, self-reports from patients on quality of life, adherence, and self-management ability, and capture of health record data on chronic illness measures.DiscussionWe expect that the mI SMART intervention, refined from participant and provider feedback, will be acceptable and feasible. We anticipate high patient-provider satisfaction, enhanced patient-provider communication, and improved health related quality of life, adherence to treatment, and self-management ability. In addition, we hypothesize that patients who use mI SMART will demonstrate improved physical outcomes such as blood glucose, blood pressure, and weight.

Impact of the Provider and Healthcare team Adherence to Treatment Guidelines (PHAT-G) intervention on adherence to national obesity clinical practice guidelines in a primary care centre

RATIONALE, AIMS AND OBJECTIVES Obesity is significantly underdiagnosed and undertreated in primary care settings. The purpose of this clinical practice change project was to increase provider adherence to national clinical practice guidelines for the diagnosis and treatment of obesity in adults. METHODS Based upon the National Institutes of Health guidelines for the diagnosis and treatment of obesity, a clinical change project was implemented. Guided by the theory of planned behaviour, the Provider and Healthcare team Adherence to Treatment Guidelines (PHAT-G) intervention includes education sessions, additional provider resources for patient education, a provider reminder system and provider feedback. RESULTS Primary care providers did not significantly increase on documentation of diagnosis and planned management of obesity for patients with body mass index (BMI) greater than or equal to 30. Medical assistants increased recording of height, weight and BMI in the patient record by 13%, which was significant. CONCLUSIONS Documentation of accurate BMI should lead to diagnosis of appropriate weight category and subsequent care planning. Future studies will examine barriers to adherence to clinical practice guidelines for obesity. Interventions are needed that include inter-professional team members and may be more successful if delivered separately from routine primary care visits.