Search

Objectives: To examine factors influencing loneliness and the effect of loneliness on physical and emotional health, in the context of the COVID-19 pandemic., Design: Prospective, observational cohort., Setting: Community-dwelling participants., Participants: Older adults (n = 238) enrolled in a longitudinal study., Measurements: Interviews were completed July-December 2020. Loneliness was measured with the UCLA 3-item loneliness scale. Data including age, marriage, education, cognitive functioning, functional impairment, vision or hearing impairment, depression, anxiety, medical comorbidity, social network size, technology use, and activity engagement were collected. Health outcomes included self-rated health, and physical and mental composites from the 12-item Short Form Survey. Physical function was measured by a PROMIS-scaled composite score., Results: Thirty-nine (16.4%) participants reported loneliness. Vulnerability factors for loneliness included age (RR = 1.08, 95% CI 1.02-1.14); impairment with instrumental activities of daily living (RR = 2.08, 95% CI 1.14-3.80); vision impairment (RR = 2.09, 95% CI 1.10-3.97); depression (RR = 1.34, 95% CI 1.25-1.43); and anxiety (RR = 1.92, 95% CI 1.55-2.39). Significant resilience factors included high cognitive functioning (RR = 0.88, 95% CI 0.83-0.94); large social network size (RR = 0.92, 95% CI 0.88-0.96); technology use (RR = 0.81, 95% CI 0.73-0.90); and social and physical activity engagement (RR = 0.91, 95% CI 0.85-0.98). Interaction analyses showed that larger social network size moderated the effect of loneliness on physical function (protective interaction effect, RR = 0.64, 95% CI 0.15-1.13, p <.01), and activity engagement moderated the effect of loneliness on mental health (protective interaction effect, RR = 0.65, 95% CI 0.25-1.05, p <.001)., Conclusions: Resilience factors may mitigate the adverse health outcomes associated with loneliness. Interventions to enhance resilience may help to diminish the detrimental effects of loneliness and hold great importance for vulnerable older adults., (Published by Elsevier Inc.)

Background: Recognizing family caregivers as vital providers of long-term assistance to loved ones with chronic illness, several national organizations developed recommendations to improve support for family caregivers., Purpose: This article categorizes these recommendations to advance family-centered nursing practice, develop health policies, and advocate for family caregiver support., Methods: Six reports of caregiver recommendations published in the United States from 2016 to 2021 were analyzed using thematic analysis., Findings: The 108 recommendations were organized into five categories: policy; caregiver assessment and support; health professional practices; public awareness; advance care planning., Discussion: Ensuring economic security, establishing a national data collection strategy, addressing caregivers' diverse needs, improving access to health care and support services, and increasing public awareness were highlighted., Conclusion: The recommendations provide a roadmap for nurses at all levels of practice to advocate for a national agenda to develop, fund, and implement inclusive health care policies and interventions to address unmet caregiver needs and maximize support., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Delirium and dementia are common causes of cognitive impairment among older adults, which often coexist. Delirium is associated with poor clinical outcomes, and is more frequent and more severe in patients with dementia. Identifying delirium in the presence of dementia, also described as delirium superimposed on dementia (DSD), is particularly challenging, as symptoms of delirium such as inattention, cognitive dysfunction, and altered level of consciousness, are also features of dementia. Because DSD is associated with poorer clinical outcomes than dementia alone, detecting delirium is important for reducing morbidity and mortality in this population. We review a number of delirium screening instruments that have shown promise for use in DSD, including the 4-DSD, combined Six Item Cognitive Impairment Test (6-CIT) and 4 'A's Test (4AT), Confusion Assessment Method (CAM), and the combined UB2 and 3D-CAM (UB-CAM). Each has advantages and disadvantages. We then describe the operationalization of a CAM-based approach in a current ECT in dementia project as an example of modifying an existing instrument for patients with moderate to severe dementia. Ultimately, any instrument modified will need to be validated against a standard clinical reference, in order to fully establish its sensitivity and specificity in the moderate to severe dementia population. Future work is greatly needed to advance the challenging area of accurate identification of delirium in moderate or severe dementia., Competing Interests: DISCLOSURES TGF TTH, PAT, EDM, FA HLH, MIL, EMS, DGH, and SKI report no conflicts with any product mentioned or concepts discussed in this article. REP has received research funding support outside of this project from support from Biogen Inc, Eisai, and Rogers Family Foundation. BPF has received has received research funding support outside of this project from the National Institute on Aging, Spier Family Foundation, Rogers Family Foundation, Biogen, and Eisai. BPF has received consultation fees from Patina Health and also serves on the Pharmacy & Therapeutics Committee for CVS Health. This work is support by grants from theNational Institute on AgingR01AG061100-05(BF/MIL);R01AG051591(BF);R33AG071744(SKI); 2R01AG044518(SKI). This work is dedicated to the memory of Joshua B. I. Helfand., (Copyright © 2022 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.)

Importance: The ability to rate delirium severity is key to providing optimal care for older adults, and such ratings would allow clinicians to target patients with severe delirium and monitor response to treatment, recovery time, and prognosis; assess nursing burden and staffing needs; and, ultimately, provide more appropriate patient-centered care. Current delirium severity measures have been limited in their content, gradations, and measurement characteristics., Objective: To examine the internal consistency, reliability, and validity for clinical outcomes of the DEL-S delirium severity score, a measure of delirium severity that was developed using advanced psychometric approaches, analogous to those of the Patient-Reported Outcomes Measurement Information System initiative., Design, Setting, and Participants: This prospective cohort study was conducted at a large academic medical center in Boston, Massachusetts. Adults aged 70 years or older who were admitted or transferred to medical or surgical services as either emergency or elective admissions were enrolled between October 20, 2015, and March 15, 2017, and were monitored for 1 year. Data analysis was performed from June 2020 to August 2021., Exposures: Delirium severity, measured by scores on the delirium severity score short-form (SF; 6 items, scored 0-13, with higher scores indicating more severe delirium) and long-form (LF; 17 items, scored 0-21), considered continuously and grouped into 5 categories., Main Outcomes and Measures: The primary outcomes were in-hospital outcomes, including length of stay and hospital costs, and posthospital (30, 90, and 365 days) outcomes, including death, health care costs, and rehospitalization., Results: The 352 participants had a median (IQR) age of 79.7 (74.6-85.5) years, 204 (58.0%) were women, and they were highly educated (median [IQR] duration of education, 14 [7-20] years). Patients in the highest delirium severity score SF group (scores 6-9) had a longer length of stay (13.3 vs 6.9 days; P for trend < .001), greater in-hospital costs ($57 700 vs $34 200), greater cumulative health care costs ($168 700 vs $106 500; P for trend = .01), and increased mortality at 1 year (50% vs 17%; P for trend = .02) compared with patients in the lowest delirium severity score SF group (score 0). Similar trends and significant findings were demonstrated for the delirium severity score LF., Conclusions and Relevance: These findings suggest that the delirium severity score provides an approach for measuring delirium severity that is associated with adverse clinical outcomes in a direct exposure-response association and that the delirium severity score may help advance patient-centered care for delirium.

The current study examined the association of patient factors, patient/caregiver relationships, and living arrangements with caregiver burden due to delirium. The sample included a subset ( N = 207) of hospitalized medical and surgical patients (aged >70 years) enrolled in the Better Assessment of Illness Study and their care-givers. The majority of caregivers were female (57%) and married (43%), and 47% reported living with the patient. Delirium occurred in 22% of the sample, and delirium severity, pre-existing cognitive impairment, and impairment of any activities of daily living (ADL) were associated with higher caregiver burden. However, only the ADL impairment of needing assistance with transfers was independently significantly associated with higher burden ( p < 0.01). Child, child-in-law, and other relatives living with or apart from the patient reported significantly higher caregiver burden compared to spouse/partners ( p < 0.01), indicating caregiver relationship and living arrangement are associated with burden. Future studies should examine additional factors contributing to delirium burden. [ Journal of Gerontological Nursing, 47 (9), 32-39.].

Introduction: Our goal was to determine if features of surgical patients, easily obtained from the medical chart or brief interview, could be used to predict those likely to experience more rapid cognitive decline following surgery., Methods: We analyzed data from an observational study of 560 older adults (≥70 years) without dementia undergoing major elective non-cardiac surgery. Cognitive decline was measured using change in a global composite over 2 to 36 months following surgery. Predictive features were identified as variables readily obtained from chart review or a brief patient assessment. We developed predictive models for cognitive decline (slope) and predicting dichotomized cognitive decline at a clinically determined cut., Results: In a hold-out testing set, the regularized regression predictive model achieved a root mean squared error (RMSE) of 0.146 and a model r-square ( R 2 ) of .31. Prediction of "rapid" decliners as a group achieved an area under the curve (AUC) of .75., Conclusion: Some of our models could predict persons with increased risk for accelerated cognitive decline with greater accuracy than relying upon chance, and this result might be useful for stratification of surgical patients for inclusion in future clinical trials., Competing Interests: The authors declare no competing interests., (© 2021 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.)

Background: Our objective was to assess the performance of machine learning methods to predict post-operative delirium using a prospective clinical cohort., Methods: We analyzed data from an observational cohort study of 560 older adults (≥ 70 years) without dementia undergoing major elective non-cardiac surgery. Post-operative delirium was determined by the Confusion Assessment Method supplemented by a medical chart review (N = 134, 24%). Five machine learning algorithms and a standard stepwise logistic regression model were developed in a training sample (80% of participants) and evaluated in the remaining hold-out testing sample. We evaluated three overlapping feature sets, restricted to variables that are readily available or minimally burdensome to collect in clinical settings, including interview and medical record data. A large feature set included 71 potential predictors. A smaller set of 18 features was selected by an expert panel using a consensus process, and this smaller feature set was considered with and without a measure of pre-operative mental status., Results: The area under the receiver operating characteristic curve (AUC) was higher in the large feature set conditions (range of AUC, 0.62-0.71 across algorithms) versus the selected feature set conditions (AUC range, 0.53-0.57). The restricted feature set with mental status had intermediate AUC values (range, 0.53-0.68). In the full feature set condition, algorithms such as gradient boosting, cross-validated logistic regression, and neural network (AUC = 0.71, 95% CI 0.58-0.83) were comparable with a model developed using traditional stepwise logistic regression (AUC = 0.69, 95% CI 0.57-0.82). Calibration for all models and feature sets was poor., Conclusions: We developed machine learning prediction models for post-operative delirium that performed better than chance and are comparable with traditional stepwise logistic regression. Delirium proved to be a phenotype that was difficult to predict with appreciable accuracy.

Background: Delirium is a common and preventable geriatric syndrome. Moving beyond the binary classification of delirium present/absent, delirium severity represents a potentially important outcome for evaluating preventive and treatment interventions and tracking the course of patients. Although several delirium severity assessment tools currently exist, most have been developed in the absence of advanced measurement methodology and have not been evaluated with rigorous validation studies., Objective: We aimed to report our development of new delirium severity items and the results of item reduction and selection activities guided by psychometric analysis of data derived from a field study., Methods: Building on our literature review of delirium instruments and expert panel process to identify domains of delirium severity, we adapted items from existing delirium severity instruments and generated new items. We then fielded these items among a sample of 352 older hospitalized patients., Results: We used an expert panel process and psychometric data analysis techniques to narrow a set of 303 potential items to 17 items for use in a new delirium severity instrument. The 17-item set demonstrated good internal validity and favorable psychometric characteristics relative to comparator instruments, including the Confusion Assessment Method - Severity (CAM-S) score, the Delirium Rating Scale Revised 98, and the Memorial Delirium Assessment Scale., Conclusion: We more fully conceptualized delirium severity and identified characteristics of an ideal delirium severity instrument. These characteristics include an instrument that is relatively quick to administer, is easy to use by raters with minimal training, and provides a severity rating with good content validity, high internal consistency reliability, and broad domain coverage across delirium symptoms. We anticipate these characteristics to be represented in the subsequent development of our final delirium severity instrument., (© 2020 S. Karger AG, Basel.)

This article presents the development and psychometric analysis of the Doctoral Readiness Self-Assessment for Doctoral Study. This survey was developed as the first step of a Web-based, on-line mentoring platform for nurses who are considering a doctoral degree program. By identifying and anticipating the predictors and barriers of success in doctoral nursing education, including practical (finances, time, geographical restriction) and personal factors (motivation, attitudes, perceived ability to navigate the application process), students are guided through a self-reflective process to determine readiness. Factor analysis revealed that interest, readiness, and support represent 3 distinct factors that may be used for additional analysis to predict future enrollment in doctoral nursing degree programs. The internal reliability analysis revealed that removing 3 items from the 15-item scale increased Cronbach's alpha from 0.75 to 0.80, and these factors explained 51.25% of variance. The self-assessment results can inform faculty's work as they mentor and guide students through the application, admission, and financial support processes for doctoral study., (Copyright © 2016 Elsevier Inc. All rights reserved.)

The New Careers in Nursing (NCIN) Program funded by The Robert Wood Johnson Foundation has expanded enrollment in schools of nursing with accelerated nursing programs and increased diversity in the nursing workforce. As the demand for highly educated and skilled nurses continues to grow, accelerated nursing programs are thriving and increasing in number. The growing cadre of nontraditional nursing students has challenged nursing faculty to institute innovative teaching methods to develop accelerated students' leadership skills and to provide mentoring resources for newly licensed nurses to guide the successful and complex transition from the student to professional practice. To support its grantee schools and their scholars, the NCIN National Program office has supported the development and distribution of toolkits and other resources and solicited request for proposals to recognize outstanding contributions. The Program Innovation grants are intended to support nurse faculty educators working to develop and enhance educational projects to implement innovative approaches to accelerated nursing education that can be taken to scale and replicated in a variety of educational settings. The Legacy Award honors a program that describes lasting impact on the school as a result of participation in the NCIN program. Two of these projects are described with emphasis on leadership development and transition to practice., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Background: Preoperative pain and depression predispose patients to delirium. Our goal was to determine whether pain and depressive symptoms interact to increase delirium risk., Methods: We enrolled 459 persons without dementia aged ≥70 years scheduled for elective orthopedic surgery. At baseline, participants reported their worst and average pain within seven days and current pain on a 0-10 scale. Depressive symptoms were assessed using the 15-item Geriatric Depression Scale and chart. Delirium was assessed with the Confusion Assessment Method and chart. We examined the relationship between preoperative pain, depressive symptoms and delirium using multivariable analysis of pain and delirium stratified by presence of depressive symptoms., Findings: Delirium, occurring in 23% of the sample, was significantly higher in those with depressive symptoms at baseline than those without (relative risk, RR, 1·6, 95% confidence interval, CI, 1·2-2·3). Preoperative pain was associated with an increased adjusted risk for delirium across all pain measures (RR from 1·07-1·08 per point of pain). In stratified analyses, patients with depressive symptoms had a 21% increased risk for delirium for each one-point increase in worst pain score, demonstrating a significant interaction ( P =0·049). Similarly, a significant 13% increased risk for delirium was demonstrated for a one-point increase in average pain score, but the interaction did not achieve statistical significance., Interpretation: Preoperative pain and depressive symptoms demonstrated increased risk for delirium independently and with substantial interaction, suggesting a cumulative impact. Thus, pain and depression are vulnerability factors for delirium that should be assessed before surgery., Funding: U.S. National Institute on Aging.

The world's older population has been growing for centuries; however, the pace of this growth is accelerating rapidly. According to the U.S. Census Bureau, by 2030, more than 60 countries will have 2 million or more older people. Population aging represents a "success story," with increasing numbers of people worldwide enjoying additional years of life. However, the sustained increase in numbers of older people (usually defined as persons over the age of 65) poses many challenges to policy makers and health care providers around the world. As the world population ages, we are just beginning to understand the social, economic, and political implications of the "age wave." The majority of older people are women, thus the implications of population changes for women and women's health are astounding. Nurses can take a national and world leadership role to adequately address the health care needs of increasing numbers of older women.