Exploring the concept of psychological frailty in older adults: a systematic scoping review

Frailty in kidney transplant recipients

Kidney transplantation is the treatment of choice even for the elderly, as it improves quality of life and life expectancy, lowering the financial burden to the health care system compared to dialysis therapy. In Japan, kidney transplant recipients have become older due to the shift in demographics. Compared to community-dwelling elderly adults, elderly kidney transplant recipients undergoing immunosuppressive therapy have a higher risk of age-related outcomes including hospital readmissions, infections, dementia, malignancies, and fractures. In frailty, patients become vulnerable to adverse events after stressors due to a lack of physiologic reserve. Although it is often associated with aging, frailty can also occur in younger individuals with certain chronic illnesses or conditions including chronic kidney disease. Limited compensatory mechanisms result in functional impairment and adverse health outcomes, such as disability, falls, decreased mobility, hospitalization, and death. Although kidney transplant recipients can restore their kidney function after transplantation, most of them still have chronic kidney disease, as well as a gradual decline in graft function as a result of chronic allograft nephropathy. Wait-listed candidates for kidney transplantation with frailty are more likely to experience wait-list removal or death. Frailty at the time of transplantation is associated with complications after kidney transplantation such as delayed graft function, longer hospital stays, rehospitalizations, immunosuppression intolerance, surgical complications, and death. Nevertheless, kidney transplantation can be a viable intervention for frailty in dialysis patients.

Common Characteristics Between Frailty and Myotonic Dystrophy Type 1: A Narrative Review

Myotonic dystrophy type 1 (DM1) is an inherited neuromuscular disorder often considered a model of accelerated aging due to the early appearance of certain age-related clinical manifestations and cellular and molecular aging markers. Frailty, a state of vulnerability related to aging, has been recently studied in neurological conditions but has received considerably less attention in neuromuscular disorders. This narrative review aims to describe 1) the common characteristics between Fried's frailty phenotype criteria (muscular weakness, slow gait speed, weight loss, exhaustion/fatigue, and low physical activity) and DM1, and 2) the psychological and social factors potentially contributing to frailty in DM1. This review gathered evidence suggesting that DM1 patients meet four of the five frailty phenotype criteria. Additionally, longitudinal studies report the deterioration of these criteria over time in DM1. Patients also exhibit psychological/cognitive and social factors that might contribute to frailty. Monitoring frailty criteria in the DM1 population could help to implement timely preventions and interventions to reduce the disease burden and severity of frailty symptoms.

Unveiling the multi-dimensional frailty network among older cancer survivors in China: A network analysis study

INTRODUCTION

Frailty has a significant impact on the overall quality of life of older cancer survivors, but the relationships among frailty symptoms are not well understood. This study aims to explore the specific associations among multidimensional symptoms of frailty among older cancer survivors by employing network analysis to provide supportive evidence for targeted interventions in the future.

MATERIALS AND METHODS

Data were obtained by cluster sampling from three large Grade-A tertiary hospitals in Shandong Province, China, and collected through face-to-face interviews by trained investigators. We included patients who were diagnosed with a solid malignant tumor at the age of 60 years or older. Frailty indicators were measured by the Groningen Frailty Indicator (GFI) and analyzed primarily through network analysis, including network estimation, centrality, and stability analysis. The relative importance of a node in a network was tested by centrality analyses, and Spearman correlations were applied to estimate the relationships between symptom pairs (symptom score) and symptom clusters (standardized symptom score) in the symptom network. In terms of centrality, the indexes of strength, closeness, and betweenness were adopted to measure the importance of nodes.

RESULTS

Five hundred and eight older cancer survivors were included, with an average age of 68.4 years (standard deviation [SD] = 5.4), and a higher proportion were male (n = 307[60.4%]). The prevalence of frailty among older cancer survivors was 58.9% (n = 299), with a mean GFI score of 4.46 (SD = 2.87). The strongest edge was between "dressing and undressing" and "going to the toilet" (r = 0.58). The nodes with the higher strength centrality were "going to the toilet" (rS=1.09), "walking around outside" (rS=0.97), and "part of social network" (rS=0.96); and the nodes with the higher closeness centrality were "mark physical fitness" (rC=0.005), "calm and relaxed" (rC=0.005), and "nervous or downhearted" (rC=0.005).

DISCUSSION

This study demonstrated that older cancer survivors in China have a high prevalence of frailty, with self-care and social participation-related symptoms playing a key role in the multidimensional network of frailty symptoms. Psychological symptoms can rapidly influence other symptoms within this network. Therefore, prioritizing psychological symptoms in the assessment of older adults with cancer is essential for effective frailty management.

Definition and assessment of psychological frailty in older adults: A scoping review

OBJECTIVES

The confusion surrounding psychological frailty and its components prompts the need for a standardized conceptual definition. To address this, we aimed to (1) identify the psychological variables included in multicomponent frailty assessment instruments used with older adults and examine their operationalization; and (2) formulate a thorough conceptualization of psychological frailty based on the variables identified.

METHODS

This study followed the most recent recommendations for conducting scoping reviews and is reported in accordance with PRISMA-ScR guidelines. We systematically searched the CINAHL, MEDLINE, PsycInfo, Scopus, and Web of Science databases, with additional searches in Google Scholar and reference lists.

RESULTS

Sixteen instruments were identified. The results suggested that: (1) In multicomponent frailty assessment instruments, psychological variables are poorly represented; (2) A wide variety of psychological variables are included in the instruments, the most frequent being cognitive functioning and affective functioning (e.g., depressive symptoms, emotional loneliness, anxiety symptoms, poor coping, and suicidal ideation); and (3) The way in which variables are referred to and operationalized varies across instruments.

CONCLUSIONS

Including both cognitive and affective variables in psychological frailty assessments may lead to inaccuracies. We suggest distinguishing between two separate dimensions within psychological frailty: cognitive frailty and affective frailty. A conceptual definition for each dimension is provided. This proposal aims to advance the debate regarding the conceptualization and assessment of psychological frailty, with further research and discussion needed to ensure its practical applicability.

Development of cognitive frailty screening tool among community-dwelling older adults

Purpose

To develop a brief screening tool consisting of twelve items that can be self-administered for rapid identification of older adults at risk of cognitive frailty (CF), named as Cognitive Frailty Screening Tool (CFST).

Patients and methods

A total of 1318 community-dwelling individuals aged 60 years and above were selected and assessed for cognitive frailty using a set of neuropsychology batteries and physical function tests. A binary logistic regression (BLR) was used to identify predictors of CF to be used as items in the screening tool. A suitable cut-off point was developed using receiver operating characteristic analysis.

Results

Twelve items were included in the screening tool, comprising of gender, education years, medical history, depressive symptoms and functional status as well as lifestyle activities. The area under the curve (AUC) was 0.817 (95 % CI:0.774-0.861), indicating an excellent discriminating power. The sensitivity and specificity for cut-off 7 were 80.8 % and 79.0 %, with an acceptable range of positive predictive value (PPV) (73.3 %) and negative predictive value (NPV) (85.2 %) for screening tools. Concurrent validity of CFST score with standard cognitive and frailty assessment tools shows a significant association with the total score of CFST with low to moderate correlation (p < 0.05 for all parameters).

Conclusion

CFST had good sensitivity and specificity and was valid for community-dwelling older adults. There is a need to evaluate further the cost-effectiveness of implementing CFST as a screening for the risk of CF in the community. Its usage in clinical settings needs further validation.

Profiles of physical frailty, social frailty, and cognitive impairment among older adults in rural areas of China: a latent profile analysis

Background

As China rapidly ages, it has now become a deeply aging society with the largest number of older individuals in the world. The issue is particularly severe in rural areas. With the aging population growing and the older population expanding, health problems are becoming more prevalent among older individuals, particularly frailty and cognitive impairments. This study aimed to identify the profiles of physical frailty, social frailty, and cognitive impairment among older adults and explore the influencing factors.

Methods

In this cross-sectional study, participants were recruited from six villages in four cities in Shandong Province, China from July to October 2023 through cluster random sampling. Latent profile analysis was used to determine the profiles of physical frailty, social frailty, and cognitive impairment. Chi-square tests and Mann-Whitney U tests were used for univariate analysis, while binary logistic regression was used to analyze the related factors.

Results

Seven hundred and sixty-nine older adult care in rural areas showed two profiles: the "high cognitive function and low frailty" group (73.7%, n = 567) and the "low cognitive function and high frailty" group (26.3%, n = 202). A binary logistic regression found that older people were more likely to be aged 80 or older (OR = 2.253, p = 0.029), have a low income level (OR = 1.051, p = 0.007), have one or two (OR = 2.287, p = 0.004), or more than three chronic diseases (OR = 3.092, p = 0.002), and report moderate (OR = 3.406, p = 0.024) or poor health status (OR = 9.085, p < 0.001) in the "low cognitive function and high frailty" group. Meanwhile, older adults who have completed high school (OR = 0.428, p = 0.005) or junior college and above (OR = 0.208, p = 0.009), and engage in adequate physical activity (OR = 0.319, p < 0.001) were more likely to be in the "high cognitive function and low frailty" group.

Conclusion

In the future, medical professors should increasingly prioritize promptly identifying and intervening in cognitive decline and frailty status in older individuals without delay.

Interventions that have potential to help older adults living with social frailty: a systematic scoping review

BACKGROUND

The impact of social frailty on older adults is profound including mortality risk, functional decline, falls, and disability. However, effective strategies that respond to the needs of socially frail older adults are lacking and few studies have unpacked how social determinants operate or how interventions can be adapted during periods requiring social distancing and isolation such as the COVID-19 pandemic. To address these gaps, we conducted a scoping review using JBI methodology to identify interventions that have the best potential to help socially frail older adults (age ≥65 years).

METHODS

We searched MEDLINE, CINAHL (EPSCO), EMBASE and COVID-19 databases and the grey literature. Eligibility criteria were developed using the PICOS framework. Our results were summarized descriptively according to study, patient, intervention and outcome characteristics. Data synthesis involved charting and categorizing identified interventions using a social frailty framework.  RESULTS: Of 263 included studies, we identified 495 interventions involving ~124,498 older adults who were mostly female. The largest proportion of older adults (40.5%) had a mean age range of 70-79 years. The 495 interventions were spread across four social frailty domains: social resource (40%), self-management (32%), social behavioural activity (28%), and general resource (0.4%). Of these, 189 interventions were effective for improving loneliness, social and health and wellbeing outcomes across psychological self-management, self-management education, leisure activity, physical activity, Information Communication Technology and socially assistive robot interventions. Sixty-three interventions were identified as feasible to be adapted during infectious disease outbreaks (e.g., COVID-19, flu) to help socially frail older adults.

CONCLUSIONS

Our scoping review identified promising interventions with the best potential to help older adults living with social frailty.

Decoding emotional resilience in aging: unveiling the interplay between daily functioning and emotional health

Background

EPs pose significant challenges to individual health and quality of life, attracting attention in public health as a risk factor for diminished quality of life and healthy life expectancy in middle-aged and older adult populations. Therefore, in the context of global aging, meticulous exploration of the factors behind emotional issues becomes paramount. Whether ADL can serve as a potential marker for EPs remains unclear. This study aims to provide new evidence for ADL as an early predictor of EPs through statistical analysis and validation using machine learning algorithms.

Methods

Data from the 2018 China Health and Retirement Longitudinal Study (CHARLS) national baseline survey, comprising 9,766 samples aged 45 and above, were utilized. ADL was assessed using the BI, while the presence of EPs was evaluated based on the record of "Diagnosed with Emotional Problems by a Doctor" in CHARLS data. Statistical analyses including independent samples t-test, chi-square test, Pearson correlation analysis, and multiple linear regression were conducted using SPSS 25.0. Machine learning algorithms, including Support Vector Machine (SVM), Decision Tree (DT), and Logistic Regression (LR), were implemented using Python 3.10.2.

Results

Population demographic analysis revealed a significantly lower average BI score of 65.044 in the "Diagnosed with Emotional Problems by a Doctor" group compared to 85.128 in the "Not diagnosed with Emotional Problems by a Doctor" group. Pearson correlation analysis indicated a significant negative correlation between ADL and EPs (r = -0.165, p < 0.001). Iterative analysis using stratified multiple linear regression across three different models demonstrated the persistent statistical significance of the negative correlation between ADL and EPs (B = -0.002, β = -0.186, t = -16.476, 95% CI = -0.002, -0.001, p = 0.000), confirming its stability. Machine learning algorithms validated our findings from statistical analysis, confirming the predictive accuracy of ADL for EPs. The area under the curve (AUC) for the three models were SVM-AUC = 0.700, DT-AUC = 0.742, and LR-AUC = 0.711. In experiments using other covariates and other covariates + BI, the overall prediction level of machine learning algorithms improved after adding BI, emphasizing the positive effect of ADL on EPs prediction.

Conclusion

This study, employing various statistical methods, identified a negative correlation between ADL and EPs, with machine learning algorithms confirming this finding. Impaired ADL increases susceptibility to EPs.

Defining and assessing psychological frailty in older adults: a scoping review protocol

INTRODUCTION

Frailty is widely acknowledged as a multidimensional construct encompassing physical, psychological and social aspects. However, the lack of consensus in defining and operationalising psychological frailty challenges the holistic approach to frailty advocated by health professionals. Consequently, there is a need to develop a comprehensive definition of psychological frailty based on contributions made by experts in the field, primarily existing frailty assessment tools. This scoping review will aim to identify the key psychological variables that are considered in frailty assessment tools used with older adults as well as to analyse how these psychological variables have been operationalised.

METHODS AND ANALYSIS

The study will be conducted in accordance with recommendations from several methodological frameworks for scoping reviews and will be reported following Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews statement guidelines. A systematic literature search will be performed in the CINAHL, MEDLINE, PsycInfo, Scopus and Web of Science databases, supplemented by a search in Google Scholar and reference lists. The focus will be on studies that describe the development of multicomponent frailty assessment tools including at least one psychological variable. Study selection and data extraction will be independently conducted by three reviewers working in pairs. Data will be presented in tabular form, and the data will be analysed using qualitative content analysis.

ETHICS AND DISSEMINATION

This study does not require ethical approval since it is based on secondary data analysis. The findings of the review will be disseminated through publication in a peer-reviewed scientific journal and will be presented at conferences and seminars.

TRIAL REGISTRATION NUMBER

The scoping review was registered in Open Science Framework on 29 March 2022 (https://osf.io/bn24y).

Demographic and biological factors in interrelationships between physical, cognitive, psychological, and social frailty in community-dwelling older adults: Data from the Birjand Longitudinal Aging Study (BLAS)

Complex interrelationships may exist among different types of frailty. This study aimed to evaluate the demographic and biological factors that influence the different types of frailty in community-dwelling older adults in Iran through a cross-sectional analysis of data obtained from the Birjand Longitudinal Aging Study. This study is an ongoing cohort study of people aged 60 years and over and employed a multistage stratified cluster random sampling. Anthropometric measures were obtained by nurses. The "Fried frailty phenotype" was defined as physical frailty. Cognitive frailty was assessed using the Mini-Mental State Examination. Social frailty was evaluated by some questions, and psychological frailty was assessed using a patient health questionnaire. Blood samples were taken after overnight fasting. All statistical analyses were performed using Stata12 (Texas, USA) and Python. Some type of frailty had been experienced by 62.27 % of the older adults. Cognitive frailty was the dominant type of frailty (55.69 %). Based on multivariate regression analysis, age, sex, education, and marital status were the influencing factors in all types of frailty. Network analysis revealed that physical, cognitive, psychological, and social frailty had synergistic effects on each other, and age and sex had dominant interactions with frailty types. Cognitive frailty was dominant compared with other types of frailty, indicating the need to detect cognitive frailty at the earliest stage and to implement an appropriate program to manage cognitive frailty in older adults.

Psychological aspects of rehabilitation nutrition: A position paper by the Japanese Association of Rehabilitation Nutrition (secondary publication)

Psychological aspects of rehabilitation nutrition affect physical, cognitive, and social rehabilitation nutrition. When depression is recognized, not only pharmacotherapy and psychotherapy, but also non-pharmacological therapies such as exercise, nutrition, psychosocial, and other interventions can be expected to improve depression. Therefore, accurate diagnosis and intervention without overlooking depression is important. Psychological aspects of preventive rehabilitation nutrition is also important because depression can be partially prevented by appropriate exercise and nutritional management. Even in the absence of psychological negatives, increasing more psychological positives from a positive psychology perspective can be useful for both patients and healthcare professionals. Positive rehabilitation nutrition interventions can increase more psychological positives, such as well-being, through cognitive-behavioral therapy and mindfulness on their own, as well as through interventions on environmental factors. Consequently, physical, cognitive, and social positives are also expected to be enhanced.

Network analysis of frailty indicators in hospitalized elderly patients: unveiling the role of depression and hemoglobin as core factors

BACKGROUND

Frailty is a significant concern among hospitalized older adults, influenced by multiple factors. Understanding the complex interactions between these variables can be facilitated through a network perspective.

AIM

This study aimed to identify the core factor and physiological indicator of frailty in hospitalized elderly patients and visualize their interactions within the network structure.

METHODS

Frailty was assessed using the Tilburg Frailty Indicators, with a score of 5 or higher indicating frailty. Additional variables related to sociodemographic, physical and clinical, psychological and cognitive aspects, as well as physiological indicators, were extracted from electronic health records. A partial correlation network analysis was conducted using an adaptive LASSO algorithm, based on univariate correlation and logistic regression, to examine the network structure and identify influential nodes.

RESULTS

The average age of participants was 70.74 ± 7.52 years, with 24.27% classified as frail. Frailty was associated with 38 of 145 initially included variables (P < 0.05). The network analysis revealed depression as the most central node, followed by drugs used, sleep disorders, loneliness, masticatory obstacles, drinking, and number of teeth missing. Hemoglobin emerged as the most central biochemical indicator in the network, based on network center index analysis (Strength = 4.858, Betweenness = 223, Closeness = 0.034).

CONCLUSIONS

Frailty in hospitalized older adults is influenced by various social, physical, and psychological factors, with depression as the core factor of utmost importance. Changes in hemoglobin levels could serve as an essential indicator. This innovative network approach provides insights into the multidimensional structure and relationships in real-world settings.

Prevalence of frailty in severe mental illness: findings from the UK Biobank

BACKGROUND

Severe mental illness (SMI) is associated with significant morbidity. Frailty combines biological ageing, comorbidity and psychosocial factors and can predict adverse health outcomes. Emerging evidence indicates that frailty is higher in individuals with SMI than in the general population, although studies have been limited by sample size.

AIMS

To describe the prevalence of frailty in people with SMI in a large cohort using three different frailty measures and examine the impact of demographic and sociodemographic variables.

METHOD

The UK Biobank survey data, which included individuals aged 37-73 years from England, Scotland and Wales from 2006 to 2010, with linked in-patient hospital episodes, were utilised. The prevalence of frailty in individuals with and without SMI was assessed through three frailty measures: frailty index, physical frailty phenotype (PFP) and Hospital Frailty Risk Score (HFRS). Stratified analysis and dichotomous logistic regression were conducted.

RESULTS

A frailty index could be calculated for 99.5% of the 502 412 UK Biobank participants and demonstrated greater prevalence of frailty in women and an increase with age. The prevalence of frailty for those with SMI was 3.19% (95% CI 3.0-3.4), 4.2% (95% CI 3.8-4.7) and 18% (95% CI 15-23) using the frailty index, PFP and HFRS respectively. The prevalence ratio was between 3 and 18 times higher than in those without SMI.

CONCLUSIONS

As a measure, frailty captures the known increase in morbidity associated with SMI and may potentially allow for earlier identification of those who will benefit from targeted interventions.