@Article{info:doi/10.2196/64853, author="Kang, Bada and Hong, Dahye and Yoon, Seolah and Kang, Chaeeun and Kim, Ivy Jennifer", title="Assessing Social Interaction and Loneliness and Their Association With Frailty Among Older Adults With Subjective Cognitive Decline or Mild Cognitive Impairment: Ecological Momentary Assessment Approach", journal="JMIR Mhealth Uhealth", year="2025", month="Apr", day="22", volume="13", pages="e64853", keywords="geriatric", keywords="older", keywords="elderly", keywords="ageing", keywords="association", keywords="correlation", keywords="cognitive impairment", keywords="ecological momentary assessment", keywords="frailty", keywords="mild behavioral impairment", keywords="dementia", keywords="Alzheimer", keywords="isolation", keywords="lonely", keywords="social", keywords="interaction", keywords="self-reported", keywords="psychogeriatrics", abstract="Background: Frail older adults are at greater risk of adverse health-related outcomes such as falls, disability, and mortality. Mild behavioral impairment (MBI), which is characterized by neurobehavioral symptoms in individuals without dementia, is a crucial factor in identifying at-risk groups and implementing early interventions for frail older adults. However, the specific role of social functioning, which encompasses social interaction and loneliness levels, in relation to frailty within this group remains unclear. Objective: This study investigated the association between frailty status, social interaction frequency, and loneliness levels among older adults with subjective cognitive decline (SCD) or mild cognitive impairment (MCI) while adjusting for MBI symptoms in 2 contexts: the presence and severity of MBI symptoms. Methods: Older adults with SCD or MCI were recruited from an outpatient clinic specializing in the early diagnosis and care management of dementia at a community health center, as well as from a community service center in Seoul, South Korea. Using an ecological momentary assessment approach, participants reported their daily social interaction frequency and loneliness level via a mobile app, 4 times daily for 2 weeks. Frailty status, the outcome variable, was assessed using the Korean version of the frailty phenotype questionnaire. Additionally, MBI symptoms were assessed using the 34-item MBI-Checklist covering 5 domains. Multinomial logistic regression analyses were performed to investigate the association between frailty status (robust, prefrail, and frail), and the independent variables, adjusting for the presence or severity of MBI symptoms. Results: Among the 101 participants analyzed, 29.7\% (n=30) of participants were classified as prefrail, and 12.8\% (n=13) of participants were classified as frail. Higher average daily social interaction scores were consistently associated with lower odds of a frail status compared to a robust status. This was evident in the models adjusted for both the global presence (relative risk ratio [RRR] 0.18, P=.02) and global severity (RRR 0.20, P=.02) of MBI symptoms. Conclusions: Frequent social interaction was inversely associated with frail status in older adults with SCD or MCI, even after adjusting for the presence and severity of MBI symptoms. These findings highlight the potential of social functioning as a modifiable factor for addressing frailty among older adults at risk of cognitive and functional decline. Future prospective studies using real-time measurements are needed to refine these findings and further investigate additional risk factors and functional outcomes in this group. ", doi="10.2196/64853", url="https://mhealth.jmir.org/2025/1/e64853", url="http://www.ncbi.nlm.nih.gov/pubmed/40210431" } @Article{info:doi/10.2196/64254, author="Ormaz{\'a}bal, Yony and Arauna, Diego and Cantillana, Carlos Juan and Palomo, Iv{\'a}n and Fuentes, Eduardo and Mena, Carlos", title="Unveiling the Frailty Spatial Patterns Among Chilean Older Persons by Exploring Sociodemographic and Urbanistic Influences Based on Geographic Information Systems: Cross-Sectional Study", journal="JMIR Aging", year="2025", month="Apr", day="17", volume="8", pages="e64254", keywords="aging", keywords="frailty", keywords="geospatial clustering", keywords="urban factors", keywords="neighborhood conditions.", abstract="Background: Frailty syndrome increases the vulnerability of older adults. The growing proportion of older adults highlights the need to better understand the factors contributing to the prevalence of frailty. Current evidence suggests that geomatic tools integrating geolocation can provide valuable information for implementing preventive measures by enhancing the urban physical environment. Objective: The aim of this study was to analyze the relationship between various elements of the urban physical environment and the level of frailty syndrome in older Chilean people. Methods: A cohort of 251 adults aged 65 years or older from Talca City, Chile, underwent comprehensive medical assessments and were geographically mapped within a Geographic Information Systems database. Frailty was determined using the Fried frailty criteria. The spatial analysis of the frailty was conducted in conjunction with layers depicting urban physical facilities within the city, including vegetables and fruit shops, senior centers or communities, pharmacies, emergency health centers, main squares and parks, family or community health centers, and sports facilities such as stadiums. Results: The studied cohort was composed of 187 women and 64 men, with no significant differences in age and BMI between genders. Frailty prevalence varied significantly across clusters, with Cluster 3 showing the highest prevalence (14/47, P=.01). Frail individuals resided significantly closer to emergency health centers (960 [SE 904] m vs 1352 [SE 936] m, P=.04), main squares/parks (1550 [SE 130] m vs. 2048 [SE 105] m, P=.03), and sports fields (3040 [SE 236] m vs 4457 [SE 322]m, P=.04) compared with nonfrail individuals. There were no significant differences in urban quality index across frailty groups, but frail individuals lived in areas with higher population density (0.013 [SE 0.001] vs 0.01 [SE 0.0007], P=.03). Conclusions: Frail individuals exhibit geospatial patterns suggesting intentional proximity to health facilities, sports venues, and urban facilities, revealing associations with adaptive responses to frailty and socioeconomic factors. This highlights the crucial intersection of urban environments and frailty, which is important for geriatric medicine and public health initiatives. ", doi="10.2196/64254", url="https://aging.jmir.org/2025/1/e64254" } @Article{info:doi/10.2196/66723, author="Chu, Jingjing and Li, Ying and Wang, Xinyi and Xu, Qun and Xu, Zherong", title="Development of a Longitudinal Model for Disability Prediction in Older Adults in China: Analysis of CHARLS Data (2015-2020)", journal="JMIR Aging", year="2025", month="Apr", day="17", volume="8", pages="e66723", keywords="disability", keywords="prediction model", keywords="older adults", keywords="China Health and Retirement Longitudinal Study", keywords="CHARLS", keywords="medical resources allocation", abstract="Background: Disability profoundly affects older adults' quality of life and imposes considerable burdens on health care systems in China's aging society. Timely predictive models are essential for early intervention. Objective: We aimed to build effective predictive models of disability for early intervention and management in older adults in China, integrating physical, cognitive, physiological, and psychological factors. Methods: Data from the China Health and Retirement Longitudinal Study (CHARLS), spanning from 2015 to 2020 and involving 2450 older individuals initially in good health, were analyzed. The dataset was randomly divided into a training set with 70\% data and a testing set with 30\% data. LASSO regression with 10-fold cross-validation identified key predictors, which were then used to develop an Extreme Gradient Boosting (XGBoost) model. Model performance was evaluated using receiever operating characteristic curves, calibration curves, and clinical decision and impact curves. Variable contributions were interpreted using SHapley Additive exPlanations (SHAP) values. Results: LASSO regression was used to evaluate 36 potential predictors, resulting in a model incorporating 9 key variables: age, hand grip strength, standing balance, the 5-repetition chair stand test (CS-5), pain, depression, cognition, respiratory function, and comorbidities. The XGBoost model demonstrated an area under the curve of 0.846 (95\% CI 0.825?0.866) for the training set and 0.698 (95\% CI 0.654?0.743) for the testing set. Calibration curves demonstrated reliable predictive accuracy, with mean absolute errors of 0.001 and 0.011 for the training and testing sets, respectively. Clinical decision and impact curves demonstrated significant utility across risk thresholds. SHAP analysis identified pain, respiratory function, and age as top predictors, highlighting their substantial roles in disability risk. Hand grip and the CS-5 also significantly influenced the model. A web-based application was developed for personalized risk assessment and decision-making. Conclusion: A reliable predictive model for 5-year disability risk in Chinese older adults was developed and validated. This model enables the identification of high-risk individuals, supports early interventions, and optimizes resource allocation. Future efforts will focus on updating the model with new CHARLS data and validating it with external datasets. ", doi="10.2196/66723", url="https://aging.jmir.org/2025/1/e66723" } @Article{info:doi/10.2196/63928, author="Shin, Jinyoung and Kweon, Jung Hyuk and Choi, Jaekyung", title="Assessment of Gait Parameters Using Wearable Sensors and Their Association With Muscle Mass, Strength, and Physical Performance in Korean Older Adults: Cross-Sectional Study", journal="JMIR Form Res", year="2025", month="Apr", day="10", volume="9", pages="e63928", keywords="gait analysis", keywords="sarcopenia", keywords="wearable electronic devices", keywords="muscle mass", keywords="physical performance", keywords="older adults", keywords="geriatric", keywords="cross-sectional study", keywords="outpatient clinic", keywords="Korea", keywords="mHealth", keywords="mobile health", abstract="Background: Gait speed indicates the onset or decline of physical performance in sarcopenia. However, real-time measurements of other gait parameters, such as step length, stride length, step width, and support time, are limited. The advent of wearable technology has facilitated the measurement of these parameters, necessitating further investigation into their potential applications. Objective: This study aimed to investigate the relationship between gait parameters measured using wearable sensors and muscle mass, strength, and physical performance in community-dwelling older adults. Methods: In a cross-sectional study of 91 participants aged ?65 years, gait parameters, such as step count, step length, cadence, single and double support times, vertical oscillation, and instantaneous vertical loading rate (IVLR), measured using a wireless earbud device, were analyzed on the basis of the appendicular skeletal muscle mass index (SMI), calf circumference, handgrip strength, 5-time chair stand test, short physical performance battery (SPPB), and the SARC-F (strength, assistance with walking, rise from a chair, climb stairs and fall frequency) questionnaire. This study was conducted from July 10 to November 1, 2023, at an outpatient clinic of a university hospital in Seoul, Korea. Multiple regression analysis was performed to investigate independent associations after adjusting for age, sex, BMI, and comorbidities. Results: Among 91 participants (45 men and 46 women; mean age 74.1 years for men and 73.6 years for women), gait speed and vertical oscillation showed negative associations with their performance in the 5-time chair stand test (P<.001) and SARC-F and positive associations with their performance in the SPPB (P<.001). Vertical oscillations were also associated with grip strength (P=.003). Single and double support times were associated with performance in the 5-time chair stand test and SPPB (P<.001). In addition, double support time was associated with SARC-F scores (P<.001). Gait speed, support time, vertical oscillation, and IVLR showed independent associations with performance in the 5-time chair stand test and SPPB (P<.001), both related to muscle strength or physical performance. Gait speed, double support time, and vertical oscillation all had significant associations with SARC-F scores. Conclusions: This study demonstrated a significant association between gait monitoring using wearable sensors and quantitative assessments of muscle strength and physical performance in older people. Furthermore, this study substantiated the extensive applicability of diverse gait parameters in predicting sarcopenia. ", doi="10.2196/63928", url="https://formative.jmir.org/2025/1/e63928" } @Article{info:doi/10.2196/62942, author="Isaradech, Natthanaphop and Sirikul, Wachiranun and Buawangpong, Nida and Siviroj, Penprapa and Kitro, Amornphat", title="Machine Learning Models for Frailty Classification of Older Adults in Northern Thailand: Model Development and Validation Study", journal="JMIR Aging", year="2025", month="Apr", day="2", volume="8", pages="e62942", keywords="aged care", keywords="gerontology", keywords="geriatric", keywords="old", keywords="aging", keywords="clinical decision support", keywords="delivering health information and knowledge to the public", keywords="diagnostic systems", keywords="digital health", keywords="epidemiology", keywords="surveillance", keywords="diagnosis", keywords="frailty", keywords="machine learning", keywords="prediction", keywords="predictive", keywords="AI", keywords="artificial intelligence", keywords="Thailand", keywords="community dwelling", keywords="health care intervention", keywords="patient care", abstract="Background: Frailty is defined as a clinical state of increased vulnerability due to the age-associated decline of an individual's physical function resulting in increased morbidity and mortality when exposed to acute stressors. Early identification and management can reverse individuals with frailty to being robust once more. However, we found no integration of machine learning (ML) tools and frailty screening and surveillance studies in Thailand despite the abundance of evidence of frailty assessment using ML globally and in Asia. Objective: We propose an approach for early diagnosis of frailty in community-dwelling older individuals in Thailand using an ML model generated from individual characteristics and anthropometric data. Methods: Datasets including 2692 community-dwelling Thai older adults in Lampang from 2016 and 2017 were used for model development and internal validation. The derived models were externally validated with a dataset of community-dwelling older adults in Chiang Mai from 2021. The ML algorithms implemented in this study include the k-nearest neighbors algorithm, random forest ML algorithms, multilayer perceptron artificial neural network, logistic regression models, gradient boosting classifier, and linear support vector machine classifier. Results: Logistic regression showed the best overall discrimination performance with a mean area under the receiver operating characteristic curve of 0.81 (95\% CI 0.75?0.86) in the internal validation dataset and 0.75 (95\% CI 0.71?0.78) in the external validation dataset. The model was also well-calibrated to the expected probability of the external validation dataset. Conclusions: Our findings showed that our models have the potential to be utilized as a screening tool using simple, accessible demographic and explainable clinical variables in Thai community-dwelling older persons to identify individuals with frailty who require early intervention to become physically robust. ", doi="10.2196/62942", url="https://aging.jmir.org/2025/1/e62942" } @Article{info:doi/10.2196/51975, author="Midao, Luis and Duarte, Mafalda and Sampaio, Rute and Almada, Marta and Dias, Camila Cl{\'a}udia and Pa{\'u}l, Constan{\c{c}}a and Costa, El{\'i}sio", title="FRAILSURVEY---an mHealth App for Self-Assessment of Frailty Based on the Portuguese Version of the Groningen Frailty Indicator: Validation and Reliability Study", journal="JMIR Form Res", year="2025", month="Mar", day="7", volume="9", pages="e51975", keywords="frailty", keywords="mHealth", keywords="assessment", keywords="validation", keywords="GFI", keywords="reliability", keywords="self-assessment", keywords="Groningen Frailty Indicator", keywords="FRAILSURVEY", keywords="mobile phone", abstract="Background: Portugal is facing the challenge of population ageing, with a notable increase in the proportion of older individuals. This has positioned the country among those in Europe with a high prevalence of frailty. Frailty, a geriatric syndrome characterized by diminished physiological reserve and heightened vulnerability to stressors, imposes a substantial burden on public health. Objective: This study seeks to address two primary objectives: (1) translation and psychometric evaluation of the European Portuguese version of the Groningen Frailty Indicator (GFI); and (2) development and evaluation of the FRAILSURVEY app, a novel assessment tool for frailty based on the GFI. By achieving these objectives, the study aims to enhance the accuracy and reliability of frailty assessment in the Portuguese context, ultimately contributing to improved health care outcomes for older individuals in the region. Methods: To accomplish the objectives of the study, a comprehensive research methodology was used. The study comprised 2 major phases: the initial translation and validation of the GFI into European Portuguese and the development of the FRAILSURVEY app. Following this, an extensive examination of the app's validity and reliability was conducted compared with the conventional paper version of the GFI. A randomized repeated crossover design was used to ensure rigorous evaluation of both assessment methods, using both the paper form of the GFI and the smartphone-based app FRAILSURVEY. Results: The findings of the study revealed promising outcomes in line with the research objectives. The meticulous translation process yielded a final version of the GFI with robust psychometric properties, ensuring clarity and comprehensibility for participants. The study included 522 participants, predominantly women (367/522, 70.3\%), with a mean age of 73.7 (SD 6.7) years. Psychometric evaluation of the European Portuguese GFI in paper form demonstrates good reliability (internal consistency: Cronbach a value of 0.759; temporal stability: intraclass correlation coefficient=0.974) and construct validity (revealing a 4D structure explaining 56\% of variance). Evaluation of the app-based European Portuguese GFI indicates good reliability (interinstrument reliability: Cohen k=0.790; temporal stability: intraclass correlation coefficient=0.800) and concurrent validity (r=0.694; P<.001). Conclusions: Both the smartphone-based app and the paper version of the GFI were feasible and acceptable for use. The findings supported that FRAILSURVEY exhibited comparable validity and reliability to its paper counterpart. FRAILSURVEY uses a standardized and validated assessment tool, offering objective and consistent measurements while eliminating subjective biases, enhancing accuracy, and ensuring reliability. This app holds promising potential for aiding health care professionals in identifying frailty in older individuals, enabling early intervention, and improving the management of adverse health outcomes associated with this syndrome. Its integration with electronic health records and other data may lead to personalized interventions, improving frailty management and health outcomes for at-risk individuals. ", doi="10.2196/51975", url="https://formative.jmir.org/2025/1/e51975", url="http://www.ncbi.nlm.nih.gov/pubmed/40053720" } @Article{info:doi/10.2196/60683, author="Tang, Wen-Zhen and Zhu, Sheng-Rui and Mo, Shu-Tian and Xie, Yuan-Xi and Tan, Zheng-Ke-Ke and Teng, Yan-Juan and Jia, Kui", title="Predictive Value of Frailty on Outcomes of Patients With Cirrhosis: Systematic Review and Meta-Analysis", journal="JMIR Med Inform", year="2025", month="Feb", day="27", volume="13", pages="e60683", keywords="frailty", keywords="cirrhosis", keywords="diagnostic efficiency", keywords="survival", keywords="meta-analysis", keywords="prognostic factor", keywords="systematic review", abstract="Background: Frailty is one of the most common symptoms in patients with cirrhosis. Many researchers have identified it as a prognostic factor for patients with cirrhosis. However, no quantitative meta-analysis has evaluated the prognostic value of frailty in patients with cirrhosis. Objective: This systematic review and meta-analysis aimed to assess the prognostic significance of frailty in patients with cirrhosis. Methods: The systematic review was conducted in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) recommendations. We conducted a comprehensive search of the literature using databases such as PubMed, Cochrane Library, Embase, and Web of Science, as well as China National Knowledge Infrastructure, encompassing the period from inception to 22 December 2023. Data were extracted for frailty to predict adverse outcomes in patients with cirrhosis. RevMan (version 5.3) and R (version 4.2.2) were used to assess the extracted data. Results: A total of 26 studies with 9597 patients with cirrhosis were included. Compared with patients having low or no frailty, the frail group had a higher mortality rate (relative ratio, RR=2.07, 95\% CI 1.82?2.34, P<.001), higher readmission rate (RR=1.50, 95\% CI 1.22?1.84, P<.001), and lower quality of life (RR=5.78, 95\% CI 2.25?14.82, P<.001). The summary receiver operator characteristic (SROC) curve of frailty for mortality in patients with cirrhosis showed that the false positive rate (FPR) was 0.25 (95\% CI 0.17-0.34), diagnostic odds ratio (DOR) was 4.17 (95\% CI 2.93-5.93), sensitivity was 0.54 (95\% CI 0.39-0.69), and specificity was 0.73 (95\% CI 0.64-0.81). The SROC curve of readmission showed that the FPR, DOR, sensitivity, and specificity were 0.39 (95\% CI 0.17-0.66), 1.38 (95\% CI 0.64-2.93), 0.46 (95\% CI 0.28-0.64), and 0.60 (95\% CI 0.28-0.85), respectively. Conclusions: This meta-analysis demonstrated that frailty is a reliable prognostic predictor of outcomes in patients with cirrhosis. To enhance the prognosis of patients with cirrhosis, more studies on frailty screening are required. Trial Registration: PROSPERO CRD42024497698; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=497698 ", doi="10.2196/60683", url="https://medinform.jmir.org/2025/1/e60683" } @Article{info:doi/10.2196/66440, author="Khalighi, Mehraneh and Thomas, C. Amy and Brown, J. Karl and Ritchey, C. Katherine", title="Agreement Between Provider-Completed and Patient-Completed Preoperative Frailty Screening Using the Clinical Risk Analysis Index: Cross-Sectional Questionnaire Study", journal="JMIR Perioper Med", year="2025", month="Feb", day="10", volume="8", pages="e66440", keywords="Risk Analysis Index", keywords="preoperative screening", keywords="questionnaire", keywords="frailty", keywords="self-reported", keywords="veteran", keywords="hip", keywords="knee", keywords="arthroplasty", keywords="elective surgery", keywords="cross-sectional", keywords="quality improvement", abstract="Background: Frailty is associated with postoperative morbidity and mortality. Preoperative screening and management of persons with frailty improves postoperative outcomes. The Clinical Risk Analysis Index (RAI-C) is a validated provider-based screening tool for assessing frailty in presurgical populations. Patient self-screening for frailty may provide an alternative to provider-based screening if resources are limited; however, the agreement between these 2 methods has not been previously explored. Objective: The objective of our study was to examine provider-completed versus patient-completed RAI-C assessments to identify areas of disagreement between the 2 methods and inform best practices for RAI-C screening implementation. Methods: Orthopedic physicians and physician assistants completed the RAI-C assessment on veterans aged 65 years and older undergoing elective total joint arthroplasty (eg, total hip or knee arthroplasty) and documented scores into the electronic health record during their preoperative clinic evaluation. Participants were then mailed the same RAI-C form after preoperative evaluation and returned responses to study coordinators. Agreement between provider-completed and patient-completed RAI-C assessments and differences within individual domains were compared. Results: A total of 49 participants aged 65 years and older presenting for total joint arthroplasty underwent RAI-C assessment between November 2022 and August 2023. In total, 41\% (20/49) of participants completed and returned an independent postvisit RAI-C assessment before surgery and within 180 days of their initial evaluation. There was a moderate but statistically significant correlation between provider-completed and patient-completed RAI-C assessments (r=0.62; 95\% CI 0.25-0.83; P=.003). Provider-completed and patient-completed RAI-C assessments resulted in the same frailty classification in 60\% (12/20) of participants, but 40\% (8/20) of participants were reclassified to a more frail category based on patient-completed assessment. Agreement was the lowest between provider-completed and patient-completed screening questions regarding memory and activities of daily living. Conclusions: RAI-C had moderate agreement when completed by providers versus the participants themselves, with more than a third of patient-completed screens resulting in a higher frailty classification. Future studies will need to explore the differences between and accuracy of RAI-C screening approaches to inform best practices for preoperative RAI-C assessment implementation. ", doi="10.2196/66440", url="https://periop.jmir.org/2025/1/e66440", url="http://www.ncbi.nlm.nih.gov/pubmed/39928399" } @Article{info:doi/10.2196/50026, author="Jang, Jieun and Kim, Anna and Choi, Mingee and McCarthy, P. Ellen and Olivieri-Mui, Brianne and Park, Mi Chan and Kim, Jae-Hyun and Shin, Jaeyong and Kim, Hyun Dae", title="Association of Frailty Index at 66 Years of Age with Health Care Costs and Utilization Over 10 Years in Korea: Retrospective Cohort Study", journal="JMIR Public Health Surveill", year="2025", month="Jan", day="27", volume="11", pages="e50026", keywords="frailty index", keywords="health care costs", keywords="health care utilization", keywords="elderly", keywords="Korea", keywords="frailty", keywords="aging", keywords="utilization", keywords="older adults", keywords="sociodemographic", keywords="cost", keywords="prevention", abstract="Background: The long-term economic impact of frailty measured at the beginning of elderhood is unknown. Objective: The objective of our study was to examine the association between an individual's frailty index at 66 years of age and their health care costs and utilization over 10 years. Methods: This retrospective cohort study included 215,887 Koreans who participated in the National Screening Program for Transitional Ages at 66 years of age between 2007?2009. Frailty was categorized using a 39-item deficit accumulation frailty index: robust (<0.15), prefrail (0.15?0.24), and frail (?0.25). The primary outcome was total health care cost, while the secondary outcomes were inpatient and outpatient health care costs, inpatient days, and number of outpatient visits. Generalized estimating equations with a gamma distribution and identity link function were used to investigate the association between the frailty index and health care costs and utilization until December 31, 2019. Results: The study population included 53.3\% (n=115,113) women, 32.9\% (n=71,082) with prefrailty, and 9.7\% (n=21,010) with frailty. The frailty level at 66 years of age was associated with higher cumulative total costs (robust to frail: \$19,815 to \$28.281; P<.001), inpatient costs (US \$11,189 to US \$16,627; P<.001), and outpatient costs (US \$8,625 to US \$11,654; P<.001) over the next 10 years. In the robust group, a one-year increase in age was associated with increased total health care costs (mean change per beneficiary per year: US \$206.2; SE: \$1.2; P<.001), inpatient costs (US \$126.8; SE: \$1.0; P<.001), and outpatient costs (US \$74.4; SE: \$0.4; P<.001). In the frail group, the increase in total health care costs was greater compared to the robust group (difference in mean cost per beneficiary per year: US \$120.9; SE: \$5.3; P<.001), inpatient costs (US \$102.8; SE: \$5.22; P<.001), and outpatient costs (US \$15.6; SE: \$1.5; P<.001). Similar results were observed for health care utilization (P<.001). Among the robust group, a one-year increase in age was associated with increased inpatient days (mean change per beneficiary per year: 0.9 d; P<.001) and outpatient visits (2.1 visits; P<.001). In the frail group, inpatient days increased annually compared to the robust group (difference in the mean inpatient days per beneficiary per year: 1.5 d; P<.001), while outpatient visits increased to a lesser extent (difference in the mean outpatient visits per beneficiary per year: ?0.2 visits; P<.001). Conclusions: Our study demonstrates the potential utility of assessing frailty at 66 years of age in identifying older adults who are more likely to incur high health care costs and utilize health care services over the subsequent 10 years. The long-term high health care costs and utilization associated with frailty and prefrailty warrants public health strategies to prevent and manage frailty in aging populations. ", doi="10.2196/50026", url="https://publichealth.jmir.org/2025/1/e50026" } @Article{info:doi/10.2196/57298, author="Kim, Taehwan and Choi, Jung-Yeon and Ko, Jin Myung and Kim, Kwang-il", title="Development and Validation of a Machine Learning Method Using Vocal Biomarkers for Identifying Frailty in Community-Dwelling Older Adults: Cross-Sectional Study", journal="JMIR Med Inform", year="2025", month="Jan", day="16", volume="13", pages="e57298", keywords="frailty", keywords="cross-sectional study", keywords="vocal biomarkers", keywords="older adults", keywords="artificial intelligence", keywords="machine learning", keywords="classification model", keywords="self-supervised", abstract="Background: The two most commonly used methods to identify frailty are the frailty phenotype and the frailty index. However, both methods have limitations in clinical application. In addition, methods for measuring frailty have not yet been standardized. Objective: We aimed to develop and validate a classification model for predicting frailty status using vocal biomarkers in community-dwelling older adults, based on voice recordings obtained from the picture description task (PDT). Methods: We recruited 127 participants aged 50 years and older and collected clinical information through a short form of the Comprehensive Geriatric Assessment scale. Voice recordings were collected with a tablet device during the Korean version of the PDT, and we preprocessed audio data to remove background noise before feature extraction. Three artificial intelligence (AI) models were developed for identifying frailty status: SpeechAI (using speech data only), DemoAI (using demographic data only), and DemoSpeechAI (combining both data types). Results: Our models were trained and evaluated on the basis of 5-fold cross-validation for 127 participants and compared. The SpeechAI model, using deep learning--based acoustic features, outperformed in terms of accuracy and area under the receiver operating characteristic curve (AUC), 80.4\% (95\% CI 76.89\%?83.91\%) and 0.89 (95\% CI 0.86?0.92), respectively, while the model using only demographics showed an accuracy of 67.96\% (95\% CI 67.63\%?68.29\%) and an AUC of 0.74 (95\% CI 0.73?0.75). The SpeechAI model outperformed the model using only demographics significantly in AUC (t4=8.705 [2-sided]; P<.001). The DemoSpeechAI model, which combined demographics with deep learning--based acoustic features, showed superior performance (accuracy 85.6\%, 95\% CI 80.03\%?91.17\% and AUC 0.93, 95\% CI 0.89?0.97), but there was no significant difference in AUC between the SpeechAI and DemoSpeechAI models (t4=1.057 [2-sided]; P=.35). Compared with models using traditional acoustic features from the openSMILE toolkit, the SpeechAI model demonstrated superior performance (AUC 0.89) over traditional methods (logistic regression: AUC 0.62; decision tree: AUC 0.57; random forest: AUC 0.66). Conclusions: Our findings demonstrate that vocal biomarkers derived from deep learning--based acoustic features can be effectively used to predict frailty status in community-dwelling older adults. The SpeechAI model showed promising accuracy and AUC, outperforming models based solely on demographic data or traditional acoustic features. Furthermore, while the combined DemoSpeechAI model showed slightly improved performance over the SpeechAI model, the difference was not statistically significant. These results suggest that speech-based AI models offer a noninvasive, scalable method for frailty detection, potentially streamlining assessments in clinical and community settings. ", doi="10.2196/57298", url="https://medinform.jmir.org/2025/1/e57298" } @Article{info:doi/10.2196/64636, author="Rong, Jian and Pathiravasan, H. Chathurangi and Zhang, Yuankai and Faro, M. Jamie and Wang, Xuzhi and Schramm, Eric and Borrelli, Belinda and Benjamin, J. Emelia and Liu, Chunyu and Murabito, M. Joanne", title="Baseline Smartphone App Survey Return in the Electronic Framingham Heart Study Offspring and Omni 1 Study: eCohort Study", journal="JMIR Aging", year="2024", month="Dec", day="31", volume="7", pages="e64636", keywords="mHealth", keywords="mobile health", keywords="mobile application", keywords="smartphone", keywords="digital health", keywords="digital technology", keywords="digital intervention", keywords="gerontology", keywords="geriatric", keywords="older adult", keywords="aging", keywords="eFHS", keywords="eCohort", keywords="smartphone app", keywords="baseline app surveys", keywords="Framingham Heart Study", keywords="health information", keywords="information collection", keywords="mobile phone", abstract="Background: Smartphone apps can be used to monitor chronic conditions and offer opportunities for self-assessment conveniently at home. However, few digital studies include older adults. Objective: We aim to describe a new electronic cohort of older adults embedded in the Framingham Heart Study including baseline smartphone survey return rates and survey completion rates by smartphone type (iPhone [Apple Inc] and Android [Google LLC] users). We also aim to report survey results for selected baseline surveys and participant experience with this study's app. Methods: Framingham Heart Study Offspring and Omni (multiethnic cohort) participants who owned a smartphone were invited to download this study's app that contained a range of survey types to report on different aspects of health including self-reported measures from the Patient-Reported Outcomes Measurement Information System (PROMIS). iPhone users also completed 4 tasks including 2 cognitive and 2 physical function testing tasks. Baseline survey return and completion rates were calculated for 12 surveys and compared between iPhone and Android users. We calculated standardized scores for the PROMIS surveys. The Mobile App Rating Scale (MARS) was deployed 30 days after enrollment to obtain participant feedback on app functionality and aesthetics. Results: We enrolled 611 smartphone users (average age 73.6, SD 6.3 y; n=346, 56.6\% women; n=88, 14.4\% Omni participants; 478, 78.2\% iPhone users) and 596 (97.5\%) returned at least 1 baseline survey. iPhone users had higher app survey return rates than Android users for each survey (range 85.5\% to 98.3\% vs 73.8\% to 95.2\%, respectively), but survey completion rates did not differ in the 2 smartphone groups. The return rate for the 4 iPhone tasks ranged from 80.9\% (380/470) for the gait task to 88.9\% (418/470) for the Trail Making Test task. The Electronic Framingham Heart Study participants had better standardized t scores in 6 of 7 PROMIS surveys compared to the general population mean (t score=50) including higher cognitive function (n=55.6) and lower fatigue (n=45.5). Among 469 participants who returned the MARS survey, app functionality and aesthetics was rated high (total MARS score=8.6 on a 1?10 scale). Conclusions: We effectively engaged community-dwelling older adults to use a smartphone app designed to collect health information relevant to older adults. High app survey return rates and very high app survey completion rates were observed along with high participant rating of this study's app. ", doi="10.2196/64636", url="https://aging.jmir.org/2024/1/e64636" } @Article{info:doi/10.2196/57320, author="Chan, Andrew and Cai, Joanne and Qian, Linna and Coutts, Brendan and Phan, Steven and Gregson, Geoff and Lipsett, Michael and R{\'i}os Rinc{\'o}n, M. Adriana", title="In-Home Positioning for Remote Home Health Monitoring in Older Adults: Systematic Review", journal="JMIR Aging", year="2024", month="Dec", day="2", volume="7", pages="e57320", keywords="gerontology", keywords="geriatrics", keywords="older adult", keywords="elderly", keywords="aging", keywords="aging-in-place", keywords="localization", keywords="ambient sensor", keywords="wearable sensor", keywords="acceptability", keywords="home monitor", keywords="health monitor", keywords="technology", keywords="digital health", keywords="e-health", keywords="telehealth", keywords="clinical studies", keywords="cognitive impairment", keywords="neuro", keywords="cognition", abstract="Background: With the growing proportion of Canadians aged >65 years, smart home and health monitoring technologies may help older adults manage chronic disease and support aging in place. Localization technologies have been used to support the management of frailty and dementia by detecting activities in the home. Objective: This systematic review aims to summarize the clinical evidence for in-home localization technologies, review the acceptability of monitoring, and summarize the range of technologies being used for in-home localization. Methods: The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology was followed. MEDLINE, Embase, CINAHL, and Scopus were searched with 2 reviewers performing screening, extractions, and quality assessments. Results: A total of 1935 articles were found, with 36 technology-focused articles and 10 articles that reported on patient outcomes being included. From moderate- to high-quality studies, 2 studies reported mixed results on identifying mild cognitive dementia or frailty, while 4 studies reported mixed results on the acceptability of localization technology. Technologies included ambient sensors; Bluetooth- or Wi-Fi--received signal strength; localizer tags using radio frequency identification, ultra-wideband, Zigbee, or GPS; and inertial measurement units with localizer tags. Conclusions: The clinical utility of localization remains mixed, with in-home sensors not being able to differentiate between older adults with healthy cognition and older adults with mild cognitive impairment. However, frailty was detectable using in-home sensors. Acceptability is moderately positive, particularly with ambient sensors. Localization technologies can achieve room detection accuracies up to 92\% and linear accuracies of up to 5-20 cm that may be promising for future clinical applications. Trial Registration: PROSPERO CRD42022339845; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=339845 ", doi="10.2196/57320", url="https://aging.jmir.org/2024/1/e57320" } @Article{info:doi/10.2196/58980, author="Mardini, T. Mamoun and Bai, Chen and Bavry, A. Anthony and Zaghloul, Ahmed and Anderson, David R. and Price, Crenshaw Catherine E. and Al-Ani, Z. Mohammad A.", title="Enhancing Frailty Assessments for Transcatheter Aortic Valve Replacement Patients Using Structured and Unstructured Data: Real-World Evidence Study", journal="JMIR Aging", year="2024", month="Nov", day="27", volume="7", pages="e58980", keywords="transcatheter aortic valve replacement", keywords="frailty", keywords="cardiology", keywords="machine learning", keywords="TAVR", keywords="minimally invasive surgery", keywords="cardiac surgery", keywords="real-world data", keywords="topic modeling", keywords="clinical notes", keywords="electronic health record", keywords="EHR", abstract="Background: Transcatheter aortic valve replacement (TAVR) is a commonly used treatment for severe aortic stenosis. As degenerative aortic stenosis is primarily a disease afflicting older adults, a frailty assessment is essential to patient selection and optimal periprocedural outcomes. Objective: This study aimed to enhance frailty assessments of TAVR candidates by integrating real-world structured and unstructured data. Methods: This study analyzed data from 14,000 patients between January 2018 and December 2019 to assess frailty in TAVR patients at the University of Florida. Frailty was identified using the Fried criteria, which includes weight loss, exhaustion, walking speed, grip strength, and physical activity. Latent Dirichlet allocation for topic modeling and Extreme Gradient Boosting for frailty prediction were applied to unstructured clinical notes and structured electronic health record (EHR) data. We also used least absolute shrinkage and selection operator regression for feature selection. Model performance was rigorously evaluated using nested cross-validation, ensuring the generalizability of the findings. Results: Model performance was significantly improved by combining unstructured clinical notes with structured EHR data, achieving an area under the receiver operating characteristic curve of 0.82 (SD 0.07), which surpassed the EHR-only model's area under the receiver operating characteristic curve of 0.64 (SD 0.08). The Shapley Additive Explanations analysis found that congestive heart failure management, back problems, and atrial fibrillation were the top frailty predictors. Additionally, the latent Dirichlet allocation topic modeling identified 7 key topics, highlighting the role of specific medical treatments in predicting frailty. Conclusions: Integrating unstructured clinical notes and structured EHR data led to a notable enhancement in predicting frailty. This method shows great potential for standardizing frailty assessments using real-world data and improving patient selection for TAVR. ", doi="10.2196/58980", url="https://aging.jmir.org/2024/1/e58980" } @Article{info:doi/10.2196/57352, author="Wong, Ching Arkers Kwan and Zhang, Qian Melissa and Bayuo, Jonathan and Chow, Sum Karen Kit and Wong, Man Siu and Wong, Po Bonnie and Liu, Man Bob Chung and Lau, Ho David Chi and Kowatsch, Tobias", title="The Effect of Young People--Assisted, Individualized, Motion-Based Video Games on Physical, Cognitive, and Social Frailty Among Community-Dwelling Older Adults With Frailty: Randomized Controlled Trial", journal="JMIR Serious Games", year="2024", month="Nov", day="20", volume="12", pages="e57352", keywords="frailty", keywords="gaming intervention", keywords="motion-based", keywords="video games", keywords="older adults", keywords="gerontology", keywords="geriatrics", keywords="randomized controlled trial", keywords="RCT", keywords="physical fitness", keywords="adolescents", keywords="young people--assisted", keywords="eHealth literacy", keywords="well-being", keywords="therapists", keywords="youth volunteers", keywords="social support", keywords="exergames", keywords="gamification", keywords="active games", keywords="physical activity", abstract="Background: The aging population highlights the need to maintain both physical and psychological well-being. Frailty, a multidimensional syndrome, increases vulnerability to adverse outcomes. Although physical exercise is effective, adherence among older adults with frailty is often low due to barriers. Motion-based video games (MBVGs) may enhance motivation and engagement. Objective: This study aims to evaluate the effect of individualized exercise programs that combine MBVGs, intergenerational support, and therapeutic frameworks on physical, cognitive, and social frailty outcomes in community-dwelling older adults. Methods: This randomized controlled trial was conducted from March 2022 to October 2023 across 6 community centers in Hong Kong. Participants aged 60 years and above with mild neurocognitive disorder were recruited, screened, and randomly assigned to either an intervention (n=101) or control group (n=101). The intervention included an 18-week program with 12 supervised exercise sessions utilizing motion-based technology, led by occupational therapists and assisted by youth volunteers. Data were collected at baseline (T1) and postintervention (T2), focusing on physical, cognitive, and social frailty outcomes, as well as client-related metrics. Statistical analyses were performed using SPSS, with significance set at P<.05. Results: A total of 202 participants were recruited, with a mean age of 78.8 years (SD 7.8). Both groups showed improvements in balance from T1 to T2, with a significant time effect ($\beta$=?0.63, P=.03). The intervention group demonstrated enhancements in hand strength and BMI, but no statistically significant between-group differences were observed. The intervention group also exhibited significant improvements in cognitive function ($\beta$=2.43, P<.001), while the control group's scores declined. Short-term memory improved for both groups, with no significant differences noted. Both groups experienced a reduction in depression levels, with a significant within-group effect at T2 ($\beta$=?1.16, P=.001). Improvements in social connectedness and eHealth literacy were observed in both groups, with the latter showing a significant within-group effect at T2 ($\beta$=3.56, P=.002). No significant effects were found for social isolation, physical activities, or quality of life. Conclusions: The growing aging population necessitates innovative strategies to support aging in place. Results indicated statistically significant improvements only in BMI and cognition, while other outcomes such as loneliness, balance, and eHealth literacy showed positive trends but lacked significance. Despite the limitations observed, particularly regarding the role of volunteer support and the diverse needs of community-dwelling older adults, the findings contribute to the foundation for future research aimed at enhancing biopsychosocial outcomes. Future studies should explore tailored interventions that consider individual preferences and abilities, as well as evaluate specific components of motion-based video games to optimize their effectiveness. Trial Registration: ClinicalTrials.gov NCT05267444; https://clinicaltrials.gov/study/NCT05267444 ", doi="10.2196/57352", url="https://games.jmir.org/2024/1/e57352" } @Article{info:doi/10.2196/58466, author="Lin, Yu-Chun and Yan, Huang-Ting and Lin, Chih-Hsueh and Chang, Hen-Hong", title="Identifying and Estimating Frailty Phenotypes by Vocal Biomarkers: Cross-Sectional Study", journal="J Med Internet Res", year="2024", month="Nov", day="8", volume="26", pages="e58466", keywords="frailty phenotypes", keywords="older adults", keywords="successful aging", keywords="vocal biomarkers", keywords="frailty", keywords="phenotype", keywords="vocal biomarker", keywords="cross-sectional", keywords="gerontology", keywords="geriatrics", keywords="older adult", keywords="Taiwan", keywords="energy-based", keywords="hybrid-based", keywords="sarcopenia", abstract="Background: Researchers have developed a variety of indices to assess frailty. Recent research indicates that the human voice reflects frailty status. Frailty phenotypes are seldom discussed in the literature on the aging voice. Objective: This study aims to examine potential phenotypes of frail older adults and determine their correlation with vocal biomarkers. Methods: Participants aged ?60 years who visited the geriatric outpatient clinic of a teaching hospital in central Taiwan between 2020 and 2021 were recruited. We identified 4 frailty phenotypes: energy-based frailty, sarcopenia-based frailty, hybrid-based frailty--energy, and hybrid-based frailty--sarcopenia. Participants were asked to pronounce a sustained vowel ``/a/'' for approximately 1 second. The speech signals were digitized and analyzed. Four voice parameters---the average number of zero crossings (A1), variations in local peaks and valleys (A2), variations in first and second formant frequencies (A3), and spectral energy ratio (A4)---were used for analyzing changes in voice. Logistic regression was used to elucidate the prediction model. Results: Among 277 older adults, an increase in A1 values was associated with a lower likelihood of energy-based frailty (odds ratio [OR] 0.81, 95\% CI 0.68-0.96), whereas an increase in A2 values resulted in a higher likelihood of sarcopenia-based frailty (OR 1.34, 95\% CI 1.18-1.52). Respondents with larger A3 and A4 values had a higher likelihood of hybrid-based frailty--sarcopenia (OR 1.03, 95\% CI 1.002-1.06) and hybrid-based frailty--energy (OR 1.43, 95\% CI 1.02-2.01), respectively. Conclusions: Vocal biomarkers might be potentially useful in estimating frailty phenotypes. Clinicians can use 2 crucial acoustic parameters, namely A1 and A2, to diagnose a frailty phenotype that is associated with insufficient energy or reduced muscle function. The assessment of A3 and A4 involves a complex frailty phenotype. ", doi="10.2196/58466", url="https://www.jmir.org/2024/1/e58466" } @Article{info:doi/10.2196/13723, author="de Vette, Frederiek and Ruiz-Rodriguez, Aurora and Tabak, Monique and Oude Nijeweme-d'Hollosy, Wendy and Hermens, Hermie and Vollenbroek-Hutten, Miriam", title="Developing Game-Based Design for eHealth in Practice: 4-Phase Game Design Process", journal="JMIR Form Res", year="2024", month="Nov", day="8", volume="8", pages="e13723", keywords="game based", keywords="gamification", keywords="game", keywords="eHealth", keywords="telemedicine", keywords="development", keywords="design", keywords="engagement", keywords="game preferences", keywords="older adults", keywords="self-management", keywords="prototyping", keywords="evaluations", keywords="creative", abstract="Background: Games are increasingly used in eHealth as a strategy for user engagement. There is an enormous diversity of end users and objectives targeted by eHealth. Hence, identifying game content that drives and sustains engagement is challenging. More openness in the game design process and motivational strategies could aid researchers and designers of future game-based apps. Objective: This study aims to provide insights into our approach to develop game-based eHealth in practice with a case study (Personalised ICT Supported Services for Independent Living and Active Ageing [PERSSILAA]). PERSSILAA is a self-management platform that aims to counter frailty by offering training modules to older adults in the domains of healthy nutrition and physical and cognitive training to maintain a healthy lifestyle. We elaborate on the entire game design process and show the motivational strategies applied. Methods: We introduce four game design phases in the process toward game-based eHealth: (1) end-user research, (2) conceptualization, (3) creative design, and (4) refinement (ie, prototyping and evaluations). Results: First, 168 participants participated in end-user research, resulting in an overview of their preferences for game content and a set of game design recommendations. We found that conventional games popular among older adults do not necessarily translate well into engaging concepts for eHealth. Recommendations include focusing game concepts on thinking, problem-solving, variation, discovery, and achievement and using high-quality aesthetics. Second, stakeholder sessions with development partners resulted in strategies for long-term engagement using indicators of user performance on the platform's training modules. These performance indicators, for example, completed training sessions or exercises, form the basis for game progression. Third, results from prior phases were used in creative design to create the game ``Stranded!'' The user plays a person who is shipwrecked who must gather parts for a life raft by completing in-game objectives. Finally, iterative prototyping resulted in the final prototype of the game-based app. A total of 35 older adults participated using simulated training modules. End users scored appreciation (74/100), ease of use (73/100), expected effectivity and motivation (62/100), fun and pleasantness of using the app (75/100), and intended future use (66/100), which implies that the app is ready for use by a larger population. Conclusions: The study resulted in a game-based app for which the entire game design process within eHealth was transparently documented and where engagement strategies were based on extensive user research. Our user evaluations indicate that the strategies for long-term engagement led to game content that was perceived as engaging by older adults. As a next step, research is needed on the user experience and actual engagement with the game to support the self-management of older adults, followed by clinical studies on its added value. ", doi="10.2196/13723", url="https://formative.jmir.org/2024/1/e13723" } @Article{info:doi/10.2196/54839, author="Wernli, Boris and Verloo, Henk and von Gunten, Armin and Pereira, Filipa", title="Using Existing Clinical Data to Measure Older Adult Inpatients' Frailty at Admission and Discharge: Hospital Patient Register Study", journal="JMIR Aging", year="2024", month="Oct", day="28", volume="7", pages="e54839", keywords="frailty", keywords="frailty assessment", keywords="electronic patient records", keywords="functional independence measure", keywords="routinely collected data", keywords="hospital register", keywords="patient records", keywords="medical records", keywords="clinical data", keywords="older adults", keywords="cluster analysis", keywords="hierarchical clustering", abstract="Background: Frailty is a widespread geriatric syndrome among older adults, including hospitalized older inpatients. Some countries use electronic frailty measurement tools to identify frailty at the primary care level, but this method has rarely been investigated during hospitalization in acute care hospitals. An electronic frailty measurement instrument based on population-based hospital electronic health records could effectively detect frailty, frailty-related problems, and complications as well be a clinical alert. Identifying frailty among older adults using existing patient health data would greatly aid the management and support of frailty identification and could provide a valuable public health instrument without additional costs. Objective: We aim to explore a data-driven frailty measurement instrument for older adult inpatients using data routinely collected at hospital admission and discharge. Methods: A retrospective electronic patient register study included inpatients aged ?65 years admitted to and discharged from a public hospital between 2015 and 2017. A dataset of 53,690 hospitalizations was used to customize this data-driven frailty measurement instrument inspired by the Edmonton Frailty Scale developed by Rolfson et al. A 2-step hierarchical cluster procedure was applied to compute e-Frail-CH (Switzerland) scores at hospital admission and discharge. Prevalence, central tendency, comparative, and validation statistics were computed. Results: Mean patient age at admission was 78.4 (SD 7.9) years, with more women admitted (28,018/53,690, 52.18\%) than men (25,672/53,690, 47.81\%). Our 2-step hierarchical clustering approach computed 46,743 inputs of hospital admissions and 47,361 for discharges. Clustering solutions scored from 0.5 to 0.8 on a scale from 0 to 1. Patients considered frail comprised 42.02\% (n=19,643) of admissions and 48.23\% (n=22,845) of discharges. Within e-Frail-CH's 0-12 range, a score ?6 indicated frailty. We found a statistically significant mean e-Frail-CH score change between hospital admission (5.3, SD 2.6) and discharge (5.75, SD 2.7; P<.001). Sensitivity and specificity cut point values were 0.82 and 0.88, respectively. The area under the receiver operating characteristic curve was 0.85. Comparing the e-Frail-CH instrument to the existing Functional Independence Measure (FIM) instrument, FIM scores indicating severe dependence equated to e-Frail-CH scores of ?9, with a sensitivity and specificity of 0.97 and 0.88, respectively. The area under the receiver operating characteristic curve was 0.92. There was a strong negative association between e-Frail-CH scores at hospital discharge and FIM scores (rs=--0.844; P<.001). Conclusions: An electronic frailty measurement instrument was constructed and validated using patient data routinely collected during hospitalization, especially at admission and discharge. The mean e-Frail-CH score was higher at discharge than at admission. The routine calculation of e-Frail-CH scores during hospitalization could provide very useful clinical alerts on the health trajectories of older adults and help select interventions for preventing or mitigating frailty. ", doi="10.2196/54839", url="https://aging.jmir.org/2024/1/e54839" } @Article{info:doi/10.2196/49975, author="Corr{\^e}a, Laura and J{\'u}dice, Andr{\'e} and Scoz, Robson and Machado, Vanessa and Mendes, Jo{\~a}o Jos{\'e} and Proen{\c{c}}a, Lu{\'i}s and Botelho, Jo{\~a}o and Ferreira, Luciano", title="Portuguese Version of the Oral Frailty Index-8: Instrument Validation Study", journal="Interact J Med Res", year="2024", month="Oct", day="28", volume="13", pages="e49975", keywords="oral frailty", keywords="oral health", keywords="functional disability", keywords="frailty", keywords="aging", keywords="dentistry", keywords="confirmatory factor analysis", keywords="psychometric validity", keywords="questionnaire development", abstract="Background: The concept of oral frailty has gained scientific and clinical relevance in recent years, and early detection can facilitate timely intervention to manage its progression. The Oral Frailty Index-8 (OFI-8) was developed to assess community-dwelling older adults at risk for oral frailty. Objective: This study aims to investigate the psychometric validity of the OFI-8 in the Portuguese population, named the Portuguese version of the OFI-8 (OFI-8-PT), which may serve as a reference for future studies related to longevity and oral function. Methods: This study included 2 main phases, involving patients aged 60 years or older, Portuguese speakers, and those who consented to participate in the study. First, the researchers translated and cross-culturally adapted the original questionnaire to make it suitable for native Portuguese speakers. The translated tool was then assessed for psychometric validation, which consisted of test-retest reliability, internal consistency, construct validity, and sex invariance measurement. Results: A total of 159 older adults participated in the baseline survey, with almost equal numbers of male (n=79, 49.7\%) and female participants (n=80, 50.3\%). The OFI-8-PT demonstrated good reliability (Cronbach $\alpha$=0.95) and construct validity (goodness-of-fit index=0.96; comparative fit index=0.85; and root mean square error of approximation=0.05, 90\% CI 0.00-0.09). The study found sex invariance, indicating that the OFI-8-PT is equally valid for male and female participants, and the tested-retest reliability of the OFI-8-PT was good, indicating consistent results over time. Conclusions: The OFI-8-PT showed psychometric validity and good reliability to be used in the Portuguese population. ", doi="10.2196/49975", url="https://www.i-jmr.org/2024/1/e49975", url="http://www.ncbi.nlm.nih.gov/pubmed/39466299" } @Article{info:doi/10.2196/58312, author="Vald{\'e}s-Aragon{\'e}s, Myriam and P{\'e}rez-Rodr{\'i}guez, Rodrigo and Carnicero, Antonio Jos{\'e} and Moreno-S{\'a}nchez, A. Pedro and Oviedo-Briones, Myriam and Villalba-Mora, Elena and Abizanda-Soler, Pedro and Rodr{\'i}guez-Ma{\~n}as, Leocadio", title="Effects of Monitoring Frailty Through a Mobile/Web-Based Application and a Sensor Kit to Prevent Functional Decline in Frail and Prefrail Older Adults: FACET (Frailty Care and Well Function) Pilot Randomized Controlled Trial", journal="J Med Internet Res", year="2024", month="Oct", day="22", volume="26", pages="e58312", keywords="frailty", keywords="functional status", keywords="older adults", keywords="new technologies", keywords="sensor", keywords="monitoring system", keywords="information and communication technologies", keywords="mobile app", keywords="sensor kit", keywords="sensors", keywords="technological ecosystem", keywords="clinical intervention", abstract="Background: Frailty represents a state of susceptibility to stressors and constitutes a dynamic process. Untreated, this state can progress to disability. Hence, timely detection of alterations in patients' frailty status is imperative to institute prompt clinical interventions and impede frailty progression. With this aim, the FACET (Frailty Care and Well Function) technological ecosystem was developed to provide clinically gathered data from the home to a medical team for early intervention. Objective: The aim of this study was to assess whether the FACET technological ecosystem prevents frailty progression and improves frailty status, according to the frailty phenotype criteria and Frailty Trait Scale-5 items (FTS-5) at 3 and 6 months of follow-up. Methods: This randomized clinical trial involved 90 older adults aged ?70 years meeting 2 or more Fried frailty phenotype criteria, having 4 or more comorbidities, and having supervision at home. This study was conducted between August 2018 and June 2019 at the geriatrics outpatient clinics in Getafe University Hospital and Albacete University Hospital. Participants were randomized into a control group receiving standard treatment and the intervention group receiving standard treatment along with the FACET home monitoring system. The system monitored functional tests at home (gait speed, chair stand test, frailty status, and weight). Outcomes were assessed using multivariate linear regression models for continuous response and multivariate logistic models for dichotomous response. P values less than .05 were considered statistically significant. Results: The mean age of the participants was 82.33 years, with 28\% (25/90) being males. Participants allocated to the intervention group showed a 74\% reduction in the risk of deterioration in the FTS-5 score (P=.04) and 92\% lower likelihood of worsening by 1 point according to Fried frailty phenotype criteria compared to the control group (P=.02) at 6 months of follow-up. Frailty status, when assessed through FTS-5, improved in the intervention group at 3 months (P=.004) and 6 months (P=.047), while when the frailty phenotype criteria were used, benefits were shown at 3 months of follow-up (P=.03) but not at 6 months. Conclusions: The FACET technological ecosystem helps in the early identification of changes in the functional status of prefrail and frail older adults, facilitating prompt clinical interventions, thereby improving health outcomes in terms of frailty and functional status and potentially preventing disability and dependency. Trial Registration: ClinicalTrials.gov NCT03707145; https://clinicaltrials.gov/study/NCT03707145 ", doi="10.2196/58312", url="https://www.jmir.org/2024/1/e58312", url="http://www.ncbi.nlm.nih.gov/pubmed/39436684" } @Article{info:doi/10.2196/59762, author="Yang, Ya and Che, Kechun and Deng, Jiayan and Tang, Xinming and Jing, Wenyuan and He, Xiuping and Yang, Jiacheng and Zhang, Wenya and Yin, Mingjuan and Pan, Congcong and Huang, Xiaoling and Zhang, Zewu and Ni, Jindong", title="Assessing the Impact of Frailty on Infection Risk in Older Adults: Prospective Observational Cohort Study", journal="JMIR Public Health Surveill", year="2024", month="Oct", day="16", volume="10", pages="e59762", keywords="community elderly", keywords="frailty", keywords="infectious diseases", keywords="infectious disease", keywords="older", keywords="China", keywords="questionnaire", keywords="survey", keywords="cohort", keywords="COVID-19", keywords="infection", keywords="chi-square", keywords="longitudinal analysis", keywords="age-related chronic disease", keywords="chronic disease", keywords="chronic diseases", abstract="Background: Infectious diseases are among the leading causes of death and disability and are recognized as a major cause of health loss globally. At the same time, frailty as a geriatric syndrome is a rapidly growing major public health problem. However, few studies have investigated the incidence and risk of infectious diseases in frail older people. Thus, research on frailty and infectious diseases is urgently needed. Objective: The purpose of this study was to evaluate the association between frailty and infectious diseases among older adults aged 65 years and older. Methods: In this prospective observational cohort study, we have analyzed the infectious disease prevalence outcomes of older adults aged 65 years and older who participated in frailty epidemiological surveys from March 1, 2018, to March 2023 in Dalang Town, Dongguan City, and from March 1, 2020, to March 2023 in Guancheng Street, Dongguan City. This study has an annual on-site follow-up. Incidence data for infectious diseases were collected through the Chinese Disease Control and Prevention Information System---Infectious Disease Monitoring and Public Health Emergency Monitoring System. A project-developed frailty assessment scale was used to assess the frailty status of study participants. We compared the incidence rate ratios (IRR) of each disease across frailty status, age, and gender to determine the associations among frailty, gender, age, and infectious diseases. Cox proportional hazards regression was conducted to identify the effect of frailty on the risk of demographic factors and frailty on the risk of infectious diseases, with estimations of the hazard ratio and 95\% CI. Results: A total of 235 cases of 12 infectious diseases were reported during the study period, with an incidence of 906.21/100,000 person-years in the frailty group. In the same age group, the risk of infection was higher in men than women. Frail older adults had a hazard ratio for infectious diseases of 1.50 (95\% CI 1.14?1.97) compared with healthy older adults. We obtained the same result after sensitivity analyses. For respiratory tract--transmitted diseases (IRR 1.97, 95\% CI 1.44?2.71) and gastrointestinal tract--transmitted diseases (IRR 3.67, 95\% CI 1.39?10.74), frail older adults are at risk. Whereas no significant association was found for blood-borne, sexually transmitted, and contact-transmitted diseases (IRR 0.76, 95\% CI 0.37?1.45). Conclusions: Our study provides additional evidence that frailty components are significantly associated with infectious diseases. Health care professionals must pay more attention to frailty in infectious disease prevention and control. ", doi="10.2196/59762", url="https://publichealth.jmir.org/2024/1/e59762" } @Article{info:doi/10.2196/50617, author="Liu, Yunmei and Huang, Lei and Hu, Fei and Zhang, Xiuwen", title="Investigating Frailty, Polypharmacy, Malnutrition, Chronic Conditions, and Quality of Life in Older Adults: Large Population-Based Study", journal="JMIR Public Health Surveill", year="2024", month="Oct", day="11", volume="10", pages="e50617", keywords="statistical analyses", keywords="data mining", keywords="older adults", keywords="geriatric syndromes", keywords="frailty", keywords="polypharmacy", keywords="malnutrition", keywords="chronic conditions", keywords="quality of life", keywords="large population-based study", abstract="Background: Aging, a significant public health issue, is associated with multiple concurrent chronic diseases and aging-related conditions (geriatric syndromes). Objective: This study aims to investigate the impact of age and chronic conditions on geriatric syndromes and the intercorrelations between multiple geriatric syndromes and quality of life (QoL) in older adults (aged ?65 years) at the population level. Methods: A large representative sample was randomly selected from a county in China, Feidong, with 17 towns and 811,867 residents. Multiple chronic conditions, geriatric syndromes (frailty, polypharmacy, and malnutrition), and QoL were assessed and compared. Associations of demographic information and chronic conditions with geriatric conditions and QoL in older adults were assessed using multivariable-adjusted logistic regression. Intercorrelations between age, multiple geriatric syndromes, and QoL were investigated using both correlation analysis and restricted cubic splines--based multivariable-adjusted dose-response analysis. Results: Older adults comprised 43.42\% (3668/8447) of the entire study population. The prevalence of frailty, premalnutrition or malnutrition, polypharmacy, and impaired QoL (median age 73, IQR 69-78 years; 1871/3668, 51\% men) was 8.26\% (303/3668), 15.59\% (572/3668), 3.22\% (118/3668), and 10.8\% (396/3668), respectively. Different age and sex subgroups mostly had similar prevalence of geriatric syndromes (except that frailty occurred more often with older age). Premalnutrition or malnutrition were associated with a lower frequency of obesity and a higher frequency of constipation, polypharmacy with a higher frequency of diabetes and constipation, frailty with a higher frequency of constipation and hernia, and impaired QoL with a higher frequency of hypertension, diabetes, physical disability, and constipation. Mini Nutritional Assessment--Short Form, Groningen Frailty Indicator, and EQ-5D-5L scores, as well as the number of medications used, mostly predicted each other and QoL. Impaired QoL was associated with a higher frequency of frailty, premalnutrition or malnutrition, and polypharmacy, and frailty with a higher frequency of premalnutrition or malnutrition and polypharmacy. At a 1.5-year follow-up, impaired QoL was linked to polypharmacy and frailty at baseline, premalnutrition or malnutrition and polypharmacy were associated with frailty at baseline, and frailty was linked to both premalnutrition or malnutrition and polypharmacy at baseline. Causal mediation analyses showed that frailty mediated the link between polypharmacy and worse QoL and that polypharmacy mediated the link between frailty and worse QoL. Conclusions: In this large population-based study of older adults, multiple chronic conditions were associated with ?1 of the investigated geriatric syndromes. Geriatric syndromes were mostly intercorrelated with, and well predictive of, each other and QoL; and causal relationships existed between geriatric syndromes and QoL, with other geriatric syndromes being mediators. The findings might be biased by residual confounding factors. It is important to perform personalized geriatric syndrome assessments stratified by chronic condition; active prevention of, or intervention for, any syndrome might help to reduce the others and improve QoL. ", doi="10.2196/50617", url="https://publichealth.jmir.org/2024/1/e50617", url="http://www.ncbi.nlm.nih.gov/pubmed/39145920" } @Article{info:doi/10.2196/60099, author="Garc{\'i}a-Sangen{\'i}s, Ana and Modena, Daniela and Jensen, Nygaard Jette and Chalkidou, Athina and Antsupova, S. Valeria and Marloth, Tina and Theut, Marie Anna and Gonz{\'a}lez L{\'o}pez-Valc{\'a}rcel, Beatriz and Raynal, Fabiana and Vallejo-Torres, Laura and Lykkegaard, Jesper and Hansen, Plejdrup Malene and S{\o}ndergaard, Jens and Olsen, Kanstrup Jonas and Munck, Anders and Balint, Andr{\'a}s and Benko, Ria and Petek, Davorina and Sodja, Nina and Kowalczyk, Anna and Godycki-Cwirko, Maciej and Glasov{\'a}, Helena and Glasa, Jozef and Radzeviciene Jurgute, Ruta and Jaruseviciene, Lina and Lionis, Christos and Anastasaki, Marilena and Angelaki, Agapi and Petelos, Elena and Alvarez, Laura and Ricart, Marta and Briones, Sergi and Ruppe, Georg and Monf{\`a}, Ramon and Bjerrum, Anders and Llor, Carl", title="Improving Antibiotic Use in Nursing Homes by Infection Prevention and Control and Antibiotic Stewardship (IMAGINE): Protocol for a Before-and-After Intervention and Implementation Study", journal="JMIR Res Protoc", year="2024", month="Sep", day="16", volume="13", pages="e60099", keywords="antimicrobial stewardship", keywords="medical audit", keywords="hygiene", keywords="antibacterial agents", keywords="quality improvement", keywords="nursing homes", keywords="health personnel", keywords="drug resistance, microbial", keywords="frail elderly", abstract="Background: Despite the extensive use of antibiotics and the growing challenge of antimicrobial resistance, there has been a lack of substantial initiatives aimed at diminishing the prevalence of infections in nursing homes and enhancing the detection of urinary tract infections (UTIs). Objective: This study aims to systematize and enhance efforts to prevent health care--associated infections, mainly UTIs and reduce antibiotic inappropriateness by implementing a multifaceted intervention targeting health care professionals in nursing homes. Methods: A before-and-after intervention study carried out in a minimum of 10 nursing homes in each of the 8 European participating countries (Denmark, Greece, Hungary, Lithuania, Poland, Slovakia, Slovenia, and Spain). A team of 4 professionals consisting of nurses, doctors, health care assistants, or health care helpers are actively involved in each nursing home. Over the initial 3-month period, professionals in each nursing home are registering information on UTIs as well as infection and prevention control measures by means of the Audit Project Odense method. The audit will be repeated after implementing a multifaceted intervention. The intervention will consist of feedback and discussion of the results from the first registration, training on the implementation of infection and prevention control techniques provided by experts, appropriateness of the diagnostic approach and antibiotic prescribing for UTIs, and provision of information materials on infection control and antimicrobial stewardship targeted to staff, residents, and relatives. We will compare the pre- and postintervention audit results using chi-square test for prescription appropriateness and Student t test for implemented hygiene elements. Results: A total of 109 nursing homes have participated in the pilot study and the first registration audit. The results of the first audit registration are expected to be published in autumn of 2024. The final results will be published by the end of 2025. Conclusions: This is a European Union--funded project aimed at contributing to the battle against antimicrobial resistance through improvement of the quality of management of common infections based on evidence-based interventions tailored to the nursing home setting and a diverse range of professionals. We expect the intervention to result in a significant increase in the number of hygiene activities implemented by health care providers and residents. Additionally, we anticipate a marked reduction in the number of inappropriately managed UTIs, as well as a substantial decrease in the overall incidence of infections following the intervention. International Registered Report Identifier (IRRID): DERR1-10.2196/60099 ", doi="10.2196/60099", url="https://www.researchprotocols.org/2024/1/e60099", url="http://www.ncbi.nlm.nih.gov/pubmed/39284176" } @Article{info:doi/10.2196/56345, author="Razjouyan, Javad and Orkaby, R. Ariela and Horstman, J. Molly and Goyal, Parag and Intrator, Orna and Naik, D. Aanand", title="The Frailty Trajectory's Additional Edge Over the Frailty Index: Retrospective Cohort Study of Veterans With Heart Failure", journal="JMIR Aging", year="2024", month="Jun", day="27", volume="7", pages="e56345", keywords="gerontology", keywords="geriatric", keywords="geriatrics", keywords="older adult", keywords="older adults", keywords="elder", keywords="elderly", keywords="older person", keywords="older people", keywords="ageing", keywords="aging", keywords="frailty", keywords="frailty index", keywords="frailty trajectory", keywords="frail", keywords="weak", keywords="weakness", keywords="heart failure", keywords="HF", keywords="cardiovascular disease", keywords="CVD", keywords="congestive heart failure", keywords="CHF", keywords="myocardial infarction", keywords="MI", keywords="unstable angina", keywords="angina", keywords="cardiac arrest", keywords="atherosclerosis", keywords="cardiology", keywords="cardiac", keywords="cardiologist", keywords="cardiologists", doi="10.2196/56345", url="https://aging.jmir.org/2024/1/e56345" } @Article{info:doi/10.2196/53098, author="Greeley, Brian and Chung, Seohyeon Sally and Graves, Lorraine and Song, Xiaowei", title="Combating Barriers to the Development of a Patient-Oriented Frailty Website", journal="JMIR Aging", year="2024", month="May", day="28", volume="7", pages="e53098", keywords="frailty", keywords="frailty website", keywords="patient-oriented assessment", keywords="community-dwelling older adults", keywords="internet security", keywords="privacy", keywords="barrier", keywords="barriers", keywords="development", keywords="implementation", keywords="patient-oriented", keywords="internet", keywords="virtual health resource", keywords="community dwelling", keywords="older adult", keywords="older adults", keywords="health care professional", keywords="caregiver", keywords="caregivers", keywords="technology", keywords="real-time", keywords="monitoring", keywords="aging", keywords="ageing", doi="10.2196/53098", url="https://aging.jmir.org/2024/1/e53098" } @Article{info:doi/10.2196/50537, author="Ambrosini, Emilia and Giangregorio, Chiara and Lomurno, Eugenio and Moccia, Sara and Milis, Marios and Loizou, Christos and Azzolino, Domenico and Cesari, Matteo and Cid Gala, Manuel and Gal{\'a}n de Isla, Carmen and Gomez-Raja, Jonathan and Borghese, Alberto Nunzio and Matteucci, Matteo and Ferrante, Simona", title="Automatic Spontaneous Speech Analysis for the Detection of Cognitive Functional Decline in Older Adults: Multilanguage Cross-Sectional Study", journal="JMIR Aging", year="2024", month="Apr", day="29", volume="7", pages="e50537", keywords="cognitive decline", keywords="speech processing", keywords="machine learning", keywords="multilanguage", keywords="Mini-Mental Status Examination", abstract="Background: The rise in life expectancy is associated with an increase in long-term and gradual cognitive decline. Treatment effectiveness is enhanced at the early stage of the disease. Therefore, there is a need to find low-cost and ecological solutions for mass screening of community-dwelling older adults. Objective: This work aims to exploit automatic analysis of free speech to identify signs of cognitive function decline. Methods: A sample of 266 participants older than 65 years were recruited in Italy and Spain and were divided into 3 groups according to their Mini-Mental Status Examination (MMSE) scores. People were asked to tell a story and describe a picture, and voice recordings were used to extract high-level features on different time scales automatically. Based on these features, machine learning algorithms were trained to solve binary and multiclass classification problems by using both mono- and cross-lingual approaches. The algorithms were enriched using Shapley Additive Explanations for model explainability. Results: In the Italian data set, healthy participants (MMSE score?27) were automatically discriminated from participants with mildly impaired cognitive function (20?MMSE score?26) and from those with moderate to severe impairment of cognitive function (11?MMSE score?19) with accuracy of 80\% and 86\%, respectively. Slightly lower performance was achieved in the Spanish and multilanguage data sets. Conclusions: This work proposes a transparent and unobtrusive assessment method, which might be included in a mobile app for large-scale monitoring of cognitive functionality in older adults. Voice is confirmed to be an important biomarker of cognitive decline due to its noninvasive and easily accessible nature. ", doi="10.2196/50537", url="https://aging.jmir.org/2024/1/e50537", url="http://www.ncbi.nlm.nih.gov/pubmed/38386279" } @Article{info:doi/10.2196/55192, author="Kvalsvik, Fifi and Larsen, Hamre Bente and Eilertsen, Grethe and Falkenberg, K. Helle and Dalen, Ingvild and Haaland, Stine and Storm, Marianne", title="Health Needs Assessment in Home-Living Older Adults: Protocol for a Pre-Post Study", journal="JMIR Res Protoc", year="2024", month="Apr", day="18", volume="13", pages="e55192", keywords="assessment", keywords="frailty", keywords="healthy aging", keywords="health care", keywords="home-living older adults", keywords="pre-post study", keywords="protocol", abstract="Background: Conducting a health needs assessment for older adults is important, particularly for early detection and management of frailty. Such assessments can help to improve health outcomes, maintain overall well-being, and support older adults in retaining their independence as they age at home. Objective: In this study, a systematic approach to health needs assessment is adopted in order to reflect real-world practices in municipal health care and capture the nuances of frailty. The aim is to assess changes in frailty levels in home-living older adults over 5 months and to examine the observable functional changes from a prestudy baseline (t1) to a poststudy period (t2). Additionally, the study explores the feasibility of conducting the health needs assessment from the perspective of home-living older adults and their informal caregivers. Methods: Interprofessional teams of registered nurses, physiotherapists, and occupational therapists will conduct 2 health needs assessments covering physical, cognitive, psychological, social, and behavioral domains. The study includes 40 home-living older adults of 75 years of age or older, who have applied for municipal health and care services in Norway. A quantitative approach will be applied to assess changes in frailty levels in home-living older adults over 5 months. In addition, we will examine the observable functional changes from t1 to t2 and how these changes correlate to frailty levels. Following this, a qualitative approach will be used to examine the perspectives of participants and their informal caregivers regarding the health needs assessment and its feasibility. The final sample size for the qualitative phase will be determined based on the participant's willingness to be interviewed. The quantitative data consist of descriptive statistics, simple tests, and present plots and correlation coefficients. For the qualitative analysis, we will apply thematic analysis. Results: The initial baseline assessments were completed in July 2023, and the second health needs assessments are ongoing. We expect the results to be available for analysis in the spring of 2024. Conclusions: This study has potential benefits for not only older adults and their informal caregivers but also health care professionals. Moreover, it can be used to inform future studies focused on health needs assessments of this specific demographic group. The study also provides meaningful insights for local policy makers, with potential future implications at the national level. Trial Registration: ClinicalTrials.gov NCT05837728; https://clinicaltrials.gov/study/NCT05837728 International Registered Report Identifier (IRRID): DERR1-10.2196/55192 ", doi="10.2196/55192", url="https://www.researchprotocols.org/2024/1/e55192", url="http://www.ncbi.nlm.nih.gov/pubmed/38635319" } @Article{info:doi/10.2196/45848, author="Carrasco-Ribelles, A. Luc{\'i}a and Cabrera-Bean, Margarita and Dan{\'e}s-Castells, Marc and Zabaleta-del-Olmo, Edurne and Roso-Llorach, Albert and Viol{\'a}n, Concepci{\'o}n", title="Contribution of Frailty to Multimorbidity Patterns and Trajectories: Longitudinal Dynamic Cohort Study of Aging People", journal="JMIR Public Health Surveill", year="2023", month="Jun", day="27", volume="9", pages="e45848", keywords="multimorbidity", keywords="frailty", keywords="clustering", keywords="electronic health record", keywords="primary care", keywords="trajectory", abstract="Background: Multimorbidity and frailty are characteristics of aging that need individualized evaluation, and there is a 2-way causal relationship between them. Thus, considering frailty in analyses of multimorbidity is important for tailoring social and health care to the specific needs of older people. Objective: This study aimed to assess how the inclusion of frailty contributes to identifying and characterizing multimorbidity patterns in people aged 65 years or older. Methods: Longitudinal data were drawn from electronic health records through the SIDIAP (Sistema d'Informaci{\'o} pel Desenvolupament de la Investigaci{\'o} a l'Atenci{\'o} Prim{\`a}ria) primary care database for the population aged 65 years or older from 2010 to 2019 in Catalonia, Spain. Frailty and multimorbidity were measured annually using validated tools (eFRAGICAP, a cumulative deficit model; and Swedish National Study of Aging and Care in Kungsholmen [SNAC-K], respectively). Two sets of 11 multimorbidity patterns were obtained using fuzzy c-means. Both considered the chronic conditions of the participants. In addition, one set included age, and the other included frailty. Cox models were used to test their associations with death, nursing home admission, and home care need. Trajectories were defined as the evolution of the patterns over the follow-up period. Results: The study included 1,456,052 unique participants (mean follow-up of 7.0 years). Most patterns were similar in both sets in terms of the most prevalent conditions. However, the patterns that considered frailty were better for identifying the population whose main conditions imposed limitations on daily life, with a higher prevalence of frail individuals in patterns like chronic ulcers \&peripheral vascular. This set also included a dementia-specific pattern and showed a better fit with the risk of nursing home admission and home care need. On the other hand, the risk of death had a better fit with the set of patterns that did not include frailty. The change in patterns when considering frailty also led to a change in trajectories. On average, participants were in 1.8 patterns during their follow-up, while 45.1\% (656,778/1,456,052) remained in the same pattern. Conclusions: Our results suggest that frailty should be considered in addition to chronic diseases when studying multimorbidity patterns in older adults. Multimorbidity patterns and trajectories can help to identify patients with specific needs. The patterns that considered frailty were better for identifying the risk of certain age-related outcomes, such as nursing home admission or home care need, while those considering age were better for identifying the risk of death. Clinical and social intervention guidelines and resource planning can be tailored based on the prevalence of these patterns and trajectories. ", doi="10.2196/45848", url="https://publichealth.jmir.org/2023/1/e45848", url="http://www.ncbi.nlm.nih.gov/pubmed/37368462" } @Article{info:doi/10.2196/38464, author="Oates, John and Shafiabady, Niusha and Ambagtsheer, Rachel and Beilby, Justin and Seiboth, Chris and Dent, Elsa", title="Evolving Hybrid Partial Genetic Algorithm Classification Model for Cost-effective Frailty Screening: Investigative Study", journal="JMIR Aging", year="2022", month="Oct", day="7", volume="5", number="4", pages="e38464", keywords="machine learning", keywords="frailty screening", keywords="partial genetic algorithms", keywords="SVM", keywords="KNN", keywords="decision trees", keywords="frailty", keywords="algorithm", keywords="cost", keywords="model", keywords="index", keywords="database", keywords="ai", keywords="ageing", keywords="adults", keywords="older people", keywords="screening", keywords="tool", abstract="Background: A commonly used method for measuring frailty is the accumulation of deficits expressed as a frailty index (FI). FIs can be readily adapted to many databases, as the parameters to use are not prescribed but rather reflect a subset of extracted features (variables). Unfortunately, the structure of many databases does not permit the direct extraction of a suitable subset, requiring additional effort to determine and verify the value of features for each record and thus significantly increasing cost. Objective: Our objective is to describe how an artificial intelligence (AI) optimization technique called partial genetic algorithms can be used to refine the subset of features used to calculate an FI and favor features that have the least cost of acquisition. Methods: This is a secondary analysis of a residential care database compiled from 10 facilities in Queensland, Australia. The database is comprised of routinely collected administrative data and unstructured patient notes for 592 residents aged 75 years and over. The primary study derived an electronic frailty index (eFI) calculated from 36 suitable features. We then structurally modified a genetic algorithm to find an optimal predictor of the calculated eFI (0.21 threshold) from 2 sets of features. Partial genetic algorithms were used to optimize 4 underlying classification models: logistic regression, decision trees, random forest, and support vector machines. Results: Among the underlying models, logistic regression was found to produce the best models in almost all scenarios and feature set sizes. The best models were built using all the low-cost features and as few as 10 high-cost features, and they performed well enough (sensitivity 89\%, specificity 87\%) to be considered candidates for a low-cost frailty screening test. Conclusions: In this study, a systematic approach for selecting an optimal set of features with a low cost of acquisition and performance comparable to the eFI for detecting frailty was demonstrated on an aged care database. Partial genetic algorithms have proven useful in offering a trade-off between cost and accuracy to systematically identify frailty. ", doi="10.2196/38464", url="https://aging.jmir.org/2022/4/e38464", url="http://www.ncbi.nlm.nih.gov/pubmed/36206042" } @Article{info:doi/10.2196/28338, author="Wang, Duanyang and Yin, Pengbin and Li, Yi and Chen, Ming and Cui, Xiang and Cheng, Shi and Lin, Yuan and Yan, Jinglong and Zhang, Licheng and Tang, Peifu", title="Frailty Factors and Outcomes in Patients Undergoing Orthopedic Surgery: Protocol for a Systematic Review and Meta-analysis", journal="JMIR Res Protoc", year="2022", month="Apr", day="15", volume="11", number="4", pages="e28338", keywords="frailty", keywords="orthopedic surgery", keywords="systemic review", keywords="meta-analysis", keywords="older adults", keywords="elderly", keywords="surgery", keywords="orthopedics", abstract="Background: Frailty is an aggregate expression of susceptibility to adverse health outcomes because of age- and disease-related deficits that accumulate across multiple domains. Previous studies have found the presence of preoperative frailty is associated with an increased risk of adverse outcomes. The number of older adults undergoing orthopedic surgery is rapidly increasing. However, there has been no evidence-based study on the relationship between frailty and outcomes in patients undergoing orthopedic surgery. Objective: The aims of this study are to investigate the association between frailty and outcomes in patients who underwent orthopedic surgery as well as patient factors associated with frailty. Methods: The methods to be used for this systematic review are reported according to the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-analysis Protocols) 2015 checklist. An extensive search will be conducted in PubMed, Embase, the Cochrane Library, and other mainstream databases. Any study where patients undergoing orthopedic surgery were assessed using a defined or validated measure of frailty and the association of frailty with patient factors and/or outcomes was reported will be included. A total of 2 researchers will independently screen articles for inclusion, with disagreements resolved by a third reviewer. We will perform a narrative synthesis of the factors associated with frailty, prevalence of frailty, effect of frailty on patient outcomes, and interventions for patients who are frail. A meta-analysis focusing on individual factors associated with frailty and the effect of frailty on patient outcomes will be performed, if applicable. The risk of bias will be evaluated. A subgroup analysis and sensitivity analysis will be performed. Results: Literature searches were conducted in September 2021 and the review is anticipated to be completed by the end of July 2022. Conclusions: This systematic review and meta-analysis will provide an overview of frailty and investigate the relationship between frailty and patient outcomes as well as the relationship between patient factors and frailty in patients undergoing orthopedic surgery. This study could potentially increase patients' awareness of the outcomes associated with frailty, compel clinical specialties to further acknowledge the concept of frailty, and enhance the development of assessment instruments and tools for frailty. Trial Registration: PROSPERO CRD42020181846; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=181846 International Registered Report Identifier (IRRID): DERR1-10.2196/28338 ", doi="10.2196/28338", url="https://www.researchprotocols.org/2022/4/e28338", url="http://www.ncbi.nlm.nih.gov/pubmed/35436222" } @Article{info:doi/10.2196/29884, author="Kang, Min-gu and Kang, Seong-Ji and Roh, Hye-Kang and Jung, Hwa-Young and Kim, Sun?wook and Choi, Jung-Yeon and Kim, Kwang-il", title="Accuracy and Diversity of Wearable Device--Based Gait Speed Measurement Among Older Men: Observational Study", journal="J Med Internet Res", year="2021", month="Oct", day="11", volume="23", number="10", pages="e29884", keywords="gait speed", keywords="sarcopenia", keywords="skeletal muscle mass", keywords="wearable device", abstract="Background: Gait speed measurements are widely used in clinical practice, as slow gait is a major predictor of frailty and a diagnostic criterion for sarcopenia. With the development of wearable devices, it is possible to estimate the gait speed in daily life by simply wearing the device. Objective: This study aims to accurately determine the characteristics of daily life gait speed and analyze their association with sarcopenia. Methods: We invited community-dwelling men aged >50 years who had visited the outpatient clinic at a tertiary university hospital to participate in the study. Daily life gait speed was assessed using a wearable smart belt (WELT) for a period of 4 weeks. Data from participants who wore the smart belt for at least 10 days during this period were included. After 4 weeks, data from a survey about medical and social history, usual gait speed measurements, handgrip strength measurements, and dual-energy x-ray absorptiometry were analyzed. Results: A total of 217,578 daily life gait speed measurements from 106 participants (mean age 71.1, SD 7.6 years) were analyzed. The mean daily life gait speed was 1.23 (SD 0.26) m/s. The daily life gait speed of the participants varied according to the time of the day and day of the week. Daily life gait speed significantly slowed down with age (P<.001). Participants with sarcopenia had significantly lower mean daily life gait speed (mean 1.12, SD 0.11 m/s) than participants without sarcopenia (mean 1.23, SD 0.08 m/s; P<.001). Analysis of factors related to mean daily life gait speed showed that age and skeletal muscle mass of the lower limbs were significantly associated characteristics. Conclusions: More diverse and accurate information about gait speed can be obtained by measuring daily life gait speed using a wearable device over an appropriate period, compared with one-time measurements performed in a laboratory setting. Importantly, in addition to age, daily life gait speed is significantly associated with skeletal muscle mass of the lower limbs. ", doi="10.2196/29884", url="https://www.jmir.org/2021/10/e29884", url="http://www.ncbi.nlm.nih.gov/pubmed/34633293" } @Article{info:doi/10.2196/27499, author="Maruster, Laura and van der Zee, Durk-Jouke and Buskens, Erik", title="Identifying Frequent Health Care Users and Care Consumption Patterns: Process Mining of Emergency Medical Services Data", journal="J Med Internet Res", year="2021", month="Oct", day="6", volume="23", number="10", pages="e27499", keywords="process mining", keywords="frequent users", keywords="hospital care", keywords="emergency medical services", keywords="regional care networks", keywords="elderly", keywords="Netherlands", abstract="Background: Tracing frequent users of health care services is highly relevant to policymakers and clinicians, enabling them to avoid wasting scarce resources. Data collection on frequent users from all possible health care providers may be cumbersome due to patient privacy, competition, incompatible information systems, and the efforts involved. Objective: This study explored the use of a single key source, emergency medical services (EMS) records, to trace and reveal frequent users' health care consumption patterns. Methods: A retrospective study was performed analyzing EMS calls from the province of Drenthe in the Netherlands between 2012 and 2017. Process mining was applied to identify the structure of patient routings (ie, their consecutive visits to hospitals, nursing homes, and EMS). Routings are used to identify and quantify frequent users, recognizing frail elderly users as a focal group. The structure of these routes was analyzed at the patient and group levels, aiming to gain insight into regional coordination issues and workload distributions among health care providers. Results: Frail elderly users aged 70 years or more represented over 50\% of frequent users, making 4 or more calls per year. Over the period of observation, their annual number and the number of calls increased from 395 to 628 and 2607 to 3615, respectively. Structural analysis based on process mining revealed two categories of frail elderly users: low-complexity patients who need dialysis, radiation therapy, or hyperbaric medicine, involving a few health care providers, and high-complexity patients for whom routings appear chaotic. Conclusions: This efficient approach exploits the role of EMS as the unique regional ``ferryman,'' while the combined use of EMS data and process mining allows for the effective and efficient tracing of frequent users' utilization of health care services. The approach informs regional policymakers and clinicians by quantifying and detailing frequent user consumption patterns to support subsequent policy adaptations. ", doi="10.2196/27499", url="https://www.jmir.org/2021/10/e27499", url="http://www.ncbi.nlm.nih.gov/pubmed/34612834" } @Article{info:doi/10.2196/16846, author="Humphry, Angharad Nia and Wilson, Thomas and Cox, Christian Michael and Carter, Ben and Arkesteijn, Marco and Reeves, Laura Nicola and Brakenridge, Scott and McCarthy, Kathryn and Bunni, John and Draper, John and Hewitt, Jonathan", title="Association of Postoperative Clinical Outcomes With Sarcopenia, Frailty, and Nutritional Status in Older Patients With Colorectal Cancer: Protocol for a Prospective Cohort Study", journal="JMIR Res Protoc", year="2021", month="Aug", day="17", volume="10", number="8", pages="e16846", keywords="sarcopenia", keywords="frailty", keywords="nutritional status", keywords="urine metabolomics", keywords="surgery", keywords="geriatric medicine", abstract="Background: Older patients account for a significant proportion of patients undergoing colorectal cancer surgery and are vulnerable to a number of preoperative risk factors that are not often present in younger patients. Further, three preoperative risk factors that are more prevalent in older adults include frailty, sarcopenia, and malnutrition. Although each of these has been studied in isolation, there is little information on the interplay between them in older surgical patients. A particular area of increasing interest is the use of urine metabolomics for the objective evaluation of dietary profiles and malnutrition. Objective: Herein, we describe the design, cohort, and standard operating procedures of a planned prospective study of older surgical patients undergoing colorectal cancer resection across multiple institutions in the United Kingdom. The objectives are to determine the association between clinical outcomes and frailty, nutritional status, and sarcopenia. Methods: The procedures will include serial frailty evaluations (Clinical Frailty Scale and Groningen Frailty Indicator), functional assessments (hand grip strength and 4-meter walk test), muscle mass evaluations via computerized tomography morphometric analysis, and the evaluation of nutritional status via the analysis of urinary dietary biomarkers. The primary feasibility outcome is the estimation of the incidence rate of postoperative complications, and the primary clinical outcome is the association between the presence of postoperative complications and frailty, sarcopenia, and nutritional status. The secondary outcome measures are the length of hospital stay, 30-day hospital readmission rate, and mortality rate at days 30 and 90. Results: Our study was approved by the National Health Service Research Ethics Committee (reference number: 19/WA/0190) via the Integrated Research Application System (project ID: 231694) prior to subject recruitment. Cardiff University is acting as the study sponsor. Our study is financially supported through an external, peer-reviewed grant from the British Geriatrics Society and internal funding resources from Cardiff University. The results will be disseminated through peer-review publications, social media, and conference proceedings. Conclusions: As frailty, sarcopenia, and malnutrition are all areas of common derangement in the older surgical population, prospectively studying these risk factors in concert will allow for the analysis of their interplay as well as the development of predictive models for those at risk of commonly tracked surgical complications and outcomes. International Registered Report Identifier (IRRID): PRR1-10.2196/16846 ", doi="10.2196/16846", url="https://www.researchprotocols.org/2021/8/e16846", url="http://www.ncbi.nlm.nih.gov/pubmed/34402798" } @Article{info:doi/10.2196/25781, author="Ara{\'u}jo, F{\'a}tima and Nogueira, Nilza Maria and Silva, Joana and Rego, S{\'i}lvia", title="A Technological-Based Platform for Risk Assessment, Detection, and Prevention of Falls Among Home-Dwelling Older Adults: Protocol for a Quasi-Experimental Study", journal="JMIR Res Protoc", year="2021", month="Aug", day="12", volume="10", number="8", pages="e25781", keywords="fall prevention", keywords="technological platform", keywords="elderly", keywords="Otago Exercise Program", abstract="Background: According to the United Nations, it is estimated that by 2050, the number of people aged 80 years and older will have increased by 3 times. Increased longevity is often accompanied by structural and functional changes that occur throughout an individual's lifespan. These changes are often aggravated by chronic comorbidities, adopted behaviors or lifestyles, and environmental exposure, among other factors. Some of the related outcomes are loss of muscle strength, decreased balance control, and mobility impairments, which are strongly associated with the occurrence of falls in the elderly. Despite the continued undervaluation of the importance of knowledge on fall prevention among the elderly population by primary care health professionals, several evidence-based (single or multifaceted) fall prevention programs such as the Otago Exercise Program (OEP) have demonstrated a significant reduction in the risk of falls and fall-related injuries in the elderly within community settings. Recent studies have strived to integrate technology into physical exercise programs, which is effective for adherence and overcoming barriers to exercise, as well as improving physical functioning. Objective: This study aims to assess the impact of the OEP on the functionality of home-dwelling elderly using a common technological platform. Particularly, the impact on muscle strength, balance, mobility, risk of falling, the perception of fear of falling, and the perception of the elderly regarding the ease of use of technology are being examined in this study. Methods: A quasi-experimental study (before and after; single group) will be conducted with male and female participants aged 65 years or older living at home in the district of Porto. Participants will be recruited through the network COLABORAR, with a minimum of 30 participants meeting the study inclusion and exclusion criteria. All participants will sign informed consent forms. The data collection instrument consists of sociodemographic and clinical variables (self-reported), functional evaluation variables, and environmental risk variables. The data collection tool integrates primary and secondary outcome variables. The primary outcome is gait (timed-up and go test; normal step). The secondary outcome variables are lower limb strength and muscle resistance (30-second chair stand test), balance (4-stage balance test), frequency of falls, functional capacity (Lawton and Brody - Portuguese version), fear of falling (Falls Efficacy Scale International - Portuguese version), usability of the technology (System Usability Scale - Portuguese version), and environmental risk variables (home fall prevention checklist for older adults). Technological solutions, such as the FallSensing Home application and Kallisto wearable device, will be used, which will allow the detection and prevention of falls. The intervention is characterized by conducting the OEP through a common technological platform 3 times a week for 8 weeks. Throughout these weeks, the participants will be followed up in person or by telephone contact by the rehabilitation nurse. Considering the COVID-19 outbreak, all guidelines from the National Health Service will be followed. The project was funded by InnoStars, in collaboration with the Local EIT Health Regional Innovation Scheme Hub of the University of Porto. Results: This study was approved on October 9, 2020 by the Ethics Committee of Escola Superior de Enfermagem do Porto (ESEP). The recruitment process was meant to start in October, but due to the COVID-19 pandemic, it was suspended. We expect to restart the study by the beginning of the third quarter of 2021. Conclusions: The findings of this study protocol will contribute to the design and development of future robust studies for technological tests in a clinical context. Trial Registration: ISRCTN 15895163; https://www.isrctn.com/ISRCTN15895163 International Registered Report Identifier (IRRID): PRR1-10.2196/25781 ", doi="10.2196/25781", url="https://www.researchprotocols.org/2021/8/e25781", url="http://www.ncbi.nlm.nih.gov/pubmed/34387557" } @Article{info:doi/10.2196/28400, author="Kwan, Cho Rick Yiu and Liu, Wa Justina Yat and Fong, Kuen Kenneth Nai and Qin, Jing and Leung, Kwok-Yuen Philip and Sin, Kan Olive Suk and Hon, Yuen Pik and Suen, W. Lydia and Tse, Man-Kei and Lai, KY Claudia", title="Feasibility and Effects of Virtual Reality Motor-Cognitive Training in Community-Dwelling Older People With Cognitive Frailty: Pilot Randomized Controlled Trial", journal="JMIR Serious Games", year="2021", month="Aug", day="6", volume="9", number="3", pages="e28400", keywords="virtual reality", keywords="motor-cognitive training", keywords="cognitive frailty", keywords="game", keywords="feasibility", keywords="VR", keywords="training", keywords="older adults", keywords="frail", keywords="pilot study", keywords="randomized controlled trial", abstract="Background: Cognitive frailty refers to the coexistence of physical frailty and cognitive impairment, and is associated with many adverse health outcomes. Although cognitive frailty is prevalent in older people, motor-cognitive training is effective at enhancing cognitive and physical function. We proposed a virtual reality (VR) simultaneous motor-cognitive training program, which allowed older people to perform daily activities in a virtual space mimicking real environments. Objective: We aimed to (1) explore the feasibility of offering VR simultaneous motor-cognitive training to older people with cognitive frailty and (2) compare its effects with an existing motor-cognitive training program in the community on the cognitive function and physical function of older people with cognitive frailty. Methods: A two-arm (1:1), assessor-blinded, parallel design, randomized controlled trial was employed. The eligibility criteria for participants were: (1) aged ?60 years, (2) community dwelling, and (3) with cognitive frailty. Those in the intervention group received cognitive training (ie, cognitive games) and motor training (ie, cycling on an ergometer) simultaneously on a VR platform, mimicking the daily living activities of older people. Those in the control group received cognitive training (ie, cognitive games) on tablet computers and motor training (ie, cycling on the ergometer) sequentially on a non-VR platform. Both groups received a 30-minute session twice a week for 8 weeks. Feasibility was measured by adherence, adverse outcomes, and successful learning. The outcomes were cognitive function, physical frailty level, and walking speed. Results: Seventeen participants were recruited and randomized to either the control group (n=8) or intervention group (n=9). At baseline, the median age was 74.0 years (IQR 9.5) and the median Montreal Cognitive Assessment score was 20.0 (IQR 4.0). No significant between-group differences were found in baseline characteristics except in the number of chronic illnesses (P=.04). At postintervention, the intervention group (Z=--2.67, P=.01) showed a significantly larger improvement in cognitive function than the control group (Z=--1.19, P=.24). The reduction in physical frailty in the intervention group (Z=--1.73, P=.08) was similar to that in the control group (Z=--1.89, P=.06). Improvement in walking speed based on the Timed Up-and-Go test was moderate in the intervention group (Z=--0.16, P=.11) and greater in the control group (Z=--2.52, P=.01). The recruitment rate was acceptable (17/33, 52\%). Both groups had a 100\% attendance rate. The intervention group had a higher completion rate than the control group. Training was terminated for one participant (1/9, 11\%) due to minimal VR sickness (Virtual Reality Sickness Questionnaire score=18.3/100). Two participants (2/8, 25\%) in the control group withdrew due to moderate leg pain. No injuries were observed in either group. Conclusions: This study provides preliminary evidence that the VR simultaneous motor-cognitive training is effective at enhancing the cognitive function of older people with cognitive frailty. The effect size on frailty was close to reaching a level of significance and was similar to that observed in the control group. VR training is feasible and safe for older people with cognitive frailty. Trial Registration: ClinicalTrials.gov NCT04467216; https://clinicaltrials.gov/ct2/show/NCT04467216 ", doi="10.2196/28400", url="https://games.jmir.org/2021/3/e28400", url="http://www.ncbi.nlm.nih.gov/pubmed/34383662" } @Article{info:doi/10.2196/22491, author="Chen, Rai-Fu and Cheng, Kuei-Chen and Lin, Yu-Yin and Chang, I-Chiu and Tsai, Cheng-Han", title="Predicting Unscheduled Emergency Department Return Visits Among Older Adults: Population-Based Retrospective Study", journal="JMIR Med Inform", year="2021", month="Jul", day="28", volume="9", number="7", pages="e22491", keywords="classification model", keywords="decision tree", keywords="emergency department", keywords="older adult patients", keywords="unscheduled return visits", abstract="Background: Unscheduled emergency department return visits (EDRVs) are key indicators for monitoring the quality of emergency medical care. A high return rate implies that the medical services provided by the emergency department (ED) failed to achieve the expected results of accurate diagnosis and effective treatment. Older adults are more susceptible to diseases and comorbidities than younger adults, and they exhibit unique and complex clinical characteristics that increase the difficulty of clinical diagnosis and treatment. Older adults also use more emergency medical resources than people in other age groups. Many studies have reviewed the causes of EDRVs among general ED patients; however, few have focused on older adults, although this is the age group with the highest rate of EDRVs. Objective: This aim of this study is to establish a model for predicting unscheduled EDRVs within a 72-hour period among patients aged 65 years and older. In addition, we aim to investigate the effects of the influencing factors on their unscheduled EDRVs. Methods: We used stratified and randomized data from Taiwan's National Health Insurance Research Database and applied data mining techniques to construct a prediction model consisting of patient, disease, hospital, and physician characteristics. Records of ED visits by patients aged 65 years and older from 1996 to 2010 in the National Health Insurance Research Database were selected, and the final sample size was 49,252 records. Results: The decision tree of the prediction model achieved an acceptable overall accuracy of 76.80\%. Economic status, chronic illness, and length of stay in the ED were the top three variables influencing unscheduled EDRVs. Those who stayed in the ED overnight or longer on their first visit were less likely to return. This study confirms the results of prior studies, which found that economically underprivileged older adults with chronic illness and comorbidities were more likely to return to the ED. Conclusions: Medical institutions can use our prediction model as a reference to improve medical management and clinical services by understanding the reasons for 72-hour unscheduled EDRVs in older adult patients. A possible solution is to create mechanisms that incorporate our prediction model and develop a support system with customized medical education for older patients and their family members before discharge. Meanwhile, a reasonably longer length of stay in the ED may help evaluate treatments and guide prognosis for older adult patients, and it may further reduce the rate of their unscheduled EDRVs. ", doi="10.2196/22491", url="https://medinform.jmir.org/2021/7/e22491", url="http://www.ncbi.nlm.nih.gov/pubmed/34319244" } @Article{info:doi/10.2196/15641, author="Piau, Antoine and Steinmeyer, Zara and Charlon, Yoann and Courbet, Laetitia and Rialle, Vincent and Lepage, Benoit and Campo, Eric and Nourhashemi, Fati", title="A Smart Shoe Insole to Monitor Frail Older Adults' Walking Speed: Results of Two Evaluation Phases Completed in a Living Lab and Through a 12-Week Pilot Study", journal="JMIR Mhealth Uhealth", year="2021", month="Jul", day="5", volume="9", number="7", pages="e15641", keywords="frail older adults", keywords="walking speed", keywords="outpatient monitoring", keywords="activity tracker", keywords="shoe insert", abstract="Background: Recent World Health Organization reports propose wearable devices to collect information on activity and walking speed as innovative health indicators. However, mainstream consumer-grade tracking devices and smartphone apps are often inaccurate and require long-term acceptability assessment. Objective: Our aim is to assess the user acceptability of an instrumented shoe insole in frail older adults. This device monitors participants' walking speed and differentiates active walking from shuffling after step length calibration. Methods: A multiphase evaluation has been designed: 9 older adults were evaluated in a living lab for a day, 3 older adults were evaluated at home for a month, and a prospective randomized trial included 35 older adults at home for 3 months. A qualitative research design using face-to-face and phone semistructured interviews was performed. Our hypothesis was that this shoe insole was acceptable in monitoring long-term outdoor and indoor walking. The primary outcome was participants' acceptability, measured by a qualitative questionnaire and average time of insole wearing per day. The secondary outcome described physical frailty evolution in both groups. Results: Living lab results confirmed the importance of a multiphase design study with participant involvement. Participants proposed insole modifications. Overall acceptability had mixed results: low scores for reliability (2.1 out of 6) and high scores for usability (4.3 out of 6) outcomes. The calibration phase raised no particular concern. During the field test, a majority of participants (mean age 79 years) were very (10/16) or quite satisfied (3/16) with the insole's comfort at the end of the follow-up. Participant insole acceptability evolved as follows: 63\% (12/19) at 1 month, 50\% (9/18) at 2 months, and 75\% (12/16) at 3 months. A total of 9 participants in the intervention group discontinued the intervention because of technical issues. All participants equipped for more than a week reported wearing the insole every day at 1 month, 83\% (15/18) at 2 months, and 94\% (15/16) at 3 months for 5.8, 6.3, and 5.1 hours per day, respectively. Insole data confirmed that participants effectively wore the insole without significant decline during follow-up for an average of 13.5 days per 4 months and 5.6 hours per day. For secondary end points, the change in frailty parameters or quality of life did not differ for those randomly assigned to the intervention group compared to usual care. Conclusions: Our study reports acceptability data on an instrumented insole in indoor and outdoor walking with remote monitoring in frail older adults under real-life conditions. To date, there is limited data in this population set. This thin instrumentation, including a flexible battery, was a technical challenge and seems to provide an acceptable solution over time that is valued by participants. However, users still raised certain acceptability issues. Given the growing interest in wearable health care devices, these results will be useful for future developments. Trial Registration: ClinicalTrials.gov NCT02316600; https://clinicaltrials.gov/ct2/show/NCT02316600 ", doi="10.2196/15641", url="https://mhealth.jmir.org/2021/7/e15641", url="http://www.ncbi.nlm.nih.gov/pubmed/36260404" } @Article{info:doi/10.2196/19859, author="Kim, Ben and Hunt, Miranda and Muscedere, John and Maslove, M. David and Lee, Joon", title="Using Consumer-Grade Physical Activity Trackers to Measure Frailty Transitions in Older Critical Care Survivors: Exploratory Observational Study", journal="JMIR Aging", year="2021", month="Feb", day="23", volume="4", number="1", pages="e19859", keywords="frailty", keywords="frail elderly", keywords="wearable electronic devices", keywords="fitness trackers", keywords="activity trackers", keywords="heart rate", keywords="sleep monitoring", keywords="critical care outcomes", abstract="Background: Critical illness has been suggested as a sentinel event for frailty development in at-risk older adults. Frail critical illness survivors are affected by increased adverse health outcomes, but monitoring the recovery after intensive care unit (ICU) discharge is challenging. Clinicians and funders of health care systems envision an increased role of wearable devices in monitoring clinically relevant measures, as sensor technology is advancing rapidly. The use of wearable devices has also generated great interest among older patients, and they are the fastest growing group of consumer-grade wearable device users. Recent research studies indicate that consumer-grade wearable devices offer the possibility of measuring frailty. Objective: This study aims to examine the data collected from wearable devices for the progression of frailty among critical illness survivors. Methods: An observational study was conducted with 12 older survivors of critical illness from Kingston General Hospital in Canada. Frailty was measured using the Clinical Frailty Scale (CFS) at ICU admission, hospital discharge, and 4-week follow-up. A wearable device was worn between hospital discharge and 4-week follow-up. The wearable device collected data on step count, physical activity, sleep, and heart rate (HR). Patient assessments were reviewed, including the severity of illness, cognition level, delirium, activities of daily living, and comorbidity. Results: The CFS scores increased significantly following critical illness compared with the pre-ICU frailty level (P=.02; d=?0.53). Survivors who were frail over the 4-week follow-up period had significantly lower daily step counts than survivors who were not frail (P=.02; d=1.81). There was no difference in sleep and HR measures. Daily step count was strongly correlated with the CFS at 4-week follow-up (r=?0.72; P=.04). The average HR was strongly correlated with the CFS at hospital discharge (r=?0.72; P=.046). The HR SD was strongly correlated (r=0.78; P=.02) with the change in CFS from ICU admission to 4-week follow-up. No association was found between the CFS and sleep measures. The pattern of increasing step count over the 4-week follow-up period was correlated with worsening of frailty (r=.62; P=.03). Conclusions: This study demonstrated an association between frailty and data generated from a consumer-grade wearable device. Daily step count and HR showed a strong association with the frailty progression of the survivors of critical illness over time. Understanding this association could unlock a new avenue for clinicians to monitor and identify a vulnerable subset of the older adult population that might benefit from an early intervention. ", doi="10.2196/19859", url="https://aging.jmir.org/2021/1/e19859", url="http://www.ncbi.nlm.nih.gov/pubmed/33620323" } @Article{info:doi/10.2196/19227, author="Mach, Markus and Watzal, Victoria and Hasan, Waseem and Andreas, Martin and Winkler, Bernhard and Weiss, Gabriel and Strouhal, Andreas and Adlbrecht, Christopher and Delle Karth, Georg and Grabenw{\"o}ger, Martin", title="Fitness-Tracker Assisted Frailty-Assessment Before Transcatheter Aortic Valve Implantation: Proof-of-Concept Study", journal="JMIR Mhealth Uhealth", year="2020", month="Oct", day="15", volume="8", number="10", pages="e19227", keywords="frailty", keywords="activity", keywords="fitness", keywords="tracker", keywords="transcatheter aortic valve implantation", keywords="transcatheter aortic valve repair", abstract="Background: While transcatheter aortic valve replacement (TAVR) has revolutionized the treatment of aortic valve stenosis, wearable health-monitoring devices are gradually transforming digital patient care. Objective: The aim of this study was to develop a simple, efficient, and economical method for preprocedural frailty assessment based on parameters measured by a wearable health-monitoring device. Methods: In this prospective study, we analyzed data of 50 consecutive patients with mean (SD) age of 77.5 (5.1) years and a median (IQR) European system for cardiac operative risk evaluation (EuroSCORE) II of 3.3 (4.1) undergoing either transfemoral or transapical TAVR between 2017 and 2018. Every patient was fitted with a wrist-worn health-monitoring device (Garmin Vivosmart 3) for 1 week prior to the procedure. Twenty different parameters were measured, and threshold levels for the 3 most predictive categories (ie, step count, heart rate, and preprocedural stress) were calculated. Patients were assigned 1 point per category for exceeding the cut-off value and were then classified into 4 stages (no, borderline, moderate, and severe frailty). Furthermore, the FItness-tracker assisted Frailty-Assessment Score (FIFA score) was compared with the scores of the preprocedural gait speed category derived from the 6-minute walk test (GSC-6MWT) and the Edmonton Frail Scale classification (EFS-C). The primary study endpoint was hospital mortality. Results: The overall preprocedural stress level (P=.02), minutes of high stress per day (P=.02), minutes of rest per day (P=.045), and daily heart rate maximum (P=.048) as single parameters were the strongest predictors of hospital mortality. When comparing the different frailty scores, the FIFA score demonstrated the greatest predictive power for hospital mortality (FIFA area under the curve [AUC] 0.844, CI 0.656-1.000; P=.048; GSC-6MWT AUC 0.671, CI 0.487-0.855; P=.42; EFS-C AUC 0.636, CI 0.254-1.000; P=.44). Conclusions: This proof-of-concept study demonstrates the strong predictive performance of the FIFA score compared to that of the conventional frailty assessments. ", doi="10.2196/19227", url="https://mhealth.jmir.org/2020/10/e19227", url="http://www.ncbi.nlm.nih.gov/pubmed/33055057" } @Article{info:doi/10.2196/19732, author="Kim, Ben and McKay, M. Sandra and Lee, Joon", title="Consumer-Grade Wearable Device for Predicting Frailty in Canadian Home Care Service Clients: Prospective Observational Proof-of-Concept Study", journal="J Med Internet Res", year="2020", month="Sep", day="3", volume="22", number="9", pages="e19732", keywords="frailty", keywords="mobile health", keywords="wearables", keywords="physical activity", keywords="home care", keywords="prediction", keywords="predictive modeling, older adults", keywords="activities of daily living, sleep", abstract="Background: Frailty has detrimental health impacts on older home care clients and is associated with increased hospitalization and long-term care admission. The prevalence of frailty among home care clients is poorly understood and ranges from 4.0\% to 59.1\%. Although frailty screening tools exist, their inconsistent use in practice calls for more innovative and easier-to-use tools. Owing to increases in the capacity of wearable devices, as well as in technology literacy and adoption in Canadian older adults, wearable devices are emerging as a viable tool to assess frailty in this population. Objective: The objective of this study was to prove that using a wearable device for assessing frailty in older home care clients could be possible. Methods: From June 2018 to September 2019, we recruited home care clients aged 55 years and older to be monitored over a minimum of 8 days using a wearable device. Detailed sociodemographic information and patient assessments including degree of comorbidity and activities of daily living were collected. Frailty was measured using the Fried Frailty Index. Data collected from the wearable device were used to derive variables including daily step count, total sleep time, deep sleep time, light sleep time, awake time, sleep quality, heart rate, and heart rate standard deviation. Using both wearable and conventional assessment data, multiple logistic regression models were fitted via a sequential stepwise feature selection to predict frailty. Results: A total of 37 older home care clients completed the study. The mean age was 82.27 (SD 10.84) years, and 76\% (28/37) were female; 13 participants were frail, significantly older (P<.01), utilized more home care service (P=.01), walked less (P=.04), slept longer (P=.01), and had longer deep sleep time (P<.01). Total sleep time (r=0.41, P=.01) and deep sleep time (r=0.53, P<.01) were moderately correlated with frailty. The logistic regression model fitted with deep sleep time, step count, age, and education level yielded the best predictive performance with an area under the receiver operating characteristics curve value of 0.90 (Hosmer-Lemeshow P=.88). Conclusions: We proved that a wearable device could be used to assess frailty for older home care clients. Wearable data complemented the existing assessments and enhanced predictive power. Wearable technology can be used to identify vulnerable older adults who may benefit from additional home care services. ", doi="10.2196/19732", url="https://www.jmir.org/2020/9/e19732", url="http://www.ncbi.nlm.nih.gov/pubmed/32880582" } @Article{info:doi/10.2196/16678, author="Tarekegn, Adane and Ricceri, Fulvio and Costa, Giuseppe and Ferracin, Elisa and Giacobini, Mario", title="Predictive Modeling for Frailty Conditions in Elderly People: Machine Learning Approaches", journal="JMIR Med Inform", year="2020", month="Jun", day="4", volume="8", number="6", pages="e16678", keywords="predictive modeling", keywords="frailty", keywords="machine learning", keywords="genetic programming", keywords="imbalanced dataset", keywords="elderly people", keywords="classification", abstract="Background: Frailty is one of the most critical age-related conditions in older adults. It is often recognized as a syndrome of physiological decline in late life, characterized by a marked vulnerability to adverse health outcomes. A clear operational definition of frailty, however, has not been agreed so far. There is a wide range of studies on the detection of frailty and their association with mortality. Several of these studies have focused on the possible risk factors associated with frailty in the elderly population while predicting who will be at increased risk of frailty is still overlooked in clinical settings. Objective: The objective of our study was to develop predictive models for frailty conditions in older people using different machine learning methods based on a database of clinical characteristics and socioeconomic factors. Methods: An administrative health database containing 1,095,612 elderly people aged 65 or older with 58 input variables and 6 output variables was used. We first identify and define six problems/outputs as surrogates of frailty. We then resolve the imbalanced nature of the data through resampling process and a comparative study between the different machine learning (ML) algorithms -- Artificial neural network (ANN), Genetic programming (GP), Support vector machines (SVM), Random Forest (RF), Logistic regression (LR) and Decision tree (DT) -- was carried out. The performance of each model was evaluated using a separate unseen dataset. Results: Predicting mortality outcome has shown higher performance with ANN (TPR 0.81, TNR 0.76, accuracy 0.78, F1-score 0.79) and SVM (TPR 0.77, TNR 0.80, accuracy 0.79, F1-score 0.78) than predicting the other outcomes. On average, over the six problems, the DT classifier has shown the lowest accuracy, while other models (GP, LR, RF, ANN, and SVM) performed better. All models have shown lower accuracy in predicting an event of an emergency admission with red code than predicting fracture and disability. In predicting urgent hospitalization, only SVM achieved better performance (TPR 0.75, TNR 0.77, accuracy 0.73, F1-score 0.76) with the 10-fold cross validation compared with other models in all evaluation metrics. Conclusions: We developed machine learning models for predicting frailty conditions (mortality, urgent hospitalization, disability, fracture, and emergency admission). The results show that the prediction performance of machine learning models significantly varies from problem to problem in terms of different evaluation metrics. Through further improvement, the model that performs better can be used as a base for developing decision-support tools to improve early identification and prediction of frail older adults. ", doi="10.2196/16678", url="http://medinform.jmir.org/2020/6/e16678/", url="http://www.ncbi.nlm.nih.gov/pubmed/32442149" } @Article{info:doi/10.2196/jmir.2529, author="Fontecha, Jes{\'u}s and Herv{\'a}s, Ramon and Bravo, Jos{\'e} and Navarro, Javier Fco", title="A Mobile and Ubiquitous Approach for Supporting Frailty Assessment in Elderly People", journal="J Med Internet Res", year="2013", month="Sep", day="04", volume="15", number="9", pages="e197", keywords="frailty", keywords="mobile computing", keywords="similarity", keywords="elderly people", abstract="Background: Frailty is a health condition related to aging and dependence. A reduction in or delay of the frailty state can improve the quality of life of the elderly. However, providing frailty assessments can be difficult because many factors must be taken into account. Usually, measurement of these factors is performed in a noncentralized manner. Additionally, the lack of quantitative methods for analysis makes it impossible for the diagnosis to be as complete or as objective as it should be. Objective: To develop a centralized mobile system to conduct elderly frailty assessments in an accurate and objective way using mobile phone capabilities. Methods: The diagnosis of frailty includes two fundamental aspects: the analysis of gait activity as the main predictor of functional disorders, and the study of a set of frailty risk factors from patient records. Thus, our system has several stages including gathering information about gait using accelerometer-enabled mobile devices, collecting values of frailty factors, performing analysis through similarity comparisons with previous data, and displaying the results for frailty on the mobile devices in a formalized way. Results: We developed a general mechanism to assess the frailty state of a group of elders by using mobile devices as supporting tools. In collaboration with geriatricians, two studies were carried out on a group of 20 elderly patients (10 men and 10 women), previously selected from a nursing home. Frailty risk factors for each patient were collected at three different times over the period of a year. In the first study, data from the group of patients were used to determine the frailty state of a new incoming patient. The results were valuable for determining the degree of frailty of a specific patient in relation to other patients in an elderly population. The most representative similarity degrees were between 73.4\% and 71.6\% considering 61 frailty factors from 64 patient instances. Additionally, from the provided results, a physician could group the elders by their degree of similarity influencing their care and treatment. In the second study, the same mobile tool was used to analyze the frailty syndrome from a nutritional viewpoint on 10 patients of the initial group during 1 year. Data were acquired at three different times, corresponding to three assessments: initial, spontaneous, and after protein supplementation. The subsequent analysis revealed a general deterioration of the subset of elders from the initial assessment to the spontaneous assessment and also an improvement of biochemical and anthropometric parameters in men and women from the spontaneous assessment to the assessment after the administration of a protein supplement. Conclusions: The problem of creating a general frailty index is still unsolved. However, in recent years, there has been an increase in the amount of research on this subject. Our studies took advantage of mobile device features (accelerometer sensors, wireless communication capabilities, and processing capacities among others) to develop a new method that achieves an objective assessment of frailty based on similarity results for an elderly population, providing an essential support for physicians. ", doi="10.2196/jmir.2529", url="http://www.jmir.org/2013/9/e197/", url="http://www.ncbi.nlm.nih.gov/pubmed/24004497" }