ADMarker: A Multi-Modal Federated Learning System for Monitoring Digital Biomarkers of Alzheimer's Disease

Alzheimer's Disease (AD) and related dementia are a growing global health challenge due to the aging population. In this paper, we present ADMarker, the first end-to-end system that integrates multi-modal sensors and new federated learning algorithms for detecting multidimensional AD digital biomarkers in natural living environments. ADMarker features a novel three-stage multi-modal federated learning architecture that can accurately detect digital biomarkers in a privacy-preserving manner. Our approach collectively addresses several major real-world challenges, such as limited data labels, data heterogeneity, and limited computing resources. We built a compact multi-modality hardware system and deployed it in a four-week clinical trial involving 91 elderly participants. The results indicate that ADMarker can accurately detect a comprehensive set of digital biomarkers with up to 93.8% accuracy and identify early AD with an average of 88.9% accuracy. ADMarker offers a new platform that can allow AD clinicians to characterize and track the complex correlation between multidimensional interpretable digital biomarkers, demographic factors of patients, and AD diagnosis in a longitudinal manner

Changes in nursing education in Hong Kong - Progressive or regressive?

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Cross-cultural applicability of the self-care self-efficacy scale in a multi-national study

The Self-Care Self-Efficacy Scale (SCSES) was newly developed as a self-report measure for self-care self-efficacy for chronic illness. This study investigated its measurement equivalence (ME) in different cultural groups, including United States, China (Hong Kong), Italy, and Brazil. Design A multi-national study for cross-cultural validation of the Scale. Methods From January 2015 - December 2018, investigators recruited 957 patients (United State: 200; Hong Kong: 300; Italy: 285; and Brazil: 142) with chronic illness from inpatient and outpatient settings. The SCSES was administered and clinical and demographic data were collected from participants. Based on the Meredith framework, multi-group confirmatory factor analysis evaluated the configural, metric, scalar, and strict invariance of the scale across the four populations through a series of nested models, with evaluation of reliability and coherence of the factor solution. Results The mean ages of the groups ranged from 65–77 years, 56.4% was male. The Cronbach's alpha coefficients of the single-factor SCSES were 0.93, 0.89, 0.92, and 0.90 for the United States, China (Hong Kong), Italy, and Brazil, respectively. Three of the four levels of ME were partially or totally supported. The highest level achieved was partial scalar invariance level (χ2 [52] = 313.4, p < 0.001; RMSEA = 0.067; 95% CI = 0.056–0.077; CFI = 0.966; TLI = 0.960, SRMR = 0.080). Conclusion Patients from the four countries shared the same philosophical orientation towards scale items, although some of the items contributed differently to represent the concept and participants shared the same schemata for score interpretation. Impact Self-efficacy is important in producing effective and sustainable self-care behavioural changes. Cultural ideation shapes the ways individuals interpret and report their self-care self-efficacy. The study findings support cross-cultural and cross-national utility of the SCSES for research on self-care across United States, China (Hong Kong), Italy, and Brazil