Falls have been recognized as the major cause of accidental death and injury in people aged 65 and above. The timely prediction of fall risks can help identify older adults prone to falls and implement preventive interventions. Recent advancements in wearable sensor-based technologies and big data analysis have spurred the development of accurate, affordable, and easy-to-use approaches to fall risk assessment. The objective of this study was to systematically assess the current state of wearable sensor-based technologies for fall risk assessment among community-dwelling older adults. Twenty-five of 614 identified research articles were included in this review. A comprehensive comparison was conducted to evaluate these approaches from several perspectives. In general, these approaches provide an accurate and effective surrogate for fall risk assessment. The accuracy of fall risk prediction can be influenced by various factors such as sensor location, sensor type, features utilized, and data processing and modeling techniques. Features constructed from the raw signals are essential for predictive model development. However, more investigations are needed to identify distinct, clinically interpretable features and develop a general framework for fall risk assessment based on the integration of sensor technologies and data modeling.
While studies have observed the short-term impact of nonstandard employment on fertility in low-fertility countries, few have sought to examine its long-term consequences despite the abundant evidence regarding the ‘scarring effects’ exerted by early-career disadvantages on later career outcomes. Our study addresses this gap by examining how the employment disadvantages that men had experienced during their early-stage careers affect their later fertility outcomes in Japan, which is a country characterized by rising nonstandard employment and a strong gender-based division of labor. Analyses of retrospective occupational history data including work entry cohorts from between 1970 and 2015 with multistate life-table models indicate that early-career disadvantages negatively affect men’s long-term fertility outcomes. Compared to men whose first jobs were in standard employment, men whose first job constituted nonstandard employment were approximately 30% less likely to have entered into marriage and approximately 35% less likely to have had a child by age 45. The scarring effect of nonstandard employment was particularly significant for the cohort who entered the labor market after the collapse of the bubble economy. Counterfactual estimates suggest that two-thirds of the cases of declining fertility due to nonstandard employment is explained by delayed marriage. We discuss the potential explanations of these results as well as the theoretical implications in other low fertility contexts.
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