Description Depressive symptoms are pervasive among older people, with 11% to 49% of the population currently experiencing depressive symptoms.[1, 2] Depressive symptoms are correlated with poorer quality of life, impaired daily function, elevated risk of other chronic diseases and mortality, and hence place a major burden on health care systems, patients and their caregivers. Effective screening of depressive symptoms in older people and subsequent intervention has proven to be effective in reducing suicidal thoughts, and reducing depressive symptoms.[7 ] Economic evaluation has revealed that screening with subsequent intervention is cost-effective for the healthcare system. Yet, timely detection of depressive symptoms remains a challenge, with recognition of depressive symptoms as low as 36%. Prior research has suggested that this may due to the lack of large-scale screening programs, and it has been estimated that only 4% of the general population visiting a primary healthcare provider are screened for depressive symptoms in the United States. Recent studies revealed that gait performance is significantly associated with the occurrence of depressive symptoms.[11-13] Older people with slower gait speed[11, 13] or shorter step length  were found to have twice the odds of developing depressive symptoms in the future. Walking speed and other characteristics of gait can be assessed using wearable sensors. Wearable sensors, often incorporating accelerometers and gyroscopes, may hold several advantages over clinical mobility tests. First, wearable sensors are capable of reliably and validly measuring parameters that reflect both gait quantity and quality. [14, 15] Second, it is feasible to conduct several days of continuous measurements, which captures gait performance of daily-life. As gait in daily-life may reflect an individual’s “usual” performance, rather than a “clinical” performance, it may better predict the development of depressive symptoms. Third, motion detecting sensors, often incorporated into smart watches or smartphones, are commercially available and increasingly ubiquitous, making sensor-based gait assessments and analysis easy to conduct remotely. This reduces commute time, risks of disease transmission and barriers towards medical attention. Further, wearable sensors provide a time- and cost-efficient means for large scale screening. However, no studies to date have investigated the association between depressive symptoms and gait with the use of wearable sensors. It has been proposed that evaluations of mental health through measuring symptom severity is incomplete, in part because an absence of mental illness is not equivalent to being mentally healthy. [17, 18] In this regard, composite scores measuring wellbeing have been developed to measure both subjective wellbeing (e.g. feelings and satisfaction with life) and psychological wellbeing (e.g. development of human potential).  Examining how gait is associated with wellbeing may provide a more complete understanding of how mobility affects mental health. The aim of this study is to determine the association of daily-life gait parameters, measured through wearable sensors, with depressive symptoms and reduced wellbeing. We will investigate whether onset of depressive symptoms and reduced wellbeing can be predicted with daily-life gait parameters in older people over two years.
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