BackgroundStudies on life-space (LS) and its determinants have previously been limited to community-dwelling subjects but are lacking in institutionalized older persons. The purpose of this study was to provide an advanced descriptive analysis of LS in nursing home residents and to identify associated factors based on an established theoretical framework, using an objective, sensor-based assessment with a high spatiotemporal resolution.MethodsCross-sectional study in two nursing homes in Heidelberg, Germany (n = 65; mean age: 82.9 years; 2/3 female). Changes of location in the nursing home (Transits) as well as time spent away from the private room (TAFR) were assessed using a wireless sensor network. Measures of physical, psychosocial, cognitive, socio-demographic, and environmental factors were assessed via established motor performance tests, interviews, and proxy-reports.ResultsLS of residents was largely restricted to the private room and the surrounding living unit (90%); 10% of daytime was spent outside the living unit and/or the facility. On average, TAFR was 5.1 h per day (±2.3; Range: 0–8); seven Transits (6.9 ± 3.2; Range: 0–18) were performed per day. Linear regression analyses revealed being male, lower gait speed, higher cognitive status, and lower apathy to be associated with more Transits; higher gait speed, lower cognitive status, and less depressive symptoms were associated with more TAFR. LS was significantly increased during institutional routines (mealtimes) as compared to the rest of the day.ConclusionsThe sensor-based LS assessment provided new, objective insights into LS of institutionalized persons living in nursing homes. It revealed that residents’ LS was severely limited to private rooms and adjacent living units, and that in institutional settings, daily routines such as meal times seem to be the major determinant of LS utilization. Gait speed, apathy, and depressive symptoms as well as institutional meal routines were the only modifiable predictors of Transits and/or TAFR, and thus have greatest potential to lead to an enhancement of LS when targeted with interventions.Trial registrationCurrent Controlled Trials ISRCTN96090441 (retrospectively registered).

A PA intervention in the NH setting impacts on LS utilization as measured using sensor-based assessment. The program has proven its practical sustainability when being handed over to NH personnel for continuation in daily practice. Further research is needed to determine whether an increase in LS utilization also impacts on social participation and quality of life.

This article examines the end-of-life development of depressive symptoms and characterizes prototypical groups following the same depressive symptoms development. We modeled time-to-death-related trajectories of depressive symptoms (Center for Epidemiologic Studies Depression Scale), applying a latent class growth analysis to deceased older adults from the English Longitudinal Study of Aging (Waves 1 to 5; NTime 1 (T1) = 2,219; MAge(T1) = 73.9 years, SDAge(T1) = 9.4 years; 51% male, 1% non-White). Four prototypical trajectories of depressive symptoms were identified at the end of life: a stably nondepressed group (31.2%); 2 groups with an exponential terminal symptom increase, of which 1 was nondepressed and 1 low depressed (8.3% and 38.4%, respectively); and a stably depressed group (22.2%). Using a combination of growth curve models and individual level and slope values as predictor variables showed that individuals suffering from increasing sensory, mobility, or overall health problems or decreasing quality of life were more likely to have an increase in symptoms of depression in their last years of life. Men were more likely to be stably nondepressed and women more likely to be chronically depressed. We conclude that a group-based analysis of end-of-life depressive symptoms is useful in adding to the understanding of distance-to-death psychology at large as well as pointing to preventive and intervention strategies when it comes to late-life depressive mood. (PsycINFO Database Record

Implementing an innovative PA intervention appears to be a promising approach to prevent the increase of NH residents' depressive symptoms. At the data-analytical level, GLMMs seem to be a promising tool for intervention research at large, because all longitudinally available data points and non-normality of outcome data can be considered.