Reliability of accelerometric measurement of physical activity in older adults-the benefit of using the trimmed sum

There is general consensus that physical activity is important for preserving functional capacities of older adults and positively influencing quality of life. While accelerometry is widely accepted and applied to assess physical activity in studies, several problems with this method remain (e.g., low retest reliability, measurement errors). The aim of this study was to test the intra-instrumental retest reliability of a wrist-worn accelerometer in a 3-day measurement of physical activity in older adults and to compare different estimators. A sample of 123 older adults (76.5?±?5.1?years, 59?% female) wore a uniaxial accelerometer continuously for 1?week. The data were split into two repeated measurement values (week set) of 3?days each. The sum, the 80?C99th quantiles and the 80?C99th trimmed sums were built for each week set. Retest reliability was assessed for each estimator and graphically demonstrated by Bland?CAltman plots. The intraclass correlation of the retest reliability ranged from 0.22 to 0.91. Retest reliability increases when a more robust estimator than the overall sum is used. Therefore, the trimmed sum can be recommended as a conservative estimate of the physical activity level of older adults.     

Environmental Influences on Well-Being: A Dyadic Latent Panel Analysis of Spousal Similarity

This article uses dyadic latent panel analysis (DLPA) to examine environmental influences on well-being. DLPA requires longitudinal dyadic data. It decomposes the observed variance of both members of a dyad into a trait, state, and an error component. Furthermore, state variance is decomposed into initial and new state variance. Total observed similarity between members of a dyad is decomposed into trait similarity, initial state similarity, new state similarity, and error similarity. Dyadic similarity in new state variance reveals that both members of a dyad change in the same direction, which is a strong indication of environmental effects. DLPA is used to examine environmental influences on life satisfaction and domain satisfaction based on 22 annual assessments of married couples in the German Socio-Economic Panel Study (N’s = 607–740). The results show high similarity in new state variance for life satisfaction and objectively identical domains (household income, housing), and less similarity for objectively less similar domains (recreation, health). This finding provides strong evidence for environmental influences on well-being. In addition, the results show high trait similarity. The implications of the latter finding for interpretation of behavioral genetics studies of well-being are discussed.     

Assessing physical activity in inpatient rehabilitation—sensor-based validation of the PAIR

Increased physical activity is positively associated with better health in community-dwelling older persons. It is unclear whether physical activity also influences success of inpatient rehabilitation. For the assessment of physical activity in inpatient rehabilitation the Physical Activity in Inpatient Rehabilitation Assessment (PAIR), a short questionnaire based on five questions, was developed and preliminary validated. In this study, the PAIR was validated against a sensor-based physical activity measurement. Seventy functionally impaired and cognitively mostly intact patients of a German geriatric inpatient rehabilitation clinic who had undergone hip surgery (n?=?62 women, median age?=?83 years) participated. Physical activity was measured using the PAIR and a sensor-based activity monitor (Physilog ®; BioAGM, CH). Assessments were conducted at admission (T1) and 2 weeks later (T2) during the rehabilitation process. To assess concurrent and predictive validity, Spearman correlations and linear regression models were calculated using sensor-based walking activity and uptime activity (walking and standing time) as dependent variables. Criterion-related concurrent validity using physical activity sensors was weak to moderate. Correlations were slightly higher at T2 (r?=?0.45-0.53) than at T1 (r?=?0.44-0.46). The objectively measured variance of physical activity, explained by the PAIR, ranged from 25 to 43 %. PAIR activity scores and sensor-based walking or total activity increased in a dose-dependent manner, confirming the scoring system of the PAIR. The application time was usually less than 2 min. The validity of the PAIR is weak to moderate when compared to a sensor-based activity monitor and comparable to existing physical activity assessments for community-dwelling older adults.     

Should I Stay or Should I Go? Explaining Turnover Intentions with Organizational Identification and Job Satisfaction*

The social identity approach is a powerful theoretical framework for the understanding of individuals' behaviour. The main argument is that individuals think and act on behalf of the group they belong to because this group membership adds to their social identity, which partly determines one's self‐esteem. In the organizational world, social identity and self‐categorization theories state that a strong organizational identification is associated with low turnover intentions. Because identification is the more general perception of shared fate between employee and organization, we propose that the relationship between identification and turnover will be mediated by job satisfaction as the more specific evaluation of one's task and working conditions. In four samples we found organizational identification feeding into job satisfaction, which in turn predicts turnover intentions.     

The Value of Weather Information for E‐Commerce Operations

To be efficient, logistics operations in e‐commerce require warehousing and transportation resources to be aligned with sales. Customer orders must be fulfilled with short lead times to ensure high customer satisfaction, and the costly under‐utilization of workers must be avoided. To approach this ideal, forecasting order quantities with high accuracy is essential. Many drivers of online sales, including seasonality, special promotions and public holidays, are well known, and they have been frequently incorporated into forecasting approaches. However, the impact of weather on e‐commerce operations has not been rigorously analyzed. In this study, we integrate weather data into the sales forecasting of the largest European online fashion retailer. We find that sunshine, temperature, and rain have a significant impact on daily sales, particularly in the summer, on weekends, and on days with extreme weather. Using weather forecasts, we have significantly improved sales forecast accuracy. We find that including weather data in the sales forecast model can lead to fewer sales forecast errors, reducing them by, on average, 8.6% to 12.2% and up to 50.6% on summer weekends. In turn, the improvement in sales forecast accuracy has a measurable impact on logistics and warehousing operations. We quantify the value of incorporating weather forecasts in the planning process for the order fulfillment center workforce and show how their incorporation can be leveraged to reduce costs and increase performance. With a perfect information planning scenario, excess costs can be reduced by 11.6% compared with the cost reduction attainable with a baseline model that ignores weather information in workforce planning.     

A hierarchical model for ordinal matrix factorization

This paper proposes a hierarchical probabilistic model for ordinal matrix factorization. Unlike previous approaches, we model the ordinal nature of the data and take a principled approach to incorporating priors for the hidden variables. Two algorithms are presented for inference, one based on Gibbs sampling and one based on variational Bayes. Importantly, these algorithms may be implemented in the factorization of very large matrices with missing entries.     

战后德国的男性人口短缺——规模、结构及其影响因素分析

本文对战后德国男性人口短缺的规模、结构及其影响因素进行了认真的分析.研究表明战后德国男性人口短缺非常严重,但随着时间的推移,男性短缺矛盾逐年趋于缓和.究其原因,性别结构因素在其中扮演了绝对重要的角色,但其影响逐年减弱,年龄结构因素的影响有限,而人口规律因素的影响则有所增强.     

Bayesian adaptive dose‐escalation procedures for binary and continuous responses utilizing a gain function

One of the main aims of early phase clinical trials is to identify a safe dose with an indication of therapeutic benefit to administer to subjects in further studies. Ideally therefore, dose‐limiting events (DLEs) and responses indicative of efficacy should be considered in the dose‐escalation procedure. Several methods have been suggested for incorporating both DLEs and efficacy responses in early phase dose‐escalation trials. In this paper, we describe and evaluate a Bayesian adaptive approach based on one binary response (occurrence of a DLE) and one continuous response (a measure of potential efficacy) per subject. A logistic regression and a linear log‐log relationship are used respectively to model the binary DLEs and the continuous efficacy responses. A gain function concerning both the DLEs and efficacy responses is used to determine the dose to administer to the next cohort of subjects. Stopping rules are proposed to enable efficient decision making. Simulation results shows that our approach performs better than taking account of DLE responses alone. To assess the robustness of the approach, scenarios where the efficacy responses of subjects are generated from an E _max model, but modelled by the linear log–log model are also considered. This evaluation shows that the simpler log–log model leads to robust recommendations even under this model showing that it is a useful approximation to the difficulty in estimating E _max model. Additionally, we find comparable performance to alternative approaches using efficacy and safety for dose‐finding. Copyright © 2015 John Wiley & Sons, Ltd.     

An Experimental Test of Loss Aversion

This paper experimentally investigates a preference condition for loss aversion in the framework of cumulative prospect theory (CPT). We propose the concepts of absolute and relative loss premiums in order to measure the extent of loss aversion and to derive notions of increasing, constant, and decreasing loss aversion. While in only one of the 28 choice situations analyzed loss neutrality and loss seeking can be rejected, about 51% of all choices are loss averse and, due to the large extent of loss aversion revealed by these choices, the average loss premium is positive for most choice situations. Female subjects exhibit both a more frequent occurrence and a larger extent of loss aversion.     

Effect of Changes in Living Conditions on Well-Being: A Prospective Top–Down Bottom–Up Model

Using the German Socio-Economic Panel, we examined life-satisfaction and housing satisfaction before and after moving (N = 3,658 participants from 2,162 households) with univariate and bivariate two-intercept two-slope latent growth models. The main findings were (a) a strong and persistent increase in average levels of housing satisfaction, (b) no increase in average life-satisfaction, (c) low stability in individuals’ level of housing satisfaction, and (d) high stability in individuals’ level of life-satisfaction. The results are discussed in the context of top–down and bottom–up models as well as adaptation theories of well-being. We conclude that moving or living in a better home is unrelated to life-satisfaction judgments for two reasons. First, housing makes a small contribution to life-satisfaction judgments. Second, positive effects of better housing are undermined by the greater costs of living in a better home. The results provide no support for the prediction of adaptation theory that shifting aspirations undermine the benefits of living in a better home.