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.     

Applications and Implementation DECISION SUPPORT SYSTEMS: AN EMPIRICAL ASSESSMENT FOR DECISION MAKING

A laboratory experiment examined the effects of applying decision support system (DSS) technology to decision making in ill-structured problem environments under varying information conditions. Marketing executives participated in the experiment which investigated the effects of DSS availability, DSS training, and data availability on dependent variables that included: (1) the number of alternatives considered by a subject during decision making, (2) the period of time spent by a subject to complete the decision-making process, (3) the subject's perceived confidence in the decisions he or she had made, (4) the amount of data considered by a subject's during decision making, (5) the individual subject's decision processing, and (6) the subject's performance overall. Our results indicate that all three factors significantly affect the number of alternatives considered by subjects during the decision-making process. We therefore suggest that DSS training be coordinated with decision training in order to realize the potential of DSSs as described in the DSS literature.     

Young Adult Gambling Behaviors and their Relationship with the Persistence of ADHD

Young adulthood is a period renowned for engagement in impulsive and risky behaviors, including gambling. There are some indications that young adults exhibit higher gambling rates in comparison to older adults. Problem gambling has also been linked to ADHD. This longitudinal study examines the relationship between gambling and ADHD among an epidemiological sample of young adults (n = 235; males = 179, females = 56) aged 18-24. Results indicate that individuals who report childhood ADHD symptoms which persist into young adulthood experience greater gambling problem severity than participants with no ADHD or those with non-persistent ADHD.     

Risk Analysis for U.S. Offshore Wind Farms: The Need for an Integrated Approach

Wind power is becoming an increasingly important part of the global energy portfolio, and there is growing interest in developing offshore wind farms in the United States to better utilize this resource. Wind farms have certain environmental benefits, notably near‐zero emissions of greenhouse gases, particulates, and other contaminants of concern. However, there are significant challenges ahead in achieving large‐scale integration of wind power in the United States, particularly offshore wind. Environmental impacts from wind farms are a concern, and these are subject to a number of on‐going studies focused on risks to the environment. However, once a wind farm is built, the farm itself will face a number of risks from a variety of hazards, and managing these risks is critical to the ultimate achievement of long‐term reductions in pollutant emissions from clean energy sources such as wind. No integrated framework currently exists for assessing risks to offshore wind farms in the United States, which poses a challenge for wind farm risk management. In this “Perspective”, we provide an overview of the risks faced by an offshore wind farm, argue that an integrated framework is needed, and give a preliminary starting point for such a framework to illustrate what it might look like. This is not a final framework; substantial work remains. Our intention here is to highlight the research need in this area in the hope of spurring additional research about the risks to wind farms to complement the substantial amount of on‐going research on the risks from wind farms.     

Estimating the effectiveness of a misdemeanor drug diversion program using propensity score matching and survival analyses

This study analyzes three years of data on misdemeanor drug offenders in Winnebago County, Wisconsin. A portion of these offenders opted into a Misdemeanor Drug Diversion Program (MDDP) offered instead of traditional adjudication. Recidivism in the treatment and comparison groups is estimated using standard binary response techniques augmented with propensity score matching to address selection bias. Results show that the MDDP reduces the probability of re-offense by 16%, after adjusting for possible selection bias. Cox proportional hazard modeling is also used to assess time-to-re-offense differentials between the treatment and comparison groups. The survival analysis indicates that the hazard rate of re-offense is 60% lower per day among those treated with the MDDP program than those who did not complete the program. The average number of days to re-offense among those that do re-offend is 297 days in the treatment group and 203 days in the comparison group.     

Economic design of acceptance sampling plans for truncated life test using Frechet distribution

In this article designing of acceptance sampling plans for the truncated life test is proposed using economic approach by assuming that the lifetime of a product follows Frechet distribution based on median. The optimal sampling plans to meet the consumer’s confidence level with minimum total cost are designed. Efficiency of the proposed plan is also analyzed.