Accelerometry analysis of physical activity and sedentary behavior in older adults: a systematic review and data analysis

Accelerometers objectively monitor physical activity and sedentary patterns and are increasingly used in the research setting. It is important to maintain consistency in data analysis and reporting, therefore, we: (1) systematically identified studies using accelerometry (ActiGraph, Pensacola, FL, USA) to measure moderate-to-vigorous physical activity (MVPA) and sedentary time in older adults, and (2) based on the review findings, we used different cut-points obtained to analyze accelerometry data from a sample of community-dwelling older women. We identified 59 articles with cut-points ranging between 574 and 3,250 counts/min for MVPA and 50 and 500 counts/min for sedentary time. Using these cut-points and data from women (mean age, 70 years), the median MVPA minutes per day ranged between 4 and 80 min while percentage of sedentary time per day ranged between 62 % and 86 %. These data highlight (1) the importance of reporting detailed information on the analysis assumptions and (2) that results can differ greatly depending on analysis parameters.     

A UNIVERSITY EXAMINATION-SCHEDULING MODEL TO MINIMIZE MULTIPLE-EXAMINATION DAYS FOR STUDENTS

Scheduling university examinations is often done with the objective of spreading a student's required examinations over an examination week. That is the equivalent of the problem of minimizing the number of examinations a student must take on any one day. An approach to scheduling exams which relates the problem to the classical assignment problem is discussed. The model developed is a symmetry-constrained assignment model, and the solution method requires use of a branch-and-bound algorithm. Results from application of the algorithm to six semesters of actual data are presented.     

A KNOWLEDGE-BASED DSS FOR MANAGERIAL PROBLEM DIAGNOSIS

A knowledge-based system supporting managerial problem diagnosis is described. The system provides the capability to monitor values of selected variables for problem situations. When problems are located, a list of problem symptoms is delivered to a problem processor for structuring and diagnosis. Problem structuring is based on a combination of concepts from expert systems and structural modeling. User assertions about cause-effect relationships between pairs of variables are maintained in a semantic network. Problem diagnosis uses the relationships in the semantic network to construct causation trees, the branches of which represent potential explanations of the problem symptoms. Mathematical models are constructed based on causation-tree branches, and values from the data base are used to test whether the model confirms the diagnosis. If so, the source of the problem has been located and it is then up to the user to resolve the problem. If the model fails to explain the problem, the model apparently is deficient and the user may perform “what if…” type scenarios in attempts to improve the model and search for problem causes. Realistic applications in the accounting and health care areas are discussed.     

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.     

Using complexity theory in kinship practice

This reflective discussion draws on data from a collaborative enquiry into kinship or family and friends practice. It introduces perspectives from complexity and chaos theory as a way of re‐examining the challenges of kinship practice. The discussion highlights the enduring challenges for practitioners, not least, managing anxiety and uncertainty, sustaining continuity and containment, becoming experienced and taking account of the complex developmental needs of the children and their families. The discussion particularly raises questions about appropriate settings for practitioners to undertake such a demanding area of child and family social work.     

The Dehumanization of Man: Dimensions and Processes

This paper is concerned with the dimensions and processes of dehumanization within the context of our contemporary social order. It considers briefly the nature of post-industrial society and its dehumanizing consequences, discussing the various dimensions of dehumanization articulated by various writers. The core argument is that dehumanization is created by external social structural conditions and only later becomes internally self-generating within the individual, which can lead to a self-perpetuating dehumanization syndrome.     

Children's Perceptions of Family Relationships as Assessed in a Doll Story Completion Task: Links to Parenting, Social Competence, and Externalizing Behavior

This study was designed to examine the links between parenting, children's perceptions of family relationships, and children's social behavior. Seventy‐four children (M age=6.01 years; 39 boys; 35 girls) and their parents took part in the study. Children completed relationship‐oriented doll stories that were coded for coherence, prosocial themes, and aggressive themes. Parents completed a report of their child's social behavior, a parenting scale, and a number of demographic items. Teachers also completed measures of children's social competence and externalizing behavior. Warm parenting predicted both a child's representation of prosocial themes in the doll stories and social competence, whereas harsh parenting predicted both a child's use of aggressive themes in the doll stories and a child's externalizing behavior. These findings support the idea that children are constructing models of relationships out of the early interactions with caregivers, and that they use these representations to guide their social behavior.