I test this prediction by carrying out a factor analysis of individual difference measures drawn from the domains listed above. The theory predicts that the inclusion of a wider variety of individual difference measures, e.g., psychological interests, values, social attitudes and work motivation, will reveal a more meaningful and larger set of basic traits than ordinary personality scales alone. EPD-R theory implies that current personality theories lack the necessary perspective to capture this dynamic structure due to a very narrow focus on affective-processing and psychopathology. These traits lead individuals to create physical and psychological environments compatible with their genotypes. Simply put EPD-R theory asserts that human beings are active agents designed to survive in their average expected environment and have evolved numerous traits that facilitate that survival. The theory, initially proposed to explain the evolution of intelligence, is generalized to all human psychological individual differences (EPD-Revised). The tool bridges a translational gap between research and environmental design practice, and may contribute to setting new industry and education standards.Įxperience Producing Drive (EPD) theory is sketched out. Implementation of the guidelines is expected to enable students to adopt healthier physical activity behaviors. The design guidelines include specific strategies in 10 school design domains. We used a qualitative review process to develop evidence-based and theory-driven school design guidelines that promote increased physical activity among students. Its aims are to provide architects and designers, as well as school planners, educators, and public health professionals, with strategies for making K-12 school environments conducive to healthy physical activity, and to engage scientists in transdisciplinary perspectives toward improved knowledge of the school environment's impact. This paper describes the development of a new practical tool: Physical Activity Design Guidelines for School Architecture.
While research has demonstrated associations between aspects of school environments and students' physical activity, the literature currently lacks a synthesis of evidence to serve as a practical, spatially-organized resource for school designers and decision-makers, as well as to point to pertinent research opportunities. Increasing children's physical activity at school is a national focus in the U.S. The results enable researchers to make a more educated choice of an appropriate sampling strategy. When proxy data are available, it is possible to evaluate random and purposive sampling strategies using simulations before the start of the study. The optimal strategy for estimating blood use was maximum variation sampling. While lowering the sample size reduced the differences between maximum variation and the random strategies, increasing sample size to n = 18 did not change the ranking of the strategies and led to only slightly better predictions. Maximum variation sampling led to a hospital level prediction error of 15 %, whereas random sampling led to a prediction error of 19 % (95 % CI 17 %-26 %). The strategy leading to the lowest prediction error in the case study was maximum variation sampling, followed by random, regional variation and two-region sampling, with sampling the largest hospitals resulting in the worst performance. The estimates are compared to the actual population values the subsequent prediction errors are used to indicate the quality of the sampling strategy. Simulations of each strategy result in different selections of hospitals, that are each used to estimate blood use in the remaining hospitals. In this paper, we evaluate both random and purposive strategies for the case of estimating blood use in Dutch hospitals.Īvailable population-wide data on hospital blood use and number of hospital beds are used to simulate five sampling strategies: (1) select only the largest hospitals, (2) select the largest and the smallest hospitals ('maximum variation'), (3) select hospitals randomly, (4) select hospitals from as many different geographic regions as possible, (5) select hospitals from only two regions. With this selection of 12 hospitals, it should be possible to estimate blood use in the remaining hospitals as well. In our case, a selection must be made of 12 hospitals (out of 89 Dutch hospitals in total). While random sampling strategies are the gold standard, in practice, random sampling of participants is not always feasible nor necessarily the optimal choice. A ubiquitous issue in research is that of selecting a representative sample from the study population.
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