San Diego State University

About: San Diego State University is a education organization based out in San Diego, California, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 12418 authors who have published 27950 publications receiving 1192375 citations. The organization is also known as: SDSU & San Diego State College.

Prevention of Eating Disorders in At-Risk College-Age Women

Abstract: Context Eating disorders, an important health problem among college-age women, may be preventable, given that modifiable risk factors for eating disorders have been identified and interventions have been evaluated to reduce these risk factors. Objective To determine if an Internet-based psychosocial intervention can prevent the onset of eating disorders (EDs) in young women at risk for developing EDs. Setting San Diego and the San Francisco Bay Area in California. Participants College-age women with high weight and shape concerns were recruited via campus e-mails, posters, and mass media. Six hundred thirty-seven eligible participants were identified, of whom 157 were excluded, for a total sample of 480. Recruitment occurred between November 13, 2000, and October 10, 2003. Intervention A randomized controlled trial of an 8-week, Internet-based cognitive-behavioral intervention (Student Bodies) that included a moderated online discussion group. Participants were studied for up to 3 years. Main Outcome Measures The main outcome measure was time to onset of a subclinical or clinical ED. Secondary measures included change in scores on the Weight Concerns Scale, Global Eating Disorder Examination Questionnaire, and Eating Disorder Inventory drive for thinness and bulimia subscales and depressed mood. Moderators of outcome were examined. Results There was a significant reduction in Weight Concerns Scale scores in the Student Bodies intervention group compared with the control group at postintervention ( P P P P = .02). Over the course of follow-up, 43 participants developed subclinical or clinical EDs. While there was no overall significant difference in onset of EDs between the intervention and control groups, the intervention significantly reduced the onset of EDs in 2 subgroups identified through moderator analyses: (1) participants with an elevated body mass index (BMI) (≥25, calculated as weight in kilograms divided by height in meters squared) at baseline and (2) at 1 site, participants with baseline compensatory behaviors (eg, self-induced vomiting, laxative use, diuretic use, diet pill use, driven exercise). No intervention participant with an elevated baseline BMI developed an ED, while the rates of onset of ED in the comparable BMI control group (based on survival analysis) were 4.7% at 1 year and 11.9% at 2 years. In the subgroup with a BMI of 25 or higher, the cumulative survival incidence was significantly lower at 2 years for the intervention compared with the control group (95% confidence interval, 0% for intervention group; 2.7% to 21.1% for control group). For the San Francisco Bay Area site sample with baseline compensatory behaviors, 4% of participants in the intervention group developed EDs at 1 year and 14.4%, by 2 years. Rates for the comparable control group were 16% and 30.4%, respectively. Conclusions Among college-age women with high weight and shape concerns, an 8-week, Internet-based cognitive-behavioral intervention can significantly reduce weight and shape concerns for up to 2 years and decrease risk for the onset of EDs, at least in some high-risk groups. To our knowledge, this is the first study to show that EDs can be prevented in high-risk groups.

Learning Pose Grammar to Encode Human Body Configuration for 3D Pose Estimation

Abstract: In this paper, we propose a pose grammar to tackle the problem of 3D human pose estimation. Our model directly takes 2D pose as input and learns a generalized 2D-3D mapping function. The proposed model consists of a base network which efficiently captures pose-aligned features and a hierarchy of Bi-directional RNNs (BRNN) on the top to explicitly incorporate a set of knowledge regarding human body configuration (i.e., kinematics, symmetry, motor coordination). The proposed model thus enforces high-level constraints over human poses. In learning, we develop a pose sample simulator to augment training samples in virtual camera views, which further improves our model generalizability. We validate our method on public 3D human pose benchmarks and propose a new evaluation protocol working on cross-view setting to verify the generalization capability of different methods. We empirically observe that most state-of-the-art methods encounter difficulty under such setting while our method can well handle such challenges.

Regional convergence, inequality, and space

Abstract: The study of regional income convergence continues to attract enormous attention. Recent emphasis has been placed on the underlying spatial dimensions of regional growth processes both from theoretical and empirical perspectives, as well as from exploratory and confirmatory methodological stances. This paper provides a critical review of empirical approaches and methodological advances with an emphasis on the treatment of spatial effects, namely spatial dependence, spatial heterogeneity, and spatial scale. A number of areas that have been overlooked are highlighted, and the paper suggests a research agenda on regional growth empirics. Copyright 2005, Oxford University Press.