Modeling multiple health behaviors and general health

Multiple Health Behavior Change assumes health behaviors are related to one another, although research evidence is mixed. More research is needed to understand which behaviors are most closely related and how they collectively predict health. Principle component analysis and structural equation modeling were used to establish a model showing relations between health behaviors, including fruit/vegetable consumption, aerobic and strength exercise, alcohol intake, and smoking, and how these behaviors relate to general physical and mental health functioning in a large, national sample. Although health behaviors were found to coalesce into a health-promoting factor of diet, and exercise, a better overall model fit was found when all behaviors were modeled as separate independent variables. Results suggest that health behaviors relate to one another in complex ways, with perceived health status serving as a mediating variable between specific health behaviors and a factor of physical and mental health. Future research should further investigate how other health behaviors relate to perceptions and overall health, especially among subpopulations

Ranch Management Practices of Beef Quality Assurance (BQA) and Non-BQA Certified Producers in Montana

The beef cattle industry continues to provide a safe, quality, and consistent product to consumers while addressing animal health and food safety issues. The study reported here sought to determine Beef Quality Assurance educational needs for record keeping, health management, marketing strategies, and perceptions of industry issues to inform and prepare Montana beef producers for changes. BQA and non-BQA certified producers had varying management strategies for animal identification, record keeping, and vaccination programs, while implant programs and marketing strategies were similar. The results of the survey will be used to determine the BQA educational needs of Montana cattle producers

ADHD Symptomology and Prescription Stimulant Misuse in College Students

Attention-Deficit Hyperactivity Disorder (ADHD) is a neurological disorder characterized by developmentally inappropriate levels of hyperactivity/impulsivity and inattention. These symptoms result in impairments for individuals across multiple settings and are developmentally inappropriate. While common during childhood, symptoms have been shown to persist into adulthood for 50% or more of those diagnosed before reaching age 18. Although prescription stimulants have been shown to benefit those with ADHD, increased popularity of prescription stimulant misuse among those without ADHD has been reported, despite the potentially harmful side effects that may accompany this use. Specifically, nonmedical use of prescription stimulants during adolescence led to increased risk of crime commitment and increased risk for subsequent addictions to other substances. Despite the negative effects of prescription stimulants on those misusing them, as many as 7% of undergraduate college students reported prescription stimulant medication misuse. The present NIH R01 funded study, Trajectories Related to ADHD in College (TRAC) is a 5-year longitudinal study conducted by Dr. Arthur Anastopoulos at the University of North Carolina at Greensboro (Lead Principal Investigator), Dr. George DuPaul at Lehigh University (Co-Principal Investigator), and Dr. Lisa Weyandt at the University of Rhode Island (Co-Principal Investigator). Through my work on this study, it became clear that although research concerning the patterns of misuse among college students has been performed and documented, the association between those with ADHD and nonmedical use of prescription stimulants has not been well studied. More specifically, research exploring the relationship between the severity of ADHD symptoms and prescription stimulant misuse is sparse. Therefore, the aim of this honors thesis is to assess the misuse among students both with, and without, ADHD, and to explore whether males and females differ in reported rates of prescription stimulant misuse

Rodeo athlete: overview

This issue of eMedRef provides information to clinicians on injuries that may occur to rodeo athletes

Staying Safe in a Tornado: A Qualitative Inquiry into Public Knowledge, Access, and Response to Tornado Warnings

Tornadoes in the southeastern United States continue to cause substantial injury, death, and destruction. The present study seeks to 1) understand inadequate warning access, less understanding, and/or less likelihood of responding to tornado warnings; 2) examine public attitudes about NWS communications; and 3) explore the perceptions of NWS personnel regarding public response to tornado warnings, factors that might influence response, and how their perceptions impact their communication. Participants include a purposive sample of NWS forecasters in Tennessee (n = 11) and residents (n = 45) who were identified as having low access to, low knowledge of, or an unsafe response to tornado warnings in a previous study. A qualitative approach with semistructured interviews was used. Findings indicated that most participants had at least one warning source. Barriers to warning access included electricity outages, rurality, lack of storm radio, heavy sleeping, and hearing impairments. Most participants had knowledge of NWS guidelines for safe shelter seeking but still engaged in behaviors considered unsafe. Proximity, personal experience, and influence of family and friends emerged as influencers of response to warnings. NWS personnel perceived that proximity played a significant role in shelter-seeking behavior as well as the need for confirmation. Poor access to safe shelter arose as a major concern for NWS personnel, specifically mobile home residents. Messaging and specificity in warnings to evoke safe shelter-seeking behavior surfaced as critical issues for NWS personnel. Implications for education and policy changes to enhance public safety and improve public health are noted

Examing Patterns of Intended Response to Tornado Warnings Among Residents of Tennessee, United States, Through a Latent Class Analysis Approach

In the past five years, the southern region of the United States has had a large number of fatal tornadoes. Previous research indicates that residents of this area may not be taking appropriate shelter. The present study uses a random sample of Tennessee residents (N = 1126) and the latent class analysis (LCA) technique to explore discrete types of responders according to their pattern of intended behaviors when presented with a tornado warning scenario in the daytime or nighttime. LCA revealed three distinct groups in the day subsample – Tech Users, Typical Actors, and Passive Reactors – and three in the night subsample – Tech Users, Typical Actors, and Non-Reactors. Being a Tech User or Typical Actor was positively associated with intending to seek safe shelter, although being a Passive Reactor or Non-Reactor was not. Further, Tech Users/Typical Actors were seeking and obtaining more warning information from other sources compared to Passive Reactors/Non-Reactors. While few demographic variables were associated with class assignment, bivariate and multivariate analyses illustrated that cognitive factors, such as previous experience with tornadoes and perceived accuracy of warnings, are significantly associated with class membership when controlling for non-cognitive factors. The distinctions made within and between the subsamples can support the National Weather Service\u27s efforts to better target the public with future messages about tornado safety as well as guide researchers on future studies

Collecting Multiple Data Linkage Consents in a Mixed-mode Survey: Evidence from a large-scale longitudinal study in the UK

Linking survey responses with administrative data is a promising practice to increase the range of research questions to be explored, at a limited interview burden, both for respondents and interviewers. We describe the protocol for asking consent to data linkage on nine different sources in a large-scale nationally representative longitudinal survey of young adults in England: the Next Steps Age 25 Survey. We present empirical evidence on consent to data linkage from qualitative interviews, a pilot study, and the mainstage survey. To the best of our knowledge, this is the first study that discusses the practicalities of implementing a data linkage protocol asking consent both retrospectively and prospectively, on multiple domains, and in the context of a mixed-mode survey

The Ultraviolet and Infrared Star Formation Rates of Compact Group Galaxies: An Expanded Sample

Compact groups of galaxies provide insight into the role of low-mass, dense environments in galaxy evolution because the low velocity dispersions and close proximity of galaxy members result in frequent interactions that take place over extended timescales. We expand the census of star formation in compact group galaxies by \citet{tzanavaris10} and collaborators with Swift UVOT, Spitzer IRAC and MIPS 24 \micron\ photometry of a sample of 183 galaxies in 46 compact groups. After correcting luminosities for the contribution from old stellar populations, we estimate the dust-unobscured star formation rate (SFR$_{\mathrm{UV}}$) using the UVOT uvw2photometry. Similarly, we use the MIPS 24 \micron\ photometry to estimate the component of the SFR that is obscured by dust (SFR$_{\mathrm{IR}}$). We find that galaxies which are MIR-active (MIR-"red"), also have bluer UV colours, higher specific star formation rates, and tend to lie in H~{\sc i}-rich groups, while galaxies that are MIR-inactive (MIR-"blue") have redder UV colours, lower specific star formation rates, and tend to lie in H~{\sc i}-poor groups. We find the SFRs to be continuously distributed with a peak at about 1 M$_{\odot}$ yr$^{-1}$, indicating this might be the most common value in compact groups. In contrast, the specific star formation rate distribution is bimodal, and there is a clear distinction between star-forming and quiescent galaxies. Overall, our results suggest that the specific star formation rate is the best tracer of gas depletion and galaxy evolution in compact groups.Comment: 19 pages, 17 figure