The understudied half of undergraduates: Risky sexual behaviors among community college students

Abstract

Objective: This study examines the prevalence and risk factors associated with risky sexual behaviors in community college students. Participants: A diverse sample of 18–19-year-old community college students (N?=?264). Methods: Baseline data from an online prevention program administered in 2015. Results: Community college students in this sample disproportionately experienced sexual assault and were unlikely to test for STIs. Higher intentions to engage in risky sexual behaviors were associated with gender and sexual experience, but also with having lower intentions to communicate with a sexual partner about pregnancy and STIs, and having higher gender norm endorsement. Conclusions: Older adolescents attending community colleges may be at high risk for poor sexual health outcomes, and appropriate theory-based education should be tailored to meet the needs of these underserved students.     

Rural-urban differences in college students’ cardiovascular risk perceptions

Abstract

Objective: To examine rural-urban differences in college students’ cardiovascular risk perceptions. Participants: College students in rural (n?=?61) and urban (n?=?57) Kentucky counties were recruited from November 2012 to May 2014. Methods: This was a secondary data analysis of a cross-sectional study examining rural-urban differences in cardiovascular risk factors. Students rated their risk for developing high blood pressure, diabetes, high cholesterol, heart disease, having a stroke, and gaining excess weight. Chi-square and logistic regression were used for data analysis. Results: Rural students had lower odds of perceived high risk for developing high blood pressure compared to urban students (odds ratio (OR): 0.32, 95% CI: 0.11–0.96) after adjusting for race, sex, and body mass index. This association was not observed after adjusting for healthcare access variables. No other significant differences were observed. Conclusions: Efforts to raise perceived risk for developing hypertension among rural college students may be warranted.     

Coworker support as a moderator in the relationship between daily experience of workload and an individual’s experience of same-day WFC: a buffer or an intensifier?

ABSTRACT

The present study looks at the interaction between daily experiences in the workplace – daily workload and daily coworker support – and examines its influence on negative affect and its subsequent impact on same-day work–family conflict (WFC). It proposes two competing moderation hypotheses (buffering vs. intensifying). According to the COR theory, support received from coworkers represents a resource that should buffer the relationship between daily workload and same-day WFC, because it should prevent individuals from experiencing negative affect triggered by high workload episodes which represents a threatening or stressful situation. In contrast, the threat to self-esteem model posits that receiving social support may engender feelings of indebtedness or helplessness at the time such support is provided, thereby amplifying the impact of workload experience on same-day WFC via an increased negative affect. Data collected from 130 pharmacists over 5 consecutive days were analyzed through multilevel structural equation modeling. The results support the hypothesis of the intensifying conditional indirect effect, and show that when individuals are provided with coworker support while experiencing high workload, negative affect is aggravated and hence, in turn, same-day WFC increases. This challenges the mainstream hypothesis that views social support as an important resource in protecting people from stressful events.     

Detecting Directionality in Time Series

Abstract

Directionality can be seen in many stationary time series from various disciplines, but it is overlooked when fitting linear models with Gaussian errors. Moreover, we cannot rely on distinguishing directionality by comparing a plot of a time series in time order with a plot in reverse time order. In general, a statistical measure is required to detect and quantify directionality. There are several quite different qualitative forms of directionality, and we distinguish: rapid rises followed by slow recessions; rapid increases and rapid decreases from the mean followed by slow recovery toward the mean; directionality above or below some threshold; and intermittent directionality. The first objective is to develop a suite of statistical measures that will detect directionality and help classify its nature. The second objective is to demonstrate the potential benefits of detecting directionality. We consider applications from business, environmental science, finance, and medicine. Time series data are collected from many processes, both natural and anthropogenic, by a wide range of organizations, and directionality can easily be monitored as part of routine analysis. We suggest that doing so may provide new insights to the processes.     

Two-stage approaches to the analysis of occupancy data I: the homogeneous case (analysis of occupancy data)

Abstract

Occupancy models are used in statistical ecology to estimate species dispersion. The two components of an occupancy model are the detection and occupancy probabilities, with the main interest being in the occupancy probabilities. We show that for the homogeneous occupancy model there is an orthogonal transformation of the parameters that gives a natural two-stage inference procedure based on a conditional likelihood. We then extend this to a partial likelihood that gives explicit estimators of the model parameters. By allowing the separate modeling of the detection and occupancy probabilities, the extension of the two-stage approach to more general models has the potential to simplify the computational routines used there.     

Improving patients’ satisfaction in a mobile hospital using Lean Six Sigma – a design-thinking intervention

Abstract

Lean Six Sigma (LSS) that offers a unique integration of Lean and Six Sigma has been accepted globally across services sectors. Previous studies that examined the application of LSS in healthcare were steered in traditional hospital settings. Apparently, there are no studies that highlight the application of LSS in mobile hospitals, an emerging trend in the healthcare sector. The aim of this article is to explore the applicability of LSS in a mobile hospital. The authors present a case study of improving patients’ satisfaction in a mobile hospital, through reducing turnaround time. Design-thinking intervention to LSS helped resolve a real-time problem using Define-Measure-Analyze-Design-Verify roadmap. This article contributes to the ‘healthcare quality” body of knowledge and is novel as it is the first of its kind of LSS application in a mobile hospital underpinning Design thinking. This study is unique as it demonstrates academia–industry collaboration in solving an organizational problem.     

PCA likelihood ratio test approach for attributed social networks monitoring

Abstract

One of the most important factors in building and changing communication mechanisms in social networks is considering features of the members of social networks. Most of the existing methods in network monitoring don’t consider effects of features in network formation mechanisms and others don’t lead to reliable results when the features abound or when there are correlations among them. In this article, we combined two methods principal component analysis (PCA) and likelihood method to monitor the underlying network model when the features of individuals abound and when some of them have high correlations with each other.     

How discrimination in adoptive,foster, and medical systems harms LGBTQ+ families: Research on the experiences of prospective parents

Abstract

LGBTQ+?people face multiple challenges to parenthood because of barriers such as discriminatory legislation and policies influencing foster parenting, adoption, and reproductive health services. This study documents these obstacles and examines their impact through a grounded theory analysis of interviews of LGBTQ+?prospective parents. Stressors included social isolation, unnecessary medicalization, prohibitive financial costs related to accessing social and medical services (sometimes across state lines), and being denied services, parental leave, and insurance coverage. Findings indicate that heteronormative attitudes and discrimination can lead to debilitating and enduring harm upon the economic, emotional, and relational well-being of growing LGBTQ+?families.     

An exploration of social & emotional factors impacting well-being in women who have sex with women (WSW)

Abstract

“Women who have sex with women” or WSW have unique perspectives within the LBGTQ spectrum. The purpose of this study included documenting perceptions, feelings, and experiences among WSW. Thirty-seven women participated in six focus groups, ages ranged from 20–64 years. Responses were transcribed and thematically coded. Four themes emerged as influencing factors: shame and fear, community, gender roles, and normalcy. Each major theme produced minor themes providing a context within major themes. Results offer valuable insights that can assist community members, health professionals, and scientists to better appraise the disparities and stigma impacting social and emotional well-being among WSW.