Educational mismatch and self-employment

Peer reviewedPreprin

Self-employment and the Paradox of the Contented Female Worker

Acknowledgements: Thanks to seminar participants at the University of Aberdeen and John Heywood for helpful comments.Publisher PD

Social Networking Sites and Our Lives

Examines the characteristics of social networking site users, their online activities, and their friendships, sense of trust, social support, perspectives, and civic engagement by site and compared with those of non-users and users of other technologies

Educational Mismatch and the Earnings Distribution : Where Does the Mismatch Bite?

Publisher PD

Educational mismatch and the earnings distribution

Thanks to the participants of the 2015 New Directions in Human Capital Theory Workshop at the University of Birmingham UK, the 2016 Midwestern Economic Society Annual Meetings, the 2017 Scottish Economic Society Annual Conference, seminar participants at the University of Aberdeen and to the editor and the two referees for helpful comments on the paper. The usual disclaimer applies.Peer reviewedPostprin

Higher Education and Shifting U.S. Demographics: Need for Visible Administrative Career Paths, Professional Development, Succession Planning & Commitment to Diversity

Higher education provides extensive opportunities for individuals seeking careers, career transition, and career advancement. The U.S. Bureau of Labor Statistics projects there are an estimated 6,000 jobs in higher education administration that will need to be filled annually through 2014 (Leubsdorf, 2006). Alice Miller, a consultant with the executive-search firm Witt/Kieffer, “predicts there will be at least a 50-percent turnover among senior administrators (higher education) in the next five to 10 years” (Leubsdorf, 2006, p. A51). Additionally, national research by the American Association of Community Colleges (AACE) (2001) and Fain (2008) reveals that 79% of current community college presidents will retire by 2012 and 84% will retire by 2016

Current trends in communication graduate degrees: Survey of communications, advertising, PR, and IMC graduate programs

© AEJMC 2015. A survey of 61 master’s degree advertising programs reveals significant trends in program titles, curriculum design, course delivery, and students served. The results provide insight for current and planned master’s degree programs as research predicts a continued increase in demand for master’s education over the next decade. Survey results are compared against overall education trends such as the growth of nontraditional students, increase in online education delivery, and the increase of for profit universities

Mental Health Prevalence in NCAA Division III Collegiate Athletes

Stressors related to academic requisites, sport participation and pressure to perform may increase college athlete risk for mental health symptoms (Cox, Ross-Stewart, & Foltz, 2017; Sudano & Miles, 2017; Yang et al., 2007). The purpose of this study was to identify the level of clinically relevant self-reported mental health symptoms in National Collegiate Athletic Association (NCAA) Division III athletes and variations based on sport participation (i.e., men’s or women’s athletics; team or individual sports) over a two-year period. A nonexperimental, trend study design was used. Data analysis included descriptive statistics, chi square test, and multivariate analysis of variance (MANOVA) which used one-way analysis of variance (ANOVA) for follow-up procedures. A MANOVA revealed a significant interaction of gender and sport type for general symptoms [F(1, 564) = 9.583, p = .002] and depression [F(1, 564) = 6.945, p = .009] but not anxiety [F(1, 564) = 3.332, p = .068, ƞ2 = .006]. The project was able to describe mental health symptoms in a population that is not often included in the literature. Knowledge of collegiate athlete mental health prevalence is important because prevention and early intervention is a key component of community-based health programming

Connectivity-enhanced diffusion analysis reveals white matter density disruptions in first episode and chronic schizophrenia.

Reduced fractional anisotropy (FA) is a well-established correlate of schizophrenia, but it remains unclear whether these tensor-based differences are the result of axon damage and/or organizational changes and whether the changes are progressive in the adult course of illness. Diffusion MRI data were collected in 81 schizophrenia patients (54 first episode and 27 chronic) and 64 controls. Analysis of FA was combined with "fixel-based" analysis, the latter of which leverages connectivity and crossing-fiber information to assess both fiber bundle density and organizational complexity (i.e., presence and magnitude of off-axis diffusion signal). Compared with controls, patients with schizophrenia displayed clusters of significantly lower FA in the bilateral frontal lobes, right dorsal centrum semiovale, and the left anterior limb of the internal capsule. All FA-based group differences overlapped substantially with regions containing complex fiber architecture. FA within these clusters was positively correlated with principal axis fiber density, but inversely correlated with both secondary/tertiary axis fiber density and voxel-wise fiber complexity. Crossing fiber complexity had the strongest (inverse) association with FA (r = -0.82). When crossing fiber structure was modeled in the MRtrix fixel-based analysis pipeline, patients exhibited significantly lower fiber density compared to controls in the dorsal and posterior corpus callosum (central, postcentral, and forceps major). Findings of lower FA in patients with schizophrenia likely reflect two inversely related signals: reduced density of principal axis fiber tracts and increased off-axis diffusion sources. Whereas the former confirms at least some regions where myelin and or/axon count are lower in schizophrenia, the latter indicates that the FA signal from principal axis fiber coherence is broadly contaminated by macrostructural complexity, and therefore does not necessarily reflect microstructural group differences. These results underline the need to move beyond tensor-based models in favor of acquisition and analysis techniques that can help disambiguate different sources of white matter disruptions associated with schizophrenia

The effect of adding comorbidities to current centers for disease control and prevention central-line–associated bloodstream infection risk-adjustment methodology

BACKGROUNDRisk adjustment is needed to fairly compare central-line–associated bloodstream infection (CLABSI) rates between hospitals. Until 2017, the Centers for Disease Control and Prevention (CDC) methodology adjusted CLABSI rates only by type of intensive care unit (ICU). The 2017 CDC models also adjust for hospital size and medical school affiliation. We hypothesized that risk adjustment would be improved by including patient demographics and comorbidities from electronically available hospital discharge codes.METHODSUsing a cohort design across 22 hospitals, we analyzed data from ICU patients admitted between January 2012 and December 2013. Demographics and International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) discharge codes were obtained for each patient, and CLABSIs were identified by trained infection preventionists. Models adjusting only for ICU type and for ICU type plus patient case mix were built and compared using discrimination and standardized infection ratio (SIR). Hospitals were ranked by SIR for each model to examine and compare the changes in rank.RESULTSOverall, 85,849 ICU patients were analyzed and 162 (0.2%) developed CLABSI. The significant variables added to the ICU model were coagulopathy, paralysis, renal failure, malnutrition, and age. The C statistics were 0.55 (95% CI, 0.51–0.59) for the ICU-type model and 0.64 (95% CI, 0.60–0.69) for the ICU-type plus patient case-mix model. When the hospitals were ranked by adjusted SIRs, 10 hospitals (45%) changed rank when comorbidity was added to the ICU-type model.CONCLUSIONSOur risk-adjustment model for CLABSI using electronically available comorbidities demonstrated better discrimination than did the CDC model. The CDC should strongly consider comorbidity-based risk adjustment to more accurately compare CLABSI rates across hospitals.Infect Control Hosp Epidemiol 2017;38:1019–1024</jats:sec