Subjecteducation of healthcare executives
health management education
health administration education
health management & policy
global health systems
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Characteristics and Predictors of Ecstasy (MDMA) Use During CollegeBrown, Ronald T.; Hanlon, Alexandra L.; Hiller, Matthew L.; Kendrick, Zebulon V.; Segal, Jay (Temple University. Libraries, 2008)This cross-sectional investigation examined characteristics of ecstasy use during college and associations between ecstasy use during college and demographic factors, family functioning, mental health, and stage of change for ecstasy use. In addition a multivariate model was developed to predict characteristics of ecstasy use during college. An electronic survey was sent to all undergraduate students enrolled at a large urban university in the mid-Atlantic region of the United States during the spring of 2007. Demographic factors and characteristics of ecstasy use were examined using standardized measures employed in national drug use surveys and by the World Health Organization. Measures associated specifically with ecstasy use during college were developed for this investigation. Family functioning was measured with the Parent Adolescent Communication Scale. Mental health was measured with the K6 screening instrument for nonspecific psychological distress. Stage of change was measured with a five-stage algorithm. The final sample for analysis consisted of 194 participants who reported ecstasy use during college and 2849 participants who reported no ecstasy use during college. Data were described using conventional descriptive statistics, chi-square statistics and non-parametric statistics. A logistic regression model was used to identify variables associated with ecstasy use during college. Based on the results, the following generalized conclusions were drawn: ecstasy continues to be used by college students at large urban universities in the mid-Atlantic region of the United States; because the majority of college students reported using ecstasy for the first time during college and also reported using ecstasy for up to two years, it appears that the college environment is a contextual factor for ecstasy use; lower family communication is associated with ecstasy use during college; psychological distress is associated with ecstasy use during college; being white (versus non-white), male (versus female) and having low or moderate (versus high) family communication each is independently associated with ecstasy use during college; differences in stage of change for ecstasy use among ecstasy users and the demographic profile of ecstasy users compared to non-ecstasy users suggest that prevention, education and intervention efforts should be designed to match the unique factors associated with ecstasy use during college.
Data Analytics and Modeling for Appointment No-show in Community Health CentersMohammadi, I; Wu, H; Turkcan, A; Toscos, T; Doebbeling, BN; Wu, Huanmei|0000-0003-0346-6044 (2018-11-01)© The Author(s) 2018. Objectives: Using predictive modeling techniques, we developed and compared appointment no-show prediction models to better understand appointment adherence in underserved populations. Methods and Materials: We collected electronic health record (EHR) data and appointment data including patient, provider and clinical visit characteristics over a 3-year period. All patient data came from an urban system of community health centers (CHCs) with 10 facilities. We sought to identify critical variables through logistic regression, artificial neural network, and naïve Bayes classifier models to predict missed appointments. We used 10-fold cross-validation to assess the models’ ability to identify patients missing their appointments. Results: Following data preprocessing and cleaning, the final dataset included 73811 unique appointments with 12,392 missed appointments. Predictors of missed appointments versus attended appointments included lead time (time between scheduling and the appointment), patient prior missed appointments, cell phone ownership, tobacco use and the number of days since last appointment. Models had a relatively high area under the curve for all 3 models (e.g., 0.86 for naïve Bayes classifier). Discussion: Patient appointment adherence varies across clinics within a healthcare system. Data analytics results demonstrate the value of existing clinical and operational data to address important operational and management issues. Conclusion: EHR data including patient and scheduling information predicted the missed appointments of underserved populations in urban CHCs. Our application of predictive modeling techniques helped prioritize the design and implementation of interventions that may improve efficiency in community health centers for more timely access to care. CHCs would benefit from investing in the technical resources needed to make these data readily available as a means to inform important operational and policy questions.
Developing a Leisure Meanings Gained & Outcomes Scale (LMGOS) and Exploring Associations of Leisure Meanings to Leisure Time Physical Activity (LTPA) Adherence among Adults with Type 2 Diabetes (T2D)Iwasaki, Yoshitaka; Shank, John (John W.); Gordon, Thomas F.; DuCette, Joseph P. (Temple University. Libraries, 2009)It is estimated that 61% of people with Type 2 Diabetes (T2D) don't engage in any form of leisure time physical activity (LTPA) (Morrato, Hill, Wyatt, Ghushchyan, & Sullivan, 2007). One of the primary interventions to manage T2D is regular engagement in Leisure Time Physical Activity (LTPA) (Sigal, Kenny, Wasserman, Castaneda-Sceppa, & White, 2006). Many studies have tried to increase the frequency of LTPA in this population with little success (e.g., Williams, Bezner, Chesbro, & Leavitt, 2005). A new innovative approach to increasing engagement in LTPA is needed. Feelings of enjoyment have been found to correlate with adherence to LTPA (e.g., Williams, Papandonatos, Napolitano, Lewis, Whiteley, & Marcus, 2006) and theorized to be an outcome of experiencing something that is personally meaningful (Snyder & Lopez, 2002). It has also been found that "participation in leisure...continues when the experiences and/or the activity are meaningful to the individual" (Ragheb, 1996, p. 247). Thus, exploration of personal meanings that are valued and experienced within LTPA may be a key approach to effectively increasing LTPA. A content-analysis of the literature yielded the identification of five leisure meanings and three outcomes that are derived within and/or from leisure activity engagement. A new scale, the Leisure Meanings Gained and Outcomes Scale (LMGOS), was developed to reflect the findings. It was confirmed by an expert panel for face and content validity and then administered to Temple University students (n = 163). Exploratory factor analyses provided evidence for construct validity and reliability and led to further refinement. The refined LMGOS was given to adults with T2D (n = 26). The results showed significant correlations between specific leisure meanings gained and LTPA engagement, as well as between outcomes of meanings gained and LTPA engagement. The implications of the study include demonstrating: (a) the utility of a theoretically and psychometrically sound measure of the meanings gained and its outcomes via leisure (i.e., LMGOS), (b) the need for acknowledging meaning-oriented experiential and emotional properties of LTPA from a more holistic and humanistic perspective, and (c) the importance of meaning-seeking or meaning-making through leisure as a key facilitator to active living and health promotion for people including individuals with T2D.