TASTE TEXTING: USING BEHAVIORAL ECONOMICS AND MOBILE HEALTH TO INCREASE HIGH SCHOOL LUNCH PARTICIPATION

In 2010, the federal Healthy Hunger Free Kids Act enacted strict new standards on school lunch. As a result, school lunch is healthier than ever. These new standards have already been associated with improved diet quality and weight status of school lunch participants. However, school lunch participation is declining nationally and is especially low among high school students. Research suggests that long lines during short lunch periods are a substantial barrier to school lunch participation. To improve high school lunch participation, we developed Taste Texting, a web-based, behavioral economics-informed program that allows students to pre-order school lunch from their computers or mobile phones and retrieve meals from kiosks, thereby bypassing lunch lines. This study combines mixed methods formative research and a multiple-baselines evaluation of the Taste Texting program in two high schools with identical menus in Chapel Hill and Carrboro, North Carolina (n = approx 2300 students). In AIM 1, we used a series of focus groups (n= 8 groups; 60 students) and surveys (n ~440) to identify the social norms surrounding school lunch and perceived barriers to school lunch participation. In AIM 2, we use longitudinal, student-ID linked transaction data and a multinomial logistic regression model to estimate associations between student-level sociodemographic characteristics and weekly school lunch participation at baseline (n ~ 2100 students, followed for 20 weeks). In AIM 3, we evaluated the impact of Taste Texting program participation on 4, 6, and 8-week changes in school lunch participation, finding that though program adoption was minimal, the heaviest program users in one school exhibited and maintained a 12% increase in weekly school lunch participation.Doctor of Philosoph

A Community-Driven Approach to Identifying “Winnableâ€? Policies Using the Centers for Disease Control and Prevention’s Common Community Measures for Obesity Prevention

Federally funded, community-based participatory research initiatives encourage the development and implementation of obesity prevention policies. In 2009, the Centers for Disease Control and Prevention (CDC) published the Common Community Measures for Obesity Prevention (COCOMO), which include recommended strategies and measures to guide communities in identifying and evaluating environmental and policy strategies to prevent obesity. Agreeing on "winnable" policy issues can be challenging for community members. We used CDC's COCOMO to structure in-depth interviews and group discussions with local stakeholders (ie, planners, town managers, and a local community advisory council) to stimulate interest in and identify health-promoting policies for local policy and planning agendas. We first asked stakeholders to rank the COCOMO recommendations according to feasibility and likelihood of success given community culture, infrastructure, extent of leadership support, and likely funding support. Rankings were used to identify the most and least "winnable" COCOMO policy strategies. We then used questions from the evidence-based Community Readiness Handbook to aid discussion with stakeholders on the facilitators and barriers to enacting the most and least winnable policy options identified. Finally, we discuss potential adaptations to COCOMO for rural jurisdictions

Design of MARQUIS2: study protocol for a mentored implementation study of an evidence-based toolkit to improve patient safety through medication reconciliation.

BackgroundThe first Multi-center Medication Reconciliation Quality Improvement Study (MARQUIS1) demonstrated that implementation of a medication reconciliation best practices toolkit decreased total unintentional medication discrepancies in five hospitals. We sought to implement the MARQUIS toolkit in more diverse hospitals, incorporating lessons learned from MARQUIS1.MethodsMARQUIS2 is a pragmatic, mentored implementation QI study which collected clinical and implementation outcomes. Sites implemented a revised toolkit, which included interventions from these domains: 1) best possible medication history (BPMH)-taking; 2) discharge medication reconciliation and patient/caregiver counseling; 3) identifying and defining clinician roles and responsibilities; 4) risk stratification; 5) health information technology improvements; 6) improved access to medication sources; 7) identification and correction of real-time discrepancies; and, 8) stakeholder engagement. Eight hospitalists mentored the sites via one site visit and monthly phone calls over the 18-month intervention period. Each site's local QI team assessed opportunities to improve, implemented at least one of the 17 toolkit components, and accessed a variety of resources (e.g. implementation manual, webinars, and workshops). Outcomes to be assessed will include unintentional medication discrepancies per patient.DiscussionA mentored multi-center medication reconciliation QI initiative using a best practices toolkit was successfully implemented across 18 medical centers. The 18 participating sites varied in size, teaching status, location, and electronic health record (EHR) platform. We introduce barriers to implementation and lessons learned from MARQUIS1, such as the importance of utilizing dedicated, trained medication history takers, simple EHR solutions, clarifying roles and responsibilities, and the input of patients and families when improving medication reconciliation

Addressing Rural Health Disparities Through Policy Change in the Stroke Belt

Obesity prevention policies are needed, particularly in low-income, rural areas of the Southern United States, where obesity and chronic disease prevalence are high. In 2009, the Centers for Disease Control and Prevention issued the “Common Community Measures for Obesity Prevention” (COCOMO), a set of 24 recommended community-level obesity prevention strategies

Associations Between Neighborhood-Level Factors Related to a Healthful Lifestyle and Dietary Intake, Physical Activity, and Support for Obesity Prevention Polices Among Rural Adults

To examine cross-sectional associations among neighborhood- and individual-level factors related to a healthful lifestyle and dietary intake, physical activity (PA), and support for obesity prevention polices in rural eastern North Carolina adults

Hospital Readmission in General Medicine Patients: A Prediction Model

Background: Previous studies of hospital readmission have focused on specific conditions or populations and generated complex prediction models. Objective: To identify predictors of early hospital readmission in a diverse patient population and derive and validate a simple model for identifying patients at high readmission risk. Design: Prospective observational cohort study. Patients: Participants encompassed 10,946 patients discharged home from general medicine services at six academic medical centers and were randomly divided into derivation (n = 7,287) and validation (n = 3,659) cohorts. Measurements: We identified readmissions from administrative data and 30-day post-discharge telephone follow-up. Patient-level factors were grouped into four categories: sociodemographic factors, social support, health condition, and healthcare utilization. We performed logistic regression analysis to identify significant predictors of unplanned readmission within 30 days of discharge and developed a scoring system for estimating readmission risk. Results: Approximately 17.5% of patients were readmitted in each cohort. Among patients in the derivation cohort, seven factors emerged as significant predictors of early readmission: insurance status, marital status, having a regular physician, Charlson comorbidity index, SF12 physical component score, ≥1 admission(s) within the last year, and current length of stay >2 days. A cumulative risk score of ≥25 points identified 5% of patients with a readmission risk of approximately 30% in each cohort. Model discrimination was fair with a c-statistic of 0.65 and 0.61 for the derivation and validation cohorts, respectively. Conclusions: Select patient characteristics easily available shortly after admission can be used to identify a subset of patients at elevated risk of early readmission. This information may guide the efficient use of interventions to prevent readmission

Associations Between Neighborhood-Level Factors Related to a Healthful Lifestyle and Dietary Intake, Physical Activity, and Support for Obesity Prevention Polices Among Rural Adults

PURPOSE: To examine cross-sectional associations among neighborhood- and individual-level factors related to a healthful lifestyle and dietary intake, physical activity (PA), and support for obesity prevention polices in rural eastern North Carolina adults. METHODS: We examined perceived neighborhood barriers to a healthful lifestyle, and associations between neighborhood barriers to healthy eating and PA, participants’ support for seven obesity prevention policies, and dependent variables of self-reported dietary and PA behaviors, and measured body mass index (BMI) (n = 366 study participants). We then used participants’ residential addresses and Geographic Information Systems (GIS) software to assess neighborhood-level factors related to access to healthy food and PA opportunities. Correlational analyses and adjusted linear regression models were used to examine associations between neighborhood-level factors related to a healthful lifestyle and dietary and PA behaviors, BMI, and obesity prevention policy support. RESULTS: The most commonly reported neighborhood barriers (from a list of 18 potential barriers) perceived by participants included: not enough bicycle lanes and sidewalks, not enough affordable exercise places, too much crime, and no place to buy a quick, healthy meal to go. Higher diet quality was inversely related to perceived and GIS-assessed neighborhood nutrition barriers. There were no significant associations between neighborhood barriers and PA. More perceived neighborhood barriers were positively associated with BMI. Support for obesity prevention policy change was positively associated with perceptions of more neighborhood barriers. CONCLUSIONS: Neighborhood factors that promote a healthful lifestyle were associated with higher diet quality and lower BMI. Individuals who perceived more neighborhood-level barriers to healthy eating and PA usually supported policies to address those barriers. Future studies should examine mechanisms to garner such support for health-promoting neighborhood changes

Associations between Attention-Deficit/Hyperactivity Disorder and various eating disorders: A Swedish nationwide population study using multiple genetically informative approaches

Background Although attention-deficit hyperactivity/impulsivity disorder (ADHD) and eating disorders (EDs) frequently co-occur, little is known about the shared etiology. In this study we comprehensively investigated the genetic association between ADHD and various EDs, including anorexia nervosa (AN) and other EDs (OED, including bulimia nervosa [BN]). Methods We applied different genetically informative designs to register-based information of a Swedish nationwide population (N=3,550,118). We first examined the familial co-aggregation of clinically diagnosed ADHD and EDs across multiple types of relatives. We then applied quantitative genetic modeling in full-sisters and maternal half-sisters to estimate the genetic correlations between ADHD and EDs. We further tested the associations between ADHD polygenic risk scores (PRS) and ED symptoms, and between AN PRS and ADHD symptoms, in a genotyped population-based sample (N=13,472). Results Increased risk of all types of EDs was found in individuals with ADHD (any ED: OR [95% CI]=3.97 [3.81-4.14], AN: 2.68 [2.15-2.86], OED: 4.66 [4.47-4.87], BN: 5.01 [4.63-5.41]) and their relatives compared to individuals without ADHD and their relatives. The magnitude of the associations reduced as the degree of relatedness decreased, suggesting shared familial liability between ADHD and EDs. Quantitative genetic models revealed stronger genetic correlation of ADHD with OED (0.37 [0.31-0.42]) than with AN (0.14 [0.05-0.22]). ADHD PRS correlated positively with ED symptom measures overall and sub-scales “drive for thinness” and “body dissatisfaction”, despite small effect sizes. Conclusions We observed stronger genetic association with ADHD for non-AN EDs than AN, highlighting specific genetic correlation beyond a general genetic factor across psychiatric disorders

Evidence-Based Practice: Promoting Nurse Retention

Nursing turnover is an increasing problem in the healthcare setting. According to Welding (2011), roughly three-fourths of new nurses cost the hospitals $22,000 by leaving their jobs in the first year. With this disconcerting statistic, one can only assume that something needs to be done to halt the persistent increase in turnover. These findings led to the following scholarly activity project question: What is the best evidence-based practice to promote nurse retention? The literature suggested several factors that could promote retention and improve the nurse turnover rate. Methods included conducting a literature review, a policy and procedure review, and observation of positive work environments related to nursing retention in the clinical setting. Although the literature review did not identify one specific, best practice, it suggested that the most influential factor used to promote nursing retention is a positive work environment including orientation programs, teamwork, communication, and adequate nurse to patient ratios. The policy & procedures and observations of nursing retention were consistent with findings in the literature. Implications for nursing practice, education, and research were provided.https://dc.swosu.edu/rf_2016/1099/thumbnail.jp