Cheryl Kelly

Objective: The objective of this program evaluation was to measure the impact of a medically tailored meals (MTM) intervention on participants’ self‐reported recovery and satisfaction while recovering from a recent hospitalization.Design: A qualitative design was employed using a brief survey among all participants at the end of the intervention and phone interviews with a subset of participants.Sample: Participants in this study were recently discharged from the hospital and were members of (redacted for review) who had received 2–4 weeks of MTM.Measurements: The survey assessed overall satisfaction with the meals and perceived impact on their recovery after hospitalization (81% response rate). Interview questions asked how they felt the meals may have helped while recovering (e.g., helped them financially or with their ability to remain independent).Results: Among survey participants, 65% were extremely or very satisfied with their meals. Reasons that MTM were helpful while they were recovering included having sufficient food to eat, having healthy food to eat, the convenience of the meals, and ease of preparing the meals.Conclusions: Participants receiving MTM were generally very satisfied with the program. Including nutrition education and more flexibility in quantity and frequency of food may improve satisfaction and consumption of food.

Purpose The coronavirus disease (COVID-19) pandemic and its economic consequences may disproportionately impact cancer survivors and their overall health-related quality of life. The objective of this study was to examine whether cancer survivors experienced higher levels of financial strain or food insecurity compared to those without a history of cancer. Methods Kaiser Permanente Research Bank (KPRB) study participants were invited to complete a series of electronic surveys starting April 2020 to assess the impact of the COVID-19 pandemic. Participants who completed the initial survey and one follow-up survey were included. The odds of financial strain and food insecurity in those with and without a history of cancer were estimated using multinomial logistic regression. Results Cancer survivors (n = 16,231) had lower odds of reporting “somewhat hard” (AOR = 0.77) and “very hard” (AOR = 0.67) financial strain, and food insecurity “sometimes” (AOR = 0.70) and “often” (AOR = 0.55) compared to those with no history of cancer (n = 88,409). Non-Hispanic (NH) Black and Hispanic cancer survivors had higher odds compared to NH Whites of reporting financial strain and food insecurity. Smokers and those with multiple comorbidities had higher odds of reporting financial strain and food insecurity among cancer survivors. Conclusions While cancer survivors overall did not report greater financial strain or food insecurity than individuals without a history of cancer, subsets of cancer survivors are experiencing greater social risks during the pandemic and should be prioritized for screening for social risk factors. Implications for Cancer Survivors Incorporating screening for social risk factors into care coordination workflows for subsets of cancer survivors should be a priority.

The growing burden of chronic disease represents a complex challenge to public health. Innovative approaches, such as system dynamics simulation modeling, can aid public health professionals in understanding such complex issues and identifying effective solutions. This paper describes a system dynamics model and its application in projecting the impacts of evidence-based interventions on chronic disease for the state of Colorado. The development of the model was guided by data and input from subject matter expertise, peer-reviewed literature, and surveillance data. The model includes 28 intervention levers for chronic disease prevention, screening, and management. Interventions were simulated from 2020 to 2050 to project their impact on ten preventable causes of death. The simulations indicated the 6 most impactful interventions by 2050 to be adult smoking prevention, diabetes prevention, smoking cessation, blood pressure management, adult physical activity promotion, and colorectal cancer screening. Together, these 6 interventions could reduce preventable deaths by 7.1%, or 74% of the 9.6% reduction from all 28 interventions combined. This system dynamics model is a flexible tool that could be adapted or extended to include other populations or preventable chronic diseases. Prioritization and wide-scale implementation of the most impactful interventions could significantly reduce preventable deaths resulting from chronic disease.

The objective of this study was to assess if built environment changes to two suburban parks that involved extensive community engagement and physical activity programming increased park use and physical activity. This study employed a natural experiment evaluation design where community engagement informed the redesign of two neighborhood parks. Community engagement in the redesign of the parks was tracked as was the diversity of the partners on the steering committee and participation by community members in the process. Before and after park improvements, data were collected using the System for Observing Play and Recreation in Communities (SOPARC) instrument to measure change in use and activity level in each park. Park use increased at both parks, but physical activity levels did not significantly improve. The number of park visitors observed increased by 53% and 50%, respectively. Both parks had increased usage during evening hours when the family programming was the greatest. This study has several implications for policy and practice. First, this study suggests that community engagement can play a role in redesigning a park and likely leads to increased awareness and use of neighborhood parks. Second, while park use increased, simply adding new features to a park may not immediately increase physical activity. Additional efforts need to be made to activate the park and increase physical activity. Third, practitioners should not discount the value of building park awareness that increases park use as it may be a first step to increasing physical activity.

Context: Only 58% of eligible Coloradans are enrolled in the Supplemental Nutrition Assistance Program (SNAP). In recent years, more community-based organizations (CBOs) and health care clinics are incorporating screening for social needs into their workflows. Program: Seven Colorado-based CBOs and 3 clinics received funding (2016-2018) to screen for food insecurity (FI) and provide SNAP application assistance to their clients and patients. Implementation: Funded agencies were required to implement strategies focused on particular populations or settings based on Food Research and Action Center recommendations. Evaluation: A 5-part care cascade from screening to SNAP enrollment was conceptualized to guide the evaluation. Funded CBOs and clinics were asked to submit de-identified individual-level data to the evaluation team (number and characteristics of individuals screened, screening results, interest in receiving assistance, submitted application, enrolled in SNAP). The purpose of the evaluation was to assess the proportion of individuals CBOs and clinics screen for FI and assist with completing a SNAP application and describe the characteristics of individuals who are not interested in receiving assistance to complete a SNAP application and the characteristics of individuals who enroll in SNAP. Results: Thirty-five percent of individuals who reported FI participated in the care cascade and enrolled in SNAP. CBOs assisted a greater proportion of food-insecure individuals (55%) than clinics (22%) (P < .001). Males, adults 40 years or older, rural residents, and African Americans were more likely to be interested in receiving assistance, and adults 40 years or older, rural residents, and American Indians/Alaska Natives were more likely to enroll in SNAP. Discussion: CBOs were more successful in assisting individuals along the care cascade than clinics. Certain subpopulations are more likely to be interested in receiving assistance and enrolling in SNAP. These findings can be used by public health practitioners to plan interventions to increase enrollment in SNAP.

BACKGROUND: The purpose of this study was to evaluate an unstructured and a structured program designed to increase physical activity (PA). The unstructured program increased the amount of equipment during recess, whereas the structured program introduced activities to students.METHODS: PA was observed using the System for Observing Play and Leisure Activity in Youth (SOPLAY) in two school districts in Colorado. Researchers recorded baseline and follow‐up observations for sedentary activity, moderate PA, and vigorous PA, as well as for available equipment for the unstructured program. Observations from schools were aggregated for data analyses at the district level.RESULTS: For the program increasing equipment, moderate PA and vigorous PA increased, while sedentary behavior decreased. For the structured program, moderate PA and vigorous PA did not increase, whereas sedentary behaviors increased following the program.CONCLUSIONS: Other variables are likely influencing student PA during recess, such as teachers' interaction with students or the fidelity of the program. Results indicate that funding and implementing a program aimed at increasing PA will not necessarily accomplish that goal, and additional research should be performed to determine the best practice for increasing PA.

Providing opportunities for students to be physically active during the school day leads to increased academic performance, better focus, and fewer behavioral problems. As schools begin to incorporate more physical activity programming into the school day, evaluators need methods to measure how much physical activity students are being offered through this programming. Because classroom-based physical activity is often offered in 3-minute to 5-minute bouts at various times of the day, depending on the teachers’ time to incorporate it, it is a challenge to evaluate this activity. This article describes a method to estimate the number of physical activity minutes provided before, during, and after school. The web-based tool can be used to gather data cost-effectively from a large number of schools. Strategies to increase teacher response rates and assess intensity of activity should be explored.