Programs and Communities
The collection collates collections by schools, centers, programs, and research groups.
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Routine cervical cancer screening has significantly decreased the mortality rate of cervical cancer. Today, cervical cancer predominantly affects those who are rarely or never screened. Government programs are in place to provide cervical cancer screening at little to no cost, yet screening rates remain suboptimal.
This project evaluated an evidence-based intervention to increase cervical cancer screening among underserved women in a federally qualified health center (FQHC). Female patients ages 21 to 65 years without history of hysterectomy (n=1,710) were sent reminders to their phones through the electronic health record (EHR). The message included educational material about the screening process and an announcement regarding government aid for free or reduced cost screening.
The number of patients who made an appointment after receiving the message was assessed two months later. In total, 156 responses were collected, and 28 patients made an appointment for screening. The most frequently observed category of Ethnicity was Hispanic/Latina (n = 24, 86%). The most frequently observed category of Insurance was Title X (n = 13, 46%). The observations for Age had an average of 41.04 (SD = 9.93). Using an EHR communication function to send motivational reminders has shown some promise for increasing cervical cancer screening, thereby reducing cervical cancer mortality among the underserved.
The New Jersey Childhood Obesity Study, funded by the Robert Wood Johnson Foundation, aims to provide vital information for planning, implementing and evaluating interventions aimed at preventing childhood obesity in five ew Jersey municipalities: Camden, Newark, New Brunswick, Trenton, and Vineland. These five communities are being supported by RWJF's New Jersey Partnership for Healthy Kids program to plan and implement policy and environmental change strategies to prevent childhood obesity.
Effective interventions for addressing childhood obesity require community specific information on who is most at risk and on contributing factors that can be addressed through tailored interventions that meet the needs of the community.
Using a comprehensive research study, the Center for State Health Policy at Rutgers University is working collaboratively with the State Program Office for New Jersey Partnership for Healthy Kids and the five communities to address these information needs. The main components of the study include:
• A household survey of 1700 families with 3 -18 year old children
• De-identified heights and weights data from public school districts
• Assessment of the food and physical activity environments using objective data
Data books and maps based on the results of the study are being shared with the community coalitions in the five communities to help them plan their interventions.
The maps in this chartbook describe the food environment in Vineland in terms of access to supermarkets, smaller grocery stores, convenience stores, and limited service restaurants. Research shows that when residents have access to healthy food outlets, they tend to eat healthy.
• Food environment maps were created using geo-coded commercially available data of food outlets (Info USA, 2008 and Trade Dimensions, 2008) in Vineland and in a 1 mile buffer area around Vineland.
•Using the commercial data and additional investigation, food outlets were classified into different categories based on their likelihood of carrying healthy choices: supermarkets carry most healthy choices; smaller grocery stores carry fewer healthy choices; convenience stores and limited service restaurants are likely to carry mostly unhealthy choices.
• Access to different types of food outlets was computed at the census block group level based on concentration of stores / restaurants per unit area and is reported as food outlet densities.
• Food outlet density maps are compared with Census 2000 data to visualize accessibility of healthy foods in neighborhoods with different characteristics.
Data Sources: Info USA food outlet 2008 data
Trade Dimensions food outlet 2008 data
Census 2000 data
New Jersey Department of Education 2008-2009 data
The maps in this chartbook describe the food environment in ewark in terms of access to supermarkets, smaller grocery stores, convenience stores, and limited service restaurants. Research shows that when residents have access to healthy food outlets, they tend to eat healthy.
• Food environment maps were created using geo-coded commercially available data of food outlets (InfoUSA, 2008 and Trade Dimensions, 2008) in Newark and in a 1 mile buffer area around Newark.
•Using the commercial data and additional investigation, food outlets were classified into different categories based on their likelihood of carrying healthy choices: supermarkets carry most healthy choices; smaller grocery stores carry fewer healthy choices; convenience stores and limited service restaurants are likely to carry mostly unhealthy choices.
• Access to different types of food outlets was computed at the census block group level based on concentration of stores / restaurants per unit area and is reported as food outlet densities.
• Food outlet density maps are compared with Census 2000 data to visualize accessibility of healthy foods in neighborhoods with different characteristics.
Data Sources: Info USA food outlet 2008 data
Trade Dimensions food outlet 2008 data
Census 2000 data
New Jersey Department of Education 2008-2009 data
The maps in this chartbook describe the food environment in Trenton in terms of access to supermarkets, smaller grocery stores, convenience stores, and limited service restaurants. Research shows that when residents have access to healthy food outlets, they tend to eat healthy.
•Food environment maps were created using geo-coded commercially available data of food outlets (InfoUSA, 2008 and Trade Dimensions, 2008) in Trenton and in a 1 mile buffer area around Trenton.
•Using the commercial data and additional investigation, food outlets were classified into different categories based on their likelihood of carrying healthy choices: supermarkets carry most healthy choices; smaller grocery stores carry fewer healthy choices; convenience stores and limited service restaurants are likely to carry mostly unhealthy choices.
• Access to different types of food outlets was computed at the census block group level based on concentration of stores / restaurants per unit area and is reported as food outlet densities.
•Food outlet density maps are compared with Census 2000 data to visualize accessibility of healthy foods in neighborhoods with different characteristics.
Data Sources: Info USA food outlet 2008 data
Trade Dimensions food outlet 2008 data
Census 2000 data
New Jersey Department of Education 2008-2009 data
The maps in this chartbook describe the food environment in Camden in terms of access to supermarkets, smaller grocery stores, convenience stores, and limited service restaurants. Research shows that when residents have access to healthy food outlets, they tend to eat healthy.
• Food environment maps were created using geo-coded commercially available data of food outlets (InfoUSA, 2008 and Trade Dimensions, 2008) in Camden and in a 1 mile buffer area around Camden.
•Using the commercial data and additional investigation, food outlets were classified into different categories based on their likeliliood of carrying healthy choices: supermarkets carry most healthy choices; smaller grocery stores carry fewer healthy choices; convenience stores and limited service restaurants are likely to carry mostly unhealthy choices.
• Access to different types of food outlets was computed at the census block group level based on concentration of stores / restaurants per unit area and is reported as food outlet densities.
•Food outlet density maps are compared with Census 2000 data to visualize accessibility of healthy food s in neighborhoods with different characteristics.
Data Sources: Info USA food outlet 2008 data
Trade Dimensions food outlet 2008 data
Census 2000 data
New Jersey Department of Education 2008-2009 data
The maps in this chartbook describe the food environment in ew Brunswick in terms of access to supermarkets, smaller grocery stores, convenience stores, and limited service restaurants. Research shows that when residents have access to healthy food outlets, they tend to eat healthy.
• Food environment maps were created using geo-coded commercially available data of food outlets (Info USA, 2008 and Trade Dimensions, 2008) in New Brunswick and in a 1 mile buffer area around New Brunswick.
•Using the commercial data and additional investigation, food outlets were classified into different categories based on their likelihood of carrying healthy choices: supermarkets carry most healthy choices; smaller grocery stores carry fewer healthy choices; convenience stores and limited service restaurants are likely to carry mostly unhealthy choices.
• Access to different types of food outlets was computed at the census block group level based on concentration of stores / restaurants per unit area and is reported as food outlet densities.
•Food outlet density maps are compared with Census 2000 data to visualize accessibility of healthy foods in neighborhoods with different characteristics.
Data Sources: Info USA food outlet 2008 data
Trade Dimensions food outlet 2008 data
Census 2000 data
New Jersey Department of Education 2008-2009 data
Purpose: To collect and analyze participant demographic information and explore use of instruments to measure perceived social support and quality of life at a local cancer support program. Specific objectives included:
1. Gather and analyze participant demographic information and program utilization by participants for a non-profit cancer support agency.
2. Assess the extent to which those using the support programs experience perceived social support (PSS) and quality of life (QOL).
3. Assess the utility of the survey process and selected instruments to guide program planning.
Background: Obtaining the diagnosis of cancer is traumatic, but support groups assist in emotional healing among group members. There is strong evidence correlating support group participation with PSS and QOL. The Wilson and Cleary model of QOL clearly links social support and QOL and provided the conceptual framework for this project.
Methods: A survey for self-reported participant demographics, support activities, QOL scores, and PSS scores was implemented. Both online and pencil and paper surveys were available. Instruments included the Flanagan Quality of Life Scale (Cronbach’s α = .82 to .92) and the Multidimensional Scale of Perceived Social Support Scale (Cronbach’s α = 0.91) and a demographic survey created for this project.
Outcomes: All but one survey was completed online (n=48). Respondents were primarily white, female, cancer free at the time of the survey, and over the age of 55. QOL and PSS scores within this sample emulated previous research of correlations between instruments and people with chronic illnesses.
Conclusion: Correlations of sample demographics and instrument scores reflected current literature; this project validates an effective and affordable means to evaluate program effectiveness. Future use of the survey is to better tailor services to meet the objectives of the agency to improve QOL for all individuals affected by cancer.
Keywords: Cancer, support group, quality of life, perceived social support
Background and Significance: CRC is the second leading cause of cancer-related deaths in the United States among men and women. Current CRC screening rates remain low, even with advanced screening options available. Meaningful Use sets specific objectives for health care providers to achieve. Documenting CRC screening status and recommending CRC screenings to patients is one of the objectives of Meaningful Use and is considered a Clinical Quality Measure (HealthIT.gov). Factors that lead to CRC screening include primary care providers (PCPs) raising the topic, involving support staff, involving patients in the decision-making process, and setting alerts in electronic health records (EHRs).
Methods: The Health Belief Model and Ottawa Model of Research Use helped guide this project. The project took place at a private primary care practice. The focus was on patients between the ages of 50 and 75 years old meeting criteria for CRC. Five PCPS and five medical assistants (MAs) chose to participate in the study. Participants were given pre and post Practice Culture Assessment (PCA) surveys to measure perceptions of the practice culture. The project included a three-part practice change: PCP and MA education about CRC screening guidelines, EHR documentation and reminders, and a change of patient visit workflow which included having MAs review patient's CRC screening status before they were seen by the PCP and handing out CRC screening brochures when appropriate. PCPs then ordered the appropriate CRC screening, and the MA documented the screening in the EHR under a designated location. CRC Screening Project Evaluation Forms were completed by MAs after each patient visit.
Outcomes: No significant difference from pre to post survey satisfaction scores were found (t (8) = - 1.542, p= = .162). Means of quantitative data were reported from the CRC screening evaluation forms; N=91. The most common method of screening chosen was colonoscopy, 87%. A strong correlation was found (r (-.293) = .01, p<.05) between receiving a CRC brochure and choosing a form of screening. Meaningful Use scores pre and post project are pending.
Conclusion: Patients are more likely to choose a screening method when the topic is raised in a primary care setting. Continued staff education on workflow is important to sustain this change. Further research is needed to evaluate cost effectiveness and sustainability of this practice change.