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Background Oncology patient navigators help individuals overcome barriers to increase access to cancer screening, diagnosis, and timely treatment. This study, part of a randomized intervention trial investigating the efficacy of patient navigation in increasing colonoscopy completion, examined navigators' activities to ameliorate barriers to colonoscopy screening in a medically disadvantaged population. Methods This study was conducted from 2012 through 2014 at Boston Medical Center. We analyzed navigator service delivery and survey data collected on 420 participants who were navigated for colonoscopy screening after randomization to this intervention. Key variables under investigation included barriers to colonoscopy, activities navigators undertook to reduce barriers, time navigators spent on each activity and per contact, and patient satisfaction with navigation services. Descriptive analysis assessed how navigators spent their time and examined what aspects of patient navigation were most valued by patients. Results Navigators spent the most time assessing patient barriers/needs; facilitating appointment scheduling; reminding patients of appointments; educating patients about colorectal cancer, the importance of screening, and the colonoscopy preparation and procedures; and arranging transportation. Navigators spent an average of 44 minutes per patient. Patients valued the navigators, especially for providing emotional/peer support and explaining screening procedures and bowel preparation clearly. Conclusions Our findings help clarify the role of the navigator in colonoscopy screening within a medically disadvantaged community. These findings may help further refine the navigator role in cancer screening and treatment programs as facilities strive to effectively and efficiently integrate navigation into their services.

Colorectal cancer is the second leading cause of cancer mortality among those cancers affecting both men and women. Screening is known to reduce mortality by detecting cancer early and through colonoscopy, removing precancerous polyps. Only 58.6% of adults are currently up-to-date with colorectal cancer screening by any method. Patient navigation shows promise in increasing adherence to colorectal cancer screening and reducing health disparities; however, it is a complex intervention that is operationalized differently across institutions. This article describes 10 key considerations in designing a patient navigation intervention for colorectal cancer screening based on a literature review and environmental scan. Factors include (1) identifying a theoretical framework and setting program goals, (2) specifying community characteristics, (3) establishing the point(s) of intervention within the cancer continuum, (4) determining the setting in which navigation services are provided, (5) identifying the range of services offered and patient navigator responsibilities, (6) determining the background and qualifications of navigators, (7) selecting the method of communications between patients and navigators, (8) designing the navigator training, (9) defining oversight and supervision for the navigators, and (10) evaluating patient navigation. Public health practitioners can benefit from the practical perspective offered here for designing patient navigation programs.

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Background Behavioral weight loss interventions can lead to an average weight loss of 5%–10% of initial body weight, however there is wide individual variability in treatment response. Although built, social, and community food environments can have potential direct and indirect influences on body weight (through their influence on physical activity and energy intake), these environmental factors are rarely considered as predictors of variation in weight loss. Objective Evaluate the association between built, social, and community food environments and changes in weight, moderate‐to‐vigorous physical activity (MVPA), and dietary intake among adults who completed an 18‐month behavioral weight loss intervention. Methods Participants included 93 adults (mean ± SD; 41.5 ± 8.3 years, 34.4 ± 4.2 kg/m2, 82% female, 75% white). Environmental variables included urbanicity, walkability, crime, Neighborhood Deprivation Index (includes 13 social economic status factors), and density of convenience stores, grocery stores, and limited‐service restaurants at the tract level. Linear regressions examined associations between environment and changes in body weight, waist circumference (WC), MVPA (SenseWear device), and dietary intake (3‐day diet records) from baseline to 18 months. Results Grocery store density was inversely associated with change in weight (β = −0.95; p = 0.02; R2 = 0.062) and WC (β = −1.23; p < 0.01; R2 = 0.109). Participants living in tracts with lower walkability demonstrated lower baseline MVPA and greater increases in MVPA versus participants with higher walkability (interaction p = 0.03). Participants living in tracts with the most deprivation demonstrated greater increases in average daily steps (β = 2048.27; p = 0.02; R2 = 0.039) versus participants with the least deprivation. Limited‐service restaurant density was associated with change in % protein intake (β = 0.39; p = 0.046; R2 = 0.051). Conclusion Environmental factors accounted for some of the variability (<11%) in response to a behavioral weight loss intervention. Grocery store density was positively associated with weight loss at 18 months. Additional studies and/or pooled analyses, encompassing greater environmental variation, are required to further evaluate whether environment contributes to weight loss variability.

This study examined variations in cigarette smoking status, home smoking and vaping rules, and attitudes toward smoking rules among U.S. adults. We analyzed data from the 2019 U.S. Census Bureau’s Current Population Survey Supplements (n = 40,296 adults) and calculated weighted prevalence estimates of adult cigarette smoking based on housing type. In 2019, multi-unit housing (MUH) residents who currently smoked were predominantly residents of privately rented housing (66.9%), followed by privately owned (17.6%) and public housing (15.5%). MUH residents who currently smoked had the highest proportions of allowing smoking (26.7%) or vaping (29.1%) anywhere inside their homes and were least likely to support rules allowing smoking inside all MUH apartments or living areas. In the adjusted models, MUH residents with a current smoking status were 92% less likely to have a complete smoking ban. More than one in four MUH residents with a current smoking status allowed all smoking inside the home and supported allowing smoking inside all MUH apartment or living areas, reinforcing how MUH residents may be at higher risk of experiencing secondhand smoke or aerosol exposure, or incursions within their places of residence. Our results can inform the development, implementation, and sustainment of strategies to reduce exposures from tobacco and nicotine products in all living environments.