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•We conducted a national survey of 1495 U.S. parents of adolescents, ages 11–17.•Parents reported on healthcare provider recommendations for HPV vaccination.•High-quality recommendations were positively associated with HPV vaccine uptake.•High-quality recommendations were negatively associated with refusal and delay.•Only about one-third of parents received high-quality recommendations. Receiving a healthcare provider's recommendation is a strong predictor of HPV vaccination, but little is known empirically about which types of recommendation are most influential. Thus, we sought to investigate the relationship between recommendation quality and HPV vaccination among U.S. adolescents. In 2014, we conducted a national, online survey of 1495 parents of 11–17-year-old adolescents. Parents reported whether providers endorsed HPV vaccination strongly, encouraged same-day vaccination, and discussed cancer prevention. Using an index of these quality indicators, we categorized parents as having received no, low-quality, or high-quality recommendations for HPV vaccination. Separate multivariable logistic regression models assessed associations between recommendation quality and HPV vaccine initiation (≥1 dose), follow through (3 doses, among initiators), refusal, and delay. Almost half (48%) of parents reported no provider recommendation for HPV vaccination, while 16% received low-quality recommendations and 36% received high-quality recommendations. Compared to no recommendation, high-quality recommendations were associated with over nine times the odds of HPV vaccine initiation (23% vs. 74%, OR=9.31, 95% CI, 7.10–12.22) and over three times the odds of follow through (17% vs. 44%, OR=3.82, 95% CI, 2.39–6.11). Low-quality recommendations were more modestly associated with initiation (OR=4.13, 95% CI, 2.99–5.70), but not follow through. Parents who received high- versus low-quality recommendations less often reported HPV vaccine refusal or delay. High-quality recommendations were strongly associated with HPV vaccination behavior, but only about one-third of parents received them. Interventions are needed to improve not only whether, but how providers recommend HPV vaccination for adolescents.

Background Area-level measures are often used to approximate socioeconomic status (SES) when individual-level data are not available. However, no national studies have examined the validity of these measures in approximating individual-level SES. Methods Data came from ~ 3,471,000 participants in the Mortality Disparities in American Communities study, which links data from 2008 American Community Survey to National Death Index (through 2015). We calculated correlations, specificity, sensitivity, and odds ratios to summarize the concordance between individual-, census tract-, and county-level SES indicators (e.g., household income, college degree, unemployment). We estimated the association between each SES measure and mortality to illustrate the implications of misclassification for estimates of the SES-mortality association. Results Participants with high individual-level SES were more likely than other participants to live in high-SES areas. For example, individuals with high household incomes were more likely to live in census tracts ( r = 0.232; odds ratio [OR] = 2.284) or counties ( r = 0.157; OR = 1.325) whose median household income was above the US median. Across indicators, mortality was higher among low-SES groups (all p < .0001). Compared to county-level, census tract-level measures more closely approximated individual-level associations with mortality. Conclusions Moderate agreement emerged among binary indicators of SES across individual, census tract, and county levels, with increased precision for census tract compared to county measures when approximating individual-level values. When area level measures were used as proxies for individual SES, the SES-mortality associations were systematically underestimated. Studies using area-level SES proxies should use caution when selecting, analyzing, and interpreting associations with health outcomes.

Introduction The number of older adults who are cancer survivors is rapidly growing. Evidence is needed to inform interventions to support successful aging among older adults (including older adult cancer survivors). Active engagement with life, that is, spending time with family and/or close friends, may be related to health outcomes, but this concept remains understudied. Methods We used survey data to assess active engagement among older adults (ages 50 + years) from seven mid-Atlantic US states ( n  = 2,914), and geocoded their residence to collect collected measures of community availability of social interaction. Outcomes were physical and mental health-related quality of life (HRQoL), assessed with the SF-12. We used multivariable, multilevel linear regression to evaluate relationships between social interactions (i.e., “active engagement with life,” or visiting with family and/or friends at least once per week and having at least three close friends, and community-level availability, measured with census tract-level park land and walkability and with county-level availability of social associations) and HRQoL. Finally, we explored differences in these relationships by recent cancer survivorship. Results Overall, 1,518 (52.3%) participants were actively engaged. Active engagement was associated with higher physical HRQoL (estimate = 0.94, standard error [SE] = 0.46, p  = .04) and mental HRQoL (estimate = 2.10, SE = 0.46, p  < .001). The relationship between active engagement and physical HRQoL was stronger for recent cancer survivors (estimate = 4.95, SE = 1.84, p  < .01) than for the general population (estimate = 1.10, SE = 0.43, p  = .01). Community-level availability of social interaction was not associated with HRQoL. Conclusion Our analysis demonstrated promising associations between active engagement with life and HRQoL among older adults, with large benefits for older cancer survivors. Additional research is needed on how active engagement is associated with better HRQoL, which can inform future policies and programs to optimize the aging process in the US.

Objective The CMS mandated hospital price transparency reporting on January 1, 2021 aiming to empower patients, enhance market competition, and curtail healthcare costs in the US. We aimed to characterize variability in hospital pricing reported by 1982 hospitals on six standard procedures (including abdominal ultrasound, diagnostic colonoscopy, kidney function blood test panel, knee arthroscopic cartilage removal, magnetic resonance imaging scan of brain, and pelvis computed tomography scan with contrast), with a particular focus on variations in pricing by insurance plan type. Results We found substantial heterogeneity across insurance plan types. The minimum number of prices reported was 18,679 for knee arthroscopic cartilage removal (reported by 908 hospitals, average = 21 prices/hospital), while the maximum number of prices reported was 44,921 for abdominal ultrasound (reported by 1861 hospitals, average = 24 prices/hospital). In general, reported hospital pricing was highest for the list price, followed by cash price and prices negotiated with commercial insurance plans. Government insurance, including Medicare, Medicaid and Veterans/Tricare plans, had much lower prices. However, prices were very heterogeneous with substantial overlaps between pricing for all plan types. The coefficients of variation for all procedures exceeded 100%, ranging from 106% for knee arthroscopic cartilage removal to 397% for kidney function blood test panel.

Background Cancer screening is suboptimal in rural areas, and interventions are needed to improve uptake. The Consolidated Framework for Implementation Research (CFIR) is a widely-used implementation science framework to optimize planning and delivery of evidence-based interventions, which may be particularly useful for screening promotion in rural areas. We examined the discussion of CFIR-defined domains and constructs in programs to improve cancer screening in rural areas. Methods We conducted a systematic search of research databases (e.g., Medline, CINAHL) to identify studies (published through November 2022) of cancer screening promotion programs delivered in rural areas in the United States. We identified 166 records, and 15 studies were included. Next, two reviewers used a standardized abstraction tool to conduct a critical scoping review of CFIR constructs in rural cancer screening promotion programs. Results Each study reported at least some CFIR domains and constructs, but studies varied in how they were reported. Broadly, constructs from the domains of Process, Intervention, and Outer setting were commonly reported, but constructs from the domains of Inner setting and Individuals were less commonly reported. The most common constructs were planning (100% of studies reporting), followed by adaptability, cosmopolitanism, and reflecting and evaluating (86.7% for each). No studies reported tension for change, self-efficacy, or opinion leader. Conclusions Leveraging CFIR in the planning and delivery of cancer screening promotion programs in rural areas can improve program implementation. Additional studies are needed to evaluate the impact of underutilized CFIR domains, i.e., Inner setting and Individuals, on cancer screening programs.

Purpose Health-related quality of life (HRQOL) among older cancer survivors can be impaired by factors such as treatment, comorbidities, and social challenges. These HRQOL impairments may be especially pronounced in rural areas, where older adults have higher cancer burden and more comorbidities and risk factors for poor health. This study aimed to assess rural–urban differences in HRQOL for older cancer survivors and controls. Methods Data came from Surveillance, Epidemiology, and End Results-Medicare Health Outcomes Survey (SEER-MHOS), which links cancer incidence from 18 U.S. population-based cancer registries to survey data for Medicare Advantage Organization enrollees (1998–2014). HRQOL measures were 8 standardized subscales and 2 global summary measures. We matched (2:1) controls to breast, colorectal, lung, and prostate cancer survivors, creating an analytic dataset of 271,640 participants (ages 65+). HRQOL measures were analyzed with linear regression models including multiplicative interaction terms (rurality by cancer status), controlling for sociodemographics, cohort, and multimorbidities. Results HRQOL scores were higher in urban than rural areas (e.g., global physical component summary score for breast cancer survivors: urban mean = 38.7, standard error [ SE ] = 0.08; rural mean = 37.9, SE  = 0.32; p  < 0.05), and were generally lower among cancer survivors compared to controls. Rural cancer survivors had particularly poor vitality (colorectal: p  = 0.05), social functioning (lung: p  = 0.05), role limitation-physical (prostate: p  < 0.01), role limitation-emotional (prostate: p  < 0.01), and global mental component summary (prostate: p  = 0.02). Conclusion Supportive interventions are needed to increase physical, social, and emotional HRQOL among older cancer survivors in rural areas. These interventions could target cancer-related stigma (particularly for lung and prostate cancers) and/or access to screening, treatment, and ancillary healthcare resources.

Background In the US, lung cancer burden is greater in counties that are either rural or in persistent poverty. This study examined lung cancer risk (e.g., smoking), incidence, and mortality across four county types defined by cross-classification of rurality and persistent poverty. Methods We conducted a secondary analysis of county characteristics and lung cancer risk, incidence and mortality. We used data from USDA to classify counties according to rurality (using rural–urban continuum codes) and persistent poverty (i.e., 20% + of residents living below the poverty line for 30 + years). We used publicly-available data to calculate mean county-level prevalence of smoking among adults (in 2019), lung cancer incidence (2015–2019), and lung cancer mortality (2015–2019) across county types. Beta and binomial regression models assessed differences in smoking, lung cancer incidence, and lung cancer mortality by rurality and persistent poverty. Results Among U.S. counties, 1,115 were urban, non-persistent poverty, 1,675 were rural, non-persistent poverty, 52 were urban, persistent poverty, and 301 were rural, persistent poverty. Smoking, lung cancer incidence, and lung cancer mortality were higher in rural counties and in persistent poverty counties than in their comparison counties. Counties that were both rural and persistent poverty had the highest rates of smoking, lung cancer incidence, and lung cancer mortality. Persistent poverty and rurality interacted in their relationship with smoking prevalence ( p  < 0.01), and lung cancer mortality ( p  < 0.10). Conclusions Smoking, lung cancer incidence, and lung cancer mortality are highest in counties that are both rural and persistent poverty, suggesting an urgent need to develop targeted lung cancer interventions in these communities.

Introduction: To characterize the impact of rural patients’ travel time to obtain healthcare on their reported utilization of preventive healthcare services and personal health outcomes. Methods: Online survey data from rural adults ages 50+ years living in the Northeastern United States were collected from February to August 2021. Study measures included self-reported travel time to obtain healthcare, use of preventive healthcare, and health outcomes. The associations between travel time with use of preventive care and health outcomes were assessed using linear, Poisson, and logistic regression analyses controlling for demographic variables. Results: Our study population included 1052 rural adults, with a mean travel time of 18.5 min (range: 0-60). Travel time was greater for racial/ethnic minority participants and for higher-income participants (both P < .05), but it was not associated with use of preventive healthcare. Greater travel time was associated with poorer mental health and more comorbidities, including cancer and diabetes (all P < .05). Conclusions: Travel time varied by patient demographic factors, and it was associated with mental health and comorbidities. There was no association between travel time and preventive care use, suggesting that other barriers likely contribute to suboptimal use of these services within rural communities. Further research is needed to elucidate the causal pathways linking travel time to mental health and comorbidities within rural communities, as increased travel may exacerbate intrarural health disparities.

Background Self-sampling for colorectal and cervical cancer screening can address the observed geographic disparities in cancer burden by alleviating barriers to screening participation, such as access to primary care. This preliminary study examines qualitative themes regarding cervical and colorectal cancer self-sampling screening tools among federally qualified health center clinical and administrative staff in underserved communities. Methods In-depth interviews were conducted with clinical or administrative employees (≥18 years of age) from FQHCs in rural and racially segregated counties in Pennsylvania. Data were managed and analyzed using QSR NVivo 12. Content analysis was used to identify themes about attitudes towards self-sampling for cancer screening. Results Eight interviews were conducted. Average participant age was 42 years old and 88% of participants were female. Participants indicated that a shared advantage for both colorectal and cervical cancer self-sampling tests was their potential to increase screening rates by simplifying the screening process and offering an alternative to those who decline traditional screening. A shared disadvantage to self-sampling was the potential for inaccurate sample collection, either through the test itself or the sample collection by the patient. Conclusions Self-sampling offers a promising solution to increase cervical and colorectal cancer screening in rural and racially segregated communities. This study’s findings can guide future research and interventions which integrate self-sampling screening into routine primary care practice.

Background Healthcare costs in the U.S. are high and variable, which can hinder access and impact health outcomes across communities. This study examined hospital‐ and county‐level characteristics to identify factors that explain geographic variation in prices for four cancer‐related procedures. Methods Data sources included Turquoise Health, which compiles publicly‐available price data from U.S. hospitals. We examined list prices for four procedures: abdominal ultrasound, diagnostic colonoscopy, brain MRI, and pelvis CT scan, which we linked to characteristics of hospitals (e.g., number of beds) and counties (e.g., metropolitan status). We used multilevel linear regression models to assess multivariable relationships between prices and hospital‐ and county‐level characteristics. Supplementary analyses repeated these models using procedures prices for commercial insurance plans. Results For each procedure, list prices varied across counties (intraclass correlation: abdominal ultrasound = 23.2%; colonoscopy = 17.1%; brain MRI = 37.2%; pelvis CT = 50.9%). List prices for each procedure were associated with hospital ownership (all p < 0.001) and percent of population without health insurance (all p < 0.05). For example, list prices for abdominal ultrasound were higher for proprietary versus Government‐owned hospitals (β = 539.10, 95% confidence interval [CI]: 256.12, 822.08, p < 0.001) and for hospitals in counties with more uninsured residents (β = 23.44, 95% CI: 2.55, 44.33, p = 0.03). Commercial insurance prices were negatively associated with metropolitan status. Conclusions Prices for cancer‐related healthcare procedures varied substantially, with considerable heterogeneity associated with county location as well as county‐level social determinants of health (e.g., health insurance coverage). Interventions and policy changes are needed to alleviate the financial burden of cancer care among patients, including geographic variation in prices for cancer‐related procedures.