Long-term cancer survivors with lymphedema may face up to 112% higher out-of-pocket costs than those without lymphedema, which influences lymphedema management, and has lasting impact on savings and productivity. Findings reinforce the need for actions at policy, provider, and individual patient levels, to reduce lymphedema costs. Future work should explore patient-driven recommendations to reduce economic burden after cancer.

Background In the United States, patients who have breast cancer experience significant economic burden compared with those who have other types of cancers. Cancer‐related economic burden is exacerbated by adverse treatment effects. Strategies to resolve the economic burden caused by breast cancer and its adverse treatment effects have stemmed from the perspectives of health care providers, oncology navigators, and other subject‐matter experts. For the current study, patient‐driven recommendations were elicited to reduce economic burden after 1) breast cancer and 2) breast cancer‐related lymphedema, which is a common, persistent adverse effect of breast cancer. Methods Qualitative interviews were conducted with 40 long‐term breast cancer survivors who were residents of Pennsylvania or New Jersey in 2015 and were enrolled in a 6‐month observational study. Purposive sampling ensured equal representation by age, socioeconomic position, and lymphedema diagnosis. Semistructured interviews addressed economic challenges, supports used, and patient recommendations for reducing financial challenges. Interviews were coded, and representative quotes from the patient recommendations were analyzed and reported to illustrate key findings. Results Of 40 interviewees (mean age, 64 years; mean time since diagnosis, 12 years), 27 offered recommendations to reduce the economic burden caused by cancer and its adverse treatment effects. Nine recommendations emerged across 4 major themes: expanding affordable insurance and insurance‐covered items, especially for lymphedema treatment (among the 60% who reported lymphedema); supportive domestic help; financial assistance from diagnosis through treatment; and employment‐preserving policies. Conclusions The current study yielded 9 actionable, patient‐driven recommendations—changes to insurance, supportive services, financial assistance, and protective policies—to reduce breast cancer‐related economic burden. These recommendations should be tested through policy and programmatic interventions.

Background Adjuvant therapy after breast cancer surgery decreases recurrence and increases survival, yet not all women receive and complete it. Previous research has suggested that distrust in medical institutions plays a role in who initiates adjuvant treatment, but has not assessed treatment completion treatment, nor the potential mediating role of physician distrust. Methods Women listed in Pennsylvania and Florida cancer registries, who were under the age of 65 when diagnosed with localized invasive breast cancer between 2005 and 2007, were surveyed by mail in 2007-2009. Survey participants self-reported: demographics; cancer stage and treatments; treatment discordance, as defined by not following their surgeon or oncologist treatment recommendation; healthcare system distrust, and physician trust. Age and cancer stage were verified against cancer registry records. Logistic regression assessed the relationship between highest and lowest tertiles of healthcare system distrust and the dichotomous outcome of treatment discordance, controlling for demographics and clinical treatment factors, and testing for mediation by physician trust. Results Of the 2,754 participants, 30.2% (n=832) reported not pursing at least one recommended treatment. The mean age was 52. Patients in the highest tertile of healthcare system distrust were 22% more likely to report treatment discordance than the lowest tertile; physician trust did not mediate the association between healthcare system distrust and treatment discordance. Conclusions Healthcare system distrust is positively associated with treatment discordance, defined as failure to initiate or complete physician recommended adjuvant treatment after breast cancer. Impact Interventions should test whether or not resolving institutional distrust reduces treatment discordance.

PurposeBreast cancer–related lymphedema is an adverse effect of breast cancer surgery affecting nearly 30% of US breast cancer survivors (BCS). Our previous analysis showed that, even 12 years after cancer treatment, out-of-pocket healthcare costs for BCS with lymphedema remained higher than for BCS without lymphedema; however, only half of the cost difference was lymphedema-related. This follow-up analysis examines what, above and beyond lymphedema, contributes to cost differences.MethodsThis mixed methods study included 129 BCS who completed 12 monthly cost diaries in 2015. Using Cohen’s d and multivariable analysis, we compared self-reported costs across 13 cost categories by lymphedema status. We elicited quotes about specific cost categories from in-person interviews with 40 survey participants.ResultsCompared with BCS without lymphedema, BCS with lymphedema faced 122% higher mean overall monthly direct costs ($355 vs $160); had significantly higher co-pay, medication, and other out-of-pocket costs, lower lotion costs; and reported inadequate insurance coverage and higher costs that persisted over time. Lotion and medication expenditure differences were driven by BCS’ socioeconomic differences in ability to pay.ConclusionsElevated patient costs for BCS with lymphedema are for more than lymphedema itself, suggesting that financial coverage for lymphedema treatment alone may not eliminate cost disparities.Implications for Cancer SurvivorsThe economic challenges examined in this paper have long been a concern of BCS and advocates, with only recent attention by policy makers, researchers, and providers. BCS identified potential policy and programmatic solutions, including expanding insurance coverage and financial assistance for BCS across socioeconomic levels.

Background and aims Among adolescents, risk preference and deviant behaviors are associated with marijuana use, which exhibit substantial historical trends. We examined (1) trends, (2) effect modification by sex and age, (3) associations of marijuana use with deviant behaviors and risk preferences and (4) differences by sex, age and year. Design Adjusted logistic and relative risk regression models, using data from the 2002-14 National Survey on Drug Use and Health, annual cross-sectional surveys of US households. Setting United States. Participants A nationally representative sample of adolescents aged 12-17 years (n = 230 452). Measurements We estimated associations between past-year marijuana use [self-reported using computer-assisted personal interviewing/audio computer-assisted self-interviewing (CAPI/ACASI)], deviant behavior (i.e. selling drugs; stealing; attacking someone) and risk preference (i.e. getting a kick; testing oneself). Findings Marijuana use, deviant behaviors and risk preferences declined among adolescents from 2002 to 2014. There were no significant sex or age differences in the decline of marijuana use over time. There were sex [sold drugs: β = 0.90, 95% confidence interval (CI) = 0.75, 1.04] and age (attacked someone: β = 0.32, 95% CI = 0.22, 0.42) differences in the prevalence of deviant behaviors, and trends over time differed by sex and age for attacking someone. Conclusions While marijuana use, deviant behavior and risk preferences among US adolescents declined from 2002 to 2014, associations have remained stable, with marijuana use positively associated with deviant behaviors and risk preferences.

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Three barriers investigators often encounter when conducting longitudinal work with homeless or other marginalized populations are difficulty tracking participants, high rates of no-shows for follow-up interviews, and high rates of loss to follow-up. Recent research has shown that homeless populations have substantial access to information technologies, including mobile devices and computers. These technologies have the potential both to make longitudinal data collection with homeless populations easier and to minimize some of these methodological challenges. This pilot study's purpose was to test whether individuals who were homeless and sleeping on the streets-the Bstreet homeless^-would answer questions remotely through a web-based data collection system at regular Bfollowup^intervals. We attempted to simulate longitudinal data collection in a condensed time period. Participants (N = 21) completed an in-person baseline interview. Each participant was given a remotely reloadable gift card. Subsequently, weekly for 8 weeks, participants were sent an email with a link to a SurveyMonkey questionnaire. Participants were given 48 h to complete each questionnaire. Data were collected about life on the streets, service use, community inclusion, substance use, and high-risk sexual behaviors. Ten dollars was remotely loaded onto each participant's gift card when they completed the questionnaire within the completion window. A substantial number of participants (67% of the total sample and 86% of the adjusted sample) completed at least seven out of the eight follow-up questionnaires. Most questionnaires were completed at public libraries, but several were completed at other types of locations (social service agencies, places of employment, relative/friend/acquaintance's domiciles, or via mobile phone). Although some of the questions were quite sensitive, very few participants skipped any questions. The only variables associated with questionnaire completion were frequency of computer use and education-both positive associations. This pilot study suggests that collecting longitudinal data online may be feasible with a subpopulation of persons experiencing homelessness. We suspect that participant follow-up rates using web-based data collection methods have the potential to exceed follow-up rates using traditional in-person interviews. If this population of persons experiencing street homelessness can be successful with this method of data collection, perhaps other disenfranchised, difficult-to-track, or difficult-to-reach populations could be followed using web-based data collection methods. Local governments are striving to decrease the Bdigital divide,^providing free or greatly discounted wi-fi connectivity as well as mobile computer lab access to low-income geographic areas. These actions, in combination with increased smart phone ownership, may permit vulnerable populations to connect and communicate with investigators.