Search

Background The rapid growth of eHealth could have the unintended effect of deepening health disparities between population subgroups. Most concerns to date have focused on population differences in access to technology, but differences may also exist in the appropriateness of online health content for diverse populations. Objective This paper reports findings from the first descriptive study of online cancer survivor stories by race and ethnicity of the survivor. Methods Using the five highest-rated Internet search engines and a set of search terms that a layperson would use to find cancer survivor stories online, we identified 3738 distinct sites. Of these, 106 met study criteria and contained 7995 total stories, including 1670 with an accompanying photo or video image of the survivor. Characteristics of both websites and survivor stories were coded. Results All racial minority groups combined accounted for 9.8% of online cancer survivor stories, despite making up at least 16.3% of prevalent cancer cases. Also notably underrepresented were stories from people of Hispanic ethnicity (4.1%), men (35.7%), survivors of colon cancer (3.5%), and older adults. Conclusions Because racial/ethnic minority cancer survivors are underrepresented in survivor stories available online, it is unlikely that this eHealth resource in its current form will help eliminate the disproportionate burden of cancer experienced by these groups.

Interdisciplinary research collaboration is needed to perform transformative science and accelerate innovation. The Science of Team Science strives to investigate, evaluate, and foster team science, including institutional policies that may promote or hinder collaborative interdisciplinary research and the resources and infrastructure needed to promote team science within and across institutions. Social network analysis (SNA) has emerged as a useful method to measure interdisciplinary science through the evaluation of several types of collaboration networks, including co-authorship networks. Likewise, research administrators are responsible for conducting rigorous evaluation of policies and initiatives. Within this paper, we present a case study using SNA to evaluate interprogrammatic collaboration (evidenced by co-authoring scientific papers) from 2007-2014 among scientists who are members of four formal research programs at an NCI-designated Cancer Center, the Markey Cancer Center (MCC) at the University of Kentucky. We evaluate change in network descriptives over time and implement separable temporal exponential-family random graph models (STERGMs) to estimate the effect of author and network variables on the tendency to form a co-authorship tie. We measure the diversity of the articles published over time (Blau's Index) to understand whether the changes in the co-authorship network are reflected in the diversity of articles published by research members. Over the 8-year period, we found increased inter-programmatic collaboration among research members as evidenced by co-authorship of published scientific papers. Over time, MCC Members collaborated more with others outside of their research program and outside their initial dense co-authorship groups, however tie formation continues to be driven by co-authoring with individuals of the same research program and academic department. Papers increased in diversity over time on all measures with the exception of author gender. This inter-programmatic research was fostered by policy changes in cancer center administration encouraging interdisciplinary research through both informal (e.g., annual retreats, seminar series) and formal (e.g., requiring investigators from more than two research programs on applications for pilot funding) means. Within this cancer center, interdisciplinary co-authorship increased over time as policies encouraging this collaboration were implemented. Yet, there is room for improvement in creating more interdisciplinary and diverse ties between research program members.

Social isolation is associated with higher mortality in studies comprising mostly white adults, yet associations among black adults are unclear. In this prospective cohort study, we evaluated whether associations of social isolation with all-cause, cardiovascular disease, and cancer mortality differed by race and sex. Adults enrolled in Cancer Prevention Study II in 1982/1983 were followed for mortality through 2012 (n = 580,182). Sex- and race-specific multivariable-adjusted hazard ratios and 95% confidence intervals were estimated for associations of a 5-point social isolation score with risk of death. Social isolation was associated with all-cause mortality in all subgroups (P for trend ≤ 0.005); for the most isolated versus the least isolated, the hazard ratios were 2.34 (95% confidence interval (CI): 1.58, 3.46) and 1.60 (95% CI: 1.41, 1.82) among black men and white men, respectively (P for interaction = 0.40) and 2.13 (95% CI: 1.44, 3.15) and 1.84 (95% CI: 1.68, 2.01) among black women and white women, respectively (P for interaction = 0.89). The association did not differ between black men and black women (P for interaction = 0.33) but was slightly stronger in white women than in white men (P for interaction = 0.01). Social isolation was associated with cardiovascular disease mortality in each subgroup (P for trend < 0.03) but with cancer mortality only among whites (P for trend < 0.0001). Subgroup differences in the influence of specific social isolation components were identified. Identifying and intervening with socially isolated adults could improve health outcomes. [ABSTRACT FROM AUTHOR]

Background: Social media is an important information source for a growing subset of the population and can likely be leveraged to provide insight into the evolving drug overdose epidemic. Twitter can provide valuable insight into trends, colloquial information available to potential users, and how networks and interactivity might influence what people are exposed to and how they engage in communication around drug use., Objective: This exploratory study was designed to investigate the ways in which unsupervised machine learning analyses using natural language processing could identify coherent themes for tweets containing substance names., Methods: This study involved harnessing data from Twitter, including large-scale collection of brand name (N=262,607) and street name (N=204,068) prescription drug-related tweets and use of unsupervised machine learning analyses (ie, natural language processing) of collected data with data visualization to identify pertinent tweet themes. Latent Dirichlet allocation (LDA) with coherence score calculations was performed to compare brand (eg, OxyContin) and street (eg, oxys) name tweets., Results: We found people discussed drug use differently depending on whether a brand name or street name was used. Brand name categories often contained political talking points (eg, border, crime, and political handling of ongoing drug mitigation strategies). In contrast, categories containing street names occasionally referenced drug misuse, though multiple social uses for a term (eg, Sonata) muddled topic clarity., Conclusions: Content in the brand name corpus reflected discussion about the drug itself and less often reflected personal use. However, content in the street name corpus was notably more diverse and resisted simple LDA categorization. We speculate this may reflect effective use of slang terminology to clandestinely discuss drug-related activity. If so, straightforward analyses of digital drug-related communication may be more difficult than previously assumed. This work has the potential to be used for surveillance and detection of harmful drug use information. It also might be used for appropriate education and dissemination of information to persons engaged in drug use content on Twitter., (©Maria A Parker, Danny Valdez, Varun K Rao, Katherine S Eddens, Jon Agley. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 28.07.2023.)

Cancer disproportionately affects the underserved. United Way 2-1-1 is an information and referral system that links underserved populations to community services. This study explores the feasibility of integrating proactive screening and referral to health services into 2-1-1. A cancer risk assessment was administered to callers (n=297), measuring their need for six cancer control services. A subset of respondents was randomized to receive generic or tailored referrals to needed services. Nearly all participants (85%) needed at least one of the services. Those who received tailored referrals were more likely to make appointments. Future research will explore approaches to address and eliminate health disparities through 2-1-1.