Using Garden Cafés to engage community stakeholders in health research

et al. 2019

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Introduction: News media play an important role in raising public awareness, framing public opinions, affecting policy formulation, and acknowledgment of public health issues. Traditional qualitative content analysis for news sentiments and focuses are time-consuming and may not efficiently convey sentiments nor the focuses of news media. Methods: We used descriptive statistics and state-of-art text mining to conduct sentiment analysis and topic modeling, to efficiently analyze over 3 million Reuters news articles during 2007–2017 for identifying their coverage, sentiments, and focuses for public health issues. Based on the top keywords from public health scientific journals, we identified 10 major public health issues (i.e., “air pollution,” “alcohol drinking,” “asthma,” “depression,” “diet,” “exercise,” “obesity,” “pregnancy,” “sexual behavior,” and “smoking”). Results: The news coverage for seven public health issues, “Smoking,” “Exercise,” “Alcohol drinking,” “Diet,” “Obesity,” “Depression,” and “Asthma” decreased over time. The news coverage for “Sexual behavior,” “Pregnancy,” and “Air pollution” fluctuated during 2007–2017. The sentiments of the news articles for three of the public health issues, “exercise,” “alcohol drinking,” and “diet” were predominately positive and associated such as “energy.” Sentiments for the remaining seven public health issues were mainly negative, linked to negative terms, e.g., diseases. The results of topic modeling reflected the media’s focus on public health issues. Conclusions: Text mining methods may address the limitations of traditional qualitative approaches. Using big data to understand public health needs is a novel approach that could help clinical and translational science awards programs focus on community-engaged research efforts to address community priorities.

Section: Discussionmentioning

confidence: 91%

Mining news media for understanding public health concerns

Zolnoori

Huang

et al. 2019

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“…Community engagement platforms to increase awareness of and decrease stigma about mental health and obesity may be useful to promote care-seeking. For example, we have implemented Garden Cafes [46] in Olmsted County which could be expanded to other locations. Another specific implication of our study findings is that CTSA hubs may consider offering health promoting activities to study participants during their study visits.…”

Section: Discussionmentioning

confidence: 99%

Rural–urban health disparities for mood disorders and obesity in a midwestern community

Juhn

Ryu

et al. 2020

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Introduction: Prior studies indicate greater disease burden for obesity among rural compared with urban residents but no differences for mood disorder based on geographic location. Recent attention has focused on the need to examine regional rural–urban disparities in disease burden. We focused on mood disorders and obesity prevalence within three southeastern Minnesota counties served by the Mayo Clinic Center for Translational Science Award, in Rochester, Minnesota, as these were top priorities identified in community health needs assessments. Methods: Cross-sectional study to assess the association of rural–urban locality on 5-year (2009–2014) prevalence of mood disorder and obesity obtained using the Rochester Epidemiological Project medical records linkage system, among subjects residing in three mixed rural–urban counties on April 1, 2014. Multivariable analyses adjusted for demographics, socioeconomic status using an individual housing-based measure, and counties. Results: The study cohort (percent rural location) included 91,202 (15%) for Olmsted, 10,197 (51%) in Dodge, and 10,184 (57%) in Wabasha counties. On multivariate analysis, 5-year prevalence of mood disorders and obesity was significantly greater for urban compared with rural residents, after adjusting for confounders; odds ratios (95% confidence intervals): 1.21 (1.17–1.26), P < 0.001, and 1.05 (1.01–1.10), P = 0.016, respectively. Observed effects were not modified in additional models adjusted for health care utilization (HCU; ≥1 general medical examination visit and flu vaccination). Conclusions: Rural–urban health disparities for burden of mood disorders and obesity are independent of socioeconomic status and HCU in a Midwestern community. It is important to assess potential regional heterogeneity of rural–urban disparities on health outcomes.

“…Science cafés and community engagement studios [17][18][19] exemplifies successful face-to-face engagement strategies. Some more unique face-to-face programs like HealthStreet and Boot Camp Translation [20,21] include a personal component that is not easily disseminated.…”

Section: Discussionmentioning

confidence: 99%

“…Formative work at Mayo Clinic indicates that social media can be used to engage underrepresented, diverse community members in time-limited, two-way dialogs about health research [22,23]. Individuals who participated in face-to-face Garden Café forums indicated they desired to continue dialogs about research on social media venues (Facebook, blog, Twitter) [18]. Evaluation of these early efforts supports the utility of developing a social media platform for ongoing, two-way communication and co-learning across diverse populations.…”

Section: Discussionmentioning

confidence: 99%

Public feedback on a proposed statewide virtual translational research community

Eder

Brockman

et al. 2019

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Introduction: Researchers have explored using the internet and social media to recruit participants to specific research projects. Less systematic work has been done to inform the engagement of large populations in virtual communities to advance clinical and translational science. We report on our first step to use social media to engage Minnesota residents by studying the willingness of participants to engage in a virtual (Facebook) community about the concepts of health and health-related research. Methods: Data were collected at the 2018 Minnesota State Fair using a cross-sectional, 46-item survey with assessment including sociodemographics and willingness to engage in a Facebook group for health-related research. Quantitative analysis included univariate, bivariate, and multivariate analyses. Content analysis was used to generate themes from open-ended survey responses. Results: Five hundred people completed the survey; after data cleaning, 418 participant responses informed this report. A majority were younger than age 50 (73%), female (66%), and married/partnered (54%). Overall, 46% of participants agreed/strongly agreed they are willing to join the Facebook group. Multivariate logistic regression identified social media use over the past 6 months as the sole variable independently associated with willingness to join the Facebook group (once a day vs. never or rarely OR = 1.82 (0.86, 3.88), several hours a day vs. never or rarely OR = 2.17 (1.17, 4.02, overall p-value 0.048). Conclusion: Facebook holds potential for reaching a broader community, democratizing access to and engagement with clinical and translational research. Social media infrastructure and content could be disseminated to other institutions with Clinical and Translational Science Awards.