Type 2 Diabetes as a Socioecological Disease: Can Youth Poets of Color Become Messengers of Truth and Catalysts for Change?

BACKGROUND: Efforts to confront the type 2 diabetes (T2D) epidemic have been stymied by an absence of effective communication on policy fronts. Whether art can be harnessed to reframe the T2D discourse from an individual, biomedical problem to a multilevel, communal and social problem is not known. METHOD: We explored whether spoken word workshops enable young artists of color to convey a critical consciousness about T2D. The Bigger Picture fosters creation and dissemination of art to shift from the narrow biomedical model toward a comprehensive socioecological model (SEM). Workshops offer (1) public health content, (2) writing exercises, and (3) feedback on drafts. Based on Freire and Boal's participatory pedagogy, workshops encourage youth to tap into their lived experiences when creating poetry. We analyzed changes in public health literary and activation among participants and mapped poems onto the SEM to assess whether their poetry conveyed the multilevel perspective critical to public health literacy. RESULTS: Participants reported significant increases in personal relevance of T2D prevention, T2D discussions with peers, concern about corporations' targeted marketing, and interest in community organizing to confront the epidemic. Across stanzas, nearly all poems (95%) featured >three of five SEM levels (systemic forces, sectors of influence, societal norms, behavioral settings, individual factors); three-quarters (78%) featured >four levels. CONCLUSIONS: Engaging youth poets of color to develop artistic content to combat T2D can increase their public health literary and social activation and foster compelling art that communicates how complex, multilevel forces interact to generate disease and disease disparities.

Seeing "The Bigger Picture:" Impact of an Arts-Focused Type 2 Diabetes Education Program in High Schools.

Traditional health education efforts rarely align with youth social justice values. The Bigger Picture (TBP), a spoken word arts campaign, leverages a social justice approach to activate youth around the social determinants of type 2 diabetes (T2D). This quasi-experimental study examines the impact of embedding TBP in urban, low-income high schools (3 intervention schools received TBP; 3 comparison schools received a non-health related spoken word program) with respect to (1) health-related mind-sets and expectations; (2) sense of belonging; and (3) civic engagement among youth. Adults and youth who participated in programming at all 6 schools were interviewed, and a content analysis of students' poems was performed. TBP was well-received by adults and students. While students in both TBP and comparison programs described multiple social determinants of T2D, intervention students more frequently articulated the connections between race/ethnicity and T2D as a social justice issue. Further, all comparison students explicitly mentioned individual dietary behavior as a T2D determinant while most, yet not all, intervention students did. Students in both programs reported a high sense of belonging at school and confidence in civic engagement. Content analysis of TBP students' poems revealed youth's detailed understanding of T2D determinants. Future studies might explore program scalability, and how the integration of civic engagement opportunities into TBP curriculum might impact students' capacity to create positive social change.

Challenges and solutions to employing natural language processing and machine learning to measure patients' health literacy and physician writing complexity: The ECLIPPSE study.

OBJECTIVE: In the National Library of Medicine funded ECLIPPSE Project (Employing Computational Linguistics to Improve Patient-Provider Secure Emails exchange), we attempted to create novel, valid, and scalable measures of both patients' health literacy (HL) and physicians' linguistic complexity by employing natural language processing (NLP) techniques and machine learning (ML). We applied these techniques to > 400,000 patients' and physicians' secure messages (SMs) exchanged via an electronic patient portal, developing and validating an automated patient literacy profile (LP) and physician complexity profile (CP). Herein, we describe the challenges faced and the solutions implemented during this innovative endeavor. MATERIALS AND METHODS: To describe challenges and solutions, we used two data sources: study documents and interviews with study investigators. Over the five years of the project, the team tracked their research process using a combination of Google Docs tools and an online team organization, tracking, and management tool (Asana). In year 5, the team convened a number of times to discuss, categorize, and code primary challenges and solutions. RESULTS: We identified 23 challenges and associated approaches that emerged from three overarching process domains: (1) Data Mining related to the SM corpus; (2) Analyses using NLP indices on the SM corpus; and (3) Interdisciplinary Collaboration. With respect to Data Mining, problems included cleaning SMs to enable analyses, removing hidden caregiver proxies (e.g., other family members) and Spanish language SMs, and culling SMs to ensure that only patients' primary care physicians were included. With respect to Analyses, critical decisions needed to be made as to which computational linguistic indices and ML approaches should be selected; how to enable the NLP-based linguistic indices tools to run smoothly and to extract meaningful data from a large corpus of medical text; and how to best assess content and predictive validities of both the LP and the CP. With respect to the Interdisciplinary Collaboration, because the research required engagement between clinicians, health services researchers, biomedical informaticians, linguists, and cognitive scientists, continual effort was needed to identify and reconcile differences in scientific terminologies and resolve confusion; arrive at common understanding of tasks that needed to be completed and priorities therein; reach compromises regarding what represents "meaningful findings" in health services vs. cognitive science research; and address constraints regarding potential transportability of the final LP and CP to different health care settings. DISCUSSION: Our study represents a process evaluation of an innovative research initiative to harness "big linguistic data" to estimate patient HL and physician linguistic complexity. Any of the challenges we identified, if left unaddressed, would have either rendered impossible the effort to generate LPs and CPs, or invalidated analytic results related to the LPs and CPs. Investigators undertaking similar research in HL or using computational linguistic methods to assess patient-clinician exchange will face similar challenges and may find our solutions helpful when designing and executing their health communications research.

Evaluating values-based message frames for type 2 diabetes prevention among Facebook audiences: Divergent values or common ground?

OBJECTIVE: To effectively confront the type 2 diabetes (T2D) epidemic, policymakers and the public need to problematize T2D less as a medical and more as a social problem. An award-winning T2D prevention campaign was harnessed to determine the most successful ways of framing ads on Facebook. HYPOTHESIS: We will observe variation in the effectiveness of ad message-frames within audience-segments. METHODS: Six parallel quasi-experiments (participants N = 203,156) were conducted with 6 disparate audience-segments defined through the Facebook ads-manager tool. Across all audiences, we exposed Facebook users to values-based ad-frames (10-15-word appeals), assigning 7 of 11 possible frames to participants within each audience in a quasi-experimental fashion (using Facebook users' birth-month). Engagement was measured by rates of ad video-views, unique-link-clicks and donations to the campaign. RESULTS: Contrary to our hypothesis, we observed remarkable consistency across target audiences. Ad-frames that ranked highly with most audience-segments included Entertainment and Emotional Appeal; Defiance Against Authority Appeal; Second-Hand Smoke/Environmental Appeal; and to a lesser extent, Common-Enemy/War-Metaphor Appeal. Conclusion and Practice-Implications: Across disparate segments of society, there appears to be a set of common values that public health communication initiatives can tap into to catalyze a more inclusive movement to confront the T2D epidemic through policy, systems and environmental approaches.

Retailer perspectives on sugar-sweetened beverage taxes in the California Bay Area.

The sugar-sweetened beverage (SSB) industry has claimed that food and beverage retailers are opposed to SSB taxes. In 2018 and 2019, we formally evaluated retailers' perceptions of SSB taxes using semi-structured interviews (including open- and closed-ended questions) with 103 randomly selected retailers (50 corner and liquor stores; 28 chain convenience, drug, and mass-merchandise stores; 18 chain supermarkets and discount supermarkets; and 7 independent supermarkets) across 3 cities with SSB taxes (Berkeley, Oakland, and San Francisco); interviews occurred in 2018 and 2019 (approximately 3 years, 1 year and 6 months post tax-implementation, respectively). A majority of both small and large retailers reported the tax had only a minimal effect on their business (70%). About half of retailers believed that other cities should adopt SSB taxes (53%), and were supportive of a statewide SSB tax (53%), noting it would level the playing field and better support health in their communities. Retailers' responses did not differ based on neighborhood income, and only 2 responses differed significantly between large and small retailers. Only 2 of 103 retailers reported raising the price of a non-beverage product in response to the tax, specifically raising the price of snack foods of low nutritional quality and alcoholic beverages. A majority of retailers in 3 California cities with SSB taxes have no concerns regarding the tax, endorse the health goals of SSB taxes and support statewide expansion of SSB tax policies.

Reproductive health and the environment: Counseling patients about risks.

Endocrine-disrupting chemicals (EDCs) are associated with reproductive complications such as infertility, pregnancy complications, poor birth outcomes, and child developmental abnormalities, although not all chemicals of concern are EDCs. Pregnant patients and women of childbearing age need reasonable advice about environmental contaminants and reproductive health.