Community engagement through social media: A promising low-cost strategy for rural recruitment?

PURPOSE: For the same reasons that rural telehealth has shown promise for enhancing the provision of care in underserved environments, social media recruitment may facilitate more inclusive research engagement in rural areas. However, little research has examined social media recruitment in the rural context, and few studies have evaluated the feasibility of using a free social media page to build a network of rural community members who may be interested in a research study. Here, we describe the rationale, process, and protocols of developing and implementing a social media approach to recruit rural residents to participate in an mHealth intervention. METHODS: Informed by extensive formative research, we created a study Facebook page emphasizing community engagement in an mHealth behavioral intervention. We distributed the page to local networks and regularly posted recruitment and community messages. We collected data on the reach of the Facebook page, interaction with our messages, and initiations of our study intake survey. FINDINGS: Over 21 weeks, our Facebook page gained 429 followers, and Facebook users interacted with our social media messages 3,080 times. Compared to messages that described desirable study features, messages that described community involvement resulted in higher levels of online interaction. Social media and other recruitment approaches resulted in 225 people initiating our in-take survey, 9 enrolling in our pilot study, and 26 placing their names on a waiting list. CONCLUSIONS: A standalone social media page highlighting community involvement shows promise for recruiting in rural areas.

Adaptation and study protocol of the evidence-based Make Better Choices (MBC2) multiple diet and activity change intervention for a rural Appalachian population.

BACKGROUND: Rural Appalachian residents experience among the highest prevalence of chronic disease, premature mortality, and decreased life expectancy in the nation. Addressing these growing inequities while avoiding duplicating existing programming necessitates the development of appropriate adaptations of evidence-based lifestyle interventions. Yet few published articles explicate how to accomplish such contextual and cultural adaptation. METHODS: In this paper, we describe the process of adapting the Make Better Choices 2 (MBC2) mHealth diet and activity randomized trial and the revised protocol for intervention implementation in rural Appalachia. Deploying the NIH's Cultural Framework on Health and Aaron's Adaptation framework, the iterative adaptation process included convening focus groups (N = 4, 38 participants), conducting key informant interviews (N = 16), verifying findings with our Community Advisory Board (N = 9), and deploying usability surveys (N = 8), wireframing (N = 8), and pilot testing (N = 9. This intense process resulted in a comprehensive revision of recruitment, retention, assessment, and intervention components. For the main trial, 350 participants will be randomized to receive either the multicomponent MBC2 diet and activity intervention or an active control condition (stress and sleep management). The main outcome is a composite score of four behavioral outcomes: two outcomes related to diet (increased fruits and vegetables and decreased saturated fat intake) and two related to activity (increased moderate vigorous physical activity [MVPA] and decreased time spent on sedentary activities). Secondary outcomes include change in biomarkers, including blood pressure, lipids, A1C, waist circumference, and BMI. DISCUSSION: Adaptation and implementation of evidence-based interventions is necessary to ensure efficacious contextually and culturally appropriate health services and programs, particularly for underserved and vulnerable populations. This article describes the development process of an adapted, community-embedded health intervention and the final protocol created to improve health behavior and, ultimately, advance health equity. TRIAL REGISTRATION: ClinicalTrials.gov Identifier NCT04309461. The trial was registered on 6/3/2020.

Practitioners Assess Achievements and Challenges of Nonfatal Injury Surveillance.

OBJECTIVE: Injury surveillance relies on data coded for administrative rather than epidemiological accuracy. The Centers for Disease Control and Prevention (CDC) established the 5-year Surveillance Quality Improvement (SQI) initiative to advance consensus and methodology for injury epidemiology reporting and analysis. Evaluation of the positive predictive value of the CDC's injury surveillance definitions based on International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) and International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) coding in designated injury categories comprised much of the SQI initiative's work. The goal of the current study is to identify achievements and challenges in SQI as articulated by experienced injury epidemiology practitioners who participated in the CDC-funded SQI initiative. DESIGN, SETTING, AND PARTICIPANTS: We conducted semistructured interviews with 12 representatives of state and federal public health agencies who had participated extensively in the SQI initiative. The interviews were transcribed and coded using NVivo qualitative analysis software. Initial coding of the data involved both in vivo coding (using the words of participants) and coding of a priori themes. MAIN OUTCOME MEASURES: Qualitative analysis identified 2 overarching themes, variability among states and observations on the science of injury surveillance. RESULTS: Within the 2 broad themes, the respondents provided valuable insights regarding access to medical records, case definition validation, unique contributions of medical record abstracting, variations in the practice of medical coding, and the potential for use of data from medical record reviews in other injury-related areas. CONCLUSIONS: The contributions of the SQI initiative have provided valuable insights into ICD-10-CM case definitions for national injury surveillance. Challenges remain with regard to data access and quality with ongoing reliance on administrative datasets for injury surveillance.

#Ebola: Emergency Risk Messages on Social Media.

Public health threats require effective communication. Evaluating effectiveness during a situation that requires emergency risk communication is difficult, however, because these events require an immediate response and collecting data may be secondary to more immediate needs. In this article, we draw on research analyzing the effectiveness of social media messages during times of imminent threat and research analyzing the emergency risk communication conceptual model in order to propose a method for evaluating emergency risk communication on social media. We demonstrate this method by evaluating 2,915 messages sent by local, state, and federal public health officials during the 2014 Ebola outbreak in the United States. The results provide empirical support for emergency risk communication and identify message strategies that have the potential to increase exposure to official communication on social media during future public health threats.

Celebrity Cancer on Twitter: Mapping a Novel Opportunity for Cancer Prevention.

Social media platforms have the potential to facilitate the dissemination of cancer prevention and control messages following celebrity cancer diagnoses. However, cancer communicators have yet to systematically leverage these naturally occurring interventions on social media as these events are difficult to identify as they are unfolding and little research has analyzed their effect on social media conversations. In this study, we add to the research by analyzing how a celebrity cancer announcement influenced Twitter conversations in terms of the volume of social media messages and the type of content. Over a 9-day period, during which actor Ben Stiller announced that he had been treated for prostate cancer, we collected 1.2 million Twitter messages about cancer. We conducted automated content analyses to identify how often common cancer sites (prostate, breast, colon, or lung) were discussed. Then, we used manual content analysis on a sample of messages to identify cancer continuum content (awareness, prevention, early detection, diagnosis, treatment, survivorship, and end of life). Chi-square analyses were implemented to evaluate changes in cancer site and cancer continuum content before and after the announcement. We found that messages related to prostate cancer increased significantly more than expected for 2 days following Stiller's announcement. However, the number of cancer messages that described other cancer locations either did not increase or did not increase by the same magnitude. In terms of message content, results showed larger than expected increases in diagnosis messages. These results suggest opportunities to shape social media conversations following celebrity cancer announcements and increase prevention and early detection messages.

Retweeting Risk Communication: The Role of Threat and Efficacy.

Social media platforms like Twitter and Facebook provide risk communicators with the opportunity to quickly reach their constituents at the time of an emerging infectious disease. On these platforms, messages gain exposure through message passing (called "sharing" on Facebook and "retweeting" on Twitter). This raises the question of how to optimize risk messages for diffusion across networks and, as a result, increase message exposure. In this study we add to this growing body of research by identifying message-level strategies to increase message passing during high-ambiguity events. In addition, we draw on the extended parallel process model to examine how threat and efficacy information influence the passing of Zika risk messages. In August 2016, we collected 1,409 Twitter messages about Zika sent by U.S. public health agencies' accounts. Using content analysis methods, we identified intrinsic message features and then analyzed the influence of those features, the account sending the message, the network surrounding the account, and the saliency of Zika as a topic, using negative binomial regression. The results suggest that severity and efficacy information increase how frequently messages get passed on to others. Drawing on the results of this study, previous research on message passing, and diffusion theories, we identify a framework for risk communication on social media. This framework includes four key variables that influence message passing and identifies a core set of message strategies, including message timing, to increase exposure to risk messages on social media during high-ambiguity events.

Lung Cancer Messages on Twitter: Content Analysis and Evaluation.

PURPOSE: The aim of this project was to describe and evaluate the levels of lung cancer communication across the cancer prevention and control continuum for content posted to Twitter during a 10-day period (September 30 to October 9) in 2016. METHODS: Descriptive and inferential statistics were used to identify relationships between tweet characteristics in lung cancer communication on Twitter and user-level data. Overall, 3,000 tweets published between September 30 and October 9 were assessed by a team of three coders. Lung cancer-specific tweets by user type (individuals, media, and organizations) were examined to identify content and structural message features. The study also assessed differences by user type in the use of hashtags, directed messages, health topic focus, and lung cancer-specific focus across the cancer control continuum. RESULTS: Across the universe of lung cancer tweets, the majority of tweets focused on treatment and the use of pharmaceutical and research interventions, followed by awareness and prevention and risk topics. Among all lung cancer tweets, messages were most consistently tweeted by individual users, and personal behavioral mobilizing cues to action were rare. CONCLUSIONS: Lung cancer advocates, as well as patient and medical advocacy organizations, with an interest in expanding the reach and effectiveness of social media efforts should monitor the topical nature of public tweets across the cancer continuum and consider integrating cues to action as a strategy to increase engagement and behavioral activation pertaining to lung cancer reduction efforts.

Social Media Messages in an Emerging Health Crisis: Tweeting Bird Flu.

Limited research has examined the messages produced about health-related crises on social media platforms and whether these messages contain content that would allow individuals to make sense of a crisis and respond effectively. This study uses the crisis and emergency risk communication (CERC) framework to evaluate the content of messages sent via Twitter during an emerging crisis. Using manual and computer-driven content analysis methods, the study analyzed 25,598 tweets about the H7N9 virus that were produced in April 2013. The study found that a large proportion of messages contained sensemaking information. However, few tweets contained efficacy information that would help individuals respond to the crisis appropriately. Implications and recommendations for practice and future study are discussed.

Constructing the uncertainty of due dates.

By its nature, the date that a baby is predicted to be born, or the due date, is uncertain. How women construct the uncertainty of their due dates may have implications for when and how women give birth. In the United States as many as 15% of births occur before 39 weeks because of elective inductions or cesarean sections, putting these babies at risk for increased medical problems after birth and later in life. This qualitative study employs a grounded theory approach to understand the decisions women make on how and when to give birth. Thirty-three women who were pregnant or had given birth within the past 2 years participated in key informant or small-group interviews. The results suggest that women interpret the uncertainty of their due dates as a reason to wait for birth and as a reason to start the process early; however, information about a baby's brain development in the final weeks of pregnancy may persuade women to remain pregnant longer. The uncertainties of due dates are analyzed using Babrow's problematic integration, which distinguishes between epistemological and ontological uncertainty. The results point to a third type of uncertainty, axiological uncertainty. Axiological uncertainty is rooted in the values and ethics of outcomes.