Addressing Antivaccine Sentiment on Public Social Media Forums Through Web-Based Conversations Based on Motivational Interviewing Techniques: Observational Study.

BACKGROUND: Health misinformation shared on social media can have negative health consequences; yet, there is a dearth of field research testing interventions to address health misinformation in real time, digitally, and in situ on social media. OBJECTIVE: We describe a field study of a pilot program of "infodemiologists" trained with evidence-informed intervention techniques heavily influenced by principles of motivational interviewing. Here we provide a detailed description of the nature of infodemiologists' interventions on posts sharing misinformation about COVID-19 vaccines, present an initial evaluation framework for such field research, and use available engagement metrics to quantify the impact of these in-group messengers on the web-based threads on which they are intervening. METHODS: We monitored Facebook (Meta Platforms, Inc) profiles of news organizations marketing to 3 geographic regions (Newark, New Jersey; Chicago, Illinois; and central Texas). Between December 2020 and April 2021, infodemiologists intervened in 145 Facebook news posts that generated comments containing either false or misleading information about vaccines or overt antivaccine sentiment. Engagement (emojis plus replies) data were collected on Facebook news posts, the initial comment containing misinformation (level 1 comment), and the infodemiologist's reply (level 2 reply comment). A comparison-group evaluation design was used, with numbers of replies, emoji reactions, and engagements for level 1 comments compared with the median metrics of matched comments using the Wilcoxon signed rank test. Level 2 reply comments (intervention) were also benchmarked against the corresponding metric of matched reply comments (control) using the Wilcoxon signed rank test (paired at the level 1 comment level). Infodemiologists' level 2 reply comments (intervention) and matched reply comments (control) were further compared using 3 Poisson regression models. RESULTS: In total, 145 interventions were conducted on 132 Facebook news posts. The level 1 comments received a median of 3 replies, 3 reactions, and 7 engagements. The matched comments received a median of 1.5 (median of IQRs 3.75) engagements. Infodemiologists made 322 level 2 reply comments, precipitating 189 emoji reactions and a median of 0.5 (median of IQRs IQR 0) engagements. The matched reply comments received a median of 1 (median of IQRs 2.5) engagement. Compared to matched comments, level 1 comments received more replies, emoji reactions, and engagements. Compared to matched reply comments, level 2 reply comments received fewer and narrower ranges of replies, reactions, and engagements, except for the median comparison for replies. CONCLUSIONS: Overall, empathy-first communication strategies based on motivational interviewing garnered less engagement relative to matched controls. One possible explanation is that our interventions quieted contentious, misinformation-laden threads about vaccines on social media. This work reinforces research on accuracy nudges and cyberbullying interventions that also reduce engagement. More research leveraging field studies of real-time interventions is needed, yet data transparency by technology platforms will be essential to facilitate such experiments.

Health-related quality of life in high-cost, high-need populations.

OBJECTIVES: To characterize patient-reported health and assess the psychometric performance of health-related quality of life (HRQOL) in high-cost, high-need (HCHN) populations. STUDY DESIGN: Retrospective longitudinal study examining health care utilization, expenditures, and patient-reported health comparing a baseline (year 1) and follow-up year (year 2). METHODS: The sample includes adults (n = 46,934) participating in the Medical Expenditure Panel Survey between 2011 and 2016. We estimated HRQOL for each sample member using the physical and mental health scales from the Medical Outcomes Study Short Form 12. We compared HRQOL stratified by HCHN, defined as patients whose baseline (year 1) demographics, utilization, and clinical characteristics predicted top decile health spending in year 2. Analyses assessed the validity, reliability, and responsiveness of physical and, separately, mental health scales. RESULTS: Among HCHN adults, the physical health scale exhibited robust measure validity, reliability, and responsiveness across all age groups; the mental health scale did not. Mean physical health was 1.25 SDs lower in HCHN vs other patients (37.9 vs 51.0 on a 0-100 scale increasing in self-perceived health; pooled SD, 10.5). Regressions indicated that a 0.5-SD increase in year 1 physical health among HCHN adults predicted a 5-percentage-point (10%) decrease in the probability of top decile health spending in year 2. In contrast to health care spending, HRQOL did not exhibit reversion to the mean in HCHN patients. CONCLUSIONS: Patient-reported health outcomes remain poor in HCHN populations, even after health care utilization recedes. HRQOL is a promising outcome measure for HCHN-focused payment and delivery interventions.

What Were the Information Voids? A Qualitative Analysis of Questions Asked by Dear Pandemic Readers between August 2020-August 2021.

In the current infodemic, how individuals receive information (channel), who it is coming from (source), and how it is framed can have an important effect on COVID-19 related mitigation behaviors. In light of these challenges presented by the infodemic, Dear Pandemic (DP) was created to directly address persistent questions related to COVID-19 and other health topics in the online environment. This is a qualitative analysis of 3806 questions that were submitted by DP readers to a question box on the Dear Pandemic website between August 30, 2020 and August 29, 2021. Analyses resulted in four themes: the need for clarification of other sources; lack of trust in information; recognition of possible misinformation; and questions on personal decision-making. Each theme reflects an unmet informational need of Dear Pandemic readers, which may be reflective of the broader informational gaps in our science communication efforts.This study highlights the role of an ad hoc risk communication platform in the current environment and uses questions submitted to the Dear Pandemic question box to identify informational needs of DP readers over the course of the COVID-19 pandemic. These findings may help clarify how organizations addressing health misinformation in the digital space can contribute to timely, responsive science communication and improve future communication efforts.

Dear Pandemic: A topic modeling analysis of COVID-19 information needs among readers of an online science communication campaign.

BACKGROUND: The COVID-19 pandemic was accompanied by an "infodemic"-an overwhelming excess of accurate, inaccurate, and uncertain information. The social media-based science communication campaign Dear Pandemic was established to address the COVID-19 infodemic, in part by soliciting submissions from readers to an online question box. Our study characterized the information needs of Dear Pandemic's readers by identifying themes and longitudinal trends among question box submissions. METHODS: We conducted a retrospective analysis of questions submitted from August 24, 2020, to August 24, 2021. We used Latent Dirichlet Allocation topic modeling to identify 25 topics among the submissions, then used thematic analysis to interpret the topics based on their top words and submissions. We used t-Distributed Stochastic Neighbor Embedding to visualize the relationship between topics, and we used generalized additive models to describe trends in topic prevalence over time. RESULTS: We analyzed 3839 submissions, 90% from United States-based readers. We classified the 25 topics into 6 overarching themes: 'Scientific and Medical Basis of COVID-19,' 'COVID-19 Vaccine,' 'COVID-19 Mitigation Strategies,' 'Society and Institutions,' 'Family and Personal Relationships,' and 'Navigating the COVID-19 Infodemic.' Trends in topics about viral variants, vaccination, COVID-19 mitigation strategies, and children aligned with the news cycle and reflected the anticipation of future events. Over time, vaccine-related submissions became increasingly related to those surrounding social interaction. CONCLUSIONS: Question box submissions represented distinct themes that varied in prominence over time. Dear Pandemic's readers sought information that would not only clarify novel scientific concepts, but would also be timely and practical to their personal lives. Our question box format and topic modeling approach offers science communicators a robust methodology for tracking, understanding, and responding to the information needs of online audiences.

Community-oriented Motivational Interviewing (MI): A novel framework extending MI to address COVID-19 vaccine misinformation in online social media platforms.

Researchers have linked circulating misinformation in online platforms to low COVID-19 vaccine uptake. Two disparate literatures provide relevant initial guidance to address the problem. Motivational Interviewing (MI) effectively reduces vaccine hesitancy in clinical environments; meanwhile, social scientists note inoculation, rebuttal, and appeals to accuracy are persuasive in digital contexts. A tension is inherent in these approaches. MI in digital forums may induce an 'illusory truth effect,' wherein falsehoods appear more accurate through repetition. Yet, rebutting misinformation directly may elicit backfire or reactance effects, motivating some to amplify their presentation of misinformation. Building on Identity Process Theory, we propose a theoretical framework for conducting MI-based infodemiology interventions among digital communities that conceptualizes the community in toto (rather than one specific person) as the unit of focus. Case examples from interventions on public Facebook posts illustrate three processes unique to such interventions: 1) Navigating tension between addressing commenters and "bystanders"; 2) Activating pro-vaccine bystanders; and 3) Reframing uncertainty or information individuals might find concerning or threatening according to implied collective values. This paper suggests community-oriented MI can maximize persuasive effects on bystanders while minimizing potential reactance from those with committed beliefs, thereby guiding community-oriented public health messaging interventions enacted in digital environments.

Lessons Learned From Dear Pandemic, a Social Media-Based Science Communication Project Targeting the COVID-19 Infodemic.

The World Health Organization has identified excessive COVID-19 pandemic-related information as a public health crisis, calling it an "infodemic." Social media allows misinformation to spread quickly and outcompete scientifically grounded information delivered via other methods. Dear Pandemic is an innovative, multidisciplinary, social media-based science communication project whose mission is to educate and empower individuals to successfully navigate the overwhelming amount of information circulating during the pandemic. This mission has 2 primary objectives: (1) to disseminate trustworthy, comprehensive, and timely scientific content about the pandemic to lay audiences via social media and (2) to promote media literacy and information-hygiene practices, equipping readers to better manage the COVID-19 infodemic within their own networks. The volunteer team of scientists publishes 8-16 posts per week on pandemic-relevant topics. Nearly 2 years after it launched in March 2020, the project has a combined monthly reach of more than 4 million unique views across 4 social media channels, an email newsletter, and a website. We describe the project's guiding principles, lessons learned, challenges, and opportunities. Dear Pandemic has emerged as an example of a promising new paradigm for public health communication and intervention. The contributors deliver content in ways that are personal, practical, actionable, responsive, and native to social media platforms. The project's guiding principles are a model for public health communication targeting future infodemics and can bridge the chasm between the scientific community and the practical daily decision-making needs of the general public.

Difficulty Obtaining Behavioral Health Services for Children: A National Survey of Multiphysician Practices.

PURPOSE: In the United States, primary care practices rely on scarce resources to deliver evidence-based care for children with behavioral health disorders such as depression, anxiety, other mental illness, or substance use disorders. We estimated the proportion of practices that have difficulty accessing these resources and whether practices owned by a health system or participating in Medicaid accountable care organizations (ACOs) report less difficulty. METHODS: This national cross-sectional study examined how difficult it is for practices to obtain pediatric (1) medication advice, (2) evidence-based psychotherapy, and (3) family-based therapy. We used the National Survey of Healthcare Organizations and Systems 2017-2018 (46.9% response rate), which sampled multiphysician primary and multispecialty care practices including 1,410 practices that care for children. We characterized practices' experience as "difficult" relative to "not at all difficult" using a 4-point ordinal scale. We used mixed-effects generalized linear models to estimate differences comparing system-owned vs independent practices and Medicaid ACO participants vs nonparticipants, adjusting for practice attributes. RESULTS: More than 85% of practices found it difficult to obtain help with evidence-based elements of pediatric behavioral health care. Adjusting for practice attributes, the percent experiencing difficulty was similar between system-owned and independent practices but was less for Medicaid ACO participants for medication advice (81% vs 89%; P = .021) and evidence-based psychotherapy (81% vs 90%; P = .006); differences were not significant for family-based treatment (85% vs 91%; P = .107). CONCLUSIONS: Most multiphysician practices struggle to obtain advice and services for child behavioral health needs, which are increasing nationally. Future studies should investigate the source of observed associations.

Dear Pandemic: Nurses as key partners in fighting the COVID-19 infodemic.

The COVID-19 pandemic and subsequent proliferation of misinformation have created parallel public health crises. Social media offers a novel platform to amplify evidence-based communication to broader audiences. This paper describes the application of science communication engagement on social media platforms by an interdisciplinary team of female scientists in a campaign called Dear Pandemic. Nurses are trusted professionals trained in therapeutic communication and are central to this effort. The Dear Pandemic campaign now has more than 97,000 followers with international and multilingual impact. Public health strategies to combat misinformation and guide individual behavior via social media show promise, and require further investment to support this novel dissemination of science communication.

Contemporaneous and long-term effects of children's public health insurance expansions on Supplemental Security Income participation.

This study explores the interplay between two important public programs for vulnerable children: Medicaid and the Supplemental Security Income (SSI) program. Children's public health insurance eligibility increased dramatically during the late 1990s with the launch of the Children's Health Insurance Program along with concurrent Medicaid expansions. We use a measure of simulated eligibility as an exogenous source of variation in Medicaid generosity to identify the effects of the eligibility expansions on SSI outcomes. Though increases in eligibility for public health insurance did not affect contemporaneous youth SSI applications or awards on average, expansions in coverage significantly decreased both applications and awards in states where SSI recipients did not automatically receive Medicaid. We attribute the difference in findings to the higher transactions costs associated with entering Medicaid via SSI in such states. In the long-term, increased public insurance eligibility during childhood reduces young adult SSI applications to some extent, consistent with recent findings that Medicaid coverage in youth improves adult health and economic outcomes.

A parent-directed language intervention for children of low socioeconomic status: a randomized controlled pilot study.

We designed a parent-directed home-visiting intervention targeting socioeconomic status (SES) disparities in children's early language environments. A randomized controlled trial was used to evaluate whether the intervention improved parents' knowledge of child language development and increased the amount and diversity of parent talk. Twenty-three mother-child dyads (12 experimental, 11 control, aged 1;5-3;0) participated in eight weekly hour-long home-visits. In the experimental group, but not the control group, parent knowledge of language development increased significantly one week and four months after the intervention. In lab-based observations, parent word types and tokens and child word types increased significantly one week, but not four months, post-intervention. In home-based observations, adult word tokens, conversational turn counts, and child vocalization counts increased significantly during the intervention, but not post-intervention. The results demonstrate the malleability of child-directed language behaviors and knowledge of child language development among low-SES parents.

Predicting high-cost pediatric patients: derivation and validation of a population-based model.

BACKGROUND: Health care administrators often lack feasible methods to prospectively identify new pediatric patients with high health care needs, precluding the ability to proactively target appropriate population health management programs to these children. OBJECTIVE: To develop and validate a predictive model identifying high-cost pediatric patients using parent-reported health (PRH) measures that can be easily collected in clinical and administrative settings. DESIGN: Retrospective cohort study using 2-year panel data from the 2001 to 2011 rounds of the Medical Expenditure Panel Survey. SUBJECTS: A total of 24,163 children aged 5-17 with family incomes below 400% of the federal poverty line were included in this study. MEASURES: Predictive performance, including the c-statistic, sensitivity, specificity, and predictive values, of multivariate logistic regression models predicting top-decile health care expenditures over a 1-year period. RESULTS: Seven independent domains of PRH measures were tested for predictive capacity relative to basic sociodemographic information: the Children with Special Health Care Needs (CSHCN) Screener; subjectively rated health status; prior year health care utilization; behavioral problems; asthma diagnosis; access to health care; and parental health status and access to care. The CSHCN screener and prior year utilization domains exhibited the highest incremental predictive gains over the baseline model. A model including sociodemographic characteristics, the CSHCN screener, and prior year utilization had a c-statistic of 0.73 (95% confidence interval, 0.70-0.74), surpassing the commonly used threshold to establish sufficient predictive capacity (c-statistic>0.70). CONCLUSIONS: The proposed prediction tool, comprising a simple series of PRH measures, accurately stratifies pediatric populations by their risk of incurring high health care costs.

Child Health and Access to Medical Care.

It might seem strange to ask whether increasing access to medical care can improve children's health. Yet Lindsey Leininger and Helen Levy begin by pointing out that access to care plays a smaller role than we might think, and that many other factors, such as those discussed elsewhere in this issue, strongly influence children's health. Nonetheless, they find that, on the whole, policies to improve access indeed improve children's health, with the caveat that context plays a big role-medical care "matters more at some times, or for some children, than others." Focusing on studies that can plausibly show a causal effect between policies to increase access and better health for children, and starting from an economic framework, they consider both the demand for and the supply of health care. On the demand side, they examine what happens when the government expands public insurance programs (such as Medicaid), or when parents are offered financial incentives to take their children to preventive appointments. On the supply side, they look at what happens when public insurance programs increase the payments that they offer to health-care providers, or when health-care providers are placed directly in schools where children spend their days. They also examine how the Affordable Care Act is likely to affect children's access to medical care. Leininger and Levy reach three main conclusions. First, despite tremendous progress in recent decades, not all children have insurance coverage, and immigrant children are especially vulnerable. Second, insurance coverage alone doesn't guarantee access to care, and insured children may still face barriers to getting the care they need. Finally, as this issue of Future of Children demonstrates, access to care is only one of the factors that policy makers should consider as they seek to make the nation's children healthier.

Predicting high-need cases among new Medicaid enrollees.

OBJECTIVES: To assess the ability of a short, self-reported health needs assessment (HNA) collected at the time of Medicaid enrollment to predict subsequent utilization and costs. STUDY DESIGN: Retrospective cohort study. METHODS: We analyzed individual-level data that included self-reported HNAs, medical care encounter records, and administrative eligibility records for 34,087 childless adult Medicaid enrollees in Wisconsin, covering the period 2009-2010. High need was operationalized using the following outcome variables measured over the first year of program enrollment: having an inpatient admission; membership in the top decile of emergency department (ED) utilization; and membership in the top cost decile. We assessed the ability of the HNA to predict high-need cases using several complementary methods: the C-statistic; integrated discrimination improvement; and sensitivity, specificity, and positive predictive value resulting from multivariate logistic regression estimates. RESULTS: Using the HNA along with sociodemographic measures met the Hosmer-Lemeshow criterion for adequate predictive performance for the high ED and high cost outcomes (C-statistics of 0.74 and 0.72, respectively). The HNA was associated with large improvements in predictive performance over sociodemographic measures alone for all 3 dependent variables (integrated discrimination improvement of 182%, 413%, and 300% for ED, cost, and inpatient variables, respectively). The HNA also led to considerable improvements in sensitivity and positive predictive value with no resulting decreases in specificity or negative predictive value. CONCLUSIONS: Collecting self-reported health measures for a Medicaid expansion population can yield data of sufficient quality for predicting high-need cases.

What fraction of Medicaid enrollees have private insurance coverage at the time of enrollment? Estimates from administrative data.

We use administrative data from Wisconsin to determine the fraction of new Medicaid enrollees who have private health insurance at the time of enrollment in the program. Through the linkage of several administrative data sources not previously used for research, we are able to observe coverage status directly for a large fraction of enrollees and indirectly for the remainder. We provide strict bounds for the percentages in each status and find that the percentage of new enrollees with private insurance coverage at the time of enrollment lies between 16 percent and 29 percent, and the percentage that dropped private coverage in favor of public insurance lies between 4 percent and 18 percent. Our point estimates indicate that, among all new enrollees, 21 percent had private health insurance at the time of enrollment and that 10 percent dropped this coverage. Our results show substantially lower rates than previous studies of crowd-out following public health insurance expansions and significant rates of dual coverage, whereby new enrollees into public insurance retain their previously held private insurance coverage.

The effects of expanding public insurance to rural low-income childless adults.

OBJECTIVE: This study measures the change in health care use after enrollment into a new public insurance program for low-income childless adults. DATA SOURCES/STUDY SETTING: The data sources include claims from a large integrated health system in rural Wisconsin and Medicaid enrollment files, January 2007-September 2012. STUDY DESIGN: We employ a regression discontinuity design to measure the causal effect of public insurance enrollment on counts of outpatient, emergency department, and inpatient events for 2 years following enrollment for a sample of previously uninsured low-income adults in rural Wisconsin. PRINCIPAL FINDINGS: Public insurance enrollment led to substantial increases in outpatient visits including preventive visits, but not mental health visits. Public insurance enrollment also led to increases in inpatient stays, but the study is inconclusive on whether it led to an increase in ED visits. CONCLUSIONS: Public insurance expansions to childless adults have the potential to impact the use of health care. The large increase in Medicaid coverage and reduction in rates of uninsurance anticipated to result from the Affordable Care Act should increase the use of inpatient and outpatient services, but they will have an uncertain impact on the use of ED among rural populations.

Using self-reported health measures to predict high-need cases among Medicaid-eligible adults.

OBJECTIVE: To assess the ability of different self-reported health (SRH) measures to prospectively identify individuals with high future health care needs among adults eligible for Medicaid. DATA SOURCES: The 1997-2008 rounds of the National Health Interview Survey linked to the 1998-2009 rounds of the Medical Expenditure Panel Survey (n = 6,725). STUDY DESIGN: Multivariate logistic regression models are fitted for the following outcomes: having an inpatient visit; membership in the top decile of emergency room utilization; and membership in the top cost decile. We examine the incremental predictive ability of six different SRH domains (health conditions, mental health, access to care, health behaviors, health-related quality of life [HRQOL], and prior utilization) over a baseline model with sociodemographic characteristics. Models are evaluated using the c-statistic, integrated discrimination improvement, sensitivity, specificity, and predictive values. PRINCIPAL FINDINGS: Self-reports of prior utilization provide the greatest predictive improvement, followed by information on health conditions and HRQOL. Models including these three domains meet the standard threshold of acceptability (c-statistics range from 0.703 to 0.751). CONCLUSIONS: SRH measures provide a promising way to prospectively profile Medicaid-eligible adults by likely health care needs.

Wisconsin experience indicates that expanding public insurance to low-income childless adults has health care impacts.

As states consider expanding Medicaid to low-income childless adults under the Affordable Care Act, their decisions will depend, in part, on how such coverage may affect the use of medical care. In 2009 Wisconsin created a new public insurance program for low-income uninsured childless adults. We analyzed administrative claims data spanning 2008 and 2009 using a case-crossover study design on a population of 9,619 Wisconsin residents with very low incomes who were automatically enrolled in this program in January 2009. In the twelve months following enrollment in public insurance, outpatient visits for the study population increased 29 percent, and emergency department visits increased 46 percent. Inpatient hospitalizations declined 59 percent, and preventable hospitalizations fell 48 percent. These results demonstrate that public insurance coverage expansions to childless adults have the potential to improve health and reduce costs by increasing access to outpatient care and reducing hospitalizations.