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IntroductionVaccine hesitancy is still rampant in the United States, including health care personnel. Vaccination of frontline essential workers (e.g. health care workers) is very important, especially during a pandemic. We tested the efficacy of a 4-week online, peer-led intervention (Harnessing Online Peer Education) to promote requests for COVID-19 vaccine information among essential workers.MethodsParticipants (N = 120) and peer leaders (N = 12) were recruited through online advertisements from July 23 to August 20, 2021. Eligibility criteria included: 18 years or older, U.S. resident, English speaker, part of phase 1a or 1 b of COVID-19 vaccine rollout (e.g. frontline essential workers), hadn't received a COVID-19 vaccine but able to receive one. This was a parallel assignment randomised trial. STATA was used to create a randomisation using a random number generator so that all possible assignments of participants and peer leaders to groups were equally likely. Participants were randomly assigned to intervention or control arms that consisted of two private, hidden Facebook groups, each with 30 participants. Peer leaders were randomly assigned to an intervention group, each with six peer leaders. Participants in the intervention arm were randomly assigned to three peer leaders. Participants were blinded after assignment. Peer leaders were tasked with reaching out to their assigned participants at least three times each week. Participants completed a baseline and a post intervention survey. The study is registered on ClinicalTrials.org under identifier NCT04376515 and is no longer recruiting. This work was supported by the NIAID under grant 5R01AI132030-05.ResultsA total of 101 participants analysed (50 intervention and 51 control). Six people in the intervention group and 0 people in the control group requested vaccine information. Ten people in the intervention group and six people in the control group provided proof of vaccination. The odds of requesting vaccine information in the intervention group was 13 times that in the control group (95% confidence interval: (1.5, 1772), p-value = 0.015). Thirty-seven participants in the intervention group and 31 in the control group were engaged at some point during the study.ConclusionsResults suggest peer-led online community groups may help to disseminate health information, aid public health efforts, and combat vaccine hesitancy. Key MessagesThe odds of requesting vaccine information was 13 times in the intervention group.Peer-led online communities may help to disseminate information and aid public health efforts to combat vaccine hesitancy.

Retention in healthcare and health behavior remains a critical issue, contributing to inequitable distribution of intervention benefits. In diseases such as HIV, where half of the new infections occur among racial and sexual minorities, it is important that interventions do not enlarge pre-existing health disparities. To effectively combat this public health issue, it is crucial that we quantify the magnitude of racial/ethnic disparity in retention. Further, there is a need to identify mediating factors to this relationship to inform equitable intervention design. In the present study, we assess the racial/ethnic disparity in retention in a peer-led online behavioral intervention to increase HIV self-testing behavior and identify explanatory factors. The research used data collected from the Harnessing Online Peer Education (HOPE) HIV Study that included 899 primarily African American and Latinx men who have sex with men (MSM) in the United States. Results show that African American participants had higher lost-to-follow-up rates at 12-week follow-up compared to Latinx participants (11.1% and 5.8% respectively, Odds Ratio=2.18, 95% confidence interval: 1.12 - 4.11, p=0.02), which is substantially mediated by participants' self-rated health score (14.1% of the variation in the African American v.s. Latinx difference in lost-follow-up, p=0.006). Thus, how MSM perceive their health may play an important role in their retention in HIV-related behavioral intervention programs and its racial/ethnic disparity.

Background: Deaths due to opioid overdose continue to rise in the United States. Despite availability of effective treatment for opioid use disorder, uptake is low among those who misuse opioids. Methods: This paper explores the role of misconception, stigma, and misinformation in influencing decisions to initiate medications for opioid use disorder among patients and providers. Conclusion: Misinformation about opioids has been prevalent among future healthcare providers and first responders as well as pharmaceutical companies, which may have implications for treatment. Among individuals with opioid use disorder, treatment uptake and adherence have been negatively affected by misconceptions about treatment efficacy and side effects, as well as stigma. We discuss the role of social media, education, and the community, in mitigating misinformation and addressing misconceptions about opioids and treatment options.

Human Immunodeficiency Virus (HIV) continues to be a significant public health problem, with ~1.2 million Americans living with HIV and ~14% unaware of their infection. The Centers for Disease Control and Prevention recommends that patients 13 to 64 years of age get screened for HIV at least once, and those with higher risk profiles screen at least annually. Unfortunately, screening rates are below recommendations for high-risk populations, leading to problems of delayed diagnosis. Novel technologies have been applied in HIV research to increase prevention, testing and treatment. Conversational agents, with potential for integrating artificial intelligence and natural language processing, may offer an opportunity to improve outreach to these high-risk populations. The feasibility, accessibility and acceptance of using conversational agents for HIV testing outreach is important to evaluate, especially amidst a global coronavirus disease 2019 pandemic when clinical services have been drastically affected. This viewpoint explores the application of a conversational agent in increasing HIV testing among high-risk populations.

Machine learning advancements in healthcare have made data collected through smartphones and wearable devices a vital source of public health and medical insights. While wearable device data helps to monitor, detect, and predict diseases and health conditions, some data owners hesitate to share such sensitive data with companies or researchers due to privacy concerns. Moreover, wearable devices have been recently available as commercial products; thus large, diverse, and representative datasets are not available to most researchers. In this article, we propose an open marketplace where wearable device users securely monetize their wearable device records by sharing data with consumers (e.g., researchers) to make wearable device data more available to healthcare researchers. To secure the data transactions in a privacy-preserving manner, we use a decentralized approach using Blockchain and Non-Fungible Tokens (NFTs). To ensure data originality and integrity with secure validation, our marketplace uses Trusted Execution Environments (TEE) in wearable devices to verify the correctness of health data. The marketplace also allows researchers to train models using Federated Learning with a TEE-backed secure aggregation of data users may not be willing to share. To ensure user participation, we model incentive mechanisms for the Federated Learning-based and anonymized data-sharing approaches using NFTs. We also propose using payment channels and batching to reduce smart contact gas fees and optimize user profits. If widely adopted, we believe that TEE and Blockchain-based incentives will promote the ethical use of machine learning with validated wearable device data in healthcare and improve user participation due to incentives.

Background People use online personal advertisements (ads) to solicit sexual partners. Data from online ads are often publicly available, allowing researchers to better understand the topics discussed and potential role of online ads in sexual health and risk behaviours. This study aims to examine those research questions. Methods We collected posts on ClassifiedAds.com from the US (August 2019– February 2020). Gender identity was abstracted from post title, when available. HIV risk-related terms were abstracted from post title and content and were used to dichotomise the following variables: (1) ads describing sexual risk behaviours; (2) ads mentioning concerns over substance use or sexually transmitted infections/HIV; and (3) ads mentioning an interest in substance use. Descriptive analysis and logistic regression were conducted. Results A total of n = 12 866 unique ads were posted; 72.4% posted by men. Most posts came from the southern US (34.7%) and from urban areas (89.6%). Few ads contained images (21.9%) or words associated with substance use (1%), while 26% mentioned substance use or STI/HIV concern. Logistic regression models indicated that ads in the South were less likely to contain substance use or STI/HIV concern than ads from the Midwest. Also, women were less likely than men to post about substance use or mention substance use or STI/HIV concern. Conclusions Personal ads offer a glimpse into Internet-mediated sex encounters and sexual health risks among those who seek sex online. The real-time data collected has potential to highlight elevated prevalence of sexual risk behaviours that may put individuals at risk for STI/HIV or substance use.

This study aimed to examine the depression and anxiety among men of color (primarily African American and Latinx) who have sex with men after the lockdown due to the COVID-19 pandemic. Outcomes included 21-item Beck Depression Inventory (BDI), 7-item Generalized Anxiety Disorder (GAD), and a 10-item COVID-related anxiety measure using a modified H1N1-related anxiety question. Independent variables were food insecurity and belief in government efficiency. Data were analyzed by Regression models with random cluster effects. Food insecurity experiences were significantly associated with higher depression (p

BACKGROUND: High-intensity drinking (HID; 8+ U.S. standard drinks for women, 10+ men) is initiated during adolescence/emerging adulthood, increasing risk for negative outcomes, including blackouts. We examined baseline data from a study of risky drinking youth to identify factors associated with HID. METHODS: Risky drinkers (ages 16-24) were recruited online (positive 3-month AUDIT-C score) as part of a larger study to examine social media interventions for risky drinking. We used baseline survey data to examine HID in relation to demographics, substance use-related variables, and individual and social factors. RESULTS: Among 931 risky drinkers, 29.8% reported past-month HID, and those with HID reported greater substance use and consequences. In multivariable analysis, HID was associated with male sex; greater social motives, impulsivity, and motivation; lower self-efficacy; and greater likelihood of not living with parents, drinking with important peers, and parental disapproval of posting drinking pictures. When examining age group interactions (16-20; 21-24), underage drinkers with high sensation seeking scores and lower parental disapproval of posting drinking pictures on social media reported greater HID. CONCLUSIONS: Among risky drinking youth, male sex, social motives, impulsivity, higher motivation to and lower-self-efficacy to reduce drinking, living away from parents, more frequent drinking with important peers, and lower parental disapproval of posting drinking pictures on social media were positively associated with HID. Further, HID was associated with greater health consequences, underscoring the need for HID interventions. Such interventions may benefit from enhancing motivation and self-efficacy, particularly in social contexts, as well as increasing positive peer and leisure activities to reduce HID.

Despite the availability of effective treatment, medications for opioid use disorder are underutilized due to a variety of practical, political, and psychological reasons. Digital inequalities, such as limited access to technology, skills to leverage the technology for desirable outcomes, and social resources, may be contributing to negative health outcomes. In addition, broader health literacy plays an integral part in the capacity of individuals to appraise opioid medication-related online information. This paper explores the role of digital inequalities in the uptake of treatment for opioid use disorder. Given the shift toward telemedicine and online counseling for substance use treatment as a consequence of the COVID-19 pandemic, more research into the digital inequalities faced by those who misuse opioids may provide insight into ways of engaging and encouraging this population to utilize treatment.

Factors related to risky drinking (e.g., motives, protective behavioral strategies [PBS]) may vary between youth who engage in polysubstance use compared to those who consume alcohol only. We examined differences in factors among youth who consume alcohol only compared to alcohol with other substances (i.e., polysubstance use), and correlates associated with risky drinking between the groups.Participants (Most participants (70.4%,Among risky drinking youth, results indicated youth engaging in polysubstance use have greater comorbidities and individual-level factors associated with risky drinking than youth who consume alcohol only. These findings may inform the tailoring of interventions for individuals who engage in risky drinking and polysubstance use.

A 6-week study was conducted to test the effectiveness of the Harnessing Online Peer Education (HOPE) intervention on anxiety, help seeking (requests for electronic resources [e-resources] on anxiety reduction), and online engagement.Three hundred participants with moderate to severe anxiety (i.e., seven-item Generalized Anxiety Disorder scale [GAD-7] scores ≥10) were randomly assigned to social media (i.e., Facebook) groups with or without peer leaders. The study was conducted from April 5 to May 17, 2020. GAD-7 scores, e-resource requests, and online engagement were measured at baseline and at weeks 2, 4, and 6.GAD-7 scores improved in both intervention and control groups, with no difference between conditions. Participants in the intervention group were more likely than those in the control group to request e-resources (OR=10.27, 95% CI=4.52-23.35) and engage online (OR=2.84, 95% CI=1.70-4.76).The HOPE intervention effectively promoted mental health help-seeking behavior and online engagement.

In response to the HIV/AIDS epidemic, stakeholders such as clinicians, community advocates, and researchers have utilized various forms of technology to mitigate the crisis. Blockchain is a nascent technology that has roots in cryptocurrency and its features are well suited for work in HIV. These features, especially the ability to securely transmit information and interactions, make it a potentially useful tool to integrate into research and practice related to stigmatized diseases, such as HIV, which require methods of maintaining high security and confidentiality. In this viewpoint, we briefly describe blockchain technology and explore its potential applications in research, clinical practice, and community settings. In research, blockchain has potential use for data collection, data storage, and dissemination of sexual health information. With respect to clinical practice, blockchain features would be well suited for storage of patient data and medical records. Potential uses in the community settings include cryptocurrency for sex work, collaboration with dating applications, and storage of test results.

Components of artificial intelligence (AI) for analysing social big data, such as natural language processing (NLP) algorithms, have improved the timeliness and robustness of health data. NLP techniques have been implemented to analyse large volumes of text from social media platforms to gain insights on disease symptoms, understand barriers to care and predict disease outbreaks. However, AI-based decisions may contain biases that could misrepresent populations, skew results or lead to errors. Bias, within the scope of this paper, is described as the difference between the predictive values and true values within the modelling of an algorithm. Bias within algorithms may lead to inaccurate healthcare outcomes and exacerbate health disparities when results derived from these biased algorithms are applied to health interventions. Researchers who implement these algorithms must consider when and how bias may arise. This paper explores algorithmic biases as a result of data collection, labelling and modelling of NLP algorithms. Researchers have a role in ensuring that efforts towards combating bias are enforced, especially when drawing health conclusions derived from social media posts that are linguistically diverse. Through the implementation of open collaboration, auditing processes and the development of guidelines, researchers may be able to reduce bias and improve NLP algorithms that improve health surveillance.

The COVID-19 pandemic and its related policies, such as social distancing orders, are affecting the ability for people with substance use disorders (SUD) to seek prevention and treatment. In this commentary, we introduce conversational agents, a type of social technology. We discuss the role of conversational agents in the prevention and treatment of SUD in social distancing contexts and the potential benefits and limitations of designing and implementing such technology in the prevention and care for patients with SUD.

Propelled by the transformative power of modern information and communication technologies, digitalization of data, and the increasing affordability of high-performance computing, Big Data science has brought forth revolutionary advancement in many areas of business, industry, health, and medicine. The HIV research and care service community is no exception to the benefits from the availability and utilization of Big Data analytics. Electronic health record (EHR) data (e.g., administrative and billing data, electronic medical records, or other digital records of information pertinent to individual or population health) are an essential source of health and disease outcome data because of the large amount of real-world, comprehensive, and often longitudinal data, which provide a good opportunity for leveraging advanced Big Data analytics in addressing challenges in HIV prevention, treatment, and care. This review focuses on studies that apply Big Data analytics to EHR data with aims to synthesize the HIV-related issues that EHR data studies can tackle, identify challenges in the utilization of EHR data in HIV research and practice, and discuss future needs and directions that can realize the promising potential role of Big Data in ending the HIV epidemic.

Since the beginning of the HIV epidemic, there have been more than 75 million cases. Currently, there about 1.2 million living with HIV in the USA. Despite current testing recommendations, test rates continue to be suboptimal. Investigators have studied the use of digital technology to promote HIV testing, especially among high-risk populations. Purpose of Review This non-systematic review provides an overview of the scientific research between 2015 and 2020 focused on the use of digital technology to bolster HIV testing and suggests novel technologies for exploration. Recent Findings A total of 40 studies were included in the review that span a wide range of available technology. Studies effectively increased HIV testing among study participants. Generally, participants in the intervention/exposure groups had significantly higher rates of HIV test uptake compared to participants in the comparison groups at study follow-up. Summary For a variety of reasons (e.g., differences in ways the technologies were used and study design), no digital tool clearly performed better than others, but each have the capacity to increase outreach and self-testing. An exploration of the potential use of nascent technologies is also discussed, as well as the authors’ experiences using a number of these technologies in our research.

Morbidity and mortality attributable to opioid use and misuse among adolescents and young adults are evident. Although recent trend data suggest a decrease in both opioid misuse and opioid use disorder among adolescents and young adults in the last few years, overdose cases continue to rise. The opioid epidemic among this population is complex and has a different profile compared to adults, with family facilitating exposure to opioids more often than other sources. Additionally, despite recommendations by experts to initiate medications for opioid use disorder, few initiate treatment. The recent COVID-19 pandemic has impacted many facets of daily life and its effects on the opioid crisis are largely unknown. Stay-at-home mandates resulting in online schooling and limited social interaction has had deleterious consequences for adolescents, especially their mental health. This viewpoint attempts to explore the effects of the pandemic on the opioid crisis in this vulnerable population.

Approximately 1.2 million people are living with HIV, with many of them unaware of their infection. Pre-exposure prophylaxis (PrEP) is available to minimize transmission among those at high risk for infection, including men who have sex with men, people who inject drugs, and female sex workers. Despite its availability, there is low usage of PrEP. To address this problem, various digital tools have been examined in HIV research. Among those, conversational agents are still underused and their capacity warrants examination to reach at-risk populations. In this paper, we discuss the potential of conversational agents in increasing uptake of PrEP by addressing barriers experienced among those at high risk for infection.