Addressing bias in artificial intelligence for public health surveillance.

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.

Impact of Sling Use on Functional Mobility in a Geriatric Population.

OBJECTIVES: Sling immobilization is commonly used following rotator cuff repair. The purpose of this study was to determine the detrimental impact of sling usage on mobility and balance in an older adult population through validated gait and balance testing. The authors hypothesize that sling use will negatively affect balance and stability. METHODS: This institutional review board-approved and registered randomized prospective clinical trial enrolled patients from 2019 to 2021. Following informed consent, patients were randomized into two groups: a sling worn (group 1) and no sling worn (group 2). Participants were assessed via the Edmonton Frail Scale as well as Tinetti gait and balance scoring. RESULTS: Fifty patients were included in the study, 23 (46%) men and 27 (54%) women, with a mean age of 72.2 years. The balance score median was 16.00 for participants not wearing a sling and 15.00 for participants wearing a sling. The gait score median was 12.00 for participants not wearing a sling and 11.50 for participants wearing a sling. The balance and gait scores were significantly greater when patients were not wearing a shoulder sling with P values of 0.006 and 0.011, respectively. The overall combined gait and balance score was significantly greater, with median values of 27.00 for participants not wearing a sling and 26.00 for participants wearing a sling (P = 0.001). Patients reported little to no anxiety about falling while wearing the sling, with a score of 0.16. CONCLUSIONS: Postoperative sling immobilization negatively affects balance and gait in the geriatric population, potentially increasing the risk of postoperative falls in an already at-risk population.

An Evaluation of the User Experience and Privacy Concerns of Individuals Misusing Opioids Using a Location Tracking Mobile Application.

Opioid use disorder is a growing public health concern in the United States, causing economic burden and hindered by stigma. New forms of data, including location data, may improve the effectiveness of interventions for preventing and treating opioid use disorder and/or misuse, increase access to treatment and address racial and ethnic disparities. This qualitative study aimed to identify factors that contribute to users' experience with a publicly available location-tracking mobile app - and investigate their privacy and ethical concerns. The study was conducted through two 15-minute interviews within a 48-h time frame. Participants were recruited from a pool of past research participants, Facebook ads, and referrals, and had to meet certain inclusion criteria related to opioid use disorder and/or misuse. The study had a final sample of 30 participants, 15 male and 15 female. The study suggests that a simple onboarding process and convenient experience can enhance participant adherence to the study app and other similar location-based research apps. However, the study also found that participants had concerns about privacy and transparency about locational privacy when sharing their location data. To improve the app, researchers suggest incorporating user behavior earlier in the app development stage. The study also highlights the importance of addressing ethical and privacy concerns such as limiting the types of collected data, incorporating data encryption and retention strategies, giving access to research staff only, and not sharing the data with third-party companies or law enforcement agencies to increase user satisfaction.

Direct and Indirect Effects of Cannabis Risk Perceptions on Cannabis Use Frequency.

Background: Perceived risk of harm associated with cannabis use has decreased in recent decades, particularly among emerging adults who show the highest prevalence of use. Cannabis-related protective behavioral strategies (PBS) are associated with lower cannabis use and fewer consequences; however, individuals who perceive using cannabis as low risk may use cannabis PBS less often. Therefore, using cross-sectional data, we examined the associations between perceived risk of harm associated with cannabis use, cannabis PBS, and cannabis use frequency. Method: Participants were 146 emerging adults between the ages of 18-25 (56.2% female) who reported consuming cannabis at least 3 times/week and completed measures of past-month cannabis use, past three-month use of cannabis PBS, and perceived risk of harm associated with cannabis use. Path analyses examined direct and indirect effects of perceived risk of cannabis-related harm on cannabis frequency through cannabis PBS. Results: Most (66.4%) participants reported no perceived risk of harm associated with occasional cannabis use, whereas 30.1% reported no perceived risk of harm associated with regular cannabis use. Findings indicated a significant indirect effect between perceived risk of harm and cannabis use frequency through cannabis PBS, b = -10.23, SE = 3.80, 95% CI [-17.67, -2.80], p = .007. Conclusions: Among emerging adults who consume cannabis regularly, findings suggest that a greater perceived risk of cannabis-related harm is associated with decreased cannabis use frequency via increased use of cannabis PBS. Although future analyses evaluating causal mechanisms are needed, these findings have clinical implications for harm reduction interventions focused on cannabis use.

Ethical Perspectives in Using Technology-Enabled Research for Key HIV Populations in Rights-Constrained Settings.

PURPOSE OF REVIEW: People who use illicit drug substances (e.g., heroin) and sex workers are vulnerable to acquiring HIV. Due to the criminalization of illicit drug substances and sex work in many countries, these populations often reside in rights-constrained settings where their well-being, freedom, and access to HIV prevention and care services may be compromised due to legal prosecutions and societal stigma. RECENT FINDINGS: This study conducted a literature review on papers that evaluated a combination of the following three components: ethics, technology-based research, and populations who use drug substances and/or sex workers. We explored research on these ethical perspectives from both key populations and researchers. Findings revealed potential risks in data security and possible harmful implications of compromised data within these rights-constrained settings. Best practices were explored within the literature to identify potential methods for addressing these ethical concerns and improving HIV prevention and care.

Data sharing to improve concordance in variant interpretation across laboratories: results from the Canadian Open Genetics Repository.

BACKGROUND: This study aimed to identify and resolve discordant variant interpretations across clinical molecular genetic laboratories through the Canadian Open Genetics Repository (COGR), an online collaborative effort for variant sharing and interpretation. METHODS: Laboratories uploaded variant data to the Franklin Genoox platform. Reports were issued to each laboratory, summarising variants where conflicting classifications with another laboratory were noted. Laboratories could then reassess variants to resolve discordances. Discordance was calculated using a five-tier model (pathogenic (P), likely pathogenic (LP), variant of uncertain significance (VUS), likely benign (LB), benign (B)), a three-tier model (LP/P are positive, VUS are inconclusive, LB/B are negative) and a two-tier model (LP/P are clinically actionable, VUS/LB/B are not). We compared the COGR classifications to automated classifications generated by Franklin. RESULTS: Twelve laboratories submitted classifications for 44 510 unique variants. 2419 variants (5.4%) were classified by two or more laboratories. From baseline to after reassessment, the number of discordant variants decreased from 833 (34.4% of variants reported by two or more laboratories) to 723 (29.9%) based on the five-tier model, 403 (16.7%) to 279 (11.5%) based on the three-tier model and 77 (3.2%) to 37 (1.5%) based on the two-tier model. Compared with the COGR classification, the automated Franklin classifications had 94.5% sensitivity and 96.6% specificity for identifying actionable (P or LP) variants. CONCLUSIONS: The COGR provides a standardised mechanism for laboratories to identify discordant variant interpretations and reduce discordance in genetic test result delivery. Such quality assurance programmes are important as genetic testing is implemented more widely in clinical care.

Potential application of conversational agents in HIV testing uptake among high-risk populations.

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.

Network interventions for managing the COVID-19 pandemic and sustaining economy.

Sustaining economic activities while curbing the number of new coronavirus disease 2019 (COVID-19) cases until effective vaccines or treatments become available is a major public health and policy challenge. In this paper, we use agent-based simulations of a network-based susceptible-exposed-infectious-recovered (SEIR) model to investigate two network intervention strategies for mitigating the spread of transmission while maintaining economic activities. In the simulations, we assume that people engage in group activities in multiple sectors (e.g., going to work, going to a local grocery store), where they interact with others in the same group and potentially become infected. In the first strategy, each group is divided into two subgroups (e.g., a group of customers can only go to the grocery store in the morning, while another separate group of customers can only go in the afternoon). In the second strategy, we balance the number of group members across different groups within the same sector (e.g., every grocery store has the same number of customers). The simulation results show that the dividing groups strategy substantially reduces transmission, and the joint implementation of the two strategies could effectively bring the spread of transmission under control (i.e., effective reproduction number ≈ 1.0).

Risky Drinking in Adolescents and Emerging Adults: Differences between Individuals Using Alcohol Only versus Polysubstances.

BACKGROUND: 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. METHODS: Participants (N = 955; ages 16-24; 54.5% female) who reported recent risky drinking completed measures of alcohol/substance use, alcohol-related consequences, drinking motives, alcohol PBS, mental health symptoms, and emotion dysregulation. Participants were in the polysubstance group if they reported using at least one other substance (e.g., cannabis, stimulants) in addition to alcohol in the past three months. Chi-square and t-tests examined differences between the two groups and multiple regression analyses examined correlates of risky drinking. RESULTS: Most participants (70.4%, n = 672) reported polysubstance use; these individuals engaged in riskier patterns of drinking, experienced more alcohol-related consequences, used fewer PBS, had stronger drinking motives (enhancement, social, coping), endorsed more mental health symptoms, and reported more emotion dysregulation. Regression models showed that emotion dysregulation significantly associated with risky drinking in the alcohol-only group; conformity and coping motives, alcohol PBS, and anxiety symptoms significantly associated with risky drinking in the polysubstance group. CONCLUSIONS: 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 Mobile Health Application Using Geolocation for Behavioral Activity Tracking.

The increasing popularity of mHealth presents an opportunity for collecting rich datasets using mobile phone applications (apps). Our health-monitoring mobile application uses motion detection to track an individual's physical activity and location. The data collected are used to improve health outcomes, such as reducing the risk of chronic diseases and promoting healthier lifestyles through analyzing physical activity patterns. Using smartphone motion detection sensors and GPS receivers, we implemented an energy-efficient tracking algorithm that captures user locations whenever they are in motion. To ensure security and efficiency in data collection and storage, encryption algorithms are used with serverless and scalable cloud storage design. The database schema is designed around Mobile Advertising ID (MAID) as a unique identifier for each device, allowing for accurate tracking and high data quality. Our application uses Google's Activity Recognition Application Programming Interface (API) on Android OS or geofencing and motion sensors on iOS to track most smartphones available. In addition, our app leverages blockchain and traditional payments to streamline the compensations and has an intuitive user interface to encourage participation in research. The mobile tracking app was tested for 20 days on an iPhone 14 Pro Max, finding that it accurately captured location during movement and promptly resumed tracking after inactivity periods, while consuming a low percentage of battery life while running in the background.

Socioeconomic Determinants of Remote Patient Monitoring Implementation Among Rural and Urban Hospitals.

Introduction: Remote patient monitoring (RPM) is a form of telehealth that improves quality of care for chronic disease treatment and reduces hospital readmission rates. Geographical proximity to health care is important for individuals of low socioeconomic status (SES) who face additional financial and transportation barriers. The goal of this study was to assess the association between social determinants of health and adoption of RPM. Methods: This cross-sectional study analyzed data from hospitals that responded to the American Hospital Association's Annual Survey (2018) and spatially linked census tract-level environmental and social determinants of health obtained from the Social Vulnerability Index (2018). Results: A total of 4,206 hospitals (1,681 rural and 2,525 urban hospitals) met study criteria. Rural hospitals near households in the lower middle quartile SES were associated with a 33.5% lower likelihood of having adopted RPM for chronic care management compared with rural hospitals near households in the highest quartile SES (adjusted odds ratios [aOR] = 0.665; 95% confidence interval [CI]: 0.453-0.977). Urban hospitals near households in the lowest quartile SES were associated with a 41.9% lower likelihood of having adopted RPM for chronic care management compared with urban hospitals near households in the highest quartile SES (aOR = 0.581; 95% CI: 0.435-0.775). Similar trends in accessibility were found with RPM for postdischarge services among urban hospitals. Conclusion: Our findings highlight the importance of hospital responsibility and state and federal policy approaches toward ensuring equitable access to RPM services for patients characterized by lower SES.

Role of Peer Coaches in Digital Interventions for MOUD Initiation and Maintenance.

Millions of Americans suffer from opioid use disorder (OUD) in the United States, resulting in thousands of deaths. The ongoing opioid crisis necessitates novel approaches to reduce the morbidity and mortality associated with misusing opioids. Studies using peer support models show success in engaging persons living with OUD in initiating treatment and decreasing relapse. Although most studies have focused on patients in clinical settings, community studies integrating peer community leaders also show promise. This viewpoint paper explores the use of peer coaches in online interventions in the community setting.

The Impact of Surgical Timing After Ankle Fracture on Clinical and Long-Term Patient Reported Outcomes.

The goal of this study is to evaluate the effect of time-to-surgery following closed ankle fractures on long-term patient reported outcomes, fracture healing, and wound complications. To date, little research has been done focusing on the impact "time to definitive fixation" has on patient reported outcomes. We performed a retrospective analysis of 215 patient records who underwent open reduction and internal fixation (ORIF) for an ankle fracture from July 2011 to July 2018. A total of 86 patients completed the patient reported outcome measurement information systems (PROMIS) survey at long-term follow-up. Primary outcomes were the rate of delayed union, postoperative wound complications, patient reported outcome measurement information system (PROMIS) pain interference (PI), and physical function (PF) scores. No differences were found when comparing time to surgery on a continuous scale with rates of delayed union, nonunion, or wound complications (p = .84, .47, and .63, respectively). PROMIS scores were collected at a median of 4.5 years (2.0 interquartile range (IQR), range 2.5-12.3) postoperatively. The time from ankle fracture to surgery was independently associated with worse PROMIS PI scores (unstandardized ß 0.38, 95% CI 0.07-0.68) but not PROMIS PF scores. Severe Lauge-Hansen injuries were independently associated with decreased PROMIS PF scores (unstandardized ß -7.02, 95% CI -12.0 to -2.04). Increased time to surgical intervention and severe Lauge-Hansen injuries were independently associated with worse long-term patient reported outcomes. Surgical timing did not impact union rates or wound complications. Surgeons should be aware that delaying ankle fracture repair beyond 12 days after injury may negatively affect long-term patient reported pain scores.

A Qualitative Exploration of the Potential Role of Using Online Social Media Support Communities to Increase Initiation of Medications for Opioid Use Disorder (MOUD).

Objectives: This study sought to explore the potential role of peer-led online communities to increase use of medications for opioid use disorder. Methods: From January through March 2020, participants with opioid use disorder and their family members/friends were recruited from paid Facebook ads; public health key stakeholders were recruited from referrals from the study team and opioid experts. Thirty participants from California were interviewed; 23 persons reporting opioid misuse, 3 family members/friends of persons misusing opioids, and 4 public health key stakeholders. We conducted semi-structured interviews asking about preferences, barriers and facilitators of treatment options for opioid use disorder, and perspectives around the use of digital/online communities. The categories of participants interviewed were each asked slightly different questions depending upon their role. Results: Results suggest that participants who misuse opioids (1) may prefer to engage in online communities rather than in-person meetings to discuss their opioid use, (2) generally prefer to receive opioid-related information from other patients with opioid use disorder and/or those in recovery rather than from health providers or other individuals, and (3) thought that an online community could be beneficial for helping address their opioid use. Conclusion: Results suggest an openness and interest in a peer-led online community to discuss opioid use and treatment among people who misuse opioids.

An Exploratory Examination of Social Media Use and Risky Sexual Practices: A Profile of Women in Rural Appalachia Who Use Drugs.

HIV/HCV risk behavior among women who use drugs is often exacerbated within high risk networks. The use of social media platforms such as Facebook to identify sex partners within these high-risk networks has not been examined among rural Appalachian women who use drugs. This paper provides an exploratory examination of Facebook use to identify sex partners among rural Appalachian women who use drugs, as well as associated risky sexual practices. Rural Appalachian women were randomly selected from two rural jails, consented, screened for eligibility (including drug use), and interviewed prior to jail release. Findings indicated that using Facebook to meet sex partners was associated with exchanging sex for drugs or money and having a male casual partner during the same time frame. These study findings suggest that the use of social media for high-risk sexual practices may provide a valuable platform for intervention delivery, particularly in resource-deprived areas where formal prevention and treatment services are limited.

Influenza vaccination during pregnancy and risk of selected major structural noncardiac birth defects, National Birth Defects Prevention Study 2006-2011.

PURPOSE: To assess associations between influenza vaccination during etiologically-relevant windows and selected major structural non-cardiac birth defects. STUDY DESIGN: We analyzed data from the National Birth Defects Prevention Study, a multisite, population-based case-control study, for 8233 case children diagnosed with a birth defect and 4937 control children without a birth defect with delivery dates during 2006-2011. For all analyses except for neural tube defects (NTDs), we classified mothers who reported influenza vaccination 1 month before through the third pregnancy month as exposed; the exposure window for NTDs was 1 month before through the first pregnancy month. For defects with five or more exposed case children, we used logistic regression to estimate propensity score-adjusted odds ratios (aORs) and 95% confidence intervals (CIs), adjusting for estimated delivery year and season; plurality; maternal age, race/ethnicity, smoking and alcohol use, low folate intake; and, for NTDs, folate antagonist medications. RESULTS: There were 334 (4.1%) case and 197 (4.0%) control mothers who reported influenza vaccination from 1 month before through the third pregnancy month. Adjusted ORs ranged from 0.53 for omphalocele to 1.74 for duodenal atresia/stenosis. Most aORs (11 of 19) were ≤1 and all adjusted CIs included the null. The unadjusted CIs for two defects, hypospadias and craniosynostosis, excluded the null. These estimates were attenuated upon covariate adjustment (hypospadias aOR: 1.25 (95% CI 0.89, 1.76); craniosynostosis aOR: 1.23 (95% CI: 0.88, 1.74)). CONCLUSIONS: Results for several non-cardiac major birth defects add to the existing evidence supporting the safety of inactivated influenza vaccination during pregnancy. Under-reporting of vaccination may have biased estimates downward.

Social Media Images as an Emerging Tool to Monitor Adherence to COVID-19 Public Health Guidelines: Content Analysis.

BACKGROUND: Innovative surveillance methods are needed to assess adherence to COVID-19 recommendations, especially methods that can provide near real-time or highly geographically targeted data. Use of location-based social media image data (eg, Instagram images) is one possible approach that could be explored to address this problem. OBJECTIVE: We seek to evaluate whether publicly available near real-time social media images might be used to monitor COVID-19 health policy adherence. METHODS: We collected a sample of 43,487 Instagram images in New York from February 7 to April 11, 2020, from the following location hashtags: #Centralpark (n=20,937), #Brooklyn Bridge (n=14,875), and #Timesquare (n=7675). After manually reviewing images for accuracy, we counted and recorded the frequency of valid daily posts at each of these hashtag locations over time, as well as rated and counted whether the individuals in the pictures at these location hashtags were social distancing (ie, whether the individuals in the images appeared to be distanced from others vs next to or touching each other). We analyzed the number of images posted over time and the correlation between trends among hashtag locations. RESULTS: We found a statistically significant decline in the number of posts over time across all regions, with an approximate decline of 17% across each site (P<.001). We found a positive correlation between hashtags (#Centralpark and #Brooklynbridge: r=0.40; #BrooklynBridge and #Timesquare: r=0.41; and #Timesquare and #Centralpark: r=0.33; P<.001 for all correlations). The logistic regression analysis showed a mild statistically significant increase in the proportion of posts over time with people appearing to be social distancing at Central Park (P=.004) and Brooklyn Bridge (P=.02) but not for Times Square (P=.16). CONCLUSIONS: Results suggest the potential of using location-based social media image data as a method for surveillance of COVID-19 health policy adherence. Future studies should further explore the implementation and ethical issues associated with this approach.

Online personal ads and its implication for sexual health risks: an observational analysis of posts.

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 =12866 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.

Accounting for Context in Randomized Trials after Assignment.

Many preventive trials randomize individuals to intervention condition which is then delivered in a group setting. Other trials randomize higher levels, say organizations, and then use learning collaboratives comprised of multiple organizations to support improved implementation or sustainment. Other trials randomize or expand existing social networks and use key opinion leaders to deliver interventions through these networks. We use the term contextually driven to refer generally to such trials (traditionally referred to as clustering, where groups are formed either pre-randomization or post-randomization - i.e., a cluster-randomized trial), as these groupings or networks provide fixed or time-varying contexts that matter both theoretically and practically in the delivery of interventions. While such contextually driven trials can provide efficient and effective ways to deliver and evaluate prevention programs, they all require analytical procedures that take appropriate account of non-independence, something not always appreciated. Published analyses of many prevention trials have failed to take this into account. We discuss different types of contextually driven designs and then show that even small amounts of non-independence can inflate actual Type I error rates. This inflation leads to rejecting the null hypotheses too often, and erroneously leading us to conclude that there are significant differences between interventions when they do not exist. We describe a procedure to account for non-independence in the important case of a two-arm trial that randomizes units of individuals or organizations in both arms and then provides the active treatment in one arm through groups formed after assignment. We provide sample code in multiple programming languages to guide the analyst, distinguish diverse contextually driven designs, and summarize implications for multiple audiences.

The Role of Misinformation and Stigma in Opioid Use Disorder Treatment Uptake.

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.