Identification of Myths and Misinformation About Treatment for Opioid Use Disorder on Social Media: Infodemiology Study.

BACKGROUND: Health misinformation and myths about treatment for opioid use disorder (OUD) are present on social media and contribute to challenges in preventing drug overdose deaths. However, no systematic, quantitative methodology exists to identify what types of misinformation are being shared and discussed. OBJECTIVE: We developed a multistage analytic pipeline to assess social media posts from Twitter (subsequently rebranded as X), YouTube, Reddit, and Drugs-Forum for the presence of health misinformation about treatment for OUD. METHODS: Our approach first used document embeddings to identify potential new statements of misinformation from known myths. These statements were grouped into themes using hierarchical agglomerative clustering, and public health experts then reviewed the results for misinformation. RESULTS: We collected a total of 19,953,599 posts discussing opioid-related content across the aforementioned platforms. Our multistage analytic pipeline identified 7 main clusters or discussion themes. Among a high-yield data set of posts (n=303) for further public health expert review, these included discussion about potential treatments for OUD (90/303, 29.8%), the nature of addiction (68/303, 22.5%), pharmacologic properties of substances (52/303, 16.9%), injection drug use (36/303, 11.9%), pain and opioids (28/303, 9.3%), physical dependence of medications (22/303, 7.2%), and tramadol use (7/303, 2.3%). A public health expert review of the content within each cluster identified the presence of misinformation and myths beyond those used as seed myths to initialize the algorithm. CONCLUSIONS: Identifying and addressing misinformation through appropriate communication strategies could be an increasingly important component of preventing overdose deaths. To further this goal, we developed and tested an approach to aid in the identification of myths and misinformation about OUD from large-scale social media content.

Buprenorphine use and setting type among reproductive-aged women self-reporting nonmedical prescription opioid use.

INTRODUCTION: Screening for opioid misuse and treatment for opioid use disorder are critical for reducing morbidity and mortality. We sought to understand the extent of self-reported past 30-day buprenorphine use in various settings among women of reproductive age with self-reported nonmedical prescription opioid use being assessed for substance use problems. METHODS: The study collected data from individuals being assessed for substance use problems using the Addiction Severity Index-Multimedia Version in 2018-2020. We stratified the sample of 10,196 women ages 12-55 self-reporting past 30-day nonmedical prescription opioid use by buprenorphine use and setting type. We categorized setting types as: buprenorphine in specialty addiction treatment, buprenorphine in office-based opioid treatment, and diverted buprenorphine. We included each woman's first intake assessment during the study period. The study assessed number of buprenorphine products, reasons for using buprenorphine, and sources of buprenorphine procurement. The study calculated frequency of reasons for using buprenorphine to treat opioid use disorder outside of a doctor-managed treatment, overall and by race/ethnicity. RESULTS: Overall, 25.5 % of the sample used buprenorphine in specialty addiction treatment, 6.1 % used buprenorphine prescribed in office-based treatment, 21.7 % used diverted buprenorphine, and 46.7 % reported no buprenorphine use during the past 30 days. Among women who reported using buprenorphine to treat opioid use disorder, but not as part of a doctor-managed treatment, 72.3 % could not find a provider or get into a treatment program, 21.8 % did not want to be part of a program or see a provider, and 6.0 % reported both; a higher proportion of American Indian/Alaska Native women (92.1 %) reported that they could not find a provider or get into a treatment program versus non-Hispanic White (78.0 %), non-Hispanic Black (76.0 %), and Hispanic (75.0 %) women. CONCLUSIONS: Appropriate screening for nonmedical prescription opioid use to assess need for treatment with medication for opioid use disorder is important for all women of reproductive age. Our data highlight opportunities to improve treatment program accessibility and availability and support the need to increase equitable access for all women.

Characteristics of Adults Aged ≥18 Years Evaluated for Substance Use and Treatment Planning - United States, 2019.

In 2019, 65.8 million U.S. adults reported past-month binge drinking and 35.8 million reported illicit drug use or prescription pain reliever misuse during the past month; 20.4 million met diagnostic criteria for a substance use disorder during the past year (1). Approximately 81,000 persons died of a drug overdose* during May 2019-May 2020; excessive alcohol use contributes to an estimated 95,000 deaths per year (2). Persons with a substance use disorder are at elevated risk for overdose and associated harms (3). To examine the prevalence of past 30-day substance use patterns and the severity of problems experienced across seven biopsychosocial domains (alcohol, drug, employment, family, legal, medical, and psychiatric), CDC used 2019 data from the National Addictions Vigilance Intervention and Prevention Program (NAVIPPRO) Addiction Severity Index-Multimedia Version (ASI-MV) tool (4); these data are collected from adults aged ≥18 years who seek substance use treatment in the United States. Alcohol was the most commonly reported substance used during the past 30 days (35.8%), followed by cannabis (24.9%), prescription opioids (misuse) (18.5%), illicit stimulants (14.0%), heroin (10.2%), prescription sedatives or tranquilizers (misuse) (8.5%), cocaine (7.4%), illicit fentanyl (4.9%), and prescription stimulants (misuse) (1.8%).† Polysubstance use (use of two or more substances) during the past 30 days was reported by 32.6% of respondents. Among the biopsychosocial domains measured, 45.4% of assessments reported more severe problems with drugs; others reported psychiatric (35.2%), legal (28.8%), medical (27.4%), employment (25.0%), alcohol (24.2%), and family problems (22.8%). These findings highlight the complex nature of substance use in the United States, the interplay between substance use and mental illness, and the complex challenges that persons with substance use disorder face when seeking treatment. Actions to enhance comprehensive substance use programs that incorporate polysubstance use and co-occurring mental health problems into strategies for prevention, treatment, and response are needed, as is expanded linkage to services. CDC provides data and resources to equip and inform states, territories, and local jurisdictions to help improve opioid prescribing practices, improve linkage to care for the treatment of opioid use disorder, and prevent and reverse overdoses.§.

Characterizing and Identifying the Prevalence of Web-Based Misinformation Relating to Medication for Opioid Use Disorder: Machine Learning Approach.

BACKGROUND: Expanding access to and use of medication for opioid use disorder (MOUD) is a key component of overdose prevention. An important barrier to the uptake of MOUD is exposure to inaccurate and potentially harmful health misinformation on social media or web-based forums where individuals commonly seek information. There is a significant need to devise computational techniques to describe the prevalence of web-based health misinformation related to MOUD to facilitate mitigation efforts. OBJECTIVE: By adopting a multidisciplinary, mixed methods strategy, this paper aims to present machine learning and natural language analysis approaches to identify the characteristics and prevalence of web-based misinformation related to MOUD to inform future prevention, treatment, and response efforts. METHODS: The team harnessed public social media posts and comments in the English language from Twitter (6,365,245 posts), YouTube (99,386 posts), Reddit (13,483,419 posts), and Drugs-Forum (5549 posts). Leveraging public health expert annotations on a sample of 2400 of these social media posts that were found to be semantically most similar to a variety of prevailing opioid use disorder-related myths based on representational learning, the team developed a supervised machine learning classifier. This classifier identified whether a post's language promoted one of the leading myths challenging addiction treatment: that the use of agonist therapy for MOUD is simply replacing one drug with another. Platform-level prevalence was calculated thereafter by machine labeling all unannotated posts with the classifier and noting the proportion of myth-indicative posts over all posts. RESULTS: Our results demonstrate promise in identifying social media postings that center on treatment myths about opioid use disorder with an accuracy of 91% and an area under the curve of 0.9, including how these discussions vary across platforms in terms of prevalence and linguistic characteristics, with the lowest prevalence on web-based health communities such as Reddit and Drugs-Forum and the highest on Twitter. Specifically, the prevalence of the stated MOUD myth ranged from 0.4% on web-based health communities to 0.9% on Twitter. CONCLUSIONS: This work provides one of the first large-scale assessments of a key MOUD-related myth across multiple social media platforms and highlights the feasibility and importance of ongoing assessment of health misinformation related to addiction treatment.

Rates of neglect in a national sample: Child and family characteristics and psychological impact.

BACKGROUND: Childhood neglect is an understudied form of childhood maltreatment despite being the most commonly reported to authorities. OBJECTIVE: This study provides national estimates of neglect subtypes, demographic variations in exposure to neglect subtypes, and examines the psychological impact. PARTICIPANTS AND SETTING: Pooled data from two representative U.S. samples from the National Surveys of Children's Exposure to Violence (NatSCEV) survey conducted in 2011 and 2014, representing the experiences of children and youth aged 1 month to 17 years (N = 8503). METHODS: Telephone surveys were used to obtain sociodemographic characteristics, six measures of past year and lifetime exposure to neglect, and assessments of trauma symptoms, suicidal ideation, alcohol use, and illicit drug use. RESULTS: More than 1 in 17 U.S. children (6.07%) experienced some form of neglect in the past year, and more than 1 in 7 (15.14%) experienced neglect at some point in their lives. Supervisory neglect, due to parental incapacitation or parental absence, was most common. Families with two biological parents had lower rates (4.29% in the past year) than other household configurations (range from 7.95% to 14.10%; p < .05). All types of neglect were associated with increased trauma symptoms and suicidal ideation (for 10-17 year olds), and several were associated with increased risk of underage alcohol and illicit drug use. CONCLUSION: More attention needs to be paid to the impact of supervisory neglect. These results underscore the importance of prevention strategies that provide the supports necessary to build safe, stable, and nurturing relationships and environments that help children thrive.

Beyond residential mobility: A broader conceptualization of instability and its impact on victimization risk among children.

Predictability in a child's environment is a critical quality of safe, stable, nurturing relationships and environments, which promote wellbeing and protect against maltreatment. Research has focused on residential mobility's effect on this predictability. This study augments such research by analyzing the impact of an instability index-including the lifetime destabilization factors (LDFs) of natural disasters, homelessness, child home removal, multiple moves, parental incarceration, unemployment, deployment, and multiple marriages--on childhood victimizations. The cross-sectional, nationally representative sample of 12,935 cases (mean age = 8.6 years) was pooled from 2008, 2011, and 2014 National Surveys of Children's Exposure to Violence (NatSCEV). Logistic regression models controlling for demographics, socio-economic status, and family structure tested the association between excessive residential mobility, alone, and with LDFs, and past year childhood victimizations (sexual victimization, witnessing community or family violence, maltreatment, physical assault, property crime, and polyvictimization). Nearly 40% of the sample reported at least one LDF. Excessive residential mobility was significantly predictive of increased odds of all but two victimizations; almost all associations were no longer significant after other destabilizing factors were included. The LDF index without residential mobility was significantly predictive of increased odds of all victimizations (AOR's ranged from 1.36 to 1.69), and the adjusted odds ratio indicated a 69% increased odds of polyvictimization for each additional LDF a child experienced. The LDF index thus provides a useful alternative to using residential moves as the sole indicator of instability. These findings underscore the need for comprehensive supports and services to support stability for children and families.

Injuries From Physical Abuse: National Survey of Children's Exposure to Violence I-III.

INTRODUCTION: Official data sources do not provide researchers, practitioners, and policy makers with complete information on physical injury from child abuse. This analysis provides a national estimate of the percentage of children who were injured during their most recent incident of physical abuse. METHODS: Pooled data from three cross-sectional national telephone survey samples (N=13,052 children) included in the National Survey of Children's Exposure to Violence completed in 2008, 2011, and 2014 were used. RESULTS: Analyses completed in 2016 indicate that 8.4% of children experienced physical abuse by a caregiver. Among those with injury data, 42.6% were injured in the most recent incident. No differences in injury were observed by sex, age, race/ethnicity, or disability status. Victims living with two parents were less likely to be injured (27.1%) than those living in other family structures (53.8%-59%, p<0.001). Incidents involving an object were more likely to result in injury (59.3% vs 38.5%, p<0.05). Injured victims were significantly more likely to experience substantial fear (57.3%) than other victims (34.4%, p<0.001). CONCLUSIONS: A substantial percentage of physical abuse victims are physically hurt to the point that they still feel pain the next day, are bruised, cut, or have a broken bone. Self-report data indicate this is a more common problem than official data sources suggest. The lack of an object in an incident of physical abuse does not protect a child from injury. The results underscore the impact of childhood physical abuse and the importance of early prevention activities.

Endothelial progenitor cell number is not decreased in 34 children with Juvenile Dermatomyositis: a pilot study.

OBJECTIVE: A pilot study to determine endothelial progenitor cells (EPC) number in children with Juvenile Dermatomyositis (JDM). METHODS: After obtaining informed consent, the EPC number from 34 fasting children with definite/probable JDM at various stages of therapy-initially untreated, active disease on medication and clinically inactive, off medication-was compared with 13 healthy fasting pediatric controls. The EPC number was determined by fluorescence activated cell sorting (FACS), CD34+/VEGFR2+/CD45dim-, and assessed in conjunction with clinical variables: disease activity scores (DAS), duration of untreated disease (DUD), TNF-α allelic polymorphism (A/G) at the promoter region of -308, number of nailfold capillary end row loop (ERL) and von Willebrand factor antigen (vWF:Ag). Correlations of the EPC numbers with the clinical and demographic variables, including DAS Skin (DAS SK), DAS Weakness (DAS WK), DAS Total Score, DUD, Cholesterol, triglycerides, High-Density Lipoprotein (HDL) and Low-Density Lipoprotein (LDL), and ERL were calculated using the Pearson correlation coefficient. Tests of associations of EPC with gender (boy vs girl), TNF-α-308A allele (GA/AA vs GG), vWF:Ag (categorized by specific ABO type) as normal/abnormal were performed, using two-sample T- tests. RESULTS: The EPC number for JDM was not significantly different from the healthy controls and was not associated with any of the clinical or cardiovascular risk factors tested. CONCLUSION: The EPC for JDM were in the normal range, similar to adults with DM. These data support the concept that the normal EPC numbers in DM/JDM, irrespective of age, differs from adult PM, where they are decreased, perhaps reflecting a different pathophysiology.