Mental Telehealth Utilization Patterns Among High School Students from Racial and Ethnic Minority Backgrounds Affected by Violence and Substance Use.

BACKGROUND: Recent data show high school students from racial and ethnic minority (REM) backgrounds in the United States confront a twofold challenge, marked by the highest rates of firearm-related homicides since 1994 and increased youth substance use. The pandemic increased online and telehealth usage opportunities for at-risk REM youth. Therefore, this study investigated (1) the frequency and prevalence of co-occurring youth violence and substance use among REM adolescents, (2) racial/ethnic, age, and natal sex (as gender data was not collected) differences in patterns and trends in co-occurring youth violence and substance use among REM adolescents, and (3) the relationship between these syndemic issues and REM adolescent mental telehealth use during the pandemic. METHODS: Data was sourced from a nationally representative sample of U.S. 9th-12th students (n = 3241) who completed the CDC's 2021 Adolescent and Behavioral Experiences Survey (ABES). Using univariate (frequency distribution), bivariate (Pearson's chi-squared test), and multivariate logistic regression models, we examined seven violence victimization outcomes, four violence perpetration outcomes, two family violence outcomes, and six substance use outcomes and their associations with telehealth use for mental health (dependent variable) among REM adolescents. RESULTS: This sample was primarily female (50.7%), Black or African American (48.3%), Hispanic or Latinx (20.6%), and identified as straight or heterosexual (69.5%). The study found significant sex-based differences in violence perpetration/victimization, substance use, and telehealth use for mental health. In general, mental telehealth use was significantly associated with substance use among REM adolescents (cigarette smoking, vaping, alcohol, marijuana, prescription meds, and illicit drug use) (p-value = .001). Mental telehealth use was also significantly associated with all peer and family violence outcomes (p < 0.001). Controlling for covariates, gun carrying was associated with 4.8 times higher odds of using mental telehealth. Students in a physical fight or carrying a weapon (gun, knife, or club) on school property had 2.45 times and 8.09 times the odds of utilizing mental telehealth. Bullied students were 2.5 times more likely to use mental telehealth (p-value < 0.05). Illicit drug use (cocaine, heroin, methamphetamines, and ecstasy) was associated with a higher likelihood of mental telehealth use (AOR = 1.3, p-value = .05). CONCLUSION: Our results suggest crucial insights for shaping violence and substance use prevention strategies, with implications for the future of online and telehealth behavioral services. Mental telehealth help-seeking emerges as a crucial avenue for supporting adolescents affected by violence and substance use, especially when they face obstacles to accessing traditional services. It can work in tandem with in-person services to address these challenges.

Performance of International Classification of Disease-10 codes in detecting emergency department patients with opioid misuse.

BACKGROUND AND AIMS: Accurate case discovery is critical for disease surveillance, resource allocation and research. International Classification of Disease (ICD) diagnosis codes are commonly used for this purpose. We aimed to determine the sensitivity, specificity and positive predictive value (PPV) of ICD-10 codes for opioid misuse case discovery in the emergency department (ED) setting. DESIGN AND SETTING: Retrospective cohort study of ED encounters from January 2018 to December 2020 at an urban academic hospital in the United States. A sample of ED encounters enriched for opioid misuse was developed by oversampling ED encounters with positive urine opiate screens or pre-existing opioid-related diagnosis codes in addition to other opioid misuse risk factors. CASES: A total of 1200 randomly selected encounters were annotated by research staff for the presence of opioid misuse within health record documentation using a 5-point scale for likelihood of opioid misuse and dichotomized into cohorts of opioid misuse and no opioid misuse. MEASUREMENTS: Using manual annotation as ground truth, the sensitivity and specificity of ICD-10 codes entered during the encounter were determined with PPV adjusted for oversampled data. Metrics were also determined by disposition subgroup: discharged home or admitted. FINDINGS: There were 541 encounters annotated as opioid misuse and 617 with no opioid misuse. The majority were males (54.4%), average age was 47 years and 68.5% were discharged directly from the ED. The sensitivity of ICD-10 codes was 0.56 (95% confidence interval [CI], 0.51-0.60), specificity 0.99 (95% CI, 0.97-0.99) and adjusted PPV 0.78 (95% CI, 0.65-0.92). The sensitivity was higher for patients discharged from the ED (0.65; 95% CI, 0.60-0.69) than those admitted (0.31; 95% CI, 0.24-0.39). CONCLUSIONS: International Classification of Disease-10 codes appear to have low sensitivity but high specificity and positive predictive value in detecting opioid misuse among emergency department patients in the United States.

Editorial: Pandemics Interact With and Amplify Child Mental Health Disparities: Further Lessons From COVID-19.

Infectious diseases change our world. It is a simple understanding that history has consistently shown but it is a set of lessons that are routinely forgotten. From cholera1 to smallpox,2 pandemics amplify and run along societal fractures that form in the context of disparities. As of early September 2023, COVID-19 had caused nearly 7 million deaths worldwide, and there have been over 1.1 million deaths in the United States.3 The scale of this impact on children and families is only beginning to become clear.

Barriers and Facilitators to Ophthalmology Visit Adherence in an Urban Hospital Setting.

Purpose: To explore barriers and facilitators to completing scheduled outpatient appointments at an urban academic hospital-based ophthalmology department. Methods: Potential participants were stratified by neighborhood Social Vulnerability Index (SVI) (range, 0-1.0, higher scores indicate greater vulnerability), and semistructured interviews were conducted with individuals 18 years and older with an SVI of greater than 0.61 (n = 17) and providers delivering care in the General Eye Clinic of the University of Illinois Chicago (n = 8). Qualitative analysis informed by human-centered design methods was conducted to classify barriers and facilitators into three domains of the Consolidated Framework for Implementation Research: outer setting, inner setting, and characteristics of individuals. Results: There were four main themes-transportation, time burden, social support, and economic situation-all of which were within the outer setting of the Consolidated Framework for Implementation Research; transportation was most salient. Although providers perceived health literacy as a barrier affecting motivation, patients expressed a high motivation to attend visits and felt well-educated about their condition. Conclusions: A lack of resources outside of the health system presents significant barriers for patients from neighborhoods with high SVI. Future efforts to improve adherence should focus on resource-related interventions in the outer setting. Improving access to eye care will require community-level interventions, particularly transportation. Translational Relevance: Understanding the barriers and facilitators within the Consolidated Framework for Implementation Research provides useful guidance for future interventions, specifically to focus future efforts to improve adherence on resource-related interventions.

"The library is so much more than books": considerations for the design and implementation of teen digital mental health services in public libraries.

Background: Adolescence is a vulnerable developmental period, characterized by high rates of mental health concerns, yet few adolescents receive treatment. Public libraries support adolescents by providing them with access to teen programming, technological resources, and have recently been providing mental health services. Digital mental health (DMH) services may help libraries provide scalable mental health solutions for their adolescent patrons and could be well positioned to address the mental health needs of historically underrepresented racial and ethnic (HURE) adolescents; however, little research has been conducted on the compatibility of DMH services with adolescent patron mental health needs or resource needs of library workers supporting them. Methods: The research team formed a partnership with a public library, which serves a large HURE adolescent population. We conducted needs assessment and implementation readiness interviews with 17 library workers, including leadership, librarians, and workers with specialized areas of practice. Interview questions focused on library infrastructure, as well as library needs and preferences around the design and implementation of DMH services for adolescents. We used the Consolidated Framework for Implementation Research as guiding implementation determinant framework to code and analyze the interview transcripts. Results: Our findings revealed library workers play an important role in guiding patrons to desired resources and share a goal of implementing adolescent DMH resources into the library and elevating marginalized adolescents' voices. Existing library resources, such as the library's role as a safe space for adolescents in the community, close relationships with external and community organizations, and availability of no-cost technological resources, could help facilitate the implementation of DMH services. Barriers related to community buy-in, mental health stigma, and library worker confidence in supporting adolescent mental health could affect service implementation. Conclusions: Our findings suggest public libraries are highly promising settings to deploy DMH services for adolescents. We identified important determinants that may impact the implementation of DMH services in public library settings. Special considerations are needed to design services to meet the mental health needs of HURE adolescent populations and those adolescents' most experiencing health inequities.

Biopsychosocial Model of Traumatic Stress Symptoms in Women Experiencing Homelessness: A Qualitative Descriptive Study.

Trauma is nearly ubiquitous among women experiencing homelessness (WEH). WEH develop post-traumatic stress disorder (PTSD) at rates far exceeding the general population. The consequences of untreated PTSD can cascade, exacerbating existing physical, mental, and social health inequities, placing this population at risk for disproportionate biopsychosocial health adversity. Despite the outsized impact of PTSD, WEH are less likely to access or receive appropriate trauma-focused services. Understanding the unique and intersecting factors that contribute to the disproportionate PTSD toll on WEH may elucidate risk and protective factors, as well as possible intervention pathways to address the disparate trauma burden. This study employed a qualitative descriptive approach to develop understanding of the determinants of trauma risk, exposure, and outcomes among WEH. Semi-structured interviews were completed with 10 WEH, six shelter staff, four mental health professionals. Six deductively biopsychosocial model-derived themes were identified, alongside supporting categories. Themes/categories highlighted the role of biological, psychological, and socio-environmental determinants in shaping risk for and actualization of traumatic events and adverse outcomes. Trauma played an outsized role in shaping the health of WEH participants in this study, and the need for and interest in tailored trauma screening, treatment, psychoeducation options was highlighted. Recursive relationships between biopsychosocial determinants and trauma impact were identified. Participants emphasized population tailored trauma-focused interventions, specifically brief co-designed and community partner implemented interventions that address substance use behaviors, while leveraging the strengths of WEH. Addressing the marked trauma burden in WEH shows promise in promoting measurable biopsychosocial health improvements in this resilient yet overlooked population.

An Implementation of a Community-Engaged, Group-Level Mental Health Pilot for Black and Latina Transgender Women.

The primary aim is to assess the implementation of an eight-session, group therapy pilot for Black and Latina transgender women in Chicago in terms of implementation outcomes regarding intervention effectiveness, acceptability, appropriateness, and feasibility. The Exploration Preparation Implementation Sustainment (EPIS) framework guided implementation processes, including community engagement as an implementation strategy, and an implementation taxonomy was used to evaluate outcomes of acceptability, appropriateness, and feasibility, in addition to intervention effectiveness regarding anxiety and community connectedness. Two rounds of the pilot were completed in 2020, during the COVID-19 pandemic, at a community-based organization serving LGBTQ+ (lesbian, gay, bisexual, transgender, queer/questioning) youth on Chicago's West Side. Participants (N = 14) completed a baseline and postintervention assessment and evaluations after each of eight intervention modules. Descriptive statistics show improvement across measures of anxiety and community connectedness, and high mean scores across domains of acceptability, appropriateness, and feasibility. Pilot findings indicate intervention effectiveness, acceptability, appropriateness, and feasibility to address mental health and social support of Black and Latina transgender women. Additional resources are needed for transgender community-engaged mental health programs and research to establish core and adaptable intervention elements, scaled-up evidence for clinical effectiveness, and, most importantly, to improve mental health outcomes and the sustainability of such interventions.

A Technology-Enhanced Intervention for Violence and Substance Use Prevention Among Young Black Men: Protocol for Adaptation and Pilot Testing.

BACKGROUND: Black boys and men from disinvested communities are disproportionately survivors and perpetrators of youth violence. Those presenting to emergency departments with firearm-related injuries also report recent substance use. However, young Black men face several critical individual and systemic barriers to accessing trauma-focused prevention programs. These barriers contribute to service avoidance, the exacerbation of violence recidivism, substance use relapse, and a revolving-door approach to prevention. In addition, young Black men are known to be digital natives. Therefore, technology-enhanced interventions offer a pragmatic and promising opportunity to mitigate these barriers, provide vital life skills for self-led behavior change, and boost service engagement with vital community resources. OBJECTIVE: The study aims to systematically adapt and pilot-test Boosting Violence-Related Outcomes Using Technology for Empowerment, Risk Reduction, and Life Skills Preparation in Youth Based on Acceptance and Commitment Therapy (BrotherlyACT), a culturally congruent, trauma-focused digital psychoeducational and service-engagement tool tailored to young Black men aged 15-24 years. BrotherlyACT will incorporate microlearning modules, interactive safety planning tools for risk assessment, goal-setting, mindfulness practice, and a service-engagement conversational agent or chatbot to connect young Black men to relevant services. METHODS: The development of BrotherlyACT will occur in 3 phases. In phase 1, we will qualitatively investigate barriers and facilitators influencing young Black men's willingness to use violence and substance use prevention services with 15-30 young Black men (aged 15-24 years) who report perpetrating violence and substance use in the past year and 10 service providers (aged >18 years; any gender; including health care providers, street outreach workers, social workers, violence interrupters, community advocates, and school staff). Both groups will be recruited from community and pediatric emergency settings. In phase 2, a steering group of topic experts (n=3-5) and a youth and community advisory board comprising young Black men (n=8-12) and service providers (n=5-10) will be involved in participatory design, alpha testing, and beta testing sessions to develop, refine, and adapt BrotherlyACT based on an existing skills-based program (Achieving Change Through Values-Based Behavior). We will use user-centered design principles and the Assessment, Decision, Administration, Production, Topical, Experts, Integration, Training, and Testing framework to guide this adaptation process (phase 2). In phase 3, a total of 60 young Black men will pilot-test the adapted BrotherlyACT over 10 weeks in a single-group, pretest-posttest design to determine its feasibility and implementation outcomes. RESULTS: Phase 1 data collection began in September 2021. Phases 2 and 3 are scheduled to start in June 2023 and end in September 2024. CONCLUSIONS: The development and testing of BrotherlyACT is a crucial first step in expanding an evidence-based psychoeducational and service-mediating intervention for young Black men involved in violence. This colocation of services shifts the current prevention strategy from telling them why to change to teaching them how. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/43842.

Geolocation Patterns, Wi-Fi Connectivity Rates, and Psychiatric Symptoms Among Urban Homeless Youth: Mixed Methods Study Using Self-report and Smartphone Data.

BACKGROUND: Despite significant research done on youth experiencing homelessness, few studies have examined movement patterns and digital habits in this population. Examining these digital behaviors may provide useful data to design new digital health intervention models for youth experiencing homelessness. Specifically, passive data collection (data collected without extra steps for a user) may provide insights into lived experience and user needs without putting an additional burden on youth experiencing homelessness to inform digital health intervention design. OBJECTIVE: The objective of this study was to explore patterns of mobile phone Wi-Fi usage and GPS location movement among youth experiencing homelessness. Additionally, we further examined the relationship between usage and location as correlated with depression and posttraumatic stress disorder (PTSD) symptoms. METHODS: A total of 35 adolescent and young adult participants were recruited from the general community of youth experiencing homelessness for a mobile intervention study that included installing a sensor data acquisition app (Purple Robot) for up to 6 months. Of these participants, 19 had sufficient passive data to conduct analyses. At baseline, participants completed self-reported measures for depression (Patient Health Questionnaire-9 [PHQ-9]) and PTSD (PTSD Checklist for DSM-5 [PCL-5]). Behavioral features were developed and extracted from phone location and usage data. RESULTS: Almost all participants (18/19, 95%) used private networks for most of their noncellular connectivity. Greater Wi-Fi usage was associated with a higher PCL-5 score (P=.006). Greater location entropy, representing the amount of variability in time spent across identified clusters, was also associated with higher severity in both PCL-5 (P=.007) and PHQ-9 (P=.045) scores. CONCLUSIONS: Location and Wi-Fi usage both demonstrated associations with PTSD symptoms, while only location was associated with depression symptom severity. While further research needs to be conducted to establish the consistency of these findings, they suggest that the digital patterns of youth experiencing homelessness offer insights that could be used to tailor digital interventions.

Building a statewide network of MOUD expertise using tiered ECHO® mentoring opportunities.

BACKGROUND: Expanding access to workforce training for opioid use disorder (OUD) treatment continues to be a priority. This study explored the use of tiered mentoring opportunities within an ECHO® model to expand treatment capacity and develop a statewide network of medications for OUD (MOUD) expertise. ECHO® engages participants in a virtual community to learn best practices through case-based learning and interactions with experts. METHODS: We studied two incentivized Illinois MOUD ECHO® training programs by examining aggregate demographic and prescribing data across eight training cohorts (n = 199 participants). Participants (n = 51) in the last two cohorts were evaluated with expanded pre- and post-training surveys. Qualitative interviews were completed with a subset (n = 13) to examine effects observed in the survey data. RESULTS: For the whole group, we found a geographic expansion of the participants' prescribing capacity that reached into rural and other underserved areas in Illinois. Participants in the last two cohorts reported both increased self-efficacy for OUD treatment and increased connectedness to the addiction treatment community in Illinois. Participants who progressed through the tiered mentorship roles were found to exhibit stepwise increases in reported self-efficacy and connectedness measures. CONCLUSION: An incentivized ECHO® program yielded substantive outcomes in terms of increased prescribing capacity across the state. The use of tiered mentoring opportunities enabled participants to develop MOUD expertise and support novice providers in a growing statewide network. There is potential to train professionals to a high level of expertise when the ECHO® model is combined with a mentorship pathway.

Findings From the Step Up, Test Up Study of an Electronic Screening and Brief Intervention for Alcohol Misuse in Adolescents and Young Adults Presenting for HIV Testing: Randomized Controlled Efficacy Trial.

BACKGROUND: Substance use, particularly binge drinking of alcohol and noninjection substance use, is associated with increased risk for HIV infection among youth, but structured substance use screening and brief intervention are not often provided as part of HIV risk reduction. OBJECTIVE: The purpose of the study was to test the efficacy of a fully automated electronic screening and brief intervention, called Step Up, Test Up, to reduce alcohol misuse among adolescents and young adults presenting for HIV testing. Secondary objectives were reduction in sexual risk and uptake of pre-exposure prophylaxis (PrEP) for HIV prevention. METHODS: Youth aged 16 years to 25 years who presented for HIV testing at community-based locations were recruited for study participation. Those who screened at moderate to high risk on the Alcohol Use Disorders Identification Test were randomized (1:1) to either an electronic brief intervention or a time-attention control. The primary outcome was change in alcohol use at 1, 3, 6, and 12-month follow-ups. Negative binomial and log binomial regression analyses with generalized estimating equations were conducted to evaluate the intervention efficacy. RESULTS: Among a sample of 329 youth, there were no significant differences in alcohol use outcomes between conditions over time or at the 1, 3, 6, or 12-month time points. In terms of secondary outcomes, there was evidence of reduction in condomless insertive anal sex under the influence of alcohol and drugs at 12 months compared with 3 months in the intervention versus the attention control condition (incidence rate ratio=0.15, 95% CI 0.05-0.44); however, there were no other significant differences in sexual risk and no difference in PrEP engagement. CONCLUSIONS: We found no effect of electronic brief intervention to reduce alcohol use and some effect on sexual risk among youth aged 16 years to 25 years who present for HIV testing. TRIAL REGISTRATION: ClinicalTrials.gov number NCT02703116; https://clinicaltrials.gov/ct2/show/NCT02703116. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s12889-020-8154-6.

A Scoping Review of Associations Between Cannabis Use and Anxiety in Adolescents and Young Adults.

Cannabis and anxiety are both rising issues that impact young people. This review seeks to explore the association between anxiety and cannabis in adolescents and young adults (AYA). A database search was run retrospectively from July 2020 through calendar year 2013. Articles had to present outcomes examining cannabis use and symptoms of anxiety, be written in English, contain samples with ≥ 50% who are age 25 or younger, and be published in a peer-reviewed journal. Forty-seven studies were identified that examined the relationship between anxiety and cannabis use. Twenty-three studies found a positive association that greater anxiety among AYA was associated with greater cannabis use. In contrast, seven studies found a negative association that greater anxiety was related to less cannabis use. And finally, 17 studies found no clear association between anxiety and cannabis use. Further research is needed to better understand the relationship between anxiety and cannabis use.

Ethical considerations for developing pediatric mhealth interventions for teens with socially complex needs.

TOPIC: Mobile Health (mHealth) stands as a potential means to better reach, assess, and intervene with teens with socially complex needs. These youth often face overlapping adversities including medical illness and a history of experiencing adverse childhood experiences (ACEs). Clinicians are faced with navigating ethical decisions when developing mHealth tools for teens who have socially complex needs. Many tools have been developed for adults from the general population. However, despite the development of thousands of mHealth interventions, developers tend to focus on designing for usability, engagement, and efficacy, with less attention on the ethical considerations of making such tools. PURPOSE: To safely move mHealth interventions from research into clinical practice, ethical standards must be met during the design phase. In this paper we adapt the Four Box Model (i.e., medical indications, preferences of patients, quality of life, and contextual features) to guide mHealth developers through ethical considerations when designing mHealth interventions for teens who present with a medical diagnosis and a history of ACEs. SOURCES: A review of language, inclusive features, data sharing, and usability is presented using both the Four Box Model and potential scenarios to guide each consideration. CONCLUSIONS: To better support designers of mHealth tools we present a framework for evaluating applications to determine overlap with ethical design and are well suited for use in clinical practice with underserved pediatric patients.

Machine Learning Techniques to Explore Clinical Presentations of COVID-19 Severity and to Test the Association With Unhealthy Opioid Use: Retrospective Cross-sectional Cohort Study.

BACKGROUND: The COVID-19 pandemic has exacerbated health inequities in the United States. People with unhealthy opioid use (UOU) may face disproportionate challenges with COVID-19 precautions, and the pandemic has disrupted access to opioids and UOU treatments. UOU impairs the immunological, cardiovascular, pulmonary, renal, and neurological systems and may increase severity of outcomes for COVID-19. OBJECTIVE: We applied machine learning techniques to explore clinical presentations of hospitalized patients with UOU and COVID-19 and to test the association between UOU and COVID-19 disease severity. METHODS: This retrospective, cross-sectional cohort study was conducted based on data from 4110 electronic health record patient encounters at an academic health center in Chicago between January 1, 2020, and December 31, 2020. The inclusion criterion was an unplanned admission of a patient aged ≥18 years; encounters were counted as COVID-19-positive if there was a positive test for COVID-19 or 2 COVID-19 International Classification of Disease, Tenth Revision codes. Using a predefined cutoff with optimal sensitivity and specificity to identify UOU, we ran a machine learning UOU classifier on the data for patients with COVID-19 to estimate the subcohort of patients with UOU. Topic modeling was used to explore and compare the clinical presentations documented for 2 subgroups: encounters with UOU and COVID-19 and those with no UOU and COVID-19. Mixed effects logistic regression accounted for multiple encounters for some patients and tested the association between UOU and COVID-19 outcome severity. Severity was measured with 3 utilization metrics: low-severity unplanned admission, medium-severity unplanned admission and receiving mechanical ventilation, and high-severity unplanned admission with in-hospital death. All models controlled for age, sex, race/ethnicity, insurance status, and BMI. RESULTS: Topic modeling yielded 10 topics per subgroup and highlighted unique comorbidities associated with UOU and COVID-19 (eg, HIV) and no UOU and COVID-19 (eg, diabetes). In the regression analysis, each incremental increase in the classifier's predicted probability of UOU was associated with 1.16 higher odds of COVID-19 outcome severity (odds ratio 1.16, 95% CI 1.04-1.29; P=.009). CONCLUSIONS: Among patients hospitalized with COVID-19, UOU is an independent risk factor associated with greater outcome severity, including in-hospital death. Social determinants of health and opioid-related overdose are unique comorbidities in the clinical presentation of the UOU patient subgroup. Additional research is needed on the role of COVID-19 therapeutics and inpatient management of acute COVID-19 pneumonia for patients with UOU. Further research is needed to test associations between expanded evidence-based harm reduction strategies for UOU and vaccination rates, hospitalizations, and risks for overdose and death among people with UOU and COVID-19. Machine learning techniques may offer more exhaustive means for cohort discovery and a novel mixed methods approach to population health.

mHealth Uses and Opportunities for Teens from Communities with High Health Disparities: A Mixed-Methods Study.

Despite widespread access to smartphones, teens from communities facing significant behavioral health disparities typically have low mobile health (mHealth) engagement. The purpose of this study was to characterize teen and caregiver perspectives about smartphone use and access, mHealth, and how mHealth could address teens' behavioral health needs during the pandemic and beyond. Remote recruitment and methodologies were used to engage 17 teens (M age = 15.9 ± 0.9) and 10 caregivers living in urban communities with significant socioeconomic and health disparities. Participants completed a focus group or interview session (based on preference) and self-report questionnaires (e.g., behavioral health history, pandemic impacts, technology use). Qualitative and quantitative data were analyzed using thematic and descriptive analyses, respectively. Both quantitative and qualitative data indicated relevant behavioral health concerns for teens and their families, impacts from the pandemic, and frequent smartphone use. Primary teen and caregiver themes included (1) health and wellness concerns, (2) barriers, (3) use of smartphones, (4) impacts of smartphones, and (5) opinions/suggestions for mHealth. This multi-method and multi-informant study highlighted the lived experiences of teens from marginalized communities and offered key insights to increase the acceptability and real-world engagement of mHealth tools. To address barriers to care for this population beyond the pandemic, clear messaging must be used for mHealth tools (e.g., data privacy, expectations of use). These findings testify to the importance of collaboration with teens and caregivers from communities facing large health disparities in future mHealth design, development, and deployment.

The Identification of Subphenotypes and Associations with Health Outcomes in Patients with Opioid-Related Emergency Department Encounters Using Latent Class Analysis.

The emergency department (ED) is a critical setting for the treatment of patients with opioid misuse. Detecting relevant clinical profiles allows for tailored treatment approaches. We sought to identify and characterize subphenotypes of ED patients with opioid-related encounters. A latent class analysis was conducted using 14,057,302 opioid-related encounters from 2016 through 2017 using the National Emergency Department Sample (NEDS), the largest all-payer ED database in the United States. The optimal model was determined by face validity and information criteria-based metrics. A three-step approach assessed class structure, assigned individuals to classes, and examined characteristics between classes. Class associations were determined for hospitalization, in-hospital death, and ED charges. The final five-class model consisted of the following subphenotypes: Chronic pain (class 1); Alcohol use (class 2); Depression and pain (class 3); Psychosis, liver disease, and polysubstance use (class 4); and Pregnancy (class 5). Using class 1 as the reference, the greatest odds for hospitalization occurred in classes 3 and 4 (Ors 5.24 and 5.33, p < 0.001) and for in-hospital death in class 4 (OR 3.44, p < 0.001). Median ED charges ranged from USD 2177 (class 1) to USD 2881 (class 4). These subphenotypes provide a basis for examining patient-tailored approaches for this patient population.

Development and multimodal validation of a substance misuse algorithm for referral to treatment using artificial intelligence (SMART-AI): a retrospective deep learning study.

BACKGROUND: Substance misuse is a heterogeneous and complex set of behavioural conditions that are highly prevalent in hospital settings and frequently co-occur. Few hospital-wide solutions exist to comprehensively and reliably identify these conditions to prioritise care and guide treatment. The aim of this study was to apply natural language processing (NLP) to clinical notes collected in the electronic health record (EHR) to accurately screen for substance misuse. METHODS: The model was trained and developed on a reference dataset derived from a hospital-wide programme at Rush University Medical Center (RUMC), Chicago, IL, USA, that used structured diagnostic interviews to manually screen admitted patients over 27 months (between Oct 1, 2017, and Dec 31, 2019; n=54 915). The Alcohol Use Disorder Identification Test and Drug Abuse Screening Tool served as reference standards. The first 24 h of notes in the EHR were mapped to standardised medical vocabulary and fed into single-label, multilabel, and multilabel with auxillary-task neural network models. Temporal validation of the model was done using data from the subsequent 12 months on a subset of RUMC patients (n=16 917). External validation was done using data from Loyola University Medical Center, Chicago, IL, USA between Jan 1, 2007, and Sept 30, 2017 (n=1991 adult patients). The primary outcome was discrimination for alcohol misuse, opioid misuse, or non-opioid drug misuse. Discrimination was assessed by the area under the receiver operating characteristic curve (AUROC). Calibration slope and intercept were measured with the unreliability index. Bias assessments were performed across demographic subgroups. FINDINGS: The model was trained on a cohort that had 3·5% misuse (n=1 921) with any type of substance. 220 (11%) of 1921 patients with substance misuse had more than one type of misuse. The multilabel convolutional neural network classifier had a mean AUROC of 0·97 (95% CI 0·96-0·98) during temporal validation for all types of substance misuse. The model was well calibrated and showed good face validity with model features containing explicit mentions of aberrant drug-taking behaviour. A false-negative rate of 0·18-0·19 and a false-positive rate of 0·03 between non-Hispanic Black and non-Hispanic White groups occurred. In external validation, the AUROCs for alcohol and opioid misuse were 0·88 (95% CI 0·86-0·90) and 0·94 (0·92-0·95), respectively. INTERPRETATION: We developed a novel and accurate approach to leveraging the first 24 h of EHR notes for screening multiple types of substance misuse. FUNDING: National Institute On Drug Abuse, National Institutes of Health.

Rates and correlates of well-being among youth experiencing homelessness.

Mental health concerns have been well studied among youth experiencing homelessness, yet few studies have explored factors that contribute to well-being in this population. The current cross-sectional study examined rates and correlates of well-being among youth experiencing homelessness. This is a descriptive, secondary analysis of the baseline data from a clinical intervention study. Ninety-nine youth (aged 16-25) who were experiencing homelessness were recruited in Chicago. Approximately 40% of the sample reported average or above average well-being relative to existing benchmarks. Having medical insurance, a mobile phone, and a history of more severe childhood trauma were unique cross-sectional predictors of worse well-being (all ps < 0.034). A significant portion of our sample experienced well-being. Having access to certain resources may be counterintuitive indicators of poorer well-being among youth experiencing homelessness, perhaps because they are indicators of greater need or increased social comparison among these youth.

The opioid use disorder core outcomes set (OUD-COS) for treatment research: findings from a Delphi consensus study.

BACKGROUND AND AIM: There is no gold-standard and considerable heterogeneity in outcome measures used to evaluate treatments for opioid use disorder (OUD) along the opioid treatment cascade. The aim of this study was to develop the US National Institute on Drug Abuse (NIDA) National Drug Abuse Treatment Clinical Trials Network (CTN) opioid use disorder core outcomes set (OUD-COS). DESIGN: Four-round, e-Delphi expert panel consensus study and plenary research group discussion and targeted consultation. SETTING: United States. PARTICIPANTS: A panel of 25 members including clinical practitioners, clinical researchers and administrative staff from the CTN, the network's affiliated clinical and community sites and the NIDA Centre for the CTN. MEASUREMENTS: From a pool of 24 candidate items in four domains (biomedical/disease status; behaviors, symptoms and functioning; opioid treatment cascade; and morbidity and mortality), the panel completed an on-line questionnaire to rank items with defined specification on a 9-point scale for importance, with a standard 70% consensus criterion. FINDINGS: After the fourth round of the questionnaire and subsequent discussion, consensus was reached for five outcomes: two patient-reported (global impression of improvement and incident non-fatal overdose); one clinician-reported (illicit/non-medical drug toxicology); and two from administrative records (duration of treatment and fatal opioid poisoning). CONCLUSIONS: An e-Delphi consensus study has produced the US National Institute on Drug Abuse (NIDA) National Drug Abuse Treatment Clinical Trials Network opioid use disorder core outcomes set (version 1) for opioid use disorder treatment efficacy and effectiveness research.