Key language markers of depression on social media depend on race

Depression has robust natural language correlates and can increasingly be measured in language using predictive models. However, despite evidence that language use varies as a function of individual demographic features (e.g., age, gender), previous work has not systematically examined whether and how depression's association with language varies by race. We examine how race moderates the relationship between language features (i.e., first-person pronouns and negative emotions) from social media posts and self-reported depression, in a matched sample of Black and White English speakers in the United States. Our findings reveal moderating effects of race: While depression severity predicts I-usage in White individuals, it does not in Black individuals. White individuals use more belongingness and self-deprecation-related negative emotions. Machine learning models trained on similar amounts of data to predict depression severity performed poorly when tested on Black individuals, even when they were trained exclusively using the language of Black individuals. In contrast, analogous models tested on White individuals performed relatively well. Our study reveals surprising race-based differences in the expression of depression in natural language and highlights the need to understand these effects better, especially before language-based models for detecting psychological phenomena are integrated into clinical practice.

A linguistic analysis of dehumanization toward substance use across three decades of news articles

Introduction

Substances and the people who use them have been dehumanized for decades. As a result, lawmakers and healthcare providers have implemented policies that subjected millions to criminalization, incarceration, and inadequate resources to support health and wellbeing. While there have been recent shifts in public opinion on issues such as legalization, in the case of marijuana in the U.S., or addiction as a disease, dehumanization and stigma are still leading barriers for individuals seeking treatment. Integral to the narrative of "substance users" as thoughtless zombies or violent criminals is their portrayal in popular media, such as films and news.

Methods

This study attempts to quantify the dehumanization of people who use substances (PWUS) across time using a large corpus of over 3 million news articles. We apply a computational linguistic framework for measuring dehumanization across three decades of New York Times articles.

Results

We show that (1) levels of dehumanization remain high and (2) while marijuana has become less dehumanized over time, attitudes toward other substances such as heroin and cocaine remain stable.

Discussion

This work highlights the importance of a holistic view of substance use that places all substances within the context of addiction as a disease, prioritizes the humanization of PWUS, and centers around harm reduction.

Relationship between self-stigma about alcohol dependence and severity of alcohol drinking and craving

BACKGROUND

The correlates and consequences of stigma surrounding alcohol use are complex. Alcohol use disorder (AUD) is typically accompanied by self-stigma, due to numerous factors, such as shame, guilt and negative stereotypes. Few studies have empirically examined the possible association between self-stigma and alcohol-related outcomes.

OBJECTIVE

To investigate the relationship between self-stigma about alcohol dependence and the severity of alcohol consumption and craving.

METHODS

In a sample of 64 participants, the majority of whom had a diagnosis of AUD (51), bivariate correlations were first conducted between Self-Stigma and Alcohol Dependence Scale (SSAD-Apply subscale) scores and Alcohol Use Disorders Identification Test (AUDIT) scores, Alcohol Timeline Follow-Back, Obsessive-Compulsive Drinking Scale (OCDS) scores and Penn Alcohol Cravings Scale scores. Based on the results, regression analyses were conducted with SSAD scores as the predictor and AUDIT and OCDS scores as the outcomes.

FINDINGS

SSAD scores positively correlated with AUDIT scores, average drinks per drinking day, number of heavy drinking days and OCDS scores (p<0.001, p=0.014, p=0.011 and p<0.001, respectively). SSAD scores were also found to be a significant predictor of AUDIT and OCDS scores (p<0.001 and p<0.001, respectively), even after controlling for demographics.

CONCLUSIONS

Higher levels of self-stigma were associated with more severe AUD, greater alcohol consumption, and more obsessive thoughts and compulsive behaviours related to alcohol.

CLINICAL IMPLICATIONS

Our results suggest that potential interventions to reduce self-stigma may lead to improved quality of life and treatment outcomes for individuals with AUD.

AI-based analysis of social media language predicts addiction treatment dropout at 90 days

The reoccurrence of use (relapse) and treatment dropout is frequently observed in substance use disorder (SUD) treatment. In the current paper, we evaluated the predictive capability of an AI-based digital phenotype using the social media language of patients receiving treatment for substance use disorders (N = 269). We found that language phenotypes outperformed a standard intake psychometric assessment scale when predicting patients' 90-day treatment outcomes. We also use a modern deep learning-based AI model, Bidirectional Encoder Representations from Transformers (BERT) to generate risk scores using pre-treatment digital phenotype and intake clinic data to predict dropout probabilities. Nearly all individuals labeled as low-risk remained in treatment while those identified as high-risk dropped out (risk score for dropout AUC = 0.81; p < 0.001). The current study suggests the possibility of utilizing social media digital phenotypes as a new tool for intake risk assessment to identify individuals most at risk of treatment dropout and relapse.

Extended impact of the COVID-19 pandemic: Trajectories of mental health and substance use among U.S. adults, September 2020-August 2021

Background

Americans reported significant increases in mental health and substance use problems after the COVID-19 pandemic outbreak. This can be a product of the pandemic disruptions in everyday life, with some populations being more impacted than others.

Objectives

To assess the ongoing impact of the COVID-19 pandemic on mental health and substance use in U.S. adults from September 2020 to August 2021.

Methods

Participants included 1056 adults (68.5% women) who participated in a national longitudinal online survey assessing the perceived impact of COVID-19 on daily life, stress, depression and anxiety symptoms, and alcohol and cannabis use at 3-time points from September 2020 to August 2021.

Results

Individuals with lower self-reported social status reported the highest perceived impact. Participants' perceived impact of the COVID-19 pandemic on daily life, stress, anxiety, and alcohol use risk significantly decreased over time but remained high. However, there was no change in depressive symptoms and cannabis use. Higher levels of perceived impact of the pandemic significantly predicted both more baseline mental health concerns and lower decreases over time. Lower self-report social status predicted more baseline mental health concerns and smaller decreases in those concerns. Black adults reported significantly higher cannabis use rates than non-Hispanic White adults.

Conclusion

The impact of COVID-19 on daily life continued to be a risk factor for mental health during the second wave of the pandemic. In addition to infection prevention, public health policies should focus on pandemic-related social factors such as economic concerns and caretaking that continue to affect mental health.

Effect of Integrating Patient-Generated Digital Data Into Mental Health Therapy: A Randomized Controlled Trial

OBJECTIVE

The authors sought to determine whether providing summaries of patients' social media and other digital data to patients and their clinicians improves patients' health-related quality of life (HRQoL) measured by the RAND 36-Item Short Form Health Survey (SF-36).

METHODS

The authors randomly assigned 115 adults receiving outpatient mental health therapy to usual care or to periodic sharing of summaries of their digital data with their clinician providing psychosocial therapy. The study was conducted October 2020-December 2021.

RESULTS

Patients' mean±SD age was 31.3±10.5 years, and 82% were women. At 60 days after enrollment, no statistically significant change was detected in SF-36 scores for patients randomly allocated to the intervention (mean difference=-0.39, 95% CI=-4.17, 3.39) or to usual care (mean difference=-1.98, 95% CI=-5.74, 1.77), and no significant between-arm difference was observed (between-arm difference=1.60, 95% CI=-3.67, 6.86).

CONCLUSIONS

Collecting and summarizing digital data for use in mental health treatment was feasible for patients but did not significantly improve their HRQoL or other measures of mental health.

Differences in mental health and alcohol use across profiles of COVID-19 disruptions

This study aimed to examine differences in mental health and alcohol use outcomes across distinct patterns of work, home, and social life disruptions associated with the COVID-19 pandemic. Data from 2093 adult participants were collected from September 2020 to April 2021 as a part of a larger study examining the impacts of the COVID-19 pandemic on substance use. Participants provided data on COVID-19 pandemic experiences, mental health outcomes, media consumption, and alcohol use at baseline. Alcohol use difficulties, including problems related to the use, desire to use alcohol, failure to cut down on alcohol use, and family/friend concern with alcohol use, were measured at 60-day follow-up. Factor mixture modeling followed by group comparisons, multiple linear regressions, and multiple logistic regressions was conducted. A four-profile model was selected. Results indicated that profile membership predicted differences in mental health and alcohol use outcomes above and beyond demographics. Individuals experiencing the most disruption reported the strongest daily impact of COVID-19 and significantly high levels of depression, anxiety, loneliness, overwhelm, alcohol use at baseline, and alcohol use difficulties measured at 60-day follow-up. The findings highlight the need for integrated mental health and/or alcohol services and social services targeting work, home, and social life during public health emergencies in order to respond effectively and comprehensively to the needs of those requiring different types of support.

Role of the media in promoting the dehumanization of people who use drugs

Dehumanization, the perception or treatment of people as subhuman, has been recognized as "endemic" in medicine and contributes to the stigmatization of people who use illegal drugs, in particular. As a result of dehumanization, people who use drugs are subject to systematically biased policies, long-lasting stigma, and suboptimal healthcare. One major contributor to the public opinion of drugs and people who use them is the media, whose coverage of these topics consistently uses negative imagery and language. This narrative review of the literature and American media on the dehumanization of illegal drugs and the people who use them provides a perspective on the components of dehumanization in each case and explores the consequences of dehumanization on health, law, and society. Drawing from language and images from American news outlets, anti-drug campaigns, and academic research, we recommend a shift away from the disingenuous trope of people who use drugs as poor, uneducated, and most likely of color. To this end, positive media portrayals and the humanization of people who use drugs can help form a common identity, engender empathy, and ultimately improve health outcomes.

Analyzing text message linguistic features: Do people with depression communicate differently with their close and non-close contacts?

BACKGROUND

Relatively little is known about how communication changes as a function of depression severity and interpersonal closeness. We examined the linguistic features of outgoing text messages among individuals with depression and their close- and non-close contacts.

METHODS

419 participants were included in this 16-week-long observational study. Participants regularly completed the PHQ-8 and rated subjective closeness to their contacts. Text messages were processed to count frequencies of word usage in the LIWC 2015 libraries. A linear mixed modeling approach was used to estimate linguistic feature scores of outgoing text messages.

RESULTS

Regardless of closeness, people with higher PHQ-8 scores tended to use more differentiation words. When texting with close contacts, individuals with higher PHQ-8 scores used more first-person singular, filler, sexual, anger, and negative emotion words. When texting with non-close contacts these participants used more conjunctions, tentative, and sadness-related words and fewer first-person plural words.

CONCLUSION

Word classes used in text messages, when combined with symptom severity and subjective social closeness data, may be indicative of underlying interpersonal processes. These data may hold promise as potential treatment targets to address interpersonal drivers of depression.

Linguistic Methodologies to Surveil the Leading Causes of Mortality: Scoping Review of Twitter for Public Health Data

BACKGROUND

Twitter has become a dominant source of public health data and a widely used method to investigate and understand public health-related issues internationally. By leveraging big data methodologies to mine Twitter for health-related data at the individual and community levels, scientists can use the data as a rapid and less expensive source for both epidemiological surveillance and studies on human behavior. However, limited reviews have focused on novel applications of language analyses that examine human health and behavior and the surveillance of several emerging diseases, chronic conditions, and risky behaviors.

OBJECTIVE

The primary focus of this scoping review was to provide a comprehensive overview of relevant studies that have used Twitter as a data source in public health research to analyze users' tweets to identify and understand physical and mental health conditions and remotely monitor the leading causes of mortality related to emerging disease epidemics, chronic diseases, and risk behaviors.

METHODS

A literature search strategy following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) extended guidelines for scoping reviews was used to search specific keywords on Twitter and public health on 5 databases: Web of Science, PubMed, CINAHL, PsycINFO, and Google Scholar. We reviewed the literature comprising peer-reviewed empirical research articles that included original research published in English-language journals between 2008 and 2021. Key information on Twitter data being leveraged for analyzing user language to study physical and mental health and public health surveillance was extracted.

RESULTS

A total of 38 articles that focused primarily on Twitter as a data source met the inclusion criteria for review. In total, two themes emerged from the literature: (1) language analysis to identify health threats and physical and mental health understandings about people and societies and (2) public health surveillance related to leading causes of mortality, primarily representing 3 categories (ie, respiratory infections, cardiovascular disease, and COVID-19). The findings suggest that Twitter language data can be mined to detect mental health conditions, disease surveillance, and death rates; identify heart-related content; show how health-related information is shared and discussed; and provide access to users' opinions and feelings.

CONCLUSIONS

Twitter analysis shows promise in the field of public health communication and surveillance. It may be essential to use Twitter to supplement more conventional public health surveillance approaches. Twitter can potentially fortify researchers' ability to collect data in a timely way and improve the early identification of potential health threats. Twitter can also help identify subtle signals in language for understanding physical and mental health conditions.

Predicting U.S. county opioid poisoning mortality from multi-modal social media and psychological self-report data

Opioid poisoning mortality is a substantial public health crisis in the United States, with opioids involved in approximately 75% of the nearly 1 million drug related deaths since 1999. Research suggests that the epidemic is driven by both over-prescribing and social and psychological determinants such as economic stability, hopelessness, and isolation. Hindering this research is a lack of measurements of these social and psychological constructs at fine-grained spatial and temporal resolutions. To address this issue, we use a multi-modal data set consisting of natural language from Twitter, psychometric self-reports of depression and well-being, and traditional area-based measures of socio-demographics and health-related risk factors. Unlike previous work using social media data, we do not rely on opioid or substance related keywords to track community poisonings. Instead, we leverage a large, open vocabulary of thousands of words in order to fully characterize communities suffering from opioid poisoning, using a sample of 1.5 billion tweets from 6 million U.S. county mapped Twitter users. Results show that Twitter language predicted opioid poisoning mortality better than factors relating to socio-demographics, access to healthcare, physical pain, and psychological well-being. Additionally, risk factors revealed by the Twitter language analysis included negative emotions, discussions of long work hours, and boredom, whereas protective factors included resilience, travel/leisure, and positive emotions, dovetailing with results from the psychometric self-report data. The results show that natural language from public social media can be used as a surveillance tool for both predicting community opioid poisonings and understanding the dynamic social and psychological nature of the epidemic.

Racial and Ethnic Bias in the Diagnosis of Alcohol Use Disorder in Veterans

OBJECTIVE

Studies show that racially and ethnically minoritized veterans have a higher prevalence of alcohol use disorder (AUD) than White veterans. The investigators examined whether the relationship between self-reported race and ethnicity and AUD diagnosis remains after adjusting for alcohol consumption, and if so, whether it varies by self-reported alcohol consumption.

METHODS

The sample included 700,012 Black, White, and Hispanic veterans enrolled in the Million Veteran Program. Alcohol consumption was defined as an individual's maximum score on the consumption subscale of the Alcohol Use Disorders Identification Test (AUDIT-C), a screen for unhealthy alcohol use. A diagnosis of AUD, the primary outcome, was defined by the presence of relevant ICD-9 or ICD-10 codes in electronic health records. Logistic regression with interactions was used to assess the association between race and ethnicity and AUD as a function of maximum AUDIT-C score.

RESULTS

Black and Hispanic veterans were more likely than White veterans to have an AUD diagnosis despite similar levels of alcohol consumption. The difference was greatest between Black and White men; at all but the lowest and highest levels of alcohol consumption, Black men had 23%-109% greater odds of an AUD diagnosis. The findings were unchanged after adjustment for alcohol consumption, alcohol-related disorders, and other potential confounders.

CONCLUSIONS

The large discrepancy in the prevalence of AUD across groups despite a similar distribution of alcohol consumption levels suggests that there is racial and ethnic bias, with Black and Hispanic veterans more likely than White veterans to receive an AUD diagnosis. Efforts are needed to reduce bias in the diagnostic process to address racialized differences in AUD diagnosis.

Patterns of demoralization and anhedonia during early substance use disorder treatment and associations with treatment attrition

BACKGROUND

Although depressive symptoms represent a promising therapeutic target to promote recovery from substance use disorders (SUD), heterogeneity in their diagnostic presentation often hinders the ability to effectively tailor treatment. We sought to identify subgroups of individuals varying in depressive symptom phenotypes (i.e., demoralization, anhedonia), and examined whether these subgroups were associated with patient demographics, psychosocial health, and treatment attrition.

METHODS

Patients (N = 10,103, 69.2 % male) were drawn from a dataset of individuals who presented for admission to SUD treatment in the US. Participants reported on their demoralization and anhedonia approximately weekly for the first month of treatment, and on their demographics, psychosocial health, and primary substance at intake. Longitudinal latent profile analysis examined patterns of demoralization and anhedonia with treatment attrition as a distal outcome.

RESULTS

Four subgroups of individuals emerged: (1) High demoralization and anhedonia, (2) Remitting demoralization and anhedonia, (3) High demoralization, low anhedonia, and (4) Low demoralization and anhedonia. Relative to the Low demoralization and anhedonia subgroup, all the other profiles were more likely to discontinue treatment. Numerous between-profile differences were observed in demographics, psychosocial health, and primary substance.

LIMITATIONS

The racial and ethnic background of the sample was skewed towards White individuals; future research is needed to determine the generalizability of our findings to minoritized racial and ethnic groups.

CONCLUSIONS

We identified four clinical profiles that varied in the joint course of demoralization and anhedonia. Findings suggest specific subgroups might benefit from additional interventions and treatments that address their unique mental health needs during SUD recovery.

Opioid death projections with AI-based forecasts using social media language

Targeting of location-specific aid for the U.S. opioid epidemic is difficult due to our inability to accurately predict changes in opioid mortality across heterogeneous communities. AI-based language analyses, having recently shown promise in cross-sectional (between-community) well-being assessments, may offer a way to more accurately longitudinally predict community-level overdose mortality. Here, we develop and evaluate, TROP (Transformer for Opiod Prediction), a model for community-specific trend projection that uses community-specific social media language along with past opioid-related mortality data to predict future changes in opioid-related deaths. TOP builds on recent advances in sequence modeling, namely transformer networks, to use changes in yearly language on Twitter and past mortality to project the following year's mortality rates by county. Trained over five years and evaluated over the next two years TROP demonstrated state-of-the-art accuracy in predicting future county-specific opioid trends. A model built using linear auto-regression and traditional socioeconomic data gave 7% error (MAPE) or within 2.93 deaths per 100,000 people on average; our proposed architecture was able to forecast yearly death rates with less than half that error: 3% MAPE and within 1.15 per 100,000 people.

Measuring disadvantage: A systematic comparison of United States small-area disadvantage indices

Extensive evidence demonstrates the effects of area-based disadvantage on a variety of life outcomes, such as increased mortality and low economic mobility. Despite these well-established patterns, disadvantage, often measured using composite indices, is inconsistently operationalized across studies. To address this issue, we systematically compared 5 U.S. disadvantage indices at the county-level on their relationships to 24 diverse life outcomes related to mortality, physical health, mental health, subjective well-being, and social capital from heterogeneous data sources. We further examined which domains of disadvantage are most important when creating these indices. Of the five indices examined, the Area Deprivation Index (ADI) and Child Opportunity Index 2.0 (COI) were most related to a diverse set of life outcomes, particularly physical health. Within each index, variables from the domains of education and employment were most important in relationships with life outcomes. Disadvantage indices are being used in real-world policy and resource allocation decisions; an index's generalizability across diverse life outcomes, and the domains of disadvantage which constitute the index, should be considered when guiding such decisions.

COVID-related social determinants of substance use disorder among diverse U.S. racial ethnic groups

OBJECTIVE

Black, Asian, and Hispanic/Latino people are disproportionately impacted by the COVID-19 pandemic and were more likely to experience coronavirus-related racial discrimination. This study examined the association between pandemic-related stressors, including employment and housing disruptions, coronavirus-related victimization distress, and perceptions of pandemic-associated increase in societal racial biases, and substance use disorder (SUD) risk among Asian, Black, Hispanic/Latino, and non-Hispanic White adults in the U.S.

METHODS

Data were collected as part of a larger national survey on substance use during the pandemic. Eligible participants for the current study were 1336 adults self-identified as Asian (8.53%), Black (10.55%), Hispanic/Latino (10.93%), and non-Hispanic White (69.99%). Measures included demographic and COVID-19-related employment, housing, and health items, the coronavirus victimization distress scale (CVD), the coronavirus racial bias scale (CRB), and measures of substance use risk.

RESULTS

Across racial/ethnic groups, employment disruption distress and housing disruption due to the pandemic were associated with SUD risk. Binary logistic regression analyses controlling for demographic variables indicated CVD was associated with higher odds of tobacco use risk (AOR = 1.36, 95% CI [1.01, 1.81]) and polysubstance use risk (AOR = 1.87, 95% CI [1.14, 3.06]), yet CRB was unrelated to any SUDs. Logistic regressions for each racial/ethnic group found different patterns of relationships between stressors and risk for SUDs.

CONCLUSIONS

Results highlight the significance of examining how the current pandemic has exacerbated racial/ethnic systemic inequalities through COVID-19 related victimization. The data also suggest that across all racial/ethnic groups employment and housing disruptions and perceptions of pandemic instigated increases in societal racial bias are risk factors for SUD. The study calls for further empirical research on substance use prevention and intervention practice sensitive to specific needs of diverse populations during the current and future health crises.

A daily diary study into the effects on mental health of COVID-19 pandemic-related behaviors

BACKGROUND

Recommendations for promoting mental health during the COVID-19 pandemic include maintaining social contact, through virtual rather than physical contact, moderating substance/alcohol use, and limiting news and media exposure. We seek to understand if these pandemic-related behaviors impact subsequent mental health.

METHODS

Daily online survey data were collected on adults during May/June 2020. Measures were of daily physical and virtual (online) contact with others; substance and media use; and indices of psychological striving, struggling and COVID-related worry. Using random-intercept cross-lagged panel analysis, dynamic within-person cross-lagged effects were separated from more static individual differences.

RESULTS

In total, 1148 participants completed daily surveys [657 (57.2%) females, 484 (42.1%) males; mean age 40.6 (s.d. 12.4) years]. Daily increases in news consumed increased COVID-related worrying the next day [cross-lagged estimate = 0.034 (95% CI 0.018-0.049), FDR-adjusted p = 0.00005] and vice versa [0.03 (0.012-0.048), FDR-adjusted p = 0.0017]. Increased media consumption also exacerbated subsequent psychological struggling [0.064 (0.03-0.098), FDR-adjusted p = 0.0005]. There were no significant cross-lagged effects of daily changes in social distancing or virtual contact on later mental health.

CONCLUSIONS

We delineate a cycle wherein a daily increase in media consumption results in a subsequent increase in COVID-related worries, which in turn increases daily media consumption. Moreover, the adverse impact of news extended to broader measures of psychological struggling. A similar dynamic did not unfold between the daily amount of physical or virtual contact and subsequent mental health. Findings are consistent with current recommendations to moderate news and media consumption in order to promote mental health.

Pandemic distress associated with segregation and social stressors

Background

Racial/ethnic minorities are disproportionately impacted by the COVID-19 pandemic, as they are more likely to experience structural and interpersonal racial discrimination, and thus social marginalization. Based on this, we tested for associations between pandemic distress outcomes and four exposures: racial segregation, coronavirus-related racial bias, social status, and social support.

Methods

Data were collected as part of a larger longitudinal national study on mental health during the pandemic (n = 1,309). We tested if county-level segregation and individual-level social status, social support, and coronavirus racial bias were associated with pandemic distress using cumulative ordinal regression models, both unadjusted and adjusted for covariates (gender, age, education, and income).

Results

Both the segregation index (PR = 1.19; 95% CI 1.03, 1.36) and the coronavirus racial bias scale (PR = 1.17; 95% CI 1.06, 1.29) were significantly associated with pandemic distress. Estimates were similar, after adjusting for covariates, for both segregation (aPR = 1.15; 95% CI 1.01, 1.31) and coronavirus racial bias (PR = 1.12; 95% CI 1.02, 1.24). Higher social status (aPR = 0.74; 95% CI 0.64, 0.86) and social support (aPR = 0.81; 95% CI 0.73, 0.90) were associated with lower pandemic distress after adjustment.

Conclusion

Segregation and coronavirus racial bias are relevant pandemic stressors, and thus have implications for minority health. Future research exploring potential mechanisms of this relationship, including specific forms of racial discrimination related to pandemic distress and implications for social justice efforts, are recommended.

Prospective associations of text-message-based sentiment with symptoms of depression, generalized anxiety, and social anxiety

OBJECTIVE

Language patterns may elucidate mechanisms of mental health conditions. To inform underlying theory and risk models, we evaluated prospective associations between in vivo text messaging language and differential symptoms of depression, generalized anxiety, and social anxiety.

METHODS

Over 16 weeks, we collected outgoing text messages from 335 adults. Using Linguistic Inquiry and Word Count (LIWC), NRC Emotion Lexicon, and previously established depression and stress dictionaries, we evaluated the degree to which language features predict symptoms of depression, generalized anxiety, or social anxiety the following week using hierarchical linear models. To isolate the specificity of language effects, we also controlled for the effects of the two other symptom types.

RESULTS

We found significant relationships of language features, including personal pronouns, negative emotion, cognitive and biological processes, and informal language, with common mental health conditions, including depression, generalized anxiety, and social anxiety (ps < .05). There was substantial overlap between language features and the three mental health outcomes. However, after controlling for other symptoms in the models, depressive symptoms were uniquely negatively associated with language about anticipation, trust, social processes, and affiliation (βs: -.10 to -.09, ps < .05), whereas generalized anxiety symptoms were positively linked with these same language features (βs: .12-.13, ps < .001). Social anxiety symptoms were uniquely associated with anger, sexual language, and swearing (βs: .12-.13, ps < .05).

CONCLUSION

Language that confers both common (e.g., personal pronouns and negative emotion) and specific (e.g., affiliation, anticipation, trust, and anger) risk for affective disorders is perceptible in prior week text messages, holding promise for understanding cognitive-behavioral mechanisms and tailoring digital interventions.

Head versus heart: social media reveals differential language of loneliness from depression

We study the language differentially associated with loneliness and depression using 3.4-million Facebook posts from 2986 individuals, and uncover the statistical associations of survey-based depression and loneliness with both dictionary-based (Linguistic Inquiry Word Count 2015) and open-vocabulary linguistic features (words, phrases, and topics). Loneliness and depression were found to have highly overlapping language profiles, including sickness, pain, and negative emotions as (cross-sectional) risk factors, and social relationships and activities as protective factors. Compared to depression, the language associated with loneliness reflects a stronger cognitive focus, including more references to cognitive processes (i.e., differentiation and tentative language, thoughts, and the observation of irregularities), and cognitive activities like reading and writing. As might be expected, less lonely users were more likely to reference social relationships (e.g., friends and family, romantic relationships), and use first-person plural pronouns. Our findings suggest that the mechanisms of loneliness include self-oriented cognitive activities (i.e., reading) and an overattention to the interpretation of information in the environment. These data-driven ecological findings suggest interventions for loneliness that target maladaptive social cognitions (e.g., through reframing the perception of social environments), strengthen social relationships, and treat other affective distress (i.e., depression).

Life under stay-at-home orders: a panel study of change in social interaction and emotional wellbeing among older Americans during COVID-19 pandemic

BACKGROUND

Recent research has shown the mental health consequence of social distancing during the COVID-19 pandemic, but longitudinal data are relatively scarce. It is unclear whether the pattern of isolation and elevated stress seen at the beginning of the pandemic persists over time. This study evaluates change in social interaction over six months and its impact on emotional wellbeing among older adults.

METHODS

We drew data from a panel study with six repeated assessments of social interaction and emotional wellbeing conducted monthly May through October 2020. The sample included a total of 380 White, Black and Hispanic participants aged 50 and over, of whom 33% had low income, who residing in fourteen U.S. states with active stay-at-home orders in May 2020. The analysis examined how change in living arrangement, in-person interaction outside the household, quality of relationship with family and friends, and perceived social support affected trajectories of isolation stress, COVID worry and sadness.

RESULTS

While their living arrangements (Odds Ratio [OR] = 0.95, 95% Confidence Interval [CI] = 0.87, 1.03) and relationship quality (OR = 0.94, 95% CI = 0.82, 1.01) remained stable, older adults experienced fluctuations in perceived social support (linear Slope b = -1.42, s.e. = 0.16, p < .001, quadratic slope b = 0.50, s.e. = 0.08, p < .001, cubic slope b = -0.04, s.e. = 0.01, p < .001) and increases in in-person conversations outside the household (OR = 1.19, 95% CI = 1.09, 1.29). Living with a spouse/partner stabilized isolation stress (change in linear slope b = 1.16, s.e. = 0.48, p < .05, in quadratic slope b = -0.62, s.e. = 0.26, p < .05, and in cubic slope = 0.09, s.e. = 0.04, p < .05) and COVID worry (change in quadratic slope b = -0.66, s.e. = 0.32, p < .05 and in cubic slope = 0.09, s.e. = 0.04, p < .05) over time. Individuals with better relationship quality with friends had decreased sadness over time (OR = 0.90, 95% CI = 0.82, 0.99). Changes in social support were associated with greater fluctuations in isolation stress and COVID worry.

CONCLUSIONS

During the pandemic, social interactions are protective and lack of stability in feeling supported makes older adults vulnerable to stress. Efforts should focus on (re)building and maintaining companionship and support to mitigate the pandemic's negative impact.

Linguistic predictors from Facebook postings of substance use disorder treatment retention versus discontinuation

Background: Early indicators of who will remain in - or leave - treatment for substance use disorder (SUD) can drive targeted interventions to support long-term recovery.Objectives: To conduct a comprehensive study of linguistic markers of SUD treatment outcomes, the current study integrated features produced by machine learning models known to have social-psychology relevance.Methods: We extracted and analyzed linguistic features from participants' Facebook posts (N = 206, 39.32% female; 55,415 postings) over the two years before they entered a SUD treatment program. Exploratory features produced by both Linguistic Inquiry and Word Count (LIWC) and Latent Dirichlet Allocation (LDA) topic modeling and the features from theoretical domains of religiosity, affect, and temporal orientation via established AI-based linguistic models were utilized.Results: Patients who stayed in the SUD treatment for over 90 days used more words associated with religion, positive emotions, family, affiliations, and the present, and used more first-person singular pronouns (Cohen's d values: [-0.39, -0.57]). Patients who discontinued their treatment before 90 days discussed more diverse topics, focused on the past, and used more articles (Cohen's d values: [0.44, 0.57]). All ps < .05 with Benjamini-Hochberg False Discovery Rate correction.Conclusions: We confirmed the literature on protective and risk social-psychological factors linking to SUD treatment in language analysis, showing that Facebook language before treatment entry could be used to identify the markers of SUD treatment outcomes. This reflects the importance of taking these linguistic features and markers into consideration when designing and recommending SUD treatment plans.

Using Facebook language to predict and describe excessive alcohol use

BACKGROUND

Assessing risk for excessive alcohol use is important for applications ranging from recruitment into research studies to targeted public health messaging. Social media language provides an ecologically embedded source of information for assessing individuals who may be at risk for harmful drinking.

METHODS

Using data collected on 3664 respondents from the general population, we examine how accurately language used on social media classifies individuals as at-risk for alcohol problems based on Alcohol Use Disorder Identification Test-Consumption score benchmarks.

RESULTS

We find that social media language is moderately accurate (area under the curve = 0.75) at identifying individuals at risk for alcohol problems (i.e., hazardous drinking/alcohol use disorders) when used with models based on contextual word embeddings. High-risk alcohol use was predicted by individuals' usage of words related to alcohol, partying, informal expressions, swearing, and anger. Low-risk alcohol use was predicted by individuals' usage of social, affiliative, and faith-based words.

CONCLUSIONS

The use of social media data to study drinking behavior in the general public is promising and could eventually support primary and secondary prevention efforts among Americans whose at-risk drinking may have otherwise gone "under the radar."

Efficacy and comparative effectiveness of telephone and smartphone remote continuing care interventions for alcohol use disorder: a randomized controlled trial

BACKGROUND AND AIMS

Management of alcohol use disorder (AUD) could be enhanced by effective remote treatments. This study tested whether supplementing intensive outpatient programs (IOPs) with continuing care delivered via (1) telephone, (2) smartphone or (3) their combination improves outcomes relative to (4) IOP only. Continuing care conditions were also compared.

DESIGN

Randomized controlled trial of four groups with 3-, 6-, 9-, 12- and 18-month follow-ups.

SETTING

University research center in Philadelphia, PA, USA.

PARTICIPANTS

Participants (n = 262) met DSM-V criteria for AUD, were largely male (71%) and African American (82%).

INTERVENTIONS AND COMPARATOR

Telephone monitoring and counseling (TMC; n = 59), addiction comprehensive health enhancement support system (ACHESS; n = 68) and TMC + ACHESS (n = 70) provided for 12 months. The control condition received IOP only (TAU; n = 65).

MEASUREMENT

The primary outcome was percentage of days heavy drinking (PDHD) in months 1-12. Secondary outcomes were any drinking, any drug use, drinking consequences and quality of life.

FINDINGS

Mean PDHD in months 1-12 was 10.29 in TAU, 5.41 in TMC, 6.80 in ACHESS and 5.99 in TMC + ACHESS. PDHD was lower in TMC [Cohen's d = 0.35, P = 0.018, 95% confidence interval (CI) = (-1.42, -0.20)], ACHESS [d = 0.31, P = 0.031, 95% CI = (-1.27, -0.06)] and TMC + ACHESS [d = 0.36, P = 0.009, 95% CI = (-1.40, -0.20)] than in TAU. Differences between TMC + ACHESS, TMC and ACHESS were small (d ≤ 0.06) and non-significant. Findings were inconclusive as to whether or not the treatment conditions differed on PDHD at 18 months. A significant effect was obtained on any drinking, which was higher in months 1-12 in TAU than in TMC [odds ratio (OR) = 3.02, standard error (SE) = 0.43, 95% CI = (1.30, 6.99), P = 0.01] and TMC + ACHESS [OR = 2.43, SE = 0.39, 95% CI = (1.12, 5.27), P = 0.025). No other significant effects were obtained on other secondary outcomes during or after treatment.

CONCLUSIONS

A telephone-delivered intervention and a smartphone-delivered intervention, alone and in combination, provided effective remote continuing care for alcohol use disorder. The combination of both interventions was not superior to either alone and effects did not persist post-treatment.

Getting "clean" from nonsuicidal self-injury: Experiences of addiction on the subreddit r/selfharm

BACKGROUND & AIMS

Previous studies have shown that nonsuicidal self-injury (NSSI) has addictive features, and an addiction model of NSSI has been considered. Addictive features have been associated with severity of NSSI and adverse psychological experiences. Yet, there is debate over the extent to which NSSI and substance use disorders (SUDs) are similar experientially.

METHODS

To evaluate the extent that people who self-injure experience NSSI like an addiction, we coded the posts of users of the subreddit r/selfharm (n = 500) for each of 11 DSM-5 SUD criteria adapted to NSSI.

RESULTS

A majority (76.8%) of users endorsed at least two adapted SUD criteria in their posts, indicative of mild, moderate, or severe addiction. The most frequently endorsed criteria were urges or cravings (67.6%), escalating severity or tolerance (46.7%), and NSSI that is particularly hazardous. User-level addictive features positively predicted number of methods used for NSSI, number of psychiatric disorders, and particularly hazardous NSSI, but not suicidality. We also observed frequent use of language and concepts common in SUD recovery circles like Alcoholics Anonymous.

DISCUSSION & CONCLUSION

Our findings support previous work describing the addiction potential of NSSI and associating addictive features with clinical severity. These results suggest that NSSI and SUD may share experiential similarities, which has implications for the treatment of NSSI. We also contribute to a growing body of work that uses social media as a window into the subjective experiences of stigmatized populations.

COVID-Related Victimization, Racial Bias and Employment and Housing Disruption Increase Mental Health Risk Among U.S. Asian, Black and Latinx Adults

Background: The mental health of racial/ethnic minorities in the U.S. has been disproportionately impacted by the COVID-19 pandemic. This study examined the extent to which disruptions in employment and housing, coronavirus-specific forms of victimization and racial bias independently and conjointly contributed to mental health risk among Asian, Black, and Latinx adults in the United States during the pandemic. Methods: This study reports on data from 401 Asian, Black, and Latinx adults (age 18-72) who participated in a larger national online survey conducted from October 2020-June 2021, Measures included financial and health information, housing disruptions and distress in response to employment changes, coronavirus related victimization distress and perceived increases in racial bias, depression and anxiety. Results: Asian participants had significantly higher levels of COVID-related victimization distress and perceived increases in racial bias than Black and Latinx. Young adults (<26 years old) were more vulnerable to depression, anxiety, and coronavirus victimization distress than older respondents. Having at least one COVID-related health risk, distress in response to changes in employment and housing disruptions, pandemic related victimization distress and perceived increases in racial bias were positively and significantly related to depression and anxiety. Structural equation modeling indicated COVID-related increases in racial bias mediated the effect of COVID-19 related victimization distress on depression and anxiety. Conclusions: COVID-19 has created new pathways to mental health disparities among racial/ethnic minorities in the U.S. by exacerbating existing structural and societal inequities linked to race. Findings highlight the necessity of mental health services sensitive to specific challenges in employment and housing and social bias experienced by people of color during the current and future health crises.

Alcohol-Associated Liver Disease Before and After COVID-19-An Overview and Call for Ongoing Investigation

The Coronavirus Disease 2019 (COVID-19) pandemic has exacted a heavy toll on patients with alcohol-associated liver disease (ALD) and alcohol use disorder (AUD). The collective burden of ALD and AUD was large and growing, even before the COVID-19 pandemic. There is accumulating evidence that this pandemic has had a large direct effect on these patients and is likely to produce indirect effects through delays in care, psychological strain, and increased alcohol use. Now a year into the pandemic, it is important that clinicians fully understand the effects of the COVID-19 pandemic on patients with ALD and AUD. To fill existing gaps in knowledge, the scientific community must set research priorities for patients with ALD regarding their risk of COVID-19, prevention/treatment of COVID-19, changes in alcohol use during the pandemic, best use of AUD treatments in the COVID-19 era, and downstream effects of this pandemic on ALD. Conclusion: The COVID-19 pandemic has already inflicted disproportionate harms on patients with ALD, and ongoing, focused research efforts will be critical to better understand the direct and collateral effects of this pandemic on ALD.

Bots and Misinformation Spread on Social Media: Implications for COVID-19

As of March 2021, the SARS-CoV-2 virus has been responsible for over 115 million cases of COVID-19 worldwide, resulting in over 2.5 million deaths. As the virus spread exponentially, so did its media coverage, resulting in a proliferation of conflicting information on social media platforms-a so-called "infodemic." In this viewpoint, we survey past literature investigating the role of automated accounts, or "bots," in spreading such misinformation, drawing connections to the COVID-19 pandemic. We also review strategies used by bots to spread (mis)information and examine the potential origins of bots. We conclude by conducting and presenting a secondary analysis of data sets of known bots in which we find that up to 66% of bots are discussing COVID-19. The proliferation of COVID-19 (mis)information by bots, coupled with human susceptibility to believing and sharing misinformation, may well impact the course of the pandemic.

Accuracy of Consumer-marketed smartphone-paired alcohol breath testing devices: A laboratory validation study

BACKGROUND

Although alcohol breath testing devices that pair with smartphones are promoted for the prevention of alcohol-impaired driving, their accuracy has not been established.

METHODS

In a within-subjects laboratory study, we administered weight-based doses of ethanol to two groups of 10 healthy, moderate drinkers aiming to achieve a target peak blood alcohol concentration (BAC) of 0.10%. We obtained a peak phlebotomy BAC and measured breath alcohol concentration (BrAC) with a police-grade device (Intoxilyzer 240) and two randomly ordered series of 3 consumer smartphone-paired devices (6 total devices) with measurements every 20 min until the BrAC reached <0.02% on the police device. Ten participants tested the first 3 devices, and the other 10 participants tested the other 3 devices. We measured mean paired differences in BrAC with 95% confidence intervals between the police-grade device and consumer devices.

RESULTS

The enrolled sample (N = 20) included 11 females; 15 white, 3 Asian, and 2 Black participants; with a mean age of 27 and mean BMI of 24.6. Peak BACs ranged from 0.06-0.14%. All 7 devices underestimated BAC by >0.01%, though the BACtrack Mobile Pro and police-grade device were consistently more accurate than the Drinkmate and Evoc. Compared with the police-grade device measurements, the BACtrack Mobile Pro readings were consistently higher, the BACtrack Vio and Alcohoot measurements similar, and the Floome, Drinkmake, and Evoc consistently lower. The BACtrack Mobile Pro and Alcohoot were most sensitive in detecting BAC driving limit thresholds, while the Drinkmate and Evoc devices failed to detect BAC limit thresholds more than 50% of the time relative to the police-grade device.

CONCLUSIONS

The accuracy of smartphone-paired devices varied widely in this laboratory study of healthy participants. Although some devices are suitable for clinical and research purposes, others underestimated BAC, creating the potential to mislead intoxicated users into thinking that they are fit to drive.

Perceived Confidentiality Risks of Mobile Technology-Based Ecologic Momentary Assessment to Assess High-Risk Behaviors Among Rural Men Who Have Sex with Men

Although men who have sex with men (MSM) within rural communities are disproportionately impacted by HIV, limited HIV research and programmatic resources are directed to these communities within the U.S. There is a need for improved behavioral data collection methods to obtain more detailed information on the relationship between rural environments, sexual behavior, and substance use. Utilization of mobile health (mHealth) technologies, such as ecologic momentary assessment (EMA), has been advocated for; however, limited research has evaluated its utility among rural MSM. Forty MSM residing in rural Oklahoma were recruited to complete in-depth interviews related to participating online/mobile-based HIV prevention research. Men described a willingness to participate in HIV and substance use studies that use EMA methodologies for data collection; however, they raised various research-related concerns. In particular, participants indicated potential privacy and confidentiality concerns related to the use of the mobile technology-based EMA in public and the storage of data by researchers. Given the varying degree of sexual orientation and substance use disclosure by participants, rural MSM were largely concerned with being inadvertently "outed" within their communities. Men described the various strategies they could employ to protect private information and methods to minimize research risk. Study findings suggest that EMA is an acceptable research methodology for use among rural MSM in the context of HIV and sexual health information, when privacy and confidentiality concerns are adequately addressed. Input from community members and stakeholders is necessary to identify potential areas of concerns for participants prior to data collection.

Perceived risks and amelioration of harm in research using mobile technology to support antiretroviral therapy adherence in the context of methamphetamine use: a focus group study among minorities living with HIV

BACKGROUND

Methamphetamine use poses a barrier to antiretroviral therapy (ART) adherence. Black and Hispanic men who have sex with men living with HIV (PLWH) shoulder much of the health burden resulting from the methamphetamine and HIV syndemic. Smartphones are nearly ubiquitous in the USA and may be promising vehicles for delivering interventions for ART adherence and drug use cessation. However, the acceptability of using applications to collect sensitive information and deliver feedback in this population has not been adequately explored.

OBJECTIVE

This study examined minority PLWH's appraisals of the risks of participating in smartphone-based research to promote ART adherence in the context of methamphetamine use and explored their views on appropriate steps to mitigate perceived risks of participation.

METHODS

Three focus groups were conducted among Black and Hispanic PLWH who use methamphetamine. Of the 13 participants, 5 had previously participated in a smartphone-based observational study of ART adherence and substance use. Discussants provided feedback on smartphone-based research, including receiving probes for HIV medication adherence, mood, and substance use as well as feedback on passive location-tracking for personalized messages. Transcribed audio-recordings were thematically coded and analyzed using the qualitative software MAXQDA.

RESULTS

Participants expressed confidentiality concerns related to potential unintentional disclosure of their HIV status and methamphetamine use and to possible legal consequences. They additionally expressed concerns around the invasiveness of daily assessments and the potential of methamphetamine use questions to trigger cravings. To mitigate these concerns, they suggested maintaining participant privacy by indirectly asking sensitive questions, focusing on positive behaviors (e.g., number of days sober), allowing user-initiated reporting of location to tailor messages, and ensuring adequate data protections. In addition to financial compensation, participants cited altruism (specifically, continuing a tradition of volunteerism in HIV research) as a motivator for potentially engaging in such research.

CONCLUSIONS

Minority PLWH have concerns regarding the use of smartphones for ART adherence and methamphetamine sobriety intervention research. However, minority PLWH are likely to participate if studies include appropriate protections against risks to confidentiality and experimental harm and are designed to offer future benefit to themselves and other PLWH.

Cultural Differences in Tweeting about Drinking Across the US

Excessive alcohol use in the US contributes to over 88,000 deaths per year and costs over $250 billion annually. While previous studies have shown that excessive alcohol use can be detected from general patterns of social media engagement, we characterized how drinking-specific language varies across regions and cultures in the US. From a database of 38 billion public tweets, we selected those mentioning “drunk”, found the words and phrases distinctive of drinking posts, and then clustered these into topics and sets of semantically related words. We identified geolocated “drunk” tweets and correlated their language with the prevalence of self-reported excessive alcohol consumption (Behavioral Risk Factor Surveillance System; BRFSS). We then identified linguistic markers associated with excessive drinking in different regions and cultural communities as identified by the American Community Project. “Drunk” tweet frequency (of the 3.3 million geolocated “drunk” tweets) correlated with excessive alcohol consumption at both the county and state levels (r = 0.26 and 0.45, respectively, p < 0.01). Topic analyses revealed that excessive alcohol consumption was most correlated with references to drinking with friends (r = 0.20), family (r = 0.15), and driving under the influence (r = 0.14). Using the American Community Project classification, we found a number of cultural markers of drinking: religious communities had a high frequency of anti-drunk driving tweets, Hispanic centers discussed family members drinking, and college towns discussed sexual behavior. This study shows that Twitter can be used to explore the specific sociocultural contexts in which excessive alcohol use occurs within particular regions and communities. These findings can inform more targeted public health messaging and help to better understand cultural determinants of substance abuse.

Recovery dialects: A pilot study of stigmatizing and nonstigmatizing label use by individuals in recovery from substance use disorders

Previous research has found language used to describe individuals with a substance use disorder (SUD; e.g., "addict," "substance abuser") contributes to and elicits negative bias among the general public and health care professionals. However, the prevalence in which recovering individuals use these labels to self-identify and the impact of such labels are unknown. The current pilot study, a cross-sectional design, examined the usage of two labels ("addict," "person with a SUD") as well as the differences in recovery outcomes among individuals in recovery. Participants (n = 54) used both labels at high rates ("addict": 66.67%; "person with a SUD": 38.89%), though mutually exclusive use was lower ("addict" only: 35.19%, "person with a SUD" only: 7.5%). Common label use settings included mutual-aid recovery meetings, with friends and family, and on social media. Analysis of variance tests found no statistically significant differences between label groups for recovery capital, self-esteem, internalized stigma and shame, flourishing, or length in recovery. Descriptively, participants using only "person with a SUD" had more positive outcomes, although these individuals also had higher levels of internalized shame. Results suggest that language may have only a marginal impact on individuals in recovery, although professionals and the general public should continue to avoid using stigmatizing labels. Additionally, many individuals in recovery have the ability to discern context and setting, switching between positive and negative labels as appropriate. Future research is warranted given these pilot findings and should focus on long-term impacts of self-labeling and internalized stereotypes among individuals in recovery. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Reducing harm and promoting recovery through community-based mutual aid: Characterizing those who engage in a hybrid peer recovery community organization

BACKGROUND

Peer-based support services are often used within harm reduction organizations, and more recently within recovery community organizations (RCO). Identifying the characteristics of individuals who engage with these novel RCOs is needed. Additionally, conducting collaborative research with communities of people who use drugs (PWUD) or are in recovery is an effective and rewarding approach that allows individuals to take ownership and play a critical role in the study.

METHODS

This exploratory study employs a community-based participatory research (CBPR) framework in partnership with a peer-led hybrid recovery community organization, Rebel Recovery, in Florida. Peer staff participated in all phases of the study, helping to inform the study protocol, data collection, analysis, interpretation, and results write-up. A cross-sectional survey instrument was used to collect consumer intake data. Pearson Chi-square tests and multivariate binomial logistic regressions were used to examine relationships between consumer characteristics and service utilization.

RESULTS

Consumers (n = 396) of Rebel Recovery peer support services had a mean age of 35.60 years (SD = 9.74). Many were experiencing homelessness (35.4%), unemployed (69.7%), high school graduates or GED holders (68.2%) and had a last year income of less than $10,000 (58.3%). The majority were users of heroin primarily (70.7%), with intravenous use being the preferred route of administration (63.9%). Exploratory analysis found that gender, marital status, and involvement in the child welfare system were significantly related to primary substance of use. Past 30-day engagement in recovery meetings had several statistically significant predictors including primary substance of use, age, housing status, annual income level, past-30-day arrests, tobacco use, and alcohol harm perception. Process findings from the CBPR methods used reconfirm the value of including peers in research involving PWUD and individuals in recovery.

CONCLUSIONS

Results suggest that peer-based support services at a hybrid recovery community organization can successfully engage populations that are often underserved (i.e., experiencing homelessness, involved in drug court, intravenous users, etc.). Significant relationships identified in the exploratory analysis suggest that additional education concerning overdose and the potential benefits of recovery meetings may be useful for specific consumers. Additionally, several recommendations and benefits of engaging in community-based participatory research with peer-led organizations are made for future research.

Responding to the opioid and overdose crisis with innovative services: The recovery community center office-based opioid treatment (RCC-OBOT) model

Opioid use disorder (OUD) and opioid-related overdose mortality are major public health concerns in the United States. Recently, several community-based and professional innovations - including hybrid recovery community organizations, peer-based emergency department warm handoff programs, emergency department buprenorphine induction, and low-threshold OUD treatment programs - have emerged or expanded in an effort to address significant obstacles to providing patients the care needed for OUD and to reduce the risk of overdose. Additional innovations are needed to address the crisis. Building upon the foundational frameworks of each of these recent innovations, a new model of OUD pharmacotherapy is proposed and discussed: the Recovery Community Center Office-Based Opioid Treatment model. Additionally, two potential implementation scenarios, the overdose and non-overdose event protocols, are detailed for communities, peers, and practitioners interested in implementing the model. Potential barriers to implementation of the model include service reimbursement, licensing regulations, and organizational concerns. Future research should seek to validate the model and to identify actual implementation and sustainability barriers and best practices.

The Language of Substance Use and Recovery: Novel Use of the Go/No-Go Association Task to Measure Implicit Bias

Previous research has found initial evidence that word choice impacts the perception and treatment of those with behavioral health disorders through explicit bias (i.e., stigma). A more robust picture of behavioral health disorder stigma should incorporate both explicit and implicit bias, rather than relying on only one form. The current study uses the Go/No-Go Association Task to calculate a d' (sensitivity) indexed score of automatic attitudes (i.e., implicit associations) to two terms, "addict" and "person with substance use disorder." Participants have significantly more negative automatic attitudes (i.e., implicit bias) toward the term "addict" in isolation as well as when compared to "person with a substance use disorder." Consistent with previous research on explicit bias, implicit bias does exist for terms commonly used in the behavioral health field. "Addict" should not be used in professional or lay settings. Additionally, these results constitute the second pilot study employed the Go/No-Go Association Task in this manner, suggesting it is a viable option for continued linguistic stigma related research.

Characterizing Participation and Perceived Engagement Benefits in an Integrated Digital Behavioral Health Recovery Community for Women: A Cross-Sectional Survey

BACKGROUND

Research suggests that digital recovery support services (D-RSSs) may help support individual recovery and augment the availability of in-person supports. Previous studies highlight the use of D-RSSs in supporting individuals in recovery from substance use but have yet to examine the use of D-RSSs in supporting a combination of behavioral health disorders, including substance use, mental health, and trauma. Similarly, few studies on D-RSSs have evaluated gender-specific supports or integrated communities, which may be helpful to women and individuals recovering from behavioral health disorders.

OBJECTIVE

The goal of this study was to evaluate the SHE RECOVERS (SR) recovery community, with the following 3 aims: (1) to characterize the women who engage in SR (including demographics and recovery-related characteristics), (2) describe the ways and frequency in which participants engage with SR, and (3) examine the perception of benefit derived from engagement with SR.

METHODS

This study used a cross-sectional survey to examine the characteristics of SR participants. Analysis of variance and chi-square tests, as well as univariate logistic regressions, were used to explore each aim.

RESULTS

Participants (N=729, mean age 46.83 years; 685/729, 94% Caucasian) reported being in recovery from a variety of conditions, although the most frequent nonexclusive disorder was substance use (86.40%, n=630). Participants had an average length in recovery (LIR) of 6.14 years (SD 7.87), with most having between 1 and 5 years (n=300). The most frequently reported recovery pathway was abstinence-based 12-step mutual aid (38.40%). Participants reported positive perceptions of benefit from SR participation, which did not vary by LIR or recovery pathway. Participants also had high rates of agreement, with SR having a positive impact on their lives, although this too did vary by recovery length and recovery pathway. Participants with 1 to 5 years of recovery used SR to connect with other women in recovery at higher rates, whereas those with less than 1 year used SR to ask for resources at higher rates, and those with 5 or more years used SR to provide support at higher rates. Lifetime engagement with specific supports of SR was also associated with LIR and recovery pathway.

CONCLUSIONS

Gender-specific and integrated D-RSSs are feasible and beneficial from the perspective of participants. D-RSSs also appear to provide support to a range of recovery typologies and pathways in an effective manner and may be a vital tool for expanding recovery supports for those lacking in access and availability because of geography, social determinants, or other barriers.

Expanding language choices to reduce stigma

Purpose

Public perception has been found to be influenced by the words used to describe those with behavioral health disorders, such that using terms like “substance abuser” can lead to higher levels of stigma. The purpose of this paper is to identify additional stigmatizing and empowering terms that are commonly used by different stakeholders.

Design/methodology/approach

Using digital Delphi groups, the paper identifies positive and negative terms related to substance use disorder (SUD) from three distinct stakeholder groups: individuals in recovery, impacted family members and loved ones, and professionals in the treatment field.

Findings

Participants identified 60 different terms that are considered stigmatizing or positive. Previously identified stigmatizing terms (abuser, addict) were present for all stakeholder groups, as was the positive term person with a SUD. Additional stigmatizing terms for all groups included junkie and alcoholic. Additional positive terms for all groups included long-term recovery.

Social implications

The results suggest that the continued use of terms like addict, alcoholic, abuser and junkie can induce stigma in multiple stakeholders. The use of more positive terms such as person with a SUD or person in recovery is suggested to reduce stigma.

Originality/value

The use of digital Delphi groups to solicit feedback from multiple stakeholder groups from the substance use community is innovative and allows for the comparison of linguistics among and between the groups.

Biased labels: An experimental study of language and stigma among individuals in recovery and health professionals

BACKGROUND

Labels such as "addict" and "substance abuser" have been found to elicit implicit and explicit stigma among the general public previously. The difference in the levels of this bias among individuals in recovery and those employed in the health profession has not yet been identified, however. The current study seeks to answer this question using measures of implicit bias.

METHODS

A subset sample (n = 299) from a previously completed study (n = 1288) was selected for analysis. Mixed-model ANOVA tests were completed to identify variance between d-prime automatic association scores with the terms "addict" and "substance abuser" among individuals in recovery and those identified as working in the health professions.

RESULTS

Individuals in recovery did not have lower negative associations with either term, whereas individuals employed as health professionals had greater negative associations with the term "substance abuser" but did not have greater negative associations with the term "addict."

CONCLUSIONS

Results provide further evidence that previously identified stigmatizing labels have the potential to influence medical care and medical practitioner perceptions of individuals with substance use disorders and should be avoided. Further exploration into the role negative associations derived from commonly used labels have in the individual recovery process is needed to draw appropriate recommendations.

Peer-delivered harm reduction and recovery support services: initial evaluation from a hybrid recovery community drop-in center and syringe exchange program

Background

Recovery from substance use disorder (SUD) is often considered at odds with harm reduction strategies. More recently, harm reduction has been categorized as both a pathway to recovery and a series of services to reduce the harmful consequences of substance use. Peer recovery support services (PRSS) are effective in improving SUD outcomes, as well as improving the engagement and effectiveness of harm reduction programs.

Methods

This study provides an initial evaluation of a hybrid recovery community organization providing PRSS as well as peer-based harm reduction services via a syringe exchange program. Administrative data collected during normal operations of the Missouri Network for Opiate Reform and Recovery were analyzed using Pearson chi-square tests and Monte Carlo chi-square tests.

Results

Intravenous substance-using participants (N = 417) had an average of 2.14 engagements (SD = 2.59) with the program. Over the evaluation period, a range of 5345–8995 sterile syringes were provided, with a range of 600–1530 used syringes collected. Participant housing status, criminal justice status, and previous health diagnosis were all significantly related to whether they had multiple engagements.

Conclusions

Results suggest that recovery community organizations are well situated and staffed to also provide harm reduction services, such as syringe exchange programs. Given the relationship between engagement and participant housing, criminal justice status, and previous health diagnosis, recommendations for service delivery include additional education and outreach for homeless, justice-involved, LatinX, and LGBTQ+ identifying individuals.

"Abusing Addiction": Our Language Still Isn't Good Enough

Background

Previous research has found initial evidence that word choice impacts the perception and treatment of those with behavioral health disorders. These previous studies have relied on vignette-based methodologies, however, and a more quantifiable index of the stigma words can produce is needed.

Method

The current study uses the Go/No-Go Association Task to calculate a d-prime (sensitivity) indexed score of automatic attitudes to two terms, "substance abuser" and "person with substance use disorder".

Results

Participants have significantly more negative automatic attitudes towards the term "substance abuser", as compared to "person with a substance use disorder".

Conclusion

Consistent with previous research, implicit bias does exist for terms commonly used in the behavioral health field. "Substance Abuser" and its derivatives should not be used in professional or lay settings.

Substance use, recovery, and linguistics: The impact of word choice on explicit and implicit bias

BACKGROUND

The general public, treatment professionals, and healthcare professionals have been found to exhibit an explicit negative bias towards substance use and individuals with a substance use disorder (SUD). Terms such as "substance abuser" and "opioid addict" have shown to elicit greater negative explicit bias. However, other common terms have yet to be empirically studied.

METHODS

1,288 participants were recruited from ResearchMatch. Participants were assigned into one of seven groups with different hypothesized stigmatizing and non-stigmatizing terms. Participants completed a Go/No Association Task (GNAT) and vignette-based social distance scale. Repeated-measures ANOVAs were used to analyze the GNAT results, and one-way ANOVAs were used to analyze vignette results.

RESULTS

The terms "substance abuser", "addict", "alcoholic", and "opioid addict", were strongly associated with the negative and significantly different from the positive counterterms. "Relapse" and "Recurrence of Use" were strongly associated with the negative; however, the strength of the "recurrence of use" positive association was higher and significantly different from the "relapse" positive association. "Pharmacotherapy" was strongly associated with the positive and significantly different than "medication-assisted treatment". Both "medication-assisted recovery" and "long-term recovery" were strongly associated with the positive, and significantly different from the negative association.

CONCLUSIONS

Results support calls to cease use of the terms "addict", "alcoholic", "opioid addict", and "substance abuser". Additionally, it is suggested that "recurrence of use" and "pharmacotherapy" be used for their overall positive benefits. Both "medication-assisted recovery" and "long-term recovery" are positive terms and can be used when applicable without promoting stigma.

Can Twitter be used to predict county excessive alcohol consumption rates?

Objectives

The current study analyzes a large set of Twitter data from 1,384 US counties to determine whether excessive alcohol consumption rates can be predicted by the words being posted from each county.

Methods

Data from over 138 million county-level tweets were analyzed using predictive modeling, differential language analysis, and mediating language analysis.

Results

Twitter language data captures cross-sectional patterns of excessive alcohol consumption beyond that of sociodemographic factors (e.g. age, gender, race, income, education), and can be used to accurately predict rates of excessive alcohol consumption. Additionally, mediation analysis found that Twitter topics (e.g. ‘ready gettin leave’) can explain much of the variance associated between socioeconomics and excessive alcohol consumption.

Conclusions

Twitter data can be used to predict public health concerns such as excessive drinking. Using mediation analysis in conjunction with predictive modeling allows for a high portion of the variance associated with socioeconomic status to be explained.

Technology and Social Media Use Among Patients Enrolled in Outpatient Addiction Treatment Programs: Cross-Sectional Survey Study

Background

Substance use disorder research and practice have not yet taken advantage of emerging changes in communication patterns. While internet and social media use is widespread in the general population, little is known about how these mediums are used in substance use disorder treatment.

Objective

The aims of this paper were to provide data on patients' with substance use disorders mobile phone ownership rates, usage patterns on multiple digital platforms (social media, internet, computer, and mobile apps), and their interest in the use of these platforms to monitor personal recovery.

Methods

We conducted a cross-sectional survey of patients in 4 intensive outpatient substance use disorder treatment facilities in Philadelphia, PA, USA. Logistic regressions were used to examine associations among variables.

Results

Survey participants (N=259) were mostly male (72.9%, 188/259), African American (62.9%, 163/259), with annual incomes less than US $10,000 (62.5%, 161/259), and averaged 39 (SD 12.24) years of age. The vast majority of participants (93.8%, 243/259) owned a mobile phone and about 64.1% (166/259) owned a mobile phone with app capabilities, of which 85.1% (207/243) accessed the internet mainly through their mobile phone. There were no significant differences in age, gender, ethnicity, or socio-economic status by computer usage, internet usage, number of times participants changed their phone, type of mobile phone contract, or whether participants had unlimited calling plans. The sample was grouped into 3 age groups (Millennials, Generation Xers, and Baby Boomers). The rates of having a social media account differed across these 3 age groups with significant differences between Baby Boomers and both Generation Xers and Millennials (P<.001 in each case). Among participants with a social media account (73.6%, 190/259), most (76.1%, 144/190) reported using it daily and nearly all (98.2%, 186/190) used Facebook. Nearly half of participants (47.4%, 90/190) reported viewing content on social media that triggered substance cravings and an equal percentage reported being exposed to recovery information on social media. There was a significant difference in rates of reporting viewing recovery information on social media across the 3 age groups with Baby Boomers reporting higher rates than Millennials (P<.001). The majority of respondents (70.1%, 181/259) said they would prefer to use a relapse prevention app on their phone or receive SMS (short message service) relapse prevention text messages (72.3%, 186/259), and nearly half (49.1%, 127/259) expressed an interest in receiving support by allowing social media accounts to be monitored as a relapse prevention technique.

Conclusions

To our knowledge, this is the first and largest study examining the online behavior and preferences regarding technology-based substance use disorder treatment interventions in a population of patients enrolled in community outpatient treatment programs. Patients were generally receptive to using relapse prevention apps and text messaging interventions and a substantial proportion supported social media surveillance tools. However, the design of technology-based interventions remains as many participants have monthly telephone plans which may limit continuity.