Insights into ALD and AUD diagnosis and prognosis: Exploring AI and multimodal data streams.

The rapid evolution of artificial intelligence and the widespread embrace of digital technologies have ushered in a new era of clinical research and practice in hepatology. Although its potential is far from realization, these significant strides have generated new opportunities to address existing gaps in the delivery of care for patients with liver disease. In this review, we discuss how artificial intelligence and opportunities for multimodal data integration can improve the diagnosis, prognosis, and management of alcohol-associated liver disease. An emphasis is made on how these approaches will also benefit the detection and management of alcohol use disorder. Our discussion encompasses challenges and limitations, concluding with a glimpse into the promising future of these advancements.

Differential temporal utility of passively sensed smartphone features for depression and anxiety symptom prediction: a longitudinal cohort study.

While studies show links between smartphone data and affective symptoms, we lack clarity on the temporal scale, specificity (e.g., to depression vs. anxiety), and person-specific (vs. group-level) nature of these associations. We conducted a large-scale (n = 1013) smartphone-based passive sensing study to identify within- and between-person digital markers of depression and anxiety symptoms over time. Participants (74.6% female; M age = 40.9) downloaded the LifeSense app, which facilitated continuous passive data collection (e.g., GPS, app and device use, communication) across 16 weeks. Hierarchical linear regression models tested the within- and between-person associations of 2-week windows of passively sensed data with depression (PHQ-8) or generalized anxiety (GAD-7). We used a shifting window to understand the time scale at which sensed features relate to mental health symptoms, predicting symptoms 2 weeks in the future (distal prediction), 1 week in the future (medial prediction), and 0 weeks in the future (proximal prediction). Spending more time at home relative to one's average was an early signal of PHQ-8 severity (distal ß = 0.219, p = 0.012) and continued to relate to PHQ-8 at medial (ß = 0.198, p = 0.022) and proximal (ß = 0.183, p = 0.045) windows. In contrast, circadian movement was proximally related to (ß = -0.131, p = 0.035) but did not predict (distal ß = 0.034, p = 0.577; medial ß = -0.089, p = 0.138) PHQ-8. Distinct communication features (i.e., call/text or app-based messaging) related to PHQ-8 and GAD-7. Findings have implications for identifying novel treatment targets, personalizing digital mental health interventions, and enhancing traditional patient-provider interactions. Certain features (e.g., circadian movement) may represent correlates but not true prospective indicators of affective symptoms. Conversely, other features like home duration may be such early signals of intra-individual symptom change, indicating the potential utility of prophylactic intervention (e.g., behavioral activation) in response to person-specific increases in these signals.

Smartphone sensor data estimate alcohol craving in a cohort of patients with alcohol-associated liver disease and alcohol use disorder.

BACKGROUND: Sensors within smartphones, such as accelerometer and location, can describe longitudinal markers of behavior as represented through devices in a method called digital phenotyping. This study aimed to assess the feasibility of digital phenotyping for patients with alcohol-associated liver disease and alcohol use disorder, determine correlations between smartphone data and alcohol craving, and establish power assessment for future studies to prognosticate clinical outcomes. METHODS: A total of 24 individuals with alcohol-associated liver disease and alcohol use disorder were instructed to download the AWARE application to collect continuous sensor data and complete daily ecological momentary assessments on alcohol craving and mood for up to 30 days. Data from sensor streams were processed into features like accelerometer magnitude, number of calls, and location entropy, which were used for statistical analysis. We used repeated measures correlation for longitudinal data to evaluate associations between sensors and ecological momentary assessments and standard Pearson correlation to evaluate within-individual relationships between sensors and craving. RESULTS: Alcohol craving significantly correlated with mood obtained from ecological momentary assessments. Across all sensors, features associated with craving were also significantly correlated with all moods (eg, loneliness and stress) except boredom. Individual-level analysis revealed significant relationships between craving and features of location entropy and average accelerometer magnitude. CONCLUSIONS: Smartphone sensors may serve as markers for alcohol craving and mood in alcohol-associated liver disease and alcohol use disorder. Findings suggest that location-based and accelerometer-based features may be associated with alcohol craving. However, data missingness and low participant retention remain challenges. Future studies are needed for further digital phenotyping of relapse risk and progression of liver disease.

Specific associations of passively sensed smartphone data with future symptoms of avoidance, fear, and physiological distress in social anxiety.

Background: Prior literature links passively sensed information about a person's location, movement, and communication with social anxiety. These findings hold promise for identifying novel treatment targets, informing clinical care, and personalizing digital mental health interventions. However, social anxiety symptoms are heterogeneous; to identify more precise targets and tailor treatments, there is a need for personal sensing studies aimed at understanding differential predictors of the distinct subdomains of social anxiety. Our objective was to conduct a large-scale smartphone-based sensing study of fear, avoidance, and physiological symptoms in the context of trait social anxiety over time. Methods: Participants (n = 1013; 74.6 % female; M age = 40.9) downloaded the LifeSense app, which collected continuous passive data (e.g., GPS, communication, app and device use) over 16 weeks. We tested a series of multilevel linear regression models to understand within- and between-person associations of 2-week windows of passively sensed smartphone data with fear, avoidance, and physiological distress on the self-reported Social Phobia Inventory (SPIN). A shifting sensor lag was applied to examine how smartphone features related to SPIN subdomains 2 weeks in the future (distal prediction), 1 week in the future (medial prediction), and 0 weeks in the future (proximal prediction). Results: A decrease in time visiting novel places was a strong between-person predictor of social avoidance over time (distal ß = -0.886, p = .002; medial ß = -0.647, p = .029; proximal ß = -0.818, p = .007). Reductions in call- and text-based communications were associated with social avoidance at both the between- (distal ß = -0.882, p = .002; medial ß = -0.932, p = .001; proximal ß = -0.918, p = .001) and within- (distal ß = -0.191, p = .046; medial ß = -0.213, p = .028) person levels, as well as between-person fear of social situations (distal ß = -0.860, p < .001; medial ß = -0.892, p < .001; proximal ß = -0.886, p < .001) over time. There were fewer significant associations of sensed data with physiological distress. Across the three subscales, smartphone data explained 9-12 % of the variance in social anxiety. Conclusion: Findings have implications for understanding how social anxiety manifests in daily life, and for personalizing treatments. For example, a signal that someone is likely to begin avoiding social situations may suggest a need for alternative types of exposure-based interventions compared to a signal that someone is likely to begin experiencing increased physiological distress. Our results suggest that as a prophylactic means of targeting social avoidance, it may be helpful to deploy interventions involving social exposures in response to decreases in time spent visiting novel places.

The association of language style matching in text messages with mood and anxiety symptoms.

Context: Impairment in social functioning is a feature and consequence of depression and anxiety disorders. For example, in depression, anhedonia and negative feelings about the self may impact relationships; in anxiety, fear of negative evaluation may interfere with getting close to others. It is unknown whether social impairment associated with depression and anxiety symptoms is reflected in day-to-day language exchanges with others, such as through reduced language style matching (LSM). Methods: Over 16 weeks, we collected text message data from 458 adults and evaluated differences in LSM between people with average scores above/below the clinical cutoff for depression, generalized anxiety, and social anxiety in text message conversations. Text message sentiment scores were computed across 73 Linguistic Inquiry and Word Count (LIWC) categories for each participant. T-tests were used to compare LSM across two groups (average scores above/below clinical cutoff) for each of the 3 diagnostic categories (depression, generalized anxiety, social anxiety), and each of the 73 LIWC categories, with correction for multiple comparisons. Results: We found reduced LSM of function words (namely, prepositions [t=-2.82, p=.032], articles [t=-5.26, p<.001], and auxiliary verbs [t=-2.64, p=.046]) in people with average scores above the clinical cutoff for generalized anxiety, and reduced LSM of prepositions (t=-4.26, p<.001) and articles (t=-3.39, p=.010) in people with average scores above the clinical cutoff for social anxiety. There were no significant differences in LSM of function words between people with average scores above and below the clinical cutoff for depression. Across all symptom categories, elevated affective psychopathology was associated with being more likely to style match on formality, including netspeak (generalized anxiety, t=5.77, p<.001; social anxiety, t=4.14, p<.001; depression, t=3.13, p=.021) and informal language (generalized anxiety, t=6.65, p<.001; social anxiety, t=5.14, p>.001; depression, t=3.20, p=.020).We also observed content-specific LSM differences across the three groups. Conclusions: Reduced LSM of function words among patients reporting elevated anxiety symptoms suggests that anxiety-related psychosocial difficulties may be perceptible in subtle cues from day-to-day language. Conversely, the absence of differences in the LSM of function words among people with average scores above and below the clinical cutoff for depression indicates a potentially distinct mechanism of social impairment. Implications: Results point to potential markers of psychosocial difficulties in daily conversations, particularly among those experiencing heightened anxiety symptoms. Future studies may consider the degree to which LSM is associated with self-reported psychosocial impairment, with the promise of informing cognitive-behavioral mechanisms and tailoring digital interventions for social skills.

Daily diary study of loneliness, alcohol, and drug use during the COVID-19 Pandemic.

BACKGROUND: Research conducted during the COVID-19 Pandemic has identified two co-occurring public health concerns: loneliness and substance use. Findings from research conducted prior to the pandemic are inconclusive as to the links between loneliness and substance use. This study aimed to measure associations of loneliness with three different types of substance use during COVID-19: daily number of alcoholic drinks, cannabis use, and non-cannabis drug use. METHOD: Data were obtained between October 2020 and May 2021 from 2,648 US adults (Mage  = 38.76, 65.4% women) diverse with respect to race and ethnicity using online recruitment. Participants completed baseline surveys and daily assessments for 30 days. A daily loneliness measure was recoded into separate within- and between-person predictor variables. Daily outcome measures included the number of alcoholic drinks consumed and dichotomous cannabis and non-cannabis drug use variables. Generalized linear multilevel models (GLMLM) were used to examine within- and between-person associations between loneliness and substance use. RESULTS: The unconditional means model indicated that 59.0% of the variance in the daily number of alcoholic drinks was due to within-person variability. GLMLM analyses revealed that, overall, people drank more on days when they felt a particularly high or particularly low degree of loneliness (positive quadratic effect). There was a negative and significant within-person association between daily loneliness and the likelihood of cannabis use. There was also a positive and significant within-person association between daily loneliness and the likelihood of non-cannabis drug use. CONCLUSIONS: Associations between loneliness and substance use vary with substance type and whether within- or between-person differences are assessed. These findings are relevant to the persistence of substance use disorders and thus of potential clinical importance. Individuals who do not experience severe loneliness at intake but who show daily increases in loneliness above baseline levels are at heightened risk of alcohol and non-cannabis drug use. Future research could profitably examine just-in-time adaptive interventions that assess fluctuations in loneliness to prevent the development or exacerbation of substance use disorders.

Loneliness and Daily Alcohol Consumption During the COVID-19 Pandemic.

AIMS: This pilot study aimed to identify associations of loneliness and daily alcohol consumption among US adults during the Coronavirus Disease-2019 pandemic. METHOD: Participants completed daily assessments for 30 days. RESULTS: Results suggest people who feel lonelier on average drink more alcohol, however, people who feel lonelier than usual drink less. CONCLUSION: Findings highlight the need to disaggregate within- and between-person components of alcohol use.

Child reward neurocircuitry and parental substance use history: Findings from the Adolescent Brain Cognitive Development Study.

BACKGROUND: Substance use research has focused on family history of alcohol use disorders but less on other addictions in biological family members. We examined how parental substance use history relates to reward system functioning, specifically nucleus accumbens (NAcc) and putamen activation at age 9-10 in the Adolescent Brain Cognitive Development (ABCD) Study. This research hopes to address limitations in prior literature by focusing analyses on a large, substance-naïve sample. METHOD: We included ABCD participants with valid Monetary Incentive Delay task fMRI Baseline data and parent substance use history at project baseline from Data Release 2.0 (N = 10,622). Parent-history-positive (PH+) participants had one or both biological parents with a history of two+problems with alcohol (n = 741; PH+A) and/or other drugs (n = 638; PH+D). Of participants who were parent-history-negative (PH-) for alcohol and/or drugs, a stratified random sample based on six sociodemographic variables was created and matched to the PH+group (PH-A n = 699; PH-D n = 615). The contrast of interest was anticipation of a large reward vs. neutral response. RESULTS: PH+A youth had more activation in the right NAcc during large reward anticipation than PH-A. PH+D youth showed enhanced left putamen activation during large reward anticipation than PH-D youth. Bayesian hypothesis testing showed moderate evidence (BF > 3) in favor of the null hypothesis. CONCLUSION: These findings suggest that pre-adolescents whose biological parents had a history of substance-related problems show small differences in reward processing compared to their PH- peers.

Beyond abstinence and relapse II: momentary relationships between stress, craving, and lapse within clusters of patients with similar patterns of drug use.

RATIONALE: Given that many patients being treated for opioid-use disorder continue to use drugs, identifying clusters of patients who share similar patterns of use might provide insight into the disorder, the processes that affect it, and ways that treatment can be personalized. OBJECTIVES AND METHODS: We applied hierarchical clustering to identify patterns of opioid and cocaine use in 309 participants being treated with methadone or buprenorphine (in a buprenorphine-naloxone formulation) for up to 16 weeks. A smartphone app was used to assess stress and craving at three random times per day over the course of the study. RESULTS: Five basic patterns of use were identified: frequent opioid use, frequent cocaine use, frequent dual use (opioids and cocaine), sporadic use, and infrequent use. These patterns were differentially associated with medication (methadone vs. buprenorphine), race, age, drug-use history, drug-related problems prior to the study, stress-coping strategies, specific triggers of use events, and levels of cue exposure, craving, and negative mood. Craving tended to increase before use in all except those who used sporadically. Craving was sharply higher during the 90 min following moderate-to-severe stress in those with frequent use, but only moderately higher in those with infrequent or sporadic use. CONCLUSIONS: People who share similar patterns of drug-use during treatment also tend to share similarities with respect to psychological processes that surround instances of use, such as stress-induced craving. Cluster analysis combined with smartphone-based experience sampling provides an effective strategy for studying how drug use is related to personal and environmental factors.

"They know what they are getting into:" Researchers confront the benefits and challenges of online recruitment for HIV research.

Online research has become a critical recruitment modality for understanding and reducing health disparities among hidden populations most at risk for HIV infection. There is a lack of consensus and guidelines for the responsible conduct of online recruitment for HIV risk populations. Using semi-structured phone interviews, this study drew on the experiences of principal investigators (PIs) engaged in online HIV research to illuminate scientific and ethical benefits and challenges of social media recruitment. Using Thematic Analysis five major themes emerged: sampling advantages and disadvantages; challenges of data integrity; control of privacy protections; researcher competence and responsibility; and resources.

Prediction of stress and drug craving ninety minutes in the future with passively collected GPS data.

Just-in-time adaptive interventions (JITAIs), typically smartphone apps, learn to deliver therapeutic content when users need it. The challenge is to "push" content at algorithmically chosen moments without making users trigger it with effortful input. We trained a randomForest algorithm to predict heroin craving, cocaine craving, or stress (reported via smartphone app 3x/day) 90 min into the future, using 16 weeks of field data from 189 outpatients being treated for opioid-use disorder. We used only one form of continuous input (along with person-level demographic data), collected passively: an indicator of environmental exposures along the past 5 h of movement, as assessed by GPS. Our models achieved excellent overall accuracy-as high as 0.93 by the end of 16 weeks of tailoring-but this was driven mostly by correct predictions of absence. For predictions of presence, "believability" (positive predictive value, PPV) usually peaked in the high 0.70s toward the end of the 16 weeks. When the prediction target was more rare, PPV was lower. Our findings complement those of other investigators who use machine learning with more broadly based "digital phenotyping" inputs to predict or detect mental and behavioral events. When target events are comparatively subtle, like stress or drug craving, accurate detection or prediction probably needs effortful input from users, not passive monitoring alone. We discuss ways in which accuracy is difficult to achieve or even assess, and warn that high overall accuracy (including high specificity) can mask the abundance of false alarms that low PPV reveals.

Comparison of Smartphone Ownership, Social Media Use, and Willingness to Use Digital Interventions Between Generation Z and Millennials in the Treatment of Substance Use: Cross-Sectional Questionnaire Study.

BACKGROUND: Problematic substance use in adolescence and emerging adulthood is a significant public health concern in the United States due to high recurrence of use rates and unmet treatment needs coupled with increased use. Consequently, there is a need for both improved service utilization and availability of recovery supports. Given the ubiquitous use of the internet and social media via smartphones, a viable option is to design digital treatments and recovery support services to include internet and social media platforms. OBJECTIVE: Although digital treatments delivered through social media and the internet are a possibility, it is unclear how interventions using these tools should be tailored for groups with problematic substance use. There is limited research comparing consumer trends of use of social media platforms, use of platform features, and vulnerability of exposure to drug cues online. The goal of this study was to compare digital platforms used among adolescents (Generation Zs, age 13-17) and emerging adults (Millennials, age 18-35) attending outpatient substance use treatment and to examine receptiveness toward these platforms in order to support substance use treatment and recovery. METHODS: Generation Zs and Millennials enrolled in outpatient substance use treatment (n=164) completed a survey examining social media use, digital intervention acceptability, frequency of substance exposure, and substance use experiences. Generation Zs (n=53) completed the survey in July 2018. Millennials (n=111) completed the survey in May 2016. RESULTS: Generation Zs had an average age of 15.66 (SD 1.18) years and primarily identified as male (50.9%). Millennials had an average age of 27.66 (SD 5.12) years and also primarily identified as male (75.7%). Most participants owned a social media account (Millennials: 82.0%, Generation Zs: 94.3%) and used it daily (Millennials: 67.6%, Generation Zs: 79.2%); however, Generation Zs were more likely to use Instagram and Snapchat, whereas Millennials were more likely to use Facebook. Further, Generation Zs were more likely to use the features within social media platforms (eg, instant messaging: Millennials: 55.0%, Generation Zs: 79.2%; watching videos: Millennials: 56.8%, Generation Zs: 81.1%). Many participants observed drug cues on social media (Millennials: 67.5%, Generation Zs: 71.7%). However, fewer observed recovery information on social media (Millennials: 30.6%, Generation Zs: 34.0%). Participants felt that social media (Millennials: 55.0%, Generation Zs: 49.1%), a mobile phone app (Millennials: 36.9%, Generation Zs: 45.3%), texting (Millennials: 28.8%, Generation Zs: 45.3%), or a website (Millennials: 39.6%, Generation Zs: 32.1%) would be useful in delivering recovery support. CONCLUSIONS: Given the high rates of exposure to drug cues on social media, disseminating recovery support within a social media platform may be the ideal just-in-time intervention needed to decrease the rates of recurrent drug use. However, our results suggest that cross-platform solutions capable of transcending generational preferences are necessary and one-size-fits-all digital interventions should be avoided.

Meta-Analysis of the Association of Alcohol-Related Social Media Use with Alcohol Consumption and Alcohol-Related Problems in Adolescents and Young Adults.

Despite the pervasive use of social media by young adults, there is comparatively little known about whether, and how, engagement in social media influences this group's drinking patterns and risk of alcohol-related problems. We examined the relations between young adults' alcohol-related social media engagement (defined as the posting, liking, commenting, and viewing of alcohol-related social media content) and their drinking behavior and problems. We conducted a systematic review and meta-analysis of studies evaluating the association of alcohol consumption and alcohol-related problems with alcohol-related social media engagement. Summary baseline variables regarding the social media platform used (e.g., Facebook and Twitter), social media measures assessed (e.g., number of alcohol photographs posted), alcohol measures (e.g., Alcohol Use Disorders Identification Test and Timeline Follow back Interview), and the number of time points at which data were collected were extracted from each published study. We used the Q statistic to examine heterogeneity in the correlations between alcohol-related social media engagement and both drinking behavior and alcohol-related problems. Because there was significant heterogeneity, we used a random-effects model to evaluate the difference from zero of the weighted aggregate correlations. We used metaregression with study characteristics as moderators to test for moderators of the observed heterogeneity. Following screening, 19 articles met inclusion criteria for the meta-analysis. The primary findings indicated a statistically significant relationship and moderate effect sizes between alcohol-related social media engagement and both alcohol consumption (r = 0.36, 95% CI: 0.29 to 0.44, p < 0.001) and alcohol-related problems (r = 0.37, 95% CI: 0.21 to 0.51, p < 0.001). There was significant heterogeneity among studies. Two significant predictors of heterogeneity were (i) whether there was joint measurement of alcohol-related social media engagement and drinking behavior or these were measured on different occasions and (ii) whether measurements were taken by self-report or observation of social media engagement. We found moderate-sized effects across the 19 studies: Greater alcohol-related social media engagement was correlated with both greater self-reported drinking and alcohol-related problems. Further research to determine the causal direction of these associations could provide opportunities for social media-based interventions with young drinkers aimed at reducing alcohol consumption and alcohol-related adverse consequences.

A review of guidelines on home drug testing web sites for parents.

OBJECTIVES: To update and extend prior work reviewing Web sites that discuss home drug testing for parents, and assess the quality of information that the Web sites provide, to assist them in deciding when and how to use home drug testing. METHODS: We conducted a worldwide Web search that identified 8 Web sites providing information for parents on home drug testing. We assessed the information on the sites using a checklist developed with field experts in adolescent substance abuse and psychosocial interventions that focus on urine testing. RESULTS: None of the Web sites covered all the items on the 24-item checklist, and only 3 covered at least half of the items (12, 14, and 21 items, respectively). The remaining 5 Web sites covered less than half of the checklist items. The mean number of items covered by the Web sites was 11. CONCLUSIONS: Among the Web sites that we reviewed, few provided thorough information to parents regarding empirically supported strategies to effectively use drug testing to intervene on adolescent substance use. Furthermore, most Web sites did not provide thorough information regarding the risks and benefits to inform parents' decision to use home drug testing. Empirical evidence regarding efficacy, benefits, risks, and limitations of home drug testing is needed.

Social networking and online recruiting for HIV research: ethical challenges.

Social networking sites and online advertising organizations provide HIV/AIDS researchers access to target populations, often reaching difficult-to-reach populations. However, this benefit to researchers raises many issues for the protections of prospective research participants. Traditional recruitment procedures have involved straightforward transactions between the researchers and prospective participants; online recruitment is a more complex and indirect form of communication involving many parties engaged in the collecting, aggregating, and storing of research participant data. Thus, increased access to online data has challenged the adequacy of current and established procedures for participants' protections, such as informed consent and privacy/confidentiality. Internet-based HIV/AIDS research recruitment and its ethical challenges are described, and research participant safeguards and best practices are outlined.

Translating SBIRT to public school settings: an initial test of feasibility.

Public schools are not traditional locations where screening, brief motivational counseling intervention and referral to treatment (SBIRT) are provided. This translational research study aimed to test the feasibility of conducting SBIRT in two urban New York schools and to examine its economic sustainability. In Spring 2012, 248 students were screened during non-academic classes: 42% of them (n=105) reported substance use (versus 28% reported in school-wide, paper anonymous survey). All but one of the positively screened students voluntarily accepted one or more brief intervention sessions and two students were referred to treatment. This school-based SBIRT model did not interfere with academic activities, was feasible to implement, and was attractive to students, teachers and administration. The data offer clear indication that further effectiveness testing is warranted and potentially valuable, however the sustainability of this model was not supported due to our lack of obtaining insurance information, authorization and reimbursement.