Implementing Programs to Initiate Buprenorphine for Opioid Use Disorder Treatment in High-Need, Low-Resource Emergency Departments: A Nonrandomized Controlled Trial.

STUDY OBJECTIVE: We hypothesized that implementation facilitation would enable us to rapidly and effectively implement emergency department (ED)-initiated buprenorphine programs in rural and urban settings with high-need, limited resources and dissimilar staffing structures. METHODS: This multicenter implementation study employed implementation facilitation using a participatory action research approach to develop, introduce, and refine site-specific clinical protocols for ED-initiated buprenorphine and referral in 3 EDs not previously initiating buprenorphine. We assessed feasibility, acceptability, and effectiveness by triangulating mixed-methods formative evaluation data (focus groups/interviews and pre/post surveys involving staff, patients, and stakeholders), patients' medical records, and 30-day outcomes from a purposive sample of 40 buprenorphine-receiving patient-participants who met research eligibility criteria (English-speaking, medically stable, locator information, nonprisoners). We estimated the primary implementation outcome (proportion receiving ED-initiated buprenorphine among candidates) and the main secondary outcome (30-day treatment engagement) using Bayesian methods. RESULTS: Within 3 months of initiating the implementation facilitation activities, each site implemented buprenorphine programs. During the 6-month programmatic evaluation, there were 134 ED-buprenorphine candidates among 2,522 encounters involving opioid use. A total of 52 (41.6%) practitioners initiated buprenorphine administration to 112 (85.1%; 95% confidence interval [CI] 79.7% to 90.4%) unique patients. Among 40 enrolled patient-participants, 49.0% (35.6% to 62.5%) were engaged in addiction treatment 30 days later (confirmed); 26 (68.4%) reported attending one or more treatment visits; there was a 4-fold decrease in self-reported overdose events (odds ratio [OR] 4.03; 95% CI 1.27 to 12.75). The ED clinician readiness increased by a median of 5.02 (95% CI: 3.56 to 6.47) from 1.92/10 to 6.95/10 (n(pre)=80, n(post)=83). CONCLUSIONS: The implementation facilitation enabled us to effectively implement ED-based buprenorphine programs across heterogeneous ED settings rapidly, which was associated with promising implementation and exploratory patient-level outcomes.

Patient Engagement in a Multimodal Digital Phenotyping Study of Opioid Use Disorder.

BACKGROUND: Multiple digital data sources can capture moment-to-moment information to advance a robust understanding of opioid use disorder (OUD) behavior, ultimately creating a digital phenotype for each patient. This information can lead to individualized interventions to improve treatment for OUD. OBJECTIVE: The aim is to examine patient engagement with multiple digital phenotyping methods among patients receiving buprenorphine medication for OUD. METHODS: The study enrolled 65 patients receiving buprenorphine for OUD between June 2020 and January 2021 from 4 addiction medicine programs in an integrated health care delivery system in Northern California. Ecological momentary assessment (EMA), sensor data, and social media data were collected by smartphone, smartwatch, and social media platforms over a 12-week period. Primary engagement outcomes were meeting measures of minimum phone carry (≥8 hours per day) and watch wear (≥18 hours per day) criteria, EMA response rates, social media consent rate, and data sparsity. Descriptive analyses, bivariate, and trend tests were performed. RESULTS: The participants' average age was 37 years, 47% of them were female, and 71% of them were White. On average, participants met phone carrying criteria on 94% of study days, met watch wearing criteria on 74% of days, and wore the watch to sleep on 77% of days. The mean EMA response rate was 70%, declining from 83% to 56% from week 1 to week 12. Among participants with social media accounts, 88% of them consented to providing data; of them, 55% of Facebook, 54% of Instagram, and 57% of Twitter participants provided data. The amount of social media data available varied widely across participants. No differences by age, sex, race, or ethnicity were observed for any outcomes. CONCLUSIONS: To our knowledge, this is the first study to capture these 3 digital data sources in this clinical population. Our findings demonstrate that patients receiving buprenorphine treatment for OUD had generally high engagement with multiple digital phenotyping data sources, but this was more limited for the social media data. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.3389/fpsyt.2022.871916.

Automated Substance Use/Sexual Risk Reporting and HIV Test Acceptance Among Emergency Department Patients Aged 13-24 Years.

Despite federal guidelines, many adolescents and emerging adults are not offered HIV testing by their healthcare providers. As such, many-including those who may be at high-risk for contracting HIV given their sexual and/or substance use risk-are not routinely tested. The current study examines sexual risk and substance use among emergency department patients aged 13-24 years (n = 147), who completed an automated screening as part of a tablet-based intervention designed to increase HIV testing. Twenty seven percent (n = 39) of participants chose to test for HIV after completing the tablet-based intervention. Among this sample, sexual risk was a significant independent predictor of HIV testing (χ2 = 16.50, p < 0.001). Problem substance use (e.g. trying but failing to quit) also predicted testing (χ2 = 7.43, p < 0.01). When considering these behaviors together, analyses indicated that the effect of problem substance use (ß = 0.648, p = 0.154) on testing is explained by sexual risk behavior (ß = 1.425, p < 0.01). The study's findings underscore the value of using routine automated risk screenings to collect sensitive data from emergency department patients, followed by computer-based HIV test offers for adolescent youth. Our research indicates tablet-based interventions can facilitate more accurate reporting of sexual behavior and substance use, and can also potentially increase HIV test uptake among those at risk.

Large-scale analysis of test-retest reliabilities of self-regulation measures.

The ability to regulate behavior in service of long-term goals is a widely studied psychological construct known as self-regulation. This wide interest is in part due to the putative relations between self-regulation and a range of real-world behaviors. Self-regulation is generally viewed as a trait, and individual differences are quantified using a diverse set of measures, including self-report surveys and behavioral tasks. Accurate characterization of individual differences requires measurement reliability, a property frequently characterized in self-report surveys, but rarely assessed in behavioral tasks. We remedy this gap by (i) providing a comprehensive literature review on an extensive set of self-regulation measures and (ii) empirically evaluating test-retest reliability of this battery in a new sample. We find that dependent variables (DVs) from self-report surveys of self-regulation have high test-retest reliability, while DVs derived from behavioral tasks do not. This holds both in the literature and in our sample, although the test-retest reliability estimates in the literature are highly variable. We confirm that this is due to differences in between-subject variability. We also compare different types of task DVs (e.g., model parameters vs. raw response times) in their suitability as individual difference DVs, finding that certain model parameters are as stable as raw DVs. Our results provide greater psychometric footing for the study of self-regulation and provide guidance for future studies of individual differences in this domain.

Scale-up of Digital Innovations in Health Care: Expert Commentary on Enablers and Barriers.

Health care delivery is undergoing a rapid change from traditional processes toward the use of digital health interventions and personalized medicine. This movement has been accelerated by the COVID-19 crisis as a response to the need to guarantee access to health care services while reducing the risk of contagion. Digital health scale-up is now also vital to achieve population-wide impact: it will only accomplish sustainable effects if and when deployed into regular health care delivery services. The question of how sustainable digital health scale-up can be successfully achieved has, however, not yet been sufficiently resolved. This paper identifies and discusses enablers and barriers for scaling up digital health innovations. The results discussed in this paper were gathered by scientists and representatives of public bodies as well as patient organizations at an international workshop on scaling up digital health innovations. Results are explored in the context of prior research and implications for future work in achieving large-scale implementations that will benefit the population as a whole.

Technology-Delivered Intervention Strategies to Bolster HIV Testing.

Since the beginning of the HIV epidemic, there have been more than 75 million cases. Currently, there about 1.2 million living with HIV in the USA. Despite current testing recommendations, test rates continue to be suboptimal. Investigators have studied the use of digital technology to promote HIV testing, especially among high-risk populations. PURPOSE OF REVIEW: This non-systematic review provides an overview of the scientific research between 2015 and 2020 focused on the use of digital technology to bolster HIV testing and suggests novel technologies for exploration. RECENT FINDINGS: A total of 40 studies were included in the review that span a wide range of available technology. Studies effectively increased HIV testing among study participants. Generally, participants in the intervention/exposure groups had significantly higher rates of HIV test uptake compared to participants in the comparison groups at study follow-up. For a variety of reasons (e.g., differences in ways the technologies were used and study design), no digital tool clearly performed better than others, but each have the capacity to increase outreach and self-testing. An exploration of the potential use of nascent technologies is also discussed, as well as the authors' experiences using a number of these technologies in our research.

Comparing the feasibility of four web-based recruitment strategies to evaluate the treatment preferences of rural and urban adults who misuse non-prescribed opioids.

This cross-sectional study examined the feasibility of using four different web-based strategies to recruit rural and urban adults who use opioids non-medically for a survey on opioid use disorder (OUD) treatment preferences, and compared the treatment preferences of rural versus urban participants. Preferences for medication for opioid use disorder (MOUD) formulation and OUD treatment models were assessed through an online survey. Recruitment advertisements were shown on Facebook, Google AdWords, Reddit, and Amazon Mechanical Turk (MTurk). Participants were categorized by zip code into urban versus rural residence using the Centers for Medicaid and Medicaid Health Resources and Services Administration definitions. OUD treatment preferences were compared using chi-square and t-tests. Among the 851 participants recruited, 815 provided zip codes and were classified as residing in rural (n = 200, 24.5%) or urban (n = 615, 75.4%) regions. A crowdsourcing service (MTurk) recruited the most rural participants, while posts on a social news website (Reddit) recruited the most urban participants (χ23 = 17.0, p < 0.01). While preferred MOUD formulation and OUD treatment model did not differ by rurality, rural participants were more likely to report a willingness to receive OUD treatment integrated with general medical care (χ21 = 18.9, p < 0.0001). This study demonstrated that web-based strategies are feasible for recruiting rural adults who misuse opioids. Results suggest OUD treatment preferences largely did not differ by rural residence, and highlight the importance of enhancing the availability and increasing education about MOUD formulations in rural regions.

Feasibility of mHealth interventions for depressive symptoms in Latin America: a systematic review.

Depression is a prevalent disorder and leading cause of disability in Latin America, where the mental health treatment gap is still above 50%. We sought to synthesise and assess the quality of the evidence on the feasibility of mHealth-based interventions for depression in Latin America. We conducted a literature search of studies published in 2007 and after using four electronic databases. We included peer-reviewed articles, in English, Spanish or Portuguese, that evaluated interventions for depressive symptoms. Two authors independently extracted data using forms developed a priori. We assessed appropriateness of reporting utilising the CONSORT checklist for feasibility trials. Eight manuscripts were included for full data extraction. Appropriate reporting varied greatly. Most (n = 6, 75%) of studies were conducted in primary care settings and sought to deliver psychoeducation or behaviour change interventions for depressive symptoms. We found great heterogeneity in the assessment of feasibility. Two studies used comparator conditions. mHealth research for depression in Latin America is scarce. Included studies showed some feasibility despite methodological inconsistencies. Given the dire need for evidence-based mental health interventions in this region, governments and stakeholders must continue promoting and funding research tailored to cultural and population characteristics with subsequent pragmatic clinical trials.

Web-based cognitive behavior therapy for chronic pain patients with aberrant drug-related behavior: How did it work and for whom?

This study explored mediating pathways, moderating factors, and moderated mediation effects of a web-based, cognitive behavioral therapy (CBT) intervention for chronic pain patients with aberrant drug-related behavior (ADRB). In a 2-arm RCT, patients with chronic pain who screened positive for ADRB received treatment-as-usual (TAU, n = 55) or TAU plus a 12-week, web-based CBT intervention (n = 55). Assessments were conducted at weeks 4, 8, and 12, and at 1- and 3-months post intervention. Web-CBT significantly reduced pain catastrophizing, which, in turn, reduced pain interference and pain severity via a pathway of pain catastrophizing. Web-CBT also significantly reduced ADRB both directly and indirectly by reducing pain catastrophizing. For pain interference and pain severity, web-CBT was more effective than TAU for younger patients (≤ age 50). For pain severity, web-CBT was more effective for both younger patients (≤ age 50), and those with a lifetime substance use disorder. Findings suggest that web-CBT's positive impact on pain outcomes and ADRB are mediated by its effect on pain catastrophizing, and its treatment effects may be most robust for younger patients and those with histories of substance dependence.

Early implementation of screening for substance use in rural primary care: A rapid analytic qualitative study.

Background: Few primary care patients are screened for substance use. As part of a phased feasibility study examining the implementation of electronic health record-integrated screening with the Tobacco, Alcohol, and Prescription Medication Screening (TAPS) Tool and clinical decision support (CDS) in rural primary care clinics, focus groups were conducted to identify early indicators of success and challenges to screening implementation. Method: Focus groups (n = 6) were conducted with medical assistants (MAs: n = 3: 19 participants) and primary care providers (PCPs: n = 3: 13 participants) approximately one month following screening implementation in three Federally Qualified Health Centers in Maine. Rapid analysis and matrix analysis using Proctor's Taxonomy of Implementation Outcomes were used to explore implementation outcomes. Results: There was consensus that screening is being used, but use of the CDS was lower, in part due to limited positive screens. Fidelity was high among MAs, though discomfort with the CDS surfaced among PCPs, impacting adoption and fidelity. The TAPS Tool's content, credibility and ease of workflow integration were favorably assessed. Challenges include screening solely at annual visits and self-administered screening for certain patients. Conclusions: Results reveal indicators of implementation success and strategies to address challenges to screening for substance use in primary care.

Correlation Database of 60 Cross-Disciplinary Surveys and Cognitive Tasks Assessing Self-Regulation.

Self-regulation is studied across various disciplines, including personality, social, cognitive, health, developmental, and clinical psychology; psychiatry; neuroscience; medicine; pharmacology; and economics. Widespread interest in self-regulation has led to confusion regarding both the constructs within the nomological network of self-regulation and the measures used to assess these constructs. To facilitate the integration of cross-disciplinary measures of self-regulation, we estimated product-moment and distance correlations among 60 cross-disciplinary measures of self-regulation (23 self-report surveys, 37 cognitive tasks) and measures of health and substance use based on 522 participants. The correlations showed substantial variability, though the surveys demonstrated greater convergent validity than did the cognitive tasks. Variables derived from the surveys only weakly correlated with variables derived from the cognitive tasks (M = .049, range = .000 to .271 for the absolute value of the product-moment correlation; M = .085, range = .028 to .241 for the distance correlation), thus challenging the notion that these surveys and cognitive tasks measure the same construct. We conclude by outlining several potential uses for this publicly available database of correlations.

Perceived safety of cannabis intoxication predicts frequency of driving while intoxicated.

Driving under the influence of cannabis (DUIC) is a public health concern, and data are needed to develop screening and prevention tools. Measuring the level of intoxication that cannabis users perceive as safe for driving could help stratify DUIC risk. This study tested whether intoxication levels perceived as safe for driving predicted past-month DUIC frequency. Online survey data were collected in 2017 from a national sample of n = 3010 past-month cannabis users with lifetime DUIC (age 18+). Respondents indicated past-month DUIC frequency, typical cannabis intoxication level (1-10 scale), and cannabis intoxication level perceived as safe for driving (0-10 scale). Approximately 24%, 38%, 13%, and 24% of respondents engaged in DUIC on 0, 1-9, 10-19, and 20-30 days respectively in the past month. Among these four DUIC frequency groups, median typical intoxication varied little (5-6), but median intoxication perceived as safe for driving varied widely (3-8). Higher intoxication levels perceived as safe for driving corresponded to frequent DUIC (Spearman's rho: 0.46). For each unit increase in intoxication level perceived as safe for driving, the odds of past-month DUIC increased 18% to 68% (multinomial logistic regression odds ratio - MOR1-9 days: 1.18, 95% CI: 1.13-1.23; MOR10-19 days: 1.40, 95% CI: 1.30-1.50; MOR20-30 days: 1.68, 95% CI: 1.57-1.80). In this targeted sample of past-month cannabis users, DUIC frequency varied widely, but daily/near-daily DUIC was common (24%). Measuring intoxication levels perceived as safe for driving permits delineation of past-month DUIC frequency. This metric has potential as a component of public health prevention tools.

Delivering information about medication assisted treatment to individuals who misuse opioids through a mobile app: a pilot study.

BACKGROUND: Digital therapeutic tools (e.g. mobile applications) can be accessible, low-cost interventions that counter misconceptions about medication assisted treatment (MAT) and/or improve deficits in MAT knowledge that are common barriers to treatment entry among individuals with opioid dependence. The purpose of this pilot study was to examine the preliminary effectiveness of a mobile application, 'uMAT-R', that includes health information about OUD recovery supported by science and MAT benefits. METHODS: Twenty-six adult participants with OUD recruited via social media completed all modules and pre/post-assessments within uMAT-R. McNemar's test was used to compare interest in treatment before and after completing the app, and paired t tests were used to compare MAT attitude scores before and after completing the modules within uMAT-R. RESULTS: Before viewing uMAT-R, 32% agreed/strongly agreed that they were interested in starting treatment to recover from opioid misuse, compared to 48% after completing uMAT-R. The average scores on the MAT attitudes scale and its Aid to Behavior Change subscale improved from before to after viewing uMAT-R. Among the participants, 88% felt that uMAT-R would be useful to consult when making decisions about recovery. CONCLUSIONS: Our encouraging pilot findings support the use of uMAT-R to help address the current opioid epidemic.

Associations Between Substance Use and Instagram Participation to Inform Social Network-Based Screening Models: Multimodal Cross-Sectional Study.

BACKGROUND: Technology-based computational strategies that leverage social network site (SNS) data to detect substance use are promising screening tools but rely on the presence of sufficient data to detect risk if it is present. A better understanding of the association between substance use and SNS participation may inform the utility of these technology-based screening tools. OBJECTIVE: This paper aims to examine associations between substance use and Instagram posts and to test whether such associations differ as a function of age, gender, and race/ethnicity. METHODS: Participants with an Instagram account were recruited primarily via Clickworker (N=3117). With participant permission and Instagram's approval, participants' Instagram photo posts were downloaded with an application program interface. Participants' past-year substance use was measured with an adapted version of the National Institute on Drug Abuse Quick Screen. At-risk drinking was defined as at least one past-year instance having "had more than a few alcoholic drinks a day," drug use was defined as any use of nonprescription drugs, and prescription drug use was defined as any nonmedical use of prescription medications. We used logistic regression to examine the associations between substance use and any Instagram posts and negative binomial regression to examine the associations between substance use and number of Instagram posts. We examined whether age (18-25, 26-38, 39+ years), gender, and race/ethnicity moderated associations in both logistic and negative binomial models. All differences noted were significant at the .05 level. RESULTS: Compared with no at-risk drinking, any at-risk drinking was associated with both a higher likelihood of any Instagram posts and a higher number of posts, except among Hispanic/Latino individuals, in whom at-risk drinking was associated with a similar number of posts. Compared with no drug use, any drug use was associated with a higher likelihood of any posts but was associated with a similar number of posts. Compared with no prescription drug use, any prescription drug use was associated with a similar likelihood of any posts and was associated with a lower number of posts only among those aged 39 years and older. Of note, main effects showed that being female compared with being male and being Hispanic/Latino compared with being White were significantly associated with both a greater likelihood of any posts and a greater number of posts. CONCLUSIONS: Researchers developing computational substance use risk detection models using Instagram or other SNS data may wish to consider our findings showing that at-risk drinking and drug use were positively associated with Instagram participation, while prescription drug use was negatively associated with Instagram participation for middle- and older-aged adults. As more is learned about SNS behaviors among those who use substances, researchers may be better positioned to successfully design and interpret innovative risk detection approaches.

Perspectives, Experiences, and Practices in the Use of Digital Information Technologies in the Management of Depression and Alcohol Use Disorder in Health Care Systems in Colombia.

Digital information technologies are increasingly used in the treatment of mental health disorders. Through this qualitative study, researchers illuminated perspectives, experiences, and practices among diverse stakeholders in the use of digital information technologies in the management of depression and alcohol use disorders in Colombia. In-depth interviews and focus groups were conducted in five primary care institutions across Colombia. Thematic analysis was used to analyze the data. The use of technology in the treatment of mental health disorders can facilitate the evaluation and diagnosis, treatment, and promotion and prevention of mental health disorders, as well as multiple nonmental health applications in the primary care setting. Potential barriers to the use of technology in this setting include challenges of digital literacy, access to technology, confidentiality, and financing. This study can inform the implementation of digital information technologies in the care of depression and problematic alcohol use within health care systems in Colombia.

Assessing the Integration of Behavioral Health Services in Primary Care in Colombia.

Integration of behavioral health care into primary care can improve health and economic outcomes. This study adapted the Behavioral Health Integration in Medical Care (BHIMC) index to the Colombian context and assessed the baseline level of behavioral health integration in a sample of primary care organizations. The BHIMC was able to detect the capacity to provide integrated behavioral care in Colombian settings. Results indicate a minimal to partial integration level across all sites, and that it is possible to measure the degree of integrated care capacity and identify improvement areas for better behavioral health care provision.

Screening for Substance Use in Rural Primary Care: a Qualitative Study of Providers and Patients.

BACKGROUND: Substance use frequently goes undetected in primary care. Though barriers to implementing systematic screening for alcohol and drug use have been examined in urban settings, less is known about screening in rural primary care. OBJECTIVE: To identify current screening practices, barriers, facilitators, and recommendations for the implementation of substance use screening in rural federally qualified health centers (FQHCs). DESIGN: As part of a multi-phase study implementing electronic health record-integrated screening, focus groups (n = 60: all stakeholder groups) and individual interviews (n = 10 primary care providers (PCPs)) were conducted. PARTICIPANTS: Three stakeholder groups (PCPs, medical assistants (MAs), and patients) at three rural FQHCs in Maine. APPROACH: Focus groups and interviews were recorded, transcribed, and content analyzed. Themes surrounding current substance use screening practices, barriers to screening, and recommendations for implementation were identified and organized by the Knowledge to Action (KTA) Framework. KEY RESULTS: Identifying the problem: Stakeholders unanimously agreed that screening is important, and that universal screening is preferred to targeted approaches. Adapting to the local context: PCPs and MAs agreed that screening should be done annually. Views were mixed regarding the delivery of screening; patients preferred self-administered, tablet-based screening, while MAs and PCPs were divided between self-administered and face-to-face approaches. Assessing barriers: For patients, barriers to screening centered around a perceived lack of rapport with providers, which contributed to concerns about trust, judgment, and privacy. For PCPs and MAs, barriers included lack of comfort, training, and preparedness to address screening results and offer treatment. CONCLUSIONS: Though stakeholders agree on the importance of implementing universal screening, concerns about the patient-provider relationship, the consequences of disclosure, and privacy appear heightened by the rural context. Findings highlight that strong relationships with providers are critical for patients, while in-clinic resources and training are needed to increase provider comfort and preparedness to address substance use.

Web-Based Cognitive Behavior Therapy for Chronic Pain Patients with Aberrant Drug-Related Behavior: Outcomes from a Randomized Controlled Trial.

Objective: There is high unmet need for effective behavioral treatments for chronic pain patients at risk for or with demonstrated histories of opioid misuse. Despite growing evidence supporting technology-based delivery of self-management interventions for chronic pain, very few such programs target co-occurring chronic pain and aberrant drug-related behavior. This randomized controlled trial evaluated the effectiveness of a novel, web-based self-management intervention, grounded in cognitive behavior therapy, for chronic pain patients with aberrant drug-related behavior. Methods: Opioid-treated chronic pain patients at a specialty pain practice who screened positive for aberrant drug-related behavior (N = 110) were randomized to receive treatment as usual plus the web-based program or treatment as usual alone. The primary outcomes of pain severity, pain interference, and aberrant drug-related behavior, and the secondary outcomes of pain catastrophizing and pain-related emergency department visits, were assessed during the 12-week intervention and at one and three months postintervention. Results: Patients assigned to use the web-based program reported significantly greater reductions in aberrant drug-related behavior, pain catastrophizing, and pain-related emergency department visits-but not pain severity or pain interference-relative to those assigned to treatment as usual. The positive outcomes were observed during the 12-week intervention and for three months postintervention. Conclusions: A web-based self-management program, when delivered in conjunction with standard specialty pain treatment, was effective in reducing chronic pain patients' aberrant drug-related behavior, pain catastrophizing, and emergency department visits for pain. Technology-based self-management tools may be a promising therapeutic approach for the vulnerable group of chronic pain patients who have problems managing their opioid medication.

Exploring the Utility of Community-Generated Social Media Content for Detecting Depression: An Analytical Study on Instagram.

BACKGROUND: The content produced by individuals on various social media platforms has been successfully used to identify mental illness, including depression. However, most of the previous work in this area has focused on user-generated content, that is, content created by the individual, such as an individual's posts and pictures. In this study, we explored the predictive capability of community-generated content, that is, the data generated by a community of friends or followers, rather than by a sole individual, to identify depression among social media users. OBJECTIVE: The objective of this research was to evaluate the utility of community-generated content on social media, such as comments on an individual's posts, to predict depression as defined by the clinically validated Patient Health Questionnaire-8 (PHQ-8) assessment questionnaire. We hypothesized that the results of this research may provide new insights into next generation of population-level mental illness risk assessment and intervention delivery. METHODS: We created a Web-based survey on a crowdsourcing platform through which participants granted access to their Instagram profiles as well as provided their responses to PHQ-8 as a reference standard for depression status. After data quality assurance and postprocessing, the study analyzed the data of 749 participants. To build our predictive model, linguistic features were extracted from Instagram post captions and comments, including multiple sentiment scores, emoji sentiment analysis results, and meta-variables such as the number of likes and average comment length. In this study, 10.4% (78/749) of the data were held out as a test set. The remaining 89.6% (671/749) of the data were used to train an elastic-net regularized linear regression model to predict PHQ-8 scores. We compared different versions of this model (ie, a model trained on only user-generated data, a model trained on only community-generated data, and a model trained on the combination of both types of data) on a test set to explore the utility of community-generated data in our predictive analysis. RESULTS: The 2 models, the first trained on only community-generated data (area under curve [AUC]=0.71) and the second trained on a combination of user-generated and community-generated data (AUC=0.72), had statistically significant performances for predicting depression based on the Mann-Whitney U test (P=.03 and P=.02, respectively). The model trained on only user-generated data (AUC=0.63; P=.11) did not achieve statistically significant results. The coefficients of the models revealed that our combined data classifier effectively amalgamated both user-generated and community-generated data and that the 2 feature sets were complementary and contained nonoverlapping information in our predictive analysis. CONCLUSIONS: The results presented in this study indicate that leveraging community-generated data from social media, in addition to user-generated data, can be informative for predicting depression among social media users.

Implementing a Mobile Health System to Integrate the Treatment of Addiction Into Primary Care: A Hybrid Implementation-Effectiveness Study.

BACKGROUND: Despite the near ubiquity of mobile phones, little research has been conducted on the implementation of mobile health (mHealth) apps to treat patients in primary care. Although primary care clinicians routinely treat chronic conditions such as asthma and diabetes, they rarely treat addiction, a common chronic condition. Instead, addiction is most often treated in the US health care system, if it is treated at all, in a separate behavioral health system. mHealth could help integrate addiction treatment in primary care. OBJECTIVE: The objective of this paper was to report the effects of implementing an mHealth system for addiction in primary care on both patients and clinicians. METHODS: In this implementation research trial, an evidence-based mHealth system named Seva was introduced sequentially over 36 months to a maximum of 100 patients with substance use disorders (SUDs) in each of three federally qualified health centers (FQHCs; primary care clinics that serve patients regardless of their ability to pay). This paper reports on patient and clinician outcomes organized according to the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. RESULTS: The outcomes according to the RE-AIM framework are as follows: Reach-Seva reached 8.31% (268/3226) of appropriate patients. Reach was limited by our ability to pay for phones and data plans for a maximum of 100 patients per clinic. Effectiveness-Patients who were given Seva had significant improvements in their risky drinking days (44% reduction, (0.7-1.25)/1.25, P=.04), illicit drug-use days (34% reduction, (2.14-3.22)/3.22, P=.01), quality of life, human immunodeficiency virus screening rates, and number of hospitalizations. Through Seva, patients also provided peer support to one another in ways that are novel in primary care settings. Adoption-Patients sustained high levels of Seva use-between 53% and 60% of the patients at the 3 sites accessed Seva during the last week of the 12-month implementation period. Among clinicians, use of the technology was less robust than use by patients, with only a handful of clinicians using Seva in each clinic and behavioral health providers making most referrals to Seva in 2 of the 3 clinics. Implementation-At 2 sites, implementation plans were realized successfully; they were delayed in the third. Maintenance-Use of Seva dropped when grant funding stopped paying for the mobile phones and data plans. Two of the 3 clinics wanted to maintain the use of Seva, but they struggled to find funding to support this. CONCLUSIONS: Implementing an mHealth system can improve care among primary care patients with SUDs, and patients using the system can support one another in their recovery. Among clinicians, however, implementation requires figuring out how information from the mHealth system will be used and making mHealth data available in the electronic health (eHealth) record. In addition, paying for an mHealth system remains a challenge.