Evaluating preferences for medication formulation and treatment model among people who use opioids non-medically: A web-based cross-sectional study.

INTRODUCTION: Over the past decade, treatment for opioid use disorder has expanded to include long-acting injectable and implantable formulations of medication for opioid use disorder (MOUD), and integrated treatment models systematically addressing both behavioral and physical health. Patient preference for these treatment options has been underexplored. Gathering data on OUD treatment preferences is critical to guide the development of patient-centered treatment for OUD. This cross-sectional study assessed preferences for long-acting MOUD and integrated treatment using an online survey. METHODS: An online Qualtrics survey assessed preferences for MOUD formulation and integrated treatment models. The study recruited participants (n = 851) in October and November 2019 through advertisements or posts on Facebook, Google AdWords, Reddit, and Amazon Mechanical Turk (mTurk). Eligible participants scored a two or higher on the opioid pain reliever or heroin scales of the Tobacco, Alcohol Prescription Medication and other Substance Use (TAPS) Tool. Structured survey items obtained patient preference for MOUD formulation and treatment model. Using stated preference methods, the study assessed preference via comparison of preferred options for MOUD and treatment model. RESULTS: In the past year, 824 (96.8 %) participants reported non-prescribed use of opioid pain relievers (mean TAPS score = 2.72, SD = 0.46) and 552 (64.9 %) reported heroin or fentanyl use (mean TAPS score = 2.73, SD = 0.51). Seventy-four percent of participants (n = 631) reported currently or previously receiving OUD treatment, with 407 (48.4 %) receiving MOUD. When asked about preferences for type of MOUD formulation, 452 (53.1 %) preferred a daily oral formulation, 115 (13.5 %) preferred an implant, 114 (13.4 %) preferred a monthly injection and 95 (11.2 %) preferred a weekly injection. Approximately 8.8 % (n = 75) would not consider MOUD regardless of formulation. The majority of participants (65.2 %, n = 555) preferred receiving treatment in a specialized substance use treatment program distinct from their medical care, compared with receiving care in an integrated model (n = 296, 34.8 %). CONCLUSIONS: Though most participants expressed willingness to try long-acting MOUD formulations, the majority preferred short-acting formulations. Likewise, the majority preferred non-integrated treatment in specialty substance use settings. Reasons for these preferences provide insight on developing effective educational tools for patients and suggesting targets for intervention to develop a more acceptable treatment system.

Momentary Self-regulation: Scale Development and Preliminary Validation.

BACKGROUND: Self-regulation refers to a person's ability to manage their cognitive, emotional, and behavioral processes to achieve long-term goals. Most prior research has examined self-regulation at the individual level; however, individual-level assessments do not allow the examination of dynamic patterns of intraindividual variability in self-regulation and thus cannot aid in understanding potential malleable processes of self-regulation that may occur in response to the daily environment. OBJECTIVE: This study aims to develop a brief, psychometrically sound momentary self-regulation scale that can be practically administered through participants' mobile devices at a momentary level. METHODS: This study was conducted in 2 phases. In the first phase, in a sample of 522 adults collected as part of a larger self-regulation project, we examined 23 previously validated assessments of self-regulation containing 594 items in total to evaluate the underlying structure of self-regulation via exploratory and confirmatory factor analyses. We then selected 20 trait-level items to be carried forward to the second phase. In the second phase, we converted each item into a momentary question and piloted the momentary items in a sample of 53 adults over 14 days. Using the results from the momentary pilot study, we explored the psychometric properties of the items and assessed their underlying structure. We then proposed a set of subscale and total score calculations. RESULTS: In the first phase, the selected individual-level items appeared to measure 4 factors of self-regulation. The factors identified were perseverance, sensation seeking, emotion regulation, and mindfulness. In the second phase of the ecological momentary assessment pilot, the selected items demonstrated strong construct validity as well as predictive validity for health risk behaviors. CONCLUSIONS: Our findings provide preliminary evidence for a 12-item momentary self-regulation scale comprising 4 subscales designed to capture self-regulatory dynamics at the momentary level.

Momentary Influences on Self-Regulation in Two Populations With Health Risk Behaviors: Adults Who Smoke and Adults Who Are Overweight and Have Binge-Eating Disorder.

Introduction: Self-regulation has been implicated in health risk behaviors and is a target of many health behavior interventions. Despite most prior research focusing on self-regulation as an individual-level trait, we hypothesize that self-regulation is a time-varying mechanism of health and risk behavior that may be influenced by momentary contexts to a substantial degree. Because most health behaviors (e.g., eating, drinking, smoking) occur in the context of everyday activities, digital technologies may help us better understand and influence these behaviors in real time. Using a momentary self-regulation measure, the current study (which was part of a larger multi-year research project on the science of behavior change) used ecological momentary assessment (EMA) to assess if self-regulation can be engaged and manipulated on a momentary basis in naturalistic, non-laboratory settings. Methods: This one-arm, open-label exploratory study prospectively collected momentary data for 14 days from 104 participants who smoked regularly and 81 participants who were overweight and had binge-eating disorder. Four times per day, participants were queried about momentary self-regulation, emotional state, and social and environmental context; recent smoking and exposure to smoking cues (smoking sample only); and recent eating, binge eating, and exposure to binge-eating cues (binge-eating sample only). This study used a novel, momentary self-regulation measure comprised of four subscales: momentary perseverance, momentary sensation seeking, momentary self-judgment, and momentary mindfulness. Participants were also instructed to engage with Laddr, a mobile application that provides evidence-based health behavior change tools via an integrated platform. The association between momentary context and momentary self-regulation was explored via mixed-effects models. Exploratory assessments of whether recent Laddr use (defined as use within 12 h of momentary responses) modified the association between momentary context and momentary self-regulation were performed via mixed-effects models. Results: Participants (mean age 35.2; 78% female) in the smoking and binge-eating samples contributed a total of 3,233 and 3,481 momentary questionnaires, respectively. Momentary self-regulation subscales were associated with several momentary contexts, in the combined as well as smoking and binge-eating samples. For example, in the combined sample momentary perseverance was associated with location, positively associated with positive affect, and negatively associated with negative affect, stress, and tiredness. In the smoking sample, momentary perseverance was positively associated with momentary difficulty in accessing cigarettes, caffeine intake, and momentary restraint in smoking, and negatively associated with temptation and urge to smoke. In the binge-eating sample, momentary perseverance was positively associated with difficulty in accessing food and restraint in eating, and negatively associated with urge to binge eat. While recent Laddr use was not associated directly with momentary self-regulation subscales, it did modify several of the contextual associations, including challenging contexts. Conclusions: Overall, this study provides preliminary evidence that momentary self-regulation may vary in response to differing momentary contexts in samples from two exemplar populations with risk behaviors. In addition, the Laddr application may modify some of these relationships. These findings demonstrate the possibility of measuring momentary self-regulation in a trans-diagnostic way and assessing the effects of momentary, mobile interventions in context. Health behavior change interventions may consider measuring and targeting momentary self-regulation in addition to trait-level self-regulation to better understand and improve health risk behaviors. This work will be used to inform a later stage of research focused on assessing the transdiagnostic mediating effect of momentary self-regulation on medical regimen adherence and health outcomes. Clinical Trial Registration: ClinicalTrials.gov, Identifier: NCT03352713.

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.

Evaluating the Effectiveness of a Web-Based Program (POP4Teens) to Prevent Prescription Opioid Misuse Among Adolescents: Randomized Controlled Trial.

BACKGROUND: Prescription opioid (PO) use is common among adolescents in the United States. Despite recent declines from unprecedented peaks in adolescent PO use (eg, in 2012-2013), there is seemingly paradoxical evidence that PO-related consequences (eg, opioid use disorder and overdoses) are increasing. These trends and their possible consequences emphasize the importance of prevention efforts targeting PO misuse. To our knowledge, we have developed the first interactive web-based program (POP4Teens [P4T]) focused specifically on the prevention of PO misuse among adolescents. OBJECTIVE: This study aimed to evaluate the effectiveness of P4T, a web-based program designed to prevent adolescent PO misuse, in comparison with JustThinkTwice (JTT), an active control website, on PO-related attitudes, knowledge, risk perception, and intentions to use. METHODS: We conducted a web-based randomized controlled trial in 2018. A total of 406 adolescents (aged 12-17 years) were randomly assigned to either P4T or JTT. The outcome variables were attitudes, knowledge, and risk perceptions associated with PO misuse, intentions to use POs, and program feedback. Data were collected at baseline and at 1, 3, and 6 months. RESULTS: Both programs resulted in significant and sustained improvements in intention to use POs, increased perceived risk, impacted expectancies consistent with prevention, and improved PO refusal skills. P4T produced significantly greater increases in PO-related knowledge than JTT did, and it was reportedly easier to use and more liked. Baseline scores for youth reporting past-year medical use of POs, friends who engage in nonmedical use of POs, and/or poor mental health underscored their at-risk status compared with youth from the other groups. CONCLUSIONS: P4T positively impacted all study variables that are known to prevent PO misuse among teens. Moreover, its web-based nature simplifies the dissemination and implementation of this novel tool designed to help meet the challenges of the evolving national opioid crisis. TRIAL REGISTRATION: ClinicalTrials.gov NCT02737696; https://clinicaltrials.gov/ct2/show/NCT02737696.

"It's way more than just writing a prescription": A qualitative study of preferences for integrated versus non-integrated treatment models among individuals with opioid use disorder.

BACKGROUND: Increasingly, treatment for opioid use disorder (OUD) is offered in integrated treatment models addressing both substance use and other health conditions within the same system. This often includes offering medications for OUD in general medical settings. It remains uncertain whether integrated OUD treatment models are preferred to non-integrated models, where treatment is provided within a distinct treatment system. This study aimed to explore preferences for integrated versus non-integrated treatment models among people with OUD and examine what factors may influence preferences. METHODS: This qualitative study recruited participants (n = 40) through Craigslist advertisements and flyers posted in treatment programs across the United States. Participants were 18 years of age or older and scored a two or higher on the heroin or opioid pain reliever sections of the Tobacco, Alcohol, Prescription Medications, and Other Substances (TAPS) Tool. Each participant completed a demographic survey and a telephone interview. The interviews were coded and content analyzed. RESULTS: While some participants preferred receiving OUD treatment from an integrated model in a general medical setting, the majority preferred non-integrated models. Some participants preferred integrated models in theory but expressed concerns about stigma and a lack of psychosocial services. Tradeoffs between integrated and non-integrated models were centered around patient values (desire for anonymity and personalization, fear of consequences), the characteristics of the provider and setting (convenience, perceived treatment effectiveness, access to services), and the patient-provider relationship (disclosure, trust, comfort, stigma). CONCLUSIONS: Among this sample of primarily White adults, preferences for non-integrated versus integrated OUD treatment were mixed. Perceived benefits of integrated models included convenience, potential for treatment personalization, and opportunity to extend established relationships with medical providers. Recommendations to make integrated treatment more patient-centered include facilitating access to psychosocial services, educating patients on privacy, individualizing treatment, and prioritizing the patient-provider relationship. This sample included very few minorities and thus findings may not be fully generalizable to the larger population of persons with OUD. Nonetheless, results suggest a need for expansion of both OUD treatment in specialty and general medical settings to ensure access to preferred treatment for all.

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.

Predicting Early Warning Signs of Psychotic Relapse From Passive Sensing Data: An Approach Using Encoder-Decoder Neural Networks.

BACKGROUND: Schizophrenia spectrum disorders (SSDs) are chronic conditions, but the severity of symptomatic experiences and functional impairments vacillate over the course of illness. Developing unobtrusive remote monitoring systems to detect early warning signs of impending symptomatic relapses would allow clinicians to intervene before the patient's condition worsens. OBJECTIVE: In this study, we aim to create the first models, exclusively using passive sensing data from a smartphone, to predict behavioral anomalies that could indicate early warning signs of a psychotic relapse. METHODS: Data used to train and test the models were collected during the CrossCheck study. Hourly features derived from smartphone passive sensing data were extracted from 60 patients with SSDs (42 nonrelapse and 18 relapse >1 time throughout the study) and used to train models and test performance. We trained 2 types of encoder-decoder neural network models and a clustering-based local outlier factor model to predict behavioral anomalies that occurred within the 30-day period before a participant's date of relapse (the near relapse period). Models were trained to recreate participant behavior on days of relative health (DRH, outside of the near relapse period), following which a threshold to the recreation error was applied to predict anomalies. The neural network model architecture and the percentage of relapse participant data used to train all models were varied. RESULTS: A total of 20,137 days of collected data were analyzed, with 726 days of data (0.037%) within any 30-day near relapse period. The best performing model used a fully connected neural network autoencoder architecture and achieved a median sensitivity of 0.25 (IQR 0.15-1.00) and specificity of 0.88 (IQR 0.14-0.96; a median 108% increase in behavioral anomalies near relapse). We conducted a post hoc analysis using the best performing model to identify behavioral features that had a medium-to-large effect (Cohen d>0.5) in distinguishing anomalies near relapse from DRH among 4 participants who relapsed multiple times throughout the study. Qualitative validation using clinical notes collected during the original CrossCheck study showed that the identified features from our analysis were presented to clinicians during relapse events. CONCLUSIONS: Our proposed method predicted a higher rate of anomalies in patients with SSDs within the 30-day near relapse period and can be used to uncover individual-level behaviors that change before relapse. This approach will enable technologists and clinicians to build unobtrusive digital mental health tools that can predict incipient relapse in SSDs.

Using behavioral rhythms and multi-task learning to predict fine-grained symptoms of schizophrenia.

Schizophrenia is a severe and complex psychiatric disorder with heterogeneous and dynamic multi-dimensional symptoms. Behavioral rhythms, such as sleep rhythm, are usually disrupted in people with schizophrenia. As such, behavioral rhythm sensing with smartphones and machine learning can help better understand and predict their symptoms. Our goal is to predict fine-grained symptom changes with interpretable models. We computed rhythm-based features from 61 participants with 6,132 days of data and used multi-task learning to predict their ecological momentary assessment scores for 10 different symptom items. By taking into account both the similarities and differences between different participants and symptoms, our multi-task learning models perform statistically significantly better than the models trained with single-task learning for predicting patients' individual symptom trajectories, such as feeling depressed, social, and calm and hearing voices. We also found different subtypes for each of the symptoms by applying unsupervised clustering to the feature weights in the models. Taken together, compared to the features used in the previous studies, our rhythm features not only improved models' prediction accuracy but also provided better interpretability for how patients' behavioral rhythms and the rhythms of their environments influence their symptom conditions. This will enable both the patients and clinicians to monitor how these factors affect a patient's condition and how to mitigate the influence of these factors. As such, we envision that our solution allows early detection and early intervention before a patient's condition starts deteriorating without requiring extra effort from patients and clinicians.

Workshop on the Development and Evaluation of Digital Therapeutics for Health Behavior Change: Science, Methods, and Projects.

The health care field has integrated advances into digital technology at an accelerating pace to improve health behavior, health care delivery, and cost-effectiveness of care. The realm of behavioral science has embraced this evolution of digital health, allowing for an exciting roadmap for advancing care by addressing the many challenges to the field via technological innovations. Digital therapeutics offer the potential to extend the reach of effective interventions at reduced cost and patient burden and to increase the potency of existing interventions. Intervention models have included the use of digital tools as supplements to standard care models, as tools that can replace a portion of treatment as usual, or as stand-alone tools accessed outside of care settings or direct to the consumer. To advance the potential public health impact of this promising line of research, multiple areas warrant further development and investigation. The Center for Technology and Behavioral Health (CTBH), a P30 Center of Excellence supported by the National Institute on Drug Abuse at the National Institutes of Health, is an interdisciplinary research center at Dartmouth College focused on the goal of harnessing existing and emerging technologies to effectively develop and deliver evidence-based interventions for substance use and co-occurring disorders. The CTBH launched a series of workshops to encourage and expand multidisciplinary collaborations among Dartmouth scientists and international CTBH affiliates engaged in research related to digital technology and behavioral health (eg, addiction science, behavioral health intervention, technology development, computer science and engineering, digital security, health economics, and implementation science). This paper summarizes a workshop conducted on the Development and Evaluation of Digital Therapeutics for Behavior Change, which addressed (1) principles of behavior change, (2) methods of identifying and testing the underlying mechanisms of behavior change, (3) conceptual frameworks for optimizing applications for mental health and addictive behavior, and (4) the diversity of experimental methods and designs that are essential to the successful development and testing of digital therapeutics. Examples were presented of ongoing CTBH projects focused on identifying and improving the measurement of health behavior change mechanisms and the development and evaluation of digital therapeutics. In summary, the workshop showcased the myriad research targets that will be instrumental in promoting and accelerating progress in the field of digital health and health behavior change and illustrated how the CTBH provides a model of multidisciplinary leadership and collaboration that can facilitate innovative, science-based efforts to address the health behavior challenges afflicting our communities.

Perceptions and preferences for long-acting injectable and implantable medications in comparison to short-acting medications for opioid use disorders.

Aim: Treatment for opioid use disorders has recently evolved to include long-acting injectable and implantable formulations of medications for opioid use disorder (MOUD). Incorporating patient preferences into treatment for substance use disorders is associated with increased motivation and treatment satisfaction. This study sought to assess treatment preferences for long-acting injectable and implantable MOUD as compared to short-acting formulations among individuals with OUD. Methods: We conducted qualitative, semi-structured telephone interviews with forty adults recruited from across the United States through Craigslist advertisements and flyers posted in treatment programs. Eligible participants scored a two or greater on the heroin or opioid pain reliever sections of the Tobacco, Alcohol, Prescription Medications, and Other Substances (TAPS) Tool, indicative of a past-year OUD. Interviews were transcribed, coded, and thematically analyzed. Results: Twenty-four participants (60%) currently or previously had been prescribed MOUD. Sixteen participants (40%) expressed general opposition to MOUD, citing concerns that MOUD is purely financial gain for pharmaceutical companies and/or a "band aid" solution replacing one drug with another, rather than a path to abstinence. Some participants expressed personal preference for long-acting injectable (n = 16/40: 40%) and implantable formulations (n = 12/40: 30%) over short-acting formulations. About half of the participants were not willing to use injectables (n = 19/40: 48%) or implantables (n = 22/40: 55%), preferring short-acting formulations. Mixed evaluations of long- and short-acting MOUD focused on considerations of medication-related beliefs (privacy, concern over an embedded foreign body), the medication-related burden (convenience, provision of structure and support, medication administration, potential side effects), and medication-taking practices (potential for non-prescribed use, control over dosage, and duration of treatment). Conclusions: Though many participants personally prefer short-acting to long-acting MOUD, some were open to including long-acting formulations in the range of options for those with OUD. Participants felt long-acting formulations may reduce medication-related burden and the risk of diversion. Conversely, participants expressed concern about invasive administration and loss of control over their treatment. Results suggest support for expanded access to a variety of formulations of MOUD. The use of shared decision making may also help patients select the formulation best aligned with their experiences, values, and treatment goals.

Working memory training and high magnitude incentives for youth cannabis use: A SMART pilot trial.

The purpose of this sequential multiple-assignment randomization treatment pilot study was to examine if (a) adding working memory training to contingency management (CM) for youth with cannabis use disorder (CUD) and (b) switching nonresponding youth to higher magnitude CM incentives boosts outcomes. In Phase 1, youth with CUD (n = 59, M age = 16, male = 71%) attending an intensive outpatient program were randomly assigned to 14 weeks of CM only or CM plus working memory training (WMT). In Week 4, a Phase 2 treatment was assigned. Those with negative urine drug tests (responders) continued in their Phase 1 treatment. Those who were drug positive (nonresponders) were randomly assigned to remain in their Phase 1 treatment or to higher magnitude CM. Zero-inflated negative binomial models comparing those assigned to CM versus CM + WMT indicated no differences in the likelihood of having ≥ 1 week of continuous abstinence or longer abstinence duration. Those assigned to WMT showed greater but nonsignificant improvements in working memory (n = 35; ß = .69, p = .06). Working memory improvements were associated with achieving any abstinence (odds ratio = 3.50, 95% CI [1.01, 12.10], p = .05). Phase 2 randomization to higher magnitude CM did not boost outcomes. Overall results suggest that WMT appears promising, but the sample size was small, attrition was high, and replication is important. Alternative strategies should continue to be explored to improve outcomes for adolescent substance use disorders, such as different approaches for nonresponders, tailoring to other baseline or response characteristics, or more robust first-line interventions. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

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.

Item Response Theory Analysis of the Five Facet Mindfulness Questionnaire and its Short Forms.

OBJECTIVES: The Five Facet Mindfulness Questionnaire (FFMQ) is a self-report measure of mindfulness with forms of several different lengths, including the FFMQ-39, FFMQ-24, and FFMQ-15. We use item response theory analysis to directly compare the functioning of these three forms. METHODS: Data were drawn from a non-clinical Amazon Mechanical Turk study (N = 522) and studies of aftercare treatment of individuals with substance use disorders (combined N = 454). The item and test functioning of the three FFMQ forms were studied and compared. RESULTS: All 39 items were strongly related to the facet latent variables, and the items discriminated over a similar range of the latent mindfulness constructs. Items provided more information in the low to medium range of latent mindfulness than in the high range. Scores in three of the five FFMQ-39 facets were unreliable when measuring individuals in the high range of latent mindfulness, resulting from ceiling effects in item responses. Reliability in the high range of mindfulness was further reduced in the FFMQ-24 and FFMQ-15, such that short forms may be ill-suited for applications that require reliable measurement in the high range. CONCLUSIONS: Results suggest the existing FFMQ item pool cannot be reduced without negatively affecting either overall reliability or the span of mindfulness over which reliability is assessed. Conditional test reliability curves and item functioning parameters can aid investigators in tailoring their choice of FFMQ form to the reliability they hope to achieve and to the range of latent mindfulness over which they must reliably measure.

Capturing behavioral indicators of persecutory ideation using mobile technology.

Most existing measures of persecutory ideation (PI) rely on infrequent in-person visits, and this limits their ability to assess rapid changes or real-world functioning. Mobile health (mHealth) technology may address these limitations. Little is known about passively sensed behavioral indicators associated with PI. In the current study, sixty-two participants with schizophrenia spectrum disorders completed momentary assessments of PI on a smartphone that also passively collected behavioral data for one year. Results suggested that PI was prevalent (n = 50, 82% of sample) but had infrequent incidence (25.2% of EMA responses). PI was also associated with changes in several passively sensed variables, including decreases in distance traveled (Mkilometers = -1.20, SD = 18.88), time spent in a vehicle (Mminutes = -4.15, SD = 49.59), length of outgoing phone calls (Mminutes = -0.79, SD = 13.13), time spent proximal to human speech (Mminutes = -6.26, SD = 153.03), and an increase in time sitting still (Mminutes = 4.04, SD = 94.69). The present study suggests changes associated with PI may be detectable by passive sensors, including reductions in moving or traveling, and time spent around others or in self-initiated phone conversations. These constructs might constitute risk for PI.

Relationships between smartphone social behavior and relapse in schizophrenia: A preliminary report.

Social dysfunction is a hallmark of schizophrenia. Social isolation may increase individuals' risk for psychotic symptom exacerbation and relapse. Monitoring and timely detection of shifts in social functioning are hampered by the limitations of traditional clinic-based assessment strategies. Ubiquitous mobile technologies such as smartphones introduce new opportunities to capture objective digital indicators of social behavior. The goal of this study was to evaluate whether smartphone-collected digital measures of social behavior can provide early indication of relapse events among individuals with schizophrenia. Sixty-one individuals with schizophrenia with elevated risk for relapse were given smartphones with the CrossCheck behavioral sensing system for a year of remote monitoring. CrossCheck leveraged the device's microphone, call record, and text messaging log to capture digital socialization data. Relapse events including psychiatric hospitalizations, suicidal ideation, and significant psychiatric symptom exacerbations were recorded by trained assessors. Exploratory mixed effects models examined relationships of social behavior to relapse, finding that reductions in number and duration of outgoing calls, as well as number of text messages were associated with relapses. Number and duration of incoming phone calls and in-person conversations were not. Smartphone enabled social activity may provide an important metric in determining relapse risk in schizophrenia and provide access to sensitive, meaningful and ecologically valid data streams never before available in routine care.

Incentivizing healthy lifestyle behaviors to reduce cardiovascular risk in people with serious mental illness: An equipoise randomized controlled trial of the wellness incentives program.

BACKGROUND: Medicaid recipients with serious mental illness die 25-30 years earlier than people in the general population due to health conditions that are modifiable through lifestyle changes. Cardiovascular diseases from excess weight, smoking, and sedentary lifestyle contribute substantially to this life expectancy disparity. The current study evaluated the impact of incentives on participation in weight management programming (for overweight and obese adults) and smoking cessation treatment (for regular smokers). METHODS: Participants were Medicaid recipients with disabling mental illness receiving services at any one of 10 community mental health centers across New Hampshire. Using an equipoise stratified randomized design, n = 1348 were enrolled and assigned to one of four weight management programs (Healthy Choices Healthy Changes: HCHC) and n = 661 were enrolled and assigned to one of three smoking cessation interventions (Breathe Well Live Well: BWLW). Following assignment to an intervention, participants were randomized to receive financial incentives (to attend weight management programs, or to achieve abstinence from smoking) or not. Data were collected at baseline and every 3 months for 12 months. DISCUSSION: New Hampshire's HCHC and BWLW programs were designed to address serious and preventable health disparities by providing incentivized health promotion programs to overweight/obese and/or tobacco-smoking Medicaid beneficiaries with mental illness. This study was an unprecedented opportunity to evaluate an innovative statewide implementation of incentivized health promotion targeting the most at-risk and costly beneficiaries. If proven effective, this program has the potential to serve as a national model for widespread implementation.

Sequential and simultaneous treatment approaches to cannabis use disorder and tobacco use.

Tobacco smoking among those seeking treatment for cannabis use disorder (CUD) is common and is a negative predictor of cannabis outcomes. Quitting tobacco may be beneficial for those seeking to quit cannabis use. This initial proof of concept, controlled trial was designed to compare a simultaneous versus sequential tobacco intervention among those seeking treatment for CUD. Sixty-seven adults received either a simultaneous (SIM) or sequential (SEQ) approach to tobacco cessation in the context of outpatient treatment for CUD. A tobacco intervention (TI) that combined web-based counseling with nicotine replacement therapy (NRT) was provided during weeks 1-12 for SIM and was delayed until weeks 13-24 for SEQ. During weeks 1-12, no between-condition significant differences were observed on treatment participation or cannabis use outcomes. The majority of SIM participants initiated TI counseling (62%), 50% made at least one quit attempt and 41% initiated NRT. Interestingly, 39% in SEQ made tobacco quit attempts and 18% initiated NRT on their own before the TI was offered to them. However, only 30% of those in SEQ continued treatment during weeks 13-24, which compromised between-condition comparisons following the TI, but illustrated a potential clinical concern with delaying the TI. Tobacco cessation outcomes generally were poor and did not differ between conditions. This initial controlled trial suggests that addressing tobacco use during CUD treatment is acceptable and generates action towards tobacco cessation. Additional trials testing more intensive TI models may be necessary to identify more efficacious interventions for co-use of cannabis and tobacco.

A Web-Delivered Multicomponent Intervention for Adolescents with Poorly Controlled Type 1 Diabetes: A Pilot Randomized Controlled Trial.

Background: Type 1 diabetes is associated with significant mortality and economic cost. Management of type 1 diabetes involves completing multiple daily adherence behaviors, and many adolescents struggle with self-management and show poor glycemic control. Purpose: The purpose was to conduct an unblinded pilot randomized controlled parallel-group study of a web-delivered multicomponent intervention targeting self-monitoring of blood glucose, working memory, and parent supervision of diabetes care among adolescents with type 1 diabetes. Intervention components included high magnitude incentives for adolescents and parents, motivational and cognitive behavioral therapy and working memory training for adolescents, and training in contingency contracting for parents. Methods: Adolescents (N = 114) with poorly controlled type 1 diabetes were screened, and N = 61 were randomized using minimum likelihood allocation to usual care (usual care, N = 31) or to a 25-week/15-session web-delivered intervention (WebRx, N = 30). Results: At the end of treatment, adolescents in WebRx had higher self-monitoring of blood glucose (d = 0.58) (primary outcome), better visual spatial working memory (d = 0.48) and inhibition (d = 0.98), and lower HbA1c (d = 0.45) than those in usual care. WebRx parents reported more frequent review of the adolescent's glucometer (d = 1.30) and reduced family conflict (d = 0.56). Between-condition differences were maintained 6 months later in self-monitoring of blood glucose (d = 0.42), visual spatial working memory (d = 0.76), family conflict (d = 0.50), and HbA1c (d = 0.44). Conclusions: Results showing sustained effects on self-monitoring of blood glucose and HbA1c support moving forward with a larger trial to test this innovative web-delivered and multicomponent intervention. ClinicalTrials.gov Number (NCT01722643).

Peer support and mobile health technology targeting obesity-related cardiovascular risk in young adults with serious mental illness: Protocol for a randomized controlled trial.

BACKGROUND: Individuals with serious mental illness (SMI) such as schizophrenia and bipolar disorder face a higher risk of early death due to cardiovascular disease and other preventable chronic illnesses. Young adulthood is a critical window of development for lifestyle interventions to improve the long-term health and quality of life in this population. Fit Forward is an NIH-funded randomized clinical trial examining the effectiveness of a group lifestyle intervention (PeerFIT) enhanced with mobile health technology compared to one-on-one mobile lifestyle coaching with Basic Education in fitness and nutrition supported by a wearable Activity Tracking device (BEAT) in achieving clinically significant weight loss and improved cardiorespiratory fitness in young adults with SMI. METHODS: Fit Forward targets 144 young adults (18 to 35 years) with SMI and a body mass index (BMI) of ≥25 receiving public mental health services. In a two-arm randomized clinical trial, participants will be randomly assigned with equal probability to PeerFIT or BEAT, stratified by birth sex and psychiatric diagnosis. Participants will be assessed at baseline, 6, and 12 months. The primary outcome is cardiovascular risk reduction indicated by either clinically significant weight loss (5% or greater) or increased fitness (>50 m on the 6-Minute Walk Test). Secondary outcomes include change in BMI, lipids, and hemoglobin A1c. Perceived self-efficacy for exercise and peer support will be evaluated as mechanisms underlying intervention effects. CONCLUSION: If effective, PeerFIT will provide a potentially scalable approach to addressing health risks among young adults with SMI in mental health settings. TRIALS REGISTRATION: ClinicalTrials.gov, NCT02815813.