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BackgroundMisuse of substances is common, can be serious and costly to society, and often goes untreated due to barriers to accessing care. Woebot is a mental health digital solution informed by cognitive behavioral therapy and built upon an artificial intelligence–driven platform to deliver tailored content to users. In a previous 2-week randomized controlled trial, Woebot alleviated depressive symptoms. ObjectiveThis study aims to adapt Woebot for the treatment of substance use disorders (W-SUDs) and examine its feasibility, acceptability, and preliminary efficacy. MethodsAmerican adults (aged 18-65 years) who screened positive for substance misuse without major health contraindications were recruited from online sources and flyers and enrolled between March 27 and May 6, 2020. In a single-group pre/postdesign, all participants received W-SUDs for 8 weeks. W-SUDs provided mood, craving, and pain tracking and modules (psychoeducational lessons and psychotherapeutic tools) using elements of dialectical behavior therapy and motivational interviewing. Paired samples t tests and McNemar nonparametric tests were used to examine within-subject changes from pre- to posttreatment on measures of substance use, confidence, cravings, mood, and pain. ResultsThe sample (N=101) had a mean age of 36.8 years (SD 10.0), and 75.2% (76/101) of the participants were female, 78.2% (79/101) were non-Hispanic White, and 72.3% (73/101) were employed. Participants’ W-SUDs use averaged 15.7 (SD 14.2) days, 12.1 (SD 8.3) modules, and 600.7 (SD 556.5) sent messages. About 94% (562/598) of all completed psychoeducational lessons were rated positively. From treatment start to end, in-app craving ratings were reduced by half (87/101, 86.1% reporting cravings in the app; odds ratio 0.48, 95% CI 0.32-0.73). Posttreatment assessment completion was 50.5% (51/101), with better retention among those who initially screened higher on substance misuse. From pre- to posttreatment, confidence to resist urges to use substances significantly increased (mean score change +16.9, SD 21.4; P

ObjectiveThe COVID-19 pandemic has produced major life disruptions and increased stress. We explored associations between pandemic-related stress and substance use problems.MethodAdults (N = 180; 65% female) with problematic substance use (CAGE-AID > 1) were recruited online June-August 2020. Measures included the 15-item Short Inventory of Problems-Alcohol and Drugs (SIP-AD), Generalized Anxiety Disorder-7 (GAD-7) seven-item anxiety measure, Patient Health Questionnaire-8 (PHQ-8) eight-item depression measure, a three-item measure of pandemic life disruptions, a six-item measure of pandemic-related mental health effects, and a five-item measure of pandemic-related personal growth. Participants reported whether they frequented bars and attended large gatherings. Participants with children (

BackgroundThe COVID-19 pandemic disrupted access to treatment for substance use disorders (SUDs), while alcohol and cannabis retail sales increased. During the pandemic, we tested a tailored digital health solution, Woebot-SUDs (W-SUDs), for reducing substance misuse.MethodsIn a randomized controlled trial, we compared W-SUDs for 8 weeks to a waitlist control. U.S. adults (N = 180) who screened positive for substance misuse (CAGE-AID>1) were enrolled June-August 2020. The primary outcome was the change in past-month substance use occasions from baseline to end-of-treatment (EOT). Study retention was 84%. General linear models tested group differences in baseline-to-EOT change scores, adjusting for baseline differences and attrition.ResultsAt baseline, the sample (age M = 40, SD = 12, 65% female, 68% non-Hispanic white) averaged 30.2 (SD = 18.6) substance occasions in the past month. Most (77%) reported alcohol problems, 28% cannabis, and 45% multiple substances; 46% reported moderate-to-severe depressive symptoms. Treatment participants averaged 920 in-app text messages (SD = 892, Median = 701); 96% of completed lessons were rated positively; and 88% would recommend W-SUDs. Relative to waitlist, W-SUDs participants significantly reduced past-month substance use occasions (M = -9.1, SE = 2.0 vs. M = -3.3, SE = 1.8; p = .039). Secondary substance use and mood outcomes did not change significantly by group; however, reductions in substance use occasions correlated significantly with increased confidence and fewer substance use problems, cravings, depression and anxiety symptoms, and pandemic-related mental health effects (p-value

BACKGROUND Misuse of substances is common, can be serious and costly to society, and often goes untreated due to barriers to accessing care. Woebot is a mental health digital solution informed by cognitive behavioral therapy and built upon an artificial intelligence–driven platform to deliver tailored content to users. In a previous 2-week randomized controlled trial, Woebot alleviated depressive symptoms. OBJECTIVE This study aims to adapt Woebot for the treatment of substance use disorders (W-SUDs) and examine its feasibility, acceptability, and preliminary efficacy. METHODS American adults (aged 18-65 years) who screened positive for substance misuse without major health contraindications were recruited from online sources and flyers and enrolled between March 27 and May 6, 2020. In a single-group pre/postdesign, all participants received W-SUDs for 8 weeks. W-SUDs provided mood, craving, and pain tracking and modules (psychoeducational lessons and psychotherapeutic tools) using elements of dialectical behavior therapy and motivational interviewing. Paired samples t tests and McNemar nonparametric tests were used to examine within-subject changes from pre- to posttreatment on measures of substance use, confidence, cravings, mood, and pain. RESULTS The sample (N=101) had a mean age of 36.8 years (SD 10.0), and 75.2% (76/101) of the participants were female, 78.2% (79/101) were non-Hispanic White, and 72.3% (73/101) were employed. Participants’ W-SUDs use averaged 15.7 (SD 14.2) days, 12.1 (SD 8.3) modules, and 600.7 (SD 556.5) sent messages. About 94% (562/598) of all completed psychoeducational lessons were rated positively. From treatment start to end, in-app craving ratings were reduced by half (87/101, 86.1% reporting cravings in the app; odds ratio 0.48, 95% CI 0.32-0.73). Posttreatment assessment completion was 50.5% (51/101), with better retention among those who initially screened higher on substance misuse. From pre- to posttreatment, confidence to resist urges to use substances significantly increased (mean score change +16.9, SD 21.4; P

ObjectiveFamily-based treatment (FBT) for adolescent anorexia nervosa (AN) promotes faster weight restoration when compared to other treatments. However, the mechanisms through which this occurs are not clarified. This study explored the trajectories of parental self-efficacy and perceived family flexibility during FBT and systemic family therapy (SyFT). We also explored whether parental self-efficacy mediates the effects of treatment on weight gain early in treatment.Method158 adolescents (12-18 years old; 89% girls) and their parents were randomized to FBT or SyFT. Parental self-efficacy as well as adolescents' and parental perceptions of the family's flexibility were collected at baseline and at sessions 2, 4, 6, and 8.ResultsOver time, only parents in FBT reported significantly greater self-efficacy. The change in maternal self-efficacy over the first 8 weeks of treatment was a significant mediator of session 10 weight gain. There were no significant group differences in perceived flexibility by session 8.DiscussionBoth parents in FBT and mothers in SyFT understand early the need to change their family's rules and roles. However, the specific strategies of FBT appear to mediate early weight gain in AN.

Objective: Open trials suggest phentermine/topiramate ER (PHEN/TPM‐ER), food and drug administration (FDA) approved for obesity, has utility for binge eating. With no randomized controlled trials (RCTs) yet performed, this trial aimed to evaluate PHEN/TPM‐ERs efficacy and safety in a crossover RCT for patients with binge‐eating disorder (BED) or bulimia nervosa (BN). Method: Participants were randomized to 12‐weeks PHEN/TPM‐ER (3.75 mg/23 mg–15 mg/92 mg) or placebo followed by 2‐weeks drug washout, then 12‐week crossover. Demographics, vitals, eating disorder behaviors, mood, and side effects were measured. Primary outcome was objective binge‐eating (OBE) days/4‐weeks; secondary outcomes included binge abstinence. Mixed‐effect models estimated treatment effects, with fixed effects adjusting for treatment, study period, and diagnosis. Results: The 22 adults (BED = 18, BN = 4) were female (96%), Caucasian (55%), aged 42.9 (SD = 10.1) years with body mass index = 31.1 (SD = 6.2) kg/m2. Baseline OBE days/4‐weeks decreased from 16.2 (SD = 7.8) to 4.2 (SD = 8.4) after PHEN/TPM‐ER versus 13.2 (SD = 9.1) after placebo (p <.0001), with abstinence rates = 63.6% on PHEN/TPM‐ER versus 9.1% on placebo (p <.0001). Weight changes = −5.8 kg on PHEN/ TPM‐ER versus +0.4 kg on placebo. Drop‐out = 2 (9%) on PHEN/TPM‐ER and 2 (9%) on placebo, with few side effects. Vital sign changes with PHEN/TPM‐ER were minimal and similar to placebo. Responses were not significantly different for BED versus BN. Discussion: This first RCT to evaluate the efficacy and safety of PHEN/TPM‐ER for BED/BN found this drug combination significantly more effective at reducing binge eating than placebo and well tolerated. However, with only four participants with BN, findings regarding the safety of PHEN/TPM‐ER in patients with BN must be taken with caution. Trial Registration: Clinicaltrials.gov identifier NCT02553824 registered on 9/17/2015. https://clinicaltrials.gov/ct2/show/NCT02553824 [ABSTRACT FROM AUTHOR]

Background: The ability of digital mental health interventions (DMHIs) to reduce mental health disparities relies on the recruitment of research participants with diverse sociodemographic and self-identity characteristics. Despite its importance, sociodemographic reporting in research is often limited, and the state of reporting practices in DMHI research in particular has not been comprehensively reviewed., Objectives: To characterise the state of sociodemographic data reported in randomised controlled trials (RCTs) of app-based DMHIs published globally from 2007 to 2022., Methods: A scoping review of RCTs of app-based DMHIs examined reporting frequency for 16 sociodemographic domains (eg, gender) and common category options within each domain (eg, woman). The search queried five electronic databases. 5079 records were screened and 299 articles were included., Results: On average, studies reported 4.64 (SD=1.79; range 0-9) of 16 sociodemographic domains. The most common were age (97%) and education (67%). The least common were housing situation (6%), residency/location (5%), veteran status (4%), number of children (3%), sexual orientation (2%), disability status (2%) and food security (<1%). Gender or sex was reported in 98% of studies: gender only (51%), sex only (28%), both (<1%) and gender/sex reported but unspecified (18%). Race or ethnicity was reported in 48% of studies: race only (14%), ethnicity only (14%), both (10%) and race/ethnicity reported but unspecified (10%)., Conclusions: This review describes the widespread underreporting of sociodemographic information in RCTs of app-based DMHIs published from 2007 to 2022. Reporting was often incomplete (eg, % female only), unclear (eg, the conflation of gender/sex) and limited (eg, only options representing majority groups were reported). Trends suggest reporting has somewhat improved in recent years. Diverse participant populations must be welcomed and described in DMHI research to broaden learning and the generalisability of results, a prerequisite of DMHI's potential to reduce disparities in mental healthcare., Competing Interests: Competing interests: AKQ, MC, MCP, SR, SP, RM, AD and AR are all employees of Woebot Health. RM is a former employee of Twill. PW is an associate editor at the Journal of Medical Internet Research and is on the editorial advisory boards of BMC Medicine, The Patient and Digital Biomarkers. PW is employed by Wicks Digital Health Ltd, which has received funding from Ada Health, AstraZeneca, Biogen, Bold Health, Corevitas, EIT, Endava, Happify, HealthUnlocked, Inbeeo, Kheiron Medical, Lindus Health, MedRhythms, Okko Health, PatientsLikeMe, Sano Genetics, The Learning Corp, The Wellcome Trust, THREAD Research, United Genomics, VeraSci and Woebot Health. PW and spouse are shareholders of WDH Investments, which owns stock in Avayl Gmbh, BlueSkeye AI, Earswitch, Lucida Medical, Sano Genetics and Una Health Gmbh. CJG is a consultant to Woebot Health. CJG would like to acknowledge support provided by the Center for Childhood Obesity Prevention funded by the National Institute of General Medical Sciences of the National Institutes of Health under Award Number P20GM109096 (Arkansas Children’s Research Institute, PI: Weber) and by the Translational Research Institute funded by the National Center For Advancing Translational Sciences of the National Institutes of Health under Award Number UL1 TR003107 (University of Arkansas for Medical Sciences, PI: James). The content is solely the responsibility of the author and does not necessarily represent the official views of the National Institutes of Health. JK and LQ are contractors to Woebot Health. JK is a former employee of PatientsLikeMe and has received funds as a consultant from PatientsLikeMe and EHIR., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)