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Symposium Focuses on Digital Tech for Mental Health

Article Excerpt: Technology offers new avenues for mental health delivery. Digital record keeping, virtual consultations, wearables that monitor activity and well-being, mindfulness apps, and AI-based chatbots are just a few examples. But these advances have not been leveraged effectively enough, Cornell Tech Professor and HealthRhythms Co-Founder Tanzeem Choudhury said in a keynote talk Tuesday at the Digital Mental Health and AI Symposium organized by the Center for Technology and Behavioral Health. Choudhury explored the challenges that have forestalled digital mental health from delivering on some of its early promises and how to move the needle forward.

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Article Source: Dartmouth News


A Mobile App to Promote Alcohol and Drug SBIRT Skill Translation Among Multi-Disciplinary Health Care Trainees: Results of a Randomized Controlled Trial

Curtis AC, Satre DD, Sarovar V, Wamsley M, Ly K & Satterfield J. (2022). A mobile app to promote alcohol and drug SBIRT skill translation among multi-disciplinary health care trainees: Results of a randomized controlled trial. Substance Abuse, 43(1), 13–22.

The aim of this study was to evaluate the effectiveness of an alcohol and drug screening, brief intervention, and referral to treatment (SBIRT) mobile app to support healthcare trainees working in various clinical settings. A randomized controlled trial of a new mobile app was conducted among 131 participants who were health profession trainees, had completed SBIRT training in the past year, and had a personal mobile device. The app had three main functions: 1) review of SBIRT skills and substance use disorders, 2) application of SBIRT (including screeners, intervention strategies and tools), and 3) data collection on SBIRT delivery via brief surveys. Participants were randomized to either the SBIRT app or the control condition (no access to the app). Participants completed weekly self-report assessments on SBIRT delivery over the 10-week study duration. Seventy-eight percent of participants assigned to the SBIRT app downloaded it and logged in. There were no statistically significant differences between the groups in the percentage of patients screened, brief interventions delivered, or referrals made to treatment. Additionally, there were no differences between the two arms at baseline nor at the end of the study for attitudes, beliefs, confidence in ability to deliver SBIRT, or behavioral intent to deliver SBIRT. In the group that received the SBIRT app, the average system usability score was 62.00 (SD=12.01), which is considered below average. Participants spent an average of 8.81 minutes in the app. Based on these findings, despite good uptake of the SBIRT app, adherence was low. Authors noted that the effect of the classroom training prior to app access is unknown; it is possible that this training reduced the need for the SBIRT app, leading to non-significant differences between the two arms. The potential for use of digital apps to support the translation of best practices from classroom to clinic is promising; however, additional research is needed to improve engagement and adherence.


Training Staff Across the Veterans Affairs Health Care System to Use Mobile Mental Health Apps: A National Quality Improvement Project

McGee-Vincent P, Mackintosh M, Jamison A, Juhasz K, Becket-Davenport C, Bosch J, Avery T, Glamb L, Hampole S. Training Staff Across the Veterans Affairs Health Care System to Use Mobile Mental Health Apps: A National Quality Improvement Project. JMIR Ment Health 2023;10:e41773 DOI: 10.2196/41773

This paper described and evaluated a training program for staff in the Veterans Affairs (VA) healthcare system to increase the reach of mobile mental health apps for veterans. Sites from all VA’s geographic regions were enrolled in this study with at least 25 staff members with direct contact with veterans recruited to participate. A total of 1110 staff from 19 VA sites completed the training program. Sixty-seven percent of participants provided mental health care. Staff training was delivered via a live, web-based format and consisted of a 3-hour core module for all staff and 1-hour module designed specifically for mental health clinicians. Program reach, satisfaction, and effectiveness of the training were assessed pre- and post-training by staff self-reported surveys. Most participants (93.9%) were satisfied with the training and 92.4% would recommend it to other staff. Knowledge about mobile apps and confidence in ability to demonstrate to veterans how to install and use mental health apps significantly increased after training (p<.001). Participants also expressed motivation to refer veterans to apps and encourage other VA staff to share apps with veterans. Overall, this study exceeded their recruitment target, indicating a higher-than-anticipated interest among staff. Further, the training program was well received and effective in promoting awareness about and motivation to recommend mobile health apps. About a third of participants came from other settings besides mental health, which suggests the value of VA mental health apps across the healthcare system. Future work is needed to evaluate the extent to which providers follow up on recommending mobile health apps to patients and patients accessing the mobile health apps.


AI Plus Mobile App May Help With Smoking Cessation

Article Excerpt: A new artificial intelligence (AI)-powered mobile app can help individuals quit smoking, according to the results of a recent study published in Nicotine & Tobacco Research. The app uses machine learning to collect information on the location, timing, and triggers of past smoking events to curate messages that assist smokers in managing their urges. Prior to this app, there had been no other ways to provide support to help smokers manage social situations and urges after quitting, Felix Naughton, PhD, MSc, a primary researcher and professor of health psychology at the University of East Anglia School of Health Sciences in England, said in a statement.

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Article Source: Pharmacy Times


Predicting symptom response and engagement in a digital intervention among individuals with schizophrenia and related psychoses

Price GD, Heinz MV, Nemesure MD, McFadden J, Jacobson NC. Predicting symptom response and engagement in a digital intervention among individuals with schizophrenia and related psychoses. Front Psychiatry. 2022;13:807116. doi:10.3389/fpsyt.2022.807116

This study utilized data from a trial delivering a psychosocial smartphone app designed for patients with psychosis (App4Independence or A4i) to better understand personalized markers of digital intervention engagement and response. Machine learning models were applied to baseline data, app use data, and semi-structured interview data to predict response to change in symptoms, level of engagement, and qualitative impressions of the A4i app. Thirty-eight participants received the A4i app intervention for one month. Machine learning models were capable of moderately predicting participant engagement and experience with the app (r=0.39) as well as changes in psychosis symptom severity (r=0.32). Participants with high baseline interpersonal sensitivity, versus low, benefitted more from the A4i intervention in reducing symptom severity. Additionally, participants with lower baseline psychotic and obsessive-compulsive traits were predicted to benefit more. Higher baseline depression predicted both higher engagement and satisfaction with the app. These findings demonstrate the potential of predicting response to a digital intervention for psychosis using unique patient factors. This study further highlights the need to investigate individual response to and engagement with digital-based mental health interventions. Future research should consider how individual demographic characteristics influence engagement with a digital intervention.


Health Inequities Impact on Digital Therapeutics

Article Excerpt: When we look at health inequities, we’ve been using different applications to bridge some of those inequities, primarily around language. We still have a long way to go with some of the cultural barriers, but we can slowly break down some of them and instill a greater understanding with different populations by putting information in front of them in a way that engages them.

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Article Source: Managed Healthcare Executive


When Naloxone Isn’t Enough: How Technology Can Save Lives when People Use Drugs Alone

Article Excerpt: Researchers from Brown and Rhode Island Hospital are working with Rhode Island community members to understand how apps, monitors and other emerging technologies can help prevent opioid overdose deaths.

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Article Source: News from Brown

Text Messages Exchanged Between Individuals With Opioid Use Disorder and Their mHealth e-Coaches: Content Analysis Study

Ranjit Y, Davis W, Fentem A, Riordan R, Roscoe R, Cavazos-Rehg P. Text Messages Exchanged Between Individuals With Opioid Use Disorder and Their mHealth e-Coaches: Content Analysis Study. JMIR Hum Factors 2023;10:e37351 DOI: 10.2196/37351

The aim of this study was to understand the text messaging communication between persons undergoing opioid use disorder (OUD) recovery and their e-coaches. The study was part of a larger mHealth intervention study called “uMAT-R”, which is a support mobile app to improve OUD treatment adherence and recovery. The uMAT-R app provides instant in-app messaging with a recovery support e-coach. Participants were recruited from various OUD recovery programs in St. Louis and were eligible if they had a formal OUD diagnosis and were currently receiving treatment. For this content analysis, messages from 70 participants were coded for emotional support, informational support, and material support (services and resources that help solve practical issues). Messages were also coded for treatment and recovery domains and problems related to mobile app usage. On average, the number of messages exchanged between participants and e-coaches was 17 (SD=16.05) and 90% of conversations were initiated by e-coaches. Emotional support was most commonly identified in conversations (196 occurrences), followed by material support (110 occurrences). For OUD treatment content, messages about OUD recovery and opioid use risk factors occurred the most (N=72), followed by motivation to avoid drug use (N=47). Depression was significantly associated with social support related messages (r=0.27, p=0.02). Overall, findings demonstrate that people in OUD recovery seek social support and relapse prevention support when provided online communication with their health care providers. Due to the need for continuous interpersonal support as part of addiction care, instant two-way text messaging could be a cost-effective and sustainable tool to support OUD recovery.


Combined Laboratory and Field Test of a Smartphone Breath Alcohol Device and Blood Alcohol Concentration Estimator to Facilitate Moderate Drinking Among Young Adults

Leeman RF, Berey BL, Frohe T, Rowland BHP, Martens MP, Fucito LM, Stellefson M, Nixon SJ, & O’Malley SS. (2022). A combined laboratory and field test of a smartphone breath alcohol device and blood alcohol concentration estimator to facilitate moderate drinking among young adults. Psychology of Addictive Behaviors, 36(6), 710–723.

This paper evaluated feasibility, usability, acceptability, and efficacy of blood alcohol content (BAC) related moderate drinking technology during a laboratory alcohol self-administration session and follow-up field test in real-world situations. Participants were randomly assigned to 1 of 3 technologies to use during a laboratory alcohol drinking session: (1) breathalyzer alcohol device connected to an app, (2) BAC estimator app where participants make entries about drinking behavior, and (3) a self-texting control condition where participants send a text after each alcoholic drink consumed. All participants completed a laboratory alcohol-drinking session while using the assigned technology procedure. After this session, participants were instructed to use all three forms of technologies for two weeks. At the end of the field-testing period, acceptability, usability, and perspectives on all three technologies were The breathalyzer and BAC estimator app both had favorable acceptability and usability ratings. Participants used at least one form of technology on 67% of drinking days. Based on self-reported data, as also significantly lower during the field-test period than at baseline. Overall, combining lab and field methods to test drinking technologies was feasible among young adults. Results support the potential of mobile interventions to help young adults in motivating behavior change given their willingness to use apps.