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Wilhelm S, Bernstein EE, Bentley KH, Snorrason I, Hoeppner SS, Klare D, Greenberg JL, Weingarden H, McCoy TH, Harrison O. Feasibility, Acceptability, and Preliminary Efficacy of a Smartphone App-Led Cognitive Behavioral Therapy for Depression Under Therapist Supervision: Open Trial. JMIR Ment Health 2024; 11:e53998. [PMID: 38592771 DOI: 10.2196/53998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 12/19/2023] [Accepted: 01/03/2024] [Indexed: 04/10/2024] Open
Abstract
BACKGROUND Major depressive disorder affects approximately 1 in 5 adults during their lifetime and is the leading cause of disability worldwide. Yet, a minority receive adequate treatment due to person-level (eg, geographical distance to providers) and systems-level (eg, shortage of trained providers) barriers. Digital tools could improve this treatment gap by reducing the time and frequency of therapy sessions needed for effective treatment through the provision of flexible, automated support. OBJECTIVE This study aimed to examine the feasibility, acceptability, and preliminary clinical effect of Mindset for Depression, a deployment-ready 8-week smartphone-based cognitive behavioral therapy (CBT) supported by brief teletherapy appointments with a therapist. METHODS This 8-week, single-arm open trial tested the Mindset for Depression app when combined with 8 brief (16-25 minutes) video conferencing visits with a licensed doctoral-level CBT therapist (n=28 participants). The app offers flexible, accessible psychoeducation, CBT skills practice, and support to patients as well as clinician guidance to promote sustained engagement, monitor safety, and tailor treatment to individual patient needs. To increase accessibility and thus generalizability, all study procedures were conducted remotely. Feasibility and acceptability were assessed via attrition, patient expectations and feedback, and treatment utilization. The primary clinical outcome measure was the clinician-rated Hamilton Depression Rating Scale, administered at pretreatment, midpoint, and posttreatment. Secondary measures of functional impairment and quality of life as well as maintenance of gains (3-month follow-up) were also collected. RESULTS Treatment credibility (week 4), expectancy (week 4), and satisfaction (week 8) were moderate to high, and attrition was low (n=2, 7%). Participants self-reported using the app or practicing (either on or off the app) the CBT skills taught in the app for a median of 50 (IQR 30-60; week 4) or 60 (IQR 30-90; week 8) minutes per week; participants accessed the app on an average 36.8 (SD 10.0) days and completed a median of 7 of 8 (IQR 6-8) steps by the week 8 assessment. The app was rated positively across domains of engagement, functionality, aesthetics, and information. Participants' depression severity scores decreased from an average Hamilton Depression Rating Scale score indicating moderate depression (mean 19.1, SD 5.0) at baseline to a week 8 mean score indicating mild depression (mean 10.8, SD 6.1; d=1.47; P<.001). Improvement was also observed for functional impairment and quality of life. Gains were maintained at 3-month follow-up. CONCLUSIONS The results show that Mindset for Depression is a feasible and acceptable treatment option for individuals with major depressive disorder. This smartphone-led treatment holds promise to be an efficacious, scalable, and cost-effective treatment option. The next steps include testing Mindset for Depression in a fully powered randomized controlled trial and real-world clinical settings. TRIAL REGISTRATION ClinicalTrials.gov NCT05386329; https://clinicaltrials.gov/study/NCT05386329?term=NCT05386329.
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Affiliation(s)
- Sabine Wilhelm
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Emily E Bernstein
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Kate H Bentley
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Ivar Snorrason
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Susanne S Hoeppner
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Dalton Klare
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Jennifer L Greenberg
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Hilary Weingarden
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Thomas H McCoy
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
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Lim CT, Fuchs C, Torous J. Integrated Digital Mental Health Care: A Vision for Addressing Population Mental Health Needs. Int J Gen Med 2024; 17:359-365. [PMID: 38318335 PMCID: PMC10840519 DOI: 10.2147/ijgm.s449474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Accepted: 01/10/2024] [Indexed: 02/07/2024] Open
Abstract
The unmet need for mental health care continues to rise across the world. This article synthesizes the evidence supporting the components of a hypothetical model of integrated digital mental health care to meet population-wide mental health needs. This proposed model integrates two approaches to broadening timely access to effective care: integrated, primary care-based mental health services and digital mental health tools. The model solves for several of the key challenges historically faced by digital health, through promoting digital literacy and access, the curation of evidence-based digital tools, integration into clinical practice, and electronic medical record integration. This model builds upon momentum toward the integration of mental health services within primary care and aligns with the principles of the Collaborative Care Model. Finally, the authors present the major next steps toward implementation of integrated digital mental health care at scale.
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Affiliation(s)
- Christopher T Lim
- Department of Psychiatry, Boston Medical Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Population Health Services, Boston Medical Center Health System, Boston, MA, USA
| | - Cara Fuchs
- Department of Psychiatry, Boston Medical Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - John Torous
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
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Langholm C, Breitinger S, Gray L, Goes F, Walker A, Xiong A, Stopel C, Zandi P, Frye MA, Torous J. Classifying and clustering mood disorder patients using smartphone data from a feasibility study. NPJ Digit Med 2023; 6:238. [PMID: 38129571 PMCID: PMC10739731 DOI: 10.1038/s41746-023-00977-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Accepted: 11/29/2023] [Indexed: 12/23/2023] Open
Abstract
Differentiating between bipolar disorder and major depressive disorder can be challenging for clinicians. The diagnostic process might benefit from new ways of monitoring the phenotypes of these disorders. Smartphone data might offer insight in this regard. Today, smartphones collect dense, multimodal data from which behavioral metrics can be derived. Distinct patterns in these metrics have the potential to differentiate the two conditions. To examine the feasibility of smartphone-based phenotyping, two study sites (Mayo Clinic, Johns Hopkins University) recruited patients with bipolar I disorder (BPI), bipolar II disorder (BPII), major depressive disorder (MDD), and undiagnosed controls for a 12-week observational study. On their smartphones, study participants used a digital phenotyping app (mindLAMP) for data collection. While in use, mindLAMP gathered real-time geolocation, accelerometer, and screen-state (on/off) data. mindLAMP was also used for EMA delivery. MindLAMP data was then used as input variables in binary classification, three-group k-nearest neighbors (KNN) classification, and k-means clustering. The best-performing binary classification model was able to classify patients as control or non-control with an AUC of 0.91 (random forest). The model that performed best at classifying patients as having MDD or bipolar I/II had an AUC of 0.62 (logistic regression). The k-means clustering model had a silhouette score of 0.46 and an ARI of 0.27. Results support the potential for digital phenotyping methods to cluster depression, bipolar disorder, and healthy controls. However, due to inconsistencies in accuracy, more data streams are required before these methods can be applied to clinical practice.
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Affiliation(s)
- Carsten Langholm
- Division of Digital Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, 02115, USA
| | - Scott Breitinger
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, 55902, USA
| | - Lucy Gray
- Division of Digital Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, 02115, USA
| | - Fernando Goes
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, 21218, USA
| | - Alex Walker
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, 21218, USA
| | - Ashley Xiong
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, 55902, USA
| | - Cindy Stopel
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, 55902, USA
| | - Peter Zandi
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, 21218, USA
| | - Mark A Frye
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, 55902, USA
| | - John Torous
- Division of Digital Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, 02115, USA.
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Perret S, Alon N, Carpenter-Song E, Myrick K, Thompson K, Li S, Sharma K, Torous J. Standardising the role of a digital navigator in behavioural health: a systematic review. Lancet Digit Health 2023; 5:e925-e932. [PMID: 38000876 DOI: 10.1016/s2589-7500(23)00152-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 07/26/2023] [Accepted: 07/28/2023] [Indexed: 11/26/2023]
Abstract
As the number and availability of digital mental health tools increases, patients and clinicians see benefit only when these tools are engaging and well integrated into care. Digital navigators-ie, members of health-care teams who are dedicated to supporting patient use of digital resources-offer one solution and continue to be piloted in behavioural health; however, little is known about the core features of this position. The aims of this systematic review were to assess how digital navigators are implemented in behavioural health, and to provide a standardised definition of this position. In January, 2023, we conducted a systematic literature search resulting in 48 articles included in this systematic review. Results showed high heterogeneity between four attributes of digital navigators: training specifications, educational background, frequency of communication, and method of communication with patients. Reported effect sizes for depression and anxiety were medium to large, but could not be synthesised due to study heterogeneity and small study sample size. This systematic review was registered with PROSPERO (CRD42023391696). Results suggest that digital navigator support can probably increase access to, engagement with, and clinical integration of digital health technology, with standards for training and defined responsibilities now emerging.
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Affiliation(s)
- Sarah Perret
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Noy Alon
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | | | - Keris Myrick
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Kennedy Thompson
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Sunnie Li
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Karuna Sharma
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - John Torous
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
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Uhlhaas PJ, Davey CG, Mehta UM, Shah J, Torous J, Allen NB, Avenevoli S, Bella-Awusah T, Chanen A, Chen EYH, Correll CU, Do KQ, Fisher HL, Frangou S, Hickie IB, Keshavan MS, Konrad K, Lee FS, Liu CH, Luna B, McGorry PD, Meyer-Lindenberg A, Nordentoft M, Öngür D, Patton GC, Paus T, Reininghaus U, Sawa A, Schoenbaum M, Schumann G, Srihari VH, Susser E, Verma SK, Woo TW, Yang LH, Yung AR, Wood SJ. Towards a youth mental health paradigm: a perspective and roadmap. Mol Psychiatry 2023; 28:3171-3181. [PMID: 37580524 PMCID: PMC10618105 DOI: 10.1038/s41380-023-02202-z] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 07/04/2023] [Accepted: 07/21/2023] [Indexed: 08/16/2023]
Abstract
Most mental disorders have a typical onset between 12 and 25 years of age, highlighting the importance of this period for the pathogenesis, diagnosis, and treatment of mental ill-health. This perspective addresses interactions between risk and protective factors and brain development as key pillars accounting for the emergence of psychopathology in youth. Moreover, we propose that novel approaches towards early diagnosis and interventions are required that reflect the evolution of emerging psychopathology, the importance of novel service models, and knowledge exchange between science and practitioners. Taken together, we propose a transformative early intervention paradigm for research and clinical care that could significantly enhance mental health in young people and initiate a shift towards the prevention of severe mental disorders.
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Affiliation(s)
- Peter J Uhlhaas
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK.
- Department of Child and Adolescent Psychiatry, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
| | - Christopher G Davey
- Department of Psychiatry, The University of Melbourne, Carlton, VIC, Australia
| | - Urvakhsh Meherwan Mehta
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Jai Shah
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - John Torous
- Division of Digital Psychiatry and Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | | | - Shelli Avenevoli
- Office of the Director, National Institute of Mental Health, Bethesda, MD, USA
| | - Tolulope Bella-Awusah
- Department of Psychiatry, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Andrew Chanen
- Orygen: National Centre of Excellence in Youth Mental Health, Parkville, VIC, Australia
- Centre for Youth Mental Health, University of Melbourne, Parkville, VIC, Australia
| | - Eric Y H Chen
- Department of Psychiatry, University of Hong Kong, Hong Kong, China
| | - Christoph U Correll
- Department of Child and Adolescent Psychiatry, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Departments of Psychiatry and Molecular Medicine, Donald and Barbara Zucker School of Medicine at Hostra/Northwell, Hempstead, NY, USA
- Department of Psychiatry, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, USA
| | - Kim Q Do
- Centre for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland
| | - Helen L Fisher
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- ESRC Centre for Society and Mental Health, King's College London, London, UK
| | - Sophia Frangou
- Department of Psychiatry, The University of British Columbia, Vancouver, BC, Canada
| | - Ian B Hickie
- Brain and Mind Centre, University of Sydney, Camperdown, NSW, Australia
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Kerstin Konrad
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, RWTH, Aachen, Germany
- JARA-Brain Institute II, Molecular Neuroscience and Neuroimaging, Research Center Jülich, Jülich, Germany
| | - Francis S Lee
- Department of Psychiatry, Weill Cornell Cornell Medicall College, New York, NY, USA
| | - Cindy H Liu
- Departments of Pediatrics and Psychiatry, Brigham and Women's Hospital/Harvard Medical School, Boston, MA, USA
| | - Beatriz Luna
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Patrick D McGorry
- Orygen: National Centre of Excellence in Youth Mental Health, Parkville, VIC, Australia
- Centre for Youth Mental Health, University of Melbourne, Parkville, VIC, Australia
| | - Andreas Meyer-Lindenberg
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
| | - Merete Nordentoft
- CORE-Copenhagen Research Centre for Mental Health, Mental Health Center Copenhagen, University of Copenhagen, Faculty of Health and Medical Sciences, Department of Clinical Medicine, Hellerup, Denmark
| | - Dost Öngür
- McLean Hospital/Harvard Medical School, Belmont, MA, USA
| | - George C Patton
- Centre for Adolescent Health, Murdoch Children's Research Institute, University of Melbourne, Parkville, VIC, Australia
| | - Tomáš Paus
- Departments of Psychiatry and Neuroscience, Faculty of Medicine and Centre Hospitalier Universitaire Sainte Justine, University of Montreal, Montreal, QC, Canada
- Department of Psychology and Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Ulrich Reininghaus
- Department of Public Mental Health, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
- Centre for Epidemiology and Public Health, Health Service and Population Research Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Akira Sawa
- The John Hopkins Schizophrenia Center, Johns Hopkins University, Baltimore, MD, USA
| | - Michael Schoenbaum
- Division of Service and Intervention Research, National Institute of Mental Health, Bethesda, MD, USA
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine, ISTBI, Fudan University, Shanghai, China
- Department of Psychiatry and Neuroscience, Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Vinod H Srihari
- Department of Psychiatry, Yale University, New Haven, CT, USA
- Program for Specialized Treatment Early in Psychosis (STEP), New Haven, VIC, USA
| | - Ezra Susser
- Departments of Epidemiology and Psychiatry, Columbia University, New York, NY, USA
- New York State Psychiatric Institute, New York, NY, USA
| | - Swapna K Verma
- Department of Psychosis, Institute of Mental Health, Buangkok, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - T Wilson Woo
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Laboratory for Cellular Neuropathology, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Lawrence H Yang
- Department of Social and Behavioral Sciences, New York University, New York, NY, USA
- Department of Epidemiology, Columbia University, New York, NY, USA
| | - Alison R Yung
- School of Medicine, Faculty of Health, Deakin University, Melbourne, VIC, Australia
- Department of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Stephen J Wood
- Orygen: National Centre of Excellence in Youth Mental Health, Parkville, VIC, Australia
- Centre for Youth Mental Health, University of Melbourne, Parkville, VIC, Australia
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Miller-Rosales C, Morden NE, Brunette MF, Busch SH, Torous JB, Meara ER. Provision of Digital Health Technologies for Opioid Use Disorder Treatment by US Health Care Organizations. JAMA Netw Open 2023; 6:e2323741. [PMID: 37459098 PMCID: PMC10352858 DOI: 10.1001/jamanetworkopen.2023.23741] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 05/31/2023] [Indexed: 07/20/2023] Open
Abstract
Importance Digital health technologies may expand organizational capacity to treat opioid use disorder (OUD). However, it remains unclear whether these technologies serve as substitutes for or complements to traditional substance use disorder (SUD) treatment resources in health care organizations. Objective To characterize the use of patient-facing digital health technologies for OUD by US organizations with accountable care organization (ACO) contracts. Design, Setting, and Participants This cross-sectional study analyzed responses to the 2022 National Survey of Accountable Care Organizations (NSACO), collected between October 1, 2021, and June 30, 2022, from US organizations with Medicare and Medicaid ACO contracts. Data analysis was performed between December 15, 2022, and January 6, 2023. Exposures Treatment resources for SUD (eg, an addiction medicine specialist, sufficient staff to treat SUD, medications for OUD, a specialty SUD treatment facility, a registry to identify patients with OUD, or a registry to track mental health for patients with OUD) and organizational characteristics (eg, organization type, Medicaid ACO contract). Main Outcomes and Measures The main outcomes included survey-reported use of 3 categories of digital health technologies for OUD: remote mental health therapy and tracking, virtual peer recovery support programs, and digital recovery support for adjuvant cognitive behavior therapy (CBT). Statistical analysis was conducted using descriptive statistics and multivariable logistic regression models. Results Overall, 276 of 505 organizations responded to the NSACO (54.7% response rate), with a total of 304 respondents. Of these, 161 (53.1%) were from a hospital or health system, 74 (24.2%) were from a physician- or medical group-led organization, and 23 (7.8%) were from a safety-net organization. One-third of respondents (101 [33.5%]) reported that their organization used at least 1 of the 3 digital health technology categories, including remote mental health therapy and tracking (80 [26.5%]), virtual peer recovery support programs (46 [15.1%]), and digital recovery support for adjuvant CBT (27 [9.0%]). In an adjusted analysis, organizations with an addiction medicine specialist (average marginal effect [SE], 32.3 [4.7] percentage points; P < .001) or a registry to track mental health (average marginal effect [SE], 27.2 [3.8] percentage points; P < .001) were more likely to use at least 1 category of technology compared with otherwise similar organizations lacking these capabilities. Conclusions and Relevance In this cross-sectional study of 276 organizations with ACO contracts, organizations used patient-facing digital health technologies for OUD as complements to available SUD treatment capabilities rather than as substitutes for unavailable resources. Future studies should examine implementation facilitators to realize the potential of emerging technologies to support organizations facing health care practitioner shortages and other barriers to OUD treatment delivery.
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Affiliation(s)
| | - Nancy E. Morden
- Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine, Lebanon, New Hampshire
- UnitedHealthcare, Minnetonka, Minnesota
| | - Mary F. Brunette
- Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine, Lebanon, New Hampshire
- Department of Psychiatry, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire
- Bureau of Mental Health Services, New Hampshire Department of Health and Human Services, Concord
| | - Susan H. Busch
- Department of Health Policy and Management, Yale School of Public Health, New Haven, Connecticut
| | - John B. Torous
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts
| | - Ellen R. Meara
- Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
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Kopka M, Camacho E, Kwon S, Torous J. Exploring how informed mental health app selection may impact user engagement and satisfaction. PLOS DIGITAL HEALTH 2023; 2:e0000219. [PMID: 36989237 DOI: 10.1371/journal.pdig.0000219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 02/22/2023] [Indexed: 03/30/2023]
Abstract
The prevalence of mental health app use by people suffering from mental health disorders is rapidly growing. The integration of mental health apps shows promise in increasing the accessibility and quality of treatment. However, a lack of continued engagement is one of the significant challenges of such implementation. In response, the M-health Index and Navigation Database (MIND)- derived from the American Psychiatric Association's app evaluation framework- was created to support patient autonomy and enhance engagement. This study aimed to identify factors influencing engagement with mental health apps and explore how MIND may affect user engagement around selected apps. We conducted a longitudinal online survey over six weeks after participants were instructed to find mental health apps using MIND. The survey included demographic information, technology usage, access to healthcare, app selection information, System Usability Scale, the Digital Working Alliance Inventory, and the General Self-Efficacy Scale questions. Quantitative analysis was performed to analyze the data. A total of 321 surveys were completed (178 at the initial, 90 at the 2-week mark, and 53 at the 6-week mark). The most influential factors when choosing mental health apps included cost (76%), condition supported by the app (59%), and app features offered (51%), while privacy and clinical foundation to support app claims were among the least selected filters. The top ten apps selected by participants were analyzed for engagement. Rates of engagement among the top-ten apps decreased by 43% from the initial to week two and 22% from week two to week six on average. In the context of overall low engagement with mental health apps, implementation of mental health app databases like MIND can play an essential role in maintaining higher engagement and satisfaction. Together, this study offers early data on how educational approaches like MIND may help bolster mental health apps engagement.
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Affiliation(s)
- Marvin Kopka
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America
- Charité -Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Medical Informatics, Charitéplatz 1, Berlin, Germany
- Technische Universität Berlin, Institute of Psychology and Ergonomics (IPA), Berlin, Germany
| | - Erica Camacho
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America
| | - Sam Kwon
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America
| | - John Torous
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America
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Chang S, Alon N, Torous J. An exploratory analysis of the effect size of the mobile mental health Application, mindLAMP. Digit Health 2023; 9:20552076231187244. [PMID: 37434734 PMCID: PMC10331229 DOI: 10.1177/20552076231187244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 06/23/2023] [Indexed: 07/13/2023] Open
Abstract
Objectives Despite the proliferation of mobile mental health apps, evidence of their efficacy around anxiety or depression is inadequate as most studies lack appropriate control groups. Given that apps are designed to be scalable and reusable tools, insights concerning their efficacy can also be assessed uniquely through comparing different implementations of the same app. This exploratory analysis investigates the potential to report a preliminary effect size of an open-source smartphone mental health app, mindLAMP, on the reduction of anxiety and depression symptoms by comparing a control implementation of the app focused on self-assessment to an intervention implementation of the same app focused on CBT skills. Methods A total of 328 participants were eligible and completed the study under the control implementation and 156 completed the study under the intervention implementation of the mindLAMP app. Both use cases offered access to the same in-app self-assessments and therapeutic interventions. Multiple imputations were utilized to impute the missing Generalized Anxiety Disorder-7 and Patient Health Questionnaire-9 survey scores of the control implementation. Results Post hoc analysis revealed small effect sizes of Hedge's g = 0.34 for Generalized Anxiety Disorder-7 and Hedge's g = 0.21 for Patient Health Questionnaire-9 between the two groups. Conclusions mindLAMP shows promising results in improving anxiety and depression outcomes in participants. Though our results mirror the current literature in assessing mental health apps' efficacy, they remain preliminary and will be used to inform a larger, well-powered study to further elucidate the efficacy of mindLAMP.
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Affiliation(s)
- Sarah Chang
- Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Noy Alon
- Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - John Torous
- Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA, USA
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