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Rothman B, Slomkowski M, Speier A, Rush AJ, Trivedi MH, Lawson E, Fahmy M, Carpenter D, Chen D, Forbes A. Evaluating the Efficacy of a Digital Therapeutic (CT-152) as an Adjunct to Antidepressant Treatment in Adults With Major Depressive Disorder: Protocol for the MIRAI Remote Study. JMIR Res Protoc 2024; 13:e56960. [PMID: 39163592 DOI: 10.2196/56960] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 05/31/2024] [Accepted: 06/17/2024] [Indexed: 08/22/2024] Open
Abstract
BACKGROUND Major depressive disorder (MDD) is common worldwide and can be highly disabling. People with MDD face many barriers to treatment and may not experience full symptom relief even when treated. Therefore, new treatment modalities are needed for MDD. Digital therapeutics (DTx) may provide people with MDD an additional treatment option. OBJECTIVE This study aimed to describe a phase 3 remote, multicenter, randomized, masked, sham-controlled trial evaluating the efficacy of a smartphone app-based DTx (CT-152) in adult participants diagnosed with MDD, used as an adjunct to antidepressant therapy (ADT). METHODS Participants aged 22-64 years with a current primary diagnosis of MDD and an inadequate response to ADT were included. Participants were randomized 1:1 to CT-152 or a sham DTx. CT-152 is a smartphone app-based DTx that delivers a cognitive-emotional and behavioral therapeutic intervention. The core components of CT-152 are the Emotional Faces Memory Task exercises, brief lessons to learn and apply key therapeutic skills, and SMS text messaging to reinforce lessons and encourage engagement with the app. The sham DTx is a digital working memory exercise with emotionally neutral stimuli designed to match CT-152 for time and attention. Participants took part in the trial for up to 13 weeks. The trial included a screening period of up to 3 weeks, a treatment period of 6 weeks, and an extension period of 4 weeks to assess the durability of the effect. Sites and participants had the option of an in-person or remote screening visit; the remaining trial visits were remote. Efficacy was evaluated using the Montgomery-Åsberg Depression Rating Scale, the Generalized Anxiety Disorder-7, Clinical Global Impression-Severity scale, the Patient Health Questionnaire-9, and the World Health Organization Disability Assessment Schedule 2.0. The durability of the effect was evaluated with the Montgomery-Åsberg Depression Rating Scale and Generalized Anxiety Disorder-7 scale. Adverse events were also assessed. Satisfaction, measured by the Participant and Healthcare Professional Satisfaction Scales, and health status, measured by the EQ-5D-5L, were summarized using descriptive statistics. RESULTS This study was initiated in February 2021 and had a primary completion date in October 2022. CONCLUSIONS This represents the methodological design for the first evaluation of CT-152 as an adjunct to ADT. This study protocol is methodologically robust and incorporates many aspects of conventional pivotal pharmaceutical phase 3 trial design, such as randomization and safety end points. Novel considerations included the use of a sham comparator, masking considerations for visible app content, and outcome measures relevant to DTx. The rigor of this methodology will provide a more comprehensive understanding of the effectiveness of CT-152. TRIAL REGISTRATION ClinicalTrials.gov NCT04770285; https://clinicaltrials.gov/study/NCT04770285. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) RR1-10.2196/56960.
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Affiliation(s)
- Brian Rothman
- Otsuka Pharmaceutical Development & Commercialization, Inc, Princeton, NJ, United States
| | - Mary Slomkowski
- Otsuka Pharmaceutical Development & Commercialization, Inc, Princeton, NJ, United States
| | - Austin Speier
- Click Therapeutics, Inc, New York, NY, United States
| | - A John Rush
- School of Medicine, Duke University, Durham, NC, United States
- Duke-National University of Singapore Medical School, Singapore, Singapore
| | - Madhukar H Trivedi
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, United States
- O'Donnell Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Erica Lawson
- Otsuka Pharmaceutical Development & Commercialization, Inc, Princeton, NJ, United States
| | - Michael Fahmy
- Otsuka Pharmaceutical Development & Commercialization, Inc, Princeton, NJ, United States
| | | | - Dalei Chen
- Otsuka Pharmaceutical Development & Commercialization, Inc, Princeton, NJ, United States
| | - Ainslie Forbes
- Otsuka Pharmaceutical Development & Commercialization, Inc, Princeton, NJ, United States
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Fulford D, Marsch LA, Pratap A. Prescription Digital Therapeutics: An Emerging Treatment Option for Negative Symptoms in Schizophrenia. Biol Psychiatry 2024:S0006-3223(24)01430-6. [PMID: 38960019 DOI: 10.1016/j.biopsych.2024.06.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Revised: 06/03/2024] [Accepted: 06/26/2024] [Indexed: 07/05/2024]
Abstract
Digital therapeutics-web-based programs, smartphone applications, and wearable devices designed to prevent, treat, or manage clinical conditions through software-driven, evidence-based intervention-can provide accessible alternatives and/or may supplement standard care for patients with serious mental illnesses, including schizophrenia. In this article, we provide a targeted summary of the rapidly growing field of digital therapeutics for schizophrenia and related serious mental illnesses. First, we define digital therapeutics. Then, we provide a brief summary of the emerging evidence of the efficacy of digital therapeutics for improving clinical outcomes, focusing on potential mechanisms of action for addressing some of the most challenging problems, including negative symptoms of psychosis. Our focus on these promising targets for digital therapeutics, including the latest in prescription models in the commercial space, highlights future directions for research and practice in this exciting field.
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Affiliation(s)
- Daniel Fulford
- Sargent College of Health & Rehabilitation Sciences, Boston University, Boston, Massachusetts; Psychological & Brain Sciences, Boston University, Boston, Massachusetts.
| | - Lisa A Marsch
- Center for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire
| | - Abhishek Pratap
- Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, Connecticut; Department of Biomedical Informatics and Medical Education, School of Medicine, University of Washington, Seattle, Washington; Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom; School of Medicine, Anatomy & Neurobiology, Boston University, Boston, Massachusetts
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Torous J, Smith KA, Hardy A, Vinnikova A, Blease C, Milligan L, Hidalgo-Mazzei D, Lambe S, Marzano L, Uhlhaas PJ, Ostinelli EG, Anmella G, Zangani C, Aronica R, Dwyer B, Cipriani A. Digital health interventions for schizophrenia: Setting standards for mental health. Schizophr Res 2024; 267:392-395. [PMID: 38640849 DOI: 10.1016/j.schres.2024.04.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Revised: 04/02/2024] [Accepted: 04/08/2024] [Indexed: 04/21/2024]
Affiliation(s)
- John Torous
- Division of Digital Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02446, USA.
| | - Katharine A Smith
- Oxford Precision Psychiatry Lab, NIHR Oxford Health Biomedical Research Centre, Oxford, UK; Department of Psychiatry, University of Oxford, Oxford, UK; Oxford Health NHS Foundation Trust, Warneford Hospital, Oxford, UK
| | - Amy Hardy
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; South London & Maudsley NHS Foundation Trust, London, UK
| | | | - Charlotte Blease
- Participatory eHealth and Health Data Research Group, Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden; Digital Psychiatry, Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, USA
| | | | - Diego Hidalgo-Mazzei
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Experimental Psychology, University of Oxford, UK
| | - Sinead Lambe
- Oxford Health NHS Foundation Trust, Warneford Hospital, Oxford, UK; Department of Experimental Psychology, University of Oxford, UK
| | - Lisa Marzano
- School of Science and Technology, Middlesex University, UK
| | - Peter J Uhlhaas
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK; Charité - Universitätsmedizin Berlin, Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Child and Adolescent Psychiatry, Augustenburger Platz 1, 13353 Berlin, Germany
| | - Edoardo G Ostinelli
- Oxford Precision Psychiatry Lab, NIHR Oxford Health Biomedical Research Centre, Oxford, UK; Department of Psychiatry, University of Oxford, Oxford, UK; Oxford Health NHS Foundation Trust, Warneford Hospital, Oxford, UK
| | - Gerard Anmella
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain
| | - Caroline Zangani
- Oxford Precision Psychiatry Lab, NIHR Oxford Health Biomedical Research Centre, Oxford, UK; Department of Psychiatry, University of Oxford, Oxford, UK; Oxford Health NHS Foundation Trust, Warneford Hospital, Oxford, UK
| | - Rosario Aronica
- Fondazione IRCCS Ca' Granda- Ospedale Maggiore Policlinico, Department of Neurosciences and Mental Health, Milan, Italy; Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Bridget Dwyer
- Division of Digital Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02446, USA
| | - Andrea Cipriani
- Oxford Precision Psychiatry Lab, NIHR Oxford Health Biomedical Research Centre, Oxford, UK; Department of Psychiatry, University of Oxford, Oxford, UK; Oxford Health NHS Foundation Trust, Warneford Hospital, Oxford, UK
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Fuhrmann LM, Weisel KK, Harrer M, Kulke JK, Baumeister H, Cuijpers P, Ebert DD, Berking M. Additive effects of adjunctive app-based interventions for mental disorders - A systematic review and meta-analysis of randomised controlled trials. Internet Interv 2024; 35:100703. [PMID: 38225971 PMCID: PMC10788289 DOI: 10.1016/j.invent.2023.100703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 12/11/2023] [Accepted: 12/17/2023] [Indexed: 01/17/2024] Open
Abstract
Background It is uncertain whether app-based interventions add value to existing mental health care. Objective To examine the incremental effects of app-based interventions when used as adjunct to mental health interventions. Methods We searched PubMed, PsycINFO, Scopus, Web of Science, and Cochrane Library databases on September 15th, 2023, for randomised controlled trials (RCTs) on mental health interventions with an adjunct app-based intervention compared to the same intervention-only arm for adults with mental disorders or respective clinically relevant symptomatology. We conducted meta-analyses on symptoms of different mental disorders at postintervention. PROSPERO, CRD42018098545. Results We identified 46 RCTs (4869 participants). Thirty-two adjunctive app-based interventions passively or actively monitored symptoms and behaviour, and in 13 interventions, the monitored data were sent to a therapist. We found additive effects on symptoms of depression (g = 0.17; 95 % CI 0.02 to 0.33; k = 7 comparisons), anxiety (g = 0.80; 95 % CI 0.06 to 1.54; k = 3), mania (g = 0.2; 95 % CI 0.02 to 0.38; k = 4), smoking cessation (g = 0.43; 95 % CI 0.29 to 0.58; k = 10), and alcohol use (g = 0.23; 95 % CI 0.08 to 0.39; k = 7). No significant effects were found on symptoms of depression within a bipolar disorder (g = -0.07; 95 % CI -0.37 to 0.23, k = 4) and eating disorders (g = -0.02; 95 % CI -0.44 to 0.4, k = 3). Studies on depression, mania, smoking, and alcohol use had a low heterogeneity between the trials. For other mental disorders, only single studies were identified. Only ten studies had a low risk of bias, and 25 studies reported insufficient statistical power. Discussion App-based interventions may be used to enhance mental health interventions to further reduce symptoms of depression, anxiety, mania, smoking, and alcohol use. However, the effects were small, except for anxiety, and limited due to study quality. Further high-quality research with larger sample sizes is warranted to better understand how app-based interventions can be most effectively combined with established interventions to improve outcomes.
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Affiliation(s)
- Lukas M. Fuhrmann
- Department of Clinical Psychology and Psychotherapy, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Kiona K. Weisel
- Department of Clinical Psychology and Psychotherapy, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Mathias Harrer
- Department of Clinical Psychology and Psychotherapy, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
- Department of Psychology and Digital Mental Health Care, Technical University Munich, Munich, Germany
| | - Jennifer K. Kulke
- Department of Clinical Psychology and Psychotherapy, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
- Department of Psychology and Digital Mental Health Care, Technical University Munich, Munich, Germany
| | - Harald Baumeister
- Department of Clinical Psychology and Psychotherapy, University of Ulm, Ulm, Germany
| | - Pim Cuijpers
- Department of Clinical, Neuro and Developmental Psychology, Vrije Universiteit Amsterdam, Amsterdam Public Health research institute, Amsterdam, the Netherlands
| | - David D. Ebert
- Department of Psychology and Digital Mental Health Care, Technical University Munich, Munich, Germany
| | - Matthias Berking
- Department of Clinical Psychology and Psychotherapy, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
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Goldberg SB, Sun S, Carlbring P, Torous J. Selecting and describing control conditions in mobile health randomized controlled trials: a proposed typology. NPJ Digit Med 2023; 6:181. [PMID: 37775522 PMCID: PMC10541862 DOI: 10.1038/s41746-023-00923-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Accepted: 09/20/2023] [Indexed: 10/01/2023] Open
Abstract
Hundreds of randomized controlled trials (RCTs) have tested the efficacy of mobile health (mHealth) tools for a wide range of mental and behavioral health outcomes. These RCTs have used a variety of control condition types which dramatically influence the scientific inferences that can be drawn from a given study. Unfortunately, nomenclature across mHealth RCTs is inconsistent and meta-analyses commonly combine control conditions that differ in potentially important ways. We propose a typology of control condition types in mHealth RCTs. We define 11 control condition types, discuss key dimensions on which they differ, provide a decision tree for selecting and identifying types, and describe the scientific inferences each comparison allows. We propose a five-tier comparison strength gradation along with four simplified categorization schemes. Lastly, we discuss unresolved definitional, ethical, and meta-analytic issues related to the categorization of control conditions in mHealth RCTs.
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Affiliation(s)
- Simon B Goldberg
- Department of Counseling Psychology, University of Wisconsin-Madison, Madison, WI, USA.
- Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI, USA.
| | - Shufang Sun
- Department of Behavioral and Social Sciences, Brown University School of Public Health, Providence, RI, USA
- International Health Institute, Brown University School of Public Health, Providence, RI, USA
- Mindfulness Center, Brown University School of Public Health, Providence, RI, USA
| | - Per Carlbring
- Department of Psychology, Stockholm University, Stockholm, Sweden
| | - John Torous
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
- Harvard Business School, Boston, MA, USA
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Grasa E, Seppälä J, Alonso-Solis A, Haapea M, Isohanni M, Miettunen J, Caro Mendivelso J, Almazan C, Rubinstein K, Caspi A, Unoka Z, Farkas K, Usall J, Ochoa S, van der Graaf S, Jewell C, Triantafillou A, Stevens M, Reixach E, Berdun J, Corripio I. m-RESIST, a Mobile Therapeutic Intervention for Treatment-Resistant Schizophrenia: Feasibility, Acceptability, and Usability Study. JMIR Form Res 2023; 7:e46179. [PMID: 37389933 PMCID: PMC10365616 DOI: 10.2196/46179] [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: 02/07/2023] [Revised: 04/21/2023] [Accepted: 04/23/2023] [Indexed: 07/01/2023] Open
Abstract
BACKGROUND In the European Union, around 5 million people are affected by psychotic disorders, and approximately 30%-50% of people with schizophrenia have treatment-resistant schizophrenia (TRS). Mobile health (mHealth) interventions may be effective in preventing relapses, increasing treatment adherence, and managing some of the symptoms of schizophrenia. People with schizophrenia seem willing and able to use smartphones to monitor their symptoms and engage in therapeutic interventions. mHealth studies have been performed with other clinical populations but not in populations with TRS. OBJECTIVE The purpose of this study was to present the 3-month prospective results of the m-RESIST intervention. This study aims to assess the feasibility, acceptability, and usability of the m-RESIST intervention and the satisfaction among patients with TRS after using this intervention. METHODS A prospective multicenter feasibility study without a control group was undertaken with patients with TRS. This study was performed at 3 sites: Sant Pau Hospital (Barcelona, Spain), Semmelweis University (Budapest, Hungary), and Sheba Medical Center and Gertner Institute of Epidemiology and Health Policy Research (Ramat-Gan, Israel). The m-RESIST intervention consisted of a smartwatch, a mobile app, a web-based platform, and a tailored therapeutic program. The m-RESIST intervention was delivered to patients with TRS and assisted by mental health care providers (psychiatrists and psychologists). Feasibility, usability, acceptability, and user satisfaction were measured. RESULTS This study was performed with 39 patients with TRS. The dropout rate was 18% (7/39), the main reasons being as follows: loss to follow-up, clinical worsening, physical discomfort of the smartwatch, and social stigma. Patients' acceptance of m-RESIST ranged from moderate to high. The m-RESIST intervention could provide better control of the illness and appropriate care, together with offering user-friendly and easy-to-use technology. In terms of user experience, patients indicated that m-RESIST enabled easier and quicker communication with clinicians and made them feel more protected and safer. Patients' satisfaction was generally good: 78% (25/32) considered the quality of service as good or excellent, 84% (27/32) reported that they would use it again, and 94% (30/32) reported that they were mostly satisfied. CONCLUSIONS The m-RESIST project has provided the basis for a new modular program based on novel technology: the m-RESIST intervention. This program was well-accepted by patients in terms of acceptability, usability, and satisfaction. Our results offer an encouraging starting point regarding mHealth technologies for patients with TRS. TRIAL REGISTRATION ClinicalTrials.gov NCT03064776; https://clinicaltrials.gov/ct2/show/record/NCT03064776. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) RR2-10.1136/bmjopen-2017-021346.
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Affiliation(s)
- Eva Grasa
- Mental Health, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
| | - Jussi Seppälä
- Social Insurance Institution of Finland, Kuopio, Finland
- Research Unit of Population Health, University of Oulu, Oulu, Finland
| | - Anna Alonso-Solis
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
- Mental Health Division, Fundació Althaia, Xarxa Assistencial Universitaria de Manresa, Manresa, Spain
| | - Marianne Haapea
- Research Unit of Population Health, University of Oulu, Oulu, Finland
- Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
- Department of Psychiatry, Oulu University Hospital, Oulu, Finland
| | - Matti Isohanni
- Research Unit of Population Health, University of Oulu, Oulu, Finland
| | - Jouko Miettunen
- Research Unit of Population Health, University of Oulu, Oulu, Finland
- Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | | | - Cari Almazan
- Agency for Health Quality and Assessment of Catalonia (AQuAS), Barcelona, Spain
| | - Katya Rubinstein
- The Gertner Institute of Epidemiology and Health Policy Research, Sheba Medical Center, Tel-Aviv University, Tel-Aviv, Israel
| | - Asaf Caspi
- The Gertner Institute of Epidemiology and Health Policy Research, Sheba Medical Center, Tel-Aviv University, Tel-Aviv, Israel
| | - Zsolt Unoka
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Kinga Farkas
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Judith Usall
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
- Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain
- Etiopatogènia i tractament dels trastorns mentals greus (MERITT), Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Spain
| | - Susana Ochoa
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
- Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain
- Etiopatogènia i tractament dels trastorns mentals greus (MERITT), Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Spain
| | | | | | | | - Matthias Stevens
- EDiT Department, imec, Ghent/Antwerp, Belgium
- Solutions Department, imec, Leuven, Belgium
| | - Elisenda Reixach
- TicSalut Health Department, Generalitat de Catalunya, Barcelona, Spain
| | - Jesus Berdun
- Digital Health Unit, Hospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Barcelona, Spain
| | - Iluminada Corripio
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
- Mental Health and Psychiatry Department, Vic Hospital Consortium, Vic, Spain
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Oh E, Gang M. [Effect of Digital Health Interventions on Psychotic Symptoms among Persons with Severe Mental Illness in Community: A Systematic Review and Meta-Analysis]. J Korean Acad Nurs 2023; 53:69-86. [PMID: 36898686 DOI: 10.4040/jkan.22121] [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: 10/06/2022] [Revised: 12/28/2022] [Accepted: 01/31/2023] [Indexed: 03/09/2023]
Abstract
PURPOSE This study aimed to evaluate the effects of digital health interventions on the psychotic symptoms among people with severe mental illness in the community. METHODS A systematic review and meta-analysis were conducted in accordance with the Cochrane Intervention Research Systematic Review Manual and PRISMA. A literature search was conducted of published randomized controlled trials (RCTs) for digital health interventions from January 2022 to April 2022. RevMan software 5.3 was used for quality assessment and meta-analysis. RESULTS A total 14 studies out of 9,864 studies were included in the review, and 13 were included in meta-analysis. The overall effect size of digital health interventions on psychotic symptoms was -0.21 (95% CI = -0.32 to -0.10). Sub-analysis showed that the reduction of the psychotic symptoms was effective in the schizophrenia spectrum group (SMD = -.0.22; 95% CI = -.0.36 to -0.09), web (SMD = -0.41; 95% CI = -0.82 to 0.01), virtual reality (SMD = -0.33; 95% CI = -0.56 to -0.10), mobile (SMD = -0.15; 95% CI = -0.28 to -0.03), intervention period of less than 3 months (SMD = -0.23; 95% CI = -0.35 to -0.11), and non-treatment group (SMD = -0.23; 95% CI = -0.36 to -0.11). CONCLUSION These findings suggest that digital health interventions alleviate psychotic symptoms in patients with severe mental illnesses. However, well-designed digital health studies should be conducted in the future.
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Affiliation(s)
- Eunjin Oh
- Department of Nursing, Songwon University, Gwangju, Korea
| | - Moonhee Gang
- College of Nursing, Chungnam National University, Daejeon, Korea.
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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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Kwon S, Firth J, Joshi D, Torous J. Accessibility and availability of smartphone apps for schizophrenia. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2022; 8:98. [PMID: 36385116 PMCID: PMC9668219 DOI: 10.1038/s41537-022-00313-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 11/05/2022] [Indexed: 05/25/2023]
Abstract
App-based interventions have the potential to enhance access to and quality of care for patients with schizophrenia. However, less is known about the current state of schizophrenia apps in research and how those translate to publicly available apps. This study, therefore, aimed to review schizophrenia apps offered on marketplaces and research literature with a focus on accessibility and availability. A search of recent reviews, gray literature, PubMed, and Google Scholar was conducted in August 2022. A search of the U.S. Apple App Store and Google Play App Store was conducted in July 2022. All eligible studies and apps were systematically screened/reviewed. The academic research search produced 264 results; 60 eligible studies were identified. 51.7% of research apps were built on psychosis-specific platforms and 48.3% of research apps were built on non-specific platforms. 83.3% of research apps offered monitoring functionalities. Only nine apps, two designed on psychosis-specific platforms and seven on non-specific platforms were easily accessible. The search of app marketplaces uncovered 537 apps; only six eligible marketplace apps were identified. 83.3% of marketplace apps only offered psychoeducation. All marketplace apps lacked frequent updates with the average time since last update 1121 days. There are few clinically relevant apps accessible to patients on the commercial marketplaces. While research efforts are expanding, many research apps are unavailable today. Better translation of apps from research to the marketplace and a focus on sustainable interventions are important targets for the field.
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Affiliation(s)
- Sam Kwon
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Joseph Firth
- Division of Psychology and Mental Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
- Greater Manchester Mental Health NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Devayani Joshi
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - John Torous
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA.
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Torous J. A path towards progress: lessons from the hard things about digital mental health. World Psychiatry 2022; 21:419-420. [PMID: 36073703 PMCID: PMC9453910 DOI: 10.1002/wps.21003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Affiliation(s)
- John Torous
- Beth Israel Deaconess Medical Center, Boston, MA, USA
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11
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Torous J, Stern AD, Bourgeois FT. Regulatory considerations to keep pace with innovation in digital health products. NPJ Digit Med 2022; 5:121. [PMID: 35986056 PMCID: PMC9390099 DOI: 10.1038/s41746-022-00668-9] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 07/28/2022] [Indexed: 12/04/2022] Open
Abstract
Rapid innovation and proliferation of software as a medical device have accelerated the clinical use of digital technologies across a wide array of medical conditions. Current regulatory pathways were developed for traditional (hardware) medical devices and offer a useful structure, but the evolution of digital devices requires concomitant innovation in regulatory approaches to maximize the potential benefits of these emerging technologies. A number of specific adaptations could strengthen current regulatory oversight while promoting ongoing innovation.
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Accounting for Patient Engagement in Randomized Controlled Trials Evaluating Digital Cognitive Behavioral Therapies. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12104952] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background: Cognitive behavioral therapy (CBT) can be a useful treatment option for various mental health disorders. Modern advances in information technology and mobile communication enable delivery of state-of-the-art CBT programs via smartphones, either as stand-alone or as an adjunct treatment augmenting traditional sessions with a therapist. Experimental CBTs require careful assessment in randomized clinical trials (RCTs). Methods: We investigate some statistical issues for an RCT comparing efficacy of an experimental CBT intervention for a mental health disorder against the control. Assuming a linear model for the clinical outcome and patient engagement as an influential covariate, we investigate two common statistical approaches to inference—analysis of covariance (ANCOVA) and a two-sample t-test. We also study sample size requirements for the described experimental setting. Results: Both ANCOVA and a two-sample t-test are appropriate for the inference on treatment difference at the average observed level of engagement. However, ANCOVA produces estimates with lower variance and may be more powerful. Furthermore, unlike the t-test, ANCOVA allows one to perform treatment comparison at the levels of engagement other than the average level observed in the study. Larger sample sizes may be required to ensure experiments are sufficiently powered if one is interested in comparing treatment effects for different levels of engagement. Conclusions: ANCOVA with proper adjustment for engagement should be used for the for the described experimental setting. Uncertainty on engagement patterns should be taken into account at the study design stage.
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