1
|
Southwick L, Sharma M, Rai S, Beidas RS, Mandell DS, Asch DA, Curtis B, Guntuku SC, Merchant RM. Integrating Patient-Generated Digital Data Into Mental Health Therapy: Mixed Methods Analysis of User Experience. JMIR Ment Health 2024; 11:e59785. [PMID: 39696769 DOI: 10.2196/59785] [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: 04/23/2024] [Revised: 10/03/2024] [Accepted: 10/04/2024] [Indexed: 12/20/2024] Open
Abstract
Background Therapists and their patients increasingly discuss digital data from social media, smartphone sensors, and other online engagements within the context of psychotherapy. Objective We examined patients' and mental health therapists' experiences and perceptions following a randomized controlled trial in which they both received regular summaries of patients' digital data (eg, dashboard) to review and discuss in session. The dashboard included data that patients consented to share from their social media posts, phone usage, and online searches. Methods Following the randomized controlled trial, patient (n=56) and therapist (n=44) participants completed a debriefing survey after their study completion (from December 2021 to January 2022). Participants were asked about their experience receiving a digital data dashboard in psychotherapy via closed- and open-ended questions. We calculated descriptive statistics for closed-ended questions and conducted qualitative coding via NVivo (version 10; Lumivero) and natural language processing using the machine learning tool latent Dirichlet allocation to analyze open-ended questions. Results Of 100 participants, nearly half (n=48, 49%) described their experience with the dashboard as "positive," while the other half noted a "neutral" experience. Responses to the open-ended questions resulted in three thematic areas (nine subcategories): (1) dashboard experience (positive, neutral or negative, and comfortable); (2) perception of the dashboard's impact on enhancing therapy (accountability, increased awareness over time, and objectivity); and (3) dashboard refinements (additional sources, tailored content, and privacy). Conclusions Patients reported that receiving their digital data helped them stay "accountable," while therapists indicated that the dashboard helped "tailor treatment plans." Patient and therapist surveys provided important feedback on their experience regularly discussing dashboards in psychotherapy.
Collapse
Affiliation(s)
- Lauren Southwick
- Department of Emergency Medicine, University of Pennsylvania Perelman School of Medicine, 3600 Civic Center Boulevard, Philadelphia, PA, 19104, United States, 1-914-582-6995
- Center for Health Care Transformation and Innovation, Penn Medicine, Philadelphia, PA, United States
| | - Meghana Sharma
- Department of Emergency Medicine, University of Pennsylvania Perelman School of Medicine, 3600 Civic Center Boulevard, Philadelphia, PA, 19104, United States, 1-914-582-6995
- Center for Health Care Transformation and Innovation, Penn Medicine, Philadelphia, PA, United States
| | - Sunny Rai
- Department of Computer and Information Science, School of Engineering, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Rinad S Beidas
- Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
| | - David S Mandell
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - David A Asch
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Brenda Curtis
- Intramural Research Program, National Institute on Drug Abuse, Baltimore, MD, United States
| | - Sharath Chandra Guntuku
- Center for Health Care Transformation and Innovation, Penn Medicine, Philadelphia, PA, United States
- Department of Computer and Information Science, School of Engineering, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Raina M Merchant
- Department of Emergency Medicine, University of Pennsylvania Perelman School of Medicine, 3600 Civic Center Boulevard, Philadelphia, PA, 19104, United States, 1-914-582-6995
- Center for Health Care Transformation and Innovation, Penn Medicine, Philadelphia, PA, United States
| |
Collapse
|
2
|
Meyer-Kalos P, Owens G, Fisher M, Wininger L, Williams-Wengerd A, Breen K, Abate JP, Currie A, Olinger N, Vinogradov S. Putting measurement-based care into action: a multi-method study of the benefits of integrating routine client feedback in coordinated specialty care programs for early psychosis. BMC Psychiatry 2024; 24:871. [PMID: 39623335 PMCID: PMC11610165 DOI: 10.1186/s12888-024-06258-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 11/05/2024] [Indexed: 12/06/2024] Open
Abstract
BACKGROUND Measurement-based care (MBC) is an effective tool in the delivery of evidence-based practices (EBPs). MBC utilizes feedback loops to share information and drive changes throughout a learning healthcare system. Few studies have demonstrated this practice in team-based care for young people with early psychosis. This paper describes the development of a personalized feedback report derived from routine assessments that is shared with clients and clinicians as part of a MBC process. METHODS We used a multi-method approach to evaluate the implementation of a personalized feedback report at 5 early psychosis coordinated specialty care programs (CSC). We compared clients enrolled in CSC who did and did not receive a feedback report over the first 6 months of treatment. The sample included 204 clients: 146 who did not receive the feedback report (treatment as usual, TAU) and were enrolled over 2 years, and 58 who received the feedback report. A subset of 67 clients completed measures at both intake and 6-month follow-up, including 42 who received the personalized feedback report and 25 who did not. We compared the two groups with regard to self-reported symptoms, likelihood of completing treatment, and perception of shared decision making. We conducted qualitative interviews with 5 clients and 5 clinicians to identify the benefits and challenges associated with the personalized feedback report. RESULTS The total sample showed significant improvements in shared decision-making and in their intent to complete the program. Post hoc analyses revealed significant increases in the personalized feedback group, and non-significant changes in the TAU group, although group-by-time interactions did not reach statistical significance. The feedback report group engaged in significantly more sessions of Supported Employment and Education (SEE), case management, and peer support, and fewer medication visits over the first 6 months of treatment. Both groups showed significant improvement in symptoms and functioning. Results from the qualitative analysis indicated that the experience of receiving the reports was valuable and validating for both patients and clinicians. CONCLUSIONS A personalized feedback report was integrated into standard of care for early psychosis programs. This process may improve shared decision-making, strengthen the likelihood to stay in treatment, and increase treatment attendance in psychosocial interventions. We posit that this process facilitates recovery-oriented care, strengths-focused treatment planning, enhances intrinsic motivation, and strengthens the therapeutic alliance.
Collapse
Affiliation(s)
- Piper Meyer-Kalos
- Department of Psychiatry & Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN, USA.
| | - Grace Owens
- Department of Psychiatry & Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Melissa Fisher
- Department of Psychiatry & Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Lionel Wininger
- Department of Psychiatry & Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Anne Williams-Wengerd
- Department of Psychiatry & Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Kimberleigh Breen
- Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN, USA
| | - Josephine Pita Abate
- Department of Psychiatry & Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Ariel Currie
- Department of Psychiatry & Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Nathan Olinger
- Department of Psychiatry & Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Sophia Vinogradov
- Department of Psychiatry & Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN, USA
| |
Collapse
|
3
|
Aldis R, Rosenfeld LC, Mulvaney-Day N, Lanca M, Zona K, Lam JA, Asfour J, Meltzer JC, Leff HS, Fulwiler C, Wang P, Progovac AM. Determinants of remote measurement-based care uptake in a safety net outpatient psychiatry department as part of learning health system transition. Learn Health Syst 2024; 8:e10416. [PMID: 38883875 PMCID: PMC11176570 DOI: 10.1002/lrh2.10416] [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: 10/31/2023] [Revised: 02/20/2024] [Accepted: 02/26/2024] [Indexed: 06/18/2024] Open
Abstract
Introduction Behavioral measurement-based care (MBC) can improve patient outcomes and has also been advanced as a critical learning health system (LHS) tool for identifying and mitigating potential disparities in mental health treatment. However, little is known about the uptake of remote behavioral MBC in safety net settings, or possible disparities occurring in remote MBC implementation. Methods This study uses electronic health record data to study variation in completion rates at the clinic and patient level of a remote MBC symptom measure tool during the first 6 months of implementation at three adult outpatient psychiatry clinics in a safety net health system. Provider-reported barriers to MBC adoption were also measured using repeated surveys at one of the three sites. Results Out of 1219 patients who were sent an MBC measure request, uptake of completing at least one measure varied by clinic: General Adult Clinic, 38% (n = 262 of 696); Substance Use Clinic, 28% (n = 73 of 265); and Transitions Clinic, 17% (n = 44 of 258). Compared with White patients, Black and Portuguese or Brazilian patients had lower uptake. Older patients also had lower uptake. Spanish language of care was associated with much lower uptake at the patient level. Significant patient-level disparities in uptake persisted after adjusting for the clinic, mental health diagnoses, and number of measure requests sent. Providers cited time within visits and bandwidth in their workflow as the greatest consistent barriers to discussing MBC results with patients. Conclusions There are significant disparities in MBC uptake at the patient and clinic level. From an LHS data infrastructure perspective, safety net health systems may need to address the need for possible ways to adapt MBC to better fit their populations and clinical needs, or identify targeted implementation strategies to close data gaps for the identified disparity populations.
Collapse
Affiliation(s)
- Rajendra Aldis
- Cambridge Health Alliance Department of Psychiatry Cambridge Massachusetts USA
- Harvard Medical School Department of Psychiatry Boston Massachusetts USA
| | - Lisa C Rosenfeld
- Cambridge Health Alliance Department of Psychiatry Cambridge Massachusetts USA
- Harvard Medical School Department of Psychiatry Boston Massachusetts USA
| | - Norah Mulvaney-Day
- Cambridge Health Alliance Department of Psychiatry Cambridge Massachusetts USA
- Harvard Medical School Department of Psychiatry Boston Massachusetts USA
| | - Margaret Lanca
- Cambridge Health Alliance Department of Psychiatry Cambridge Massachusetts USA
- Harvard Medical School Department of Psychiatry Boston Massachusetts USA
| | - Kate Zona
- Cambridge Health Alliance Department of Psychiatry Cambridge Massachusetts USA
- Harvard Medical School Department of Psychiatry Boston Massachusetts USA
| | - Jeffrey A Lam
- Cambridge Health Alliance Department of Psychiatry Cambridge Massachusetts USA
- Harvard Medical School Department of Psychiatry Boston Massachusetts USA
| | - Julia Asfour
- Cambridge Health Alliance Department of Psychiatry Cambridge Massachusetts USA
- Public Health and Community Medicine Tufts University School of Medicine Boston Massachusetts USA
| | - Jonah C Meltzer
- Cambridge Health Alliance Department of Psychiatry Cambridge Massachusetts USA
- Public Health and Community Medicine Tufts University School of Medicine Boston Massachusetts USA
| | - H Stephen Leff
- Cambridge Health Alliance Department of Psychiatry Cambridge Massachusetts USA
- Harvard Medical School Department of Psychiatry Boston Massachusetts USA
| | - Carl Fulwiler
- Cambridge Health Alliance Department of Psychiatry Cambridge Massachusetts USA
- Harvard Medical School Department of Psychiatry Boston Massachusetts USA
| | - Philip Wang
- Cambridge Health Alliance Department of Psychiatry Cambridge Massachusetts USA
- Harvard Medical School Department of Psychiatry Boston Massachusetts USA
| | - Ana M Progovac
- Cambridge Health Alliance Department of Psychiatry Cambridge Massachusetts USA
- Harvard Medical School Department of Psychiatry Boston Massachusetts USA
| |
Collapse
|
4
|
Higashi RT, Etingen B, Richardson E, Palmer J, Zocchi MS, Bixler FR, Smith B, McMahon N, Frisbee KL, Fortney JC, Turvey C, Evans J, Hogan TP. Veteran Experiences With an mHealth App to Support Measurement-Based Mental Health Care: Results From a Mixed Methods Evaluation. JMIR Ment Health 2024; 11:e54007. [PMID: 38728684 PMCID: PMC11127133 DOI: 10.2196/54007] [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: 10/31/2023] [Revised: 02/28/2024] [Accepted: 03/15/2024] [Indexed: 05/12/2024] Open
Abstract
BACKGROUND Mental health conditions are highly prevalent among US veterans. The Veterans Health Administration (VHA) is committed to enhancing mental health care through the integration of measurement-based care (MBC) practices, guided by its Collect-Share-Act model. Incorporating the use of remote mobile apps may further support the implementation of MBC for mental health care. OBJECTIVE This study aims to evaluate veteran experiences with Mental Health Checkup (MHC), a VHA mobile app to support remote MBC for mental health. METHODS Our mixed methods sequential explanatory evaluation encompassed mailed surveys with veterans who used MHC and follow-up semistructured interviews with a subset of survey respondents. We analyzed survey data using descriptive statistics. We then compared responses between veterans who indicated having used MHC for ≥3 versus <3 months using χ2 tests. We analyzed interview data using thematic analysis. RESULTS We received 533 surveys (533/2631, for a 20% response rate) and completed 20 interviews. Findings from these data supported one another and highlighted 4 key themes. (1) The MHC app had positive impacts on care processes for veterans: a majority of MHC users overall, and a greater proportion who had used MHC for ≥3 months (versus <3 months), agreed or strongly agreed that using MHC helped them be more engaged in their health and health care (169/262, 65%), make decisions about their treatment (157/262, 60%), and set goals related to their health and health care (156/262, 60%). Similarly, interviewees described that visualizing progress through graphs of their assessment data over time motivated them to continue therapy and increased self-awareness. (2) A majority of respondents overall, and a greater proportion who had used MHC for ≥3 months (versus <3 months), agreed/strongly agreed that using MHC enhanced their communication (112/164, 68% versus 51/98, 52%; P=.009) and rapport (95/164, 58% versus 42/98, 43%; P=.02) with their VHA providers. Likewise, interviewees described how MHC helped focus therapy time and facilitated trust. (3) However, veterans also endorsed some challenges using MHC. Among respondents overall, these included difficulty understanding graphs of their assessment data (102/245, 42%), not receiving enough training on the app (73/259, 28%), and not being able to change responses to assessment questions (72/256, 28%). (4) Interviewees offered suggestions for improving the app (eg, facilitating ease of log-in, offering additional reminder features) and for increasing adoption (eg, marketing the app and its potential advantages for veterans receiving mental health care). CONCLUSIONS Although experiences with the MHC app varied, veterans were positive overall about its use. Veterans described associations between the use of MHC and engagement in their own care, self-management, and interactions with their VHA mental health providers. Findings support the potential of MHC as a technology capable of supporting the VHA's Collect-Share-Act model of MBC.
Collapse
Affiliation(s)
- Robin T Higashi
- Peter O'Donnell Jr School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX, United States
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, Bedford, MA, United States
| | - Bella Etingen
- Peter O'Donnell Jr School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX, United States
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, Bedford, MA, United States
- Research and Development Service, Dallas Veterans Affairs Medical Center, Dallas, TX, United States
| | - Eric Richardson
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, Bedford, MA, United States
- Center for Healthcare Organization and Implementation Research (CHOIR), Veterans Affairs Boston Healthcare System, Boston, MA, United States
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States
| | - Jennifer Palmer
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, Bedford, MA, United States
- Center for Healthcare Organization and Implementation Research (CHOIR), Veterans Affairs Boston Healthcare System, Boston, MA, United States
- Section of General Internal Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
| | - Mark S Zocchi
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, Bedford, MA, United States
- Center for Healthcare Organization and Implementation Research (CHOIR), Veterans Affairs Bedford Healthcare System, Bedford, MA, United States
| | - Felicia R Bixler
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, Bedford, MA, United States
- Center of Innovation for Complex Chronic Healthcare (CINCCH), Hines Veterans Affairs Hospital, Hines, IL, United States
| | - Bridget Smith
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, Bedford, MA, United States
- Center of Innovation for Complex Chronic Healthcare (CINCCH), Hines Veterans Affairs Hospital, Hines, IL, United States
- Northwestern University Feinberg School of Medicine, Chicago, IL, United States
| | - Nicholas McMahon
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, Bedford, MA, United States
- Center for Healthcare Organization and Implementation Research (CHOIR), Veterans Affairs Bedford Healthcare System, Bedford, MA, United States
| | - Kathleen L Frisbee
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, Bedford, MA, United States
- Office of Connected Care, Veterans Health Administration, US Department of Veterans Affairs, Washington, DC, United States
| | - John C Fortney
- Center of Innovation for Veteran-Centered and Value-Driven Care, Veterans Affairs Puget Sound Health Care System, Seattle, WA, United States
- Division of Population Health, Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States
| | - Carolyn Turvey
- Center for Access & Delivery Research and Evaluation, Iowa City Veterans Affairs Health Care System, Iowa City, IA, United States
- Office of Rural Health, Veterans Rural Health Resource Center - Iowa City, Iowa City Veterans Affairs Health Care System, Iowa City, IA, United States
- Department of Psychiatry, University of Iowa, Iowa City, IA, United States
| | - Jennifer Evans
- Office of Mental Health and Suicide Prevention, US Department of Veterans Affairs, Washington, DC, United States
| | - Timothy P Hogan
- Peter O'Donnell Jr School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX, United States
- eHealth Partnered Evaluation Initiative, Veterans Affairs Bedford Healthcare System, Bedford, MA, United States
- Center for Healthcare Organization and Implementation Research (CHOIR), Veterans Affairs Bedford Healthcare System, Bedford, MA, United States
| |
Collapse
|
5
|
Kuo PB, Tanana MJ, Goldberg SB, Caperton DD, Narayanan S, Atkins DC, Imel ZE. Machine-Learning-Based Prediction of Client Distress From Session Recordings. Clin Psychol Sci 2024; 12:435-446. [PMID: 39104662 PMCID: PMC11299859 DOI: 10.1177/21677026231172694] [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] [Indexed: 08/07/2024]
Abstract
Natural language processing (NLP) is a subfield of machine learning that may facilitate the evaluation of therapist-client interactions and provide feedback to therapists on client outcomes on a large scale. However, there have been limited studies applying NLP models to client outcome prediction that have (a) used transcripts of therapist-client interactions as direct predictors of client symptom improvement, (b) accounted for contextual linguistic complexities, and (c) used best practices in classical training and test splits in model development. Using 2,630 session recordings from 795 clients and 56 therapists, we developed NLP models that directly predicted client symptoms of a given session based on session recordings of the previous session (Spearman's rho =0.32, p<.001). Our results highlight the potential for NLP models to be implemented in outcome monitoring systems to improve quality of care. We discuss implications for future research and applications.
Collapse
|
6
|
Machleid F, Michnevich T, Huang L, Schröder-Frerkes L, Wiegmann C, Muffel T, Kaminski J. Remote measurement based care (RMBC) interventions for mental health-Protocol of a systematic review and meta-analysis. PLoS One 2024; 19:e0297929. [PMID: 38363769 PMCID: PMC10871474 DOI: 10.1371/journal.pone.0297929] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 01/14/2024] [Indexed: 02/18/2024] Open
Abstract
BACKGROUND Poor management of mental illnesses is associated with lower treatment adherence, chronification, avoidable re-hospitalisations, and high costs. Remote measurement based care (RMBC) interventions have gained increasing relevance due to its potential in providing a comprehensive and patient-centric approach to mental health management. OBJECTIVES The systematic review and meta-analysis aims to provide a comprehensive overview and analysis of existing evidence on the use of RMBC for patients with mental illness and to examine the effectiveness of RMBC interventions in alleviating disorder-specific symptoms, reducing relapse and improving recovery-oriented outcomes, global functioning, and quality of life. METHODS AND ANALYSIS Our multidisciplinary research team will develop a comprehensive search strategy, adapted to each electronic database (PubMed, Medline, Embase, and PsychINFO) to be examined systematically. Studies with patients formally diagnosed by the International Classification of Diseases or the Diagnostic and Statistical Manual of Mental Disorders which include assessment of self-reported psychiatric symptoms will be included. Publications will be reviewed by teams of independent researchers. Quality of studies will be assessed using the Cochrane Collaboration's tool for assessing risk of bias. Outcomes cover symptom-focused or disease-specific outcomes, relapse, recovery-focused outcomes, global functioning, quality of life and acceptability of the intervention. Further data that will be extracted includes study characteristics, target population, intervention, and tracking characteristics. Data will be synthesised qualitatively, summarising findings of the systematic review. Randomised controlled trials (RCTs) will be considered for meta-analysis if data is found comparable in terms of mental illness, study design and outcomes. Cumulative evidence will be evaluated according to the Grading of Recommendations Assessment, Development and Evaluation framework. TRIAL REGISTRATION Trial registration number: PROSPERO CRD42022356176.
Collapse
Affiliation(s)
- Felix Machleid
- Department of Psychiatry and Psychotherapy, Charité Campus Mitte, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Twyla Michnevich
- Department of Psychiatry and Psychotherapy, Charité Campus Mitte, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Leu Huang
- Department of Infectious Diseases and Respiratory Medicine, Charité Campus Virchow-Klinikum, Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Louisa Schröder-Frerkes
- Clinic for Psychiatry, Psychotherapy and Psychosomatics, Krankenhaus am Urban, Berlin, Germany
| | - Caspar Wiegmann
- Clinics for Psychiatry and Psychotherapy, Clinics at the Theodor-Wenzel-Werk, Berlin, Germany
- Recovery Cat GmbH, Berlin, Germany
| | | | - Jakob Kaminski
- Department of Psychiatry and Psychotherapy, Charité Campus Mitte, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany
- Recovery Cat GmbH, Berlin, Germany
| |
Collapse
|
7
|
Meyer-Kalos P, Owens G, Fisher M, Wininger L, Williams-Wengerd A, Breen K, Abate J, Currie A, Olinger N, Vinogradov S. Putting measurement-based care into action: A mixed methods study of the benefits of integrating routine client feedback in coordinated specialty care programs for early psychosis. RESEARCH SQUARE 2024:rs.3.rs-3918063. [PMID: 38405727 PMCID: PMC10889084 DOI: 10.21203/rs.3.rs-3918063/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Background Measurement-based care (MBC) is an effective tool in the delivery of evidence-based practices (EBPs). MBC utilizes feedback loops to share information and drive changes throughout a learning healthcare system. Few studies have demonstrated this practice in team-based care for people with early psychosis. This paper describes the development of a personalized feedback report derived from routine assessments that is shared with clients and clinicians as part of a MBC process. Methods We used a quasi pre-post comparison design with mixed methods to evaluate the implementation of a personalized feedback report at 5 early psychosis coordinated specialty care programs (CSC). We compared clients enrolled in CSC who did and did not receive a feedback report over the first 6 months of treatment. The sample included 204 clients: 146 who did not receive the feedback report and were enrolled over 2 years, and 58 who received the feedback report. A subset of 67 clients completed measures at both intake and 6-month follow-up, including 42 who received the report and 25 who did not. We compared the two groups with regard to self-reported symptoms, likelihood of completing treatment, and perception of shared decision making. We conducted qualitative interviews with 5 clients and 5 clinicians to identify the benefits and challenges associated with the personalized feedback report. Results People who received a personalized feedback report reported significant improvements in shared decision-making and had greater improvements over time in their intent to attend future treatment sessions. They engaged in more sessions for Supported Employment and Education (SEE), case management, and peer support, and fewer medication visits over the first 6 months of treatment. Both groups showed significant improvement in symptoms and functioning. Results from the qualitative analysis indicated that the experience of receiving the reports was valuable and validating for both patients and clinicians. Conclusions A personalized feedback report was integrated into standard of care for early psychosis programs. This process may improve shared decision-making, strengthen the likelihood to stay in treatment, and increase engagement in psychosocial interventions. We posit that this process facilitates strengths-focused discussions, enhances intrinsic motivation, and strengthens the therapeutic alliance.
Collapse
|
8
|
Cho CH, Lee HJ, Kim YK. Telepsychiatry in the Treatment of Major Depressive Disorders. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1456:333-356. [PMID: 39261437 DOI: 10.1007/978-981-97-4402-2_17] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/13/2024]
Abstract
This chapter explores the transformative role of telepsychiatry in managing major depressive disorders (MDD). Traversing geographical barriers and reducing stigma, this innovative branch of telemedicine leverages digital platforms to deliver effective psychiatric care. We investigate the evolution of telepsychiatry, examining its diverse interventions such as videoconferencing-based psychotherapy, medication management, and mobile applications. While offering significant advantages like increased accessibility, cost-effectiveness, and improved patient engagement, challenges in telepsychiatry include technological barriers, privacy concerns, ethical and legal considerations, and digital literacy gaps. Looking forward, emerging technologies like virtual reality, artificial intelligence, and precision medicine hold immense potential to personalize and enhance treatment effectiveness. Recognizing its limitations and advocating for equitable access, this chapter underscores telepsychiatry's power to revolutionize MDD treatment, making quality mental healthcare a reality for all.
Collapse
Affiliation(s)
- Chul-Hyun Cho
- Department of Psychiatry, Korea University College of Medicine, Seoul, Republic of Korea
| | - Heon-Jeong Lee
- Department of Psychiatry, Korea University College of Medicine, Seoul, Republic of Korea
| | - Yong-Ku Kim
- Department of Psychiatry, Korea University College of Medicine, Seoul, Republic of Korea.
| |
Collapse
|
9
|
Rosansky JA, Okst K, Tepper MC, Baumgart Schreck A, Fulwiler C, Wang PS, Schuman-Olivier Z. Participants' Engagement With and Results From a Web-Based Integrative Population Mental Wellness Program (CHAMindWell) During the COVID-19 Pandemic: Program Evaluation Study. JMIR Ment Health 2023; 10:e48112. [PMID: 37883149 PMCID: PMC10636615 DOI: 10.2196/48112] [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: 04/11/2023] [Revised: 08/31/2023] [Accepted: 09/03/2023] [Indexed: 10/27/2023] Open
Abstract
BACKGROUND The COVID-19 pandemic involved a prolonged period of collective trauma and stress during which substantial increases in mental health concerns, like depression and anxiety, were observed across the population. In this context, CHAMindWell was developed as a web-based intervention to improve resilience and reduce symptom severity among a public health care system's patient population. OBJECTIVE This program evaluation was conducted to explore participants' engagement with and outcomes from CHAMindWell by retrospectively examining demographic information and mental health symptom severity scores throughout program participation. METHODS We examined participants' symptom severity scores from repeated, web-based symptom screenings through Computerized Adaptive Testing for Mental Health (CAT-MH) surveys, and categorized participants into symptom severity-based tiers (tier 1=asymptomatic to mild; tier 2=moderate; and tier 3=severe). Participants were provided tier-based mindfulness resources, treatment recommendations, and referrals. Logistic regressions were conducted to evaluate associations between demographic variables and survey completion. The McNemar exact test and paired sample t tests were performed to evaluate changes in the numbers of participants in tier 1 versus tier 2 or 3 and changes in depression, anxiety, and posttraumatic stress disorder severity scores between baseline and follow-up. RESULTS The program enrolled 903 participants (664/903, 73.5% female; 556/903, 61.6% White; 113/903, 12.5% Black; 84/903, 9.3% Asian; 7/903, 0.8% Native; 36/903, 4% other; and 227/903, 25.1% Hispanic) between December 16, 2020, and March 17, 2022. Of those, 623 (69%) completed a baseline CAT-MH survey, and 196 completed at least one follow-up survey 3 to 6 months after baseline. White racial identity was associated with completing baseline CAT-MH (odds ratio [OR] 1.80, 95% CI 1.14-2.84; P=.01). Participants' odds of having symptom severity below the clinical threshold (ie, tier 1) were significantly greater at follow-up (OR 2.60, 95% CI 1.40-5.08; P=.001), and significant reductions were observed across symptom domains over time. CONCLUSIONS CHAMindWell is associated with reduced severity of mental health symptoms. Future work should aim to address program engagement inequities and attrition and compare the impacts of CHAMindWell to a control condition to better characterize its effects.
Collapse
Affiliation(s)
- Joseph A Rosansky
- Department of Psychiatry, Cambridge Health Alliance, Cambridge, MA, United States
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States
| | - Kayley Okst
- Department of Psychiatry, Cambridge Health Alliance, Cambridge, MA, United States
- Department of Psychology, New York University, New York, NY, United States
| | - Miriam C Tepper
- Department of Psychiatry, Cambridge Health Alliance, Cambridge, MA, United States
- New York State Psychiatric Institute, Columbia University, New York, NY, United States
| | - Ana Baumgart Schreck
- Department of Psychiatry, Cambridge Health Alliance, Cambridge, MA, United States
| | - Carl Fulwiler
- Department of Psychiatry, Cambridge Health Alliance, Cambridge, MA, United States
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States
| | - Philip S Wang
- Department of Psychiatry, Cambridge Health Alliance, Cambridge, MA, United States
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States
- Department of Psychiatry, Brigham and Women's Hospital, Boston, MA, United States
| | - Zev Schuman-Olivier
- Department of Psychiatry, Cambridge Health Alliance, Cambridge, MA, United States
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States
| |
Collapse
|
10
|
Hickie IB, Iorfino F, Rohleder C, Song YJC, Nichles A, Zmicerevska N, Capon W, Guastella AJ, Leweke FM, Scott J, McGorry P, Mihalopoulos C, Killackey E, Chong MK, McKenna S, Aji M, Gorban C, Crouse JJ, Koethe D, Battisti R, Hamilton B, Lo A, Hackett ML, Hermens DF, Scott EM. EMPOWERED trial: protocol for a randomised control trial of digitally supported, highly personalised and measurement-based care to improve functional outcomes in young people with mood disorders. BMJ Open 2023; 13:e072082. [PMID: 37821139 PMCID: PMC10583041 DOI: 10.1136/bmjopen-2023-072082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 08/08/2023] [Indexed: 10/13/2023] Open
Abstract
OBJECTIVES Many adolescents and young adults with emerging mood disorders do not achieve substantial improvements in education, employment, or social function after receiving standard youth mental health care. We have developed a new model of care referred to as 'highly personalised and measurement-based care' (HP&MBC). HP&MBC involves repeated assessment of multidimensional domains of morbidity to enable continuous and personalised clinical decision-making. Although measurement-based care is common in medical disease management, it is not a standard practice in mental health. This clinical effectiveness trial tests whether HP&MBC, supported by continuous digital feedback, delivers better functional improvements than standard care and digital support. METHOD AND ANALYSIS This controlled implementation trial is a PROBE study (Prospective, Randomised, Open, Blinded End-point) that comprises a multisite 24-month, assessor-blinded, follow-up study of 1500 individuals aged 15-25 years who present for mental health treatment. Eligible participants will be individually randomised (1:1) to 12 months of HP&MBC or standardised clinical care. The primary outcome measure is social and occupational functioning 12 months after trial entry, assessed by the Social and Occupational Functioning Assessment Scale. Clinical and social outcomes for all participants will be monitored for a further 12 months after cessation of active care. ETHICS AND DISSEMINATION This clinical trial has been reviewed and approved by the Human Research Ethics Committee of the Sydney Local Health District (HREC Approval Number: X22-0042 & 2022/ETH00725, Protocol ID: BMC-YMH-003-2018, protocol version: V.3, 03/08/2022). Research findings will be disseminated through peer-reviewed journals, presentations at scientific conferences, and to user and advocacy groups. Participant data will be deidentified. TRIAL REGISTRATION NUMBER ACTRN12622000882729.
Collapse
Affiliation(s)
- Ian B Hickie
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Frank Iorfino
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Cathrin Rohleder
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Yun Ju Christine Song
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Alissa Nichles
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Natalia Zmicerevska
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - William Capon
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Adam J Guastella
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - F Markus Leweke
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
- Faculty of Medicine Mannheim, Psychiatry and Psychotherapy, Central Institute of Mental Health, Heidelberg University, Mannheim, Germany
| | - Jan Scott
- Newcastle University, Newcastle upon Tyne, UK
| | - Patrick McGorry
- Centre for Youth Mental Health, University of Melbourne Australia, Parkville, Victoria, Australia
- Orygen, The National Centre of Excellence in Youth Mental Health, Parkville, Victoria, Australia
| | - Cathrine Mihalopoulos
- School of Public Health and Preventive Medicine, Monash University, Clayton, Victoria, Australia
| | - Eoin Killackey
- Centre for Youth Mental Health, University of Melbourne Australia, Parkville, Victoria, Australia
- Orygen, The National Centre of Excellence in Youth Mental Health, Parkville, Victoria, Australia
| | - Min K Chong
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Sarah McKenna
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Melissa Aji
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Carla Gorban
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Jacob J Crouse
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Dagmar Koethe
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | | | - Blake Hamilton
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
- headspace Camperdown, Camperdown, New South Wales, Australia
| | - Alice Lo
- Mind Plasticity, Sydney, New South Wales, Australia
| | - Maree L Hackett
- George Institute for Global Health, Newtown, New South Wales, Australia
| | - Daniel F Hermens
- Thompson Institute, University of the Sunshine Coast, Birtinya, Queensland, Australia
| | - Elizabeth M Scott
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| |
Collapse
|
11
|
Staab EM, Franco MI, Zhu M, Wan W, Gibbons RD, Vinci LM, Beckman N, Yohanna D, Laiteerapong N. Population Health Management Approach to Depression Symptom Monitoring in Primary Care via Patient Portal: A Randomized Controlled Trial. Am J Med Qual 2023; 38:188-195. [PMID: 37314235 DOI: 10.1097/jmq.0000000000000126] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Depression is undertreated in primary care. Using patient portals to administer regular symptom assessments could facilitate more timely care. At an urban academic medical center outpatient clinic, patients with active portal accounts and depression on their problem list or a positive screen in the past year were randomized to assessment during triage at visits (usual care) versus usual care plus assessment via portal (population health care). Portal invitations were sent regardless of whether patients had scheduled appointments. More patients completed assessments in the population health care arm than usual care: 59% versus 18%, P < 0.001. Depression symptoms were more common among patients who completed their initial assessment via the portal versus in the clinic. In the population health care arm, 57% (N = 80/140) of patients with moderate-to-severe symptoms completed at least 1 follow-up assessment versus 37% (N = 13/35) in usual care. A portal-based population health approach could improve depression monitoring in primary care.
Collapse
Affiliation(s)
- Erin M Staab
- Department of Medicine, University of Chicago, Chicago, IL
| | | | - Mengqi Zhu
- Department of Medicine, University of Chicago, Chicago, IL
| | - Wen Wan
- Department of Medicine, University of Chicago, Chicago, IL
| | - Robert D Gibbons
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL
- Department of Public Health Sciences, University of Chicago, Chicago, IL
| | - Lisa M Vinci
- Department of Medicine, University of Chicago, Chicago, IL
| | - Nancy Beckman
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL
| | - Daniel Yohanna
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL
| | | |
Collapse
|
12
|
Ko H, Gatto AJ, Jones SB, O'Brien VC, McNamara RS, Tenzer MM, Sharp HD, Kablinger AS, Cooper LD. Improving measurement-based care implementation in adult ambulatory psychiatry: a virtual focus group interview with multidisciplinary healthcare professionals. BMC Health Serv Res 2023; 23:408. [PMID: 37101134 PMCID: PMC10132409 DOI: 10.1186/s12913-023-09202-3] [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: 06/14/2022] [Accepted: 02/20/2023] [Indexed: 04/28/2023] Open
Abstract
BACKGROUND Measurement-Based Care (MBC) is an evidence-based practice shown to enhance patient care. Despite being efficacious, MBC is not commonly used in practice. While barriers and facilitators of MBC implementation have been described in the literature, the type of clinicians and populations studied vary widely, even within the same practice setting. The current study aims to improve MBC implementation in adult ambulatory psychiatry by conducting focus group interviews while utilizing a novel virtual brainwriting premortem method. METHODS Semi-structured focus group interviews were conducted with clinicians (n = 18) and staff (n = 7) to identify their current attitudes, facilitators, and barriers of MBC implementation in their healthcare setting. Virtual video-conferencing software was used to conduct focus groups, and based on transcribed verbatin, emergent barriers/facilitators and four themes were identified. Mixed methods approach was utilized for this study. Specifically, qualitative data was aggregated and re-coded separately by three doctoral-level coders. Quantitative analyses were conducted from a follow-up questionnaire surveying clinician attitudes and satisfaction with MBC. RESULTS The clinician and staff focus groups resulted in 291 and 91 unique codes, respectively. While clinicians identified a similar number of barriers (40.9%) and facilitators (44.3%), staff identified more barriers (67%) than facilitators (24.7%) for MBC. Four themes emerged from the analysis; (1) a description of current status/neutral opinion on MBC; (2) positive themes that include benefits of MBC, facilitators, enablers, or reasons on why they conduct MBC in their practice, (3) negative themes that include barriers or issues that hinder them from incorporating MBC into their practice, and (4) requests and suggestions for future MBC implementation. Both participant groups raised more negative themes highlighting critical challenges to MBC implementation than positive themes. The follow-up questionnaire regarding MBC attitudes showed the areas that clinicians emphasized the most and the least in their clinical practice. CONCLUSION The virtual brainwriting premortem focus groups provided critical information on the shortcomings and strengths of MBC in adult ambulatory psychiatry. Our findings underscore implementation challenges in healthcare settings and provide insight for both research and clinical practice in mental health fields. The barriers and facilitators identified in this study can inform future training to increase sustainability and better integrate MBC with positive downstream outcomes in patient care.
Collapse
Affiliation(s)
- Hayoung Ko
- Department of Psychology, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
| | - Alyssa J Gatto
- Department of Psychiatry and Human Behavior, Brown University, Providence, RI, USA
| | - Sydney B Jones
- Department of Psychology, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA
| | - Virginia C O'Brien
- Department of Psychiatry and Behavioral Medicine, Virginia Tech Carilion School of Medicine, Roanoke, Virginia, USA
| | - Robert S McNamara
- Department of Psychiatry and Behavioral Medicine, Virginia Tech Carilion School of Medicine, Roanoke, Virginia, USA
| | - Martha M Tenzer
- Health Analytics Research Team, Carilion Clinic, Roanoke, Virginia, USA
| | - Hunter D Sharp
- Health Analytics Research Team, Carilion Clinic, Roanoke, Virginia, USA
| | - Anita S Kablinger
- Department of Psychiatry and Behavioral Medicine, Virginia Tech Carilion School of Medicine, Roanoke, Virginia, USA
| | - Lee D Cooper
- Department of Psychology, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA
| |
Collapse
|
13
|
Gual-Montolio P, Suso-Ribera C, García-Palacios A, Castilla D, Zaragoza I, Bretón-López J. Enhancing Internet-based psychotherapy for adults with emotional disorders using ecological momentary assessments and interventions: Study protocol of a feasibility trial with "My EMI, Emotional Well-being" app. Internet Interv 2023; 31:100601. [PMID: 36686334 PMCID: PMC9852876 DOI: 10.1016/j.invent.2023.100601] [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: 10/20/2022] [Revised: 12/20/2022] [Accepted: 01/04/2023] [Indexed: 01/07/2023] Open
Abstract
Introduction Emotional disorders are the most frequent mental health problems globally. To ensure the dissemination of psychological treatments for these conditions, novel forms of delivery (e.g., Internet or mobile apps) and more scalable forms of psychotherapy (e.g., transdiagnostic interventions) have become increasingly popular. Research, however, shows that a significant number of patients, around 40 % according to some studies, do not respond to the interventions as expected (i.e., not-on-track patients). Ecological momentary assessments (EMAs) and ecological momentary interventions (EMIs) could simplify tailoring treatments to the patients' progress and rapidly respond to undesired outcomes during psychotherapy. Therefore, these would facilitate measurement-based care with little therapist involvement. This study aims to explore the feasibility of an app-based system called My EMI, Emotional Well-being for people with emotional disorders. According to daily EMAs, the app will provide personalized EMIs while participants receive a self-applied online transdiagnostic treatment. The app will be used as an add-tool to the online intervention to address emotion dysregulation, foster adherence, and reinforce contents. The current study describes the study protocol for this trial. Method and analysis A single-group, open trial design will be used. Participants will be 30 adults suffering from emotional disorders. Primary outcomes will be app usability, acceptability, and response rates. Secondary outcomes will be either evaluated in Qualtrics at pre-treatment, post-treatment, and 3-month follow-up (depression and anxiety severity, and transdiagnostic dimensions of emotional disorders) or daily throughout the study with the app (EMAs of mood and five transdiagnostic mechanisms of therapeutic change). EMIs will consist of brief, evidence-based transdiagnostic CBT digital content (images, infographics, or videos) delivered just-in-time. Only if problems persist, short phone calls or episodic videocalls will be conducted. The Ethics Committee of the Jaume I University approved the study and all its procedures (CD/111/2021) in December 2021. Discussion Identifying personalized and scalable interventions is paramount to improve mental health care, especially its accessibility, and to reduce the psychological distress of people with mental health problems. Feasibility data of the app (EMA and EMI system) supported by a self-applied online transdiagnostic intervention will be important to explore whether this modern approach is a real option to move forward personalized psychological interventions for persons with emotional disorders. Trial registration ClinicalTrials.gov Identifier: NCT05109780. Registered 05 November 2021, https://clinicaltrials.gov/ct2/show/NCT05109780.
Collapse
Affiliation(s)
- Patricia Gual-Montolio
- Department of Basic and Clinical Psychology and Psychobiology, Jaume I University, Avda. Vicent Sos Baynat s/n, 12071 Castellon de la Plana, Spain
| | - Carlos Suso-Ribera
- Department of Basic and Clinical Psychology and Psychobiology, Jaume I University, Avda. Vicent Sos Baynat s/n, 12071 Castellon de la Plana, Spain
- CIBER Fisiopatología Obesidad y Nutrición (CIBERObn), Instituto Salud Carlos III, Madrid, Spain
| | - Azucena García-Palacios
- Department of Basic and Clinical Psychology and Psychobiology, Jaume I University, Avda. Vicent Sos Baynat s/n, 12071 Castellon de la Plana, Spain
- CIBER Fisiopatología Obesidad y Nutrición (CIBERObn), Instituto Salud Carlos III, Madrid, Spain
| | - Diana Castilla
- Department of Personality, Assessment, and Psychological Treatments, Universidad de Valencia, 46010 Valencia, Spain
- CIBER Fisiopatología Obesidad y Nutrición (CIBERObn), Instituto Salud Carlos III, Madrid, Spain
| | - Irene Zaragoza
- Department of Personality, Assessment, and Psychological Treatments, Universidad de Valencia, 46010 Valencia, Spain
- CIBER Fisiopatología Obesidad y Nutrición (CIBERObn), Instituto Salud Carlos III, Madrid, Spain
| | - Juana Bretón-López
- Department of Basic and Clinical Psychology and Psychobiology, Jaume I University, Avda. Vicent Sos Baynat s/n, 12071 Castellon de la Plana, Spain
- CIBER Fisiopatología Obesidad y Nutrición (CIBERObn), Instituto Salud Carlos III, Madrid, Spain
| |
Collapse
|
14
|
de Angel V, Adeleye F, Zhang Y, Cummins N, Munir S, Lewis S, Laporta Puyal E, Matcham F, Sun S, Folarin AA, Ranjan Y, Conde P, Rashid Z, Dobson R, Hotopf M. The Feasibility of Implementing Remote Measurement Technologies in Psychological Treatment for Depression: Mixed Methods Study on Engagement. JMIR Ment Health 2023; 10:e42866. [PMID: 36692937 PMCID: PMC9906314 DOI: 10.2196/42866] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 11/10/2022] [Accepted: 11/26/2022] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Remote measurement technologies (RMTs) such as smartphones and wearables can help improve treatment for depression by providing objective, continuous, and ecologically valid insights into mood and behavior. Engagement with RMTs is varied and highly context dependent; however, few studies have investigated their feasibility in the context of treatment. OBJECTIVE A mixed methods design was used to evaluate engagement with active and passive data collection via RMT in people with depression undergoing psychotherapy. We evaluated the effects of treatment on 2 different types of engagement: study attrition (engagement with study protocol) and patterns of missing data (engagement with digital devices), which we termed data availability. Qualitative interviews were conducted to help interpret the differences in engagement. METHODS A total of 66 people undergoing psychological therapy for depression were followed up for 7 months. Active data were gathered from weekly questionnaires and speech and cognitive tasks, and passive data were gathered from smartphone sensors and a Fitbit (Fitbit Inc) wearable device. RESULTS The overall retention rate was 60%. Higher-intensity treatment (χ21=4.6; P=.03) and higher baseline anxiety (t56.28=-2.80, 2-tailed; P=.007) were associated with attrition, but depression severity was not (t50.4=-0.18; P=.86). A trend toward significance was found for the association between longer treatments and increased attrition (U=339.5; P=.05). Data availability was higher for active data than for passive data initially but declined at a sharper rate (90%-30% drop in 7 months). As for passive data, wearable data availability fell from a maximum of 80% to 45% at 7 months but showed higher overall data availability than smartphone-based data, which remained stable at the range of 20%-40% throughout. Missing data were more prevalent among GPS location data, followed by among Bluetooth data, then among accelerometry data. As for active data, speech and cognitive tasks had lower completion rates than clinical questionnaires. The participants in treatment provided less Fitbit data but more active data than those on the waiting list. CONCLUSIONS Different data streams showed varied patterns of missing data, despite being gathered from the same device. Longer and more complex treatments and clinical characteristics such as higher baseline anxiety may reduce long-term engagement with RMTs, and different devices may show opposite patterns of missingness during treatment. This has implications for the scalability and uptake of RMTs in health care settings, the generalizability and accuracy of the data collected by these methods, feature construction, and the appropriateness of RMT use in the long term.
Collapse
Affiliation(s)
- Valeria de Angel
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, United Kingdom
| | - Fadekemi Adeleye
- Department of Psychology, King's College London, London, United Kingdom
| | - Yuezhou Zhang
- Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Nicholas Cummins
- Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Sara Munir
- Lewisham Talking Therapies, South London and Maudsley NHS Foundation Trust, London, United Kingdom
| | - Serena Lewis
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- Department of Psychology, University of Bath, Bath, United Kingdom
| | - Estela Laporta Puyal
- Biomedical Signal Interpretation and Computational Simulation Group, Aragón Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain
- Centro de Investigación Biomédica en Red of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain
| | - Faith Matcham
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- School of Psychology, University of Sussex, Brighton, United Kingdom
| | - Shaoxiong Sun
- Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Amos A Folarin
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, United Kingdom
- Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- Institute of Health Informatics, University College London, London, United Kingdom
- Health Data Research UK London, University College London, London, United Kingdom
- NIHR Biomedical Research Centre at University College London Hospitals, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Yatharth Ranjan
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Pauline Conde
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Zulqarnain Rashid
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Richard Dobson
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, United Kingdom
| | - Matthew Hotopf
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, United Kingdom
| |
Collapse
|
15
|
Wiegmann C, Quinlivan E, Michnevich T, Pittrich A, Ivanova P, Rohrbach AM, Kaminski J. A digital patient-reported outcome (electronic patient-reported outcome) system for patients with severe psychiatric disorders: User-centered development study and study protocol of a multicenter-controlled trial. Digit Health 2023; 9:20552076231191009. [PMID: 37900257 PMCID: PMC10605665 DOI: 10.1177/20552076231191009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Accepted: 07/13/2023] [Indexed: 10/31/2023] Open
Abstract
Background The effective treatment of patients with severe psychiatric disorders primarily relies on subjective reporting of symptoms and side-effects. This information is crucial for a clinician's decision regarding medication adjustment. Treatment adjustment usually happens at a low frequency (∼4-8 weeks). In between points of care, patients are left alone with their symptoms and side-effects. This leads to uncertainty regarding the treatment, non-adherence, possible relapse, and rehospitalization. Objectives We aim to design a flexible electronic patient-reported outcome (ePRO) system, which allows patients with severe psychiatric disorders to: (a) record their symptoms using an app; (b) share the data with the clinical team at points of care; and (c) utilize the data to support therapy decisions. Methods In this article, we describe the development process which included the following steps: (a) formation of a co-design team; (b) stakeholder interviews with patients, practitioners, and digital health experts to access needs, requirements, and barriers; (c) prototype conceptualization and design; (d) user acceptance testing and refinement; and (e) finalization of the system for testing in a pilottrial. Results We included input from patients with lived experience of psychiatric disorders, clinical team members, software engineers, and researchers. A prototype system was refined, and iterative changes were made before finalization during a series of operational meetings. The system allows patients to digitally self-report their symptoms and provides longitudinal ePRO symptom data for export into the electronic health record. Conclusions Routine ePRO collection has the potential to improve outcomes and hereby also reduce health service costs. We have successfully developed a trial-ready ePRO system for severe psychiatric disorders. The findings were incorporated in the planning of a feasibility pilot trial. Assuming feasibility will be established, the system might be subjected to a certification process evaluation of safety and efficacy including a randomized controlled trial.
Collapse
Affiliation(s)
- Caspar Wiegmann
- Klinik für Psychiatrie und Psychotherapie, Kliniken im Theodor-Wenzel-Werk, Berlin, Germany
| | - Esther Quinlivan
- Department of Psychiatry and Neurosciences CCM, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Twyla Michnevich
- Department of Psychiatry and Neurosciences CCM, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | | | - Petja Ivanova
- Hochschule für angewandte Wissenschaften, Hamburg, Germany
| | | | - Jakob Kaminski
- Department of Psychiatry and Neurosciences CCM, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| |
Collapse
|
16
|
Van Tiem J, Wirtz E, Suiter N, Heeren A, Fuhrmeister L, Fortney J, Reisinger H, Turvey C. The Implementation of Measurement-Based Care in the Context of Telemedicine: Qualitative Study. JMIR Ment Health 2022; 9:e41601. [PMID: 36422884 PMCID: PMC9732750 DOI: 10.2196/41601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 10/21/2022] [Accepted: 11/09/2022] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND The Measurement Based Care in Mental Health Initiative launched by the Department of Veterans Affairs in 2016 is an example of an evidence-based practice that uses patient-reported outcome measures (PROMs) to improve patient outcomes. The acceptance of measurement-based care (MBC) among Veterans Affairs providers is relatively high. However, there are barriers to MBC for telehealth providers. Health information technologies might afford opportunities to address some of the barriers related to the uptake of MBC. OBJECTIVE This paper reports on an implementation effort to integrate MBC into mental health care telehealth practice using eHealth solutions. METHODS Qualitative data were generated from 22 semistructured interviews with psychiatrists (n=4), psychologists (n=3), social workers (n=3), nurses (n=6), a pharmacist (n=1), and administrative staff (n=5) who provide telemental health care through a community-based outpatient clinic in the rural Midwestern United States. The interviews were conducted during the pilot phase of an implementation initiative to increase the adoption of MBC by revising clinic workflows to integrate the use of eHealth technologies. Data were analyzed using thematic analysis. RESULTS Time burden and workflow issues were the most common barrier to provider adoption of MBC; sharing and reviewing pencil-and-paper measures and results in the same room was no longer possible in novel telehealth workflows necessitated by the COVID-19 pandemic. Providers voiced concerns about how long it would take to collect, adequately score, interpret, share, and document the PROMs during the telehealth visit. Concerns about time might also correspond to a gap in providers' familiarity with these assessments, greater comfort in assessing symptoms through clinical interviews, and being accustomed to using the assessments as screening tools more so than longitudinal outcome measures. Capacities associated with eHealth technologies may address workflow concerns and promote providers' understanding and use of the measures as tracking tools. CONCLUSIONS The need to use limited appointment time well was a top priority for telemental health providers. eHealth technologies provided operative supports that protect time in appointments by shifting when and how PROMs are collected. Bolstering providers' familiarity with how to use PROMs in the course of treatment may impact providers' buy-in by encouraging them to reconsider how sharing and acting on PROMs could be time well spent.
Collapse
Affiliation(s)
- Jen Van Tiem
- Department of Veterans Affairs, Health Services Research & Development, Center for Access and Delivery Research and Evaluation, Iowa City Veterans Affairs Health Care System, Iowa City, IA, United States.,Department of Veterans Affairs Office of Rural Health, Veterans Rural Health Resource Center-Iowa City, Iowa City VA Healthcare System, Iowa City, IA, United States
| | - Elizabeth Wirtz
- Department of Veterans Affairs, Health Services Research & Development, Center for Access and Delivery Research and Evaluation, Iowa City Veterans Affairs Health Care System, Iowa City, IA, United States.,Department of Veterans Affairs Office of Rural Health, Veterans Rural Health Resource Center-Iowa City, Iowa City VA Healthcare System, Iowa City, IA, United States
| | - Natalie Suiter
- Department of Veterans Affairs, Health Services Research & Development, Center for Access and Delivery Research and Evaluation, Iowa City Veterans Affairs Health Care System, Iowa City, IA, United States.,Department of Veterans Affairs Office of Rural Health, Veterans Rural Health Resource Center-Iowa City, Iowa City VA Healthcare System, Iowa City, IA, United States
| | - Amanda Heeren
- Department of Veterans Affairs Office of Rural Health, Veterans Rural Health Resource Center-Iowa City, Iowa City VA Healthcare System, Iowa City, IA, United States.,Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City, IA, United States
| | - Lindsey Fuhrmeister
- Department of Veterans Affairs Office of Rural Health, Veterans Rural Health Resource Center-Iowa City, Iowa City VA Healthcare System, Iowa City, IA, United States.,Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City, IA, United States
| | - John Fortney
- Department of Veterans Affairs, Health Services Research & Development, Center of Innovation for Veteran-Centered and Values-Driven Care, Veterans Affairs Puget Sound Health Care System, Seattle, WA, United States.,Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, United States
| | - Heather Reisinger
- Department of Veterans Affairs, Health Services Research & Development, Center for Access and Delivery Research and Evaluation, Iowa City Veterans Affairs Health Care System, Iowa City, IA, United States.,Institute for Clinical and Translational Science, University of Iowa, Iowa City, IA, United States.,Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City, IA, United States
| | - Carolyn Turvey
- Department of Veterans Affairs, Health Services Research & Development, Center for Access and Delivery Research and Evaluation, Iowa City Veterans Affairs Health Care System, Iowa City, IA, United States.,Department of Veterans Affairs Office of Rural Health, Veterans Rural Health Resource Center-Iowa City, Iowa City VA Healthcare System, Iowa City, IA, United States.,Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City, IA, United States
| |
Collapse
|
17
|
Richardson E, Hogan TP, Shimada SL, Sliwinski SK, Kim B. Common procedures of remote measurement-based care in an integrated behavioural health context: protocol for a scoping review. BMJ Open 2022; 12:e064450. [PMID: 36171037 PMCID: PMC9528588 DOI: 10.1136/bmjopen-2022-064450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2022] Open
Abstract
INTRODUCTION Integrated behavioural health, a model of care that embeds mental health services in primary care, can potentially increase access to mental healthcare. With the increase in health information technologies, remote measurement-based care (RMBC) presents an opportunity to improve support of integrated care. This scoping review will comprehensively examine what common procedures are followed when RMBC for mental health is tested in integrated care settings. METHODS AND ANALYSIS Based on an established six-step framework for conducting scoping reviews, we will search PubMed, Embase, PsycINFO, Cochrane, EBSCOhost and Web of Science with search terms related to 'integrated care' and 'RMBC'. Articles published from 2015 onwards, in English, including an intervention that meets our definition of RMBC, and are conducted in collaboration with primary care or in a primary care setting will be included. After data extraction, we will categorise key findings along the following dimensions: (1) common delivery practices of RMBC; (2) common technologies and instruments used and (3) most common barriers and facilitators when implementing RMBC in an integrated care model. ETHICS AND DISSEMINATION Ethics approval is not required for this scoping review. For maximum impact, we will disseminate the findings to the scientific community (via publication in a peer-reviewed journal and at national conferences) and to the broader healthcare community. We will share findings with the broader healthcare community through our research centre's existing stakeholder communication structures and through guidance from our multidisciplinary research team. These key stakeholder relationships will continue to guide our subsequent RMBC research following the review.
Collapse
Affiliation(s)
- Eric Richardson
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston, Massachusetts, USA
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA
| | - Timothy P Hogan
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston, Massachusetts, USA
- Department of Population and Data Sciences, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Stephanie L Shimada
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston, Massachusetts, USA
- Department of Health Law, Policy and Management, Boston University School of Public Health, Boston, Massachusetts, USA
- Department of Population and Quantitative Health Sciences, UMass Chan Medical School, Worcester, Massachusetts, USA
| | - Samantha K Sliwinski
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Bo Kim
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston, Massachusetts, USA
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA
| |
Collapse
|
18
|
Buck B, Gagen EC, Halverson TF, Nagendra A, Ludwig KA, Fortney JC. A systematic search and critical review of studies evaluating psychometric properties of patient-reported outcome measures for schizophrenia. J Psychiatr Res 2022; 147:13-23. [PMID: 35007807 PMCID: PMC8882143 DOI: 10.1016/j.jpsychires.2021.12.053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 12/09/2021] [Accepted: 12/23/2021] [Indexed: 10/19/2022]
Abstract
Measurement-based care (MBC) involves the regular administration of outcome assessments to track and evaluate treatment progress and requires psychometrically sound instruments. While there are widely used patient-reported outcome measures (PROMs) for several psychiatric disorders and symptom categories (e.g., depression, anxiety), there is less consensus about self-report assessments for measurement-based care of schizophrenia. The present review provides an initial guide to this area by reporting on psychometric studies that introduce or evaluate PROMs designed for the ongoing treatment of schizophrenia. Out of an initial database of 6,153 articles, and review of 141 full-text articles, an analysis of 21 articles examining 12 measures is presented in this review. Findings suggest robust options exist for clinical and research institutions aiming to assess symptom outcomes in schizophrenia, with most measures showing strengths in internal consistency, test-retest reliability, and a number of measures with evidence of convergent or criterion validity. While there exist heterogeneous options, multiple measures demonstrated promising psychometric strengths. Future work validating consistent psychometric validity could involve measures which could be valuable in context of MBC for schizophrenia.
Collapse
Affiliation(s)
- Benjamin Buck
- Behavioral Research in Technology and Engineering (BRiTE) Center, Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA.
| | - Emily C. Gagen
- Department of Psychiatry, Harvard Medical School, Boston, MA,Massachusetts Mental Health Center, Boston, MA
| | | | - Arundati Nagendra
- Department of Psychiatry, Harvard Medical School, Boston, MA,Department of Psychiatry, Massachusetts General Hospital, Boston, MA
| | - Kelsey A. Ludwig
- Durham VA Health Care System – Durham, NC,Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill – Chapel Hill, NC
| | - John C. Fortney
- Division of Population Health, Department of Psychiatry and Behavioral Sciences, University of Washington,VA Puget Sound Health Services Research & Development, Denver-Seattle Center of Innovation for Veteran-Centered Value-Driven Care
| |
Collapse
|
19
|
Kablinger AS, Gatto AJ, O'Brien VC, Ko H, Jones S, McNamara RS, Sharp HD, Tenzer MM, Cooper LD. Effects of COVID-19 on Patients in Adult Ambulatory Psychiatry: Using Patient-Rated Outcome Measures and Telemedicine. Telemed J E Health 2022; 28:1421-1430. [PMID: 35167369 PMCID: PMC9587767 DOI: 10.1089/tmj.2021.0642] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Introduction: To examine the effects of coronavirus disease 2019 (COVID-19) on patients in an academic psychiatric ambulatory clinic, data from a measurement-based care (MBC) system were analyzed to evaluate impacts on psychiatric functioning in patients using telemedicine. Psychiatric functioning was evaluated for psychological distress (brief adjustment scale [BASE]-6), depression (patient health questionnaire [PHQ]-9), and anxiety (generalized anxiety disorder [GAD]-7), including initial alcohol (U.S. alcohol use disorders identification test) and substance use (drug abuse screening test-10) screening. Methods: This observational study included MBC data collected from November 2019 to March 2021. Patient-Reported Outcome Measures (PROMs) were examined to determine changes in symptomatology over the course of treatment, as well as symptom changes resulting from the pandemic. Patients were included in analyses if they completed at least one PROM in the MBC system. Results: A total of 2,145 patients actively participated in the MBC system completing at least one PROM, with engagement ranging from 35.07% to 83.50% depending on demographic factors, where completion rates were significantly different for age, payor status, and diagnostic group. Average baseline scores for new patients varied for the GAD-7, PHQ-9, and BASE-6. Within-person improvements in mental health before and after the pandemic were statistically significant for anxiety, depression, and psychological adjustment. Discussion: MBC is a helpful tool in determining treatment progress for patients engaging in telemedicine. This study showed that patients who engaged in psychiatric services incorporating PROMs had improvements in mental health during the COVID-19 pandemic. Additional research is needed exploring whether PROMs might serve as a protective or facilitative factor for those with mental illness during a crisis when in-person visits are not possible.
Collapse
Affiliation(s)
- Anita S Kablinger
- Department of Psychiatry and Behavioral Medicine, Virginia Tech Carilion School of Medicine, Roanoke, Virginia, USA
| | - Alyssa J Gatto
- Department of Psychology, Brown University, Providence, Rhode Island, USA
| | - Virginia C O'Brien
- Department of Psychiatry and Behavioral Medicine, Virginia Tech Carilion School of Medicine, Roanoke, Virginia, USA
| | - Hayoung Ko
- Department of Psychology, Virginia Tech, Blacksburg, Virginia, USA
| | - Sydney Jones
- Department of Psychology, Virginia Tech, Blacksburg, Virginia, USA
| | - Robert S McNamara
- Department of Psychiatry and Behavioral Medicine, Virginia Tech Carilion School of Medicine, Roanoke, Virginia, USA
| | - Hunter D Sharp
- Health Analytics Research Team (HART), Carilion Clinic, Roanoke, Virginia, USA
| | - Martha M Tenzer
- Health Analytics Research Team (HART), Carilion Clinic, Roanoke, Virginia, USA
| | - Lee D Cooper
- Department of Psychology, Virginia Tech, Blacksburg, Virginia, USA
| |
Collapse
|
20
|
Bougeard A, Guay Hottin1 R, Houde V, Jean T, Piront T, Potvin S, Bernard P, Tourjman V, De Benedictis L, Orban P. Le phénotypage digital pour une pratique clinique en santé mentale mieux informée. SANTE MENTALE AU QUEBEC 2021. [DOI: 10.7202/1081513ar] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Objectifs Cette revue trouve sa motivation dans l’observation que la prise de décision clinique en santé mentale est limitée par la nature des mesures typiquement obtenues lors de l’entretien clinique et la difficulté des cliniciens à produire des prédictions justes sur les états mentaux futurs des patients. L’objectif est de présenter un survol représentatif du potentiel du phénotypage digital couplé à l’apprentissage automatique pour répondre à cette limitation, tout en en soulignant les faiblesses actuelles.
Méthode Au travers d’une revue narrative de la littérature non systématique, nous identifions les avancées technologiques qui permettent de quantifier, instant après instant et dans le milieu de vie naturel, le phénotype humain au moyen du téléphone intelligent dans diverses populations psychiatriques. Des travaux pertinents sont également sélectionnés afin de déterminer l’utilité et les limitations de l’apprentissage automatique pour guider les prédictions et la prise de décision clinique. Finalement, la littérature est explorée pour évaluer les barrières actuelles à l’adoption de tels outils.
Résultats Bien qu’émergeant d’un champ de recherche récent, de très nombreux travaux soulignent déjà la valeur des mesures extraites des senseurs du téléphone intelligent pour caractériser le phénotype humain dans les sphères comportementale, cognitive, émotionnelle et sociale, toutes étant affectées par les troubles mentaux. L’apprentissage automatique permet d’utiles et justes prédictions cliniques basées sur ces mesures, mais souffre d’un manque d’interprétabilité qui freinera son emploi prochain dans la pratique clinique. Du reste, plusieurs barrières identifiées tant du côté du patient que du clinicien freinent actuellement l’adoption de ce type d’outils de suivi et d’aide à la décision clinique.
Conclusion Le phénotypage digital couplé à l’apprentissage automatique apparaît fort prometteur pour améliorer la pratique clinique en santé mentale. La jeunesse de ces nouveaux outils technologiques requiert cependant un nécessaire processus de maturation qui devra être encadré par les différents acteurs concernés pour que ces promesses puissent être pleinement réalisées.
Collapse
Affiliation(s)
- Alan Bougeard
- Étudiant, Centre de recherche de l’Institut universitaire en santé mentale de Montréal
| | - Rose Guay Hottin1
- Étudiante, Centre de recherche de l’Institut universitaire en santé mentale de Montréal
| | - Valérie Houde
- M.D., étudiante, Centre de recherche de l’Institut universitaire en santé mentale de Montréal
| | - Thierry Jean
- Étudiant, Centre de recherche de l’Institut universitaire en santé mentale de Montréal
| | - Thibault Piront
- Professionnel de recherche, Centre de recherche de l’Institut universitaire en santé mentale de Montréal
| | - Stéphane Potvin
- Ph. D., chercheur, Centre de recherche de l’Institut universitaire en santé mentale de Montréal – professeur sous octroi titulaire, Département de psychiatrie et d’addictologie, Université de Montréal
| | - Paquito Bernard
- Ph. D., chercheur, Centre de recherche de l’Institut universitaire en santé mentale de Montréal – professeur régulier, Département des sciences de l’activité physique, Université du Québec à Montréal
| | - Valérie Tourjman
- M.D., psychiatre, Institut universitaire en santé mentale de Montréal – professeure agrégée de clinique, Département de psychiatrie et d’addictologie, Université de Montréal
| | - Luigi De Benedictis
- M.D., psychiatre, Institut universitaire en santé mentale de Montréal – professeur adjoint de clinique, Département de psychiatrie et d’addictologie, Université de Montréal
| | - Pierre Orban
- Ph. D., chercheur, Centre de recherche de l’Institut universitaire en santé mentale de Montréal – professeur sous octroi adjoint, Département de psychiatrie et d’addictologie, Université de Montréal
| |
Collapse
|
21
|
Levis M, Levis AJ. Contextual assessment: evaluating a novel self-guided online therapeutic assessment. Int J Psychiatry Clin Pract 2021; 25:206-215. [PMID: 32701050 PMCID: PMC11151187 DOI: 10.1080/13651501.2020.1794010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/01/2020] [Revised: 05/20/2020] [Accepted: 07/05/2020] [Indexed: 10/23/2022]
Abstract
BACKGROUND Paper introduces Conflict Analysis (CA), an online self-guided therapeutic assessment. CA combines a diagnostic self-report scale with narrative exercises and self-analytical tasks. CA automatically generates detailed diagnostic records and frameworks for changes. OBJECTIVE To evaluate therapeutic and diagnostic benefits associated with CA over time. METHODS This online study compared CA over 2 weeks on outcome measures predicting psychotherapy outcome. Novel scale measuring perceived diagnostic benefit and perceived therapeutic benefit was delivered at post and follow-up. Cohort (n = 59, average age = 35, 50% female) was either in therapy or interested to start therapy in near future. RESULTS Repeated-measure ANOVAs suggest that scores significantly changed on measures predicting negative affect, depression, performance and appearance self-esteem, insight, and growth initiative. Agreement rates on items measuring perceived diagnostic and therapeutic benefits were at least 74.5% for both post and follow-up. CONCLUSIONS Evidence supports further exploration of CA as a self-guided diagnostic and therapeutic resource.Key pointsResults demonstrate feasibility and utility of online self-guided therapeutic assessment.Described model is associated with increased perceived diagnostic and therapeutic benefits.Described model illustrates therapeutic benefits over time.Results demonstrate that even self-guided assessment can have therapeutic implications.
Collapse
Affiliation(s)
- Maxwell Levis
- White River Junction VA Medical Center, White River Junction, VT, USA
- Department of Psychiatry, Geisel School of Medicine, Dartmouth College, Hanover, NH, USA
- Museum of the Creative Process, Manchester, VT, USA
| | | |
Collapse
|
22
|
Rauschenberg C, Schick A, Hirjak D, Seidler A, Paetzold I, Apfelbacher C, Riedel-Heller SG, Reininghaus U. Evidence Synthesis of Digital Interventions to Mitigate the Negative Impact of the COVID-19 Pandemic on Public Mental Health: Rapid Meta-review. J Med Internet Res 2021; 23:e23365. [PMID: 33606657 PMCID: PMC7951054 DOI: 10.2196/23365] [Citation(s) in RCA: 107] [Impact Index Per Article: 26.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Revised: 02/14/2021] [Accepted: 02/17/2021] [Indexed: 12/18/2022] Open
Abstract
Background Accumulating evidence suggests the COVID-19 pandemic has negative effects on public mental health. Digital interventions that have been developed and evaluated in recent years may be used to mitigate the negative consequences of the pandemic. However, evidence-based recommendations on the use of existing telemedicine and internet-based (eHealth) and app-based mobile health (mHealth) interventions are lacking. Objective The aim of this study was to investigate the theoretical and empirical base, user perspective, safety, effectiveness, and cost-effectiveness of digital interventions related to public mental health provision (ie, mental health promotion, prevention, and treatment of mental disorders) that may help to reduce the consequences of the COVID-19 pandemic. Methods A rapid meta-review was conducted. The MEDLINE, PsycINFO, and CENTRAL databases were searched on May 11, 2020. Study inclusion criteria were broad and considered systematic reviews and meta-analyses that investigated digital tools for health promotion, prevention, or treatment of mental health conditions and determinants likely affected by the COVID-19 pandemic. Results Overall, 815 peer-reviewed systematic reviews and meta-analyses were identified, of which 83 met the inclusion criteria. Our findings suggest that there is good evidence on the usability, safety, acceptance/satisfaction, and effectiveness of eHealth interventions. Evidence on mHealth apps is promising, especially if social components (eg, blended care) and strategies to promote adherence are incorporated. Although most digital interventions focus on the prevention or treatment of mental disorders, there is some evidence on mental health promotion. However, evidence on process quality, cost-effectiveness, and long-term effects is very limited. Conclusions There is evidence that digital interventions are particularly suited to mitigating psychosocial consequences at the population level. In times of physical distancing, quarantine, and restrictions on social contacts, decision makers should develop digital strategies for continued mental health care and invest time and efforts in the development and implementation of mental health promotion and prevention programs.
Collapse
Affiliation(s)
- Christian Rauschenberg
- Department of Public Mental Health, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.,Department of Psychiatry and Neuropsychology, School of Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Anita Schick
- Department of Public Mental Health, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Dusan Hirjak
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Andreas Seidler
- Institute and Policlinic of Occupational and Social Medicine, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Isabell Paetzold
- Department of Public Mental Health, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Christian Apfelbacher
- Institute of Social Medicine and Health Systems Research, Otto von Guericke University Magdeburg, Magdeburg, Germany
| | - Steffi G Riedel-Heller
- Institute of Social Medicine, Occupational Health and Public Health, University of Leipzig, Leipzig, Germany
| | - Ulrich Reininghaus
- Department of Public Mental Health, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.,Centre for Epidemiology and Public Health, Health Service and Population Research Department, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.,ESRC Centre for Society and Mental Health, King´s College London, London, United Kingdom
| |
Collapse
|
23
|
Chang D, Carlo AD, Khor S, Drake L, Lee ES, Avery M, Unützer J, Flum DR. Transforming Population-Based Depression Care: a Quality Improvement Initiative Using Remote, Centralized Care Management. J Gen Intern Med 2021; 36:333-340. [PMID: 32869208 PMCID: PMC7878605 DOI: 10.1007/s11606-020-06136-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2019] [Accepted: 08/11/2020] [Indexed: 10/23/2022]
Abstract
INTRODUCTION With the growing prevalence of value-based contracts, health systems are incentivized to consider population approaches to service delivery, particularly for chronic conditions like depression. To this end, UW Medicine implemented the Depression-Population Approach to Health (PATH) program in primary care (PC) as part of a system-wide Center for Medicare and Medicaid Innovation (CMMI) quality improvement (QI) initiative. AIM To examine the feasibility of a pilot PATH program and its impact on clinical and process-of-care outcomes. SETTING A large, diverse, geographically disparate academic health system in Western Washington State including 28 PC clinics across five networks. PROGRAM DESCRIPTION The PATH program was a population-level, centralized, measurement-based care intervention that utilized a clinician to provide remote monitoring of treatment progress via chart review and facilitate patient engagement when appropriate. The primary goals of the program were to improve care engagement and increase follow-up PHQ-9 assessments for patients with depression and elevated initial PHQ-9 scores. PROGRAM EVALUATION We employed a prospective, observational study design, including commercially insured adult patients with new depression diagnoses and elevated initial PHQ-9 scores. The pilot intervention group, consisting of accountable care network (ACN) self-enrollees (N = 262), was compared with a similar commercially insured cohort (N = 2527) using difference-in-differences analyses adjusted for patient comorbidities, initial PHQ-9 score, and time trends. The PATH program was associated with three times the odds of PHQ-9 follow-up (OR 3.28, 95% CI 1.79-5.99), twice the odds of a follow-up PC clinic visit (OR 1.74, 95% CI 0.99-3.08), and twice the odds of treatment response, defined as reduction in PHQ-9 score by ≥ 50% (OR 2.02, 95% CI 0.97-4.21). DISCUSSION Our results demonstrate that a centralized, remote care management initiative is both feasible and effective for large academic health systems aiming to improve depression outcome ascertainment, treatment engagement, and clinical care.
Collapse
Affiliation(s)
- Denise Chang
- Department of Psychiatry and Behavioral Sciences, University of Washington Medical Center, Seattle, WA, USA.
| | - Andrew D Carlo
- Department of Psychiatry and Behavioral Sciences, University of Washington Medical Center, Seattle, WA, USA
| | - Sara Khor
- Department of Surgery, University of Washington, Seattle, WA, USA.,The Comparative Health Outcomes, Policy, and Economics (CHOICE) Institute, University of Washington, Seattle, WA, USA
| | - Lauren Drake
- UW Medicine Population Health Management, Seattle, WA, USA
| | - E Sally Lee
- UW Medicine, Population Health Analytics, Seattle, WA, USA
| | - Marc Avery
- Department of Psychiatry and Behavioral Sciences, University of Washington Medical Center, Seattle, WA, USA.,Health Management Associates, Seattle, WA, USA
| | - Jürgen Unützer
- Department of Psychiatry and Behavioral Sciences, University of Washington Medical Center, Seattle, WA, USA
| | - David R Flum
- Department of Surgery, University of Washington, Seattle, WA, USA
| |
Collapse
|
24
|
Buck B, Hallgren KA, Campbell AT, Choudhury T, Kane JM, Ben-Zeev D. mHealth-Assisted Detection of Precursors to Relapse in Schizophrenia. Front Psychiatry 2021; 12:642200. [PMID: 34135781 PMCID: PMC8202824 DOI: 10.3389/fpsyt.2021.642200] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 05/03/2021] [Indexed: 11/18/2022] Open
Abstract
Theoretical views and a growing body of empirical evidence suggest that psychiatric relapses in schizophrenia-spectrum disorders (SSDs) have measurable warning signs. However, because they are time- and resource-intensive, existing assessment approaches are not well-suited to detect these warning signs in a timely, scalable fashion. Mobile technologies deploying frequent measurements-i.e., ecological momentary assessment-could be leveraged to detect increases in symptoms that may precede relapses. The present study examined EMA measurements with growth curve models in the 100 days preceding and following 27 relapses (among n = 20 individuals with SSDs) to identify (1) what symptoms changed in the periods gradually preceding, following, and right as relapses occur, (2) how large were these changes, and (3) on what time scale did they occur. Results demonstrated that, on average, participants reported elevations in negative mood (d = 0.34), anxiety (d =0.49), persecutory ideation (d =0.35), and hallucinations (d =0.34) on relapse days relative to their average during the study. These increases emerged gradually on average from significant and steady increases (d = 0.05 per week) in persecutory ideation and hallucinations over the 100-day period preceding relapse. This suggests that brief (i.e., 1-2 item) assessments of psychotic symptoms may detect meaningful signals that precede psychiatric relapses long before they occur. These assessments could increase opportunities for relapse prevention as remote measurement-based care management platforms develop.
Collapse
Affiliation(s)
- Benjamin Buck
- Department of Psychiatry and Behavioral Sciences, Behavioral Research in Technology and Engineering (BRiTE) Center, University of Washington, Seattle, WA, United States
| | - Kevin A Hallgren
- Department of Psychiatry and Behavioral Sciences, Behavioral Research in Technology and Engineering (BRiTE) Center, University of Washington, Seattle, WA, United States
| | - Andrew T Campbell
- Department of Computer Science, Dartmouth College, Hanover, NH, United States
| | - Tanzeem Choudhury
- Department of Information Science, Cornell University, Ithaca, NY, United States
| | - John M Kane
- The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, United States.,Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, United States
| | - Dror Ben-Zeev
- Department of Psychiatry and Behavioral Sciences, Behavioral Research in Technology and Engineering (BRiTE) Center, University of Washington, Seattle, WA, United States
| |
Collapse
|
25
|
How Are Information and Communication Technologies Supporting Routine Outcome Monitoring and Measurement-Based Care in Psychotherapy? A Systematic Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17093170. [PMID: 32370140 PMCID: PMC7246636 DOI: 10.3390/ijerph17093170] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Revised: 04/27/2020] [Accepted: 04/29/2020] [Indexed: 11/16/2022]
Abstract
Psychotherapy has proven to be effective for a wide range of mental health problems. However, not all patients respond to the treatment as expected (not-on-track patients). Routine outcome monitoring (ROM) and measurement-based care (MBC), which consist of monitoring patients between appointments and using this data to guide the intervention, have been shown to be particularly useful for these not-on-track patients. Traditionally, though, ROM and MBC have been challenging, due to the difficulties associated with repeated monitoring of patients and providing real-time feedback to therapists. The use of information and communication technologies (ICTs) might help reduce these challenges. Therefore, we systematically reviewed evidence regarding the use of ICTs for ROM and MBC in face-to-face psychological interventions for mental health problems. The search included published and unpublished studies indexed in the electronic databases PubMed, PsycINFO, and SCOPUS. Main search terms were variations of the terms “psychological treatment”, “progress monitoring or measurement-based care”, and “technology”. Eighteen studies met eligibility criteria. In these, ICTs were frequently handheld technologies, such as smartphone apps, tablets, or laptops, which were involved in the whole process (assessment and feedback). Overall, the use of technology for ROM and MBC during psychological interventions was feasible and acceptable. In addition, the use of ICTs was found to be effective, particularly for not-on-track patients, which is consistent with similar non-ICT research. Given the heterogeneity of reviewed studies, more research and replication is needed to obtain robust findings with different technological solutions and to facilitate the generalization of findings to different mental health populations.
Collapse
|
26
|
Internet-Based Management for Depressive Disorder. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2019; 1180:267-276. [PMID: 31784968 DOI: 10.1007/978-981-32-9271-0_14] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
The advances in the Internet and related technologies may lead to changes in professional roles of psychiatrists and psychotherapists. The application of artificial intelligence (AI) and electronic measurement-based care (eMBC) in the treatment of depressive disorder has addressed more interest. AI could play a role in population health management and patient administration as well as assist physicians to make a decision in the real-world clinical practice. The eMBC strengthens MBC through web/mobile devices and telephone consulting services, to monitor disease progression, and customizes the MBC interface in electronic medical record systems (EMRs).
Collapse
|
27
|
Deligianni F, Guo Y, Yang GZ. From Emotions to Mood Disorders: A Survey on Gait Analysis Methodology. IEEE J Biomed Health Inform 2019; 23:2302-2316. [PMID: 31502995 DOI: 10.1109/jbhi.2019.2938111] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Mood disorders affect more than 300 million people worldwide and can cause devastating consequences. Elderly people and patients with neurological conditions are particularly susceptible to depression. Gait and body movements can be affected by mood disorders, and thus they can be used as a surrogate sign, as well as an objective index for pervasive monitoring of emotion and mood disorders in daily life. Here we review evidence that demonstrates the relationship between gait, emotions and mood disorders, highlighting the potential of a multimodal approach that couples gait data with physiological signals and home-based monitoring for early detection and management of mood disorders. This could enhance self-awareness, enable the development of objective biomarkers that identify high risk subjects and promote subject-specific treatment.
Collapse
|
28
|
Buck B, Scherer E, Brian R, Wang R, Wang W, Campbell A, Choudhury T, Hauser M, Kane JM, Ben-Zeev D. Relationships between smartphone social behavior and relapse in schizophrenia: A preliminary report. Schizophr Res 2019; 208:167-172. [PMID: 30940400 PMCID: PMC6580857 DOI: 10.1016/j.schres.2019.03.014] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Revised: 03/05/2019] [Accepted: 03/18/2019] [Indexed: 02/07/2023]
Abstract
Social dysfunction is a hallmark of schizophrenia. Social isolation may increase individuals' risk for psychotic symptom exacerbation and relapse. Monitoring and timely detection of shifts in social functioning are hampered by the limitations of traditional clinic-based assessment strategies. Ubiquitous mobile technologies such as smartphones introduce new opportunities to capture objective digital indicators of social behavior. The goal of this study was to evaluate whether smartphone-collected digital measures of social behavior can provide early indication of relapse events among individuals with schizophrenia. Sixty-one individuals with schizophrenia with elevated risk for relapse were given smartphones with the CrossCheck behavioral sensing system for a year of remote monitoring. CrossCheck leveraged the device's microphone, call record, and text messaging log to capture digital socialization data. Relapse events including psychiatric hospitalizations, suicidal ideation, and significant psychiatric symptom exacerbations were recorded by trained assessors. Exploratory mixed effects models examined relationships of social behavior to relapse, finding that reductions in number and duration of outgoing calls, as well as number of text messages were associated with relapses. Number and duration of incoming phone calls and in-person conversations were not. Smartphone enabled social activity may provide an important metric in determining relapse risk in schizophrenia and provide access to sensitive, meaningful and ecologically valid data streams never before available in routine care.
Collapse
Affiliation(s)
- Benjamin Buck
- Health Services Research & Development, Puget Sound VA Healthcare System, Seattle, WA, United States of America; Department of Health Services, School of Public Health, Univ. of Washington, Seattle, WA, United States of America; Behavioral Research in Technology and Engineering (BRiTE) Center, Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States of America.
| | - Emily Scherer
- Geisel School of Medicine, Dartmouth College, Hanover, NH
| | - Rachel Brian
- Behavioral Research in Technology and Engineering (BRiTE) Center, Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA
| | - Rui Wang
- Department of Computer Science, Dartmouth College, Hanover, NH
| | - Weichen Wang
- Department of Computer Science, Dartmouth College, Hanover, NH
| | - Andrew Campbell
- Department of Computer Science, Dartmouth College, Hanover, NH
| | | | - Marta Hauser
- The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY,Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY
| | - John M. Kane
- The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY,Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY
| | - Dror Ben-Zeev
- Behavioral Research in Technology and Engineering (BRiTE) Center, Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA
| |
Collapse
|