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Hong CS, Smith TR. Aerobic exercise interventions to address impaired quality of life in patients with pituitary tumors. PLoS One 2023; 18:e0295907. [PMID: 38100429 PMCID: PMC10723697 DOI: 10.1371/journal.pone.0295907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 12/01/2023] [Indexed: 12/17/2023] Open
Abstract
Patients with pituitary tumors may experience persistent fatigue and reduced physical activity, based on subjective measures after treatment. These symptoms may persist despite gross total resection of their tumors and biochemical normalization of pituitary function. While reduced quality of life has been commonly acknowledged in pituitary tumor patients, there is a lack of studies on what interventions may be best implemented to ameliorate these issues, particularly when hormonal levels have otherwise normalized. Aerobic exercise programs have been previously described to ameliorate symptoms of chronic fatigue and reduced physical capacity across a variety of pathologies in the literature. As such, a prescribed aerobic exercise program may be an underrecognized but potentially impactful intervention to address quality of life in pituitary tumor patients. This review seeks to summarize the existing literature on aerobic exercise interventions in patients with pituitary tumors. In addition, future areas of study are discussed, including tailoring exercise programs to the hormonal status of the patient and incorporating more objective measures in monitoring response to interventions.
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Affiliation(s)
- Christopher S. Hong
- Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Computational Neuroscience Outcomes Center (CNOC), Boston, Masachusettts, United States of America
| | - Timothy R. Smith
- Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Computational Neuroscience Outcomes Center (CNOC), Boston, Masachusettts, United States of America
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2
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Kalman JL, Burkhardt G, Samochowiec J, Gebhard C, Dom G, John M, Kilic O, Kurimay T, Lien L, Schouler-Ocak M, Vidal DP, Wiser J, Gaebel W, Volpe U, Falkai P. Digitalising mental health care: Practical recommendations from the European Psychiatric Association. Eur Psychiatry 2023; 67:e4. [PMID: 38086744 PMCID: PMC10790232 DOI: 10.1192/j.eurpsy.2023.2466] [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: 06/08/2023] [Revised: 09/17/2023] [Accepted: 10/12/2023] [Indexed: 01/06/2024] Open
Abstract
The digitalisation of mental health care is expected to improve the accessibility and quality of specialised treatment services and introduce innovative methods to study, assess, and monitor mental health disorders. In this narrative review and practical recommendation of the European Psychiatric Association (EPA), we aim to help healthcare providers and policymakers to navigate this rapidly evolving field. We provide an overview of the current scientific and implementation status across two major domains of digitalisation: i) digital mental health interventions and ii) digital phenotyping, discuss the potential of each domain to improve the accessibility and outcomes of mental health services, and highlight current challenges faced by researchers, clinicians, and service users. Furthermore, we make several recommendations meant to foster the widespread adoption of evidence-based digital solutions for mental health care in the member states of the EPA. To realise the vision of a digitalised, patient-centred, and data-driven mental health ecosystem, a number of implementation challenges must be considered and addressed, spanning from human, technical, ethical-legal, and economic barriers. The list of priority areas and action points our expert panel has identified could serve as a playbook for this process.
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Affiliation(s)
- Janos L. Kalman
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Department of Psychiatry and Psychotherapy, LMU University Hospital, Munich, Germany
| | - Gerrit Burkhardt
- Department of Psychiatry and Psychotherapy, LMU University Hospital, Munich, Germany
| | - Jerzy Samochowiec
- Department of Psychiatry, Pomeranian Medical University, Szczecin, Poland
| | | | - Geert Dom
- Collaborative Antwerp Psychiatric Research Institute (CAPRI), University of Antwerp, Antwerp, Belgium
| | - Miriam John
- Department of Psychiatry and Psychotherapy, LMU University Hospital, Munich, Germany
| | - Ozge Kilic
- Department of Psychiatry, Bezmialem Vakıf University Faculty of Medicine, Istanbul, Turkey
| | - Tamas Kurimay
- North-Buda Saint John Central Hospital, Buda Family Centred Mental Health Centre, Department of Psychiatry and Psychiatric Rehabilitation, Teaching Department of Semmelweis University, Budapest, Hungary
| | - Lars Lien
- National Advisory Unit on Concurrent Substance Abuse and Mental Health Disorders, Innlandet Hospital Trust, Hamar, Norway, Faculty of Social and Health Sciences, Inland Norway University of Applied Sciences, Elverum, Norway
| | - Meryam Schouler-Ocak
- Psychiatric University Clinic of Charité at St. Hedwig Hospital, Berlin, Germany
| | - Diego Palao Vidal
- Mental Health Service, Parc Taulí University Hospital, Unitat Mixta de Neurociència Traslacional I3PT-INc-UAB, Sabadell, Spain
- Department of Psychiatry and Forensic Medicine, Autonomous University of Barcelona, Cerdanyola del Vallès, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
| | - Jan Wiser
- CNWL NHS Foundation Trust, London, UK
| | - Wolfgang Gaebel
- WHO Collaborating Centre DEU-131, VR-Klinikum Düsseldorf, Department of Psychiatry and Psychotherapy, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany
| | - Umberto Volpe
- Unit of Clinical Psychiatry, Department of Clinical Neurosciences/DIMSC, School of Medicine, Università Politecnica delle Marche, Ancona, Italy
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, LMU University Hospital, Munich, Germany
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3
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Oudin A, Maatoug R, Bourla A, Ferreri F, Bonnot O, Millet B, Schoeller F, Mouchabac S, Adrien V. Digital Phenotyping: Data-Driven Psychiatry to Redefine Mental Health. J Med Internet Res 2023; 25:e44502. [PMID: 37792430 PMCID: PMC10585447 DOI: 10.2196/44502] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 07/10/2023] [Accepted: 08/21/2023] [Indexed: 10/05/2023] Open
Abstract
The term "digital phenotype" refers to the digital footprint left by patient-environment interactions. It has potential for both research and clinical applications but challenges our conception of health care by opposing 2 distinct approaches to medicine: one centered on illness with the aim of classifying and curing disease, and the other centered on patients, their personal distress, and their lived experiences. In the context of mental health and psychiatry, the potential benefits of digital phenotyping include creating new avenues for treatment and enabling patients to take control of their own well-being. However, this comes at the cost of sacrificing the fundamental human element of psychotherapy, which is crucial to addressing patients' distress. In this viewpoint paper, we discuss the advances rendered possible by digital phenotyping and highlight the risk that this technology may pose by partially excluding health care professionals from the diagnosis and therapeutic process, thereby foregoing an essential dimension of care. We conclude by setting out concrete recommendations on how to improve current digital phenotyping technology so that it can be harnessed to redefine mental health by empowering patients without alienating them.
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Affiliation(s)
- Antoine Oudin
- Infrastructure for Clinical Research in Neurosciences, Paris Brain Institute, Sorbonne University- Institut national de la santé et de la recherche médicale - Centre national de la recherche scientifique, Paris, France
- Department of Psychiatry, Pitié-Salpêtrière Hospital, Public Hospitals of Sorbonne University, Paris, France
| | - Redwan Maatoug
- Infrastructure for Clinical Research in Neurosciences, Paris Brain Institute, Sorbonne University- Institut national de la santé et de la recherche médicale - Centre national de la recherche scientifique, Paris, France
- Department of Psychiatry, Pitié-Salpêtrière Hospital, Public Hospitals of Sorbonne University, Paris, France
| | - Alexis Bourla
- Infrastructure for Clinical Research in Neurosciences, Paris Brain Institute, Sorbonne University- Institut national de la santé et de la recherche médicale - Centre national de la recherche scientifique, Paris, France
- Department of Psychiatry, Saint-Antoine Hospital, Public Hospitals of Sorbonne University, Paris, France
- Medical Strategy and Innovation Department, Clariane, Paris, France
- NeuroStim Psychiatry Practice, Paris, France
| | - Florian Ferreri
- Infrastructure for Clinical Research in Neurosciences, Paris Brain Institute, Sorbonne University- Institut national de la santé et de la recherche médicale - Centre national de la recherche scientifique, Paris, France
- Department of Psychiatry, Saint-Antoine Hospital, Public Hospitals of Sorbonne University, Paris, France
| | - Olivier Bonnot
- Department of Child and Adolescent Psychiatry, Nantes University Hospital, Nantes, France
- Pays de la Loire Psychology Laboratory, Nantes University, Nantes, France
| | - Bruno Millet
- Infrastructure for Clinical Research in Neurosciences, Paris Brain Institute, Sorbonne University- Institut national de la santé et de la recherche médicale - Centre national de la recherche scientifique, Paris, France
- Department of Psychiatry, Pitié-Salpêtrière Hospital, Public Hospitals of Sorbonne University, Paris, France
| | - Félix Schoeller
- Institute for Advanced Consciousness Studies, Santa Monica, CA, United States
- Media Lab, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Stéphane Mouchabac
- Infrastructure for Clinical Research in Neurosciences, Paris Brain Institute, Sorbonne University- Institut national de la santé et de la recherche médicale - Centre national de la recherche scientifique, Paris, France
- Department of Psychiatry, Saint-Antoine Hospital, Public Hospitals of Sorbonne University, Paris, France
| | - Vladimir Adrien
- Infrastructure for Clinical Research in Neurosciences, Paris Brain Institute, Sorbonne University- Institut national de la santé et de la recherche médicale - Centre national de la recherche scientifique, Paris, France
- Department of Psychiatry, Saint-Antoine Hospital, Public Hospitals of Sorbonne University, Paris, France
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4
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Digital tools for the assessment of pharmacological treatment for depressive disorder: State of the art. Eur Neuropsychopharmacol 2022; 60:100-116. [PMID: 35671641 DOI: 10.1016/j.euroneuro.2022.05.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 05/13/2022] [Accepted: 05/17/2022] [Indexed: 12/23/2022]
Abstract
Depression is an invalidating disorder, marked by phenotypic heterogeneity. Clinical assessments for treatment adjustments and data-collection for pharmacological research often rely on subjective representations of functioning. Better phenotyping through digital applications may add unseen information and facilitate disentangling the clinical characteristics and impact of depression and its pharmacological treatment in everyday life. Researchers, physicians, and patients benefit from well-understood digital phenotyping approaches to assess the treatment efficacy and side-effects. This review discusses the current possibilities and pitfalls of wearables and technology for the assessment of the pharmacological treatment of depression. Their applications in the whole spectrum of treatment for depression, including diagnosis, treatment of an episode, and monitoring of relapse risk and prevention are discussed. Multiple aspects are to be considered, including concerns that come with collecting sensitive data and health recordings. Also, privacy and trust are addressed. Available applications range from questionnaire-like apps to objective assessment of behavioural patterns and promises in handling suicidality. Nonetheless, interpretation and integration of this high-resolution information with other phenotyping levels, remains challenging. This review provides a state-of-the-art description of wearables and technology in digital phenotyping for monitoring pharmacological treatment in depression, focusing on the challenges and opportunities of its application in clinical trials and research.
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Milne R, Costa A, Brenman N. Digital phenotyping and the (data) shadow of Alzheimer's disease. BIG DATA & SOCIETY 2022; 9:20539517211070748. [PMID: 36793447 PMCID: PMC7614175 DOI: 10.1177/20539517211070748] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
Abstract
In this paper, we examine the practice and promises of digital phenotyping. We build on work on the 'data self' to focus on a medical domain in which the value and nature of knowledge and relations with data have been played out with particular persistence, that of Alzheimer's disease research. Drawing on research with researchers and developers, we consider the intersection of hopes and concerns related to both digital tools and Alzheimer's disease using the metaphor of the 'data shadow'. We suggest that as a tool for engaging with the nature of the data self, the shadow is usefully able to capture both the dynamic and distorted nature of data representations, and the unease and concern associated with encounters between individuals or groups and data about them. We then consider what the data shadow 'is' in relation to ageing data subjects, and the nature of the representation of the individual's cognitive state and dementia risk that is produced by digital tools. Second, we consider what the data shadow 'does', through researchers and practitioners' discussions of digital phenotyping practices in the dementia field as alternately empowering, enabling and threatening.
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Affiliation(s)
- Richard Milne
- Engagement and Society, Wellcome Connecting Science, Hinxton, UK
- Cambridge Public Health, University of Cambridge, Cambridge, UK
| | - Alessia Costa
- Engagement and Society, Wellcome Connecting Science, Hinxton, UK
| | - Natassia Brenman
- Cambridge Public Health, University of Cambridge, Cambridge, UK
- Department of Sociology, Goldsmiths, University of London, London, UK
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6
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Blom JMC, Colliva C, Benatti C, Tascedda F, Pani L. Digital Phenotyping and Dynamic Monitoring of Adolescents Treated for Cancer to Guide Intervention: Embracing a New Era. Front Oncol 2021; 11:673581. [PMID: 34262863 PMCID: PMC8273734 DOI: 10.3389/fonc.2021.673581] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Accepted: 06/07/2021] [Indexed: 11/13/2022] Open
Affiliation(s)
- Johanna M. C. Blom
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
| | - Chiara Colliva
- Azienda Unità Sanitaria Locale di Modena, Distretto di Carpi, Carpi, Italy
| | - Cristina Benatti
- Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
- Department of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Fabio Tascedda
- Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
- Department of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Luca Pani
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
- Department of Psychiatry and Behavioral Sciences, University of Miami, Miami, FL, United States
- VeraSci., Durham, NC, United States
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7
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Vlisides-Henry RD, Gao M, Thomas L, Kaliush PR, Conradt E, Crowell SE. Digital Phenotyping of Emotion Dysregulation Across Lifespan Transitions to Better Understand Psychopathology Risk. Front Psychiatry 2021; 12:618442. [PMID: 34108893 PMCID: PMC8183608 DOI: 10.3389/fpsyt.2021.618442] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Accepted: 04/26/2021] [Indexed: 11/13/2022] Open
Abstract
Ethical and consensual digital phenotyping through smartphone activity (i. e., passive behavior monitoring) permits measurement of temporal risk trajectories unlike ever before. This data collection modality may be particularly well-suited for capturing emotion dysregulation, a transdiagnostic risk factor for psychopathology, across lifespan transitions. Adolescence, emerging adulthood, and perinatal transitions are particularly sensitive developmental periods, often marked by increased distress. These participant groups are typically assessed with laboratory-based methods that can be costly and burdensome. Passive monitoring presents a relatively cost-effective and unobtrusive way to gather rich and objective information about emotion dysregulation and risk behaviors. We first discuss key theoretically-driven concepts pertaining to emotion dysregulation and passive monitoring. We then identify variables that can be measured passively and hold promise for better understanding emotion dysregulation. For example, two strong markers of emotion dysregulation are sleep disturbance and problematic use of Internet/social media (i.e., use that prompts negative emotions/outcomes). Variables related to mobility are also potentially useful markers, though these variables should be tailored to fit unique features of each developmental stage. Finally, we offer our perspective on candidate digital variables that may prove useful for each developmental transition. Smartphone-based passive monitoring is a rigorous method that can elucidate psychopathology risk across human development. Nonetheless, its use requires researchers to weigh unique ethical considerations, examine relevant theory, and consider developmentally-specific lifespan features that may affect implementation.
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Affiliation(s)
| | - Mengyu Gao
- Department of Psychology, University of Utah, Salt Lake City, UT, United States
| | - Leah Thomas
- Department of Psychology, University of Utah, Salt Lake City, UT, United States
| | - Parisa R Kaliush
- Department of Psychology, University of Utah, Salt Lake City, UT, United States
| | - Elisabeth Conradt
- Department of Psychology, University of Utah, Salt Lake City, UT, United States.,Department of Obstetrics and Gynecology, University of Utah, Salt Lake City, UT, United States.,Department of Pediatrics, University of Utah, Salt Lake City, UT, United States
| | - Sheila E Crowell
- Department of Psychology, University of Utah, Salt Lake City, UT, United States.,Department of Obstetrics and Gynecology, University of Utah, Salt Lake City, UT, United States.,Department of Psychiatry, University of Utah, Salt Lake City, UT, United States
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8
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Jayakumar P, Lin E, Galea V, Mathew AJ, Panda N, Vetter I, Haynes AB. Digital Phenotyping and Patient-Generated Health Data for Outcome Measurement in Surgical Care: A Scoping Review. J Pers Med 2020; 10:E282. [PMID: 33333915 PMCID: PMC7765378 DOI: 10.3390/jpm10040282] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Revised: 12/08/2020] [Accepted: 12/11/2020] [Indexed: 12/13/2022] Open
Abstract
Digital phenotyping-the moment-by-moment quantification of human phenotypes in situ using data related to activity, behavior, and communications, from personal digital devices, such as smart phones and wearables-has been gaining interest. Personalized health information captured within free-living settings using such technologies may better enable the application of patient-generated health data (PGHD) to provide patient-centered care. The primary objective of this scoping review is to characterize the application of digital phenotyping and digitally captured active and passive PGHD for outcome measurement in surgical care. Secondarily, we synthesize the body of evidence to define specific areas for further work. We performed a systematic search of four bibliographic databases using terms related to "digital phenotyping and PGHD," "outcome measurement," and "surgical care" with no date limits. We registered the study (Open Science Framework), followed strict inclusion/exclusion criteria, performed screening, extraction, and synthesis of results in line with the PRISMA Extension for Scoping Reviews. A total of 224 studies were included. Published studies have accelerated in the last 5 years, originating in 29 countries (mostly from the USA, n = 74, 33%), featuring original prospective work (n = 149, 66%). Studies spanned 14 specialties, most commonly orthopedic surgery (n = 129, 58%), and had a postoperative focus (n = 210, 94%). Most of the work involved research-grade wearables (n = 130, 58%), prioritizing the capture of activity (n = 165, 74%) and biometric data (n = 100, 45%), with a view to providing a tracking/monitoring function (n = 115, 51%) for the management of surgical patients. Opportunities exist for further work across surgical specialties involving smartphones, communications data, comparison with patient-reported outcome measures (PROMs), applications focusing on prediction of outcomes, monitoring, risk profiling, shared decision making, and surgical optimization. The rapidly evolving state of the art in digital phenotyping and capture of PGHD offers exciting prospects for outcome measurement in surgical care pending further work and consideration related to clinical care, technology, and implementation.
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Affiliation(s)
- Prakash Jayakumar
- Department of Surgery and Perioperative Care, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA; (E.L.); (A.J.M.); (A.B.H.)
| | - Eugenia Lin
- Department of Surgery and Perioperative Care, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA; (E.L.); (A.J.M.); (A.B.H.)
| | - Vincent Galea
- School of Medicine, New York Medical College, Valhalla, NY 10595, USA;
| | - Abraham J. Mathew
- Department of Surgery and Perioperative Care, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA; (E.L.); (A.J.M.); (A.B.H.)
| | - Nikhil Panda
- Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA;
| | - Imelda Vetter
- Department of Medical Education, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA;
| | - Alex B. Haynes
- Department of Surgery and Perioperative Care, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA; (E.L.); (A.J.M.); (A.B.H.)
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Ebner-Priemer UW, Mühlbauer E, Neubauer AB, Hill H, Beier F, Santangelo PS, Ritter P, Kleindienst N, Bauer M, Schmiedek F, Severus E. Digital phenotyping: towards replicable findings with comprehensive assessments and integrative models in bipolar disorders. Int J Bipolar Disord 2020; 8:35. [PMID: 33211262 PMCID: PMC7677415 DOI: 10.1186/s40345-020-00210-4] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Accepted: 10/21/2020] [Indexed: 01/05/2023] Open
Abstract
Background Digital phenotyping promises to unobtrusively obtaining a continuous and objective input of symptomatology from patients’ daily lives. The prime example are bipolar disorders, as smartphone parameters directly reflect bipolar symptomatology. Empirical studies, however, have yielded inconsistent findings. We believe that three main shortcomings have to be addressed to fully leverage the potential of digital phenotyping: short assessment periods, rare outcome assessments, and an extreme fragmentation of parameters without an integrative analytical strategy. Methods To demonstrate how to overcome these shortcomings, we conducted frequent (biweekly) dimensional and categorical expert ratings and daily self-ratings over an extensive assessment period (12 months) in 29 patients with bipolar disorder. Digital phenotypes were monitored continuously. As an integrative analytical strategy, we used structural equation modelling to build latent psychopathological outcomes (mania, depression) and latent digital phenotype predictors (sleep, activity, communicativeness). Outcomes Combining gold-standard categorical expert ratings with dimensional self and expert ratings resulted in two latent outcomes (mania and depression) with statistically meaningful factor loadings that dynamically varied over 299 days. Latent digital phenotypes of sleep and activity were associated with same-day latent manic psychopathology, suggesting that psychopathological alterations in bipolar disorders relate to domains (latent variables of sleep and activity) and not only to specific behaviors (such as the number of declined incoming calls). The identification of latent psychopathological outcomes that dimensionally vary on a daily basis will enable to empirically determine which combination of digital phenotypes at which days prior to an upcoming episode are viable as digital prodromal predictors.
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Affiliation(s)
- Ulrich W Ebner-Priemer
- Mental mHealth Lab, Institute of Sport and Sport Sciences, Karlsruhe Institute of Technology, Karlsruhe, Germany. .,Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannheim/Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
| | - Esther Mühlbauer
- Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Andreas B Neubauer
- DIPF - Leibniz Institute for Research and Information in Education, Frankfurt, Germany
| | - Holger Hill
- Mental mHealth Lab, Institute of Sport and Sport Sciences, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Fabrice Beier
- Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Philip S Santangelo
- Mental mHealth Lab, Institute of Sport and Sport Sciences, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Philipp Ritter
- Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Nikolaus Kleindienst
- Institute of Psychiatric and Psychosomatic Psychotherapy, Central Institute of Mental Health, Mannheim / Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Michael Bauer
- Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Florian Schmiedek
- DIPF - Leibniz Institute for Research and Information in Education, Frankfurt, Germany.,Department of Psychology, Goethe University, Frankfurt, Germany
| | - Emanuel Severus
- Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
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10
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Ebner-Priemer U, Santangelo P. Digital phenotyping: hype or hope? Lancet Psychiatry 2020; 7:297-299. [PMID: 31635970 DOI: 10.1016/s2215-0366(19)30380-3] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Accepted: 09/27/2019] [Indexed: 10/25/2022]
Affiliation(s)
- Ulrich Ebner-Priemer
- Mental mhealth Lab, Institute of Sports and Sports Science, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany.
| | - Philip Santangelo
- Department of Psychology, College of Arts and Sciences, Syracuse University, New York, NY, USA
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11
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Fagherazzi G. Deep Digital Phenotyping and Digital Twins for Precision Health: Time to Dig Deeper. J Med Internet Res 2020; 22:e16770. [PMID: 32130138 PMCID: PMC7078624 DOI: 10.2196/16770] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Revised: 12/21/2019] [Accepted: 12/21/2019] [Indexed: 12/15/2022] Open
Abstract
This viewpoint describes the urgent need for more large-scale, deep digital phenotyping to advance toward precision health. It describes why and how to combine real-world digital data with clinical data and omics features to identify someone’s digital twin, and how to finally enter the era of patient-centered care and modify the way we view disease management and prevention.
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Affiliation(s)
- Guy Fagherazzi
- Luxembourg Institute of Health, Department of Population Health, Digital Epidemiology Hub, Strassen, Luxembourg
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12
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Barnett S, Huckvale K, Christensen H, Venkatesh S, Mouzakis K, Vasa R. Intelligent Sensing to Inform and Learn (InSTIL): A Scalable and Governance-Aware Platform for Universal, Smartphone-Based Digital Phenotyping for Research and Clinical Applications. J Med Internet Res 2019; 21:e16399. [PMID: 31692450 PMCID: PMC6868504 DOI: 10.2196/16399] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Revised: 10/22/2019] [Accepted: 10/22/2019] [Indexed: 02/06/2023] Open
Abstract
In this viewpoint we describe the architecture of, and design rationale for, a new software platform designed to support the conduct of digital phenotyping research studies. These studies seek to collect passive and active sensor signals from participants' smartphones for the purposes of modelling and predicting health outcomes, with a specific focus on mental health. We also highlight features of the current research landscape that recommend the coordinated development of such platforms, including the significant technical and resource costs of development, and we identify specific considerations relevant to the design of platforms for digital phenotyping. In addition, we describe trade-offs relating to data quality and completeness versus the experience for patients and public users who consent to their devices being used to collect data. We summarize distinctive features of the resulting platform, InSTIL (Intelligent Sensing to Inform and Learn), which includes universal (ie, cross-platform) support for both iOS and Android devices and privacy-preserving mechanisms which, by default, collect only anonymized participant data. We conclude with a discussion of recommendations for future work arising from learning during the development of the platform. The development of the InSTIL platform is a key step towards our research vision of a population-scale, international, digital phenotyping bank. With suitable adoption, the platform will aggregate signals from large numbers of participants and large numbers of research studies to support modelling and machine learning analyses focused on the prediction of mental illness onset and disease trajectories.
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Affiliation(s)
- Scott Barnett
- Applied Artificial Intelligence Institute (A2I2), Deakin University, Geelong, Australia
| | - Kit Huckvale
- Black Dog Institute, UNSW Sydney, Randwick, Australia
| | - Helen Christensen
- Black Dog Institute, UNSW Sydney, Randwick, Australia.,Mindgardens Neuroscience Network, Sydney, Australia
| | - Svetha Venkatesh
- Applied Artificial Intelligence Institute (A2I2), Deakin University, Geelong, Australia
| | - Kon Mouzakis
- Black Dog Institute, UNSW Sydney, Randwick, Australia
| | - Rajesh Vasa
- Applied Artificial Intelligence Institute (A2I2), Deakin University, Geelong, Australia
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13
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Huckvale K, Venkatesh S, Christensen H. Toward clinical digital phenotyping: a timely opportunity to consider purpose, quality, and safety. NPJ Digit Med 2019; 2:88. [PMID: 31508498 PMCID: PMC6731256 DOI: 10.1038/s41746-019-0166-1] [Citation(s) in RCA: 141] [Impact Index Per Article: 28.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Accepted: 08/09/2019] [Indexed: 02/07/2023] Open
Abstract
The use of data generated passively by personal electronic devices, such as smartphones, to measure human function in health and disease has generated significant research interest. Particularly in psychiatry, objective, continuous quantitation using patients' own devices may result in clinically useful markers that can be used to refine diagnostic processes, tailor treatment choices, improve condition monitoring for actionable outcomes, such as early signs of relapse, and develop new intervention models. If a principal goal for digital phenotyping is clinical improvement, research needs to attend now to factors that will help or hinder future clinical adoption. We identify four opportunities for research directed toward this goal: exploring intermediate outcomes and underlying disease mechanisms; focusing on purposes that are likely to be used in clinical practice; anticipating quality and safety barriers to adoption; and exploring the potential for digital personalized medicine arising from the integration of digital phenotyping and digital interventions. Clinical relevance also means explicitly addressing consumer needs, preferences, and acceptability as the ultimate users of digital phenotyping interventions. There is a risk that, without such considerations, the potential benefits of digital phenotyping are delayed or not realized because approaches that are feasible for application in healthcare, and the evidence required to support clinical commissioning, are not developed. Practical steps to accelerate this research agenda include the further development of digital phenotyping technology platforms focusing on scalability and equity, establishing shared data repositories and common data standards, and fostering multidisciplinary collaborations between clinical stakeholders (including patients), computer scientists, and researchers.
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Affiliation(s)
- Kit Huckvale
- Black Dog Institute, UNSW Sydney, Sydney, NSW Australia
| | | | - Helen Christensen
- Black Dog Institute, UNSW Sydney, Sydney, NSW Australia
- Mindgardens Neuroscience Network, Sydney, NSW Australia
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14
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Messner EM, Sariyska R, Mayer B, Montag C, Kannen C, Schwerdtfeger A, Baumeister H. Insights – Future Implications of Passive Smartphone Sensing in the Therapeutic Context. VERHALTENSTHERAPIE 2019. [DOI: 10.1159/000501951] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
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15
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Messner EM, Sariyska R, Mayer B, Montag C, Kannen C, Schwerdtfeger A, Baumeister H. Insights: Anwendungsmöglichkeiten von passivem Smartphone-Tracking im therapeutischen Kontext. VERHALTENSTHERAPIE 2019. [DOI: 10.1159/000501735] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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16
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Poletti M, Gebhardt E, Kvande MN, Ford J, Raballo A. Motor Impairment and Developmental Psychotic Risk: Connecting the Dots and Narrowing the Pathophysiological Gap. Schizophr Bull 2019; 45:503-508. [PMID: 30007369 PMCID: PMC6483583 DOI: 10.1093/schbul/sby100] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
The motor system in its manifold articulations is receiving increasing clinical and research attention. This is because motor impairments constitute a central, expressive component of the mental state examination and a key transdiagnostic feature indexing disease severity. Furthermore, within the schizophrenia spectrum, the integration of neurophysiological, developmental, and phenomenological perspectives suggests that motor impairment is not simply a generic, extrinsic proxy of an altered neurodevelopment, but might be more intimately related to psychotic risk. Therefore, an increased understanding, conceptualization, and knowledge of such motor system and its anomalies could empower contemporary risk prediction and diagnostic procedures.
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Affiliation(s)
- Michele Poletti
- Department of Mental Health, Reggio Emilia Local Health Trust, Reggio Emilia, Italy
| | - Eva Gebhardt
- Cmed Polyspecialistic Diagnostic and Therapeutic Centre, Rome, Italy
| | - Marianne N Kvande
- Department of Psychology, Psychopathology and development Research Unit, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Judith Ford
- Psychiatry Service (116D), San Francisco VA Medical Center, San Francisco, CA,Department of Psychiatry, University of California, San Francisco, CA
| | - Andrea Raballo
- Department of Psychology, Psychopathology and development Research Unit, Norwegian University of Science and Technology (NTNU), Trondheim, Norway,Department of Medicine, Division of Psychiatry, Clinical Psychology and Rehabilitation, University of Perugia, Perugia, Italy,To whom correspondence should be addressed; Piazzale Lucio Severi 1, 06132 Perugia, Italy, tel: +390755784100, e-mail:
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17
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Concept, Possibilities and Pilot-Testing of a New Smartphone Application for the Social and Life Sciences to Study Human Behavior Including Validation Data from Personality Psychology. J 2019. [DOI: 10.3390/j2020008] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
With the advent of the World Wide Web, the smartphone and the Internet of Things, not only society but also the sciences are rapidly changing. In particular, the social sciences can profit from these digital developments, because now scientists have the power to study real-life human behavior via smartphones and other devices connected to the Internet of Things on a large-scale level. Although this sounds easy, scientists often face the problem that no practicable solution exists to participate in such a new scientific movement, due to a lack of an interdisciplinary network. If so, the development time of a new product, such as a smartphone application to get insights into human behavior takes an enormous amount of time and resources. Given this problem, the present work presents an easy way to use a smartphone application, which can be applied by social scientists to study a large range of scientific questions. The application provides measurements of variables via tracking smartphone–use patterns, such as call behavior, application use (e.g., social media), GPS and many others. In addition, the presented Android-based smartphone application, called Insights, can also be used to administer self-report questionnaires for conducting experience sampling and to search for co-variations between smartphone usage/smartphone data and self-report data. Of importance, the present work gives a detailed overview on how to conduct a study using an application such as Insights, starting from designing the study, installing the application to analyzing the data. In the present work, server requirements and privacy issues are also discussed. Furthermore, first validation data from personality psychology are presented. Such validation data are important in establishing trust in the applied technology to track behavior. In sum, the aim of the present work is (i) to provide interested scientists a short overview on how to conduct a study with smartphone app tracking technology, (ii) to present the features of the designed smartphone application and (iii) to demonstrate its validity with a proof of concept study, hence correlating smartphone usage with personality measures.
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18
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Van Dam L, Rietstra S, Van der Drift E, Stams GJJM, Van der Mei R, Mahfoud M, Popma A, Schlossberg E, Pentland A, Reid TG. Can an Emoji a Day Keep the Doctor Away? An Explorative Mixed-Methods Feasibility Study to Develop a Self-Help App for Youth With Mental Health Problems. Front Psychiatry 2019; 10:593. [PMID: 31507464 PMCID: PMC6716472 DOI: 10.3389/fpsyt.2019.00593] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2019] [Accepted: 07/26/2019] [Indexed: 11/13/2022] Open
Abstract
Today's smartphones allow for a wide range of "big data" measurement, for example, ecological momentary assessment (EMA), whereby behaviours are repeatedly assessed within a person's natural environment. With this type of data, we can better understand - and predict - risk for behavioral and health issues and opportunities for (self-monitoring) interventions. In this mixed-methods feasibility study, through convenience sampling we collected data from 32 participants (aged 16-24) over a period of three months. To gain more insight into the app experiences of youth with mental health problems, we interviewed a subsample of 10 adolescents who received psycthological treatment. The results from this feasibility study indicate that emojis) can be used to identify positive and negative feelings, and individual pattern analyses of emojis may be useful for clinical purposes. While adolescents receiving mental health care are positive about future applications, these findings also highlight some caveats, such as possible drawback of inaccurate representation and incorrect predictions of emotional states. Therefore, at this stage, the app should always be combined with professional counseling. Results from this small pilot study warrant replication with studies of substantially larger sample size.
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Affiliation(s)
- Levi Van Dam
- Spirit Youth Care Amsterdam, Amsterdam, Netherlands.,Department of Child Development and Education, University of Amsterdam, Amsterdam, Netherlands
| | - Sianne Rietstra
- Department of Child Development and Education, University of Amsterdam, Amsterdam, Netherlands
| | | | - Geert Jan J M Stams
- Department of Child Development and Education, University of Amsterdam, Amsterdam, Netherlands
| | | | - Maria Mahfoud
- Centrum Wiskunde and Informatica, Amsterdam, Netherlands
| | - Arne Popma
- Department of Child and Adolescent Psychiatry, Amsterdam UMC/De Bascule, Amsterdam, Netherlands.,Institute for Criminal Law and Criminology, Leiden University, Leiden, Netherlands
| | - Eric Schlossberg
- Connection Science, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Alex Pentland
- Connection Science, Massachusetts Institute of Technology, Cambridge, MA, United States.,Media Lab, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Todd G Reid
- Connection Science, Massachusetts Institute of Technology, Cambridge, MA, United States.,Media Lab, Massachusetts Institute of Technology, Cambridge, MA, United States.,Harvard T. H. Chan School of Public Health, Boston, MA, United States
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19
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Martinez-Martin N, Insel TR, Dagum P, Greely HT, Cho MK. Data mining for health: staking out the ethical territory of digital phenotyping. NPJ Digit Med 2018; 1:68. [PMID: 31211249 PMCID: PMC6550156 DOI: 10.1038/s41746-018-0075-8] [Citation(s) in RCA: 67] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2018] [Accepted: 11/19/2018] [Indexed: 01/17/2023] Open
Abstract
Digital phenotyping uses smartphone and wearable signals to measure cognition, mood, and behavior. This promising new approach has been developed as an objective, passive assessment tool for the diagnosis and treatment of mental illness. Digital phenotyping is currently used with informed consent in research studies but is expected to expand to broader uses in healthcare and direct-to-consumer applications. Digital phenotyping could involve the collection of massive amounts of individual data and potential creation of new categories of health and risk assessment data. Because existing ethical and regulatory frameworks for the provision of mental healthcare do not clearly apply to digital phenotyping, it is critical to consider its possible ethical, legal, and social implications. This paper addresses four major areas where guidelines and best practices will be helpful: transparency, informed consent, privacy, and accountability. It will be important to consider these issues early in the development of this new approach so that its promise is not limited by harmful effects or unintended consequences.
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Affiliation(s)
| | - Thomas R. Insel
- Mindstrong Health, 248 Homer Street, Palo Alto, CA 94301 USA
| | - Paul Dagum
- Mindstrong Health, 248 Homer Street, Palo Alto, CA 94301 USA
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