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Galderisi S, Appelbaum PS, Gill N, Gooding P, Herrman H, Melillo A, Myrick K, Pathare S, Savage M, Szmukler G, Torous J. Ethical challenges in contemporary psychiatry: an overview and an appraisal of possible strategies and research needs. World Psychiatry 2024; 23:364-386. [PMID: 39279422 PMCID: PMC11403198 DOI: 10.1002/wps.21230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/18/2024] Open
Abstract
Psychiatry shares most ethical issues with other branches of medicine, but also faces special challenges. The Code of Ethics of the World Psychiatric Association offers guidance, but many mental health care professionals are unaware of it and the principles it supports. Furthermore, following codes of ethics is not always sufficient to address ethical dilemmas arising from possible clashes among their principles, and from continuing changes in knowledge, culture, attitudes, and socio-economic context. In this paper, we identify topics that pose difficult ethical challenges in contemporary psychiatry; that may have a significant impact on clinical practice, education and research activities; and that may require revision of the profession's codes of ethics. These include: the relationships between human rights and mental health care, research and training; human rights and mental health legislation; digital psychiatry; early intervention in psychiatry; end-of-life decisions by people with mental health conditions; conflicts of interests in clinical practice, training and research; and the role of people with lived experience and family/informal supporters in shaping the agenda of mental health care, policy, research and training. For each topic, we highlight the ethical concerns, suggest strategies to address them, call attention to the risks that these strategies entail, and highlight the gaps to be narrowed by further research. We conclude that, in order to effectively address current ethical challenges in psychiatry, we need to rethink policies, services, training, attitudes, research methods and codes of ethics, with the concurrent input of a range of stakeholders, open minded discussions, new models of care, and an adequate organizational capacity to roll-out the implementation across routine clinical care contexts, training and research.
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Affiliation(s)
| | - Paul S Appelbaum
- Columbia University and New York State Psychiatric Institute, New York, NY, USA
| | - Neeraj Gill
- School of Medicine and Dentistry, Griffith University, Gold Coast, Brisbane, QLD, Australia
- Mental Health Policy Unit, Health Research Institute, University of Canberra, Canberra, NSW, Australia
- Mental Health and Specialist Services, Gold Coast Health, Southport, QLD, Australia
| | - Piers Gooding
- La Trobe Law School, La Trobe University, Melbourne, VIC, Australia
| | - Helen Herrman
- Orygen, Parkville, VIC, Australia
- University of Melbourne, Parkville, VIC, Australia
| | | | - Keris Myrick
- Division of Digital Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Soumitra Pathare
- Centre for Mental Health Law and Policy, Indian Law Society, Pune, India
| | - Martha Savage
- Victoria University of Wellington, School of Geography, Environment and Earth Sciences, Wellington, New Zealand
| | - George Szmukler
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - John Torous
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
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Slater K, Schofield PN, Wright J, Clift P, Irani A, Bradlow W, Aziz F, Gkoutos GV. Talking about diseases; developing a model of patient and public-prioritised disease phenotypes. NPJ Digit Med 2024; 7:263. [PMID: 39349692 PMCID: PMC11443070 DOI: 10.1038/s41746-024-01257-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 09/11/2024] [Indexed: 10/04/2024] Open
Abstract
Deep phenotyping describes the use of standardised terminologies to create comprehensive phenotypic descriptions of biomedical phenomena. These characterisations facilitate secondary analysis, evidence synthesis, and practitioner awareness, thereby guiding patient care. The vast majority of this knowledge is derived from sources that describe an academic understanding of disease, including academic literature and experimental databases. Previous work indicates a gulf between the priorities, perspectives, and perceptions held by different healthcare stakeholders. Using social media data, we develop a phenotype model that represents a public perspective on disease and compare this with a model derived from a combination of existing academic phenotype databases. We identified 52,198 positive disease-phenotype associations from social media across 311 diseases. We further identified 24,618 novel phenotype associations not shared by the biomedical and literature-derived phenotype model across 304 diseases, of which we considered 14,531 significant. Manifestations of disease affecting quality of life, and concerning endocrine, digestive, and reproductive diseases were over-represented in the social media phenotype model. An expert clinical review found that social media-derived associations were considered similarly well-established to those derived from literature, and were seen significantly more in patient clinical encounters. The phenotype model recovered from social media presents a significantly different perspective than existing resources derived from biomedical databases and literature, providing a large number of associations novel to the latter dataset. We propose that the integration and interrogation of these public perspectives on the disease can inform clinical awareness, improve secondary analysis, and bridge understanding and priorities across healthcare stakeholders.
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Affiliation(s)
- Karin Slater
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.
- Centre for Environmental Research and Justice, University of Birmingham, Birmingham, UK.
- Centre for Health Data Science, University of Birmingham, Birmingham, UK.
- University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
| | - Paul N Schofield
- Department of Physiology, Development, and Neuroscience, University of Cambridge, Cambridge, UK
| | | | - Paul Clift
- University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Anushka Irani
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Division of Rheumatology, Mayo Clinic Florida, Jacksonville, FL, USA
| | - William Bradlow
- University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Furqan Aziz
- Centre for Health Data Science, University of Birmingham, Birmingham, UK
- School of Computing and Mathematical Sciences, University of Leicester, Leicester, UK
| | - Georgios V Gkoutos
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Centre for Environmental Research and Justice, University of Birmingham, Birmingham, UK
- Centre for Health Data Science, University of Birmingham, Birmingham, UK
- University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
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Grosman-Rimon L, Wegier P. With advancement in health technology comes great responsibility - Ethical and safety considerations for using digital health technology: A narrative review. Medicine (Baltimore) 2024; 103:e39136. [PMID: 39151529 PMCID: PMC11332755 DOI: 10.1097/md.0000000000039136] [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: 03/06/2024] [Revised: 07/04/2024] [Accepted: 07/09/2024] [Indexed: 08/19/2024] Open
Abstract
The accelerated adoption of digital health technologies in the last decades has raised important ethical and safety concerns. Despite the potency and usefulness of digital health technologies, addressing safety, and ethical considerations needs to take greater prominence. This review paper focuses on ethical and safety facets, including health technology-related risks, users' safety and well-being risks, security and privacy concerns, and risks to transparency and diminished accountability associated with the utilization of digital health technologies. In order to maximize the potential of health technology benefits, awareness of safety risks, and ethical concerns should be increased, and the use of appropriate strategies and measures should be considered.
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Affiliation(s)
- Liza Grosman-Rimon
- Levinsky-Wingate Academic College, Wingate Institute, Netanya, Israel
- Research Institute, Humber River Health, Toronto, ON, Canada
| | - Pete Wegier
- Research Institute, Humber River Health, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
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Jahanshad N, Lenzini P, Bijsterbosch J. Current best practices and future opportunities for reproducible findings using large-scale neuroimaging in psychiatry. Neuropsychopharmacology 2024:10.1038/s41386-024-01938-8. [PMID: 39117903 DOI: 10.1038/s41386-024-01938-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Revised: 06/05/2024] [Accepted: 07/09/2024] [Indexed: 08/10/2024]
Abstract
Research into the brain basis of psychopathology is challenging due to the heterogeneity of psychiatric disorders, extensive comorbidities, underdiagnosis or overdiagnosis, multifaceted interactions with genetics and life experiences, and the highly multivariate nature of neural correlates. Therefore, increasingly larger datasets that measure more variables in larger cohorts are needed to gain insights. In this review, we present current "best practice" approaches for using existing databases, collecting and sharing new repositories for big data analyses, and future directions for big data in neuroimaging and psychiatry with an emphasis on contributing to collaborative efforts and the challenges of multi-study data analysis.
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Affiliation(s)
- Neda Jahanshad
- Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, 90292, USA.
| | - Petra Lenzini
- Department of Radiology, Washington University School of Medicine, Saint Louis, MO, 63110, USA
| | - Janine Bijsterbosch
- Department of Radiology, Washington University School of Medicine, Saint Louis, MO, 63110, USA.
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Bilal AM, Pagoni K, Iliadis SI, Papadopoulos FC, Skalkidou A, Öster C. Exploring User Experiences of the Mom2B mHealth Research App During the Perinatal Period: Qualitative Study. JMIR Form Res 2024; 8:e53508. [PMID: 39115893 PMCID: PMC11342009 DOI: 10.2196/53508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 02/27/2024] [Accepted: 05/26/2024] [Indexed: 08/10/2024] Open
Abstract
BACKGROUND Perinatal depression affects a significant number of women during pregnancy and after birth, and early identification is imperative for timely interventions and improved prognosis. Mobile apps offer the potential to overcome barriers to health care provision and facilitate clinical research. However, little is known about users' perceptions and acceptability of these apps, particularly digital phenotyping and ecological momentary assessment apps, a relatively novel category of apps and approach to data collection. Understanding user's concerns and the challenges they experience using the app will facilitate adoption and continued engagement. OBJECTIVE This qualitative study explores the experiences and attitudes of users of the Mom2B mobile health (mHealth) research app (Uppsala University) during the perinatal period. In particular, we aimed to determine the acceptability of the app and any concerns about providing data through a mobile app. METHODS Semistructured focus group interviews were conducted digitally in Swedish with 13 groups and a total of 41 participants. Participants had been active users of the Mom2B app for at least 6 weeks and included pregnant and postpartum women, both with and without depression symptomatology apparent in their last screening test. Interviews were recorded, transcribed verbatim, translated to English, and evaluated using inductive thematic analysis. RESULTS Four themes were elicited: acceptability of sharing data, motivators and incentives, barriers to task completion, and user experience. Participants also gave suggestions for the improvement of features and user experience. CONCLUSIONS The study findings suggest that app-based digital phenotyping is a feasible and acceptable method of conducting research and health care delivery among perinatal women. The Mom2B app was perceived as an efficient and practical tool that facilitates engagement in research as well as allows users to monitor their well-being and receive general and personalized information related to the perinatal period. However, this study also highlights the importance of trustworthiness, accessibility, and prompt technical issue resolution in the development of future research apps in cooperation with end users. The study contributes to the growing body of literature on the usability and acceptability of mobile apps for research and ecological momentary assessment and underscores the need for continued research in this area.
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Affiliation(s)
- Ayesha-Mae Bilal
- Department of Medical Sciences, Psychiatry, Uppsala University, Uppsala, Sweden
- Centre for Women's Mental Health During the Reproductive Lifespan (WOMHER), Uppsala University, Uppsala, Sweden
| | - Konstantina Pagoni
- Department of Medical Sciences, Psychiatry, Uppsala University, Uppsala, Sweden
| | - Stavros I Iliadis
- Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden
| | | | - Alkistis Skalkidou
- Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden
| | - Caisa Öster
- Department of Medical Sciences, Psychiatry, Uppsala University, Uppsala, Sweden
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Ortiz A, Mulsant BH. Beyond Step Count: Are We Ready to Use Digital Phenotyping to Make Actionable Individual Predictions in Psychiatry? J Med Internet Res 2024; 26:e59826. [PMID: 39102686 PMCID: PMC11333868 DOI: 10.2196/59826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Revised: 07/09/2024] [Accepted: 07/16/2024] [Indexed: 08/07/2024] Open
Abstract
Some models for mental disorders or behaviors (eg, suicide) have been successfully developed, allowing predictions at the population level. However, current demographic and clinical variables are neither sensitive nor specific enough for making individual actionable clinical predictions. A major hope of the "Decade of the Brain" was that biological measures (biomarkers) would solve these issues and lead to precision psychiatry. However, as models are based on sociodemographic and clinical data, even when these biomarkers differ significantly between groups of patients and control participants, they are still neither sensitive nor specific enough to be applied to individual patients. Technological advances over the past decade offer a promising approach based on new measures that may be essential for understanding mental disorders and predicting their trajectories. Several new tools allow us to continuously monitor objective behavioral measures (eg, hours of sleep) and densely sample subjective measures (eg, mood). The promise of this approach, referred to as digital phenotyping, was recognized almost a decade ago, with its potential impact on psychiatry being compared to the impact of the microscope on biological sciences. However, despite the intuitive belief that collecting densely sampled data (big data) improves clinical outcomes, recent clinical trials have not shown that incorporating digital phenotyping improves clinical outcomes. This viewpoint provides a stepwise development and implementation approach, similar to the one that has been successful in the prediction and prevention of cardiovascular disease, to achieve clinically actionable predictions in psychiatry.
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Affiliation(s)
- Abigail Ortiz
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Benoit H Mulsant
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
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Illner V, Novotný M, Kouba T, Tykalová T, Šimek M, Sovka P, Švihlík J, Růžička E, Šonka K, Dušek P, Rusz J. Smartphone Voice Calls Provide Early Biomarkers of Parkinsonism in Rapid Eye Movement Sleep Behavior Disorder. Mov Disord 2024. [PMID: 39001636 DOI: 10.1002/mds.29921] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 06/03/2024] [Accepted: 06/21/2024] [Indexed: 09/05/2024] Open
Abstract
BACKGROUND Speech dysfunction represents one of the initial motor manifestations to develop in Parkinson's disease (PD) and is measurable through smartphone. OBJECTIVE The aim was to develop a fully automated and noise-resistant smartphone-based system that can unobtrusively screen for prodromal parkinsonian speech disorder in subjects with isolated rapid eye movement sleep behavior disorder (iRBD) in a real-world scenario. METHODS This cross-sectional study assessed regular, everyday voice call data from individuals with iRBD compared to early PD patients and healthy controls via a developed smartphone application. The participants also performed an active, regular reading of a short passage on their smartphone. Smartphone data were continuously collected for up to 3 months after the standard in-person assessments at the clinic. RESULTS A total of 3525 calls that led to 5990 minutes of preprocessed speech were extracted from 72 participants, comprising 21 iRBD patients, 26 PD patients, and 25 controls. With a high area under the curve of 0.85 between iRBD patients and controls, the combination of passive and active smartphone data provided a comparable or even more sensitive evaluation than laboratory examination using a high-quality microphone. The most sensitive features to induce prodromal neurodegeneration in iRBD included imprecise vowel articulation during phone calls (P = 0.03) and monopitch in reading (P = 0.05). Eighteen minutes of speech corresponding to approximately nine calls was sufficient to obtain the best sensitivity for the screening. CONCLUSION We consider the developed tool widely applicable to deep longitudinal digital phenotyping data with future applications in neuroprotective trials, deep brain stimulation optimization, neuropsychiatry, speech therapy, population screening, and beyond. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Vojtěch Illner
- Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Michal Novotný
- Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Tomáš Kouba
- Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Tereza Tykalová
- Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Michal Šimek
- Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Pavel Sovka
- Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Jan Švihlík
- Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
- Department of Computing and Control Engineering, Faculty of Chemical Engineering, University of Chemistry and Technology, Prague, Czech Republic
| | - Evžen Růžička
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Karel Šonka
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Petr Dušek
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Jan Rusz
- Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, Charles University, Prague, Czech Republic
- Department of Neurology and ARTORG Center, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
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Janssen Daalen JM, van den Bergh R, Prins EM, Moghadam MSC, van den Heuvel R, Veen J, Mathur S, Meijerink H, Mirelman A, Darweesh SKL, Evers LJW, Bloem BR. Digital biomarkers for non-motor symptoms in Parkinson's disease: the state of the art. NPJ Digit Med 2024; 7:186. [PMID: 38992186 PMCID: PMC11239921 DOI: 10.1038/s41746-024-01144-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Accepted: 05/22/2024] [Indexed: 07/13/2024] Open
Abstract
Digital biomarkers that remotely monitor symptoms have the potential to revolutionize outcome assessments in future disease-modifying trials in Parkinson's disease (PD), by allowing objective and recurrent measurement of symptoms and signs collected in the participant's own living environment. This biomarker field is developing rapidly for assessing the motor features of PD, but the non-motor domain lags behind. Here, we systematically review and assess digital biomarkers under development for measuring non-motor symptoms of PD. We also consider relevant developments outside the PD field. We focus on technological readiness level and evaluate whether the identified digital non-motor biomarkers have potential for measuring disease progression, covering the spectrum from prodromal to advanced disease stages. Furthermore, we provide perspectives for future deployment of these biomarkers in trials. We found that various wearables show high promise for measuring autonomic function, constipation and sleep characteristics, including REM sleep behavior disorder. Biomarkers for neuropsychiatric symptoms are less well-developed, but show increasing accuracy in non-PD populations. Most biomarkers have not been validated for specific use in PD, and their sensitivity to capture disease progression remains untested for prodromal PD where the need for digital progression biomarkers is greatest. External validation in real-world environments and large longitudinal cohorts remains necessary for integrating non-motor biomarkers into research, and ultimately also into daily clinical practice.
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Affiliation(s)
- Jules M Janssen Daalen
- Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Nijmegen, The Netherlands.
| | - Robin van den Bergh
- Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Nijmegen, The Netherlands
| | - Eva M Prins
- Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Nijmegen, The Netherlands
| | - Mahshid Sadat Chenarani Moghadam
- Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Nijmegen, The Netherlands
| | - Rudie van den Heuvel
- HAN University of Applied Sciences, School of Engineering and Automotive, Health Concept Lab, Arnhem, The Netherlands
| | - Jeroen Veen
- HAN University of Applied Sciences, School of Engineering and Automotive, Health Concept Lab, Arnhem, The Netherlands
| | | | - Hannie Meijerink
- ParkinsonNL, Parkinson Patient Association, Bunnik, The Netherlands
| | - Anat Mirelman
- Tel Aviv University, Sagol School of Neuroscience, Department of Neurology, Faculty of Medicine, Laboratory for Early Markers of Neurodegeneration (LEMON), Center for the Study of Movement, Cognition, and Mobility (CMCM), Tel Aviv, Israel
| | - Sirwan K L Darweesh
- Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Nijmegen, The Netherlands
| | - Luc J W Evers
- Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Nijmegen, The Netherlands
- Radboud University, Institute for Computing and Information Sciences, Nijmegen, The Netherlands
| | - Bastiaan R Bloem
- Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Nijmegen, The Netherlands.
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O’Leary A, Lahey T, Lovato J, Loftness B, Douglas A, Skelton J, Cohen JG, Copeland WE, McGinnis RS, McGinnis EW. Using Wearable Digital Devices to Screen Children for Mental Health Conditions: Ethical Promises and Challenges. SENSORS (BASEL, SWITZERLAND) 2024; 24:3214. [PMID: 38794067 PMCID: PMC11125700 DOI: 10.3390/s24103214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Revised: 05/13/2024] [Accepted: 05/16/2024] [Indexed: 05/26/2024]
Abstract
In response to a burgeoning pediatric mental health epidemic, recent guidelines have instructed pediatricians to regularly screen their patients for mental health disorders with consistency and standardization. Yet, gold-standard screening surveys to evaluate mental health problems in children typically rely solely on reports given by caregivers, who tend to unintentionally under-report, and in some cases over-report, child symptomology. Digital phenotype screening tools (DPSTs), currently being developed in research settings, may help overcome reporting bias by providing objective measures of physiology and behavior to supplement child mental health screening. Prior to their implementation in pediatric practice, however, the ethical dimensions of DPSTs should be explored. Herein, we consider some promises and challenges of DPSTs under three broad categories: accuracy and bias, privacy, and accessibility and implementation. We find that DPSTs have demonstrated accuracy, may eliminate concerns regarding under- and over-reporting, and may be more accessible than gold-standard surveys. However, we also find that if DPSTs are not responsibly developed and deployed, they may be biased, raise privacy concerns, and be cost-prohibitive. To counteract these potential shortcomings, we identify ways to support the responsible and ethical development of DPSTs for clinical practice to improve mental health screening in children.
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Affiliation(s)
- Aisling O’Leary
- Department of Philosophy, Virginia Polytechnic Institute and State University, Blacksburg, VA 24060, USA;
| | - Timothy Lahey
- University of Vermont Medical Center, Burlington, VT 05401, USA; (T.L.); (A.D.)
| | - Juniper Lovato
- Complex Systems Center, University of Vermont, Burlington VT 05405, USA; (J.L.); (B.L.)
| | - Bryn Loftness
- Complex Systems Center, University of Vermont, Burlington VT 05405, USA; (J.L.); (B.L.)
| | - Antranig Douglas
- University of Vermont Medical Center, Burlington, VT 05401, USA; (T.L.); (A.D.)
| | - Joseph Skelton
- Department of Pediatrics, Wake Forest University School of Medicine, Winston-Salem 27101, NC, USA;
- Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem 27101, NC, USA
| | - Jenna G. Cohen
- Department of Electrical and Biomedical Engineering, University of Vermont, Burlington VT 05405, USA;
| | | | - Ryan S. McGinnis
- Department of Biomedical Engineering, Wake Forest University School of Medicine, Winston-Salem 27101, NC, USA
| | - Ellen W. McGinnis
- Department of Pediatrics, Wake Forest University School of Medicine, Winston-Salem 27101, NC, USA;
- Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem 27101, NC, USA
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Pavarini G, Lyreskog DM, Newby D, Lorimer J, Bennett V, Jacobs E, Winchester L, Nevado-Holgado A, Singh I. Tracing Tomorrow: young people's preferences and values related to use of personal sensing to predict mental health, using a digital game methodology. BMJ MENTAL HEALTH 2024; 27:e300897. [PMID: 38508686 PMCID: PMC11021752 DOI: 10.1136/bmjment-2023-300897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Accepted: 11/30/2023] [Indexed: 03/22/2024]
Abstract
BACKGROUND Use of personal sensing to predict mental health risk has sparked interest in adolescent psychiatry, offering a potential tool for targeted early intervention. OBJECTIVES We investigated the preferences and values of UK adolescents with regard to use of digital sensing information, including social media and internet searching behaviour. We also investigated the impact of risk information on adolescents' self-understanding. METHODS Following a Design Bioethics approach, we created and disseminated a purpose-built digital game (www.tracingtomorrow.org) that immersed the player-character in a fictional scenario in which they received a risk assessment for depression Data were collected through game choices across relevant scenarios, with decision-making supported through clickable information points. FINDINGS The game was played by 7337 UK adolescents aged 16-18 years. Most participants were willing to personally communicate mental health risk information to their parents or best friend. The acceptability of school involvement in risk predictions based on digital traces was mixed, due mainly to privacy concerns. Most participants indicated that risk information could negatively impact their academic self-understanding. Participants overwhelmingly preferred individual face-to-face over digital options for support. CONCLUSIONS The potential of digital phenotyping in supporting early intervention in mental health can only be fulfilled if data are collected, communicated and actioned in ways that are trustworthy, relevant and acceptable to young people. CLINICAL IMPLICATIONS To minimise the risk of ethical harms in real-world applications of preventive psychiatric technologies, it is essential to investigate young people's values and preferences as part of design and implementation processes.
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Affiliation(s)
- Gabriela Pavarini
- Ethox Centre, Oxford Population Health, University of Oxford, Oxford, UK
- Wellcome Centre for Ethics and Humanities, University of Oxford, Oxford, UK
| | - David M Lyreskog
- Wellcome Centre for Ethics and Humanities, University of Oxford, Oxford, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Danielle Newby
- Department of Psychiatry, University of Oxford, Oxford, UK
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Jessica Lorimer
- Wellcome Centre for Ethics and Humanities, University of Oxford, Oxford, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
| | | | - Edward Jacobs
- Wellcome Centre for Ethics and Humanities, University of Oxford, Oxford, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
| | | | | | - Ilina Singh
- Wellcome Centre for Ethics and Humanities, University of Oxford, Oxford, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
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11
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Fuhr DC, Wolf-Ostermann K, Hoel V, Zeeb H. [Digital technologies to improve mental health]. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2024; 67:332-338. [PMID: 38294700 DOI: 10.1007/s00103-024-03842-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 01/26/2024] [Indexed: 02/01/2024]
Abstract
The burden of mental diseases is enormous and constantly growing worldwide. The resulting increase in demand for psychosocial help is also having a negative impact on waiting times for psychotherapy in Germany. Digital interventions for mental health, such as interventions delivered through or with the help of a website (e.g. "telehealth"), smartphone, or tablet app-based interventions and interventions that use text messages or virtual reality, can help. This article begins with an overview of the functions and range of applications of digital technologies for mental health. The evidence for individual digital forms of interventions is addressed. Overall, it is shown that digital interventions for mental health are likely to be cost-effective compared to no therapy or a non-therapeutic control group. Newer approaches such as "digital phenotyping" are explained in the article. Finally, individual papers from the "Leibniz ScienceCampus Digital Public Health" are presented, and limitations and challenges of technologies for mental health are discussed.
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Affiliation(s)
- Daniela C Fuhr
- Abteilung für Evaluation und Prävention, Leibniz Institut für Präventionsforschung und Epidemiologie, Achterstr. 30, 28359, Bremen, Deutschland.
- Gesundheitswissenschaften, Universität Bremen, Bremen, Deutschland.
| | - Karin Wolf-Ostermann
- Institut für Public Health und Pflegeforschung, Universität Bremen, Bremen, Deutschland
| | - Viktoria Hoel
- Institut für Public Health und Pflegeforschung, Universität Bremen, Bremen, Deutschland
| | - Hajo Zeeb
- Abteilung für Evaluation und Prävention, Leibniz Institut für Präventionsforschung und Epidemiologie, Achterstr. 30, 28359, Bremen, Deutschland
- Gesundheitswissenschaften, Universität Bremen, Bremen, Deutschland
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12
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Hurley ME, Sonig A, Herrington J, Storch EA, Lázaro-Muñoz G, Blumenthal-Barby J, Kostick-Quenet K. Ethical considerations for integrating multimodal computer perception and neurotechnology. Front Hum Neurosci 2024; 18:1332451. [PMID: 38435745 PMCID: PMC10904467 DOI: 10.3389/fnhum.2024.1332451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 01/30/2024] [Indexed: 03/05/2024] Open
Abstract
Background Artificial intelligence (AI)-based computer perception technologies (e.g., digital phenotyping and affective computing) promise to transform clinical approaches to personalized care in psychiatry and beyond by offering more objective measures of emotional states and behavior, enabling precision treatment, diagnosis, and symptom monitoring. At the same time, passive and continuous nature by which they often collect data from patients in non-clinical settings raises ethical issues related to privacy and self-determination. Little is known about how such concerns may be exacerbated by the integration of neural data, as parallel advances in computer perception, AI, and neurotechnology enable new insights into subjective states. Here, we present findings from a multi-site NCATS-funded study of ethical considerations for translating computer perception into clinical care and contextualize them within the neuroethics and neurorights literatures. Methods We conducted qualitative interviews with patients (n = 20), caregivers (n = 20), clinicians (n = 12), developers (n = 12), and clinician developers (n = 2) regarding their perspective toward using PC in clinical care. Transcripts were analyzed in MAXQDA using Thematic Content Analysis. Results Stakeholder groups voiced concerns related to (1) perceived invasiveness of passive and continuous data collection in private settings; (2) data protection and security and the potential for negative downstream/future impacts on patients of unintended disclosure; and (3) ethical issues related to patients' limited versus hyper awareness of passive and continuous data collection and monitoring. Clinicians and developers highlighted that these concerns may be exacerbated by the integration of neural data with other computer perception data. Discussion Our findings suggest that the integration of neurotechnologies with existing computer perception technologies raises novel concerns around dignity-related and other harms (e.g., stigma, discrimination) that stem from data security threats and the growing potential for reidentification of sensitive data. Further, our findings suggest that patients' awareness and preoccupation with feeling monitored via computer sensors ranges from hypo- to hyper-awareness, with either extreme accompanied by ethical concerns (consent vs. anxiety and preoccupation). These results highlight the need for systematic research into how best to implement these technologies into clinical care in ways that reduce disruption, maximize patient benefits, and mitigate long-term risks associated with the passive collection of sensitive emotional, behavioral and neural data.
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Affiliation(s)
- Meghan E. Hurley
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, United States
| | - Anika Sonig
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, United States
| | - John Herrington
- Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
| | - Eric A. Storch
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, United States
| | - Gabriel Lázaro-Muñoz
- Center for Bioethics, Harvard Medical School, Boston, MA, United States
- Department of Psychiatry and Behavioral Sciences, Massachusetts General Hospital, Boston, MA, United States
| | | | - Kristin Kostick-Quenet
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, United States
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13
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Shen FX, Baum ML, Martinez-Martin N, Miner AS, Abraham M, Brownstein CA, Cortez N, Evans BJ, Germine LT, Glahn DC, Grady C, Holm IA, Hurley EA, Kimble S, Lázaro-Muñoz G, Leary K, Marks M, Monette PJ, Jukka-Pekka O, O’Rourke PP, Rauch SL, Shachar C, Sen S, Vahia I, Vassy JL, Baker JT, Bierer BE, Silverman BC. Returning Individual Research Results from Digital Phenotyping in Psychiatry. THE AMERICAN JOURNAL OF BIOETHICS : AJOB 2024; 24:69-90. [PMID: 37155651 PMCID: PMC10630534 DOI: 10.1080/15265161.2023.2180109] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Psychiatry is rapidly adopting digital phenotyping and artificial intelligence/machine learning tools to study mental illness based on tracking participants' locations, online activity, phone and text message usage, heart rate, sleep, physical activity, and more. Existing ethical frameworks for return of individual research results (IRRs) are inadequate to guide researchers for when, if, and how to return this unprecedented number of potentially sensitive results about each participant's real-world behavior. To address this gap, we convened an interdisciplinary expert working group, supported by a National Institute of Mental Health grant. Building on established guidelines and the emerging norm of returning results in participant-centered research, we present a novel framework specific to the ethical, legal, and social implications of returning IRRs in digital phenotyping research. Our framework offers researchers, clinicians, and Institutional Review Boards (IRBs) urgently needed guidance, and the principles developed here in the context of psychiatry will be readily adaptable to other therapeutic areas.
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Affiliation(s)
- Francis X. Shen
- Harvard Medical School
- Massachusetts General Hospital
- Harvard Law School
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Mason Marks
- Harvard Law School
- Florida State University College of Law
- Yale Law School
| | | | | | | | - Scott L. Rauch
- Harvard Medical School
- McLean Hospital
- Mass General Brigham
| | | | | | | | - Jason L. Vassy
- Harvard Medical School
- Brigham and Women’s Hospital
- VA Boston Healthcare System
| | | | - Barbara E. Bierer
- Harvard Medical School
- Brigham and Women’s Hospital
- Multi-Regional Clinical Trials Center of Brigham and Women’s Hospital and Harvard
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14
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Nagappan A, Kalokairinou L, Wexler A. Ethical issues in direct-to-consumer healthcare: A scoping review. PLOS DIGITAL HEALTH 2024; 3:e0000452. [PMID: 38349902 PMCID: PMC10863864 DOI: 10.1371/journal.pdig.0000452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 01/18/2024] [Indexed: 02/15/2024]
Abstract
An increasing number of health products and services are being offered on a direct-to-consumer (DTC) basis. To date, however, scholarship on DTC healthcare products and services has largely proceeded in a domain-specific fashion, with discussions of relevant ethical challenges occurring within specific medical specialties. The present study therefore aimed to provide a scoping review of ethical issues raised in the academic literature across types of DTC healthcare products and services. A systematic search for relevant publications between 2011-2021 was conducted on PubMed and Google Scholar using iteratively developed search terms. The final sample included 86 publications that discussed ethical issues related to DTC healthcare products and services. All publications were coded for ethical issues mentioned, primary DTC product or service discussed, type of study, year of publication, and geographical context. We found that the types of DTC healthcare products and services mentioned in our sample spanned six categories: neurotechnology (34%), testing (20%), in-person services (17%), digital health tools (14%), telemedicine (13%), and physical interventions (2%). Ethical arguments in favor of DTC healthcare included improved access (e.g., financial, geographical; 31%), increased autonomy (29%), and enhanced convenience (16%). Commonly raised ethical concerns included insufficient regulation (72%), questionable efficacy and quality (70%), safety and physical harms (66%), misleading advertising claims (56%), and privacy (34%). Other frequently occurring ethical concerns pertained to financial costs, targeting vulnerable groups, informed consent, and potential burdens on healthcare providers, the healthcare system, and society. Our findings offer insights into the cross-cutting ethical issues associated with DTC healthcare and underscore the need for increased interdisciplinary communication to address the challenges they raise.
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Affiliation(s)
- Ashwini Nagappan
- Department of Health Policy and Management, University of California, Los Angeles, Los Angeles, California, United States of America
- Department of Medical Ethics and Health Policy, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Louiza Kalokairinou
- Department of Medical Ethics and Health Policy, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, Texas, United States of America
| | - Anna Wexler
- Department of Medical Ethics and Health Policy, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
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15
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Barrette-Moran J, Dupras C. Contending with Real and Perceived Intrusiveness in Digital Phenotyping Research. THE AMERICAN JOURNAL OF BIOETHICS : AJOB 2024; 24:108-110. [PMID: 38295258 DOI: 10.1080/15265161.2023.2296421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/02/2024]
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16
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Erickson CM, Wexler A, Largent EA. Alzheimer's in the modern age: Ethical challenges in the use of digital monitoring to identify cognitive changes. Inform Health Soc Care 2024; 49:1-13. [PMID: 38116960 PMCID: PMC11001527 DOI: 10.1080/17538157.2023.2294203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
Pushes toward earlier detection of Alzheimer's disease (AD)-related cognitive changes are creating interest in leveraging technologies, like cellphones, that are already widespread and well-equipped for data collection to facilitate digital monitoring for AD. Studies are ongoing to identify and validate potential "digital biomarkers" that might indicate someone has or is at risk of developing AD dementia. Digital biomarkers for AD have potential as a tool in aiding more timely diagnosis, though more robust research is needed to support their validity and utility. While there are grounds for optimism, leveraging digital monitoring and informatics for cognitive changes also poses ethical challenges, related to topics such as algorithmic bias, consent, and data privacy and security. As we confront the modern era of Alzheimer's disease, individuals, companies, regulators and policymakers alike must prepare for a future in which our day-to-day interactions with technology in our daily life may identify AD-related cognitive changes.
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Affiliation(s)
- Claire M Erickson
- Department of Medical Ethics and Health Policy, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Anna Wexler
- Department of Medical Ethics and Health Policy, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Emily A Largent
- Department of Medical Ethics and Health Policy, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
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17
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Fedor S, Lewis R, Pedrelli P, Mischoulon D, Curtiss J, Picard RW. Wearable Technology in Clinical Practice for Depressive Disorder. N Engl J Med 2023; 389:2457-2466. [PMID: 38157501 DOI: 10.1056/nejmra2215898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/03/2024]
Affiliation(s)
- Szymon Fedor
- From the MIT Media Lab, Massachusetts Institute of Technology, Cambridge (S.F., R.L., R.W.P.), and the Depression Clinical and Research Program, Massachusetts General Hospital (P.P., D.M., J.C.), and the Applied Psychology Department, Northeastern University (J.C.), Boston - all in Massachusetts
| | - Robert Lewis
- From the MIT Media Lab, Massachusetts Institute of Technology, Cambridge (S.F., R.L., R.W.P.), and the Depression Clinical and Research Program, Massachusetts General Hospital (P.P., D.M., J.C.), and the Applied Psychology Department, Northeastern University (J.C.), Boston - all in Massachusetts
| | - Paola Pedrelli
- From the MIT Media Lab, Massachusetts Institute of Technology, Cambridge (S.F., R.L., R.W.P.), and the Depression Clinical and Research Program, Massachusetts General Hospital (P.P., D.M., J.C.), and the Applied Psychology Department, Northeastern University (J.C.), Boston - all in Massachusetts
| | - David Mischoulon
- From the MIT Media Lab, Massachusetts Institute of Technology, Cambridge (S.F., R.L., R.W.P.), and the Depression Clinical and Research Program, Massachusetts General Hospital (P.P., D.M., J.C.), and the Applied Psychology Department, Northeastern University (J.C.), Boston - all in Massachusetts
| | - Joshua Curtiss
- From the MIT Media Lab, Massachusetts Institute of Technology, Cambridge (S.F., R.L., R.W.P.), and the Depression Clinical and Research Program, Massachusetts General Hospital (P.P., D.M., J.C.), and the Applied Psychology Department, Northeastern University (J.C.), Boston - all in Massachusetts
| | - Rosalind W Picard
- From the MIT Media Lab, Massachusetts Institute of Technology, Cambridge (S.F., R.L., R.W.P.), and the Depression Clinical and Research Program, Massachusetts General Hospital (P.P., D.M., J.C.), and the Applied Psychology Department, Northeastern University (J.C.), Boston - all in Massachusetts
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18
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Nourse R, Dingler T, Kelly J, Kwasnicka D, Maddison R. The Role of a Smart Health Ecosystem in Transforming the Management of Chronic Health Conditions. J Med Internet Res 2023; 25:e44265. [PMID: 38109188 PMCID: PMC10758944 DOI: 10.2196/44265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 06/07/2023] [Accepted: 06/29/2023] [Indexed: 12/19/2023] Open
Abstract
The effective management of chronic conditions requires an approach that promotes a shift in care from the clinic to the home, improves the efficiency of health care systems, and benefits all users irrespective of their needs and preferences. Digital health can provide a solution to this challenge, and in this paper, we provide our vision for a smart health ecosystem. A smart health ecosystem leverages the interoperability of digital health technologies and advancements in big data and artificial intelligence for data collection and analysis and the provision of support. We envisage that this approach will allow a comprehensive picture of health, personalization, and tailoring of behavioral and clinical support; drive theoretical advancements; and empower people to manage their own health with support from health care professionals. We illustrate the concept with 2 use cases and discuss topics for further consideration and research, concluding with a message to encourage people with chronic conditions, their caregivers, health care professionals, policy and decision makers, and technology experts to join their efforts and work toward adopting a smart health ecosystem.
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Affiliation(s)
- Rebecca Nourse
- School of Exercise and Nutrition Sciences, Deakin University, Burwood, Australia
| | - Tilman Dingler
- School of Computing and Information Systems, University of Melbourne, Melbourne, Australia
| | - Jaimon Kelly
- Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia
| | - Dominika Kwasnicka
- NHMRC CRE in Digital Technology to Transform Chronic Disease Outcomes, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia
- Faculty of Psychology, SWPS University of Social Sciences and Humanities, Wroclaw, Poland
| | - Ralph Maddison
- School of Exercise and Nutrition Sciences, Deakin University, Burwood, Australia
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Slack SK, Barclay L. First-person disavowals of digital phenotyping and epistemic injustice in psychiatry. MEDICINE, HEALTH CARE, AND PHILOSOPHY 2023; 26:605-614. [PMID: 37725254 PMCID: PMC10725846 DOI: 10.1007/s11019-023-10174-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 08/16/2023] [Indexed: 09/21/2023]
Abstract
Digital phenotyping will potentially enable earlier detection and prediction of mental illness by monitoring human interaction with and through digital devices. Notwithstanding its promises, it is certain that a person's digital phenotype will at times be at odds with their first-person testimony of their psychological states. In this paper, we argue that there are features of digital phenotyping in the context of psychiatry which have the potential to exacerbate the tendency to dismiss patients' testimony and treatment preferences, which can be instances of epistemic injustice. We first explain what epistemic injustice is, and why it is argued to be an extensive problem in health and disability settings. We then explain why epistemic injustice is more likely to apply with even greater force in psychiatric contexts, and especially where digital phenotyping may be involved. Finally, we offer some tentative suggestions of how epistemic injustice can be minimised in digital psychiatry.
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Affiliation(s)
- Stephanie K Slack
- Philosophy, School of Philosophical, Historical and International Studies, Monash University, Clayton, VIC, 3800, Australia.
| | - Linda Barclay
- Philosophy, School of Philosophical, Historical and International Studies, Monash University, Clayton, VIC, 3800, Australia
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20
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Mathews D, Abernethy A, Butte AJ, Enriquez J, Kocher B, Lisanby SH, Persons TM, Fabi R, Offodile AC, Sherkow JS, Sullenger RD, Freiling E, Balatbat C. Neurotechnology and Noninvasive Neuromodulation: Case Study for Understanding and Anticipating Emerging Science and Technology. NAM Perspect 2023; 2023:202311c. [PMID: 38812840 PMCID: PMC11136498 DOI: 10.31478/202311c] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2024]
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21
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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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22
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Mayer G, Zafar A, Hummel S, Landau F, Schultz JH. Individualisation, personalisation and person-centredness in mental healthcare: a scoping review of concepts and linguistic network visualisation. BMJ MENTAL HEALTH 2023; 26:e300831. [PMID: 37844963 PMCID: PMC10583082 DOI: 10.1136/bmjment-2023-300831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 09/13/2023] [Indexed: 10/18/2023]
Abstract
BACKGROUND Targeted mental health interventions are increasingly described as individualised, personalised or person-centred approaches. However, the definitions for these terms vary significantly. Their interchangeable use prevents operationalisations and measures. OBJECTIVE This scoping review provides a synthesis of key concepts, definitions and the language used in the context of these terms in an effort to delineate their use for future research. STUDY SELECTION AND ANALYSIS Our search on PubMed, EBSCO and Cochrane provided 2835 relevant titles. A total of 176 titles were found eligible for extracting data. A thematic analysis was conducted to synthesise the underlying aspects of individualisation, personalisation and person-centredness. Network visualisations of co-occurring words in 2625 abstracts were performed using VOSViewer. FINDINGS Overall, 106 out of 176 (60.2%) articles provided concepts for individualisation, personalisation and person-centredness. Studies using person-centredness provided a conceptualisation more often than the others. A thematic analysis revealed medical, psychological, sociocultural, biological, behavioural, economic and environmental dimensions of the concepts. Practical frameworks were mostly found related to person-centredness, while theoretical frameworks emerged in studies on personalisation. Word co-occurrences showed common psychiatric words in all three network visualisations, but differences in further contexts. CONCLUSIONS AND CLINICAL IMPLICATIONS The use of individualisation, personalisation and person-centredness in mental healthcare is multifaceted. While individualisation was the most generic term, personalisation was often used in biomedical or technological studies. Person-centredness emerged as the most well-defined concept, with many frameworks often related to dementia care. We recommend that the use of these terms follows a clear definition within the context of their respective disorders, treatments or medical settings. SCOPING REVIEW REGISTRATION Open Science Framework: osf.io/uatsc.
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Affiliation(s)
- Gwendolyn Mayer
- Department of General Internal Medicine and Psychosomatics, Heidelberg University Hospital Psychosocial Medicine Center, Heidelberg, Germany
| | - Ali Zafar
- Department of General Internal Medicine and Psychosomatics, Heidelberg University Hospital Psychosocial Medicine Center, Heidelberg, Germany
- Heidelberg Academy of Sciences and Humanities, Heidelberg, Germany
| | - Svenja Hummel
- Department of General Internal Medicine and Psychosomatics, Heidelberg University Hospital Psychosocial Medicine Center, Heidelberg, Germany
| | - Felix Landau
- Department of General Internal Medicine and Psychosomatics, Heidelberg University Hospital Psychosocial Medicine Center, Heidelberg, Germany
| | - Jobst-Hendrik Schultz
- Department of General Internal Medicine and Psychosomatics, Heidelberg University Hospital Psychosocial Medicine Center, Heidelberg, Germany
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23
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Stange JP, Li J, Xu EP, Ye Z, Zapetis SL, Phanord CS, Wu J, Sellery P, Keefe K, Forbes E, Mermelstein RJ, Trull TJ, Langenecker SA. Autonomic complexity dynamically indexes affect regulation in everyday life. JOURNAL OF PSYCHOPATHOLOGY AND CLINICAL SCIENCE 2023; 132:847-866. [PMID: 37410429 PMCID: PMC10592626 DOI: 10.1037/abn0000849] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/07/2023]
Abstract
Affect regulation often is disrupted in depression. Understanding biomarkers of affect regulation in ecologically valid contexts is critical for identifying moments when interventions can be delivered to improve regulation and may have utility for identifying which individuals are vulnerable to psychopathology. Autonomic complexity, which includes linear and nonlinear indices of heart rate variability, has been proposed as a novel marker of neurovisceral integration. However, it is not clear how autonomic complexity tracks with regulation in everyday life, and whether low complexity serves as a marker of related psychopathology. To measure regulation phenotypes with diminished influence of current symptoms, 37 young adults with remitted major depressive disorder (rMDD) and 28 healthy comparisons (HCs) completed ambulatory assessments of autonomic complexity and affect regulation across one week in everyday life. Multilevel models indicated that in HCs, but not rMDD, autonomic complexity fluctuated in response to regulation cues, increasing in response to reappraisal and distraction and decreasing in response to negative affect. Higher complexity across the week predicted greater everyday regulation success, whereas greater variability of complexity predicted lower (and less variable) negative affect, rumination, and mind-wandering. Results suggest that ambulatory assessment of autonomic complexity can passively index dynamic aspects of real-world affect and regulation, and that dynamic physiological reactivity to regulation is restricted in rMDD. These results demonstrate how intensive sampling of dynamic, nonlinear regulatory processes can advance our understanding of potential mechanisms underlying psychopathology. Such measurements might inform how to test interventions to enhance neurovisceral complexity and affect regulation success in real time. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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Affiliation(s)
- Jonathan P. Stange
- Department of Psychology, University of Southern California
- Department of Psychiatry and Behavioral Sciences, University of Southern California
| | - Jiani Li
- Department of Psychology, University of Southern California
| | - Ellie P. Xu
- Department of Psychology, University of Southern California
| | - Zihua Ye
- Department of Psychology, University of Illinois at Urbana-Champaign
| | | | | | - Jenny Wu
- Department of Psychology, University of Massachusetts Boston
| | - Pia Sellery
- Department of Psychology, University of Colorado at Boulder
| | - Kaley Keefe
- Department of Psychology, University of Southern California
| | - Erika Forbes
- Department of Psychiatry, University of Pittsburgh
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Aschbacher K, Rivera LM, Hornstein S, Nelson BW, Forman-Hoffman VL, Peiper NC. Longitudinal Patterns of Engagement and Clinical Outcomes: Results From a Therapist-Supported Digital Mental Health Intervention. Psychosom Med 2023; 85:651-658. [PMID: 37409793 DOI: 10.1097/psy.0000000000001230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/07/2023]
Abstract
OBJECTIVE Digital mental health interventions (DMHIs) are an effective treatment modality for common mental disorders like depression and anxiety; however, the role of intervention engagement as a longitudinal "dosing" factor is poorly understood in relation to clinical outcomes. METHODS We studied 4978 participants in a 12-week therapist-supported DMHI (June 2020-December 2021), applying a longitudinal agglomerative hierarchical cluster analysis to the number of days per week of intervention engagement. The proportion of people demonstrating remission in depression and anxiety symptoms during the intervention was calculated for each cluster. Multivariable logistic regression models were fit to examine associations between the engagement clusters and symptom remission, adjusting for demographic and clinical characteristics. RESULTS Based on clinical interpretability and stopping rules, four clusters were derived from the hierarchical cluster analysis (in descending order): a) sustained high engagers (45.0%), b) late disengagers (24.1%), c) early disengagers (22.5%), and d) immediate disengagers (8.4%). Bivariate and multivariate analyses supported a dose-response relationship between engagement and depression symptom remission, whereas the pattern was partially evident for anxiety symptom remission. In multivariable logistic regression models, older age groups, male participants, and Asians had increased odds of achieving depression and anxiety symptom remission, whereas higher odds of anxiety symptom remission were observed among gender-expansive individuals. CONCLUSIONS Segmentation based on the frequency of engagement performs well in discerning timing of intervention disengagement and a dose-response relationship with clinical outcomes. The findings among the demographic subpopulations indicate that therapist-supported DMHIs may be effective in addressing mental health problems among patients who disproportionately experience stigma and structural barriers to care. Machine learning models can enable precision care by delineating how heterogeneous patterns of engagement over time relate to clinical outcomes. This empirical identification may help clinicians personalize and optimize interventions to prevent premature disengagement.
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Affiliation(s)
- Kirstin Aschbacher
- From Meru Health (Aschbacher, Rivera, Nelson, Forman-Hoffman, Peiper), San Mateo, California; Department of Anthropology (Rivera), Emory University, Atlanta, Georgia; Department of Psychology (Hornstein), Humboldt-Universität zu Berlin, Berlin, Germany; Department of Psychology and Neuroscience (Nelson), University of North Carolina Chapel Hill, Chapel Hill, North Carolina; Department of Epidemiology (Forman-Hoffman), The University of Iowa, Iowa City, Iowa; and Department of Epidemiology and Population Health (Peiper), University of Louisville, Louisville, Kentucky
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Alfalahi H, Dias SB, Khandoker AH, Chaudhuri KR, Hadjileontiadis LJ. A scoping review of neurodegenerative manifestations in explainable digital phenotyping. NPJ Parkinsons Dis 2023; 9:49. [PMID: 36997573 PMCID: PMC10063633 DOI: 10.1038/s41531-023-00494-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 03/16/2023] [Indexed: 04/03/2023] Open
Abstract
Neurologists nowadays no longer view neurodegenerative diseases, like Parkinson's and Alzheimer's disease, as single entities, but rather as a spectrum of multifaceted symptoms with heterogeneous progression courses and treatment responses. The definition of the naturalistic behavioral repertoire of early neurodegenerative manifestations is still elusive, impeding early diagnosis and intervention. Central to this view is the role of artificial intelligence (AI) in reinforcing the depth of phenotypic information, thereby supporting the paradigm shift to precision medicine and personalized healthcare. This suggestion advocates the definition of disease subtypes in a new biomarker-supported nosology framework, yet without empirical consensus on standardization, reliability and interpretability. Although the well-defined neurodegenerative processes, linked to a triad of motor and non-motor preclinical symptoms, are detected by clinical intuition, we undertake an unbiased data-driven approach to identify different patterns of neuropathology distribution based on the naturalistic behavior data inherent to populations in-the-wild. We appraise the role of remote technologies in the definition of digital phenotyping specific to brain-, body- and social-level neurodegenerative subtle symptoms, emphasizing inter- and intra-patient variability powered by deep learning. As such, the present review endeavors to exploit digital technologies and AI to create disease-specific phenotypic explanations, facilitating the understanding of neurodegenerative diseases as "bio-psycho-social" conditions. Not only does this translational effort within explainable digital phenotyping foster the understanding of disease-induced traits, but it also enhances diagnostic and, eventually, treatment personalization.
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Affiliation(s)
- Hessa Alfalahi
- Department of Biomedical Engineering, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates.
- Healthcare Engineering Innovation Center (HEIC), Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates.
| | - Sofia B Dias
- Department of Biomedical Engineering, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
- Healthcare Engineering Innovation Center (HEIC), Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
- CIPER, Faculdade de Motricidade Humana, University of Lisbon, Lisbon, Portugal
| | - Ahsan H Khandoker
- Department of Biomedical Engineering, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
- Healthcare Engineering Innovation Center (HEIC), Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
| | - Kallol Ray Chaudhuri
- Parkinson Foundation, International Center of Excellence, King's College London, Denmark Hills, London, UK
- Department of Basic and Clinical Neurosciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Leontios J Hadjileontiadis
- Department of Biomedical Engineering, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
- Healthcare Engineering Innovation Center (HEIC), Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
- Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece
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Khati A, Wickersham JA, Rosen AO, Luces JRB, Copenhaver N, Jeri-Wahrhaftig A, Ab Halim MA, Azwa I, Gautam K, Ooi KH, Shrestha R. Ethical Issues in the Use of Smartphone Apps for HIV Prevention in Malaysia: Focus Group Study With Men Who Have Sex With Men. JMIR Form Res 2022; 6:e42939. [PMID: 36563046 PMCID: PMC9823573 DOI: 10.2196/42939] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Revised: 11/19/2022] [Accepted: 11/28/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND The use of smartphone apps can improve the HIV prevention cascade for key populations such as men who have sex with men (MSM). In Malaysia, where stigma and discrimination toward MSM are high, mobile health app-based strategies have the potential to open new frontiers for HIV prevention. However, little guidance is available to inform researchers about the ethical concerns that are unique to the development and implementation of app-based HIV prevention programs. OBJECTIVE This study aimed to fill this gap by characterizing the attitudes and concerns of Malaysian MSM regarding HIV prevention mobile apps, particularly regarding the ethical aspects surrounding their use. METHODS We conducted web-based focus group discussions with 23 MSM between August and September 2021. Using in-depth semistructured interviews, participants were asked about the risks and ethical issues they perceived to be associated with using mobile apps for HIV prevention. Each session was digitally recorded and transcribed. Transcripts were inductively coded using the Dedoose software (SocioCultural Research Consultants) and analyzed to identify and interpret emerging themes. RESULTS Although participants were highly willing to use app-based strategies for HIV prevention, they raised several ethical concerns related to their use. Prominent concerns raised by participants included privacy and confidentiality concerns, including fear of third-party access to personal health information (eg, friends or family and government agencies), issues around personal health data storage and management, equity and equitable access, informed consent, and regulation. CONCLUSIONS The study's findings highlight the role of ethical concerns related to the use of app-based HIV prevention programs. Given the ever-growing nature of such technological platforms that are intermixed with a complex ethical-legal landscape, mobile health platforms must be safe and secure to minimize unintended harm, safeguard user privacy and confidentiality, and obtain public trust and uptake.
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Affiliation(s)
- Antoine Khati
- Department of Allied Health Sciences, University of Connecticut, Storrs, CT, United States
| | | | - Aviana O Rosen
- Department of Allied Health Sciences, University of Connecticut, Storrs, CT, United States
| | | | - Nicholas Copenhaver
- Department of Allied Health Sciences, University of Connecticut, Storrs, CT, United States
| | - Alma Jeri-Wahrhaftig
- Department of Allied Health Sciences, University of Connecticut, Storrs, CT, United States
| | - Mohd Akbar Ab Halim
- Centre of Excellence for Research in AIDS (CERiA), University of Malaya, Kuala Lumpur, Malaysia
| | - Iskandar Azwa
- Centre of Excellence for Research in AIDS (CERiA), University of Malaya, Kuala Lumpur, Malaysia
| | - Kamal Gautam
- Department of Allied Health Sciences, University of Connecticut, Storrs, CT, United States
| | - Kai Hong Ooi
- Centre of Excellence for Research in AIDS (CERiA), University of Malaya, Kuala Lumpur, Malaysia
| | - Roman Shrestha
- Department of Allied Health Sciences, University of Connecticut, Storrs, CT, United States
- AIDS Program, Yale School of Medicine, New Haven, CT, United States
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Potier R. Revue critique sur le potentiel du numérique dans la recherche en psychopathologie : un point de vue psychanalytique. L'ÉVOLUTION PSYCHIATRIQUE 2022. [DOI: 10.1016/j.evopsy.2022.09.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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Dlima SD, Shevade S, Menezes SR, Ganju A. Digital Phenotyping in Health Using Machine Learning Approaches: Scoping Review. JMIR BIOINFORMATICS AND BIOTECHNOLOGY 2022; 3:e39618. [PMID: 38935947 PMCID: PMC11135220 DOI: 10.2196/39618] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 07/01/2022] [Accepted: 07/04/2022] [Indexed: 06/29/2024]
Abstract
BACKGROUND Digital phenotyping is the real-time collection of individual-level active and passive data from users in naturalistic and free-living settings via personal digital devices, such as mobile phones and wearable devices. Given the novelty of research in this field, there is heterogeneity in the clinical use cases, types of data collected, modes of data collection, data analysis methods, and outcomes measured. OBJECTIVE The primary aim of this scoping review was to map the published research on digital phenotyping and to outline study characteristics, data collection and analysis methods, machine learning approaches, and future implications. METHODS We utilized an a priori approach for the literature search and data extraction and charting process, guided by the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-analyses Extension for Scoping Reviews). We identified relevant studies published in 2020, 2021, and 2022 on PubMed and Google Scholar using search terms related to digital phenotyping. The titles, abstracts, and keywords were screened during the first stage of the screening process, and the second stage involved screening the full texts of the shortlisted articles. We extracted and charted the descriptive characteristics of the final studies, which were countries of origin, study design, clinical areas, active and/or passive data collected, modes of data collection, data analysis approaches, and limitations. RESULTS A total of 454 articles on PubMed and Google Scholar were identified through search terms associated with digital phenotyping, and 46 articles were deemed eligible for inclusion in this scoping review. Most studies evaluated wearable data and originated from North America. The most dominant study design was observational, followed by randomized trials, and most studies focused on psychiatric disorders, mental health disorders, and neurological diseases. A total of 7 studies used machine learning approaches for data analysis, with random forest, logistic regression, and support vector machines being the most common. CONCLUSIONS Our review provides foundational as well as application-oriented approaches toward digital phenotyping in health. Future work should focus on more prospective, longitudinal studies that include larger data sets from diverse populations, address privacy and ethical concerns around data collection from consumer technologies, and build "digital phenotypes" to personalize digital health interventions and treatment plans.
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Martinez-Martin N. Envisioning a Path toward Equitable and Effective Digital Mental Health. AJOB Neurosci 2022; 13:196-198. [PMID: 35797130 PMCID: PMC9295896 DOI: 10.1080/21507740.2022.2082597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
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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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Miller ML, Raugh IM, Strauss GP, Harvey PD. Remote digital phenotyping in serious mental illness: Focus on negative symptoms, mood symptoms, and self-awareness. Biomark Neuropsychiatry 2022. [DOI: 10.1016/j.bionps.2022.100047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
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Shen FX, Silverman BC, Monette P, Kimble S, Rauch SL, Baker JT. An Ethics Checklist for Digital Health Research in Psychiatry: Viewpoint. J Med Internet Res 2022; 24:e31146. [PMID: 35138261 PMCID: PMC8867294 DOI: 10.2196/31146] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 08/23/2021] [Accepted: 10/29/2021] [Indexed: 01/23/2023] Open
Abstract
BACKGROUND Psychiatry has long needed a better and more scalable way to capture the dynamics of behavior and its disturbances, quantitatively across multiple data channels, at high temporal resolution in real time. By combining 24/7 data-on location, movement, email and text communications, and social media-with brain scans, genetics, genomics, neuropsychological batteries, and clinical interviews, researchers will have an unprecedented amount of objective, individual-level data. Analyzing these data with ever-evolving artificial intelligence could one day include bringing interventions to patients where they are in the real world in a convenient, efficient, effective, and timely way. Yet, the road to this innovative future is fraught with ethical dilemmas as well as ethical, legal, and social implications (ELSI). OBJECTIVE The goal of the Ethics Checklist is to promote careful design and execution of research. It is not meant to mandate particular research designs; indeed, at this early stage and without consensus guidance, there are a range of reasonable choices researchers may make. However, the checklist is meant to make those ethical choices explicit, and to require researchers to give reasons for their decisions related to ELSI issues. The Ethics Checklist is primarily focused on procedural safeguards, such as consulting with experts outside the research group and documenting standard operating procedures for clearly actionable data (eg, expressed suicidality) within written research protocols. METHODS We explored the ELSI of digital health research in psychiatry, with a particular focus on what we label "deep phenotyping" psychiatric research, which combines the potential for virtually boundless data collection and increasingly sophisticated techniques to analyze those data. We convened an interdisciplinary expert stakeholder workshop in May 2020, and this checklist emerges out of that dialogue. RESULTS Consistent with recent ELSI analyses, we find that existing ethical guidance and legal regulations are not sufficient for deep phenotyping research in psychiatry. At present, there are regulatory gaps, inconsistencies across research teams in ethics protocols, and a lack of consensus among institutional review boards on when and how deep phenotyping research should proceed. We thus developed a new instrument, an Ethics Checklist for Digital Health Research in Psychiatry ("the Ethics Checklist"). The Ethics Checklist is composed of 20 key questions, subdivided into 6 interrelated domains: (1) informed consent; (2) equity, diversity, and access; (3) privacy and partnerships; (4) regulation and law; (5) return of results; and (6) duty to warn and duty to report. CONCLUSIONS Deep phenotyping research offers a vision for vastly more effective care for people with, or at risk for, psychiatric disease. The potential perils en route to realizing this vision are significant; however, and researchers must be willing to address the questions in the Ethics Checklist before embarking on each leg of the journey.
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Affiliation(s)
- Francis X Shen
- Harvard Medical School, Boston, MA, United States
- Law School, University of Minnesota, Minneapolis, MN, United States
| | - Benjamin C Silverman
- Harvard Medical School, Boston, MA, United States
- Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, United States
| | - Patrick Monette
- Harvard Medical School, Boston, MA, United States
- Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, United States
| | - Sara Kimble
- Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, United States
| | - Scott L Rauch
- Harvard Medical School, Boston, MA, United States
- Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, United States
| | - Justin T Baker
- Harvard Medical School, Boston, MA, United States
- Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, United States
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Costa A, Milne R. Understanding 'passivity' in digital health through imaginaries and experiences of coronavirus disease 2019 contact tracing apps. BIG DATA & SOCIETY 2022; 9:20539517221091138. [PMID: 36819735 PMCID: PMC7614187 DOI: 10.1177/20539517221091138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Growing interest is being directed to the health applications of so-called 'passive data' collected through wearables and sensors without active input by users. High promises are attached to passive data and their potential to unlock new insights into health and illness, but as researchers and commentators have noted, this mode of data gathering also raises fundamental questions regarding the subject's agency, autonomy and privacy. To explore how these tensions are negotiated in practice, we present and discuss findings from an interview study with 30 members of the public in the UK and Italy, which examined their views and experiences of the coronavirus disease 2019 contact tracing apps as a large-scale, high-impact example of digital health technology using passive data. We argue that, contrary to what the phrasing 'passive data' suggests, passivity is not a quality of specific modes of data collection but is contingent on the very practices that the technology is supposed to unobtrusively capture.
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Affiliation(s)
- Alessia Costa
- Wellcome Connecting Science, Engagement and Society, Cambridgeshire, Hinxton, UK
| | - Richard Milne
- Wellcome Connecting Science, Engagement and Society, Cambridgeshire, Hinxton, UK
- Kavli Centre for Ethics, Science and the Public, Faculty of Education, University of Cambridge
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Möllmann NR, Mirbabaie M, Stieglitz S. Is it alright to use artificial intelligence in digital health? A systematic literature review on ethical considerations. Health Informatics J 2021; 27:14604582211052391. [PMID: 34935557 DOI: 10.1177/14604582211052391] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The application of artificial intelligence (AI) not only yields in advantages for healthcare but raises several ethical questions. Extant research on ethical considerations of AI in digital health is quite sparse and a holistic overview is lacking. A systematic literature review searching across 853 peer-reviewed journals and conferences yielded in 50 relevant articles categorized in five major ethical principles: beneficence, non-maleficence, autonomy, justice, and explicability. The ethical landscape of AI in digital health is portrayed including a snapshot guiding future development. The status quo highlights potential areas with little empirical but required research. Less explored areas with remaining ethical questions are validated and guide scholars' efforts by outlining an overview of addressed ethical principles and intensity of studies including correlations. Practitioners understand novel questions AI raises eventually leading to properly regulated implementations and further comprehend that society is on its way from supporting technologies to autonomous decision-making systems.
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Affiliation(s)
- Nicholas Rj Möllmann
- Research Group Digital Communication and Transformation, 27170University of Duisburg-Essen, Duisburg, Germany
| | - Milad Mirbabaie
- Faculty of Business Administration and Economics, 9168Paderborn University, Paderborn, Germany
| | - Stefan Stieglitz
- Research Group Digital Communication and Transformation, 27170University of Duisburg-Essen, Duisburg, Germany
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Khalili-Mahani N, Holowka E, Woods S, Khaled R, Roy M, Lashley M, Glatard T, Timm-Bottos J, Dahan A, Niesters M, Hovey RB, Simon B, Kirmayer LJ. Play the Pain: A Digital Strategy for Play-Oriented Research and Action. Front Psychiatry 2021; 12:746477. [PMID: 34975566 PMCID: PMC8714795 DOI: 10.3389/fpsyt.2021.746477] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 11/11/2021] [Indexed: 12/26/2022] Open
Abstract
The value of understanding patients' illness experience and social contexts for advancing medicine and clinical care is widely acknowledged. However, methodologies for rigorous and inclusive data gathering and integrative analysis of biomedical, cultural, and social factors are limited. In this paper, we propose a digital strategy for large-scale qualitative health research, using play (as a state of being, a communication mode or context, and a set of imaginative, expressive, and game-like activities) as a research method for recursive learning and action planning. Our proposal builds on Gregory Bateson's cybernetic approach to knowledge production. Using chronic pain as an example, we show how pragmatic, structural and cultural constraints that define the relationship of patients to the healthcare system can give rise to conflicted messaging that impedes inclusive health research. We then review existing literature to illustrate how different types of play including games, chatbots, virtual worlds, and creative art making can contribute to research in chronic pain. Inspired by Frederick Steier's application of Bateson's theory to designing a science museum, we propose DiSPORA (Digital Strategy for Play-Oriented Research and Action), a virtual citizen science laboratory which provides a framework for delivering health information, tools for play-based experimentation, and data collection capacity, but is flexible in allowing participants to choose the mode and the extent of their interaction. Combined with other data management platforms used in epidemiological studies of neuropsychiatric illness, DiSPORA offers a tool for large-scale qualitative research, digital phenotyping, and advancing personalized medicine.
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Affiliation(s)
- Najmeh Khalili-Mahani
- McGill Centre for Integrative Neuroscience, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- Division of Social & Transcultural Psychiatry, McGill University, Montreal, QC, Canada
- Culture and Mental Health Research Unit, Lady Davis Institute, Jewish General Hospital, Montreal, QC, Canada
- Technoculture, Arts and Game Centre, Milieux Institute for Art, Culture and Technology, Concordia University, Montreal, QC, Canada
| | - Eileen Holowka
- Technoculture, Arts and Game Centre, Milieux Institute for Art, Culture and Technology, Concordia University, Montreal, QC, Canada
| | | | - Rilla Khaled
- Technoculture, Arts and Game Centre, Milieux Institute for Art, Culture and Technology, Concordia University, Montreal, QC, Canada
| | - Mathieu Roy
- Department of Psychology, McGill University, Montreal, QC, Canada
| | - Myrna Lashley
- Division of Social & Transcultural Psychiatry, McGill University, Montreal, QC, Canada
- Culture and Mental Health Research Unit, Lady Davis Institute, Jewish General Hospital, Montreal, QC, Canada
| | - Tristan Glatard
- Department of Computer Science, Concordia University, Montreal, QC, Canada
- PERFORM Centre, Concordia University, Montreal, QC, Canada
| | - Janis Timm-Bottos
- Department of Creative Art Therapies, Concordia University, Montreal, QC, Canada
| | - Albert Dahan
- Department of Anesthesiology, Leiden University Medical Centre, Leiden University, Leiden, Netherlands
| | - Marieke Niesters
- Department of Anesthesiology, Leiden University Medical Centre, Leiden University, Leiden, Netherlands
| | | | - Bart Simon
- Technoculture, Arts and Game Centre, Milieux Institute for Art, Culture and Technology, Concordia University, Montreal, QC, Canada
- Department of Sociology, Concordia University, Montreal, QC, Canada
| | - Laurence J. Kirmayer
- Division of Social & Transcultural Psychiatry, McGill University, Montreal, QC, Canada
- Culture and Mental Health Research Unit, Lady Davis Institute, Jewish General Hospital, Montreal, QC, Canada
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Haines S, Savic M, Nielsen S, Carter A. Key considerations for the implementation of clinically focused Prescription Drug Monitoring Programs to avoid unintended consequences. THE INTERNATIONAL JOURNAL OF DRUG POLICY 2021; 101:103549. [PMID: 34920217 DOI: 10.1016/j.drugpo.2021.103549] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 11/18/2021] [Accepted: 11/22/2021] [Indexed: 11/28/2022]
Abstract
Prescription Drug Monitoring Programs (PDMP) are electronic databases that are used to track and monitor the prescribing and dispensing of controlled substances, including opioid analgesics and benzodiazepines. PDMP have been widely implemented throughout North America and are currently being introduced in Australia and some parts of Europe. PDMP were originally developed by and for law enforcement, however many jurisdictions have now shifted use toward clinical care and harm reduction through early identification of prescription dependence and extra-medical use, and to ensure appropriate supply of controlled substances to the community through monitoring health care provider prescribing and dispensing patterns (Deloitte, 2018; Picco et al., 2021a; CDC, 2021a, U.S Department of Justice, 2018). Clinically-motivated PDMP highlight medication-related risk, based on the patient's prescribing and dispensing history. Health care professionals can use this information to aid or inform clinical decision-making and provide opportunities for intervention and treatment (Deloitte, 2018) . However, a number of harms have been associated with the use of PDMP, including increased stigma and discrimination, untreated pain and mental illness, and denial of appropriate health care for those identified as 'high risk'. In this article we examine these harms and potential mitigating factors. We conclude with some suggestions and future directions for research to address some of the current uncertainties regarding PDMP use. We highlight the need for mixed methods research to better understand the personal impacts of PDMP policy on the populations they were designed to aid.
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Affiliation(s)
- Sarah Haines
- Turner Institute for Brain and Mental Health, Monash University 18 Innovation Walk, Clayton VIC 3800, Australia.
| | - Michael Savic
- Turning Point Research Centre, Eastern Health, 110 Church Street, Richmond, 3121, Australia; Monash Addiction Research Centre, Monash University, Level 3, Building G Moorooduc Hwy, Frankston VIC 3199, Australia
| | - Suzanne Nielsen
- Monash Addiction Research Centre, Monash University, Level 3, Building G Moorooduc Hwy, Frankston VIC 3199, Australia
| | - Adrian Carter
- Turner Institute for Brain and Mental Health, Monash University 18 Innovation Walk, Clayton VIC 3800, Australia
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Coghlan S, D’Alfonso S. Digital Phenotyping: an Epistemic and Methodological Analysis. PHILOSOPHY & TECHNOLOGY 2021; 34:1905-1928. [PMID: 34786325 PMCID: PMC8581123 DOI: 10.1007/s13347-021-00492-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 11/04/2021] [Indexed: 11/30/2022]
Abstract
Some claim that digital phenotyping will revolutionize understanding of human psychology and experience and significantly promote human wellbeing. This paper investigates the nature of digital phenotyping in relation to its alleged promise. Unlike most of the literature to date on philosophy and digital phenotyping, which has focused on its ethical aspects, this paper focuses on its epistemic and methodological aspects. The paper advances a tetra-taxonomy involving four scenario types in which knowledge may be acquired from human "digitypes" by digital phenotyping. These scenarios comprise two causal relations and a correlative and constitutive relation that can exist between information generated by digital systems/devices on the one hand and psychological or behavioral phenomena on the other. The paper describes several modes of inference involved in deriving knowledge within these scenarios. After this epistemic mapping, the paper analyzes the possible knowledge potential and limitations of digital phenotyping. It finds that digital phenotyping holds promise of delivering insight into conditions and states as well producing potentially new psychological categories. It also argues that care must be taken that digital phenotyping does not make unwarranted conclusions and is aware of potentially distorting effects in digital sensing and measurement. If digital phenotyping is to truly revolutionize knowledge of human life, it must deliver on a range of fronts, including making accurate forecasts and diagnoses of states and behaviors, providing causal explanations of these phenomena, and revealing important constituents of human conditions, psychology, and experience.
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Affiliation(s)
- Simon Coghlan
- School of Computing & Information Systems, Faculty of Engineering and Information Technology, The University of Melbourne, Victoria, Australia
| | - Simon D’Alfonso
- School of Computing & Information Systems, Faculty of Engineering and Information Technology, The University of Melbourne, Victoria, Australia
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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.
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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
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Laestadius LI, Craig KA, Campos-Castillo C. Perceptions of Alerts Issued by Social Media Platforms in Response to Self-injury Posts Among Latinx Adolescents: Qualitative Analysis. J Med Internet Res 2021; 23:e28931. [PMID: 34383683 PMCID: PMC8386397 DOI: 10.2196/28931] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 04/22/2021] [Accepted: 07/05/2021] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND There is growing interest in using social media data to detect and address nonsuicidal self-injury (NSSI) among adolescents. Adolescents often do not seek clinical help for NSSI and may adopt strategies to obscure detection; therefore, social media platforms may be able to facilitate early detection and treatment by using machine learning models to screen posts for harmful content and subsequently alert adults. However, such efforts have raised privacy and ethical concerns among health researchers. Little is currently known about how adolescents perceive these efforts. OBJECTIVE The aim of this study is to examine perceptions of automated alerts for NSSI posts on social media among Latinx adolescents, who are at risk for NSSI yet are underrepresented in both NSSI and health informatics research. In addition, we considered their perspectives on preferred recipients of automated alerts. METHODS We conducted semistructured, qualitative interviews with 42 Latinx adolescents between the ages of 13 and 17 years who were recruited from a nonprofit organization serving the Latinx community in Milwaukee, Wisconsin. The Latinx population in Milwaukee is largely of Mexican descent. All interviews were conducted between June and July 2019. Transcripts were analyzed using framework analysis to discern their perceptions of automated alerts sent by social media platforms and potential alert recipients. RESULTS Participants felt that automated alerts would make adolescents safer and expedite aid before the situation escalated. However, some worried that hyperbolic statements would generate false alerts and instigate conflicts. Interviews revealed strong opinions about ideal alert recipients. Parents were most commonly endorsed, but support was conditional on perceptions that the parent would respond appropriately. Emergency services were judged as safer but inappropriate for situations considered lower risk. Alerts sent to school staff generated the strongest privacy concerns. Altogether, the preferred alert recipients varied by individual adolescents and perceived risks in the situation. None raised ethical concerns about the collection, analysis, or storage of personal information regarding their mental health status. CONCLUSIONS Overall, Latinx adolescents expressed broad support for automated alerts for NSSI on social media, which indicates opportunities to address NSSI. However, these efforts should be co-constructed with adolescents to ensure that preferences and needs are met, as well as embedded within broader approaches for addressing structural and cultural barriers to care.
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Affiliation(s)
- Linnea I Laestadius
- Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI, United States
| | - Katherine A Craig
- Department of Sociology, University of Colorado Boulder, Boulder, CO, United States
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Vilaza GN, McCashin D. Is the Automation of Digital Mental Health Ethical? Applying an Ethical Framework to Chatbots for Cognitive Behaviour Therapy. Front Digit Health 2021; 3:689736. [PMID: 34713163 PMCID: PMC8521996 DOI: 10.3389/fdgth.2021.689736] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Accepted: 07/16/2021] [Indexed: 11/13/2022] Open
Abstract
The COVID-19 pandemic has intensified the need for mental health support across the whole spectrum of the population. Where global demand outweighs the supply of mental health services, established interventions such as cognitive behavioural therapy (CBT) have been adapted from traditional face-to-face interaction to technology-assisted formats. One such notable development is the emergence of Artificially Intelligent (AI) conversational agents for psychotherapy. Pre-pandemic, these adaptations had demonstrated some positive results; but they also generated debate due to a number of ethical and societal challenges. This article commences with a critical overview of both positive and negative aspects concerning the role of AI-CBT in its present form. Thereafter, an ethical framework is applied with reference to the themes of (1) beneficence, (2) non-maleficence, (3) autonomy, (4) justice, and (5) explicability. These themes are then discussed in terms of practical recommendations for future developments. Although automated versions of therapeutic support may be of appeal during times of global crises, ethical thinking should be at the core of AI-CBT design, in addition to guiding research, policy, and real-world implementation as the world considers post-COVID-19 society.
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van Draanen J, Satti S, Morgan J, Gaudette L, Knight R, Ti L. Using passive surveillance technology for overdose prevention: Key ethical and implementation issues. Drug Alcohol Rev 2021; 41:406-409. [PMID: 34355446 DOI: 10.1111/dar.13373] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Revised: 05/21/2021] [Accepted: 07/17/2021] [Indexed: 11/29/2022]
Abstract
Passive surveillance technology has the potential to increase safety through monitoring spaces where people are at risk of overdose. One key opportunity for the use of passive surveillance technology to prevent overdose fatality is in bathrooms where people may be using drugs. However, uncertainty remains with regards to how to attain informed consent, implications for data storage and privacy and potential negative socio-legal ramifications for people who use drugs. In addition, there are issues regarding responsibility and liability for the devices. Transparency with regards to data privacy and security may also be needed before bathroom users will feel comfortable with such solutions. In this article, we discuss these issues and offer recommendations to provide a foundation for future research and policy development.
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Affiliation(s)
- Jenna van Draanen
- British Columbia Centre on Substance Use, Vancouver, Canada.,Child, Family, and Population Health Nursing, University of Washington, Seattle, USA
| | | | - Jeffrey Morgan
- British Columbia Centre on Substance Use, Vancouver, Canada
| | - Laural Gaudette
- Overdose Prevention Society, Overdose Prevention Participatory Research Assistant Program, Vancouver, Canada
| | - Rod Knight
- British Columbia Centre on Substance Use, Vancouver, Canada.,Department of Medicine, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - Lianping Ti
- British Columbia Centre on Substance Use, Vancouver, Canada.,Department of Medicine, Faculty of Medicine, University of British Columbia, Vancouver, Canada
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Martinez-Martin N, Greely HT, Cho MK. Ethical Development of Digital Phenotyping Tools for Mental Health Applications: Delphi Study. JMIR Mhealth Uhealth 2021; 9:e27343. [PMID: 34319252 PMCID: PMC8367187 DOI: 10.2196/27343] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 05/06/2021] [Accepted: 05/21/2021] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND Digital phenotyping (also known as personal sensing, intelligent sensing, or body computing) involves the collection of biometric and personal data in situ from digital devices, such as smartphones, wearables, or social media, to measure behavior or other health indicators. The collected data are analyzed to generate moment-by-moment quantification of a person's mental state and potentially predict future mental states. Digital phenotyping projects incorporate data from multiple sources, such as electronic health records, biometric scans, or genetic testing. As digital phenotyping tools can be used to study and predict behavior, they are of increasing interest for a range of consumer, government, and health care applications. In clinical care, digital phenotyping is expected to improve mental health diagnoses and treatment. At the same time, mental health applications of digital phenotyping present significant areas of ethical concern, particularly in terms of privacy and data protection, consent, bias, and accountability. OBJECTIVE This study aims to develop consensus statements regarding key areas of ethical guidance for mental health applications of digital phenotyping in the United States. METHODS We used a modified Delphi technique to identify the emerging ethical challenges posed by digital phenotyping for mental health applications and to formulate guidance for addressing these challenges. Experts in digital phenotyping, data science, mental health, law, and ethics participated as panelists in the study. The panel arrived at consensus recommendations through an iterative process involving interviews and surveys. The panelists focused primarily on clinical applications for digital phenotyping for mental health but also included recommendations regarding transparency and data protection to address potential areas of misuse of digital phenotyping data outside of the health care domain. RESULTS The findings of this study showed strong agreement related to these ethical issues in the development of mental health applications of digital phenotyping: privacy, transparency, consent, accountability, and fairness. Consensus regarding the recommendation statements was strongest when the guidance was stated broadly enough to accommodate a range of potential applications. The privacy and data protection issues that the Delphi participants found particularly critical to address related to the perceived inadequacies of current regulations and frameworks for protecting sensitive personal information and the potential for sale and analysis of personal data outside of health systems. CONCLUSIONS The Delphi study found agreement on a number of ethical issues to prioritize in the development of digital phenotyping for mental health applications. The Delphi consensus statements identified general recommendations and principles regarding the ethical application of digital phenotyping to mental health. As digital phenotyping for mental health is implemented in clinical care, there remains a need for empirical research and consultation with relevant stakeholders to further understand and address relevant ethical issues.
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Affiliation(s)
- Nicole Martinez-Martin
- Center for Biomedical Ethics, School of Medicine, Stanford University, Stanford, CA, United States
| | | | - Mildred K Cho
- Center for Biomedical Ethics, School of Medicine, Stanford University, Stanford, CA, United States
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Prakash J, Chaudhury S, Chatterjee K. Digital phenotyping in psychiatry: When mental health goes binary. Ind Psychiatry J 2021; 30:191-192. [PMID: 35017799 PMCID: PMC8709510 DOI: 10.4103/ipj.ipj_223_21] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 11/10/2021] [Accepted: 11/10/2021] [Indexed: 11/04/2022] Open
Affiliation(s)
- Jyoti Prakash
- Department of Psychiatry, Armed Forces Medical College, Pune, Maharashtra, India
| | - Suprakash Chaudhury
- Department of Psychiatry, Dr. D. Y. Patil Medical College, Pune, Maharashtra, India
| | - Kaushik Chatterjee
- Department of Psychiatry, Armed Forces Medical College, Pune, Maharashtra, India
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Kim M, Yang J, Ahn WY, Choi HJ. Machine Learning Analysis to Identify Digital Behavioral Phenotypes for Engagement and Health Outcome Efficacy of an mHealth Intervention for Obesity: Randomized Controlled Trial. J Med Internet Res 2021; 23:e27218. [PMID: 34184991 PMCID: PMC8277339 DOI: 10.2196/27218] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2021] [Revised: 04/28/2021] [Accepted: 05/06/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND The digital health care community has been urged to enhance engagement and clinical outcomes by analyzing multidimensional digital phenotypes. OBJECTIVE This study aims to use a machine learning approach to investigate the performance of multivariate phenotypes in predicting the engagement rate and health outcomes of digital cognitive behavioral therapy. METHODS We leveraged both conventional phenotypes assessed by validated psychological questionnaires and multidimensional digital phenotypes within time-series data from a mobile app of 45 participants undergoing digital cognitive behavioral therapy for 8 weeks. We conducted a machine learning analysis to discriminate the important characteristics. RESULTS A higher engagement rate was associated with higher weight loss at 8 weeks (r=-0.59; P<.001) and 24 weeks (r=-0.52; P=.001). Applying the machine learning approach, lower self-esteem on the conventional phenotype and higher in-app motivational measures on digital phenotypes commonly accounted for both engagement and health outcomes. In addition, 16 types of digital phenotypes (ie, lower intake of high-calorie food and evening snacks and higher interaction frequency with mentors) predicted engagement rates (mean R2 0.416, SD 0.006). The prediction of short-term weight change (mean R2 0.382, SD 0.015) was associated with 13 different digital phenotypes (ie, lower intake of high-calorie food and carbohydrate and higher intake of low-calorie food). Finally, 8 measures of digital phenotypes (ie, lower intake of carbohydrate and evening snacks and higher motivation) were associated with a long-term weight change (mean R2 0.590, SD 0.011). CONCLUSIONS Our findings successfully demonstrated how multiple psychological constructs, such as emotional, cognitive, behavioral, and motivational phenotypes, elucidate the mechanisms and clinical efficacy of a digital intervention using the machine learning method. Accordingly, our study designed an interpretable digital phenotype model, including multiple aspects of motivation before and during the intervention, predicting both engagement and clinical efficacy. This line of research may shed light on the development of advanced prevention and personalized digital therapeutics. TRIAL REGISTRATION ClinicalTrials.gov NCT03465306; https://clinicaltrials.gov/ct2/show/NCT03465306.
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Affiliation(s)
- Meelim Kim
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jaeyeong Yang
- Department of Psychology, Seoul National University, Seoul, Republic of Korea
| | - Woo-Young Ahn
- Department of Psychology, Seoul National University, Seoul, Republic of Korea.,Department of Brain and Cognitive Sciences, Seoul National University, Seoul, Republic of Korea
| | - Hyung Jin Choi
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Anatomy and Cell Biology, Neuroscience Research Institute, Wide River Institute of Immunology, Gangwon-do, Republic of Korea
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Gooding P, Kariotis T. Ethics and Law in Research on Algorithmic and Data-Driven Technology in Mental Health Care: Scoping Review. JMIR Ment Health 2021; 8:e24668. [PMID: 34110297 PMCID: PMC8262551 DOI: 10.2196/24668] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 03/11/2021] [Accepted: 04/15/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Uncertainty surrounds the ethical and legal implications of algorithmic and data-driven technologies in the mental health context, including technologies characterized as artificial intelligence, machine learning, deep learning, and other forms of automation. OBJECTIVE This study aims to survey empirical scholarly literature on the application of algorithmic and data-driven technologies in mental health initiatives to identify the legal and ethical issues that have been raised. METHODS We searched for peer-reviewed empirical studies on the application of algorithmic technologies in mental health care in the Scopus, Embase, and Association for Computing Machinery databases. A total of 1078 relevant peer-reviewed applied studies were identified, which were narrowed to 132 empirical research papers for review based on selection criteria. Conventional content analysis was undertaken to address our aims, and this was supplemented by a keyword-in-context analysis. RESULTS We grouped the findings into the following five categories of technology: social media (53/132, 40.1%), smartphones (37/132, 28%), sensing technology (20/132, 15.1%), chatbots (5/132, 3.8%), and miscellaneous (17/132, 12.9%). Most initiatives were directed toward detection and diagnosis. Most papers discussed privacy, mainly in terms of respecting the privacy of research participants. There was relatively little discussion of privacy in this context. A small number of studies discussed ethics directly (10/132, 7.6%) and indirectly (10/132, 7.6%). Legal issues were not substantively discussed in any studies, although some legal issues were discussed in passing (7/132, 5.3%), such as the rights of user subjects and privacy law compliance. CONCLUSIONS Ethical and legal issues tend to not be explicitly addressed in empirical studies on algorithmic and data-driven technologies in mental health initiatives. Scholars may have considered ethical or legal matters at the ethics committee or institutional review board stage. If so, this consideration seldom appears in published materials in applied research in any detail. The form itself of peer-reviewed papers that detail applied research in this field may well preclude a substantial focus on ethics and law. Regardless, we identified several concerns, including the near-complete lack of involvement of mental health service users, the scant consideration of algorithmic accountability, and the potential for overmedicalization and techno-solutionism. Most papers were published in the computer science field at the pilot or exploratory stages. Thus, these technologies could be appropriated into practice in rarely acknowledged ways, with serious legal and ethical implications.
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Affiliation(s)
- Piers Gooding
- Melbourne Law School, University of Melbourne, Melbourne, Australia
- Mozilla Foundation, Mountain View, CA, United States
| | - Timothy Kariotis
- Melbourne School of Government, University of Melbourne, Melbourne, Australia
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Brinberg M, Ram N. Do New Romantic Couples Use More Similar Language Over Time? Evidence from Intensive Longitudinal Text Messages. THE JOURNAL OF COMMUNICATION 2021; 71:454-477. [PMID: 34335083 PMCID: PMC8315721 DOI: 10.1093/joc/jqab012] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
The digital text traces left by computer-mediated communication (CMC) provide a new opportunity to test theories of relational processes that were originally developed through observation of face-to-face interactions. Communication accommodation theory, for example, suggests that conversation partners' verbal (and non-verbal) behaviors become more similar as relationships develop. Using a corpus of 1+ million text messages that 41 college-age romantic couples sent to each other during their first year of dating, this study examines how linguistic alignment of new romantic couples' CMC changes during relationship formation. Results from nonlinear growth models indicate that three aspects of daily linguistic alignment (syntactic-language style matching, semantic-latent semantic analysis, overall-cosine similarity) all exhibit exponential growth to an asymptote as romantic relationships form. Beyond providing empirical support that communication accommodation theory also applies in romantic partners' CMC, this study demonstrates how relational processes can be examined using digital trace data.
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Affiliation(s)
- Miriam Brinberg
- Department of Communication Arts and Sciences, Pennsylvania State University, State College, PA 16801, USA
- Corresponding author: Miriam Brinberg; e-mail:
| | - Nilam Ram
- Departments of Communication and Psychology, Stanford University, Stanford, CA 94305, USA
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Pavarini G, McMillan R, Robinson A, Singh I. Design Bioethics: A Theoretical Framework and Argument for Innovation in Bioethics Research. THE AMERICAN JOURNAL OF BIOETHICS : AJOB 2021; 21:37-50. [PMID: 33502959 PMCID: PMC8676709 DOI: 10.1080/15265161.2020.1863508] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Empirical research in bioethics has developed rapidly over the past decade, but has largely eschewed the use of technology-driven methodologies. We propose "design bioethics" as an area of conjoined theoretical and methodological innovation in the field, working across bioethics, health sciences and human-centred technological design. We demonstrate the potential of digital tools, particularly purpose-built digital games, to align with theoretical frameworks in bioethics for empirical research, integrating context, narrative and embodiment in moral decision-making. Purpose-built digital tools can engender situated engagement with bioethical questions; can achieve such engagement at scale; and can access groups traditionally under-represented in bioethics research and theory. If developed and used with appropriate rigor, tools motivated by "design bioethics" could offer unique insights into new and familiar normative and empirical issues in the field.
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2020 International Neuroethics Society Annual Meeting Top Abstracts. AJOB Neurosci 2021; 15:1-23. [PMID: 34060979 DOI: 10.1080/21507740.2021.1917726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Skorburg JA, Yam J. Is There an App for That?: Ethical Issues in the Digital Mental Health Response to COVID-19. AJOB Neurosci 2021; 13:177-190. [PMID: 33989127 DOI: 10.1080/21507740.2021.1918284] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Well before COVID-19, there was growing excitement about the potential of various digital technologies such as tele-health, smartphone apps, or AI chatbots to revolutionize mental healthcare. As the SARS-CoV-2 virus spread across the globe, clinicians warned of the mental illness epidemic within the coronavirus pandemic. Now, funding for digital mental health technologies is surging and many researchers are calling for widespread adoption to address the mental health sequelae of COVID-19. Reckoning with the ethical implications of these technologies is urgent because decisions made today will shape the future of mental health research and care for the foreseeable future. We contend that the most pressing ethical issues concern (1) the extent to which these technologies demonstrably improve mental health outcomes and (2) the likelihood that wide-scale adoption will exacerbate the existing health inequalities laid bare by the pandemic. We argue that the evidence for efficacy is weak and that the likelihood of increasing inequalities is high. First, we review recent trends in digital mental health. Next, we turn to the clinical literature to show that many technologies proposed as a response to COVID-19 are unlikely to improve outcomes. Then, we argue that even evidence-based technologies run the risk of increasing health disparities. We conclude by suggesting that policymakers should not allocate limited resources to the development of many digital mental health tools and should focus instead on evidence-based solutions to address mental health inequalities.
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Gloster AT, Meyer AH, Klotsche J, Villanueva J, Block VJ, Benoy C, Rinner MTB, Walter M, Lang UE, Karekla M. The spatiotemporal movement of patients in and out of a psychiatric hospital: an observational GPS study. BMC Psychiatry 2021; 21:165. [PMID: 33761921 PMCID: PMC7992323 DOI: 10.1186/s12888-021-03147-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Accepted: 02/23/2021] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Movement is a basic component of health. Little is known about the spatiotemporal movement of patients with mental disorders. The aim of this study was to determine how spatiotemporal movement of patients related to their symptoms and wellbeing. METHOD A total of 106 patients (inpatients (n = 69) and outpatients (n = 37)) treated for a wide range of mental disorders (transdiagnostic sample) carried a GPS-enabled smartphone for one week at the beginning of treatment. Algorithms were applied to establish spatiotemporal clusters and subsequently related to known characteristics of these groups (i.e., at the hospital, at home). Symptomatology, Wellbeing, and Psychological flexibility were also assessed. RESULTS Spatiotemporal patterns of inpatients and outpatients showed differences consistent with predictions (e.g., outpatients showed higher active areas). These patterns were largely unassociated with symptoms (except for agoraphobic symptoms). Greater movement and variety of movement were more predictive of wellbeing, however, in both inpatients and outpatients. CONCLUSION Measuring spatiotemporal patterns is feasible, predictive of wellbeing, and may be a marker of patient functioning. Ethical issues of collecting GPS data are discussed.
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Affiliation(s)
- Andrew T. Gloster
- grid.6612.30000 0004 1937 0642University of Basel, Department of Psychology, Division of Clinical Psychology & Intervention Science, Missionsstrasse 62A, CH-4055 Basel, Switzerland
| | - Andrea H. Meyer
- grid.6612.30000 0004 1937 0642University of Basel, Department of Psychology, Division of Clinical Psychology & Epidemiology, Basel, Switzerland
| | - Jens Klotsche
- grid.6363.00000 0001 2218 4662German Rheumatism Research Center Berlin, Epidemiology unit and Charité Universitaetsmedizin Berlin, Institute for Social Medicine, Epidemiology and Health Economics, Berlin, Germany
| | - Jeanette Villanueva
- grid.6612.30000 0004 1937 0642University of Basel, Department of Psychology, Division of Clinical Psychology & Intervention Science, Missionsstrasse 62A, CH-4055 Basel, Switzerland
| | - Victoria J. Block
- grid.6612.30000 0004 1937 0642University of Basel, Department of Psychology, Division of Clinical Psychology & Intervention Science, Missionsstrasse 62A, CH-4055 Basel, Switzerland
| | - Charles Benoy
- grid.6612.30000 0004 1937 0642University Psychiatric Clinics (UPK), University of Basel, Basel, Switzerland
| | - Marcia T. B. Rinner
- grid.6612.30000 0004 1937 0642University of Basel, Department of Psychology, Division of Clinical Psychology & Intervention Science, Missionsstrasse 62A, CH-4055 Basel, Switzerland
| | - Marc Walter
- grid.6612.30000 0004 1937 0642University Psychiatric Clinics (UPK), University of Basel, Basel, Switzerland
| | - Undine E. Lang
- grid.6612.30000 0004 1937 0642University Psychiatric Clinics (UPK), University of Basel, Basel, Switzerland
| | - Maria Karekla
- grid.6603.30000000121167908University of Cyprus, Department of Psychology, Nicosia, Cyprus
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