Ethical Considerations of Digital Phenotyping from the Perspective of a Healthcare Practitioner

Dagum, Paul; Montag, Christian

doi:10.1007/978-3-030-31620-4_2

Cited by 20 publications

(23 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The clinical use of digital phenotyping tools is also thought to have the potential to disrupt the traditional patient-therapist relationship. Artificial intelligence tools are thought to have the potential to disrupt or even replace some of the roles traditionally held by therapists or clinicians [82][83][84]. The use of artificial intelligence methods, such as machine learning and natural language processing, is thought to raise issues of whether the device's findings will be viewed by physicians and patients as more objective than as physician judgment or patient's self-report, thus intruding upon the therapeutic relationship.…”

Section: Introductionmentioning

confidence: 99%

Ethical Development of Digital Phenotyping Tools for Mental Health Applications: Delphi Study

Martinez-Martin¹,

Greely²,

Cho³

2021

JMIR Mhealth Uhealth

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionmentioning

confidence: 99%

Ethical Development of Digital Phenotyping Tools for Mental Health Applications: Delphi Study

Martinez-Martin¹,

Greely²,

Cho³

2021

JMIR Mhealth Uhealth

View full text Add to dashboard Cite

show abstract

“…Aside from this, problems arise because Big Data analysis might lead to spurious findings (multiple testing might lead to lots of false-positive findings; therefore, replication of findings is of high relevance-as in other fields of the psychological sciences [65]). Beyond statistical problems, digital phenotyping and mobile sensing endangers privacy of the patients afflicted [57]. It needs to be made sure that the recorded data underlies strong data protection plans together with ethical guidelines in what areas what kind of data can be used.…”

Section: Challenges In the Realm Of Applying Methods From Psychoinformatics: Statistics And Privacymentioning

confidence: 99%

“…What has not been discussed so far is the perspective from the clinician's perspective. Tracking the relevant digital markers on smartphones and other devices covarying with the addictive disorder will help to get insights into the development of the mental disorder and could even result in realtime interventions, when the digital data hint towards an emergency state on the patient side (for exact processes of such an intervention, see an app developed by Mindstrong Health to treat patients with affective disorders as described in Dagum and Montag [57]). In this context, we explicitly mention that this approach not only comprises the study of patients, but the complete spectrum from healthy via problematic to diagnosed psychopathological behavior.…”

Section: The Potential Of Psychoinformatics For Intervention-purposes In Internet Use Disordersmentioning

confidence: 99%

The Potential of Digital Phenotyping and Mobile Sensing for Psycho-Diagnostics of Internet Use Disorders

Montag¹,

Rumpf

2021

Curr Addict Rep

Self Cite

View full text Add to dashboard Cite

Purpose of Review The present paper provides an accessible overview on the potential of digital phenotyping and mobile sensing not only shedding light on the nature of Internet Use Disorders (IUD), but also to provide new ideas on how to improve psycho-diagnostics of mental processes linked to IUD. Recent Findings In detail, the psycho-diagnostic areas of prevention, treatment, and aftercare in the realm of IUDs are focused upon in this work. Before each of these areas is presented in more specificity, the terms digital phenotyping and mobile sensing are introduced against the background of an interdisciplinary research endeavor called Psychoinformatics. Obstacles to overcome problems in this emerging research endeavor—sensing psychological traits/states from digital footprints—are discussed together with risks and chances, which arise from the administration of online-tracking technologies in the field of IUDs. Summary Given the limited validity and reliability of traditional assessment via questionnaires or diagnostic interviews with respect to recall bias and tendencies to answer towards social desirability, digital phenotyping and mobile sensing offer a novel approach overcoming recall bias and other limitations of usual assessment approaches. This will not only set new standards in precisely mapping behavior, but it will also offer scientists and practitioners opportunities to detect risky Internet use patterns in a timely manner and to establish tailored feedback as a means of intervention.

show abstract

“…Using a smartphone app installed on the personal smartphone of participants for data assessment requires particular attention to data security (for a broader discussion on ethical concerns regarding digital phenotyping procedures in the psychological and psychiatric sciences see [59,60]). Therefore, subjects must provide additional consent to collect data within the app and grant the necessary permissions to the app on the smartphones (such as being notified by the app about available surveys).…”

Section: Methodsmentioning

confidence: 99%

Transdiagnostic phenotyping of psychopathology in a help-seeking population (PhenoNetz): A study protocol for an experience sampling study

Rosen

Betz

Montag³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

Background: Prevention in psychiatry provides a promising way to address the burden by mental illness. However, established approaches focus on specific diagnoses and do not address the heterogeneity and manifold potential outcomes of help-seeking populations that present at early recognition services. Thus, novel preventive approaches have been suggested, focusing on a broad transdiagnostic risk syndrome associated with different mental disorders. Conceptualizing such a pluripotent risk syndrome from a network perspective of interacting symptoms allows transdiagnostic investigations beyond binary disease categories. Furthermore, modern technologies such as smartphones facilitate the application of Experience Sampling Methods (ESM). A combination of ESM with network analyses provides valid insights beyond established assessment instruments. Methods: We will examine n = 75 individuals (age 18-40 years) of the help-seeking population of the Cologne early recognition centre (FETZ). For a maximally naturalistic sample, only minimal exclusion criteria will be applied. We will collect data for 14 days utilizing a mobile application to assess ten transdiagnostic symptoms, i.e., depressive, anxiety and psychotic symptoms as well as distress level. These data will allow to build both personalized and group symptom network models. Additionally, we will explore associations between symptom networks and sociodemographic, risk and resilience factors, as well as psychosocial functioning. Discussion: Our study will provide insights about feasibility and utility of ESM in a help-seeking population. Providing a first explorative phenotyping of the proposed broad transdiagnostic risk syndrome, this study will contribute to innovation of early recognition in psychiatry. Results will help to pave the way for prevention and targeted early intervention in a broader patient group and thus, enable greater intended effects in alleviating the burden of psychiatric disorders. In particular, individual insights provided by our study design are important in the context of precision medicine as well as for patients' own self-management.

show abstract

Ethical Considerations of Digital Phenotyping from the Perspective of a Healthcare Practitioner

Cited by 20 publications

References 29 publications

Ethical Development of Digital Phenotyping Tools for Mental Health Applications: Delphi Study

Ethical Development of Digital Phenotyping Tools for Mental Health Applications: Delphi Study

The Potential of Digital Phenotyping and Mobile Sensing for Psycho-Diagnostics of Internet Use Disorders

Transdiagnostic phenotyping of psychopathology in a help-seeking population (PhenoNetz): A study protocol for an experience sampling study

Contact Info

Product

Resources

About