Mobile applications for client use: Ethical and legal
                        considerations.

Edwards‐Stewart, Amanda; Alexander, Cynthia L.; Armstrong, Christina M.; Hoyt, Tim; O’Donohue, William

doi:10.1037/ser0000321

Cited by 25 publications

(26 citation statements)

References 24 publications

(40 reference statements)

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“…This expanded scope is a sign that the ethical literature concerning digital technology in the mental health context is growing [20,24,[32][33][34], even if ethical analyses may not occur in most applied initiatives, as suggested by Lederman et al [25]. Legal scholarship on digital technology in mental health care is sparse [1] but tends to focus on the regulatory frameworks applicable to digital health, privacy, confidentiality, cybersecurity, and software as medical devices [35][36][37][38][39].…”

Section: Ethics and Lawmentioning

confidence: 99%

Ethics and Law in Research on Algorithmic and Data-Driven Technology in Mental Health Care: Scoping Review

Gooding¹,

Kariotis²

2021

JMIR Ment Health

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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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Section: Ethics and Lawmentioning

confidence: 99%

Ethics and Law in Research on Algorithmic and Data-Driven Technology in Mental Health Care: Scoping Review

Gooding¹,

Kariotis²

2021

JMIR Ment Health

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“…Medico-legal, ethics, and professionalism issues are common with both synchronous and asynchronous health technologies (Chan et al, 2018;Edwards-Stewart et al, 2019).…”

Section: Organizational Responses To Sensors Wearables and Remote Patient Monitoringmentioning

confidence: 99%

A Scoping Review of Sensors, Wearables, and Remote Monitoring For Behavioral Health: Uses, Outcomes, Clinical Competencies, and Research Directions

Hilty

Armstrong

Luxton

et al. 2021

J. technol. behav. sci.

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Sensors and wearables measure physiological and behavioral data in real time for behavioral health, using a variety of methods, interventions, and outcomes. A six-stage scoping review of 10 literature databases focused on keywords in four concept areas: (1) mobile technologies; (2) sensors, wearables, and remote monitoring; (3) mood and anxiety disorders, as well as stress; and (4) behavioral health care. Two authors independently screened results based on titles and abstracts, reviewed the full-text articles, and used inclusion/exclusion criteria to find research that studied self-report or management of symptoms and interventions. Out of a total of 5468 potential references, 76 papers were selected and an additional 16 studies were discovered in references. Of the 92 studies, 54 (58.7%) focused on mood (depressive, N = 28; bipolar, N = 26), 18 (19.6%) on anxiety disorders, and 20 (21.7%) on psychological stress/stress disorders. There were 7 (7.6%) randomized controlled trials, and 31 (33.7%) comparison studies. Research is shifting toward standardized methods, interventions, and evaluation measures, with longitudinal correlation, prediction, and/or biomarking/digital phenotyping of patients' outcomes. These technologies pose several challenges for users, clinicians (e.g., selection, training, skills), healthcare systems (e.g., technology, integration into workflow, privacy), and organizations (e.g., training, creating a professional e-culture, change). Future research is needed on clinical health outcomes; human-computer interaction; medico-legal, professional, and privacy policy issues; models of service delivery; and effectiveness at a population level, across cultures, and related to economic costs. Clinician and institutional competencies could ensure quality of care, integration of missions, and institutional change.

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“…Multiple authors, therefore, recommend increasing education to improve digital literacy and citizenship, both among professionals and patients [74,122,123]. Some authors additionally point out the "notice and choice paradigm" whereby the limited user interfaces inherent to many mHealth products make it difficult to surface adequate notice of privacy policies; while vendors can and do send their policy statements through e-mail, the user may not directly associate them with the app or wearable [33].…”

Section: Informed Consent Privacy Policies and Access Controlmentioning

confidence: 99%

Developments in Privacy and Data Ownership in Mobile Health Technologies, 2016-2019

Galvin

DeMuro²

2020

Yearb Med Inform

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Objectives: To survey international regulatory frameworks that serve to protect privacy of personal data as a human right as well as to review the literature regarding privacy protections and data ownership in mobile health (mHealth) technologies between January 1, 2016 and June 1, 2019 in order to identify common themes. Methods: We performed a review of relevant literature available in English published between January 1, 2016 and June 1, 2019 from databases including PubMed, Google Scholar, and Web of Science, as well as relevant legislative background material. Articles out of scope (as detailed below) were eliminated. We categorized the remaining pool of articles and discrete themes were identified, specifically: concerns around data transmission and storage, including data ownership and the ability to re-identify previously de-identified data; issues with user consent (including the availability of appropriate privacy policies) and access control; and the changing culture and variable global attitudes toward privacy of health data. Results: Recent literature demonstrates that the security of mHealth data storage and transmission remains of wide concern, and aggregated data that were previously considered “de-identified” have now been demonstrated to be re-identifiable. Consumer-informed consent may be lacking with regard to mHealth applications due to the absence of a privacy policy and/or to text that is too complex and lengthy for most users to comprehend. The literature surveyed emphasizes improved access control strategies. This survey also illustrates a wide variety of global user perceptions regarding health data privacy. Conclusion: The international regulatory framework that serves to protect privacy of personal data as a human right is diverse. Given the challenges legislators face to keep up with rapidly advancing technology, we introduce the concept of a “healthcare fiduciary” to serve the best interest of data subjects in the current environment.

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Mobile applications for client use: Ethical and legal considerations.

Cited by 25 publications

References 24 publications

Ethics and Law in Research on Algorithmic and Data-Driven Technology in Mental Health Care: Scoping Review

Ethics and Law in Research on Algorithmic and Data-Driven Technology in Mental Health Care: Scoping Review

A Scoping Review of Sensors, Wearables, and Remote Monitoring For Behavioral Health: Uses, Outcomes, Clinical Competencies, and Research Directions

Developments in Privacy and Data Ownership in Mobile Health Technologies, 2016-2019

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