Ethical, Legal and Social Implications in the Use of Digital Technology for Mental Health Applications

使用数字技术进行心理健康应用的伦理、法律和社会影响

• 批准号: 10478953
• 负责人: Nicole A Martinez-Martin
• 金额: $ 12.69万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2023-10-15
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10478953
• 关键词: Accountability; Address; Adolescent; Adoption; Algorithms; Area; Attention; Behavior monitoring; Behavioral; Big Data; Caring; Categories; Cellular Phone; Clinical; Communication; Cultural Backgrounds; Data; Data Protection; Devices; Diagnostic; Dimensions; Empirical Research; Ethical Issues; Ethics; Family; Foundations; Future; Genetic; Genomics; Goals; Guidelines; Health; Health Services Accessibility; Health Technology; Healthcare; Improve Access; Informed Consent; Institution; Interview; Judgment; Knowledge; Location; Machine Learning; Mediating; Mental Health; Mental Health Services; Mental disorders; Methods; Minority Groups; Monitor; Mood Disorders; Motion; Patient Care; Patient Self-Report; Patients; Physicians; Privacy; Psychotic Disorders; Psychotic Mood Disorders; Qualitative Methods; Recommendation; Recording of previous events; Research; Research Personnel; Risk; Risk Assessment; Safety; Scholarship; Social Policies; Surveys; Technology; Therapeutic; Training; Translating; Translations; Trust; Voice; age group; behavioral health; chatbot; clinical care; community setting; computer science; dashboard; data management; digital; digital health; digital mental health; ethical legal social implication; expectation; experience; health application; health data; health information technology; improved; mHealth; neurotechnology; novel; patient subsets; programs; risk minimization; sensor; social implication; socioeconomics; tool; treatment adherence; uptake

Digital mental health technology (DMHT) –digital devices (smartphones, sensors) that can monitor and collect personal data from patients (tracking location/voice/motion, self-report), apply algorithms and machine learning (“ML”) to generate and integrate health and risk information (from genomics/family history), and even mediate care (monitoring treatment adherence or chatbot therapy)– is being integrated into mental health clinical care, with the goal of improving access, diagnostics and treatment for mental illness. DMHT poses novel ethical challenges because (1) use of DMHT disrupts traditional frameworks, such as the physician-patient dyad, for addressing ethical obligations and challenges in mental health care; (2) DMHT will contribute to the creation of novel and massive amount of behavioral data and risk categories, particularly when combined with other technologies, such as WGS, which may be difficult for clinicians and patients to evaluate and meaningfully use; and 3) behavioral health data will be created and used outside of frameworks for protecting the privacy of health data and may be experienced as surveillance by patients. The goals of the project are to: (1) examine how key stakeholders – DMHT developers, clinicians and patients – conceptualize and operationalize the ethical, legal and social implications of DMHT as it is translated into clinical care for the treatment of mood and psychotic disorders; and (2) use qualitative and quantitative methods to interview and survey clinicians, patients and consumers who use DMHT to examine the ethical, legal and social implications of the technology, particularly in relation to trust, privacy, data protection and management, and surveillance; and (3) provide improved understandings of how developers, patients, and clinicians perceive and manage ethical, legal and social implications of DMHT, that can be used as a foundation for further research and to provide guidance for ethical and safe use of digital technology in mental health care. he long-term goals of the project are to: 1) develop a research program exploring the ethical, legal and social implications of digital health technologies in mental health care and the potential impact on ethical frameworks in healthcare; 2) generate empirical research that improves understandings of the ethical, legal and social, implications of digital health technology; and 3) to improve understandings of the ethical issues involved in the use of DMHT to inform guidelines and social policy for the use of digital health technology in research, clinical, and community settings.

数字心理健康技术（DMHT）——数字设备（智能手机、传感器）可以

项目成果

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

• DOI: 10.2196/27343
• 发表时间: 2021-07-28
• 期刊: JMIR mHealth and uHealth
• 影响因子: 5
• 作者: Martinez-Martin N;Greely HT;Cho MK
• 通讯作者: Cho MK

Bridging the AI Chasm: Can EBM Address Representation and Fairness in Clinical Machine Learning?

• DOI: 10.1080/15265161.2022.2055212
• 发表时间: 2022-05
• 期刊: AMERICAN JOURNAL OF BIOETHICS
• 影响因子: 13.4
• 作者: Martinez-Martin, Nicole;Cho, Mildred K.
• 通讯作者: Cho, Mildred K.

Ethical issues in using ambient intelligence in health-care settings.

• DOI: 10.1016/s2589-7500(20)30275-2
• 发表时间: 2021-03
• 期刊: The Lancet. Digital health
• 作者: Martinez-Martin N;Luo Z;Kaushal A;Adeli E;Haque A;Kelly SS;Wieten S;Cho MK;Magnus D;Fei-Fei L;Schulman K;Milstein A
• 通讯作者: Milstein A

Addressing COVID-19 Health Disparities & Latinidad.

• DOI: 10.1080/15265161.2020.1871115
• 发表时间: 2021-03
• 期刊: AMERICAN JOURNAL OF BIOETHICS
• 影响因子: 13.4
• 作者: Martinez-Martin, Nicole

Envisioning a Path toward Equitable and Effective Digital Mental Health.

• DOI: 10.1080/21507740.2022.2082597
• 发表时间: 2022-07
• 期刊: AJOB neuroscience