Related papers: Designing Value-Centered Consent Interfaces: A Mix…
Routinely collected clinical patient data posits a valuable resource for data-driven medical innovation. Such secondary data use for medical research purposes is dependent on the patient's consent. To gain an understanding of the patients'…
Health information technologies are transforming how mental healthcare is paid for through value-based care programs, which tie payment to data quantifying care outcomes. But, it is unclear what outcomes data these technologies should…
Consent is an ethical cornerstone of clinical research and healthcare in general. Although the ethical principles of consent - providing information, ensuring comprehension, and ensuring voluntariness - are well-defined, the technological…
This thesis addresses the question of how usable openEHR-aware clinical decision support can be designed and developed in order to improve the quality of health care. To answer this research question, several sub-questions were identified…
The field of digital mental health is advancing at a rapid pace. Passively collected data from user engagements with digital tools and services continue to contribute new insights into mental health and illness. As the field of digital…
De-identified health data are frequently used in research. As AI advances heighten the risk of re-identification, it is important to respond to concerns about transparency, data privacy, and patient preferences. However, few practical and…
In modern healthcare systems, being able to share electronic health records is crucial for providing quality care and for enabling a larger spectrum of health services. Health data sharing is dependent on obtaining individual consent which,…
This paper presents the first multistakeholder approach for translating diverse stakeholder values into an evaluation metric setup for Recommender Systems (RecSys) in digital archives. While commercial platforms mainly rely on engagement…
Patient-controlled data-sharing systems are increasingly promoted as a way to empower patients with greater autonomy over their health data. Yet it remains unclear how different stakeholders, especially patients and health system leaders,…
Artificial intelligence (AI)-based computer perception (CP) technologies use mobile sensors to collect behavioral and physiological data for clinical decision-making. These tools can reshape how clinical knowledge is generated and…
There is a clear need to involve patients in medical decisions. However, cognitive psychological research has highlighted the cognitive limitations of humans with respect to 1. Probabilistic assessment of the patient state and of potential…
While companies increasingly rely on data, especially when it comes to targeted advertising, adapting content to users, selling data and training machine learning models, the collection of data raises privacy concerns. One way of collecting…
Social media are a rich source of insight for data mining and user-centred research, but the question of consent arises when studying such data without the express knowledge of the creator. Case studies that mine social data from users of…
In the era of digital health and artificial intelligence, the management of patient data privacy has become increasingly complex, with significant implications for global health equity and patient trust. This paper introduces a novel…
Respect for persons is a cornerstone value for any conception of research ethics--though how to best realize respect in practice is an ongoing question. In the late 19th and early 20th centuries, "informed consent" emerged as a particular…
In pediatrics, patients, caregivers, and clinicians share responsibility for health decisions, but limited collaboration can undermine outcomes. We conducted a qualitative study examining decision-makers perceptions toward collaborative…
While automated experiments and high-throughput methods are becoming more mainstream in the age of data, empowering individual researchers to capture, collate, and contextualize their data faster and more reproducibly still remains a…
Datasets play a key role in imparting advanced capabilities to artificial intelligence (AI) foundation models that can be adapted to various downstream tasks. These downstream applications can introduce both beneficial and harmful…
Developing robust and fair AI systems require datasets with comprehensive set of labels that can help ensure the validity and legitimacy of relevant measurements. Recent efforts, therefore, focus on collecting person-related datasets that…
Privacy policies are intended to support informed consent, yet users rarely read them fully. This study examines how common privacy policy interface structures influence attention allocation, reading behavior, and perceived experience.…