Journal of Participatory Medicine

Patient engagement in research represents an evolution in how new knowledge is being created. Individuals and teams seeking to conduct research in this way want to learn how to best approach this work. Specialized training is required to ensure that these individuals and groups have the knowledge and skills to engage with and accomplish these goals. We developed an on-line training program, called Patient-Oriented Research Training & Learning - Primary Health Care (PORTL-PHC), to address this need.

Patient portals demonstrate significant potential for improving healthcare engagement but face critical adoption challenges. Disparities persist across different demographic groups, creating a digital divide in healthcare access. Targeted training strategies, particularly personalized and one-on-one approaches, show promise in increasing portal utilization. Innovative solutions, like community health workers specializing in digital navigation, offer a potential pathway to reduce enrollment barriers. The key challenge remains developing a scalable, cost-effective training model.

This paper will view the rise of the e-patient, who is “equipped, enabled, empowered and engaged” through the lens of the evolution of successive digital technology innovations, each building on its predecessors, creating new tools for patient empowerment. We begin with the dawn of the Web and the proliferation of health websites and discuss the use of digital communication tools. We then discuss the adoption of electronic health records which enabled the rise of patient portals. This digitization of health data, along with the rapid adoption of mobile internet access and the proliferation of health-related smartphone apps, in turn, provided a platform for patients to co-produce healthcare by contributing their own health data to their self-care and healthcare. The exchange of health information between patients and providers has also been facilitated by telehealth/telemedicine technology which enables direct care delivery. The use of social networks in health, in use since the early days of the Web, has expanded since COVID, when public health authorities worldwide, as well as patients, sought the use of social media channels to get connected and share information. Most recently, artificial intelligence and large language models have emerged with yet untapped potential to provide patients with the information that could improve their understanding of their conditions and treatment options. We conclude that innovations in digital health technology have symbiotically evolved with the ascendance of the e-patient, enabling improved communication, collaboration, and coordination between patients and clinicians and forging a healthcare system that is safer and more responsive to patient needs.

Chronic wounds affect 1-2% of the global population, and pose significant health and quality-of-life challenges for patients and caregivers. Advances in artificial intelligence (AI) and computer vision (CV) technologies present new opportunities for enhancing wound care, particularly through remote monitoring and patient engagement. A Digital Wound Care Solution (DWCS) that facilitates wound tracking using AI/CV was redesigned as a patient-facing mobile application to empower patients and caregivers to actively participate in wound monitoring and management.

Clinical trial registries were designed to help patients search for potentially suitable clinical trials. When our family faced another serious cancer diagnosis, we searched multiple international clinical trial registries. Despite increasing evidence that trials designed WITH patients can be better for trial participants (eg, more relevant outcome measures, fewer burdens), it is currently impossible to search registries for these specific types of trials. In this Patient Perspective article, we make the first ‘call to action’ for clinical trial registries to include (1) a filter that allows for efficient searching for clinical trials designed with patients and (2) structured information, in plain language, on how patients were involved. We propose how these two innovations could help reduce barriers to clinical trial participation. We also highlight how new regulatory and ethical guidelines are encouraging patient involvement in trial design and we identify the benefits to many of doing so. Given the pressing need to improve clinical trial participation, we respectively call on the clinical trial community to respond to our ‘call to action’ and consider our proposed action plan. Ideally, when patients want to search for clinical trials designed with patients for patients, we should be able to find them. A plain language summary for this publication is available (Supplementary File 1).

The proliferation of AI mental health chatbots, such as those on platforms like OpenAI’s GPT Store and Character.AI, raises issues of safety, effectiveness, and ethical use; they also raise an opportunity for patients and consumers to ensure AI tools clearly communicate how they meet their needs. While many of these tools claim to offer therapeutic advice, their unregulated status and lack of systematic evaluation create risks for users, particularly vulnerable individuals. This viewpoint article highlights the urgent need for a standardized framework to assess and demonstrate the safety, ethics, and evidence basis of AI chatbots used in mental health contexts. Drawing on clinical expertise, research, co-design experience, and WHO guidance, the authors propose key evaluation criteria: adherence to ethical principles, evidence-based responses, conversational skills, safety protocols, and accessibility. Implementation challenges, including setting output criteria without one ‘right answer’, evaluating multi-turn conversations, and involving experts for oversight at scale, are explored. The authors advocate for greater consumer engagement in chatbot evaluation to ensure these tools address user needs effectively and responsibly, emphasizing the ethical obligation of developers to prioritize safety and a strong base in empirical evidence.

The Pancreatic Cancer Action Network (PanCAN) established its Patient Registry to gather real-world data from patients with pancreatic cancer and their caregivers, related to their diagnosis, symptoms and symptom management, treatments, and more. Described here are results from version 2 of the PanCAN Registry.

Artificial intelligence (AI) and large language models (LLMs) offer significant potential to enhance many aspects of daily life. Patients and caregivers are increasingly using AI for their own knowledge and to address personal challenges. The growth of AI has been extraordinary; however, the field is only beginning to explore its intersection with participatory medicine. For many years, the Journal of Participatory Medicine has published insights on tech-enabled patient empowerment and strategies to enhance patient-clinician relationships. This theme issue on Patient and Consumer Use of AI for Health to explore the use of AI for health from the perspective of patients and the public.

Surgical ward rounds (SWRs) are typically led by doctors, with limited involvement from key participants, including patients, family members, and bedside nurses. Despite the potential benefits of a more collaborative and person-centered approach, efforts to engage these stakeholders remain rare.

Smartphone apps can improve access to bipolar disorder (BD) care by delivering elements of effective psychological interventions, thereby promoting quality of life and reducing relapse risk and mood instability in BD. While many people with BD are interested in using publicly available mental health smartphone apps, without guidance, they risk selecting apps that are unsafe or ineffective.

Low retention and adherence increase clinical trial costs and timelines. Burdens associated with participating in a clinical trial contribute to early study termination. Electronic patient reported outcome (ePRO) tools reduce participant burden by allowing remote participation, and facilitate communication between researchers and participants. The Datacubed Health (DCH) mobile application is unique among ePRO platforms in its application of behavioral science principles (reward, motivation, identity, etc.) in clinical trials to promote engagement, adherence, and retention.

Newborn screening aims to identify babies affected by rare but serious genetic conditions. As technology advances, there is the potential to expand the newborn screening program following evaluation of the likely benefits and drawbacks. To inform these decisions, it is important to consider the family experience of screening and the views of the public. Engaging in public dialogue can be difficult. The conditions, screening processes, and associated moral and ethical considerations are complex.