JMIR Formative Research

The potential of artificial intelligence (AI) chatbots, particularly ChatGPT with GPT-4 (OpenAI), in assisting with medical diagnosis is an emerging research area. However, it is not yet clear how well AI chatbots can evaluate whether the final diagnosis is included in differential diagnosis lists.

Multidisciplinary clinics (MDCs) provide benefits to patients with amyotrophic lateral sclerosis (ALS) and their caregivers, but MDC visits are information-heavy and can last 4 hours, with patients and caregivers meeting with multiple specialists within each MDC visit. There are questions about the effectiveness of current methods of sharing information from MDCs with patients. Video recordings are a promising new method of sharing information that may allow patients and caregivers to revisit the MDC and remind them of clinical recommendations and conversations.

Age-related vision changes significantly contribute to fatal crashes at night among older drivers. However, the effects of lighting conditions on age-related vision changes and associated driving performance remain unclear.

Meaning in life is positively associated with health, well-being, and longevity, which may be partially explained by engagement in healthier behaviors, including physical activity (PA). However, promoting awareness of meaning is a behavior change strategy that has not been tested in previous PA interventions.

Accelerated digitalization in the health sector requires the development of appropriate evaluation methods to ensure that digital health technologies (DHTs) are safe and effective. Software as a medical device (SaMD) is a commonly used DHT by clinicians to provide care to patients. Traditional research methods for evaluating health care products, such as randomized clinical trials, may not be suitable for DHTs, such as SaMD. However, evidence to show their safety and efficacy is needed by regulators before they can be used in practice. Clinical simulation can be used by researchers to test SaMD in an agile and low-cost way; yet, there is limited research on criteria to assess the robustness of simulations and, subsequently, their relevance for a regulatory decision.

Large-scale crisis events such as COVID-19 often have secondary impacts on individuals’ mental well-being. University students are particularly vulnerable to such impacts. Traditional survey-based methods to identify those in need of support do not scale over large populations and they do not provide timely insights. We pursue an alternative approach through social media data and machine learning. Our models aim to complement surveys and provide early, precise, and objective predictions of students disrupted by COVID-19.

Measurement-based care in behavioral health uses patient-reported outcome measures (PROMs) to screen for mental health symptoms and substance use and to assess symptom change over time. While PROMs are increasingly being integrated into electronic health record systems and administered electronically, paper-based PROMs continue to be used. It is unclear if it is feasible to administer a PROM on paper when the PROM was initially developed for electronic administration.

Timely detection of stress in people with dementia and people with an intellectual disability (ID) may reduce the occurrence of challenging behavior. However, detecting stress is often challenging as many long-term care (LTC) residents with dementia and residents with ID have communication impairments, limiting their ability to express themselves. Wearables can help detect stress but are not always accepted by users and are uncomfortable to wear for longer periods. Integrating sensors into clothing may be a more acceptable approach for users in LTC. To develop a sensor system for early stress detection that is accepted by LTC residents with dementia and residents with ID, understanding their perceptions and requirements is essential.

The longevity of the world population can contribute to an increase in hospitalizations and, consequently, to the emergence of functional limitations, resulting in the need for family caregivers. Hospitalized older adults may become dependent and require more care, increasing the burden on family caregivers. Thus, the nursing team in the hospital environment faces a new situation: an increase in the number of older adults occupying hospital beds and the presence of their family caregivers.

Mobile health (mHealth) apps have proven useful for people with multiple sclerosis (MS). Thus, easy-to-use digital solutions are now strongly required to assess and monitor cognitive impairment, one of the most disturbing symptoms in MS that is experienced by almost 43% to 70% of people with MS. Therefore, we developed DIGICOG-MS (Digital assessment of Cognitive Impairment in Multiple Sclerosis), a smartphone- and tablet-based mHealth app to self-assess cognitive impairment in MS.

The Mediterranean diet has been linked to reduced risk for several cardiometabolic diseases. The lack of a clear definition of the Mediterranean diet in the scientific literature and the documented proliferation of nutrition misinformation on the internet suggest the potential for confusion among consumers seeking web-based Mediterranean diet information.

Chronic pain is prevalent in our society, with conditions such as fibromyalgia being notably widespread. The gold standard for aiding individuals dealing with chronic pain involves interdisciplinary approaches rooted in a biopsychosocial perspective. Regrettably, access to such care is difficult for most of the people in need. Information and communication technologies (ICTs) have been used as a way of overcoming access barriers (among other advantages).