JMIR Formative Research

Alcohol and tobacco use frequently co-occur and contribute significantly to the global burden of disease. Despite the well-established benefits of addressing both behaviors simultaneously, health care professionals often face substantial challenges in delivering integrated interventions, including limited time, training, and resources. Digital health interventions offer a promising avenue to directly support patients in reducing alcohol and tobacco use, while bypassing some of the barriers encountered in clinical settings. However, there is a lack of consensus on the key behavior change techniques (BCTs) that must be incorporated to ensure that interventions are evidence based and contextually appropriate, making them effective.

Digital health data and infrastructure facilitate rapid analysis to provide actionable data, thereby fulfilling the principles of a learning health system. In response to a report from the UK Medicines and Healthcare Products Regulatory Agency (MHRA), a rapid service evaluation was carried out to identify patterns of modified-release (MR) opioid use after elective surgery.

Determining the appropriate dosage of pediatric occupational therapy, physical therapy, and speech-language pathology services is important when supporting families of children with disabilities. However, therapy dosage is inconsistently reported, and caregiver-delivered practice between sessions is rarely documented. Ecological momentary assessment (EMA) offers a method to capture caregiver practice in real time and to examine factors that influence it.

Virtual reality (VR) is increasingly used for adjunctive relaxation training in psychiatric care. However, evidence remains limited among hospitalized patients with depressive disorders, particularly in routine inpatient settings in China, and little is known about whether improvement varies by session frequency.

Informal caregivers of people living with dementia often experience high rates of caregiver burnout while providing care. Although there are many websites and mobile apps available to help caregivers, many do not use digital tools. The Olera platform was developed to be an easily adoptable web-based support tool, connecting caregivers with long-term services and supports, financial assistance, and educational resources. The platform was developed based on the Build-Measure-Learn framework with input from caregiver needs assessments and usability studies.

Machine learning models for surgical applications require large, diverse datasets; however, data scarcity remains a critical limitation due to privacy regulations, institutional variability, and the rarity of many surgical procedures. Large language models (LLMs) offer a potential solution through synthetic data generation, but their performance and reliability in specialized surgical domains remain underexplored.

Depressive symptoms are common among older adults and can significantly impact their quality of life. However, many older adults face barriers to accessing psychological treatment. Internet-based cognitive behavioral therapy (iCBT) is a promising alternative to face-to-face treatments, but its feasibility among older adults has been less extensively studied than in adult populations.

Dysarthria is a frequent motor speech disorder following a stroke, affecting up to 42% of survivors and resulting in reduced speech intelligibility and diminished quality of life. Clinical assessments, such as the Frenchay Dysarthria Assessment, Second Edition (FDA-2), rely heavily on the subjective judgment of speech-language pathologists (SLPs), which limits comparability and scalability. Telepractice solutions have the potential to extend access to care, but validated digital tools that combine automatic analysis with clinically usable interfaces remain scarce.

In recent years, artificial intelligence (AI) has ushered in a promising era in medicine, particularly in medical education. However, studies assessing the knowledge, attitudes, and practices related to AI among medical students in Vietnam remain limited.

Digital health offers opportunities to facilitate symptom assessments and communication for children with cancer, particularly after discharge. However, access to these tools must be established to ensure that they effectively support the user. PicPecc (Pictorial Support in Person-Centered Care for Children) is a mobile health tool developed to enable children to remotely assess symptoms and communicate with health care professionals. Understanding access to PicPecc is essential for evaluating its use in pediatric oncology.

Medical interview training faces limitations in both implementation and evaluation. While generative artificial intelligence (GenAI) offers a potential solution, it remains unclear whether reasoning-oriented models improve evaluation, particularly for the Japanese language.

Optic disc tilt is a morphological change in myopic eyes that complicates clinical interpretation and artificial intelligence (AI)–based analysis of fundus images. Accurate detection of optic disc tilt is necessary to avoid misinterpretation of disc morphology and enhance diagnostic reliability across different disease types.