JMIR Formative Research

Management of chronic recurrent medical conditions (CRMC), such as migraine headaches, chronic pain and anxiety/depression, is a major challenge for modern providers. The fact that often the most effective treatments and/or preventative measures for CRMCs vary from patient to patient lends itself to a platform for self-management by patients. However, to develop such an mHealth app requires an understanding of the various applications, and barriers, to real-world use. In this pilot study with in...

Digital self-guided mobile health (mHealth) applications are cost-effective, accessible, and well-suited to improve mental health at scale. This randomized controlled trial (RCT) evaluated the effectiveness of a recently developed mHealth programme based on cognitive-behavioral therapy (CBT) principles in improving worry. We also examined psychological mindedness (PM) as a mediator by which app engagement is thought to improve outcomes. The intervention group completed a 2-week "Anxiety and Worr...

BackgroundDigital health technologies are increasingly being used to monitor, assess, and treat depressive symptoms in the community. However, many such technologies rely on screening tools which were originally designed for use in primary care clinics, such as the Patient Health Questionnaire (PHQ-9). These scales are symptom-focused and do not capture the wider experiences of the patient. We developed a new screen for assessing depressive symptoms in a digital setting. Named the Mindstep Mood ...

BackgroundUnderstanding user engagement with conversational agents (CAs) in mobile health apps is crucial for improving sustained usage. We analyzed CA interactions in a mobile health app to identify usage patterns and potential barriers. Materials and MethodsRetrospective data from 100,571 active users of the Albert Health app in 2022 were analyzed. Interactions with CA were categorized by demographics (gender and age), interaction type (health information, medication-related, clinical paramet...

There is a growing interest to investigate the feasibility of using voice user interfaces as a platform for digital therapeutics in chronic disease management. While mostly deployed as smartphone applications, some demographics struggle when using touch screens and often cannot complete tasks independently. This research aimed to evaluate how heart failure patients interacted with a voice app version of an already existing digital therapeutic, Medly, using a mixed-methods concurrent triangulatio...

The global impact of COVID-19 pandemic has increased the need to rapidly develop and improve utilization of mobile applications across the healthcare continuum to address rising barriers of access to care due to social distancing challenges and allow continuity in sharing of health information, assist with COVID-19 activities including contact tracing, and providing useful information as needed. Here we provide an overview of mobile applications being currently utilized for COVID-19 related acti...

BackgroundDocumentation demands in psychiatric practice diminish time for direct patient care and are associated with clinician burnout. Ambient artificial intelligence (AI) scribes may facilitate more efficient and higher-quality documentation while reducing clinician workload and preserving the integrity of the clinical encounter. This study aims to determine the impact of an ambient AI scribe in improving documentation quality and efficiency while reducing clinician workload during simulated ...

Anxiety is highly prevalent among college communities, with significant numbers of students, faculty, and staff experiencing severe anxiety symptoms. Despite this high prevalence, many individuals remain untreated due to barriers such as time, stigma, waitlists, and cost of services. Digital mental health interventions (DMHIs), including Cognitive Bias Modification for Interpretation (CBM-I), offer promising solutions to enhance access to mental health care, yet there is a critical need to evalu...

Artificial intelligence (AI) large language models (LLMs) hold great potential to transform psychiatry and mental health care by delivering relevant and tailored mental health information. This study aimed to evaluate the quality of mental health information generated by LLMs by determining their level of accessibility, reliability, and interpreting any bias present. Generative Pre-trained Transformer-4 (GPT-4) (San Francisco, California: Open AI), Gemini 1.5 Flash (Mountain View, California: Go...

BackgroundConversational agents based on large language models (LLMs) have shown moderate efficacy in reducing depressive and anxiety symptoms. However, most existing evaluations lack methodological transparency, rely on closed-source models, and show limited standardization in performance and safety assessment. ObjectiveWe have two study objectives: (1) to develop an LLM-based conversational agent through system design analysis and initial functionality testing, and (2) to evaluate its safety ...

Peripartum depression (PPD) affects 12 to 25% pregnant women worldwide, yet screening often misses real-time symptom changes. Digital phenotyping (DP) offers a promising support, using data like text entries or sleep tracking to detect PPD. This review (PROSPERO: CRD42023461325) evaluated 14 studies, highlighting the substantial potential of personal history and semi-random ecological-momentary data. Future work should focus on improving models and advancing their translation into clinical setti...

Timely support after referral to mental healthcare is crucial, yet patients often face prolonged wait times without intervention. Digital mental health interventions offer scalable solutions, but many struggle to achieve acceptable patient engagement. Tailoring and personalizing materials to individual needs is paramount for driving engagement, a task that generative artificial intelligence AI (genAI) is potentially able to achieve. To examine this promise, we conducted a randomized controlled t...

This research evaluates the usability of Pathpoint(R) Outcomes Software, aligning with IEC 62366-1:2015 standards to ensure rigour and accuracy. The study involved diverse user groups like Healthcare Professionals and the General Population to provide varied perspectives. The study focused on the softwares usability, safety, and effectiveness, which are crucial to user experience, satisfaction, and performance. Any potential risks to users or patient data were identified to ensure safety standar...

BackgroundIn Germany, most patients with coronavirus disease 2019 (COVID-19) are treated in an outpatient setting. To improve assessments of the health status of COVID-19 outpatients, various remote monitoring models have been developed. However, little information exists on experiences acquired with remote monitoring in an outpatient setting, particularly from a patient perspective. The aim of our COVID-19@home study was therefore to implement and evaluate an app-based remote monitoring concep...

People with and without disabilities sought information online during the initial onset of COVID-19 during the official public health emergency from March 2020 to May 2023. After the public health emergency ended, though, there has been little information to assess the user experience of online health information seeking with respect to COVID-19, which remains a public health concern, in people with and without disabilities. The goal of this research is to assess the extent to which online conte...

BackgroundIn recent years, Instagram has become the most popular tool among professional doctors in Azerbaijan for educating their patients. The use of the Instagram application aims to raise patients awareness of the importance of taking care of their health and to increase their knowledge about their health conditions using modern services. In this article, the authors examine the quality of Instagram content for health education among the population. MethodsWe conducted a survey to collect a...

BackgroundEmergency physicians face considerable workflow challenges in the emergency department (ED) due to unpredictable work environments, frequent interruptions, and mounting documentation requirements. Excessive time away from direct patient care is increasingly viewed as detrimental to care quality, communication, and patient safety. ObjectiveThis study aimed to quantify and visualize how emergency physicians allocate their time during ED shifts, particularly time spent on the computer. ...

RationaleA reliable and valid instrument is needed to measure exposure to psychedelic-related media to examine the impact of media and expectations on outcomes in psychedelic clinical trials. ObjectivesOur aim was to explore the psychometric properties of the Psychedelic Media Exposure Questionnaire (PMEQ) and to validate the scale. MethodsFirst, items were developed by a team of experts, reviewed by external expert collaborators, and revised. Psychometric validation of the PMEQ was carried ou...

The pressure on healthcare is increasing worldwide. The trend toward digitalization in recent decades and the emergence of modern technologies have enabled remote treatment and offered patients new ways to interact with physicians. Despite numerous studies showing promising results in the use of video calls for primary care consultations, some survey studies report lingering doubts about the effectiveness of this method among general practitioners (GPs) and patients. Because the organization of ...

ObjectiveAifred is an artificial intelligence (AI)-powered clinical decision support system (CDSS) for the treatment of major depression. Here, we explore use of a simulation centre environment in evaluating the usability of Aifred, particularly its impact on the physician-patient interaction. MethodsTwenty psychiatry and family medicine attending staff and residents were recruited to complete a 2.5-hour study at a clinical interaction simulation centre with standardized patients. Each physicia...