Journal of Medical Internet Research

With increasing adoption of remote clinical trials in digital mental health, identifying cost-effective and time-efficient recruitment methodologies is crucial for the success of such trials. Evidence on whether web-based recruitment methods are more effective than traditional methods such as newspapers, media, or flyers is inconsistent. Here we present insights from our experience recruiting tertiary education students for a digital mental health artificial intelligence–driven adaptive trial—Vibe Up.

In online mental health communities, the interactions among members can significantly reduce their psychological distress and enhance their mental well-being. The overall quality of support from others varies due to differences in people’s capacities to help others. This results in some support seekers’ needs being met, while others remain unresolved.

Artificial intelligence (AI) social chatbots represent a major advancement in merging technology with mental health, offering benefits through natural and emotional communication. Unlike task-oriented chatbots, social chatbots build relationships and provide social support, which can positively impact mental health outcomes like loneliness and social anxiety. However, the specific effects and mechanisms through which these chatbots influence mental health remain underexplored.

Speech sound disorders (SSDs) are common communication challenges in children, typically assessed by speech-language pathologists (SLPs) using standardized tools. However, traditional evaluation methods are time-intensive and prone to variability, raising concerns about reliability.

This study examines disparities in research retractions due to misconduct, identifying countries with the highest retraction counts and those disproportionately represented relative to population and publication output. The findings emphasize the need for improved research integrity measures.

The COVID-19 pandemic, declared in March 2020, profoundly affected global health, societal, and economic frameworks. Vaccination became a crucial tactic in combating the virus. Simultaneously, the pandemic likely underscored the internet’s role as a vital resource for seeking health information. The proliferation of misinformation on social media was observed, potentially influencing vaccination decisions and timing.

Increasing life expectancy has led to a rise in nursing home admissions, a context in which older adults often experience chronic physical and mental health conditions, chronic pain, and reduced well-being. Nonpharmacological approaches are especially important for managing older adults’ chronic pain, mental health conditions (such as anxiety and depression), and overall well-being, including sensory stimulation (SS) and therapist support (TS). However, the combined effects of SS and TS have not been investigated.

If the most evidence-based and effective smoking cessation apps are not selected by smokers wanting to quit, their potential to support cessation is limited.

HIV/AIDS remains a significant global challenge, and with the rapid advancement of technology, there has been an increasing number of interventions aimed at improving HIV/AIDS cognition and self-management behaviors among patients. However, there is still a lack of detailed literature integrating relevant evidence.

Despite the ample benefits of physical activity (PA), many individuals do not meet the minimum PA recommended by health organizations. Structured questionnaires and interviews are commonly used to study why individuals perform PA and their strategies to adhere to PA. However, certain biases are inherent to these tools that limit what can be concluded from their results. Collecting data from social media channels can complement these studies and provide a more comprehensive overview of PA motives and adherence strategies.

The escalating global scarcity of skilled health care professionals is a critical concern, further exacerbated by rising stress levels and clinician burnout rates. Artificial intelligence (AI) has surfaced as a potential resource to alleviate these challenges. Nevertheless, it is not taken for granted that AI will inevitably augment human performance, as ill-designed systems may inadvertently impose new burdens on health care workers, and implementation may be challenging. An in-depth understanding of how AI can effectively enhance rather than impair work conditions is therefore needed.

Diabetes, a chronic disease necessitating long-term treatment and self-management, presents significant challenges for patients who spend most of their treatment time outside of hospitals. The potential of digital therapeutics for diabetes has garnered recognition from different organizations. Although some prior studies have demonstrated successful reductions in patients’ blood glucose levels and body weight through digital diabetes programs, many studies were limited by including patients with prediabetes, including patients treated with mostly premixed insulin, or evaluating user engagement outcomes rather than clinical outcomes. Consequently, limited evidence remains regarding the effectiveness of health management mobile apps specifically designed for patients with type 2 diabetes mellitus (T2DM) initiating basal insulin (BI). Based on this, a data-based and artificial intelligence management system named “TRIO” was developed to provide patients with more personalized intervention methods in stages, in groups, and around the clock. TRIO assists doctors and nurses in achieving better blood glucose controls, truly carries out standardized management around patients, and allows them to have a higher quality of life. TRIO represents the 3 essential pillars in comprehensive diabetes management: physician, nurse, and patient.