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Medication adherence is important for glycaemic control. However, less than half of those with Type 2 diabetes take medications as prescribed. One of the known barriers to medication adherence is forgetfulness. Given the current ubiquity of smartphones, diabetes self‐management apps represent a valuable avenue for providing medication reminders to help users adhere to their medication treatments and improve health outcomes. We assessed 181 diabetes management apps for the presence of medication reminder features and compared their characteristics with the evidence provided in studies showing the effectiveness of SMS reminders. We found that only 55.8% of the apps had a basic medication reminder function, although those that had them conformed to the characteristics of SMS reminders shown to be effective. This is an important missed opportunity for diabetes management apps to contribute not only to improving medication adherence, but also in having a positive effect on the health outcomes of this population. [ABSTRACT FROM AUTHOR]

• This research answers the call for longitudinal studies on cyberchondria. • Health anxiety at Wave 1 had a cross-lagged effect on information insufficiency at Wave 2. • Information insufficiency at Wave 1 increased online health information seeking (OHIS) at Wave 2, which further predicted cyberchondria at Wave 3. • With few exemptions, health anxiety, information insufficiency, and OHIS increased cyberchondria across study waves. Cyberchondria describes online health information seeking (OHIS) in an excessive pattern, along with other characteristics, including distress, reassurance, and compulsion. Drawing upon the risk information seeking and processing model and the hybrid model of cyberchondria, this study investigated how health anxiety, information insufficiency, OHIS contributed to cyberchondria over time. We conducted a three-wave panel survey in China (N = 1,271, W 1 in June 2021; N = 816, W 2 in July 2021; N = 654, W 3 in August 2021). Results of a cross-lagged panel model demonstrated that health anxiety at Wave 1 had a cross-lagged effect on information insufficiency at Wave 2. Moreover, information insufficiency at Wave 1 increased OHIS at Wave 2, which further predicted cyberchondria at Wave 3. Health anxiety, information insufficiency, and OHIS were directly and positively related to cyberchondria across the waves, except that information insufficiency at Wave 1 did not predict cyberchondria at Wave 2. This study documented the dynamic and intricate processes underlying the development of cyberchondria, providing both theoretical and practical insights in this nascent research area. [ABSTRACT FROM AUTHOR]

Social support and resilience were considered to be two significant influential factors for depression in late life. The study aims to present a mediation model for understanding the interrelations among social support, resilience, and geriatric depression. A cross-sectional survey study was conducted among 162 community-dwelling Chinese older adults in Singapore. Findings indicated a significant indirect effect of social support on geriatric depression through the mediation of resilience, by controlling demographic variables. Further, an identical influencing pattern between problem-solving resilience and emotion regulation resilience were found in the two individual models, suggesting a similar mediation role in linking social support and geriatric depression. These results extended and integrated earlier findings on the relationship of psychosocial factors and geriatric depression, and pointed out practical implications for future work on depression interventions. [ABSTRACT FROM AUTHOR]

• A theoretical model is proposed to describe how individuals develop cyberchondria when they seek medical information on the Internet. • Cyberchondria is conceptualized as a negative outcome of online health information seeking, including a set of patterns (i.e., excessiveness, compulsion, distress, and reassurance). • Perceived health threat of common symptoms can be a trigger of health anxiety that motivates online health information seeking through the perception of information insufficiency. • Negative metacognitive beliefs provide a boundary condition for how regular online health information seeking results in cyberchondria. Cyberchondria describes excessive online health searches associated with increased emotional distress. While previous research has examined various antecedents of cyberchondria, how regular online health information seeking (OHIS) turns into cyberchondria has received minimal theoretical attention. This study proposes a theoretical model that illuminates the processes of cyberchondria development among individuals who are anxious about their health. Results from an online survey of 426 Chinese Internet users lend support to the proposed theoretical model, which posits perceived health threat of common symptoms as a trigger of health anxiety that motivates OHIS through the perception of information insufficiency. In this process, positive source beliefs strengthen the effect of information insufficiency on OHIS. This study further identifies negative metacognitive beliefs as a boundary condition for how regular OHIS results in cyberchondria. By conceptualizing the processes of cyberchondria development, this integrative model provides guidance for future theory development and testing in this new research area. [ABSTRACT FROM AUTHOR]

Background: The risk of development of chronic diseases related to poor nutrition increases with age. In the face of an aging population, it is important for health care sectors to find solutions in delivering health services efficiently and effectively to middle-aged and older adults.Objective: The aim of this systematic review and meta-analysis was to consolidate the literature that reported the effectiveness of eHealth apps in delivering nutritional interventions for middle-aged and older adults.Methods: A literature search from five databases (PubMed, CINAHL, Cochrane, Web of Science, and Global Health) from the past 5 years was performed. Studies were selected for inclusion that used eHealth to deliver nutritional interventions to adults aged 40 years and above, and reported health and behavioral outcomes. Two independent reviewers searched for research articles and assessed the eligibility of studies to be included in the review. A third reviewer resolved disagreements on study inclusion. We also assessed the quality of the included studies using the CONSORT 2010 checklist.Results: A total of 70 studies were included for analysis. The study quality ranged from 44% to 85%. The most commonly used eHealth intervention type was mobile apps (22/70, 31%). The majority of studies (62/70, 89%) provided multicomponent health interventions, which aimed to improve nutrition and other health behaviors (eg, exercise, smoking cessation, medication adherence). Meta-analysis results indicated high and significant heterogeneity; hence, conclusions based on these results should be considered with caution. Nonetheless, the results generally showed that eHealth interventions improved anthropometric and clinical outcomes, but not behavioral outcomes such as fruit and vegetable consumption.Conclusions: The use of eHealth apps to deliver health interventions has been increasing in recent years, and these apps have the potential to deliver health services to a larger group of people. Our findings showed that the effectiveness of eHealth apps to deliver health interventions for middle-aged to older adults was supported by the improvement of anthropometric and clinical outcomes. Future work could aim to develop research frameworks in administering eHealth interventions to address heterogeneity in this field of research. [ABSTRACT FROM AUTHOR]

Background: Conversational agents, also known as chatbots, are computer programs designed to simulate human text or verbal conversations. They are increasingly used in a range of fields, including health care. By enabling better accessibility, personalization, and efficiency, conversational agents have the potential to improve patient care.Objective: This study aimed to review the current applications, gaps, and challenges in the literature on conversational agents in health care and provide recommendations for their future research, design, and application.Methods: We performed a scoping review. A broad literature search was performed in MEDLINE (Medical Literature Analysis and Retrieval System Online; Ovid), EMBASE (Excerpta Medica database; Ovid), PubMed, Scopus, and Cochrane Central with the search terms "conversational agents," "conversational AI," "chatbots," and associated synonyms. We also searched the gray literature using sources such as the OCLC (Online Computer Library Center) WorldCat database and ResearchGate in April 2019. Reference lists of relevant articles were checked for further articles. Screening and data extraction were performed in parallel by 2 reviewers. The included evidence was analyzed narratively by employing the principles of thematic analysis.Results: The literature search yielded 47 study reports (45 articles and 2 ongoing clinical trials) that matched the inclusion criteria. The identified conversational agents were largely delivered via smartphone apps (n=23) and used free text only as the main input (n=19) and output (n=30) modality. Case studies describing chatbot development (n=18) were the most prevalent, and only 11 randomized controlled trials were identified. The 3 most commonly reported conversational agent applications in the literature were treatment and monitoring, health care service support, and patient education.Conclusions: The literature on conversational agents in health care is largely descriptive and aimed at treatment and monitoring and health service support. It mostly reports on text-based, artificial intelligence-driven, and smartphone app-delivered conversational agents. There is an urgent need for a robust evaluation of diverse health care conversational agents' formats, focusing on their acceptability, safety, and effectiveness. [ABSTRACT FROM AUTHOR]

Background: Recently, many studies have been conducted to investigate the effects of exergames on the social well-being of older adults.Objective: The aim of this paper is to synthesize existing studies and provide an overall picture on the social effects of exergames on older adults.Methods: A comprehensive literature search with inclusive criteria was conducted in major social science bibliographic databases. The characteristics of exergames, participants, methodology, as well as outcome measurements were extracted from the relevant studies included in the review. The bibliometric and altmetric outreach of the included studies were also investigated.Results: A total of 10 studies were included in the review, with 8 studies having used the Nintendo Wii platform. Most of the studies recruited healthy older adults from local communities or senior activity centers. Three groups of social-related outcomes have been identified, including emotion-related, behavior-related, and attitude-related outcomes. A metric analysis has shown that the emotion-related and behavior-related outcomes received high attention from both the academic community and social media platforms.Conclusions: Overall, the majority of exergame studies demonstrated promising results for enhanced social well-being, such as reduction of loneliness, increased social connection, and positive attitudes towards others. The paper also provided implications for health care researchers and exergame designers. [ABSTRACT FROM AUTHOR]