Aging and Engaging: A Pilot Randomized Controlled Trial of an Online Conversational Skills Coach for Older Adults

Roles, Users, Benefits, and Limitations of Chatbots in Health Care: Rapid Review

BACKGROUND

Chatbots, or conversational agents, have emerged as significant tools in health care, driven by advancements in artificial intelligence and digital technology. These programs are designed to simulate human conversations, addressing various health care needs. However, no comprehensive synthesis of health care chatbots' roles, users, benefits, and limitations is available to inform future research and application in the field.

OBJECTIVE

This review aims to describe health care chatbots' characteristics, focusing on their diverse roles in the health care pathway, user groups, benefits, and limitations.

METHODS

A rapid review of published literature from 2017 to 2023 was performed with a search strategy developed in collaboration with a health sciences librarian and implemented in the MEDLINE and Embase databases. Primary research studies reporting on chatbot roles or benefits in health care were included. Two reviewers dual-screened the search results. Extracted data on chatbot roles, users, benefits, and limitations were subjected to content analysis.

RESULTS

The review categorized chatbot roles into 2 themes: delivery of remote health services, including patient support, care management, education, skills building, and health behavior promotion, and provision of administrative assistance to health care providers. User groups spanned across patients with chronic conditions as well as patients with cancer; individuals focused on lifestyle improvements; and various demographic groups such as women, families, and older adults. Professionals and students in health care also emerged as significant users, alongside groups seeking mental health support, behavioral change, and educational enhancement. The benefits of health care chatbots were also classified into 2 themes: improvement of health care quality and efficiency and cost-effectiveness in health care delivery. The identified limitations encompassed ethical challenges, medicolegal and safety concerns, technical difficulties, user experience issues, and societal and economic impacts.

CONCLUSIONS

Health care chatbots offer a wide spectrum of applications, potentially impacting various aspects of health care. While they are promising tools for improving health care efficiency and quality, their integration into the health care system must be approached with consideration of their limitations to ensure optimal, safe, and equitable use.

Senescence Seclusion Syndrome: Appraising the Efficacy of Current Interventions

The proportion of senior citizens in the global population has been on a steady rise, and the current population is forecasted to double in a few decades. Against this backdrop, the prevalence of senescence seclusion syndrome, characterized by prolonged social isolation in the elderly, is increasing concurrently. Given the profound threats this syndrome poses to the mental, physical, and social well-being of this vulnerable demographic, implementing effective interventions is imperative to mitigate these threats and enhance the quality of life. This review aims to assess the efficacy of the interventional modalities critically. Studies were reviewed following comprehensive searches in databases such as PubMed, Scopus, and Google Scholar, and focusing on empirical studies from 2019 to 2024 that evaluated the efficacy of the major intervention categories - social, technological, psychological, and physical interventions. The findings indicate that initiatives that promote consistent social engagement, such as community-organized social events and structured group activities, significantly reduced loneliness and bolstered social connections. Furthermore, technological interventions, including artificial intelligence and virtual reality, have notably enhanced elderly connectivity with their communities. Additionally, psychological interventions, such as cognitive-behavioral therapy, have also been effective in alleviating symptoms of anxiety and depression associated with the syndrome, with group sessions enhancing social interaction and significantly diminishing isolation. Moreover, physical interventions involving group exercises and other activities have fostered improvements in the physical, mental, and social well-being of the elderly. This study underscores the importance of a multifaceted approach that is individualized according to preference and circumstance in addressing senescence seclusion syndrome.

Developmental Study on "Smart Silver Care": A Mobile Application to Alleviate Loneliness in Older Adults within the Community

BACKGROUND

Loneliness poses a significant threat to the quality of life of older adults. Therefore, it is essential to implement non-face-to-face services to solve the loneliness of older adults in the community.

OBJECTIVES

This study used the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) model to develop mobile applications as a loneliness intervention for older adults living in the community.

METHODS

A mobile application was developed using the ADDIE model to alleviate loneliness in older adults living in the community. The development process included a systematic review, a face-to-face preference survey, and an experts' evaluation. From 11 to 15 June 2021, the following six databases were used to search for related articles: Ovid-Medline, Ovid-EMBASE, Cochrane Library, KISS, Korea Med, RISS. A preference analysis was conducted on 100 adults aged 65 or older living in the community from 15 July to 31 August 2021.

RESULTS

A mobile application for community-dwelling older adults was developed. Its contents included emotional support, cognition, physical activity, health data, nutrition, and motivation. They were organized through a systematic review and preference survey in the analysis stage. They were also designed as main menus and sub-content at the design stage. They also designed the structure, functionality, and interface layout. The application was developed by integrating the designed content and determining the operating system, language, access method, privacy, and server history. Then, experts evaluated the validity of the application.

CONCLUSIONS

The prototype mobile application incorporates emotional support, cognition, physical activity, health data, nutrition, and motivation. It is expected to help older adults achieve their goals by promoting participation. By incorporating expert validity into the content development process of early prototypes, we have improved the usability and acceptability of our products. Future pilot trials are needed to evaluate the effectiveness of this mobile application among older adults.

Conversational Agent Interventions for Mental Health Problems: Systematic Review and Meta-analysis of Randomized Controlled Trials

BACKGROUND

Mental health problems are a crucial global public health concern. Owing to their cost-effectiveness and accessibility, conversational agent interventions (CAIs) are promising in the field of mental health care.

OBJECTIVE

This study aims to present a thorough summary of the traits of CAIs available for a range of mental health problems, find evidence of efficacy, and analyze the statistically significant moderators of efficacy via a meta-analysis of randomized controlled trial.

METHODS

Web-based databases (Embase, MEDLINE, PsycINFO, CINAHL, Web of Science, and Cochrane) were systematically searched dated from the establishment of the database to October 30, 2021, and updated to May 1, 2022. Randomized controlled trials comparing CAIs with any other type of control condition in improving depressive symptoms, generalized anxiety symptoms, specific anxiety symptoms, quality of life or well-being, general distress, stress, mental disorder symptoms, psychosomatic disease symptoms, and positive and negative affect were considered eligible. This study followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Data were extracted by 2 independent reviewers, checked by a third reviewer, and pooled using both random effect models and fixed effects models. Hedges g was chosen as the effect size.

RESULTS

Of the 6900 identified records, a total of 32 studies were included, involving 6089 participants. CAIs showed statistically significant short-term effects compared with control conditions in improving depressive symptoms (g=0.29, 95% CI 0.20-0.38), generalized anxiety symptoms (g=0.29, 95% CI 0.21-0.36), specific anxiety symptoms (g=0.47, 95% CI 0.07-0.86), quality of life or well-being (g=0.27, 95% CI 0.16-0.39), general distress (g=0.33, 95% CI 0.20-0.45), stress (g=0.24, 95% CI 0.08-0.41), mental disorder symptoms (g=0.36, 95% CI 0.17-0.54), psychosomatic disease symptoms (g=0.62, 95% CI 0.14-1.11), and negative affect (g=0.28, 95% CI 0.05-0.51). However, the long-term effects of CAIs for the most mental health outcomes were not statistically significant (g=-0.04 to 0.39). Personalization and empathic response were 2 critical facilitators of efficacy. The longer duration of interaction with conversational agents was associated with the larger pooled effect sizes.

CONCLUSIONS

The findings show that CAIs are research-proven interventions that ought to be implemented more widely in mental health care. CAIs are effective and easily acceptable for those with mental health problems. The clinical application of this novel digital technology will conserve human health resources and optimize the allocation of mental health services.

TRIAL REGISTRATION

PROSPERO CRD42022350130; https://tinyurl.com/mvhk6w9p.

Artificial intelligence in elderly healthcare: A scoping review

The ageing population has led to a surge in the adoption of artificial intelligence (AI) technologies in elderly healthcare worldwide. However, in the advancement of AI technologies, there is currently a lack of clarity about the types and roles of AI technologies in elderly healthcare. This scoping review aimed to provide a comprehensive overview of AI technologies in elderly healthcare by exploring the types of AI technologies employed, and identifying their roles in elderly healthcare based on existing studies. A total of 10 databases were searched for this review, from January 1 2000 to July 31 2022. Based on the inclusion criteria, 105 studies were included. The AI devices utilized in elderly healthcare were summarised as robots, exoskeleton devices, intelligent homes, AI-enabled health smart applications and wearables, voice-activated devices, and virtual reality. Five roles of AI technologies were identified: rehabilitation therapists, emotional supporters, social facilitators, supervisors, and cognitive promoters. Results showed that the impact of AI technologies on elderly healthcare is promising and that AI technologies are capable of satisfying the unmet care needs of older adults and demonstrating great potential in its further development in this area. More well-designed randomised controlled trials are needed in the future to validate the roles of AI technologies in elderly healthcare.

Needs Analysis for Non-Face-to-Face Services among Older Adults to Reduce Loneliness

Background: Considering older adults’ interests and physical abilities, non-face-to-face services precipitated positive acceptance and reduced loneliness. Developing non-face-to-face services designed after investigating older adults’ needs is necessary. Research question: What is the need for non-face-to-face services to reduce loneliness among older adults in the community? Methods: A questionnaire was developed through a content validity evaluation of a group of experts based on a prior systematic review. The survey was administered to 100 community-dwelling older adults between 15 July and 31 August 2021. The need for non-face-to-face services for older adults was analyzed. Results: This study found that non-face-to-face services precipitate positive perceptions and satisfy the needs of older adults in the community. Additionally, the older adults preferred integrated content from non-face-to-face services. Through the analysis of preference differences according to the general characteristics, this study shows the possibility of inducing participation by developing content that attracts older adults’ attention. Conclusion: This study is expected to provide basic data for content development of non-face-to-face services to reduce loneliness among older adults in the community by investigating their needs.

Conversational agents in healthcare: a scoping review of their behavior change techniques and underpinning theory (Preprint)

Background

Conversational agents (CAs) are increasingly used in health care to deliver behavior change interventions. Their evaluation often includes categorizing the behavior change techniques (BCTs) using a classification system of which the BCT Taxonomy v1 (BCTTv1) is one of the most common. Previous studies have presented descriptive summaries of behavior change interventions delivered by CAs, but no in-depth study reporting the use of BCTs in these interventions has been published to date.

Objective

This review aims to describe behavior change interventions delivered by CAs and to identify the BCTs and theories guiding their design.

Methods

We searched PubMed, Embase, Cochrane’s Central Register of Controlled Trials, and the first 10 pages of Google and Google Scholar in April 2021. We included primary, experimental studies evaluating a behavior change intervention delivered by a CA. BCTs coding followed the BCTTv1. Two independent reviewers selected the studies and extracted the data. Descriptive analysis and frequent itemset mining to identify BCT clusters were performed.

Results

We included 47 studies reporting on mental health (n=19, 40%), chronic disorders (n=14, 30%), and lifestyle change (n=14, 30%) interventions. There were 20/47 embodied CAs (43%) and 27/47 CAs (57%) represented a female character. Most CAs were rule based (34/47, 72%). Experimental interventions included 63 BCTs, (mean 9 BCTs; range 2-21 BCTs), while comparisons included 32 BCTs (mean 2 BCTs; range 2-17 BCTs). Most interventions included BCTs 4.1 “Instruction on how to perform a behavior” (34/47, 72%), 3.3 “Social support” (emotional; 27/47, 57%), and 1.2 “Problem solving” (24/47, 51%). A total of 12/47 studies (26%) were informed by a behavior change theory, mainly the Transtheoretical Model and the Social Cognitive Theory. Studies using the same behavior change theory included different BCTs.

Conclusions

There is a need for the more explicit use of behavior change theories and improved reporting of BCTs in CA interventions to enhance the analysis of intervention effectiveness and improve the reproducibility of research.

Social Disconnection in Late Life Suicide: An NIMH Workshop on State of the Research in Identifying Mechanisms, Treatment Targets, and Interventions

Both social disconnection and suicide are significant public health concerns among older adults, and social disconnection is associated with greater risk for suicide-related thoughts and behaviors in late life. We present a synthesis of research discussed during a workshop hosted by the National Institute of Mental Health on social disconnection and late-life suicide. Social disconnection is related to suicide risk in late life via a variety of mechanisms, including biological, behavioral, and psychological correlates. Researchers in several scientific fields have begun to establish these connections and identify targets for interventions to reduce risk in late life. While research has demonstrated that social connection is amenable to change, there is little research to date on the most evidence-based interventions to mitigate social disconnection or the related risks. However, there are several promising biological, behavioral, and psychological interventions that may target various mechanisms, as well as social disconnection itself. With a relative paucity of research in this area, these lines of study are ripe for innovative investigation. In order to most effectively advance the field, we must establish more consistent definitions of social connection and disconnection; more accurately measure and assess older adults' social needs; examine the most effective approaches and modalities for assessment and intervention; take into account important contextual factors; and apply a translational, convergent scientific approach.

Voice-enabled Intelligent Virtual Agents for People with Amnesia: Systematic Review (Preprint)

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Objective

Methods

Results

Conclusions