Use of conversational agents in rehabilitation following brain injury, disease, or stroke: a scoping review protocol

Encouraging arm use in stroke survivors: the impact of smart reminders during a home-based intervention

BACKGROUND

Upper limb impairment post-stroke often leads to a predominant use of the less affected arm and consequent learned disuse of the affected side, hindering upper limb outcome. Wearable sensors such as accelerometers, combined with smart reminders (i.e., based on the amount of arm activity), offer a potential approach to promote increased use of the affected arm to improve upper limb use during daily life. This study aimed to evaluate the efficacy of wrist vibratory reminders during a six-week home-based intervention in chronic stroke survivors.

METHODS

We evaluated the impact of the home-based intervention on the primary outcome, the Motor Activity Log-14 Item Version scores Amount of Use (MAL-14 AOU), and the secondary outcomes MAL-14 Quality of Movement (QOM) and sensor-derived activity metrics from the affected arm. A randomized controlled trial design was used for the study: the intervention group received personalized reminders based on individualized arm activity goals, while the control group did not receive any feedback. Mixed linear models assessed the influence of the group, week of the intervention period, and initial impairment level on MAL-14 and arm activity metrics.

RESULTS

Forty-two participants were enrolled in the study. Overall, participants exhibited modest but not clinically relevant increases in MAL-14 AOU (+ 0.2 points) and QOM (+ 0.2 points) after the intervention period, with no statistically significant differences between the intervention and control group. Feasibility challenges were noted, such as adherence to wearing the trackers and sensor data quality. However, in participants with sufficiently available sensor data (n = 23), the affected arm use extracted from the sensor data was significantly higher in the intervention group (p < 0.05). The initial impairment level strongly influenced affected arm use and both MAL-14 AOU and QOM (p < 0.01).

CONCLUSIONS

The study investigated the effectiveness of incorporating activity trackers with smart reminders to increase affected arm activity among stroke survivors during daily life. While the results regarding the increased arm use at home are promising, patient-reported outcomes remained below clinically meaningful thresholds and showed no group differences. Further, it is essential to acknowledge feasibility issues such as adherence to wearing the trackers during the intervention and missing sensor data.

TRIAL REGISTRATION

NCT03294187.

Technologies in Home-Based Digital Rehabilitation: Scoping Review

BACKGROUND

Due to growing pressure on the health care system, a shift in rehabilitation to home settings is essential. However, efficient support for home-based rehabilitation is lacking. The COVID-19 pandemic has further exacerbated these challenges and has affected individuals and health care professionals during rehabilitation. Digital rehabilitation (DR) could support home-based rehabilitation. To develop and implement DR solutions that meet clients' needs and ease the growing pressure on the health care system, it is necessary to provide an overview of existing, relevant, and future solutions shaping the constantly evolving market of technologies for home-based DR.

OBJECTIVE

In this scoping review, we aimed to identify digital technologies for home-based DR, predict new or emerging DR trends, and report on the influences of the COVID-19 pandemic on DR.

METHODS

The scoping review followed the framework of Arksey and O'Malley, with improvements made by Levac et al. A literature search was performed in PubMed, Embase, CINAHL, PsycINFO, and the Cochrane Library. The search spanned January 2015 to January 2022. A bibliometric analysis was performed to provide an overview of the included references, and a co-occurrence analysis identified the technologies for home-based DR. A full-text analysis of all included reviews filtered the trends for home-based DR. A gray literature search supplemented the results of the review analysis and revealed the influences of the COVID-19 pandemic on the development of DR.

RESULTS

A total of 2437 records were included in the bibliometric analysis and 95 in the full-text analysis, and 40 records were included as a result of the gray literature search. Sensors, robotic devices, gamification, virtual and augmented reality, and digital and mobile apps are already used in home-based DR; however, artificial intelligence and machine learning, exoskeletons, and digital and mobile apps represent new and emerging trends. Advantages and disadvantages were displayed for all technologies. The COVID-19 pandemic has led to an increased use of digital technologies as remote approaches but has not led to the development of new technologies.

CONCLUSIONS

Multiple tools are available and implemented for home-based DR; however, some technologies face limitations in the application of home-based rehabilitation. However, artificial intelligence and machine learning could be instrumental in redesigning rehabilitation and addressing future challenges of the health care system, and the rehabilitation sector in particular. The results show the need for feasible and effective approaches to implement DR that meet clients' needs and adhere to framework conditions, regardless of exceptional situations such as the COVID-19 pandemic.

Design, development, and use of conversational agents in rehabilitation for adults with brain-related neurological conditions: a scoping review

OBJECTIVE

The objective of this review was to identify how conversational agents are designed and used in rehabilitation for adults with brain-related neurological conditions.

INTRODUCTION

Adults with brain-related neurological conditions experience varied cognitive and functional challenges that can persist long term. However, rehabilitation services are time- and resource-limited, and novel rehabilitation approaches are warranted. Conversational agents provide a human-computer interface with which the user can converse. A conversational agent can be designed to meet specific user needs, such as rehabilitation and support.

INCLUSION CRITERIA

Studies focused on the design and use of conversational agents for rehabilitation for people aged 18 years or older with brain-related neurological conditions were considered for inclusion. Eligible publication types included peer-reviewed publications (quantitative, qualitative, and/or mixed methods study designs; research protocols; peer-reviewed expert opinion papers; clinical studies, including pilot trials; systematic or scoping reviews), full conference papers, and master's or PhD theses. Eligible types of research included prototype development, feasibility testing, and clinical trials.

METHODS

Online databases, including MEDLINE, Scopus, ProQuest (all databases), Web of Science, and gray literature sources were searched with no date limit. Only English publications were considered due to a lack of resourcing available for translations. Title and abstract screening and full-text review were conducted by two independent reviewers. Data extraction was shared by three independent reviewers. The data extraction instrument was iteratively refined to meet the requirements of all included papers, and covered details for technological aspects and the clinical context. Results are presented narratively and in tabular format, with emphasis on participants, concept and context, and data extraction instrument components.

RESULTS

Eleven papers were included in the review, which represented seven distinct conversational agent prototypes. Methodologies included technology description (n = 9) and initial user testing (n = 6). The intended clinical cohorts for the reported conversational agents were people with dementia (n = 5), Parkinson disease (n = 2), stroke (n = 1), traumatic brain injury (n = 1), mixed dementia and mild cognitive impairment (n = 1), and mixed dementia and Parkinson disease (n = 1). Two studies included participants who were healthy or otherwise from the general community. The design of the conversational agents considered technology aspects and clinical purposes. Two conversational agent prototypes incorporated a speaking humanoid avatar as reported in five of the papers. Topics of conversation focused on subjects enjoyable to the user (life history, hobbies, where they lived). The clinical purposes reported in the 11 papers were to increase the amount of conversation the user has each day (n = 4), reminiscence (n = 2), and one study each for anxiety management and education, Parkinson disease education, to obtain and analyze a recording of the user's voice, to monitor well-being, and to build rapport before providing daily task prompts. One study reported clinician oversight of the conversational agent use. The studies had low sample sizes (range: 1-33). No studies undertook effectiveness testing. Outcome measures focused on usability, language detection and production, and technological performance. No health-related outcomes were measured. No adverse events were reported, and only two studies reported safety considerations.

CONCLUSIONS

Current literature reporting the design and use of conversational agents for rehabilitation for adults with brain-related neurological conditions is heterogeneous and represents early stages of conversational agent development and testing. We recommend, as per our customized data extraction instrument, that studies of conversational agents for this population clearly define technical aspects, methodology for developing the conversation content, recruitment methods, safety issues, and requirements for clinician oversight.

Conversational Agents in Health Education: Protocol for a Scoping Review

BACKGROUND

Conversational agents have the ability to reach people through multiple mediums, including the online space, mobile phones, and hardware devices like Alexa and Google Home. Conversational agents provide an engaging method of interaction while making information easier to access. Their emergence into areas related to public health and health education is perhaps unsurprising. While the building of conversational agents is getting more simplified with time, there are still requirements of time and effort. There is also a lack of clarity and consistent terminology regarding what constitutes a conversational agent, how these agents are developed, and the kinds of resources that are needed to develop and sustain them. This lack of clarity creates a daunting task for those seeking to build conversational agents for health education initiatives.

OBJECTIVE

This scoping review aims to identify literature that reports on the design and implementation of conversational agents to promote and educate the public on matters related to health. We will categorize conversational agents in health education in alignment with current classifications and terminology emerging from the marketplace. We will clearly define the variety levels of conversational agents, categorize currently existing agents within these levels, and describe the development models, tools, and resources being used to build conversational agents for health care education purposes.

METHODS

This scoping review will be conducted by employing the Arksey and O'Malley framework. We will also be adhering to the enhancements and updates proposed by Levac et al and Peters et al. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for scoping reviews will guide the reporting of this scoping review. A systematic search for published and grey literature will be undertaken from the following databases: (1) PubMed, (2) PsychINFO, (3) Embase, (4) Web of Science, (5) SCOPUS, (6) CINAHL, (7) ERIC, (8) MEDLINE, and (9) Google Scholar. Data charting will be done using a structured format.

RESULTS

Initial searches of the databases retrieved 1305 results. The results will be presented in the final scoping review in a narrative and illustrative manner.

CONCLUSIONS

This scoping review will report on conversational agents being used in health education today, and will include categorization of the levels of the agents and report on the kinds of tools, resources, and design and development methods used.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/31923.