Digital technologies are increasingly empowering individuals to take charge of their health and improve their well-being. However, there are disparities in access related to demographic, economic, and sociocultural factors that result in exclusion from the use of digital technologies for different groups of the population. The development of digital technology in health is a powerful lever for improving care and services, but also brings risks for certain users in vulnerable situations. Increased digital health inequalities are associated with limited digital literacy, lack of interest, and low levels of self-efficacy in using technology. In the context of the COVID-19 pandemic and post-pandemic healthcare systems, the leap to digital is essential. To foster responsible innovation and optimal use of digital health by all, including vulnerable groups, we propose that patient and citizen engagement must be an essential component of the research strategy. Patient partners will define expectations and establish research priorities using their experiential knowledge, while benefiting from rich exposure to the research process to increase their self-efficacy and digital literacy. We will support this proposition with an operationalised example aiming to implement a Virtual Community of Patients and Citizens Partners (COMVIP), a digital tool co-created with patients and public experts, as active team members in research. Founded on the principles of equity, diversity and inclusion, this base of citizen expertise will assemble individuals from different backgrounds and literacy levels living in vulnerable situations to acquire knowledge, and share their experiences, while contributing actively in the co-development of innovative strategies and health technology assessment.
Background Interactive conversational agents, also known as “chatbots,” are computer programs that use natural language processing to engage in conversations with humans to provide or collect information. Although the literature on the development and use of chatbots for health interventions is growing, important knowledge gaps remain, such as identifying design aspects relevant to health care and functions to offer transparency in decision-making automation. Objective This paper presents the protocol for a scoping review that aims to identify and categorize the interactive conversational agents currently used in health care. Methods A mixed methods systematic scoping review will be conducted according to the Arksey and O’Malley framework and the guidance of Peters et al for systematic scoping reviews. A specific search strategy will be formulated for 5 of the most relevant databases to identify studies published in the last 20 years. Two reviewers will independently apply the inclusion criteria using the full texts and extract data. We will use structured narrative summaries of main themes to present a portrait of the current scope of available interactive conversational agents targeting health promotion, prevention, and care. We will also summarize the differences and similarities between these conversational agents. Results The search strategy and screening steps were completed in March 2022. Data extraction and analysis started in May 2022, and the results are expected to be published in October 2022. Conclusions This fundamental knowledge will be useful for the development of interactive conversational agents adapted to specific groups in vulnerable situations in health care and community settings. International Registered Report Identifier (IRRID) DERR1-10.2196/40265
Background The COVID-19 pandemic has profoundly affected the health and care of older adults, with particularly negative consequences for those residing in long-term care homes (LTCH) and retirement homes (RH). To inform the implementation of interventions with the most potential for impact, Healthcare Excellence Canada identified six promising practices and policy options that can be introduced to ensure that LTCH and RH are better prepared for potential future outbreaks. A total of 22 implementation science teams (ISTs) were funded to support LTCH and RH across Canada in their implementation of these practices. This study aims to identify the enablers and barriers to the successful implementation of evidence-based practices and the impact of intervention in LTCH and RH across Canada. Methods A survey-based longitudinal correlational design will be used. The Organizational Readiness for Knowledge Translation (OR4KT) tool will be used to assess the readiness of LTCH and RH to implement the selected practice. The OR4KT includes 59 questions and takes about 15 min to complete. Five to ten respondents per organization, holding different job positions, will be invited by the ISTs to complete the OR4KT in 91 LTCH or RH across Canada at the beginning of the project (T1) and 6 months after the first measurement (T2). Discussion The study will provide a benchmark for assessing the readiness of LTCH and RH to implement evidence-based practices. It will also inform decision-makers about barriers and facilitators that influence the integration of promising practices in these organizations.
BACKGROUND Interactive conversational agents, also known as “chatbots”, are computer programs that use natural language processing to engage in conversations with humans to provide or to collect information. Although the literature on the development and use of chatbots for health interventions is growing, there are still important knowledge gaps that remain, such as identifying design aspects relevant to healthcare and functions to offer transparency in decision making automation. OBJECTIVE To identify and categorize the current interactive conversational agents used in healthcare. METHODS A mixed methods systematic scoping review will be conducted according to the Arksey and O'Malley framework and the guidance of Peters et al. for systematic scoping reviews. A specific search strategy will be formulated for five of the most relevant databases to identify studies published in the last 20 years. Two reviewers will independently apply the inclusion criteria using the full texts and extract the data. RESULTS We will use structured narrative summaries of main themes to present a portrait of the current scope of available interactive conversational agents targeting health promotion, prevention, and care. We will also summarize the differences and similarities between the conversational agents. CONCLUSIONS This fundamental knowledge will be useful for the development of interactive conversational agents adapted to specific groups in vulnerable situations in healthcare and community settings.
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