Background: The use of social robots as innovative therapeutic tools has been increasingly explored in recent years in an effort to address the growing need for alternative intervention modalities in mental health care. Objective: The aim of this scoping review was to identify and describe social robot interventions in mental health facilities and to highlight their outcomes as well as the barriers and facilitators to their implementation. Methods: A scoping review of the literature published since 2015 was conducted using the Arksey and O’Malley’s framework. The MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and PsycINFO databases were searched, and 2239 papers were retrieved. The papers included were primary empirical studies published in peer-reviewed literature. Eligible studies were set in mental health facilities and they included participants with a known mental health disorder. The methodological quality of the included papers was also assessed using the Mixed Methods Appraisal Tool. Results: A total of 30 papers met the eligibility criteria for this review. Studies involved participants with dementia, cognitive impairment, schizophrenia, depression, autism spectrum disorder, attention-deficit hyperactivity disorder, and an intellectual disability. The outcomes studied included engagement, social interaction, emotional state, agitation, behavior, and quality of life. Conclusions: The methodological weaknesses of the studies conducted this far and the lack of diversity in the conditions studied limit the generalizability of the results. However, despite the presence of certain barriers to their implementation (eg, technical problems, unsuitable environment, staff resistance), social robot interventions generally show positive effects on patients with mental health disorders. Studies of stronger methodological quality are needed to further understand the benefits and the place of social robots in mental health care.

Background: Patient engagement in care is a priority and a key component of clinical practice. Different approaches to care have been introduced to foster patient engagement. There is a lack of a recent review on tools for assessing the main concepts and dimensions related to patient engagement in care.Objective: Our scoping review sought to map and summarize recently validated tools for assessing various concepts and dimensions of patient engagement in care.Search Strategy: A scoping review of recent peer‐reviewed articles describing tools that assess preferences in and experience with patient engagement in care was conducted in four databases (Ovid Medline, Ovid EMBASE, Cochrane Database of Systematic Reviews, CINAHL‐EBSCO). We adopted a broad definition based on the main concepts of patient engagement in care: patient‐centredness, empowerment, shared decision‐making and partnership in care.Main Results: Of 2161 articles found, 16, each describing a different tool, were included and analysed. Shared decision‐making and patient‐centredness are the two main concepts evaluated, often simultaneously in most of the tools. Only four scales measure patient‐centredness, empowerment and shared decision‐making at the same time, but no tool measures the core dimensions of partnership in care. Most of the tools did not include patients in their development or validation or just consulted them during the validation phase.Discussion and Conclusion: There is no tool coconstructed with patients from development to validation, which can be used to assess the main concepts and dimensions of patient engagement in care at the same time.Patient and Public Contribution: This manuscript was prepared with a patient expert who is one of the authors. Vincent Dumez, who is a patient expert and codirector of the Center of Excellence on Partnership with Patients and the Public, has contributed to the preparation of the manuscript.

Background: Given the magnitude and speed of SARS-CoV-2 transmission, achieving timely and effective manual contact tracing has been a challenging task. Early in the pandemic, contact tracing apps generated substantial enthusiasm due to their potential for automating tracing and reducing transmission rates while enabling targeted confinement strategies. However, although surveys demonstrate public interest in using such apps, their actual uptake remains limited. Their social acceptability is challenged by issues around privacy, fairness, and effectiveness, among other concerns.Objective: This study aims to examine the extent to which design and implementation considerations for contact tracing apps are detailed in the available literature, focusing on aspects related to participatory and responsible eHealth innovation, and synthesize recommendations that support the development of successful COVID-19 contact tracing apps and related eHealth technologies.Methods: Searches were performed on five databases, and articles were selected based on eligibility criteria. Papers pertaining to the design, implementation, or acceptability of contact tracing apps were included. Articles published since 2019, written in English or French, and for which the full articles were available were considered eligible for analysis. To assess the scope of the knowledge found in the current literature, we used three complementary frameworks: (1) the Holistic Framework to Improve the Uptake and Impact of eHealth Technologies, (2) the Montreal model, and (3) the Responsible Innovation in Health Assessment Tool.Results: A total of 63 articles qualified for the final analysis. Less than half of the selected articles cited the need for a participatory process (n=25, 40%), which nonetheless was the most frequently referenced item of the Framework to Improve the Uptake and Impact of eHealth Technologies. Regarding the Montreal model, stakeholder consultation was the most frequently described level of engagement in the development of contact tracing apps (n=24, 38%), while collaboration and partnership were cited the least (n=2, 3%). As for the Responsible Innovation in Health framework, all the articles (n=63, 100%) addressed population health, whereas only 2% (n=1) covered environmental considerations.Conclusions: Most studies lacked fundamental aspects of eHealth development and implementation. Our results demonstrate that stakeholders of COVID-19 contact tracing apps lack important information to be able to critically appraise this eHealth innovation. This may have contributed to the modest uptake of contact tracing apps worldwide. We make evidence-informed recommendations regarding data management, communication, stakeholder engagement, user experience, and implementation strategies for the successful and responsible development of contact tracing apps.

Background: Artificial intelligence (AI)–based chatbots could help address some of the challenges patients face in acquiring information essential to their self-health management, including unreliable sources and overburdened health care professionals. Research to ensure the proper design, implementation, and uptake of chatbots is imperative. Inclusive digital health research and responsible AI integration into health care require active and sustained patient and stakeholder engagement, yet corresponding activities and guidance are limited for this purpose. Objective: In response, this manuscript presents a master protocol for the development, testing, and implementation of a chatbot family in partnership with stakeholders. This protocol aims to help efficiently translate an initial chatbot intervention (MARVIN) to multiple health domains and populations. Methods: The MARVIN chatbots study has an adaptive platform trial design consisting of multiple parallel individual chatbot substudies with four common objectives: (1) co-construct a tailored AI chatbot for a specific health care setting, (2) assess its usability with a small sample of participants, (3) measure implementation outcomes (usability, acceptability, appropriateness, adoption, and fidelity) within a large sample, and (4) evaluate the impact of patient and stakeholder partnerships on chatbot development. For objective 1, a needs assessment will be conducted within the setting, involving four 2-hour focus groups with 5 participants each. Then, a co-construction design committee will be formed with patient partners, health care professionals, and researchers who will participate in 6 workshops for chatbot development, testing, and improvement. For objective 2, a total of 30 participants will interact with the prototype for 3 weeks and assess its usability through a survey and 3 focus groups. Positive usability outcomes will lead to the initiation of objective 3, whereby the public will be able to access the chatbot for a 12-month real-world implementation study using web-based questionnaires to measure usability, acceptability, and appropriateness for 150 participants and meta-use data to inform adoption and fidelity. After each objective, for objective 4, focus groups will be conducted with the design committee to better understand their perspectives on the engagement process. Results: From July 2022 to October 2023, this master protocol led to four substudies conducted at the McGill University Health Centre or the Centre hospitalier de l’Université de Montréal (both in Montreal, Quebec, Canada): (1) MARVIN for HIV (large-scale implementation expected in mid-2024), (2) MARVIN-Pharma for community pharmacists providing HIV care (usability study planned for mid-2024), (3) MARVINA for breast cancer, and (4) MARVIN-CHAMP for pediatric infectious conditions (both in preparation, with development to begin in early 2024). Conclusions: This master protocol offers an approach to chatbot development in partnership with patients and health care professionals that includes a comprehensive assessment of implementation outcomes. It also contributes to best practice recommendations for patient and stakeholder engagement in digital health research. Trial Registration: ClinicalTrials.gov NCT05789901; https://classic.clinicaltrials.gov/ct2/show/NCT05789901 International Registered Report Identifier (IRRID): PRR1-10.2196/54668

Context: Partnership between patients and health‐care professionals (HCPs) is a concept that needs a valid, practical measure to facilitate its use by patients and HCPs.Objective: To co‐construct a tool for measuring the degree of partnership between patients and HCPs.Design: The CADICEE tool was developed in four steps: (1) generate key dimensions of patient partnership in clinical care; (2) co‐construct the tool; (3) assess face and content validity from patients’ and HCPs’ viewpoints; and (4) assess the usability of the tool and explore its measurement performance.Results: The CADICEE tool comprises 24 items under 7 dimensions: 1) relationship of Confidence or trust between the patient and the HCPs; 2) patient Autonomy; 3) patient participation in Decisions related to care; 4) shared Information on patient health status or care; 5) patient personal Context; 6) Empathy; and 7) recognition of Expertise.Assessment of the tool's usability and measurement performance showed, in a convenience sample of 246 patients and relatives, high face validity, acceptability and relevance for both patients and HCPs, as well as good construct validity.Conclusions: The CADICEE tool is developed in co‐construction with patients to evaluate the degree of partnership in care desired by patients in their relationship with HCPs. The tool can be used in various clinical contexts and in different health‐care settings.Patient or Public Contribution: Patients were involved in determining the importance of constructing this questionnaire. They co‐constructed it, pre‐tested it and were part of the entire questionnaire development process. Three patients participated in the writing of the article.

Introduction: Since 2018, four establishments in Quebec, Canada, have decided to implement the PAROLE‐Onco programme, which introduced accompanying patients (APs) in healthcare teams to improve the experience of cancer patients. APs are patient advisors who have had a cancer treatment experience and who conduct consultations to complement the service offered by providing emotional, informational and educational support to patients undergoing treatments (e.g., radiotherapy, chemotherapy, surgery), mostly for breast cancer. We aimed to explore the evolution of APs' perspectives regarding their activities within the clinical oncology teams as well as the perceived effects of their intervention with patients, the clinical team and themselves.Methods: A qualitative study based on semistructured interviews and focus groups was conducted with APs at the beginning of their intervention (T1) and 2 years afterwards (T2). The themes discussed were APs' activities and the perceived effects of their interventions on themselves, on the patients and on the clinical team.Results: In total, 20 APs were interviewed. In T2, APs' activities shifted from listening and sharing experiences to empowering patients by helping them become partners in their care and felt generally more integrated into the clinical team. APs help patients feel understood and supported, alleviate stress and become partners in the care they receive. They also alleviate the clinical team's workload by offering a complementary service through emotional support, which, according to them, helps patients feel calmer and more prepared for their appointments with healthcare professionals. They communicate additional information about their patients' health journey, which makes the appointment more efficient for healthcare professionals. When APs accompany patients, they feel as if they can make a difference in patients' lives. Their activities are perceived by some as an opportunity to give back but also as a way of giving meaning to their own experience, in turn serving as a learning experience.Conclusion: By mobilizing their experiential knowledge, APs provide emotional, informational, cognitive and navigational support, which allows patients to be more empowered in their care and which complements professionals' scientific knowledge, thereby helping to refine their sensitivity to the patients' experiences.Patient or Public Contribution: Two patient–researchers have contributed to the study design, the conduct of the study, the data analysis and interpretation, as well as in the preparation and writing of this manuscript.