Telehealth for Indigenous Children Worldwide: A Scoping Review.

PURPOSE: Indigenous children worldwide face healthcare disparities due, in part, to resource scarcity in remote settings which may be mitigated with technology. This study aims to determine the use of telehealth for this population, with respect to feasibility, acceptability, and the degree of patient/family involvement in reported interventions. We focused on the use of telehealth to support perioperative care. METHODS: To identify relevant studies, five databases were searched to find articles that focused on the role of telehealth in caring for Indigenous populations worldwide, with an emphasis on the pediatric population. Studies that lacked insight into those themes, as well as protocols and review articles, were excluded. Analysis was done according to the non-adoption, abandonment, scale-up, spread, and sustainability (NASSS) framework, the Montreal Model (patient involvement), and the theoretical framework of acceptability (TFA). RESULTS: Of the 1690 articles screened, 34 met the eligibility criteria. The most frequent uses of telehealth for Indigenous children were in ENT and psychiatry. Most of those had a low degree of complexity across the NASSS framework domains, suggesting greater feasibility. In 13 articles, the patient involvement was limited to information (lowest level of involvement in the Montreal Model). Only 11 articles directly assessed patient/family-perceived acceptability. Finally, two articles addressed telehealth in the surgical context. CONCLUSIONS: The relative simplicity of the proposed telehealth applications may support their sustained impact and use in other settings such as for perioperative care. Early and longitudinal involvement of communities is essential for responsible telehealth development that addresses local needs. LEVEL OF EVIDENCE: Level V.

Exploring the digital divide: results of a survey informing mobile application development.

Introduction: Mobile health apps risk widening health disparities if they overlook digital inclusion. The digital divide, encompassing access, familiarity, and readiness, poses a significant barrier to medical interventions. Existing literature lacks exploration of the digital divide's contributing factors. Hence, data are needed to comprehend the challenges in developing inclusive health apps. Methods: We created a survey to gauge internet and smartphone access, smartphone familiarity, and readiness for using mobile health apps among caregivers of pediatric patients in tertiary care. Open-ended questions solicited feedback and suggestions on mobile health applications. Responses were categorized by similarity and compared. Developed with patient partners, the survey underwent cognitive testing and piloting for accuracy. Results: Data from 209 respondents showed that 23% were affected by the digital divide, mainly due to unfamiliarity with digital skills. Among 49 short text responses about health app concerns, 31 mentioned security and confidentiality, with 7 mentioning the impersonal nature of such apps. Desired features included messaging healthcare providers, scheduling, task reminders, and simplicity. Conclusions: This study underscores a digital divide among caregivers of pediatric patients, with nearly a quarter affected primarily due to a lack of digital comfort. Respondents emphasized user-friendliness and online security for health apps. Future apps should prioritize digital inclusion by addressing the significant barriers and carefully considering patient and family concerns.

Adapting and Evaluating an AI-Based Chatbot Through Patient and Stakeholder Engagement to Provide Information for Different Health Conditions: Master Protocol for an Adaptive Platform Trial (the MARVIN Chatbots Study).

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.