Public attitudes to the use of remote data collection in clinical research

Field based research in the era of the pandemic in resource limited settings: challenges and lessons for the future

The coronavirus pandemic that began in December 2019, has had an unprecedented impact on the global economy, health systems and infrastructure, in addition to being responsible for significant mortality and morbidity worldwide. The "new normal" has brought along, unforeseen challenges for the scientific community, owing to obstructions in conducting field-based research in lieu of minimizing exposure through in-person contact. This has had greater ramifications for the LMICs, adding to the already existing concerns. As a response to COVID-19 related movement restrictions, public health researchers across countries had to switch to remote data collections methods. However, impediments like lack of awareness and skepticism among participants, dependence on paper-based prescriptions, dearth of digitized patient records, gaps in connectivity, reliance on smart phones, concerns with participant privacy at home and greater loss to follow-up act as hurdles to carrying out a research study virtually, especially in resource-limited settings. Promoting health literacy through science communication, ensuring digitization of health records in hospitals, and employing measures to encourage research participation among the general public are some steps to tackle barriers to remote research in the long term. COVID-19 may not be a health emergency anymore, but we are not immune to future pandemics. A more holistic approach to research by turning obstacles into opportunities will not just ensure a more comprehensive public health response in the coming time, but also bolster the existing infrastructure for a stronger healthcare system for countries.

Matching science to reality: how to deploy a participant-driven digital brain health platform

Introduction

Advances in digital technologies for health research enable opportunities for digital phenotyping of individuals in research and clinical settings. Beyond providing opportunities for advanced data analytics with data science and machine learning approaches, digital technologies offer solutions to several of the existing barriers in research practice that have resulted in biased samples.

Methods

A participant-driven, precision brain health monitoring digital platform has been introduced to two longitudinal cohort studies, the Boston University Alzheimer's Disease Research Center (BU ADRC) and the Bogalusa Heart Study (BHS). The platform was developed with prioritization of digital data in native format, multiple OS, validity of derived metrics, feasibility and usability. A platform including nine remote technologies and three staff-guided digital assessments has been introduced in the BU ADRC population, including a multimodal smartphone application also introduced to the BHS population. Participants select which technologies they would like to use and can manipulate their personal platform and schedule over time.

Results

Participants from the BU ADRC are using an average of 5.9 technologies to date, providing strong evidence for the usability of numerous digital technologies in older adult populations. Broad phenotyping of both cohorts is ongoing, with the collection of data spanning cognitive testing, sleep, physical activity, speech, motor activity, cardiovascular health, mood, gait, balance, and more. Several challenges in digital phenotyping implementation in the BU ADRC and the BHS have arisen, and the protocol has been revised and optimized to minimize participant burden while sustaining participant contact and support.

Discussion

The importance of digital data in its native format, near real-time data access, passive participant engagement, and availability of technologies across OS has been supported by the pattern of participant technology use and adherence across cohorts. The precision brain health monitoring platform will be iteratively adjusted and improved over time. The pragmatic study design enables multimodal digital phenotyping of distinct clinically characterized cohorts in both rural and urban U.S. settings.

Virtual engagement of under-resourced communities: Lessons learned during the COVID-19 pandemic for creating crisis-resistant research infrastructure

The COVID-19 pandemic led to an increased need to conduct research and community engagement using digital methods. Unfortunately, the shift away from in-person research activities can make it difficult to engage and recruit participants from under-resourced communities that lack adequate digital infrastructure. At the beginning of the pandemic, our team recognized that imminent lockdowns would significantly disrupt ongoing engagement with low-income housing resident community partners and that we would ultimately bear responsibility if that occurred. This manuscript outlines the development of methods designed to create capacity for virtual engagement with a community advisory board that were subsequently applied to a longitudinal mixed-methods study. We describe how our experience engaging low-income housing residents during the height of the pandemic influenced the approach and offer guidelines useful for engaging under-resourced communities regardless of setting. Of these, a strong commitment to providing technology, unlimited data connectivity, and basic digital literacy training/technical support is most important. While each of these is essential and failure in any one area will reduce overall effectiveness of the effort, providing adequate technical support while maintaining ongoing relationships with community members is the most important and resource-intensive.