Exploring the Use of Activity Trackers in Underserved Populations

Over the past decade, wearable activity trackers such as FitBits have come to the forefront of personal health. They have been shown to help produce positive behavioral changes ranging from increased activity to better sleeping habits. However, a major issue with this technology is that it is often only utilized by populations that need it the least: young, healthy, and affluent. We are interested in seeing how effective these trackers can be in underserved populations and what roadblocks exist for large-scale adoption. We are partnering with wellness groups at MGH Revere, where participants in these demographics will receive free FitBits to keep during their program as well as afterwards indefinitely. We will interview all consenting participants afterwards to get their feedback on the efficacy of such technology in their lives. A robust analysis will then be conducted correlating responses with both clinical and tracker data. We hope our findings can lead to recommendations on how to better implement these digital technologies in the populations that need them the most.

Balancing Need and Fear: Changes in Health Information Seeking Behavior During the COVID-19 Pandemic

As patients balance their need for health information with their fears about accessing medical care during the COVID-19 pandemic, health information seeking behaviors have changed. Our population of interest is people who are seeking answers to questions about their health that are not specifically COVID-19 related, yet who are not seeing their providers due to actual or perceived reduced availability or fear of COVID-19 exposure at medical appointments. Our focus is on those who are participating in online health communities; in particular, we seek to understand why participation has increased, how people are locating them, the types of participation, and how participation influences decisions to use, or not use traditional medical care. We plan to evaluate the benefits of participation, e.g., greater peer support and social capital, and the drawbacks, e.g., misinformation and delayed treatment. Our study will be done using a three-pronged approach which includes participant surveys, analysis of analytics, and analysis of content for five online health communities covering different health conditions. Given that the pandemic shows no indication of ending, our findings will inform insurers and providers how and when to recommend or provide online health communities to their patients. Furthermore, we hope our findings lead to better support of patient decision-making to reverse the trend during the pandemic of delayed screening, testing, and treatment.