Longitudinal studies are powerful tools in medical research armamentarium. Researchers gain valuable information following the same group of people with repeated measured variables over time. This type of research provides rates of change of continuous variable(s) over weeks, months, or years allowing researchers to assess patterns in human behavior or cause and effect relationships. The major differentiator of a longitudinal study compared to a cross-sectional study is how time is utilized in the research. A cross-sectional study assesses data at a single point in time whereas longitudinal studies are assessing the same data variables at multiple time points allowing researchers to examine possible trends. The Framingham Heart Study of 1948 followed over 5,209 participants for 20 years to determine risk factors for cardiovascular disease and is considered the quintessential, longitudinal study of medical research. Most longitudinal studies are relatively short compared to the 20-year Framingham study, spanning only weeks or months, however, patterns and relationships are still able to be assessed.
Some longitudinal studies are strictly observational (such as the Framingham Heart Study) while others assess a relationship to an interventional (such as the effectiveness of a vaccine). A large proportion of longitudinal studies examine the consequence of a population’s exposure to suspected causes of disease. When medical researchers are investigating specific questions about a disease or condition longitudinal clinical follow-up studies are designed to help determine the answers and provide valuable medical guidance to the population at large. Overall, longitudinal studies are very effective in observing clinical trends, provide a clear focus of cause/effect relationships, and can be highly accurate in extrapolating trends to wider populations.
Regardless of the reason, method, or duration of longitudinal research they all share the same challenges to their design – the largest of which is retaining study participants throughout the duration of the research. Study participants must be willing to commit to attend regularly scheduled follow-up visits, take time off work, navigate transportation issues to study sites, overcome mobility/disability issues, use work-vacation time, and work inconvenient study-visit timing into their busy schedules. This level of commitment can be challenging with shorter-term studies but is even more daunting for a longer-term study. Longitudinal research loses statistical value (and therefore its ability to provide generalized findings to a wider population) with every participant who does not continue in the study. The inability to retain research participants is the single-most statistical and economical loss in medical research.
One of the ways to overcome the participant retention issue is to make study visits as convenient as possible by eliminating common issues that prevent study participants from keeping their study visits. At-home visits address many of these issues by bringing the study visit to the participant as opposed to having the participant go to the study visit. At-home study visits eliminate transportation, time off work, and mobility/disability issues. Within the parameters of the study, visits are scheduled according to the participants’ busy lives as opposed to a participant having to schedule their lives around a busy study-site schedule.
Longitudinal studies provide extremely valuable information to medical researchers that cannot be obtained with cross-sectional studies. For example, to determine if a vaccine is effective, longitudinal research is needed to assess the retention of immunity over time while monitoring safety signals. Making study visits as convenient as possible for participants allows researchers to achieve statistical validity by retaining participants throughout the study which equates to valuable information that can be translated to global vaccine initiatives.
ABOUT THE AUTHOR:
Brian Neman serves as the Co-Founder and CEO of Sanguine Biosciences. Brian focuses on all items relating to commercialization and relationships with researchers; he is an adjunct professor of Digital Health at USC, and co-founded Sanguine in 2010 out of his graduate program in healthcare administration at USC. He is also on the boards and committees of various organizations including HD Care, BIOCOM Big Data Committee, and more.
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