A new research study supported by Johnson & Johnson Health and Wellness Solutions suggests that health risk assessments (HRAs) can help predict depression in segments of the population who may not be routinely screened in traditional healthcare settings. HRAs are often used by employers and health plans to identify modifiable health risks, such as stress, sleep and quality of life. This new study demonstrates the value of HRAs to identify predictors for depression.
The research study found that about 25 percent of the HRA participants experienced mild or "sub-threshold" symptoms of depression. One in five of them deteriorated over time to more significant distress, as measured by an increase in symptoms of depression. These individuals had a similar level of symptoms as individuals with chronic depression at the end of the study and experienced an even greater level of functional impairment in their day to day lives. The study also identified key risk factors that predicted both positive and negative changes in depressive symptoms. As employers look for ways to increase the health and productivity of their employees, the value of further research using HRAs to study populations at risk for depression is notable.
"This study indicates that HRAs can be a useful and powerful analytic tool to identify and begin early intervention for at-risk populations," said Heather Cole-Lewis, PhD, Behavioral Scientist, Johnson & Johnson Health and Wellness Solutions. "There is a substantial group of people among our HRA participants who have depressive symptoms but might not necessarily meet criteria indicating a need for clinical management. We know now that a significant portion of them are at risk of progressing to levels of distress and experiencing considerable productivity impairment in the process. We need to find ways to reach these individuals before they experience such difficulties."
Symptoms of depression have been shown to decrease daily function and productivity, and play a significant role in determining the success of population health management efforts. Given that 53 percent of large U.S. employers and 23 percent of small U.S. employers use HRAs with employees, the opportunity for further longitudinal data analysis in large populations is compelling and has the potential to facilitate earlier interventions for preventing depression.
"HRAs have been used for a long time to look at the health information for populations at large. One of the most useful takeaways from this study is that HRAs can help identify individuals with subthreshold depressive symptoms who may deteriorate over time, as well as those who are at risk of chronic depression," said Jennifer Turgiss, Vice President, Behavioral Science & Advanced Analytics, Johnson & Johnson Health and Wellness Solutions. "We at Johnson & Johnson recommend that health plan providers, including self-insured employers, consider using HRAs to help identify subthreshold individuals and explore new methods to reach them as early as possible with solutions that build important skills, such as resilience, to help manage and improve low-levels of depression."
About the Study
The study, "Trajectories of Depressive Symptoms among Online Health Risk Assessment Participants," was published in the Journal of Medical Internet Research on March 31, 2017. It was conducted by Johnson & Johnson Health and Wellness Solutions as part of the company's commitment to health and wellbeing. The study used data collected from the online HRAs of 22,963 adult participants.
The study used a growth mixture model to examine longitudinal trends in depressive symptoms of voluntary HRA adult participants. The study identified five classes of depressive symptom trajectories: "minimal depression" (scores were consistently low across time), "low risk" (scores remained sub-threshold over time), "deteriorating" (scores began at sub-threshold but approached severe depression over time), "chronic" (scores remained in highly depressive category over time) and "remitting" (moderate depression to start but crossed into minimal by the end).
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