Date Presented 03/27/20
This study used smartphone-based EMA to investigate moment-to-moment associations between poststroke depressive symptoms and daily functioning. We found that fatigue and lack of interest can be target symptoms to improve daily functioning among stroke survivors. Improving self-appraisals of daily functioning can be an effective way to manage depressive symptoms. EMA can be a useful tool to track real-time target symptoms in naturalistic contexts.
Primary Author and Speaker: Yejin Lee
Additional Authors and Speakers: Eric Lenze, Carolyn Baum, Jin-Moo Lee, Christopher Metts, Michael Yingling, Robert Fucetola, Mandy Fong, Colin Depp, Robert Heaton, Chenyang Lu, Albert Lai
Contributing Authors: Alex Wong
PURPOSE: Stroke survivors experience limitations in daily functional tasks. These limitations are associated with an increased risk of developing depression after stroke (Brown, Hasson, Thyselius, & Almborg, 2012). Considering that mood and function can fluctuate from day to day and are very context-dependent (Kratz, Murphy, & Braley, 2017), a better understanding of moment-to-moment associations between post-stroke daily functioning and depressive symptoms could provide insight for developing just-in-time adaptive interventions to improve daily functioning among stroke survivors. Ecological momentary assessment (EMA) is an effective measure to capture within-person dynamics in the person’s natural environment and offers benefits over recall surveys, including improved reliability (Shiffman & Stone, 2008). Therefore, this study aimed to examine moment-to-moment associations between these factors after stroke using EMA. Three hypotheses were established in this study: (1) concurrent associations: depressive symptoms will be associated with daily functioning at the same time point, (2) lagged associations: depressive symptoms will be associated with daily functioning at the next time point, and (3) lagged associations: daily functioning will be associated with depressive symptoms at the next time point.
DESIGN: The study design was a repeated-measures observational study of daily monitoring using EMA.
METHOD: Participants completed EMA surveys 5 times a day for 14 days. For each survey, they reported the current-moment activities in which they were participating and appraised their performance via a smartphone. Participants also rated their levels of seven depressive symptoms, including fatigue, depression, worthlessness, lack of concentration, lack of interest, poor appetite, and slowness. Multilevel models were used to analyze moment-to-moment associations of these factors by controlling for age, race, sex, education, and marital status.
RESULTS: Forty-eight participants completed the study. The total number of collected EMA time points was 2753. To address hypothesis 1, our findings from concurrent associations suggested that higher fatigue (coefficient = -0.804; 95% CI -1.09 to -0.51) and lack of interest (coefficient = -0.497; 95% CI -0.75 to -0.24) were related to poorer daily functioning at the same time point. To address hypothesis 2, findings from lagged associations suggested that higher fatigue predicted lower daily functioning at the next time point (coefficient = -0.481; 95% CI -0.87 to -0.09). To address hypothesis 3, findings from lagged associations suggested that people with lower average daily functioning reported higher momentary fatigue, depression, worthlessness, lack of concentration, lack of interest, and slowness at the next time point (p < 0.05), but no significant results were found for within-person variables (p > 0.05).
CONCLUSION: Fatigue and lack of interest can be target symptoms to improve daily functioning among stroke survivors. Conversely, identifying ways to improve self-appraisals of daily functioning can also be an effective way to manage depressive symptoms, which may serve as a potential intervention to optimize psychological well-being in this population. This study also suggests that smartphone-based EMA can be a useful tool to monitor dynamic associations between post-stroke symptoms and daily functioning and to identify real-time targets, which will be helpful for occupational therapists to design and deliver personalized interventions to improve mood and daily functioning.
References
Brown, C., Hasson, H., Thyselius, V., & Almborg, A. H. (2012). Post-stroke depression and functional independence: a conundrum. Acta Neurologica Scandinavica, 126(1), 45-51. doi: https://doi.org/10.1111/j.1600-0404.2011.01595.x
Kratz, A. L., Murphy, S. L., & Braley, T. J. (2017). Ecological momentary assessment of pain, fatigue, depressive, and cognitive symptoms reveals significant daily variability in multiple sclerosis. Archives of Physical Medicine and Rehabilitation, 98(11), 2142-2150. doi: 10.1016/j.apmr.2017.07.002
Shiffman, S., Stone, A. A., & Hufford, M. R. (2008). Ecological momentary assessment. Annual Review of Clinical Psychology, 4, 1-32. doi: https://doi.org/10.1146/annurev.clinpsy.3.022806.091415
