RESUMO
Effective interventions to support compassionate patient- and self-care requires an understanding of how to best assess compassion. Micro-ecological momentary assessment (micro-EMA), a method in which participants provide brief responses in real-time within their own environments, can capture changes in compassion across time and contexts. This study examined a micro-EMA approach for measuring the temporal dynamics of compassion in medical students during the COVID-19 pandemic. Medical students (N = 47) completed demographic information and self-report questionnaires assessing empathy and compassion for self and others. Participants then completed six bursts of micro-EMA smartphone-delivered surveys. Each burst was 14 days, with 28 days between bursts. During each burst, participants received four daily micro-EMA surveys assessing compassion, stress, positive affect, and negative affect. Dynamic structural equation modeling was used to examine micro-EMA responses. The overall micro-EMA response rate was 83.75%. On average, daily compassion did not significantly change across the academic year. However, there was significant within-person variability in medical students' compassion trajectories over the training year (b = 0.027, p < .01). At concurrent timepoints, micro-EMA assessed compassion was associated with greater happiness (b = 0.142, p < .001) and lower stress (b = -0.052, p < .05) but was not associated with sadness. In lagged analyses, higher micro-EMA assessed compassion predicted higher next day happiness (b = 0.116, p < .01) and vice versa (b = 0.185, p < .01). Results suggest it is feasible to use micro-EMA to assess daily levels of compassion among medical students. Additionally, there is wide variability in day-to-day fluctuations in compassion levels among medical students, with some students showing substantial increases in daily compassion across the training year and others showing decreases. Positive affect as opposed to negative affect may have particularly strong associations with compassion. Further examination of antecedents and consequences of fluctuations in daily compassion could inform potent intervention targets.
RESUMO
OBJECTIVE: Neuropsychological impairments are observed in individuals with Bipolar Disorder (BD), yet knowledge of how cognitive deficits unfold in real-time remains limited. Given intraindividual variability in mood observed in people with BD, and the potential for mood and cognition to be mutually influential, we employed ambulatory assessment technologies to examine potential contemporaneous (same survey) and lagged (next survey) relationships of congition and mood. METHODS: Outpatients with BD (n = 46) or no psychiatric disorders (heathy volunteers [HV]; n = 20) completed in-laboratory neurobehavioral assessments and 14 days of smartphone-administered mobile cognitive tests and ratings of affective variables. Linear mixed-effects models were used to analyze real-time relationships between mobile cognitive test performance and mood. RESULTS: On in-laboratory tests, participants with BD showed worse cognitive performance than HVs as well as mild depression severity; mood and cognitive performance were unrelated. On mobile cognitive tests and surveys, participants with BD showed somewhat worse cognitive performance and ratings of lower energy and greater sadness relative to HV participants. Among those with BD, mania and sadness earlier in the day related to worse processing speed and better working memory performance, respectively, on the next survey. In contrast, same survey ratings of greater stress related to better working memory, and greater happiness related to better processing speed. CONCLUSIONS: Real-time assessments of mood and cognition provide incremental information beyond what can be gleaned from laboratory assessments. Understanding how these affect-related changes in processing speed emerge and play out in daily life may provide clinically useful information for treatment planning.