Abstract Background Accurate assessments of mood, pain, and fatigue, are fundamental for evaluating and optimizing well-being in later life. However, traditional methods often do not capture instability – a measure of variability that incorporates the temporal order of the experiences. Objectives: Using the Real-time Online Assessment and Mobility Monitoring (ROAMM), a novel smartwatch platform, we sought to compare the instability of ecologically derived ratings of mood, pain, and fatigue symptoms among community-dwelling older adults. Methods Thirty-one participants answered questions on a smartwatch for approximately 2 weeks. Questions were delivered in the morning, afternoon, and evening, three days a week. Participants rated their current mood, pain, and fatigue on an anchored scale ranging from 0 to 10. We calculated the mean squared successive difference (MSSD) between ratings to determine the instability of each symptom. Results On average, instability was highest for mood (MSSD = 4.44) and lowest for pain (MSSD=1.51). Mood instability was moderately correlated with pain (r= 0.42, p = 0.02) and fatigue (r= 0.45, p = 0.01) instability, while fatigue and pain instability were strongly correlated (r=0.82, p< 0.01). Conclusions Results suggest that instability in pain, mood, and fatigue ratings are inter-correlated. The strong association between pain and fatigue instability suggests a co-occurrence that will aid in understanding the origins of these complex states. Repeated ecological assessment of common gerontological symptoms might provide new knowledge about the psychosocial well-being of older adults.