Abstract
Computerized ecological momentary assessment (EMA) is widely accepted as a “gold standard” method for capturing momentary symptoms repeatedly experienced in daily life. Although many studies have addressed the within-individual temporal variations in momentary symptoms compared with simultaneously measured external criteria, their concurrent associations, specifically with continuous physiological measures, have not been rigorously examined. Therefore, in the present study, we first examined the variations in momentary symptoms by validating the associations among self-reported symptoms measured simultaneously (depressive mood, anxious mood, and fatigue) and then investigated covariant properties between the symptoms (especially, depressive mood) and local statistics of locomotor activity as the external objective criteria obtained continuously. Healthy subjects (N = 85) from three different populations (adolescents, undergraduates, and office workers) wore a watch-type computer device equipped with EMA software for recording the momentary symptoms experienced by the subjects. Locomotor activity data were also continuously obtained by using an actigraph built into the device. Multilevel modeling analysis confirmed convergent associations by showing positive correlations among momentary symptoms. The increased intermittency of locomotor activity, characterized by a combination of reduced activity with occasional bursts, appeared concurrently with the worsening of depressive mood. Further, this association remained statistically unchanged across groups regardless of group differences in age, lifestyle, and occupation. These results indicate that the temporal variations in the momentary symptoms are not random but reflect the underlying changes in psychophysiological variables in daily life. In addition, our findings on the concurrent changes in depressive mood and locomotor activity may contribute to the continuous estimation of changes in depressive mood and early detection of depressive disorders.
Highlights
Ecological momentary assessment (EMA) is a method of acquiring self-reported information about a person’s subjective symptoms at the moment of recording and is used continuously in most cases to record instantaneous states of feeling without recall bias [1,2]
Symptom diaries derived from computerized EMA are generally regarded as the “gold standard” in the fields of psychiatric/psychosomatic medicine and has recently attracted increasing attention as an essential component for healthcare monitoring systems based on the information and communication technology (ICT) [4,5]
To examine the cross validation for the associations of depressive mood scores with local statistics of locomotor activity across the three groups, we considered one categorical variable representing “group.” There was no significant difference in the coefficient for either predictor (Table 3) among the groups, which supports the cross validity of our results
Summary
Ecological momentary assessment (EMA) is a method of acquiring self-reported information about a person’s subjective symptoms at the moment of recording and is used continuously in most cases to record instantaneous states of feeling without recall bias [1,2]. EMA scores for, e.g., depressive mood and fatigue, which are the key symptoms of depression [6] studied mainly in this paper, inevitably fluctuate because of their repetitive nature. Characteristics of these fluctuations have been studied by examining the relationships among simultaneously measured self-reported symptoms [7,8,9]. Some studies demonstrated that addictive behaviors such as smoking [18,19] and alcohol consumption [20,21] are related to the fluctuations in psychological states, e.g., positive/ negative affect and craving. The associations of momentary psychological states with self-reported physical activity were demonstrated [22,23]
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