Abstract
The current paper introduced the two joint studies by the study group of social medicine and health economist. The study group collected digital data consisting of individual activity records such as location or mobility information (lifelog data) from 89 patients who were on maintenance therapy for depression for a year, using a smartphone application and a wearable device.
Before these joint studies, no prior studies have established a method that could identify the warning signs of its recurrence. In addition, to prevent relapse of patients with major depression, it is necessary to examine the predictors influencing false negatives and identify the early signs of recurrence.
The first study by a panel vector autoregressive model indicated that long sleep time was an important risk factor for the recurrence of depression. Long sleep predicted the recurrence of depression after 3 weeks. Recurrent depression was defined by the Kessler Psychological Distress Scale and the Patient Health Questionnaire-9 scores. In contrast, considering the small number of relapsed cases and the overdispersion generated by excess zero, the second study aimed to investigate “sitting idly” as a predictor influencing falsenegatives using a zero-inflated negative binomial model because false negatives which can lead to delays in diagnosis and treatment must be avoided. Estimates of the population-averaged parameters indicated that daily hours of sitting idly increased the chances of recurrent depression two or four weeks later. The change in exposure to daily UV light from non-exposure reduced recurrent depression.
Before the commencement of the joint study, it is indispensable to explain the significance of the economic study clearly to medical researchers. In the academic society where both of medical researchers and economists belong to, it is important to arrange the opportunity to understand the difference in each idea.
