ABSTRACT
When studying recurrence of depression, researchers should pay attention to cases where physicians' assessment corresponds to the patients' perception. However, they should also focus on potential signs of recurrence when the recurrence is suspected by the physicians but not the patients (false-negative zeros). Because false negatives can delay diagnosis and treatment, we aimed to investigate "sitting idly" as a predictor influencing no alert sign of recurrence and estimated the counts of recurrence of depression. A smartphone application and a wearable device were used to collect lifelog data from 89 remitted depressive patients over one year. Recurrent depression was defined using the Japanese version of the Kessler Psychological Distress Scale and Patient Health Questionnaire-9 scores. Estimates of the population-averaged parameters indicated that daily hours of sitting idly increased the chances of recurrent depression occurring two to four weeks later. Exposure to daily ultraviolet light reduced depression relapse. Although long sleep was a determinant of zero outcome of the recurrence of depression after two to four weeks, daily hours of sitting idly can negate it. Thus, daily hours of sitting idly could reduce overdispersion of the recurrence of depression, and we could measure recurrent depression accurately by considering changes in sitting idly.
Subject(s)
Depression , Depressive Disorder, Major , Depression/diagnosis , Depressive Disorder, Major/diagnosis , Humans , Patient Health Questionnaire , Recurrence , SoftwareABSTRACT
BACKGROUND: Although depression has a high rate of recurrence, no prior studies have established a method that could identify the warning signs of its recurrence. METHODS: We 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. We assessed depression and its recurrence using both the Kessler Psychological Distress Scale (K6) and the Patient Health Questionnaire-9. RESULTS: A panel vector autoregressive analysis indicated that long sleep time was a important risk factor for the recurrence of depression. Long sleep predicted the recurrence of depression after 3 weeks. CONCLUSIONS: The panel vector autoregressive approach can identify the warning signs of depression recurrence; however, the convenient sampling of the present cohort may limit the scope towards drawing a generalised conclusion.
Subject(s)
Depression/diagnosis , Early Diagnosis , Adult , Feasibility Studies , Female , Humans , Male , Middle Aged , Patient Health Questionnaire , Recurrence , Regression Analysis , Risk Factors , Software , Wearable Electronic DevicesABSTRACT
[This corrects the article DOI: 10.2196/jmir.8602.].
ABSTRACT
BACKGROUND: In the treatment of major depression, antidepressants are effective but not curative. Cognitive behavioral therapy (CBT) is also effective, alone or in combination with pharmacotherapy, but accessibility is a problem. OBJECTIVE: The aim is to evaluate the effectiveness of a smartphone CBT app as adjunctive therapy among patients with antidepressant-resistant major depression. METHODS: A multisite, assessor-masked, parallel-group randomized controlled trial was conducted in 20 psychiatric clinics and hospitals in Japan. Participants were eligible if they had a primary diagnosis of major depression and were antidepressant-refractory after taking one or more antidepressants at an adequate dosage for four or more weeks. After a 1-week run-in in which participants started the medication switch and had access to the welcome session of the app, patients were randomized to medication switch alone or to medication switch plus smartphone CBT app via the centralized Web system. The smartphone app, called Kokoro-app ("kokoro" means "mind" in Japanese), included sessions on self-monitoring, behavioral activation, and cognitive restructuring presented by cartoon characters. The primary outcome was depression severity as assessed by masked telephone assessors with the Patient Health Questionnaire-9 (PHQ-9) at week 9. The secondary outcomes included the Beck Depression Inventory-II (BDI-II) and Frequency, Intensity, and Burden of Side Effects Ratings (FIBSER). RESULTS: In the total sample (N=164), 81 participants were allocated to the smartphone CBT in addition to medication change and 83 to medication change alone. In the former group, all but one participant (80/81, 99%) completed at least half, and 71 (88%) completed at least six of eight sessions. In the intention-to-treat analysis, patients allocated the CBT app scored 2.48 points (95% CI 1.23-3.72, P<.001; standardized mean difference 0.40) lower on PHQ-9 than the control at week 9. The former group also scored 4.1 points (95% CI 1.5-6.6, P=.002) lower on BDI-II and 0.76 points (95% CI -0.05 to 1.58, P=.07) lower on FIBSER. In the per-protocol sample (comfortable with the smartphone app, still symptomatic, and adherent to medication with mild or less side effects after run-in), the intervention group (n=60) scored 1.72 points (95% CI 0.25-3.18, P=.02) lower on PHQ-9, 3.2 points (95% CI -0.01 to 6.3, P=.05) lower on BDI-II, and 0.75 points (95% CI 0.03-1.47, P=.04) lower on FIBSER than the control (n=57). The treatment benefits were maintained up to week 17. CONCLUSIONS: This is the first study to demonstrate the effectiveness of a smartphone CBT in the treatment of clinically diagnosed depression. Given the merits of the mobile mental health intervention, including accessibility, affordability, quality control, and effectiveness, it is clinically worthwhile to consider adjunctive use of a smartphone CBT app when treating patients with antidepressant-resistant depression. Research into its effectiveness in wider clinical contexts is warranted. TRIAL REGISTRATION: Japanese Clinical Trials Registry UMIN CTR 000013693; https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ ctr_view.cgi?recptno=R000015984 (Archived by WebCite at http://www.webcitation.org/6u6pxVwik).
