{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T03:36:19Z","timestamp":1789529779445,"version":"build-2803163510"},"reference-count":63,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Form Res"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n Just-in-time adaptive interventions (JITAIs) are a promising approach in mental health care given the potential scalability (ie, interventions are offered automatically and remotely) and preciseness (ie, the right interventions are offered at the right moments). Typically, a smartphone app is programmed to assess users\u2019 psychological states in daily life; when a particular state is detected, the app prompts users to engage in specific behaviors. Conceptually, JITAIs hold significant potential for precision health, although there is currently limited evidence in the literature.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n We implemented this scheme as a smartphone intervention for daily stress management, based on cognitive behavioral therapy (CBT), and evaluated its feasibility and efficacy using a single-case experimental design.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n A total of 8 Japanese adults (community sample: 4 women; mean 37.6, SD 13.1 y) were recruited. An phase design with multiple random baselines was used, where \u201cA\u201d represents the baseline phase and \u201cB\u201d represents the intervention phase. Throughout the study period (28 d), participants were prompted to indicate their momentary levels of stress (range 0\u2010100) using a smartphone thrice a day. The baseline phase duration was randomly varied among participants, lasting between 7 and 14 days. The remaining period was used as the intervention phase (14\u201021 d), where 6 CBT-based exercises (ie, breath control, mindfulness, relaxation, self-talk, cognitive defusion, and cognitive restructuring) were offered depending on the reported levels of stress.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n Approximately 70% (6\/8) of the participants perceived the intervention to be useful and helpful. A randomization test detected a statistically significant decrease in reported stress levels after the intervention began (\n P<\/jats:italic>\n =.005), though this effect was less pronounced when analyzed individually for each participant. Multilevel model analysis detected a significant acute reduction in the momentary level of stress right after completing a CBT-based exercise (pre-exercise: mean 47.98, SD 21.65; post exercise: mean 42.13, SD 19.88;\n P<\/jats:italic>\n =.03; Cohen\n dz<\/jats:italic>\n =0.58). Also, a significant reduction in depressive rumination was observed in the postintervention assessment (preintervention: mean 13.00, SD 3.21; post intervention: mean 9.25, SD 2.60;\n P<\/jats:italic>\n =.01, Cohen\n dz<\/jats:italic>\n =1.17).\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n The intervention was feasible and effective in reducing subjective stress (and rumination) in the study sample. The small sample size and the nonclinical nature of the sample may limit the generalizability and implications of the study findings for clinical practice. More evidence should be collected to draw solid conclusions for technical and technological as well as clinical aspects of mobile interventions. Accumulating exemplars with different implementations will clarify how a JITAI can be designed and developed on a mobile platform and how the program can be delivered in the prevention and treatment of mental ill health.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/69556","type":"journal-article","created":{"date-parts":[[2025,4,11]],"date-time":"2025-04-11T07:35:06Z","timestamp":1744356906000},"page":"e69556-e69556","source":"Crossref","is-referenced-by-count":1,"title":["Just-in-Time Delivery of Cognitive Behavioral Therapy\u2013Based Exercises: Single-Case Experimental Design With Random Multiple 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