BACKGROUND Patients with substance use disorders (SUD) are at increased risk for symptom deterioration following treatment, with up to 60% resuming substance use the first-year post treatment, and craving, together with neurocognitive and mental health variables play important roles in the understanding of the trajectories from abstinence to substance use. OBJECTIVE This study aims to improve our understanding of specific profiles of variables explaining SUD symptom deterioration. Specifically how individual variability in mental health, neurocognitive functioning, and smartphone use is associated with craving and substance use in a young adult clinical population. METHODS In this pilot study, 26 patients with SUD were included 2 weeks prior to discharge from inpatient SUD treatment. Patients underwent baseline neuropsychological and mental health assessments and were equipped with smartwatches and downloaded an app for mobile sensor data collection on their smartphones. Every 2 days for up to 8 weeks the patients were administered mobile ecological momentary assessments (EMA) assessing substance use, craving, mental health, cognition, and a mobile go/no-go performance task. Repeated EMAs, as well as battery use sensor data was averaged across all days per subject and used as candidate input variables in models of craving intensity and relapse. RESULTS A total of 455 momentary assessments were completed. Using EMA and baseline data as candidate input variables, and craving and substance use as responses, automated model selection identified mean craving intensity as the most important predictor of substance use, with variability in self-reported impulsivity, mental health, and battery use as the significant predictors of craving intensity. CONCLUSIONS This study adds novelty by collecting high intensity data, for a considerable period of time, including both mobile sensor and mobile cognitive assessment data. The study also contributes to our knowledge about the most severe part of this clinical population in a vulnerable period during and after discharge from inpatient treatment. We confirmed the importance of temporal variability in executive dysfunction and mood in explaining variability in craving, and in addition that phone use may add to this understanding. Finally, we found that craving intensity is an important explanatory variable in relapse prediction. Our results inform further work towards precision medicine and just-in-time interventions with young adults with substance use disorders and may serve as decision support for clinicians evaluating discharge.

Background Patients with substance use disorders (SUDs) are at increased risk for symptom deterioration following treatment, with up to 60% resuming substance use within the first year posttreatment. Substance use craving together with cognitive and mental health variables play important roles in the understanding of the trajectories from abstinence to substance use. Objective This prospective observational feasibility study aims to improve our understanding of specific profiles of variables explaining SUD symptom deterioration, in particular, how individual variability in mental health, cognitive functioning, and smartphone use is associated with craving and substance use in a young adult clinical population. Methods In this pilot study, 26 patients with SUDs were included at about 2 weeks prior to discharge from inpatient SUD treatment from 3 different treatment facilities in Norway. Patients underwent baseline neuropsychological and mental health assessments; they were equipped with smartwatches and they downloaded an app for mobile sensor data collection in their smartphones. Every 2 days for up to 8 weeks, the patients were administered mobile ecological momentary assessments (EMAs) to evaluate substance use, craving, mental health, cognition, and a mobile Go/NoGo performance task. Repeated EMAs as well as the smartphone’s battery use data were averaged across all days per individual and used as candidate input variables together with the baseline measures in models of craving intensity and the occurrence of any substance use episodes. Results A total of 455 momentary assessments were completed out of a potential maximum of 728 assessments. Using EMA and baseline data as candidate input variables and craving and substance use as responses, model selection identified mean craving intensity as the most important predictor of having one or more substance use episodes and with variabilities in self-reported impulsivity, mental health, and battery use as significant explanatory variables of craving intensity. Conclusions This prospective observational feasibility study adds novelty by collecting high-intensity data for a considerable period of time, including mental health data, mobile cognitive assessments, and mobile sensor data. Our study also contributes to our knowledge about a clinical population with the most severe SUD presentations in a vulnerable period during and after discharge from inpatient treatment. We confirmed the importance of variability in cognitive function and mood in explaining variability in craving and that smartphone usage may possibly add to this understanding. Further, we found that craving intensity is an important explanatory variable in understanding substance use episodes.