Research People and Projects

Although therapeutic use of cannabis is increasing, findings are mixed regarding therapeutic effects of cannabis for certain conditions, such as anxiety. Further, acute cannabis effects could adversely impact psychomotor performance (e.g., slowed reaction time), with subsequent negative effects on daily activities (e.g., work performance, driving skills). Low burden methods to monitor acute cannabis effects through sensors in personal smartphones and keystroke monitoring could ultimately help reduce cannabis’s acute negative effects on psychomotor performance by helping to raise a person’s awareness of cannabis-related impairment. Toward this goal, this U01 will collaborate with individuals who use medical cannabis (MC) in monitoring, with their smartphone and computer, acute therapeutic and adverse effects of cannabis use. Individuals who use MC commonly report cannabis use to relieve chronic pain and/or anxiety, the two conditions of interest for this R01. Smartphone will be used to conduct symptom monitoring of acute cannabis effects on chronic pain and anxiety using Ecological Momentary Assessment (EMA). Phone sensor data will be used to examine acute cannabis effects on psychomotor performance. These fine-grained smartphone “micro” data (e.g., momentary-level) will be combined with longer-term follow-up over 1-year, to examine the impact of cannabis use at a more “macro” level (e.g., over months), because cannabis effects (e.g., on anxiety) at “micro” and “macro” time scales may differ. This U01 will recruit individuals who report therapeutic use of cannabis, with chronic pain and/or anxiety as the primary reasons for MC use (N=400, age >18; 50% female). Participants complete lab assessments at baseline, 3-, 6-, and 12-months in a repeated measures design. Urine sample for THC and CBD level will be done at baseline, 3-, 6-, and 12-months. Each assessment (baseline, 3-, 6-, 12-months) is followed by 14-day daily EMA and phone sensor data collection. Daily EMA (3x/day) and self-initiated EMA of cannabis use (medical, non-medical) will be used. Phone sensor data include, for example, keyboard use (not message content), and accelerometer (e.g., to detect activity level). Study aim 1 will examine links between acute cannabis use and effects (EMA report), psychomotor performance (phone sensor data), and self-reported daily cognitive functioning (e.g., react slowly to things). Study aim 2 will test links, over 1-year, of longer-term effects of cannabis use, computerized measures of psychomotor performance, and self-report of cannabis-related consequences. For each aim, gender differences in cannabis’s short and longer term effects will be explored. The combination of fine-grained subjective (EMA) and objective (phone sensor) data, collected at micro (EMA) and macro time scales over 1-year, will help resolve mixed findings on possible cannabis-related therapeutic benefit, acute risks, and longer-term outcomes (e.g., on psychomotor performance). In line with NIDA priorities, this R01’s novel combination of symptom monitoring methods (EMA, phone sensor data), and “micro” and “macro” data, will guide development of mHealth interventions that reduce risk for cannabis-related harm.