Clinical trial · Interventional
Adaptive Mobile Interventions to Reduce Cancer Risk Behaviors
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 12, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260912-000001
Summary
Brief summary (as posted)
Tobacco use remains the leading cause of preventable death, causing over 400,000 annual deaths in the United States alone. Smartphone-based interventions, particularly those leveraging real-time adaptive messaging, represent a promising yet underutilized approach to delivering personalized tobacco and cannabis treatment. The investigator's ongoing NCI funded micro-randomized trial (MRT; R01 CA246590) has shown initial feasibility in reducing smoking urges through situationally tailored cognitive-behavioral therapy (CBT) and mindfulness-based acceptance and commitment-based therapy (ACT) messages triggered by real-time contextual data (e.g., geolocation, momentary stress). To advance from a static MRT framework to a dynamic, data-driven just-in-time adaptive intervention (JITAI), this project aims to develop, test, and refine a reinforcement learning (RL) algorithm that can continuously adapt to user needs in real-time, enhancing treatment outcomes for various tobacco and cannabis products. To ensure optimal usability and engagement, the investigators will conduct user-centered testing with the developed RL-based intervention delivery in one cohort (N=7) over 45 days. This will include usability assessment via the System Usability Scale, analysis of app interaction metrics, and semi-structured interviews to gather feedback for refining message content, timing, and design.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Smoking Cessation | — | UNRESOLVED | — |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Smartphone-based intervention messages | Behavioral | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- type
- EXPERIMENTAL
- label
- RL-informed intervention
- description
- Participants complete a 14-day Ecological Momentary Assessment (EMA) training phase using a smartphone app (MetricWire), during which the participant responds to up to 3 randomly prompted and cigarette-triggered EMA surveys per day while the app passively collects GPS data. These data are used to identify high-risk locations and time periods and to inform a previously trained reinforcement learning (RL) algorithm. During the subsequent 30-day intervention phase, the RL algorithm delivers personalized intervention messages (cognitive-behavioral therapy \[CBT\], acceptance and commitment therapy \[ACT\], or attention control) triggered by geofence entry at high-risk locations.
- interventionNames
- Behavioral: Smartphone-based intervention messages
Primary outcomes (3)
- measure
- Change in smoking urge as assessed by a single item
- timeFrame
- 15 minutes after message delivery
- description
- The primary outcome will be change in participants' rating of smoking urge in EMA-post surveys, prompted 15 minutes after intervention message delivery, and controlling for the ratings in EMA-pre surveys. Urge will be assessed by a single item on a 5-point scale, ranging from 1-5; (1-very low, to 5-very high).
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
- Maximum age
- 40 Years
Show eligibility criteria text
Inclusion Criteria: * live in the U.S.; * are between 18 and 40 years of age; * own a smartphone with iOS and Android operating system and GPS capabilities; * are carrying smartphone every day; * are willing to participate in the study for 44 days and give the research team access to the phone GPS data; * have smoked ≥100 cigarettes in the participant's life and currently smoke at least 3 cigarettes per day on 5 or more days of the week; * are planning to quit smoking within the next 30 days. Exclusion Criteria: * None
References
Publications (0)
Data not yet available