ArticleBehavior therapy2024
Development of Mobile Contingency Management for Cannabis Use Reduction.
Article in Behavior therapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Current methods for analyzing time-series patient-generated health data to assess treatment response: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Proof-of-Concept Pilot Study on the Integration of a Contingency Management Model to Address Substance Use Among Individuals Enrolled in Early Intervention Programs for Psychosis.Early intervention in psychiatry · 2025Article
- Cannabis use disorder: from neurobiology to treatment.The Journal of clinical investigation · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 3 institutions in 2 countries.
Funding
Abstract
Many interventions for cannabis use disorder (CUD) are associated with decreases in frequency and quantity of use but fail to increase overall rates of sustained abstinence. It is currently unknown whether reductions in use (in the absence of sustained abstinence) result in clinically significant improvements in functioning. The objective of this study was to refine a mobile contingency management approach to reduce cannabis use to ultimately evaluate whether reductions in frequency and quantity of cannabis are related to improvements in functional and mental health status. Three cohorts of participants (n = 18 total, n = 10 women) were enrolled and completed 2 weeks of ecological momentary assessment (EMA) during a baseline ad lib cannabis use period, followed by a 6-week reduction period. Participants completed EMA assessments multiple times per day and were prompted to provide videotaped saliva cannabis testing 2-3 times daily. Data from participants who were at least 80% adherent to all EMA prompts were analyzed (13 out of 18). During the ad lib phase, participants were using cannabis on 94% of the days and reported using a mean of 1.42 grams daily. The intervention was a mobile application that participants used to record cannabis use by saliva tests to bioverify abstinence and participants completed electronic diaries to report their grams used. During the 6-week intervention phase, participants reported reducing their use days to 47% of the days with a reported mean of .61 grams daily. In the last cohort, at least 50% of the heavy users were able to reduce their cannabis use by at least 50%. The effect of cannabis reduction (versus abstinence) is largely unknown. Observations suggest that it is possible to develop a mobile intervention to reduce cannabis use among heavy users, and this paradigm can be utilized in future work to evaluate whether reductions in cannabis use among heavy users will result in improvements in functional and mental health status.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.