Introduction Cannabis legalization and adult use are expanding across the U.S., requiring greater knowledge of cannabis risks and benefits. Cannabis use measures traditionally assessed frequency but omitted quantity, an essential element of consumption that is complicated by increasingly varied cannabis products and use patterns. To address this, we developed the self-administered CEI (Cannabis Exposure Inventory) to determine milligrams of THC used per using day (mgTHC/using day). In this study, we examined the test-retest reliability of the CEI mgTHC measure and key component items (i.e., products, routes of administration). Methods Participants were recruited through social media (Facebook and Instagram ads) and Qualtrics Research panels. Eligible participants (n=511) completed initial and retest CEI surveys. Chance-corrected agreement between initial and retest surveys on mean mgTHC/using day was indicated with Intraclass Correlation Coefficients (ICCs); kappa (k) indicated reliability of key dichotomous component variables. Results Overall, ICC for mean mgTHC/using day=0.77, indicating substantial reliability. In demographic subgroups, ICCs were 0.54 (‘other’ race/ethnicity) to 0.86 (Hispanic). ICCs for mean mgTHC/using day among those who used for medical-only, recreational-only and medical-plus-recreational reasons were 0.72, 0.69 and 0.77, respectively; ICCs for those in non-legalized, medical-only and medical-plus-recreational states were 0.70, 0.92 and 0.75, respectively. Binary measures generally exhibited substantial reliability (mean k, last 30 days=0.74; last 7 days=0.73). Conclusion Findings support the CEI mgTHC measure as a reliable instrument for quantifying cannabis use, addressing a critical gap in cannabis measurement. This measure offers a promising approach to provide urgently-needed information on potential harms and benefits of THC exposure.

Introduction: Cannabis use has risen disproportionately among middle-aged and older U.S. adults, groups particularly vulnerable to adverse effects, including cannabis use disorder (CUD). Consumption patterns have diversified in recent years. The quantity of cannabis use, historically measured in limited ways (e.g., number of joints), is now considered a key risk factor for CUD. However, age-related differences in consumption patterns and their relationships with CUD remain understudied. This study investigated age-related differences in consumption patterns and examined the relationship between quantity of use-measured by milligrams of THC (mgTHC)-and self-reported CUD in individuals with regular cannabis use. Materials and Methods: A total of 4134 U.S. adults (ages 18+; 45.9% male, 54.1% female) who reported daily cannabis use completed an online survey assessing cannabis consumption patterns and self-reported Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition's CUD criteria. Pearson's chi-square tests and one-way analysis of variance examined differences in sex, reasons for use, methods of consumption, CUD severity, criteria count, and mgTHC with comparisons across three age-groups (18-49, 50-64, 65+). Regression models, adjusted for sex and reasons for use, analyzed age-specific associations between mgTHC and CUD. Results: Overall, over 70% reported using cannabis for both medical and recreational purposes. Middle-aged adults were more likely to report medical use than younger ones (18.1% vs. 13.7%; p < 0.001) and older adults (14.1%; p = 0.027). Older adults were more likely to report recreational-only use compared with middle-aged adults (15.8% vs. 10.5%; p = 0.002). Smoking buds was the most common consumption method across age-groups, while high-potency concentrate use declined with age. In the overall sample, daily mgTHC was associated with CUD severity, and middle-aged and older adults endorsed fewer CUD criteria than younger adults at all levels of mgTHC; however, age effects were not statistically significant. Discussion: Among daily cannabis consumers, middle-aged and older adults differed from younger consumers in methods of consumption and reasons for use. While both groups consumed lower quantities than their younger counterparts, no age-related differences were observed in the relationship between mgTHC consumption and CUD, contrasting with evidence suggesting that older cannabis consumers may be more vulnerable to cannabis-related negative outcomes.

Objective: Estimating delta-9 tetrahydrocannabinol (mgTHC) using hits involves converting hits to grams via a grams-per-hit ratio (GPHR). Previous studies assumed a single hit size (SHS), ignoring individual hit size variations. This study investigates a multiple qualitative hit size (MQHS) approach based on self-reported hit sizes (small, medium, large) to improve mgTHC estimates. Method: Adults (N = 1,824) who used cannabis in the past week completed an online survey on cannabis consumption, reporting quantities in hits and grams, and estimating their hit sizes. We calculated mgTHC using both SHS (0.06g/hit for flower, 0.012g/hit for concentrate) and MQHS. For the MQHS approach, we calculated median GPHRs for each hit size group and assigned those medians to individuals within that group. Results: For flower, median GPHR increased with hit size (small: 0.042, medium: 0.062, large: 0.093). The MQHS estimate for mgTHC from flower was higher than SHS for large hits (95% CI:[12.4, 50.0]) but showed no difference for medium or small hits (95% CI: [-3.2, 8.1]; 95%CI: [-27.6, 3.4]). For concentrate, median GPHR was similar for small and medium hits but lower than large hits (small: 0.024, medium: 0.025, large: 0.035). MQHS estimates for mgTHC were higher than SHS for all hit sizes (95% CI: [46.3, 86.3]; 95% CI: [24.8, 45.5]; 95% CI: [11.5, 36.5] for large, medium, small hits, respectively). Conclusions: The MQHS estimates captures hit size variability for flower. The floor effect with median GPHRs for concentrates suggests further investigation is needed for MQHS estimates with concentrates. The MQHS approach illustrates a method to develop new standard GPHRs for each qualitative hit size group, after further investigation.

Cannabis legalization has expanded access to high-potency products (e.g., dab concentrates) that deliver large amounts of delta-9-tetrahydrocannabinol (THC). It is unclear whether cannabis consumers mitigate the effects of higher-potency products by consuming smaller amounts (i.e., self-titration). We investigated whether users adjust consumption amounts in response to potency when using cannabis flower and concentrates. Data come from four online surveys of U.S. cannabis consumers (N = 8158) reporting past-month flower and/or dab concentrate use. Participants reported their typical amounts (number of hits or grams) and potencies (%THC). We analyzed relationships between consumption amounts and %THC in three ways: (1) within-subject/between-product, (2) between-subject/between-product, (3) between-subject/within-product. To assess selection biases, we examined correlations among potency, use frequency, and age of initiation. Participants were approximately 52 % female, 84 % White, and 73 % reported daily cannabis use; average age was 42 years (SD = 16). In within-subject/between-product analyses, 59 %-92 % of participants used larger amounts of flower than concentrates. In between-subject/between-product analyses, flower-only consumers reported greater amounts than concentrate-only consumers (Median Hits: 8-14 vs. 5-8; Median Grams: 1-1.5 vs. 0.18-0.5). In between-subject/within-product analyses, using higher-THC versions of a product predicted larger amounts (Flower/Hits: rs = 0.12-0.19; Flower/Grams: rs = 0.07-0.29; Concentrate/Hits: rs = 0.09-0.14; Concentrate/Grams: rs = 0.19-0.25), more frequent use (rs = -0.01-0.39), and earlier initiation (rs = -0.06 to -0.33). Results suggest that cannabis consumers self-titrate when switching between flower and concentrate product types, but more frequent consumers prefer higher-potency versions of a given product type and consume them in larger amounts.

Cannabis use problems are on the rise in the USA, and there is a significant need for novel approaches to increase heavy cannabis users’ access to evidence-based treatment. The objective of this randomized clinical trial (RCT) was to evaluate the efficacy of mobile contingency management (mCM) to reduce cannabis use among individuals with heavy cannabis use. Participants completed 2 weeks of daily ecological momentary assessments and twice daily video saliva tests during a baseline ad lib cannabis use period. Participants randomly assigned to mCM then received 6 weeks of the mCM intervention, whereas control participants received non-contingent payments. Consistent with our main hypothesis, participants in the mCM condition reported significantly greater reductions in bioverified use days (43.1

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.

Anhedonia and depressed mood are two cardinal symptoms of major depressive disorder (MDD). Prior work has demonstrated that cannabis consumers often endorse anhedonia and depressed mood, which may contribute to greater cannabis use (CU) over time. However, it is unclear (1) how the unique influence of anhedonia and depressed mood affect CU and (2) how these symptoms predict CU over more proximal periods of time, including the next day or week (rather than proceeding weeks or months). The current study used data collected from ecological momentary assessment (EMA) in a sample with MDD (N=55) and employed mixed effects models to detect and predict weekly and daily CU from anhedonia and depressed mood over 90 days. Results indicated that anhedonia and depressed mood were significantly associated with CU, yet varied at daily and weekly scales. Moreover, these associations varied in both strength and directionality. In weekly models, less anhedonia and greater depressed mood were associated with greater CU, and directionality of associations were reversed in the models looking at any CU (compared to none). Findings provide evidence that anhedonia and depressed mood demonstrate complex associations with CU and emphasize leveraging EMA-based studies to understand these associations with more fine-grained detail.

LGBT+ adults demonstrate greater cannabis-related problems (e.g., Cannabis Use Disorder [CUD]) compared to non-LGBT+ counterparts. No study has explored age-related disparities in cannabis problems across the adult lifespan, nor have studies identified specific CUD criteria that contribute to elevated CUD among LGBT+ adults. The purpose of this study was to examine associations between LGBT+ identity and age with endorsement of CUD criteria in a sample of regular cannabis consumers. An online sample of N = 4334 (25.1% LGBT+) adults aged 18-64 residing in the U.S. completed an online survey about cannabis use behaviors and CUD diagnostic criteria. Bivariate contrasts revealed significantly greater CUD criteria endorsement among LGBT+ respondents, largely driven by differences at younger ages. However, this effect disappeared in the majority of adjusted logistic regression models. LGBT+ identity was associated with greater probability of use in larger amounts (adjOR = 2.10, 95% CI: 1.22-3.60) and use despite physical/mental health problems (adjOR = 2.51, 95% CI:1.23-5.03). No age*LGBT+ identity interactions were detected. Plotted trends depict more pronounced disparities in outcomes among LGBT+ adults under 35 years. Several potential risk and protective factors including employment, education, and reasons for use were identified. There were age-related differences in these characteristics among LGBT+ and non-LGBT+ respondents. Initial findings highlight the need for LGBT+ research examining trends in health outcomes and sociodemographic and cannabis characteristics across the lifespan. The study also provides a substantive contribution regarding specific cannabis-related problems that young LGBT+ cannabis consumers may be more likely to endorse than their non-LGBT+ counterparts.

Background: Although research suggests that early-life adversity (ELA) and cannabis use are linked, researchers have not established factors that mediate or modify this relationship. Identifying such factors could help in developing targeted interventions. We explored chronic pain as a potential mediator or moderator of this relationship. Methods: Using an online study, we collected cross-sectional data about ELA, cannabis use, and chronic pain to test whether ELA (adverse childhood experiences total score) is associated with cannabis use, and to examine pain as a potential mediator or moderator. Cannabis use was examined two ways: times used per day, and categorized as non-, some, or regular use. Chronic pain was measured as present/absent and as the number of painful body locations (0-8). Analyses used linear and multinomial regression. Results: ELA, chronic pain, and cannabis use were common among respondents. ELA was strongly associated with both measures of cannabis use. The number of painful body locations modestly mediated the association of ELA with cannabis use, reducing the magnitude of regression coefficients by about 1/7. The number of painful body locations modified the association between ELA and cannabis use (p≤0.006), while chronic pain presence/absence (a less-informative measure) had only a nonsignificant modification effect (p≥0.10). When either ELA or pain was high, the other was not associated with cannabis use; when either ELA or pain was low, more painful locations or higher ELA (respectively) was associated with more intense cannabis use. Conclusion: These exploratory findings suggest the importance of ELA and chronic pain as factors contributing to cannabis use, and of accounting for these factors in developing treatment and prevention strategies addressing cannabis use.

BACKGROUND AND AIMS:Amid escalating cannabis legalization and daily consumption in the United States (US), determining the risk of cannabis use disorder (CUD) and relevant consequences among daily consumers has become a public health priority. Understanding these risks requires valid assessment of the daily quantity of delta-9-tetrahydrocannabinol (THC) consumed and its relation to consequences. This study characterized daily cannabis consumption using a new method for estimating milligrams of THC (mgTHC), and examined the relationship between daily mgTHC and CUD severity in a large national sample of daily consumers. DESIGN, SETTING AND PARTICIPANTS:US adult (aged 18+ years) daily cannabis consumers (n = 4134) completed a comprehensive online survey of cannabis consumption patterns (e.g. frequency, quantity, product types, potencies, administration methods) and Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5) CUD criteria. MEASUREMENTS:The primary exposure was past-week daily mgTHC consumption, calculated from survey responses to queries about product type, amount and potency consumed and including adjustments for puff size and loss of THC from specific methods of administration. The primary outcomes were (1) number of CUD criteria (range = 0-11) and (2) CUD severity categories: none, mild, moderate, severe. FINDINGS:Median daily consumption was ~130 mgTHC, with substantial variability (25% ≤ 50 mg and 25% ≥ 290 mg). On average, participants endorsed 2.5 CUD criteria, and 65% met criteria for CUD (39% mild, 18% moderate, 8% severe). Greater daily mgTHC predicted higher CUD criteria count [betalog(mgTHC) = 0.50, 95% confidence interval (CI) = 0.267-0.734] and higher odds of mild [log odds ratio (logOR) = 0.238, 95% CI = 0.184-0.292], moderate (logOR = 0.303, 95% CI = 0.232-0.374) or severe (logOR = 0.335, 95% CI = 0.236-0.435) CUD. CONCLUSIONS:Among daily consumers of cannabis, there appears to be a positive relationship between the daily quantity of cannabis consumed (measured in milligrams of delta-9-tetrahydrocannabinol) and both the risk and severity of cannabis use disorder.

INTRODUCTION:Over the past decade, treatment for opioid use disorder has expanded to include long-acting injectable and implantable formulations of medication for opioid use disorder (MOUD), and integrated treatment models systematically addressing both behavioral and physical health. Patient preference for these treatment options has been underexplored. Gathering data on OUD treatment preferences is critical to guide the development of patient-centered treatment for OUD. This cross-sectional study assessed preferences for long-acting MOUD and integrated treatment using an online survey. METHODS:An online Qualtrics survey assessed preferences for MOUD formulation and integrated treatment models. The study recruited participants (n = 851) in October and November 2019 through advertisements or posts on Facebook, Google AdWords, Reddit, and Amazon Mechanical Turk (mTurk). Eligible participants scored a two or higher on the opioid pain reliever or heroin scales of the Tobacco, Alcohol Prescription Medication and other Substance Use (TAPS) Tool. Structured survey items obtained patient preference for MOUD formulation and treatment model. Using stated preference methods, the study assessed preference via comparison of preferred options for MOUD and treatment model. RESULTS:In the past year, 824 (96.8 %) participants reported non-prescribed use of opioid pain relievers (mean TAPS score = 2.72, SD = 0.46) and 552 (64.9 %) reported heroin or fentanyl use (mean TAPS score = 2.73, SD = 0.51). Seventy-four percent of participants (n = 631) reported currently or previously receiving OUD treatment, with 407 (48.4 %) receiving MOUD. When asked about preferences for type of MOUD formulation, 452 (53.1 %) preferred a daily oral formulation, 115 (13.5 %) preferred an implant, 114 (13.4 %) preferred a monthly injection and 95 (11.2 %) preferred a weekly injection. Approximately 8.8 % (n = 75) would not consider MOUD regardless of formulation. The majority of participants (65.2 %, n = 555) preferred receiving treatment in a specialized substance use treatment program distinct from their medical care, compared with receiving care in an integrated model (n = 296, 34.8 %). CONCLUSIONS:Though most participants expressed willingness to try long-acting MOUD formulations, the majority preferred short-acting formulations. Likewise, the majority preferred non-integrated treatment in specialty substance use settings. Reasons for these preferences provide insight on developing effective educational tools for patients and suggesting targets for intervention to develop a more acceptable treatment system.

Abstract With the escalation of cannabis legalization and commercialization, the need to differentiate low- vs. high-risk patterns of cannabis use, especially among frequent consumers, becomes essential for development of prevention and intervention strategies and public health messaging. The diversity of cannabis products and methods of intake make this task complex. In particular, the lack of valid methods for quantifying use of the intoxicating component of cannabis, i.e., THC, poses a difficult challenge. This presentation will describe a series of internet-based, personalized survey studies of adults who consume cannabis frequently. The aims of the studies are to develop methods for quantifying THC from self-reports of use, identify patterns of use, and determine associations between use and risk. In the first study of adult daily cannabis consumers (n>4000), rates of CUD were 35% no disorder, 39% mild, 18% moderate, 8% severe disorder. Higher severity was significantly related to younger age, unemployment, and specific reasons for use. Latent class analyses identified four distinct subgroups and preliminary analyses showed that those more likely to report oral use were less likely to meet CUD criteria, and those more likely to report use of high potency products were more likely to meet moderate/severe criteria. Two studies (n’s >2000) compared different quantitative formulas for estimating daily THC consumption from vaping or smoking cannabis products. Findings demonstrated how quantity (mgTHC) relates to socio-demographics, use patterns, and CUD severity. However, substantial variability in the estimates obtained across quantitation methods indicates the need for additional studies to determine optimal approaches. Overall, findings show that specific characteristics of use can discriminate low- from high-risk consumption among those who use frequently, which is critical for developing cannabis policy and public health messaging. Disclosure of Interest None Declared

Background: Cannabis use is increasing among middle-aged and older US adults, populations that are particularly vulnerable to the adverse effects of cannabis. Risks for adverse effects differ by cannabis use patterns, which have become increasingly heterogeneous. Nevertheless, little is known about age differences in such patterns.Objective: To investigate age differences in cannabis use patterns, comparing younger (age 18-49), middle-aged (age 50-64), and older adults (age ≥65).Methods: A total of 4,151 US adults with past 7-day cannabis consumption completed an online survey (35.1% male; 60.1% female; 4.8% identified as "other"). Regression models examined age differences in cannabis use patterns.Results: Compared to younger adults, middle-aged and older adults were more likely to consume cannabis during evening hours (50-64: adjusted odds ratio [aOR] = 2.98, 95% CI 2.24-3.96; ≥65: aOR = 4.23, 95 CI 2.82-6.35); by only one method (50-64: aOR = 1.67, 95% CI 1.34-2.09; ≥65: aOR = 3.38, 95 CI 2.24-5.09); primarily by smoking as the only method (50-64: aOR = 1.52, 95% CI 1.29-1.78; ≥65: aOR = 2.12, 95 CI 1.64-2.74); but less likely to consume concentrated cannabis products (concentrates) with extremely high %THC (50-64: aOR = 0.71, 95% CI 0.54-0.93; ≥65: aOR = 0.30, 95 CI 0.16-0.55). Age differences in cannabis use patterns were also observed between middle-aged and older adults.Conclusion: Findings suggest that middle-aged and older adults may engage in less risky cannabis use patterns compared to younger groups (e.g. lower likelihood of consuming highly potent concentrates). However, findings also underscore the importance of recognizing risks unique to these older demographics, such as smoking-related health events. Consequently, prevention strategies targeting such use patterns are needed.

Background Existing interventions for co-occurring depression and cannabis use often do not treat both disorders simultaneously and can result in higher rates of symptom relapse. Traditional in-person interventions are often difficult to obtain due to financial and time limitations, which may further prevent individuals with co-occurring depression and cannabis use from receiving adequate treatment. Digital interventions can increase the scalability and accessibility for these individuals, but few digital interventions exist to treat both disorders simultaneously. Targeting transdiagnostic processes of these disorders with a digital intervention—specifically positive valence system dysfunction—may yield improved access and outcomes. Objective Recent research has highlighted a need for the inclusion of individuals with lived experiences to assist in the co-design of interventions to enhance scalability and relevance of an intervention. Thus, the purpose of this study is to describe the process of eliciting feedback from individuals with elevated depressed symptoms and cannabis use and co-designing a digital intervention, Amplification of Positivity—Cannabis Use Disorder (AMP-C), focused on improving positive valence system dysfunction in these disorders. Methods Ten individuals who endorsed moderate to severe depressive symptoms and regular cannabis use (2-3×/week) were recruited online via Meta ads. Using a mixed methods approach, participants completed a 1-hour mixed methods interview over Zoom (Zoom Technologies Inc) where they gave their feedback and suggestions for the development of a mental health app, based on an existing treatment targeting positive valence system dysfunction, for depressive symptoms and cannabis use. The qualitative approach allowed for a broader investigation of participants’ wants and needs regarding the engagement and scalability of AMP-C, and the quantitative approach allowed for specific ratings of intervention components to be potentially included. Results Participants perceived the 13 different components of AMP-C as overall helpful (mean 3.9-4.4, SD 0.5-1.1) and interesting (mean 4.0-4.9, SD 0.3-1.1) on a scale from 1 (not at all) to 5 (extremely). They gave qualitative feedback for increasing engagement in the app, including adding a social component, using notifications, and being able to track their symptoms and progress over time. Conclusions This study highlights the importance of including individuals with lived experiences in the development of interventions, including digital interventions. This inclusion resulted in valuable feedback and suggestions for improving the proposed digital intervention targeting the positive valence system, AMP-C, to better match the wants and needs of individuals with depressive symptoms and cannabis use.

BACKGROUND AND OBJECTIVES:Limited evidence guides the efficacy and safety of cannabis for therapeutic purposes (CTP). Healthcare providers lack requisite knowledge to advise and support patients. This study aimed to describe and compare several aspects of initial CTP interactions across different provider types. METHODS:Adult cannabis consumers (N = 507) from the United States completed an anonymous online survey about their initial CTP interaction with their healthcare provider. Providers were categorized into four groups (Mental Health [MH], Family Medicine [FM], Medical Clinics [MC], and Other Specialty [OS]). Analyses compared several aspects of the interaction (e.g., risk mitigation, recommendations, satisfaction/confidence) across groups. RESULTS:Less than half of the sample reported discussion of cannabis risks (44.0%) or follow-ups at subsequent visits (46.7%). Recommendations (where to obtain, consumption method, dose, frequency, and authorization) were uncommon (9.7%-25.2%). While the MH group reported the highest rates of risk mitigation behaviors, regression models adjusted for sociodemographic and cannabis characteristics were largely nonsignificant. For recommendations, the MC group was more likely than the MH group to report receiving all recommendations (p < .05). Younger age and greater cannabis-related problems increased likelihood of risk mitigation and recommendations. DISCUSSION AND CONCLUSIONS:CTP interactions focused on risk but generally lacked comprehensive recommendations that could potentially promote safe use. Data from provider perspectives could support the need for CTP guidelines and develop training for healthcare providers to promote safe CTP practices. SCIENTIFIC SIGNIFICANCE:For the first time, this study explored several aspects of CTP interactions and compared experiences across a variety of providers.

Objective: Rates of problematic cannabis use among young adults are high and increasing. Craving for cannabis varies throughout the day and is an important risk factor for cannabis use, yet no studies to date have tested interventions offered at the moment craving is experienced in the natural environment. Method: This study used an efficient and innovative microrandomized trial design to test two distinct types of coping messages (mindfulness strategy vs. distraction strategy) offering brief coping strategies when moderate to severe craving was reported via ecological momentary assessment (EMA). Results: Young adults who regularly use cannabis (N = 53) were readily engaged in this 4-week intervention, and EMA completion was high throughout, demonstrating excellent feasibility of this approach. However, results indicated that coping messages did not reduce craving at the next EMA relative to control (thank you) messages, with no significant change in efficacy over time. Furthermore, exploratory analyses found that neither mindfulness nor distraction resulted in reduced craving relative to the control message. Conclusions: Despite this outcome, this method of testing digital interventions targeting momentary risks for substance use such as craving holds promise for rapidly and efficiently screening a wide variety of intervention strategies for inclusion in future just-in-time adaptive interventions.