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Advancements in artificial intelligence (AI) for point-of-care ultrasound (POCUS) have ushered in new possibilities for medical diagnostics in low-resource settings. This review explores the current landscape of AI applications in POCUS across these environments, analyzing studies sourced from three databases-SCOPUS, PUBMED, and Google Scholars. Initially, 1196 records were identified, of which 1167 articles were excluded after a two-stage screening, leaving 29 unique studies for review. The majority of studies focused on deep learning algorithms to facilitate POCUS operations and interpretation in resource-constrained settings. Various types of low-resource settings were targeted, with a significant emphasis on low- and middle-income countries (LMICs), rural/remote areas, and emergency contexts. Notable limitations identified include challenges in generalizability, dataset availability, regional disparities in research, patient compliance, and ethical considerations. Additionally, the lack of standardization in POCUS devices, protocols, and algorithms emerged as a significant barrier to AI implementation. The diversity of POCUS AI applications in different domains (e.g., lung, hip, heart, etc.) illustrates the challenges of having to tailor to the specific needs of each application. By separating out the analysis by application area, researchers will better understand the distinct impacts and limitations of AI, aligning research and development efforts with the unique characteristics of each clinical condition. Despite these challenges, POCUS AI systems show promise in bridging gaps in healthcare delivery by aiding clinicians in low-resource settings. Future research endeavors should prioritize addressing the gaps identified in this review to enhance the feasibility and effectiveness of POCUS AI applications to improve healthcare outcomes in resource-constrained environments.
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HIV-related stigma is a primary barrier to seeking HIV care. Online social media interventions utilizing peer-led approaches provide an opportunity to revolutionize HIV health behavior change. Secondary analysis of the UCLA HOPE Study (6 waves) was done to examine the effectiveness of an online peer-led intervention in reducing HIV-related internalized stigma (IS), association between IS and sexual risk behaviors (SRB), and associated costs for changing the likelihood of HIV testing. Among 897 participants, an inverse relationship between IS (Discomfort with people with HIV, Stereotypes, Moral Judgment) and SRB (Number of Sexual Partners, Sexual Encounters) factors was identified over time (p < .05). Engagement in stigma conversations increased participant likelihood to request HIV tests (B = 0.02, Wald = 8.10, p = .004) when made in group versus one-on-one contact. Innovative technology has potential to improve HIV-care efforts through expanded reach to at-risk populations, improved communication maintenance, ease of accessibility, and user anonymity.
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Infecções por HIV , Grupo Associado , Comportamento Sexual , Mídias Sociais , Estigma Social , Humanos , Infecções por HIV/psicologia , Masculino , Feminino , Adulto , Comportamento Sexual/psicologia , Assunção de Riscos , Pessoa de Meia-Idade , Parceiros Sexuais/psicologia , Aceitação pelo Paciente de Cuidados de Saúde/psicologia , Teste de HIV/métodos , Estereotipagem , Adulto JovemRESUMO
Digital health tracking is a source of valuable insights for public health research and consumer health technology. The brain is the most complex organ, containing information about psychophysical and physiological biomarkers that correlate with health. Specifically, recent developments in electroencephalogram (EEG), functional near-infra-red spectroscopy (fNIRS), and photoplethysmography (PPG) technologies have allowed the development of devices that can remotely monitor changes in brain activity. The inclusion criteria for the papers in this review encompassed studies on self-applied, remote, non-invasive neuroimaging techniques (EEG, fNIRS, or PPG) within healthcare applications. A total of 23 papers were reviewed, comprising 17 on using EEGs for remote monitoring and 6 on neurofeedback interventions, while no papers were found related to fNIRS and PPG. This review reveals that previous studies have leveraged mobile EEG devices for remote monitoring across the mental health, neurological, and sleep domains, as well as for delivering neurofeedback interventions. With headsets and ear-EEG devices being the most common, studies found mobile devices feasible for implementation in study protocols while providing reliable signal quality. Moderate to substantial agreement overall between remote and clinical-grade EEGs was found using statistical tests. The results highlight the promise of portable brain-imaging devices with regard to continuously evaluating patients in natural settings, though further validation and usability enhancements are needed as this technology develops.
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Background: Perceived risk of harm associated with cannabis use has decreased in recent decades, particularly among emerging adults who show the highest prevalence of use. Cannabis-related protective behavioral strategies (PBS) are associated with lower cannabis use and fewer consequences; however, individuals who perceive using cannabis as low risk may use cannabis PBS less often. Therefore, using cross-sectional data, we examined the associations between perceived risk of harm associated with cannabis use, cannabis PBS, and cannabis use frequency. Method: Participants were 146 emerging adults between the ages of 18-25 (56.2% female) who reported consuming cannabis at least 3 times/week and completed measures of past-month cannabis use, past three-month use of cannabis PBS, and perceived risk of harm associated with cannabis use. Path analyses examined direct and indirect effects of perceived risk of cannabis-related harm on cannabis frequency through cannabis PBS. Results: Most (66.4%) participants reported no perceived risk of harm associated with occasional cannabis use, whereas 30.1% reported no perceived risk of harm associated with regular cannabis use. Findings indicated a significant indirect effect between perceived risk of harm and cannabis use frequency through cannabis PBS, b = -10.23, SE = 3.80, 95% CI [-17.67, -2.80], p = .007. Conclusions: Among emerging adults who consume cannabis regularly, findings suggest that a greater perceived risk of cannabis-related harm is associated with decreased cannabis use frequency via increased use of cannabis PBS. Although future analyses evaluating causal mechanisms are needed, these findings have clinical implications for harm reduction interventions focused on cannabis use.
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Opioid use disorder is a growing public health concern in the United States, causing economic burden and hindered by stigma. New forms of data, including location data, may improve the effectiveness of interventions for preventing and treating opioid use disorder and/or misuse, increase access to treatment and address racial and ethnic disparities. This qualitative study aimed to identify factors that contribute to users' experience with a publicly available location-tracking mobile app - and investigate their privacy and ethical concerns. The study was conducted through two 15-minute interviews within a 48-h time frame. Participants were recruited from a pool of past research participants, Facebook ads, and referrals, and had to meet certain inclusion criteria related to opioid use disorder and/or misuse. The study had a final sample of 30 participants, 15 male and 15 female. The study suggests that a simple onboarding process and convenient experience can enhance participant adherence to the study app and other similar location-based research apps. However, the study also found that participants had concerns about privacy and transparency about locational privacy when sharing their location data. To improve the app, researchers suggest incorporating user behavior earlier in the app development stage. The study also highlights the importance of addressing ethical and privacy concerns such as limiting the types of collected data, incorporating data encryption and retention strategies, giving access to research staff only, and not sharing the data with third-party companies or law enforcement agencies to increase user satisfaction.
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Aplicativos Móveis , Transtornos Relacionados ao Uso de Opioides , Humanos , Masculino , Feminino , Estados Unidos , Privacidade , Analgésicos Opioides , Coleta de DadosRESUMO
Components of artificial intelligence (AI) for analysing social big data, such as natural language processing (NLP) algorithms, have improved the timeliness and robustness of health data. NLP techniques have been implemented to analyse large volumes of text from social media platforms to gain insights on disease symptoms, understand barriers to care and predict disease outbreaks. However, AI-based decisions may contain biases that could misrepresent populations, skew results or lead to errors. Bias, within the scope of this paper, is described as the difference between the predictive values and true values within the modelling of an algorithm. Bias within algorithms may lead to inaccurate healthcare outcomes and exacerbate health disparities when results derived from these biased algorithms are applied to health interventions. Researchers who implement these algorithms must consider when and how bias may arise. This paper explores algorithmic biases as a result of data collection, labelling and modelling of NLP algorithms. Researchers have a role in ensuring that efforts towards combating bias are enforced, especially when drawing health conclusions derived from social media posts that are linguistically diverse. Through the implementation of open collaboration, auditing processes and the development of guidelines, researchers may be able to reduce bias and improve NLP algorithms that improve health surveillance.
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Inteligência Artificial , Vigilância em Saúde Pública , Humanos , Viés , Coleta de Dados , Surtos de DoençasRESUMO
The increasing popularity of mHealth presents an opportunity for collecting rich datasets using mobile phone applications (apps). Our health-monitoring mobile application uses motion detection to track an individual's physical activity and location. The data collected are used to improve health outcomes, such as reducing the risk of chronic diseases and promoting healthier lifestyles through analyzing physical activity patterns. Using smartphone motion detection sensors and GPS receivers, we implemented an energy-efficient tracking algorithm that captures user locations whenever they are in motion. To ensure security and efficiency in data collection and storage, encryption algorithms are used with serverless and scalable cloud storage design. The database schema is designed around Mobile Advertising ID (MAID) as a unique identifier for each device, allowing for accurate tracking and high data quality. Our application uses Google's Activity Recognition Application Programming Interface (API) on Android OS or geofencing and motion sensors on iOS to track most smartphones available. In addition, our app leverages blockchain and traditional payments to streamline the compensations and has an intuitive user interface to encourage participation in research. The mobile tracking app was tested for 20 days on an iPhone 14 Pro Max, finding that it accurately captured location during movement and promptly resumed tracking after inactivity periods, while consuming a low percentage of battery life while running in the background.
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Blockchain , Aplicativos Móveis , Smartphone , Publicidade , AlgoritmosRESUMO
This study examines the factors associated with COVID-19 testing, vaccination intent (both individually and jointly), and willingness to use contact tracing digital apps among a cohort of Black and Latinx men who have sex with men (BLMSM) living in Los Angeles during the initial peak (July 2020) of the COVID-19 pandemic. A questionnaire detailing participants COVID-19 experiences was sent to 300 primarily BLMSM after the first state-wide COVID-19 lockdown. Logistic regression models with random cluster effects were used for analyses. Forty-two percent (42%) tested for COVID-19, 27% were willing to get vaccinated, and about 45% reported willingness to use contact tracing digital apps. Controlling for intervention participation, age, education, marital status, employment, health, tobacco, binge drinking, and self-reported anxiety, those who were depressed had 33% (95% CI: 0.13 to 0.82) odds of using a prevention strategy (either test for COVID-19 or vaccination intent) as the group who were not depressed. Those who had high school diploma or less had 23% (95% CI: 0.11 to 0.48) odds to use digital contact tracing apps as the group with education level of at least Associate's or Bachelor's degree. Without considering the format of the test kits, vaccine side effects, and ease of use for digital contact tracing apps, participants appeared to still be hesitant in using COVID-19 prevention strategies at the initial height of the pandemic. Our findings suggest the need for further investigation into this hesitancy to better inform and prepare for future epidemics.
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This cross-sectional study used search data from Google Trends to estimate public interest in self-managed abortion.
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Aborto Induzido , Autogestão , Gravidez , Feminino , Humanos , Estados Unidos , InternetRESUMO
Public health research relies heavily on participant involvement. Investigators have examined factors that affect participation and found that altruism enables engagement. At the same time, time commitment, family concerns, multiple follow-up visits, and potential adverse events are barriers to engagement. Thus, investigators may need to find new methods to attract and motivate participants to participate, including new compensation methods. As cryptocurrency is being increasingly used and accepted to pay and reimburse people for work activities, this currency should be similarly explored as an option for research participants to attempt to incentivize them to participate in studies and offer new possibilities for study reimbursement. This paper explores the potential use of cryptocurrency as a form of compensation in public health research studies and discusses the pros and cons of its use. Although few studies have used cryptocurrency to compensate participants, cryptocurrency may be used as a reward for various research tasks, including filling out surveys, participating in in-depth interviews or focus groups, and/or completing interventions. Using cryptocurrencies to compensate participants in health-related studies can provide benefits such as anonymity, security, and convenience. However, it also poses potential challenges, including volatility, legal and regulatory challenges, and the risk of hacking and fraud. Researchers must carefully weigh the benefits against the potential downsides before using them as a compensation method in health-related studies.
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Retention in healthcare and health behavior remains a critical issue, contributing to inequitable distribution of intervention benefits. In diseases such as HIV, where half of the new infections occur among racial and sexual minorities, it is important that interventions do not enlarge pre-existing health disparities. To effectively combat this public health issue, it is crucial that we quantify the magnitude of racial/ethnic disparity in retention. Further, there is a need to identify mediating factors to this relationship to inform equitable intervention design. In the present study, we assess the racial/ethnic disparity in retention in a peer-led online behavioral intervention to increase HIV self-testing behavior and identify explanatory factors. The research used data collected from the Harnessing Online Peer Education (HOPE) HIV Study that included 899 primarily African American and Latinx men who have sex with men (MSM) in the United States. Results show that African American participants had higher lost-to-follow-up rates at 12-week follow-up compared to Latinx participants (11.1% and 5.8% respectively, Odds Ratio = 2.18, 95% confidence interval: 1.12 - 4.11, p = 0.02), which is substantially mediated by participants' self-rated health score (14.1% of the variation in the African American v.s. Latinx difference in lost-follow-up, p = 0.006). Thus, how MSM perceive their health may play an important role in their retention in HIV-related behavioral intervention programs and its racial/ethnic disparity.
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PURPOSE OF REVIEW: People who use illicit drug substances (e.g., heroin) and sex workers are vulnerable to acquiring HIV. Due to the criminalization of illicit drug substances and sex work in many countries, these populations often reside in rights-constrained settings where their well-being, freedom, and access to HIV prevention and care services may be compromised due to legal prosecutions and societal stigma. RECENT FINDINGS: This study conducted a literature review on papers that evaluated a combination of the following three components: ethics, technology-based research, and populations who use drug substances and/or sex workers. We explored research on these ethical perspectives from both key populations and researchers. Findings revealed potential risks in data security and possible harmful implications of compromised data within these rights-constrained settings. Best practices were explored within the literature to identify potential methods for addressing these ethical concerns and improving HIV prevention and care.
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Infecções por HIV , Drogas Ilícitas , Profissionais do Sexo , Humanos , Infecções por HIV/epidemiologia , Infecções por HIV/prevenção & controle , Estigma Social , Trabalho SexualRESUMO
Human Immunodeficiency Virus (HIV) continues to be a significant public health problem, with ~1.2 million Americans living with HIV and ~14% unaware of their infection. The Centers for Disease Control and Prevention recommends that patients 13 to 64 years of age get screened for HIV at least once, and those with higher risk profiles screen at least annually. Unfortunately, screening rates are below recommendations for high-risk populations, leading to problems of delayed diagnosis. Novel technologies have been applied in HIV research to increase prevention, testing and treatment. Conversational agents, with potential for integrating artificial intelligence and natural language processing, may offer an opportunity to improve outreach to these high-risk populations. The feasibility, accessibility and acceptance of using conversational agents for HIV testing outreach is important to evaluate, especially amidst a global coronavirus disease 2019 pandemic when clinical services have been drastically affected. This viewpoint explores the application of a conversational agent in increasing HIV testing among high-risk populations.
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COVID-19 , Infecções por HIV , Humanos , Estados Unidos , Infecções por HIV/diagnóstico , Infecções por HIV/prevenção & controle , Inteligência Artificial , Programas de Rastreamento , COVID-19/diagnóstico , COVID-19/epidemiologia , Teste de HIVRESUMO
OBJECTIVE: A 6-week study was conducted to test the effectiveness of the Harnessing Online Peer Education (HOPE) intervention on anxiety, help seeking (requests for electronic resources [e-resources] on anxiety reduction), and online engagement. METHODS: Three hundred participants with moderate to severe anxiety (i.e., seven-item Generalized Anxiety Disorder scale [GAD-7] scores ≥10) were randomly assigned to social media (i.e., Facebook) groups with or without peer leaders. The study was conducted from April 5 to May 17, 2020. GAD-7 scores, e-resource requests, and online engagement were measured at baseline and at weeks 2, 4, and 6. RESULTS: GAD-7 scores improved in both intervention and control groups, with no difference between conditions. Participants in the intervention group were more likely than those in the control group to request e-resources (OR=10.27, 95% CI=4.52-23.35) and engage online (OR=2.84, 95% CI=1.70-4.76). CONCLUSIONS: The HOPE intervention effectively promoted mental health help-seeking behavior and online engagement.
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Transtornos de Ansiedade , Ansiedade , Humanos , Transtornos de Ansiedade/terapia , Saúde Mental , Grupo AssociadoRESUMO
Millions of Americans suffer from opioid use disorder (OUD) in the United States, resulting in thousands of deaths. The ongoing opioid crisis necessitates novel approaches to reduce the morbidity and mortality associated with misusing opioids. Studies using peer support models show success in engaging persons living with OUD in initiating treatment and decreasing relapse. Although most studies have focused on patients in clinical settings, community studies integrating peer community leaders also show promise. This viewpoint paper explores the use of peer coaches in online interventions in the community setting.
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Analgésicos Opioides , Transtornos Relacionados ao Uso de Opioides , Humanos , Cognição , Transtornos Relacionados ao Uso de Opioides/terapia , Grupo AssociadoRESUMO
BACKGROUND: Factors related to risky drinking (e.g., motives, protective behavioral strategies [PBS]) may vary between youth who engage in polysubstance use compared to those who consume alcohol only. We examined differences in factors among youth who consume alcohol only compared to alcohol with other substances (i.e., polysubstance use), and correlates associated with risky drinking between the groups. METHODS: Participants (N = 955; ages 16-24; 54.5% female) who reported recent risky drinking completed measures of alcohol/substance use, alcohol-related consequences, drinking motives, alcohol PBS, mental health symptoms, and emotion dysregulation. Participants were in the polysubstance group if they reported using at least one other substance (e.g., cannabis, stimulants) in addition to alcohol in the past three months. Chi-square and t-tests examined differences between the two groups and multiple regression analyses examined correlates of risky drinking. RESULTS: Most participants (70.4%, n = 672) reported polysubstance use; these individuals engaged in riskier patterns of drinking, experienced more alcohol-related consequences, used fewer PBS, had stronger drinking motives (enhancement, social, coping), endorsed more mental health symptoms, and reported more emotion dysregulation. Regression models showed that emotion dysregulation significantly associated with risky drinking in the alcohol-only group; conformity and coping motives, alcohol PBS, and anxiety symptoms significantly associated with risky drinking in the polysubstance group. CONCLUSIONS: Among risky drinking youth, results indicated youth engaging in polysubstance use have greater comorbidities and individual-level factors associated with risky drinking than youth who consume alcohol only. These findings may inform the tailoring of interventions for individuals who engage in risky drinking and polysubstance use.
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Consumo de Bebidas Alcoólicas , Cannabis , Humanos , Adulto , Adolescente , Feminino , Adulto Jovem , Masculino , Consumo de Bebidas Alcoólicas/epidemiologia , Consumo de Bebidas Alcoólicas/psicologia , Comportamento Social , Motivação , Adaptação PsicológicaRESUMO
Despite the availability of effective treatment, medications for opioid use disorder are underutilized due to a variety of practical, political, and psychological reasons. Digital inequalities, such as limited access to technology, skills to leverage the technology for desirable outcomes, and social resources, may be contributing to negative health outcomes. In addition, broader health literacy plays an integral part in the capacity of individuals to appraise opioid medication-related online information. This paper explores the role of digital inequalities in the uptake of treatment for opioid use disorder. Given the shift toward telemedicine and online counseling for substance use treatment as a consequence of the COVID-19 pandemic, more research into the digital inequalities faced by those who misuse opioids may provide insight into ways of engaging and encouraging this population to utilize treatment.
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Objectives: This study sought to explore the potential role of peer-led online communities to increase use of medications for opioid use disorder. Methods: From January through March 2020, participants with opioid use disorder and their family members/friends were recruited from paid Facebook ads; public health key stakeholders were recruited from referrals from the study team and opioid experts. Thirty participants from California were interviewed; 23 persons reporting opioid misuse, 3 family members/friends of persons misusing opioids, and 4 public health key stakeholders. We conducted semi-structured interviews asking about preferences, barriers and facilitators of treatment options for opioid use disorder, and perspectives around the use of digital/online communities. The categories of participants interviewed were each asked slightly different questions depending upon their role. Results: Results suggest that participants who misuse opioids (1) may prefer to engage in online communities rather than in-person meetings to discuss their opioid use, (2) generally prefer to receive opioid-related information from other patients with opioid use disorder and/or those in recovery rather than from health providers or other individuals, and (3) thought that an online community could be beneficial for helping address their opioid use. Conclusion: Results suggest an openness and interest in a peer-led online community to discuss opioid use and treatment among people who misuse opioids.
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INTRODUCTION: Vaccine hesitancy is still rampant in the United States, including health care personnel. Vaccination of frontline essential workers (e.g. health care workers) is very important, especially during a pandemic. We tested the efficacy of a 4-week online, peer-led intervention (Harnessing Online Peer Education) to promote requests for COVID-19 vaccine information among essential workers. METHODS: Participants (N = 120) and peer leaders (N = 12) were recruited through online advertisements from July 23 to August 20, 2021. Eligibility criteria included: 18 years or older, U.S. resident, English speaker, part of phase 1a or 1 b of COVID-19 vaccine rollout (e.g. frontline essential workers), hadn't received a COVID-19 vaccine but able to receive one. This was a parallel assignment randomised trial. STATA was used to create a randomisation using a random number generator so that all possible assignments of participants and peer leaders to groups were equally likely. Participants were randomly assigned to intervention or control arms that consisted of two private, hidden Facebook groups, each with 30 participants. Peer leaders were randomly assigned to an intervention group, each with six peer leaders. Participants in the intervention arm were randomly assigned to three peer leaders. Participants were blinded after assignment. Peer leaders were tasked with reaching out to their assigned participants at least three times each week. Participants completed a baseline and a post intervention survey. The study is registered on ClinicalTrials.org under identifier NCT04376515 and is no longer recruiting. This work was supported by the NIAID under grant 5R01AI132030-05. RESULTS: A total of 101 participants analysed (50 intervention and 51 control). Six people in the intervention group and 0 people in the control group requested vaccine information. Ten people in the intervention group and six people in the control group provided proof of vaccination. The odds of requesting vaccine information in the intervention group was 13 times that in the control group (95% confidence interval: (1.5, 1772), p-value = 0.015). Thirty-seven participants in the intervention group and 31 in the control group were engaged at some point during the study. CONCLUSIONS: Results suggest peer-led online community groups may help to disseminate health information, aid public health efforts, and combat vaccine hesitancy. Key MessagesThe odds of requesting vaccine information was 13 times in the intervention group.Peer-led online communities may help to disseminate information and aid public health efforts to combat vaccine hesitancy.
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Vacinas contra COVID-19 , COVID-19 , Humanos , Vacinas contra COVID-19/uso terapêutico , SARS-CoV-2 , COVID-19/epidemiologia , COVID-19/prevenção & controle , Pandemias/prevenção & controle , Pessoal de SaúdeRESUMO
Same-day alcohol and cannabis use is relatively common in adolescents and young adults, constituting a higher-risk behavior relative to single-substance use. However, the association between quantity of alcohol and cannabis use on co-use days is understudied. We examined the association between the quantity of alcohol and same-day cannabis use with a multilevel regression analysis in a sample of youth (16-24 years old) with risky alcohol use. Participants reported one or more days of alcohol and cannabis over the past month (N = 468). Quantity of cannabis use was highest on heavy drinking days [M = 0.91 grams, SD = 0.68] followed by moderate drinking days (M = 0.78 grams, SD = 0.63), and lowest on days without alcohol use (M = 0.74 grams, SD = 0.64, p < 0.001). In multilevel modeling analyses, adjusted for clustering within individuals, greater quantity of drinking on a given day was associated with greater cannabis use (estimate = 0.03, p < 0.001). When using alcohol and cannabis on the same day, greater alcohol use was associated with greater cannabis use. Preventing days of heavy use of multiple substances, particularly among at-risk drinkers, may complement interventions addressing co-use generally to prevent substance-related consequences.