We examined CEMA by Latino youth in outpatient treatment and highlighted a number of important contextual factors related to AOD use. Better understanding context provides an immediate benefit by informing the development of general EMI content and strategies that use, for example, smartphone geo-location data to trigger in-the-moment interventions. The full capabilities of EMI can be recognized by using context to trigger EMI with content that is appropriate for the context. For example, real time advice delivered by EMI can differ depending on the time of day, location, and presence of peers. Social context appears to be an important contextual AOD-use factor in our study as it has in prior studies. AOD use was most frequently reported with close friends and while hanging out relative to other types of associations and activities, respectively. Alcohol by itself was more frequently reported at a friend’s house while marijuana and other substances were more frequently reported at other locations. Social context has traditionally been self-reported and in turn, difficult to harness in automated applications. However, there are promising developments in providing passive mobile data streams. Many users access social networking sites through their phones that leave digital footprints of social interactions. Phone logs are also recorded and can be accessed as other researchers have done . Social network information can be further refined by combining it with GPS location traces to determine time spent with friends at one of their homes. In our study, AOD use was more frequently reported in the afternoon and nighttime and about half the time on weekends. This is in line with other studies that have found AOD use to bemore common after school hours and on weekends . Alcohol consumption by itself was more frequently reported at night and on weekends relative to marijuana and other substances and warrants closer examination in larger samples.
Temporal information provides a good starting point for actionable EMI information. Date and time stamps can be passively collected without user burden and provide quantifiable information, such as weekend or weekday categories,wholesale vertical grow factories that can be incorporated into classifiers that trigger EMI. Cravings provided useful self-reported data, with strong cravings more frequently reported on AOD use days. Cravings can be categorized in a binary fashion with reporting operationalized as a button on a phone’s desktop for easy access and more frequent reporting. Random prompts can be used throughout the day to query cravings similar to Piasecki et al. . This offers an improvement over our study design in the ability to better understand temporal context for AOD use. Affective states are multi-faceted and more difficult to quantify. Happiness tended to be the most frequently reported affective state across CEMA strategies, but were reported to the same degree when AOD use did and did not occur. Thoughts of wanting to get buzzed were more common for alcohol use alone and thoughts of relaxation were more common for marijuana and other substances. Reports of context, cravings and affect were robust to CEMA reporting strategy, whether reports were based on recall or in the moment. An exception was that marijuana use was most commonly reported in the morning based on recall and only reported in the afternoon based on EBA. In-the-moment RA does not provide a comparison as youth were not prompted in the morning. Further study is needed to see if time-of-day differences in reporting marijuana hold in larger samples. Overall robustness in reporting context is encouraging and suggests that there is flexibility in using different CEMA strategies. Flexibility in assessment is important with youth in consideration of school activities and other events that may make it difficult to implement one assessment strategy. Next steps call for studies with larger sample sizes to examine overlap between contextual factors and explore temporal relationships with AOD use, similar to multilevel analyses by Piasecki et al. that analyzed nicotine use in mostly white youth.
The small number of participants, low rates of AOD use, and missing data due to non-response made this impractical in our study and are limitations. This hampered our ability to provide subgroup analyses by age and gender; both characteristics are linked to AOD use and context . There is variation in the degree of AOD use across participants that may also relate to context but was impractical to explore in our sample. Caution is also warranted in generalizing our findings for normative samples of AOD users as participants were in a substance abuse treatment program. Lastly, RA occurred once a day after school hours and more closely mimicked EoDA than true RA that typically occurs multiple times a day. Our assessment scheme limited our ability to address the second hypothesis and explore if different assessment methods elicited different types of AOD use-related context. Notwithstanding sample size limitations, our sample is representative of Latino youth in outpatient treatment. We did not see evidence of self-selection to participate in our study; there was a lot of interest to participate. The use of a study phone and free cell phone minutes that accompanied participation provided strong incentives. Enrollment was limited by the number of study phones. Interest in our study highlights an important opportunity to develop substance use interventions for youth through a medium they already use in their daily lives.Spontaneous EBR has become increasingly popular as a putative behavioural marker of endogenous dopamine. Interestingly, most of the past studies that have used sEBR in this capacity have loosely referred to ‘dopamine function’ or ‘dopamine activity’, perhaps reflecting the current dearth of knowledge regarding which specific aspect of the dopamine system correlate with sEBR. Here we tested the hypothesis of a positive relationship between sEBR and striatal dopamine synthesis capacity, based on the proposal that sEBR is positively related to striatal dopamine function , and previous results showing a positive correlation between sEBR and striatal dopamine levels measured in post-mortem monkey brains . Both frequentist and Bayesian statistics, as well as ROI and voxel-wise analyses, argue against the existence of such a positive relationship in our sample and show that, if anything, the evidence is in favour of a negative relationship.
While we prefer to refrain from making speculative interpretations regarding the existence of a negative relationship, given the moderate level of evidence, we believe these data provide a strong cautionary message against the use of sEBR as a positive predictor of pre-synaptic striatal dopamine. Importantly, our data speak specifically to dopamine synthesis capacity and do not preclude correlations of sEBR with other aspects of the dopamine system, including dopamine D2 receptor availability. It has been suggested that sEBR might primarily reflect striatal D2 receptor activity, based on the observation of a positive correlation with D2 receptor availability in monkeys , and the observation that sEBR better predicts D2-mediated punishment learning than D1-mediated reward learning . However, this relationship between sEBR and dopamine D2 functioning has been recently questioned by a PET study which failed to replicate it in humans . Also, such a relationship remains difficult to reconcile with recent findings showing a positive association between dopamine D2 receptor availability and dopamine synthesis capacity , as this would predict a positive relationship between sEBR and dopamine synthesis capacity, in contrast to our results. These inconsistencies certainly call for further research to better elucidate the dopaminergic mechanisms underlying sEBR. This study is not devoid of limitations. First, our sample size is relatively small, although one should note that it is larger than the samples used in many of the psychopharmacological studies that have investigated dopaminergic drug effects on sEBR . In fact, a power analysis performed with GPower3.1 suggests that a sample size of 12 individuals should have been sufficient to replicate with 95% power the positive relationship reported by Taylor et al. between striatal dopamine levels and sEBR in monkeys . In addition,grow rack as argued by Dang et al. , the use of sEBR as a reliable predictor of dopamine function implicitly requires that the positive relationship between these two variables should be strong and thus observable even in small samples. For these reasons, we believe that the preliminary evidence reported here is valuable, even though a replication in a larger sample size is warranted. Another aspect that may be perceived as a limitation is the use of a mixed population of healthy participants and pathological gamblers. While we acknowledge that pathological gamblers are not typical individuals and are characterized, among other things, by elevated striatal dopamine synthesis , we believe that this is not necessarily an issue in the context of the current study. Indeed, our goal was to examine whether individual differences in sEBR and dopamine synthesis were positively related, regardless of the origin of these individual differences. If sEBR is to be used as proxy measure of dopamine levels, it should be insensitive to the underlying causes of individual variations, so that it can be effectively used in both clinical and non-clinical populations. In fact, a large portion of the literature that has led to the hypothesis of a link between sEBR and dopamine function is based on the study of clinical populations characterized by dopamine dysfunctions. Finally, one should note that restricting our analyses to healthy individuals did not affect the results, still showing moderate evidence against a positive correlation.
To conclude, our study does not support the hypothesis of a positive relationship between sEBR and striatal dopamine synthesis, and if anything, provides evidence against it. Even though it is based on a modest sample size and needs to be replicated in a larger sample – which we are currently attempting to do, it warrants caution for future studies that may be tempted to use sEBR as a proxy measure of striatal dopamine synthesis capacity.Misuse of substances is common, can be serious and costly to society, and often goes untreated due to barriers to accessing care. Globally, 3.5 million people die from alcohol and illicit drug use each year. Over 20 million Americans had a substance use disorder in 2018, 73% had an alcohol use disorder, 40% had an illicit drug use disorder, and 13% had both alcohol and illicit drug use disorders. Approximately half of Americans with an SUD had a co-occurring mental illness. Treatment of depression and anxiety, the most common psychiatric comorbidities among patients with SUDs, may reduce craving and substance use and enhance overall outcomes. In 2018, less than 1 in 5 individuals with a SUD received addiction treatment. Alcohol and illicit drug misuse and addiction cost the United States over US $440 billion annually in lost workplace productivity, health care expenses, and crime-related costs. Potential effects on individuals include an array of physical and mental health problems, overdose, trauma, and violence. Web-based interventions and digital health apps may reduce or eliminate common, significant barriers to traditional SUD treatment. Preliminary evidence suggests that digital SUD interventions affect substance use behavior and have the potential to reduce the population burden of SUDs. To date, most digital SUD interventions have been delivered on a web platform, rather than via mobile apps. The widespread use of smartphones makes app-based intervention delivery a viable and scalable medium. In 2019, about 8 out of 10 White, Black, and Latinx adults owned a smartphone. Although lower-income adults were less likely to own a smartphone than higher-income adults, they were more likely to rely on smartphones for internet access. In a 2015 survey, 58% of mobile phone owners reported downloading a health app. Texting is the most widely and frequently used app on a smartphone, with 97% of Americans texting at least once a day. Automated conversational agents can deliver a coach-like or sponsor-like experience and yet do not require human implementation assistance for in-the-moment treatment delivery. As recent meta-analytic work suggests, conversational text-based agents may increase engagement and enjoyment in digitized mental health care, whereas most general mental health care apps face difficulty sustaining engagement with high dropout. Conversational agents can provide real-time support to address substance use urges, unlike traditional in-person frameworks of weekly visits. The scale potential of conversational agents is unconstrained, immediate, and available to users in an instant. Being nonhuman based also reduces perceived stigma.