Hemp Growing

E-cigarettes have been marketed as a form of harm reduction from traditional cigarette smoking, but neither the safety nor the efficacy of these devices has been established, and little is known about the short and long term pulmonary and systemic health effects. This review focuses on the known and unknown toxins contained in e-cigarette aerosols, lung diseases induced by vaping, and the predicted long-term consequences of e-cigarette use. Particular attention is given to the e-cigarette or vaping product use-associated lung injury epidemic that began in 2019 and is ongoing. E-cigarettes are devices composed of a power source, heating element, and liquid reservoir that heat and aerosolize e-liquids to make vapor that is inhaled into the lungs in a process known as vaping. E-liquids are most often composed of 1) Addictive substances such as nicotine and/or tetrahydrocannabinol , 2) Flavorings, and 3) Solvents . There are many types of vaping devices, but the most frequently used include pod vapes, box mods, and vape pens . The pod devices were widely popularized by the company Juul, which developed its sleek device to look like a flash-drive that quickly became the most profitable e-cigarette by the end of 2017. The e-liquids in Juul pods contain high concentrations of the more rapidly absorbed nicotinic salts complexed with benzoic acid, compared to free based nicotine, thus increasing the addictive potential and toxicity. Given that nicotine exposure influences long-term molecular, biochemical, and functional changes in the adolescent brain, it is not surprising that teens who vape are at increased risk of subsequent use of traditional cigarettes, marijuana, opioids, and other illicit drugs with addictive potential.

THC also induces alterations in reward networks in the adolescent brain, which increases risk for future drug use,plant bench indoor and regular cannabis users of any age have poorer neurocognitive functioning and functional brain alterations relative to nonusers. Although vaping devices are not an approved nicotine replacement therapy, the Federal Drug Administration has allowed e-cigarette manufacturers to design e-liquids using components that have been ”generally recognized as safe” . Compounds that have GRAS status are only assessed as safe to ingest via the gastrointestinal tract, or put on the skin. Thus, the vast majority of compounds with this designation have not been tested for safety via the inhalation route. There are thousands of different flavoring ingredients used, and thermal decomposition of propylene glycol, glycerol, and flavoring agents result in the production of toxic aldehydes at levels that exceed occupational safety standards. Chemical flavorings such as diacetyl and 2,3-pentanedione, present in many e-liquids, have been found to induce transcriptomic changes that disrupt cilia function in human airway epithelium, impairing mucociliary clearance. Cumulative exposure to diacetyl is well known to be associated with the development of the irreversible airway fibrosing disorder bronchiolitis obliterans , with the term “popcorn lung” used when referring to BO described in microwave popcorn factory workers. Other toxins found in e-cigarette vapor with inhalant and systemic toxicities including terpenes, acrylonitrile, formaldehyde, crotonaldehyde, propylene oxide, acrylamide, and heavy metals. None of these products are currently regulated, but there is even greater cause for concern regarding the inhalant toxicity for the components in “black market” or counterfeit e-liquids and devices as well modified devices. Finally, microbial toxins may contaminate vaping devices even prior to use.

One study tested the leading U.S. pod vape and found that 81% of devices contained B-D-glucan, a fungal cell wall marker, and 23% contained endotoxin, found in the outer wall of gram-negative bacteria. Both of these microbial contaminants are associated with asthma and hypersensitivity pneumonitis.E-cigarettes have been marketed as a form of harm reduction from traditional cigarette smoking, but neither the safety nor the efficacy of these devices has been established, and little is known about the short and long term pulmonary and systemic health effects. There have been increasing reports in the literature of negative pulmonary effects with the recent epidemic of e-cigarette or vaping product use-associated lung injury  being the most immediately concerning. Reports of the development of chronic respiratory symptoms, increased asthma morbidity, and the development of diffuse lung disease in both adolescents and adults highlight significant pulmonary toxicity and compel further research. E-cigarette users are more likely to report chronic respiratory symptoms and conditions in both adolescents and adults. In a large study from Hong Kong of 45,000 adolescents who vaped in the previous month reported chronic cough or phlegm production with increased odds. In a smaller study of 2,000 high school students in Southern California, past and current vaping was associated with a nearly two-fold increase in the risk of chronic bronchitis symptoms. In a longitudinal analysis of adults in the Population Assessment of Tobacco and Health Waves 1, 2, and 3 with data collected from 2013-2016, a significant association between former and current use at Wave 1 and incident respiratory disease at Waves 2 or 3 was demonstrated, controlling for combustible tobacco smoking and other demographic, and clinical variables. In this study, dual use of cigarettes and ecigarettes had increased odds of developing respiratory disease of 3.30 compared with a never smoker/vaper. Among asthmatic patients, primary e-cigarette use and secondhand exposure confers increased morbidity.

Interestingly, vaping is more popular among asthmatic teenagers as compared to their non-asthmatic peers. The reason for this observation is unclear, but may be related to the commonly held belief that vaping is safer than smoking cigarettes. Among adult never cigarette smokers, current e-cigarette use was associated with 39% higher odds of self-reported asthma compared to never e-cigarette users. In South Korea, vaping in high school students was associated with increased odds of being diagnosed with asthma and more missed days of school secondary to asthma. The Florida Youth Tobacco Survey showed that past-30-day e-cigarette use was associated with having an asthma attack in the past 12 months among high school participants with asthma. This survey later revealed that 33% of 11- to 17-year-olds with asthma had secondhand ecigarette exposure, and this exposure was associated with increased risk of asthma exacerbation. There are also case reports of two adolescent asthmatic e-cigarette users who presented with life-threatening status asthmaticus requiring VV-ECMO[36]. This may indicate increased risk for more severe exacerbations among asthmatic teens who are vaping. In addition, EVALI cases from both the Illinois and Wisconsin cohort and Rochester cohort reported higher- than expected rate of EVALI in asthmatics. Vaping has been linked to various rare pulmonary conditions and pathologic abnormalities. There have been multiple case reports of different types of severe and life-threatening diffuse lung disease in patients using vaping products including hypersensitivity pneumonitis, eosinophilic pneumonitis, diffuse alveolar hemorrhage, lipoid pneumonia and bronchiolitis. These case reports demonstrate that there is undeniable harm associated with vaping even before decades of use. Among patients with EVALI, pathology results included findings consistent with acute lung injury including acute fibrinous pneumonitis,greenhouse rolling racks diffuse alveolar damage, and organizing pneumonia. Taken together these pathological findings indicate that severe lung injury in multiple different patterns can occur in the setting of vaping. Although the mechanism of injury in these patients is currently unknown, it is presumed that there are both product and host related factors contributing to lung injury. Given that multiple components of vaping products can cause pulmonary toxicity, it is unlikely that there is only one chemical component leading to these diverse patterns of toxic lung injury. Beyond the scope of this review are systemic toxicities as well as trauma due to explosions, thermal injuries and acute intoxications including ingestion of e-liquids.The national outbreak of e-cigarette, or vaping, product use-associated lung injury has been the first vaping related disease to affect thousands of people . At its core, it is a chemical inhalation injury, most likely caused by heating, aerosolization and inhalation of Vitamin E within THC liquids and vape pens. Examination of airways and lungs of those affected has yielded a pattern of epithelial and alveolar damage. Neutrophils and foamy macrophages are often documented, with lipid laden phagosomes when directly tested through appropriate lipid stains; however, lipid laden macrophages are most likely evidence of vaping in general, not specific to EVALI.

Although it has been clear for years that users of e-cigarettes and vaping devices were inhaling known toxins such as diacetyl and formaldehyde, this disease entity was the first to demonstrate that inhalation of clouds of chemicals that have never been tested for safety via inhalation methods can lead to significant impacts on public health. EVALI was first recognized in August 2019, with the number of recognized cases rising precipitously until December 2019. The connection with THC was made within several weeks – approximately 82% of those affected had vaped THC – while the identification of Vitamin E acetate as a prime suspect took months, and has not been confirmed as the etiologic agent at this time. Fourteen percent of those affected vaped nicotine containing e-liquids only, but upon review these subjects were older, female and had less leukocytosis, suggesting that they may have been suffering from a different vaping induced lung disease. Overall, EVALI is a disease of the young, with a median age of 24 years. It also predominantly affects males , which may be directly related to epidemiologic patterns of THC vaping. The majority of patients present with respiratory , gastrointestinal and systemic symptoms, and are found to have elevations in erythrocyte sedimentation rate , Creactive protein , white blood cell counts, and liver function tests. Beyond these factors, bilateral lung infiltrates are the key diagnostic finding on radiographic imaging. The mortality rate is quite low, at 2.4% , with the highest mortality rate in older e-cigarette users with comorbidities. The median age of deceased EVALI patients was 49.5 years, with a range from 15 up to 75 years. Of the cases identified up to December, approximately 47% required ICU admission and 22% required intubation. Because only moderate to severe cases were tracked, the reported numbers are likely to severely underestimate those affected. Since Vitamin E acetate within THC e-liquids has been identified as a likely causal agent, and with the intense media coverage of this disease entity, there is hope that the incidence of this particular vaping disease will decrease. However, as vaping increases across society, with millions of users inhaling hundreds of thousands of chemicals including lipophilic agents similar to VEA, it is clear that vaping associated lung diseases are here to stay. Conventional tobacco has been smoked for over 5000 years and is very well known to cause a myriad of long-term health problems, not the least of which is lung disease. Because modern vaping devices have been on the market for less than 16 years, and only widely used for 5, very little is known about how chronic use will affect human health. Murine data suggest that some vapers will develop emphysema, heart disease, renal failure, and even liver fibrosis, but these diseases will be couched in genetic predisposition, type of e-device used and the chemicals within the inhaled aerosol. Because vaping aerosols contain chemicals that cytotoxic and cause DNA damage, it is unsurprising that murine models have demonstrated increased occurrence of lung toxicities. Thus, it is hypothesized that long-term vaping will lead to increased incidence of cancer. Because acute and subacute vaping can increase airway resistance and airway reactivity, it is believed that chronic use of e-cigarettes will lead to more severe disease in asthmatics. Vaping alters the function of myeloid cells, including granulocytes, such that it is likely that vaping will alter the function of eosinophils as well, leading to vaping induced changes in allergic diseases. Asthma has many phenotypes, including eosinophilic and neutrophilic subtypes, and with the knowledge that vaping has broad effects on immune cells, e-cigarette use may impact multiple asthma phenotypes. Studies in humans thus far are limited to acute and short-term effects, but consistently demonstrate that vaping impacts both pulmonary and cardiovascular function. Gene expression from airway samples evidence changes that parallel those in cigarette smoking, which is worrisome in that it predicts that vapers will develop the same lung diseases that smokers do – namely emphysema, chronic obstructive pulmonary disease , and respiratory bronchiolitis interstitial lung disease. In addition, altered human neutrophil function suggests that vapers will be at higher risk for bacterial infections as well as autoimmune disease. While longitudinal studies on the health effects of chronic e-cigarette use are needed, the data thus far suggest that vaping will have substantial adverse impacts across organ systems, leading to significant morbidity and mortality over time.

For home prepared diets, a list of ingredients and the source of the recipe was requested. Participants also identified where they obtained information on choosing the diet. For the supplement section, participants answered questions on which products were added or stopped in response to the cancer diagnosis, in addition to which supplements participants maintained both before and after the diagnosis. Participants were then asked where they obtained information on supplements and where they purchased these products for their dogs. The treat section asked for the names of commonly given treats, how often the treat was given, and if the treat was used as a food topper or given with medications. The diet and supplement sections collected both past and present information, whereas the treat section only collected present information. To accommodate requests from initial survey testers and increase the overall survey experience, some questions did not force a response . This was to allow dog owners to complete the survey, even if they did not remember specifics for a particular question, and to reduce the total number of survey pages. Owners who altered their dog’s diets because of a cancer diagnosis were given questions on the previous diet, but responses were not forced for brand , form of diet , ingredients , or recipe source . For the supplement section, responses were only forced for general supplement categories . Questions involving specific supplement types , informational resources used, and where supplements were bought did not force a response. The questions in the treat section did not force responses.Data were collected from the medical record including date of birth, date of first visit to the oncology services, body weight at first visit , sex, spay/neuter status, diagnosis, time from diagnosis to survey completion, breed, body condition score , appetite level at first visit ,cannabis growing system whether or not any signs of gastrointestinal disease were present at latest visit, and address. Address information was used to determine 2021 estimated census tract median family income.

Survey data were exported into RStudio version 2022.12.0 for statistical analysis using R version 4.2.2 . Descriptive statistics were used to describe dog demographics. For diets and supplement use, reasons for changes and informational resources were reported as n values and percentages. Data were checked for normality using a Shapiro-Wilk’s test. A logistic regression model was fitted to predict diet swapping based on information in the medical record or survey. We used the Akaike information criterion to select from the possible variables of using veterinarians as a diet information resource, weight , diagnosis group, estimated family income , BCS, sex, and appetite at first visit . A P value of <.05 was considered statistically significant.The survey was distributed to 438 owners . Ten owners completed the survey but did not meet inclusion criteria, and these responses were omitted from analysis. One hundred twenty-eight responses included data for at least 1 nutrition related question and were retained for analysis. One hundred twenty of the responses were complete; any survey that reached the end was considered complete, regardless of optional questions answered. The median time from diagnosis to survey response was 61 days, with a range of 2 to 472 days . Most questions forced responses and the reported sample sizes will align with the number of respondents reaching a particular part of the survey . However, the sections that did not force a response had fluctuating sample sizes resulting from respondents proceeding through the survey without answering a particular question.Out of the 128 dogs for which we had available survey data, 55.5% were male and 44.5% were female . Omitting 2 dogs without date of birth in their medical records, the ages of 126 dogs were normally distributed with a mean of 9.9 years and a SD of 3.1 years. Omitting 1 dog without weight recorded at time of visit, 127 dogs had a median weight of 26.0 kg, with a range of 3.2 to 64.0 kg. All dogs had their breed recorded in the medical record, with 25.0% listed as mixed breed.

Among purebred dogs , the most common breeds were golden retrievers , Labrador retrievers , and German shepherds . Only 102 of the 128 dogs had a BCS recorded in their medical record; the median BCS was a 5, with a minimum of 3 and a maximum of 9. Diagnoses for all 128 dogs were divided into 5 categories: epithelial origin tumors , mesenchymal origin tumors , round cell tumors , benign tumors with clinical effect diagnosed as pituitary tumors or thymomas, and undefined masses . For the 108 dogs with appetite described in the medical record at the time of visit, 13 had decreased appetite , 91 had normal appetite , and 4 had increased appetite . 22.7% of all respondents reported any GI clinical signs in the time between initial presentation and survey completion. Out of 128 respondents who answered diet information questions, 47.7% altered their dog’s diet in response to a cancer diagnosis. Out of 124 respondents providing supplement information, 28.2% altered supplements in response to a cancer diagnosis, 20.9% altered both diets and supplements, and 54.8% altered diets and/or supplements.The informational resource most widely used for both diets and supplements was veterinarians . Among owners who changed their dog’s diet , the most common reason was loss of appetite , followed by veterinarian recommendation , and felt old diet was unhealthy . Only 8% of respondents who changed their dog’s diet did so for both reasons of loss of appetite and a veterinarian recommendation. Many owners selected the “other” option . In this textbox, owners listed out reasons including previous dogs with cancer doing well on another diet, adding more meat, or reducing carbohydrates. Owners could select multiple options, with 28% of owners reporting multiple reasons. Before diagnosis , 72.7% of dogs were fed commercial diets exclusively, 3.1% of dogs were fed home prepared diets exclusively, and 24.2% were fed a combination of commercial and home-prepared diets.

After diagnosis, 59.4% of dogs were fed commercial diets exclusively, 7.0% of dogs were fed home-prepared diets exclusively, and 33.6% were fed a combination of commercial and home-prepared diets. There was a significant increase in proportion of dogs fed at least some home-prepared foods as part of their diet after the cancer diagnosis . However, there was no significant difference in the proportion of dogs fed any portion of their intake from a commercial diet after the cancer diagnosis . However, many dogs fed commercial diets both before and after diagnosis changed commercial formulas; out of 49 respondents that provided this information for both time points, 23 switched diets . The most common recipe source for those making home-prepared diets, both before and after a cancer diagnosis, was self formulation . Of the 31 owners using home-prepared diets before diagnosis, 45% reported using self-formulation as the only recipe source. Of the 51 owners using home-prepared diets after diagnosis, 39% only used self-formulation. Veterinarians were the second most used resource both before and after a cancer diagnosis . The most common special diet category fed before diagnosis was grain-free diets, and the most common after diagnosis was diets for a medical condition . The term “natural” was included in the brand or product name of 6.9% of commercial diets before diagnosis and 6.0% of diets after, which was not significantly different .An overview of supplements given,flood table including proportions given both before and after diagnosis, is presented in Table 4. Out of 124 respondents providing full or partial supplement information, 85 owners reported supplement use at any time, including 70 owners who reported supplement usage before diagnosis and 76 who reported supplement usage after diagnosis. There was no significant difference in number of dogs receiving supplements before or after a diagnosis . The most common supplements were joint support products . The most commonly added supplements after diagnosis were herbal products . Out of the 14 owners who added herbal supplements, 12 owners provided specific types; among these owners, 7 reported adding mushroom supplements, and 4 reported adding cannabidiol or tetrahydrocannabinol . Among 83 respondents who specified where supplements were purchased, they were most likely to buy some or all of them online , followed by veterinary offices and pet stores . Other responses included warehouse stores , pharmacies , dispensaries , or other locations .This study examined owner decisions regarding diet and supplement alterations after a cancer diagnosis. The average age of dogs in this sample, around 10 years old, is similar to what has been reported in other studies for the age of development of cancer.Given that older dogs have a higher incidence of degenerative joint disease, this might be related to the finding that joint support products were the most commonly used supplements, both before and after a cancer diagnosis; this is consistent with supplement use in dogs with cancer.For total number of dogs receiving supplements, our data showed no significant change after a cancer diagnosis. Dogs with cancer are more likely to receive supplements than healthy dogs in the general population,which was not evaluated in this study.

Our findings might also reflect the owner’s focus on supporting their dog during chemotherapy and other treatments during the period of time close to diagnosis. Some owners added supplement products after diagnosis. Mushroom-based and CBD/THC supplements were added at the highest rates after a cancer diagnosis; this is consistent with these supplements being more commonly given to dogs with cancer when compared to healthy dogs.This helps to confirm that some of these differences are attributable to a cancer diagnosis, rather than solely because of other factors such as age. Although mushrooms have anticancer potential in mice, this has not been shown in dogs.Similarly, although CBD use is common and has some efficacy in inducing apoptosis and perturbing mitochondrial function in canine glioma cell lines,there are currently no studies on its anti-cancer effect in vivo. Furthermore, the addition of CBD to treats, foods, and supplements intended for animals is not allowed by the United States Food and Drug Administration and remains an illegal practice, which might have led to under reporting in this survey.Another potential instance of under reporting was loss of appetite; more owners reported loss of appetite in the survey than during their initial visit to the oncology service. However, this could also be the result of appetite normalizing before the visit, or appetite loss occurring between the visit and survey completion. We predicted this increase before conducting the survey, and this increase was in-line with the results of a previous study.An increase in feeding of home-prepared foods is similarly reported when comparing the general dog population to those with cancer.The increased use of these foods could potentially lead to inadequate nutrient intake, given that home prepared diets are commonly unbalanced.This concern is compounded by self-formulation of recipes, which was the most common source for home-prepared diets in the present study. However, this could be skewed by owners who added just a couple self-selected ingredients to supplement a commercial diet, rather than fully developed recipes, since many owners gave home-prepared meals in conjunction with commercial diets. One strategy to address this potential problem would be referral to a board-certified veterinary nutritionist to ensure any home-prepared diet is complete and balanced. An alternative strategy could be to discuss with the owner their concerns with commercial pet foods. Collecting a comprehensive nutritional history is not only important for ensuring dietary needs are met, but the conversation could lead to discussion regarding perceived problems of commercial pet foods. The current study did not find the accompanying decrease in commercial diets that has been shown elsewhere with the vast majority of owners using a commercial diet for part or all of their dog’s foods. As our sample comprised dogs with a recent diagnosis of cancer, this might suggest that inclusion of home-prepared elements precedes the complete exclusion of commercial diets, and our survey was conducted too close to the time of diagnosis to find exclusion of commercial diets. However, for owners feeding a commercial diet both before and after diagnosis, nearly half stopped feeding the pre-cancer diagnosis diet. It is possible that our sample would ultimately have stayed on their second commercial diet, rather than eliminating commercial elements entirely.

Among methodologic considerations and limitations, the main outcome measure in this study, initiation of any tobacco use, is a critical milestone, particularly among youth for whom daily smoking may develop over several years.However, long-term established tobacco use deserves attention in future research. Speculatively, youth might report tobacco use differently with in-home questionnaire administration versus in-school questionnaire administration, with unclear impact on the present results. In our 2- and 3-year models, we did not account for the timing of tobacco initiation or time-varying exposures or covariables. However, in an 11-year longitudinal study in Italy, the authors reported that living with smoking family members in adolescence and absence of a household smoking ban in young adulthood were both associated with established smoking among young adults.In the current study, findings were similar in a 1-year repeated measures analysis that allowed for intraperson variation.The COVID-19 pandemic has led to disruptions in daily social activities, schooling, and employment for millions of people globally. For some, the pandemic has also led to financial insecurity, exposure to potentially hazardous working conditions, illness, and the illness and/or loss of a loved one. Research has linked traumatic stress from previous viral outbreaks and other mass-traumatic events to increases in alcohol use, particularly in vulnerable groups such as those with a history of alcohol use disorders . Much less is known, however, about the risk and protective factors for alcohol use during and after prolonged stressors, such as the COVID-19 pandemic. While there is mixed evidence across different study populations,weed trimming tray several initial reports have suggested that rates of alcohol use have increased since the start of the COVID-19 pandemic for some vulnerable groups.

Researchers have posited a variety of COVID-19-related hardships, such as social disconnection, lack of access to healthcare services, and economic difficulties, as potential explanations for these increases. However, it remains unknown which specific types of stressful COVID-19-related experiences are associated with increases in alcohol misuse and what healthy coping strategies might mitigate risk. Prior research has demonstrated that some groups are more vulnerable to stress-related increases in alcohol misuse. For example, stressful events are associated with the recurrence of AUD, which underscores concern about the COVID-19 pandemic’s effect on alcohol use among individuals with a history of AUD. One recent study found that approximately half of adults in recovery from a substance use disorder reported cravings during a pandemic isolation period and that their craving was prompted by loneliness, lack of support, and financial stress, among other factors. In addition, during the COVID-19 pandemic, access to mutual-help groups and specialized AUD treatments may have diminished. This has played out in some early data on individuals with a lifetime history of AUD, which showed that ~20% of participants reported increases in their alcohol use since the pandemic began, with a significant portion of individuals reporting decreased access to substance use disorder treatment. However, other data have shown that 88.9% of women and 88.8% of men in a national survey of adults with ‘resolved’ AUD reported that the COVID-19 pandemic had not affected their recovery at all, and that ‘return to drinking’ events were infrequent. These mixed findings indicate that research is needed to understand the association between potential stressors related to the COVID-19 pandemic and increases in drinking among individuals with a past AUD, and differences between those in remission from AUD and those who are experiencing symptoms of AUD. Women may be particularly vulnerable to increases in drinking during the COVID-19 pandemic.

Two independent studies found that women were more likely than men to have a recurrence of AUD when experiencing interpersonal conflict, whereas men were more likely than women to have a recurrence of AUD in response to social isolation. Higher trauma exposure was associated with a higher risk of relapse only in women. Being married has been identified as a relapse risk factor for women but a protective factor for men. Because gender differences are often not examined in studies of individuals with AUD, robust, nuanced, and consistent findings regarding the role of gender in the associations of stress with drinking outcomes are unavailable. Since the start of the COVID-19 pandemic, some studies have found greater increases in adverse drinking outcomes among women than men. Given the unique stressors experienced by women during the COVID-19 pandemic, primarily related to balancing work and caregiving duties, further research is needed regarding gender differences in the relationships between COVID-19 pandemic stressors and increases in drinking among individuals with past AUD. In addition, individuals at heightened risk for AUD are more vulnerable to stress-related alcohol use. For example, genetic and/ or neural risk factors for AUD have been shown to increase the association between traumatic stress and alcohol use problems. There is also a growing literature suggesting that individuals exposed to traumatic stress differ in terms of temporally sensitive EEG-based measures of neural functional connectivity, which are also associated with heightened risk for alcohol use disorder. EEG coherence, the degree of synchrony in brain oscillatory activity between neural networks in two brain regions, is a heritable measure of neural functional connectivity that has been studied extensively and is correlated with various aspects of cognitive functioning and psychopathology.

While decades of research have focused on genetic and neurocognitive differences observed among those with alcohol use problems, few studies have examined interactions between measures of brain functioning and social environmental factors with respect to risk for alcohol use/misuse. Research teasing apart specific types of stressful COVID-19- related experiences associated with problematic alcohol use , and detailing how they interact with individualized risk factors , will allow us to better understand strategies that may buffer against the re-emergence, exacerbation, or new development of AUD that may occur as the COVID-19 pandemic continues to unfold. This study analyzed new data collected during the first months of the COVID-19 pandemic from longtime participants in the Collaborative Study on the Genetics of Alcoholism study, in conjunction with their data on AUD and drinking collected in prior assessments. The primary aim of this study was to examine the associations between COVID-19-related stressors and coping activities with changes in drunkenness frequency since the start of the pandemic among men and women with and without a history of AUD. Using information from earlier data collections, we further categorized individuals as having had no prior history of AUD pre-pandemic, having been symptomatic of AUD prepandemic, having been in remission from AUD but drinking prepandemic, or having been in remission from AUD and abstinent pre-pandemic. Gender differences in the associations of COVID- 19-related stressors and coping activities with changes in drunkenness frequency were also examined. An exploratory aim was to examine the roles that polygenic risk for problematic alcohol use and neural connectivity played as moderators of these associations.Details on the Collaborative Study on the Genetics of Alcoholism data collection and procedures have been published previously. Briefly,cannabis grow setup since 1990 over 17,000 individuals from families densely affected with AUD and from community comparison families have participated in the COGA study. Participants were administered a comprehensive evaluation that included clinical assessments of substance use and psychiatric disorders using the Semi-Structured Assessment for the Genetics of Alcoholism research interview. In a subset of families, DNA was collected, and a brain functioning protocol was administered that included measures of EEG during resting state, such as measures of neural connectivity. The current COGA protocol began in 2019 when the project turned to a onetime follow-up assessment of previous COGA participants currently in two life stages: participants aged 50 or older , the majority of whom have a lifetime history of AUD, and participants aged 30–40 from a longitudinal study of youth and young adult offspring from COGA families, approximately half of whom have a lifetime history of AUD. In these samples, over 95% had DNA and GWAS data available, and over 75% completed at least one EEG assessment. Further details on these earlier studies have been published.Descriptive characteristics of the analytic sample are displayed in Table 1. Briefly, the average age of participants was 51; 62% were women, 16% self-identified as Black, and 8% self-identified as Hispanic . Differences in characteristics of each analytic group as a function of past AUD history are depicted in Table 1. Individuals without a history of AUD were more likely to be women and Black and had less severe alcohol-related history and other substance use, compared to individuals with a history of AUD and were younger compared only to abstinent individuals in remission from AUD. Increases in drunkenness frequency since the start of the pandemic as a function of pre-pandemic AUD status are displayed in Fig. 1.

Increases in drunkenness frequency since the start of the pandemic were significantly greater among those experiencing AUD symptoms prior to the start of the pandemic when compared to those without a history of AUD . Among individuals in remission from AUD prior to the start of the pandemic, rates of increased drunkenness were 10% for those who were drinking pre-pandemic and 4% for those who had previously been abstinent. Across all groups, women reported nominally greater increases in drunkenness frequency when compared with men; however, only women experiencing pre-pandemic AUD symptoms reported significantly greater rates of increased drunkenness since the start of the pandemic compared to women without a history of AUD . To capture the shared variance represented by the 33 COVID- 19-related stress and coping activities items shown in Supplementary Table 1 and to reduce the multiple test burden, each item was entered into an exploratory factor analysis. While models ranging from 7 to 11 factors all provided a good fit to the data , a 9-factor solution provided the best balance of model fit and interpretability. To obtain factor scores, we subsequently conducted a confirmatory factor analysis including 9 latent factors indexing COVID-19 related illness and severity, family member illness and death, media consumption, perceived stress, economic hardship, healthy coping activities, relationship quality, social disconnection, and essential worker status. Several of the COVID-19-related factors were correlated ; among the most highly correlated factors were perceived stress with social disconnection , media consumption , and economic hardships . Essential worker status was also highly correlated with COVID illness . The main effects of COVID-19-related stress and healthy coping latent factors on change in drunkenness frequency are displayed in Table 2 and Fig. 2. Note, Fig. 2 depicts group-level change in terms of participants who reported that their frequency of drunkenness has increased or decreased since the start of the pandemic. Among those without a prior history of AUD, associations between COVID-19 risk and protective factors with increases in drunkenness frequency were not observed. Among all groups with a history of AUD , perceived stress was associated with increases in drunkenness. Among the remitted-abstinent group, essential worker status was associated with increases in drunkenness. Gender differences in these associations were observed . Among women in the remitted-abstinent group, essential worker status, perceived stress, media consumption, and social disconnection were associated with increases in drunkenness. Among men in the remitted-drinking group, perceived stress was associated with increases in drunkenness, and increased relationship quality was associated with decreases in drunkenness. Exploratory analyses examining whether polygenic risk for ‘problematic alcohol use’ and/or low alpha EEG interhemispheric coherence moderate the associations of the COVID-19 factors and changes in drunkenness are presented in Supplementary Table 3. Exploratory analyses indicated that associations between family illness or death with increases in drunkenness and increased relationship quality with decreases in drunkenness were more pronounced among the remitted-drinking participants with higher PRS. Associations between family illness or death, media consumption, and economic hardships with increases in drunkenness and healthy coping with decreases in drunkenness were more pronounced among the remitted-abstinent group with lower interhemispheric alpha EEG connectivity. In this study, we examined the association of COVID-19-related stress and healthy coping activities with changes in drunkenness frequency since the start of the COVID-19 pandemic among participants with and without a history of AUD, including those experiencing symptoms and those in remission from AUD prior to the pandemic. Our results demonstrated that compared to those without a lifetime history of AUD, non-remitted individuals with a history of AUD reported greater increases in drunkenness frequency since the start of the COVID-19 pandemic; however, this difference was not observed among those who had been in remission from their AUD, regardless of their drinking status.

The oral microbiome is one of the most diverse microbial niches in the human body, including over 600 different microorganisms . It is in continual contact with the environment, and has been shown to be susceptible to many environmental effects. These environmental factors include tobacco use, romantic partners, and cohabitation. The microbes reside in sub-niches along the oral cavity including on the tongue, cheek, and teeth. The salivary microbiome has been shown to be representative of many the oral microbiome niches, which is thought to be due to the fact that microorganisms from the oral cavity surfaces shed into the saliva. Previous salivary microbiome studies have identified specific microbiota that are present in almost all individuals, referred to as the core microbiome. Saliva is also accessible, making it ideal for surveys of populations for microbiome studies. In this paper, we describe an unbiased approach to studying the effects of human genes on the oral microbiome with a two-step strategy. The first step utilizes twin information to establish heritable phenotypes related to the microbiome; and the second identifies DNA sequence variation associated with the identified highly heritable traits. From 16S rRNA sequence information, a large number of potential phenotypes can be explored with the twin studies to allow identification of the most heritable and therefore the phenotypes most likely to be mapped in the association study. A key strength of this approach lies in the independence of the data underlying the two steps reducing multiple testing and type 1 effects on the power to carry out the test for association. The ability to refine a phenotype prior to carrying out an association study can lead to greater likelihood of detecting specific SNPs that influence it. We show,plant benches with the largest oral microbiome twin study to date, that multiple phenotypes of the salivary microbiome are heritable.

Using these phenotypes, we identify promising host gene candidates in a genome wide association study of an separate sample that may play a role in establishing the oral microbiome.Samples from 1504 twins of whom 111 within-twin longitudinal samples with at least 3500 reads and DNA samples from 1481 unrelated individuals with at least 3000 reads produced 2664 and 2679 OTUs respectively. All samples were rarefied to 2500 sequences to retain as many samples as possible to improve power with little effect to results. To avoid analyses of OTUs that were the result of sequencing or PCR error, OTUs that were not present in at least 2 subjects and observed at least 10 times were removed, resulting in 895 OTUs in the twins and 931 OTUs in the unrelated individuals. One of the unrelated individuals was later removed during analysis due to cryptic relatedness leaving 1480 people in the unrelated sample.β-diversity was analyzed via Bray Curtis and UniFrac using QIIME and R. Analyses included 366 MZ pairs, 386 DZ pairs, and 37,832 unrelated pairs obtained by using age and DNA collection year matched non-cotwin pairs from the twin sets. P values were calculated similarly to as previously described. In short, the pair labels were permuted 10,000 times and the W test statistic collected from each permutation. The P value was then calculated by dividing the number of W test statistics greater than the observed W test statistic plus 1 by the number of permutations plus 1. Biplot analyses were used as implemented in QIIME . In experiments where cohabitation was required, only cotwins 18 and under and those over 18 who identified themselves as cohabitating were included, which removed 328 subjects from the total twin sample who were living separate from their cotwin. This population of 588 twins pairs is referred to as the “cohabitation sample.” Cohen’s D effect size for β-diversity measurements was calculated using the R package ‘effectsize’ .

Microbial traits included taxonomic groups, OTUs, α -diversity measurements, and principal coordinates from β-diversity measurements , collapsing all perfectly correlated traits. Microbial traits were then processed within each population separately: twin pairs, European unrelated , and Admixture American unrelated . Traits were transformed to z-scores and then categorized as either continuous or categorical . Shapiro Wilk test was performed use the R packaged ‘stats’. Categorical traits were then binned based upon z-score transformation on all non-zero values : zero counts, less than or equal to −1, greater than −1 and equal or less than 0, greater than 0 and less than or equal to 1, greater than 1. Some traits failed to categorize due to lack of variation, resulting in the final trait counts: twins , EUR unrelated , ADM unrelated . Only the continuous traits were used in the EUR and ADM populations so data is provided only for those traits. Descriptions of all traits can be found in Additional file 1: Tables S11–14.The MZ and DZ ICC values were calculated using the R package ‘irr’ and were compared using the Wilcoxon Signed Rank Sum test function in the R package ‘stats’. The ICC values were calculated for all taxonomic groups that were categorized to be treated as continuous traits . P value was calculated as similarly to as previously described in which the zygosity labels of the twin pairs were randomized 10,000 times and the ICC values then calculated. This analysis compared the overall distribution of the ICC values for the MZ twin pairs compared to the DZ twin pairs. Because the entire distribution was compared and not each taxa individually multiple testing correction was not needed. In addition the ICC values for the remaining 17 continuous traits were determined .Genome Complex Trait Analysis was performed on all traits categorized as continuous in both the twin and unrelated populations using the GCTA software. The GCTA analysis was performed on the cleaned imputed genotypes described above in the European sample . The following covariates were included in the model: age; sex; sequencing run ; year DNA was collected; saliva collection method for 16S sequencing; DNA collection method for host genotyping; and the first 10 PCs to control for population stratification.

GCTA estimates for the Admixture American sample were not reported due to the small sample size after the threshold of IBS estimates less than 0.025 were applied.Genome wide association study analyses were performed using the software EPACTS. The Q.EMMAX function was used, analyzing the dosage information for each variant. The GWAS analyses were performed in the ADM and EUR ancestry groups separately. For both analyses a kinship matrix and first 10 principal components were included to control for population stratification within each ancestry sample . In addition to controlling for population stratification the following covariates were included in the model: age; sex; sequencing run ; year DNA was collected; saliva collection method for 16S sequencing; DNA collection method for host genotyping; and tobacco use . The kinship matrix was created based upon all 22 autosomes using the kinship function in EPACTS. To rule out the possibility that stratification or computational method influenced results, three additional methods utilizing different programs and methods for controlling for population stratification were carried out. These were: EPACTS with only the kinship matrix made from all SNPs ; PLINK with the first 10 PCs ; and GCTA with the leave-one-out kinship matrix . For all methods the following covariates were included in the model: age; sex; sequencing run ; year DNA was collected; saliva collection method for 16S sequencing; and DNA collection method for host genotyping.We performed an analysis of 752 twin pairs from the Colorado Twin Registry to estimate host genetic and environmental contributions to salivary microbiome composition. The sample included 366 monozygoticpairs , 263 same sex,rolling bench and 123 opposite sex dizygotic pairs that ranged from 11 to 24 years of age. Taxonomic analyses using sequencing of variable region IV of the 16S rRNA amplicon prepared from the saliva of each twin was carried out using QIIME on high-quality Illumina MiSeq paired end reads as previously reported. We determined phyla abundances to be Firmicutes , Proteobacteria , Bacteriodites , Actinobacteria , and Fusobacteria from the 2664 operational taxonomic units found, which is consistent with the “core” salivary microbiome we and others have previously reported. All of our analyses included only OTUs that were present in at least 2 subjects and observed at least 10 times in total after rarefying at 2500 reads. This filtering yielded 895 OTUs that were considered for all subsequent experiments. Measurements comparing mean β-diversity among MZ, DZ and unrelated individuals allows for assessment of microbial population differences between groups. With either Bray-Curtis or Weighted UniFrac measures of β-diversity among MZ twin pairs were significantly more similar to each other than DZ twin pairs, and for all 3 β-diversity measurements MZ and DZ twin pairs were significantly more similar to each other than to unrelated individuals . This analysis was also carried out with abundant OTUs and all OTUs with very similar results .

Rarefaction at 2500 reads produced consistent results across all rarefactions , so for subsequent analyses, one rarefaction to 2500 reads is shown. We could detect no significant effect on any β-diversity measure due to sex when comparing same sex vs opposite sex dizygotic twin pairs perhaps because the sample size did provide enough power to differentiate sex effects from interindividual variation . In subsequent DZ analyses therefore, opposite sex pairs were included. The Colorado Twin Registry includes highly detailed phenotypic information that is invaluable inidentifying and controlling for environmental confounders that may play an important role. Living together is a covariate influencing microbial populations in humans. It is well-known that MZs tend to cohabitate longer than DZs and indeed our previous work has shown that shared environment influences the oral microbiome. Therefore, it was possible that the tendency of MZ cotwins to live together longer could be driving the observed heritability. To examine this potential confounder, we reanalyzed the data in Fig. 1a based on questionnaire data from the sample in which we restricted the analysis to only cohabitating pairs . While ideally we would have also analyzed only twin pairs living apart, our sample size did not permit it. As seen in Fig. 1b, MZs remained significantly more similar to each other than DZ twin pairs for the Bray-Curtis and Weighted UniFrac measurement, and was also observed in the abundant and unfiltered/ unrarefied OTU tables described above . We conclude that cohabitation does not play a significant role in the observed microbiome heritability. To quantify the differences between groups the Cohen’s D effect size was calculated for all β-diversity measurements for both the full sample and the sample limited to twin pairs who were cohabitating . Comparisons between the unrelated and twin pairs yielded medium to large effect sizes. All other comparisons were either small or negligible, the largest of which being between MZ and DZ pairs for Bray Curtis. To quantify the effect cohabitation had on β-diversity measurements the effect size between all twin pairs and just pairs living together were compared for all measurements yielding only negligible effect sizes consistent with a conclusion that cohabitation was not driving observed heritability. The stability of the oral microbiome over time in adults is reported to be remarkably high relative to that of other body sites. To confirm and extend this observation, we assessed the stability of the oral microbiome in longitudinal samples from our cohort for 111 individuals, 2–7 years apart . The mean β-diversity measurements between longitudinal samples were compared to the mean of unrelated individuals of different ages. For all three β-diversity measurements examined subjects were significantly more similar to themselves than were unrelated individuals . Intraclass correlation coefficients are useful for estimating heritability of individual observations within a group of related observations ; the higher the ICC values for MZ pairs compared to DZ pairs, the greater the heritability. As shown in Fig. 2, ICC values for essentially all abundant taxa are significantly greater in MZ than DZ pairs. No significant difference was observed between the same sex and opposite sex DZ pairs across the taxa analyzed. The set of taxa analyzed were those that were categorized as continuous . Significance was established with Wilcoxon Signed Rank tests strongly supporting the heritability of taxon abundance in this twin set. We also tested 4 different alpha diversity measures , the first 3 principal coordinates for three different β-diversity measurements and saw that most traits were consistent with the conclusion that MZ cotwins are more similar than DZ cotwins.

We will also examine intervention efficacy on other opioid outcomes , other substance misuse and consequences, and impaired driving. Further, we will also measure intervention costs and identify moderators/mediators of efficacy. In this paper, we describe the RCT protocol with a focus on evaluation of primary and secondary outcomes.We are testing the efficacy of behavioral interventions as secondary prevention for opioid misuse and opioid use disorder among AYAs in a 2 x 2 factorial RCT design with two intake and two post-intake conditions. Conditions delivered at intake are: 1) a single video delivered health coach session, and 2) an EUC control condition of a community resource brochure. Post-intake conditions are: 1) portal messaging that lasts for 30 days, or 2) EUC control brochure delivered at 30 days. This combination effectively results in 4 groups as shown in Figure 1 . The health coach session occurs during intake and the portal begins at intake and occurs over the following 30 days. Depending on randomization, the EUC resource brochure is either delivered at intake or 30 days later . EUC essentially functions as a control condition, with the provision of minimal resources that exceed the current standard of care in the ED pertaining to opioid screening and prevention as done in a number of prior ED-based studies.In total, we seek to enroll 1170 ED patients ages 16 to 30 . Recruitment occurs either in-person or remotely, a secondary recruitment approach that was added because of restrictions on in-person research activities during the COVID-19 pandemic. All procedures are IRB approved.As part of our funding mechanism and with IRB approval, we piloted the interventions and EUC described in detail below in the Spring of 2020, with N = 40 AYAs enrolled with informed consent/assent and the same trial eligibility criteria described below.

Each participant received the EUC at enrollment,cut flower transport bucket the health coach session, 30 days of portal messaging, and a 1-month follow-up invitation e-mail . After enrolling the first 10 participants using ED-based recruitment methods, we paused recruitment to refine interventions based on participants’ feedback. During this pause, in-person recruitment efforts were suspended due to the COVID-19 pandemic, and the remaining 30 participants were recruited remotely after their ED visit and all interventions were delivered remotely in private from staff homes to participants’ homes. Among the participants who participated in pilot testing the health coach session, 38 provided acceptability ratings. Their intervention satisfaction was M = 9.3 on a 10-point scale with 10 being the highest possible rating. Similarly, on a 10-point scale, ratings for recommending the intervention were M = 9.0 . Fidelity coding of selected sessions was based on the Motivational Interviewing Treatment Integrity Code33 with fidelity exceeding “fair” thresholds, and nearly all markers exceeding “good” thresholds. These included the following means: M = 4.3 relational scale, M = 3.9 technical score, M = 71.5% complex reflections, and M = 1.7:1 reflection/question ratio. Next with regard to the portal, among our first 10 participants, portal engagement was lower than expected with only 60% replying at all. Thus, we used participant feedback to make several functional and design changes prior to recruiting the next 30 participants. These changes included adding a “remember me” function to avoid needing to remember a password, updating the look and feel of the portal, adding use of an emoji avatar chosen by participants, branded token items valuing ~$1 mailed weekly . We also evaluated use of an incentive structure for portal messaging with the final 30 participants.

Thus, we enrolled 10 participants each into cohorts: a) no incentive for message replies, b) $1 incentive for each reply with ability to earn up to $20, and c) $5 incentive for each reply with ability to earn up to $20. Engagement, as measured by number of replies from participants, was higher in these latter cohorts. The no incentive cohort had a M = 11.8 messages received with 100% replying, the $1 incentive group had M = 10.0 messages received with 80% replying, and the $5 incentive group had M = 15.6 messages received with 100% replying. Given that functional and design changes in the portal appeared to result in increased engagement without the use of additional incentives, we elected to not incentivize participation in the planned RCT, especially since there would be additional challenges associated with later implementation of incentives within healthcare systems. Finally, among 37 pilot participants who provided feedback ratings for the portal, ratings of satisfaction were M = 8.5 and recommendation were M =8.9 , on a 10-point scale with 10 being the highest rating. Modified MITI fidelity coding for complex reflections and reflection-to-question ratio exceeded benchmarks such that were on average 59.5% complex reflections and the average reflection-to-question ratio was 2.9:1. Overall, the feasibility of our pilot testing supported the inclusion of the intervention conditions in the planned RCT. The acceptability data provided by participants at follow-up was promising, particularly given refinements to the portal condition, and staff demonstrated acceptable fidelity to the intervention model. Participants are recruited from the Michigan Medicine pediatric and adult EDs in Ann Arbor, Michigan. Combined, these EDs have about 100,000 visits per year and are located in adjacent, but separate hospitals and maintain independently functioning systems of triage, medical staffing, and physical space allocation.

Recruiting from both EDs enhances generalizability to pediatric and adult ED settings. Historically, the average ED length of stay as been 3-4 hours which facilitates completion of in-person research protocols during the visit, although the COVID-19 pandemic has altered ED patient flow. Currently, there are no opioid-focused prevention programs in the study setting and opioid-related clinical care focuses primarily on treatment referrals and prescription monitoring. We attempt to recruit English-speaking patients ages 16-30 presenting to the ED for any reason in-person or remotely to complete an eligibility screening. Staff approach participants in the ED, and remote recruitment is used when staff are unable to recruit in the ED or to supplement in-person recruitment because of physical distancing limitations on approaching patients with suspected COVID and the number of staff who can be present at any one time due to COVID-related restrictions. When approaching potential participants, they must be medically and cognitively able to provide consent/assent; thus patients presenting with acute substance intoxication are excluded until able to consent. Individuals presenting to the ED with a chief complaint of acute sexual assault or acute suicidality will be excluded from screening. Those presenting with a current cancer diagnosis or currently receiving cancer treatment and pregnant women will also be excluded . AYAs who participated in our pilot study described below or who may be taking part in other current behavioral intervention trials at this study site are also excluded . Screened participants are eligible for the trial based on past 12-month prescription opioid use plus at least 1 other risk factor , or 12-month opioid misuse as described in the measures below . Screened individuals reporting injecting drugs or screening as high risk for current opioid use disorder based on a NIDA-Modified ASSIST V229–32 score of 27+ are excluded due to the study focus on prevention of development of opioid use disorder. These individuals are instead referred for treatment; staff direct them to options listed in study resource brochure if recruited remotely and if in recruited in-person staff offer referral to ED social worker. All procedures herein have been piloted in the study setting and among AYAs,procona flower transport containers including consenting and enrolling minors. Research assistants identify patients ages 16-30 via the electronic health record and tracking system, with a waiver of HIPAA authorization. Patients who meet screening exclusion criteria are not approached. Staff approach screening eligible patients based on triage time/status or discharge date/time using a standard script. Two-stage consent for ages 18+ and parental consent/child assent rare obtained for screening and, subsequently, the RCT. Staff review limits to confidentiality and study procedures during consenting/assenting. Specifically, parents are consented concurrently for screen and baseline . Subsequently, youth assent is obtained for screen and baseline. Study data is not shared with parents or guardians and confidentiality would only be broken in the case of acute risk, such as acute suicidality, homicidality, or child abuse, to preserve adolescents’ or others’ safety. For in-person recruitment, research staff approach ED patients ages 16-30 for consent/assent to self-administer a brief web-based screening survey on iPads. Surveys are paused during medical procedures and consultations such as x-rays, assessments, and blood draws.

For remote recruitment, research assistants contact ED patients ages 16-30 after discharge for consent/assent to complete the screening survey on their personal device or by phone. Participants screened in person receive a gift valuing $1.00 for survey completion. AYAs meeting eligibility criteria above are invited to participate in the RCT. After consenting/assenting, RCT participants complete a baseline survey and are randomized to conditions. Randomization is stratified by sex, age , and opioid risk severity : none or higher and occurs in blocks of 8 within strata to equalize over time. Randomization is computer generated in Qualtrics and is not be known by recruitment staff until after completion of the baseline survey when staff run the randomization program to reveal condition. Staff then orient participants to their assigned condition. Because this is a behavioral intervention where participants are receiving counseling interventions, participants and coaches are not blind to their condition. Participants then receive their assigned intake condition at intake and are then oriented to their post-intake condition . If needed, those unable to complete all intake activities in the ED may complete them in person, by telephone, or video call; these activities are scheduled prior to leaving the ED. Participants who join the study remotely, or who do not complete enrollment during the ED visit, may have up to 30 days to complete intake activities. Enrolled participants receive a token gift in-person or by mail. Participants are asked to complete follow-up assessments lasting approximately 25-30 minutes that mirror baseline measures at 3-, 6-, and 12-months. Participants are remunerated in cash or gift card . Follow-ups are primarily online, without staff interaction, however, in the event a participant elects in-person follow-up staff administering assessments are blinded to condition assignment.Consistent with a telemedicine hub model, research assistants connect participants to the remote health coach using a telehealth platform such as Facetime or Zoom. Health coaches are bachelor’s-level or higher staff hired who have relevant backgrounds and experience in fields such as social work, psychology, counseling. Health coaches are further trained in MI and CBT strategies by the study team and supervised weekly by experienced master’s-level coordinators and doctoral-level investigators. The ~45 minute session blends elements of efficacious brief motivational interventions from our prior work, including an opioid-focused brief intervention and developmentally appropriate content for ages 16-30 based on our prior alcohol-focused brief interventions.The intervention guide is housed in an internal website that is only accessible to study staff and includes decision-support screens to guide intervention delivery and enhance fidelity , allowing health coaches to collect within session para-data , consistent with prior work that found para-data are associated with important MI mechanisms and clinical outcomes.Our session, outlined in Table 1 is rooted in the Why Change and How Change model of MI.The remote health coach session uses MI strategies to engage and explore individuals’ situations, allowing for in-the-moment tailoring to address needs relevant for AYAs using MI concepts . During Why Change, health coaches review and affirm participants’ goals and strengths, and invite discussion of opioid misuse as well as other substance use. MI skills , seeking permission, Elicit-Provide-Elicit, elaboration, rulers, and autonomy support are used. Elicit-Provide-Elicit is a tool for collaborative psychoeducation used to explore risk perceptions of opioid medications and/or overdose in a highly tailored manner .Personallyspecific benefits of change are elicited and reinforced; as many young people may be pre-contemplative about change, health coaches learn to elicit hypothetical benefits of future change or scenarios for choosing to avoid use . After summarizing change talk, health coaches explore How Change, eliciting personally tailored tools to address misuse of substances and risk factors. Tools include brainstorming alternatives to address motives and risks . If applicable, participants are encouraged to consult their primary care or other medical providers with questions.

CBSST appears to be an effective intervention to address these concerns that requires minimal resources and a relatively brief treatment interval, making it ideally suited to adaptation to a variety of clinical settings. Future studies will compare CBSST to standard outpatient care with a focus on additional outcomes, including quality of life and healthcare utilization.Bipolar disorder is a severe, chronic, and disabling mental illness characterized by recurrent episodes of hypomania or mania and depression. The evidence from twin, family, and adoption studies provide compelling evidence for a strong genetic predisposition to BPD with heritability estimated to be as high as ≥80% . Given BPD is a heterogeneous disease with substantial phenotypic and genetic complexities, the identification for BPD risk loci has proven to be difficult. Some researchers have proposed that dissecting BPD into clinical subgroups with distinct sub-phenotypes may result in genetically homogeneous cohorts to facilitate the mapping of BPD susceptibility genes . Among the subphenotypes, early-onset BPD is of particular interest as several independent cohort studies have demonstrated their existence. Comparing to the non-early-onset BPD, the early-onset subtype is associated with a more severe form of clinical manifestations characterized by frequent psychotic features, more mixed episodes, greater psychiatric comorbidity such as drug and alcohol abuse and anxiety disorders, higher risk of suicide attempt, worse cognitive performance, and poorer response to prophylactic lithium treatment. In addition, the pattern of disease inheritance seems to differ between early‐ and late‐onset BPD families, with the former involving greater heritability. These observations indicate that early-onset BPD may be a genetically homogenoussubset and thus could be used for genetic study to identify its susceptibility genes.

A number of BPD genes identified by genome-wide association study have been widely replicated and intensively studied,cannabis grow equipment but these studies did not include early-onset BPD. Over the past two decades, a host of studies have investigated genetic loci responsible for early-onset BPD through linkage-analyses, candidate–gene association, analyses of copy number variants , and GWAS, but findings are inconclusive. Candidate–gene association studies have identified a number of genes potentially associated with early-onset BPD, including glycogen synthase kinase 3-β gene, circadian clock gene Per 3, serotonin transporter gene, brain-derived neurotrophic factor gene, and gene coding synaptosomal-associated protein SNAP25. However, very few positive findings of these studies have been replicated independently. Findings from linkage studies suggested chromosomal regions harboring the susceptibility genes at 3p14 and 21q22, plus the loci at 18p11, 6q25, 9q34 and 20q11 with nominal significance. Studies of CNVs in early-onset BPD were based on relatively small effect sizes and were irreproducible, suggesting that CNVs are unlikely the major source of liability. Finally, GWAS failed to find any risk variant with genome-wide statistical significance in Caucasian populations, despite some variants showed suggestive significance. In previous genetic studies, the definition of early-onset in BPD typically ranged from 15 to 25 years of age. These association studies were largely conducted with small sample size and were under powered . Most of them compared early-onset BPD vs. healthy control. Such a case–control design is more likely to identify susceptibility gene for BPD per se, but not for the early-onset sub-type. The optimal strategy to identify gene for the early-onset BPD is to include the non-early-onset BPD group for comparison. In this paper, we reported findings from a GWAS with high-density SNP chips on early-onset, defined as ≤20 years of age, BPI patients of Han Taiwanese descent.

The clinical phenotype assessment of manic and depressive episodes was performed by well-trained psychiatric nurses and psychiatrists using a cross culturally validated and reliable Chinese version of the Schedules for Clinical Assessment in Neuropsychiatry, supplemented by available medical records. All of them were diagnosed according to the DSM-IV criteria for BPI disorder with recurrent episodes of mania with or without depressive episode. The assessment of onset age was based on a life chart prepared with graphic depiction of lifetime clinical course for each of the BPI patient recruited. This life chart included largely all the mood episodes with date of onset , duration, and severity . The construction of this life chart was based on integrated information gathered from direct interview with patients and their family members, interviews with in-charge psychiatrists, and a thorough medical chart review. Different definitions for early onset of BPI have been proposed in previous work. Our selection of 20 as the age threshold was based on a systematic review for pediatric BPD. The age at onset was defined by the first mood episode . Of all patients, 1306 with genotyping data available were included in the discovery group for GWAS and the rest 473 without genotyping data were included in the replication group.In this paper, we have reported one of the largest GWASs to investigate genetic susceptibility to early-onset BPI with the first mood episode occurring ≤20 years of age. We employed standardized psychiatric interview and constructed a life chart with detailed clinical history to ensure the accuracy and homogeneity of phenotype for genotyping. Our GWAS with high-density SNP chips identified the SNP rs11127876 in CADM2 gene to be associated with early-onset BPI in both discovery and replication groups, and meta-analysis for the association was close to genome-wide significance .

The gene CADM2 on chromosome 3 encodes a synaptic cell adhesion molecule that is prominently expressed in neurons, and plays key roles in the development, differentiation, and maintaining synaptic circuitry of the central nervous system. In previous GWASs, CADM2 has been found to be associated with a number of mental health related traits, including alcohol consumption, cannabis use, reduced anxiety, neuroticism and conscientiousness, and increased risk-taking behavior. CADM2 was also reported to be associated with executive functioning and processing speed, general cognitive function, and educational attainment. Though there have been no investigations examining the risk-taking phenotype in early-onset relative to non early-onset BPD, Homes et al. showed that BPD patients with a past history of alcohol abuse or dependence had a higher risk-taking propensity, suggesting a relationship between early-onset BPD and risk-taking propensity. Of note, Morris et al. suggested that CADM2 variants may not only link with psychological traits, but also influence metabolic-related traits, such as body mass index, blood pressure, and C-reactive protein. In addition, they found that CADM2 variants had genotype specific effects on CADM2 expression levels in adult brain and adipose tissues. The finding highlights the potential pleiotropy of CADM2 gene, i.e., the genetic variants may influence multiple traits, and shared biological mechanisms across brain and adipose tissues through the regulation of CADM2 expression. Given that the metabolic comorbidities are prevalent in patients with early-onset BPD, it is conceivable that CADM2 variants may influence both psychological and physical traits, further contributing to a more severe clinical subtype of BPD with accompanying risk of metabolic adversities. In addition, an association between risk-taking and obesity has also been implicated in previous research, which suggests that risk takers tend to overlook health-related outcomes and are prone to aberrant reward circuitry predisposing them to poor dietary choices and excessive intake. Collectively,vertical grow rack in line with the characteristics found to be associated with CADM2 variants, it is likely that CADM2 may exert an effect on the constellation of clinical features related to early-onset BPD with greater symptom severity . Therefore, our findings suggest that CADM2 genetic variants may have significant effects on a subtype of BPD with early-onset. Two previous GWASs comparing early-onset BPD patients with healthy controls did not find any genetic variants reaching genome-wide significance. Our study included a larger sample of early-onset BPI patients to conduct GWAS using high-density genotyping . The statistical power was calculated using Post-hoc Power Calculator , combining the allelic frequencies of both discovery and replication groups. In this study of two independent samples of BPI with dichotomous endpoint, the power reached 99.4% and 18.2% under type I error = 0.05 and = 5 × 10−8 , respectively. Results of our study are also likely to be under powered under the stringency setting of type I error. However, the frequency of risk allele T was higher in patients with onset ≤20 than in patients with onset >20 in both discovery and replication groups. We believe all these have provided strong evidence to confirm the association of this SNP with earlyonset BPD. In Table 2, the minor allele frequencies differ quite a bit between the discovery and replication cohorts. In the NCBI SNP database, minor allele frequency of rs11127876 is 0.08 in Han Chinese in Beijing, close to our results and suggest that the different allele frequencies observed in Table 2 may mainly result from our sampling. The over-representative minor allele frequency in replication group may have come from random sampling or effects of hidden characters of our patients recruited. Genetic variant of CADM2 has been reported to be associated with behavioral and metabolic traits, which were not assessed in this study.

Though the minor allele frequencies of rs11127876 were different in discovery and replication groups, the same direction of ORs of rs11127876 minor allele supports the reliability of our findings. The SNP rs75928006 located in the upstream of MIR522 reached genome-wide significance in discovery group but failed to show statistical significance in replication group. MIR522 promotes glioblastoma cell proliferation, but there was no evidence to suggest its association with any psychiatric disorders. One major limitation of this study is the possibility of recall bias about the exact onset age of the first mood episode of BPI, particular when there was a long history of the illness. Previous studies have however suggested that age at onset can be assessed reliably. The preparation of life chart containing detailed clinical course and treatment based on a semi-structured clinical interview plus a thorough medical chart review for individual patients should have overcome this potential limitation satisfactorily. In summary, we have identified a genetic locus rs11127876 in CADM2 gene to be associated with earlyonset BPI. The finding has reflected the co-sharing genetic features of psychiatric disorders and behavioral traits. Further investigations of the CADM2 biological function in BPI are warranted.The misuse of opiates is a serious problem worldwide, is increasing in young adults, and has substantial individual and societal consequences. In 2014 in the United States alone, approximately 1.9 million people had an opiate use disorder, including 586,000 heroin users. Neuroimaging in opiate dependence indicates both altered brain structure, particularly in the anterior cingulate cortex , and brain function involving dorsolateral prefrontal cortex and ACC. Magnetic resonance spectroscopy allows the non-invasive quantitation of brain metabolites that provide information on the neurophysiologic integrity of brain tissue. The few 1H MRS studies in opiate dependence to date revealed lower concentration of N-acetylaspartate , a marker of neuronal integrity, in the medial frontal cortex, including the ACC, as well as lower glutamate , a primary excitatory neurotransmitter, or glutamate+glutamine concentration in some but not all studies. The discrepant MRS findings may relate to differences among study participants regarding the prevalence and severity of comorbid substance use , the type, dose and duration of replacement therapy for heroin users , and/or participant age. The ACC, DLPFC and orbitofrontal cortex are important components of the brain reward/executive oversight system, a neural network critically involved in the development and maintenance of addictive disorders. Structural brain imaging in opiate dependence revealed generally lower gray matter volume or density in frontal regions, including the DLPFC, with thinner frontal cortices related to longer duration of opiate misuse. Functional MR imaging showed that the DLPFC, OFC and ACC are involved in decision making, and in opiate dependent individuals, lower task-based fMRI activity in the ACC related to compromised behavioural control of cognitive interference. Furthermore, smaller frontal gray matter volume in opiate dependence related to higher impulsivity on the Barratt Impulsivity Scale . Correspondingly, opiate dependence is associated with cognitive deficits, primarily in executive functioning and self-regulation . Thus, the neuroimaging literature in opiate dependence suggests altered frontal brain structure as well as compromised neuronal integrity and glutamatergic metabolism. Few if any studies however investigated their relationships to opioid and other substance use behaviour or cognition. Further research into specific regional brain effects and their potential cognitive and behavioural correlates may inform better targeted treatment of individuals with opioid use disorders.

Approximately 23% reported using alcohol and drugs prior to sex in the last six months. Participants who had a partner on PrEP reported a higher number of sex partners in the last six months compared to those with only HIV-positive partners and those with HIV-negative partners not on PrEP . However, condomless sex did not statistically differ across the three partner groups, with a prevalence of condomless sex in the last six months of 13% among PWH who had a partner on PrEP, 19% among those with only HIV-positive partners, and 16% among PWH without PrEP partners .This study examined the association of alcohol and drug use and partner use of PrEP with STI risk among PWH with a history of unhealthy drinking. Results indicated that, although PWH in this cohort have reduced HIV transmission risk based on their viral suppression and/or the use of PrEP by partners, the risk of STI transmission remained a concern. We found that participants who had a partner on PrEP had nearly three times the prevalence of STIs compared with those who had HIV-negative partners not taking PrEP. Approximately 8% of the participants in our study had a positive STI test result during the study period. The prevalence we observed was slightly lower compared to recent estimates in the STD Surveillance Network. However, Lucar et al.found similar STI rates in their clinic-based cohort of PWH across multiple sites in the Washington DC metropolitan area. These findings should be interpreted with the context that overall STI incidence among MSM has been steadily increasing over the last two decades. In one study at a community health centre in Boston, incidence of STIs among MSM increased from 4.6 to 26.8 per 100 person-years between 2005 and 2015.This trend is likely multi-factorial and partly due to a decline in condom use, enhanced STI testing, flood tray and broader perception of HIV as a manageable illness.Some have proposed that the roll-out of PrEP has contributed to increases in condomless sex, thus driving incident STIs among MSM.

However, surveillance data have noted increases in STI prevalence in the general MSM population well before the widespread use of PrEP.In our analysis, we found no statistically significant differences in condom use among PWH who had a partner on PrEP and those who did not, suggesting the potential role of other behavioural factors, such as number of partners and alcohol and drug use. Sexual network characteristics may account for the associations we observed. PWH who had a partner on PrEP had four times the median number of sex partners in the last six months compared to others, suggesting a higher probability of STI exposure. Other network characteristics such as background STI prevalence, rate of partner exchange, concurrency of sex partners, and network density or how interconnected individuals are in a sexual network might have also influenced STI risk.w1 As PWH who had a partner on PrEP were more sexually active than others in our cohort, they may also have been screened for STIs more frequently, leading to increased detection of asymptomatic infections. We also found that PWH who used alcohol and drugs prior to sex had a higher STI prevalence, although estimates were not statistically significant. Chemsex, or the use of sex enhancing drugs such as amphetamines during sex, has become increasingly popular among MSM in industrialized countries, and is a well-known driver of sexual risk-taking.The associations we observed were attenuated in adjusted analyses but the direction of each association was consistent with findings from previous reports. For example, alcohol and drug use have been associated with condomless sex, impaired sexual decision-making, and having higher numbers of sexual partners.Our findings also support the need for ongoing discussions around sexual risk behaviours and STI risk reduction during routine clinic visits.

Given the cross-sectional design of our study, we cannot conclude that partner PrEP use is causally associated with STIs in PWH. However, this study has important implications for public health efforts. The prevalence of STIs among PWH who have partners on PrEP suggests that this subgroup may be a high-yield focus for targeted interventions. Along with efforts to increase STI screening, enhanced outreach that integrate HIV and STI care coordination, and novel strategies, such as STI post-exposure prophylaxis, are needed. A key strength of our analysis is the use of a primary care-based cohort in an integrated healthcare system, which allowed us to link interview data with laboratory-confirmed STI test results. However, we acknowledge some important limitations. We were limited in our ability to characterize participants’ sexual networks and assess temporality of exposure and outcome. It is conceivable that participants acquired an STI before any encounter with a partner on PrEP or acquired the infection from others in their sexual network. It is also possible that participants may not have accurately reported their partner’s PrEP use or their condom use behaviours due to recall bias, social desirability, and/or misinformation. Some in our sample may also have received STI testing outside of the KPNC healthcare system, results of which would not be captured in the electronic health record. All participants had a history of unhealthy alcohol use in the prior year, so findings may not be reflective of the experiences of other PWH. However, the prevalence of hazardous alcohol use in our cohort based on AUDIT scores was similar to other studies involving general PWH populations.Lastly, the majority of the participants in our study were MSM and all of them were insured; therefore findings may not be generalizable to the broader population of PWH, particularly cisgender women, transgender people, and those without health insurance coverage.

Despite these limitations, this study provides important insights that can inform efforts to address the STI epidemic. However, prospective studies are needed to more clearly understand the relationship between partner PrEP use and STI incidence among PWH.Health complications related to preterm birth may impose lifelong sequelae or death.In the United States, 17% to 34% of infant deaths within the first year of life are attributable to prematurity.Children born preterm are more likely to have vision or hearing loss, cerebral palsy, and physical or learning delays.The societal economic burden associated with preterm birth in the United States was estimated to be over $26 billion annually more than a decade ago.Years of study have identified numerous risk factors for preterm birth, including obesity, hypertension, diabetes, smoking, drug or alcohol dependence/abuse during pregnancy and a short interval between pregnancies.Few protective factors against preterm birth have been identified, but include maternal birth outside of the United States and interpregnancy interval of 24 to 60 months.Identification of risk and protective factors has not decreased preterm birth rates in the United States – instead rates have been showing an upward trend. In an effort to improve infant health outcomes, there has been a recent upsurge in efforts to reduce preterm birth rates in the United States.This effort is challenging, due to the complex biology of preterm birth, various clinical presentations,ebb and flow tray and socioeconomic and psychosocial influences.Due to the need for multi-pronged approaches to decrease preterm birth rates, a collaborative place-based approach may be an effective way to decrease rates locally. A place-based approach is designed to take into account the unique local and contextual conditions of specific locations, engage a diverse range of sectors in a collaborative decision making process, and leverage local talent, knowledge, and assets.By addressing drivers of preterm birth that may be more frequent based on location , this method recognizes that one size may not fit all, either in terms of drivers or interventions. California reports a 2016 preterm birth rate of 8.5%, with the highest rate in Fresno County, located in the Central Valley region. Fresno County has just under one million residents, half of whom are Hispanic, and has the highest value of agricultural crops by any county in the United States.Fresno County reports the highest poverty rate in California, with 32.3% of families with children living below the poverty level, and is considered a Primary Care Health Professional Shortage Area.In this study we evaluated the influences of maternal characteristics and obstetric factors on timing of birth in Fresno County to evaluate both risk and prevalence of risk by urban, suburban, and rural residence.

We aimed to identify risk and protective factors for birth before 37 weeks’ gestation that can inform policy and health care priorities designed to reduce preterm birth rates in Fresno County. In this retrospective cohort study, our sample was drawn from California live births between January 1, 2007 and December 31, 2012. The sample was restricted to women with singleton births with best obstetric estimate of gestation at delivery between 20 and 44 weeks, linked to the birth cohort database maintained by the California Office of Statewide Health Planning and Development, with no known chromosomal abnormalities or major structural birth defects, and a Fresno County census tract . The birth cohort database contained linked birth and death certificates, as well as detailed information on maternal and infant characteristics, hospital discharge diagnoses and procedures recorded as early as one year before delivery and as late as one year post-delivery. Data files provided diagnoses and procedure codes based on the International Classification of Diseases, 9th Revision, Clinical Modification .Structural birth defects for the study were considered “major” if determined by clinical review as causing major morbidity and mortality that would likely be identified in the hospital at birth or lead to hospitalization during the first year of life.The sample of Fresno County women was stratified by residence in urban, suburban and rural census tracts as defined by the Medical Service Study Areas . MSSAs “are recognized by the U.S. Health Resources and Services Administration, Bureau of Health Professions’ Office of Shortage Designation as rational service areas for purposes of designating Health Professional Shortage Areas , and Medically Underserved Areas and Medically Underserved Populations ”.Within each of these residence strata, known maternal preterm birth risk factors were compared for women who delivered before 37 weeks’ gestation to those of women who delivered between 37 and 44 completed weeks’ gestation, using Poisson logistic regression to calculate crude relative risks and 95% confidence intervals . Comparisons using data from birth certificate records included race/ethnicity, maternal age, education, payment for delivery, participation in the Women, Infants, and Children program ,parity, maternal birthplace, report of smoking during pregnancy, maternal body mass index , trimester when prenatal care began, and number of prenatal care visits. For multi-parous women, we examined the relationship between preterm birth and previous preterm birth, previous cesarean delivery, and interpregnancy interval. Interpregnancy interval was calculated from previous live birth as reported in linked records and estimated as months to conception of the index pregnancy. Given that the day of previous live birth was not available, the middle of the month was used for calculation purposes.Factors from hospital discharge ICD-9 diagnoses included: Preexisting hypertension without progression to preeclampsia, preexisting hypertension with progression to preeclampsia, gestational hypertension without progression to preeclampsia, gestational hypertension with progression to preeclampsia, preexisting diabetes, and gestational diabetes. We also compared preterm birth with respect to the frequency of coded infection, anemia, drug or alcohol dependence/abuse, and mental disorder . Multivariable models of maternal risk and protective factors for preterm birth were built for each location of residence category using backwards-stepwise Poisson logistic regression wherein initial inclusion was determined by a threshold of p < .20 in crude analyses. Adjusted RRs and their 95% CIs were calculated for each residence stratum. In an effort to visualize overall risk of preterm birth by census tract, cumulative risk scores estimated the overall risk of preterm birth. Scores were calculated for each woman by adding her risks and subtracting her protective factors – 1 remaining in the final multi-variable model. Risk scores were grouped into scores 0.0 or less, 0.1 to 0.9, 1.0 to 1.9, 2.0 to 2.9 and 3.0 or more. Drug dependence/abuse and mental illnesses were further classified based on ICD-9 diagnostic codes, although risks calculations were not computed due to small numbers. Drug dependence/abuse was defined by classification of drug: opioid, cocaine, cannabis, amphetamine, other drug dependence/abuse, and poly substance dependence/abuse. Mental illnesses were further classified as: schizophrenic disorders, bipolar disorder, major depression, depressive disorder, anxiety disorders, personality disorders, and more than one of the previously mentioned categories. Infection was further classified as asymptomatic bacteriuria, urinary tract infection, sexually transmitted infection, and viral infection .

Utilizing data from the IMAGEN study that included longitudinal fMRI and measures of PS at follow-up, Papanstasiou et al. observed increases in right frontal activation during reward anticipation and feedback of win from age 14 to 19 that was associated with PS at age 19; this increase over time was not observed in youth who did not report PS. The authors speculate whether this finding could be a possible compensatory mechanism. However, given that PS were not assessed at age 14, results are to be interpreted with caution. Unlike task-based fMRI, it is less susceptible to performance and vigilance differences between groups, which facilitates interpretation of group differences. Again, the PNC has allowed large-scale investigation of functional connectivity across development. With regard to static functional connectivity , Satterthwaite et al. showed that PS youth exhibited similar patterns of dysconnectivity to patients with overt psychosis. In particular, they observed hyperconnectivity within the default-mode network and reduced functional connectivity within the executive control network . However, in one of the largest pediatric population-based samples Karcher et al. recently reported hypoconnectivity within the DMN and within the executive control networks that is associated with increased PS in 9- to 11-year old children . These differences in observed hypo- vs. hyperconnectivity may be attributable to age differences between the two studies. Nevertheless, there has been a similar dissonance in adult cohorts with overt psychosis, where both hypo- and hyperconnectivity of the DMN and executive control networks has been described . In an elegant follow-up study that applied multivariate sparse canonical correlation analysis to the PNC resting state data, Xia and colleagues corroborated that in fact the segregation between the DMN and executive control networks is a common feature across multiple psychopathology dimensions, but the psychosis dimension shows the strongest effect .

Moreover, a recent study of this cohort that investigated dynamic properties of functional connectivity, i.e., time-varying patterns of whole-brain connectivity,vertical grow system found that previously described dysconnectivity between the DMN and executive control networks in youth experiencing PS is time-dependent, and only occurs during certain periods of a resting-state scan, whereas dysconnectivity in visual and sensorimotor areas is much more pervasive . The Human Connectome Project is an adult cohort in which resting-state fMRI as well as self-reported PS were acquired. Here, PS were significantly inversely correlated with cognitive abilities, an effect that was partially mediated by global efficiency of the executive control network, a measure of network integration . With regard to dynamic functional connectivity in the HCP, it has recently been shown that adults experiencing PS spend more time in a dynamic state, i.e., a distinct time-varying connectivity pattern, characterized by reduced connectivity within the DMN ; a finding that mirrors previous results in studies on individuals with overt psychosis . Even though pediatric population neuroscience is still in its infancy, studies overwhelmingly find that PS in childhood and adolescence pose a risk factor for later development of overt psychiatric illness, and are overall associated with reduced functioning and quality of life. Many early intervention specialty programs offer a coherent multi-modal treatment framework for clients, including psychopharmacological treatment, psychotherapy and psychoeducation as well as vocational counseling. Meta-analytic results suggest that multidisciplinary therapies can delay or prevent transition to overt psychosis . Low risk psychosocial interventions targeting functioning have been shown to be effective in CHR youth; such approaches are likely to be also effective in a broader audience .

These results find consideration in the recently published guidelines of the European Psychiatric Association where a dual treatment consisting of cognitive behavioral therapy and pharmacological treatment yields recommendation grade A for adult CHR individuals. For children and adolescents experiencing PS, as targeted by pediatric population neuroscience, the expert recommendation is specific psychological interventions to improve functioning and close monitoring of PS. PS are often preceded by non-specific behavioral and emotional problems in childhood related to increased adversity and trauma. Since these precursors in themselves pose a risk for development of diverse psychopathologies, we argue – as others before us – that these childhood-onset problems offer another promising target for population-based preventive interventions. However, causal mechanisms from abnormal neurodevelopment to subsequent psychopathology are not yet understood and require further longitudinal research. Since only a minority of individuals with PS access appropriate mental health services, it will be important to implement services appropriate to a broad audience, for example in schools. It will be essential to identify those individuals at highest risk, and to reduce the number of false positives in order to provide cost effective services and to reduce stigma. Individual risk calculators developed and tested in CHR cohorts may not work as well when broadening the target audience. With sufficient longitudinal data, questionnaires such as the Psychosis Questionnaire, Brief Version may be amenable for community samples, and may be used to develop risk calculators for youth in the general population. Given the evidence presented here and results from the Outreach and Support in South London and Headspace initiatives , we argue that findings from population-based studies are adequate for guiding policy-making toward further emphasis on public health efforts, although more systematic research is needed in this area.

Destigmatization initiatives for mental illness have been shown to be effective in reducing discrimination and stigma , and broadly accessible mental health programs like Headspace and Jigsaw are promising to make a difference in the field of adolescent mental health . However, the specific efficacy of these programs warrants further study, and caution is advised to not over-pathologize potentially transient occurrence of mental health problems.The prevalence of alcohol, tobacco, and other substance use is higher among gay, bisexual, and other men who have sex with men than in the overall population . Although Hughes and Eliason noted that substance and alcohol use have declined in lesbian, gay, bisexual, and transgender populations, the prevalence of heavy alcohol and substance use remains high among younger lesbians and gay men, and in some cases older lesbians and gay men. Marginalization on the basis of sexual orientation increases the risk for problematic substance use. For example, GBM men were approximately one and half times more likely to have reported being diagnosed with a substance use disorder during their lifetime than heterosexual men , and one and a half times more likely to have been dependent on alcohol or other substances in the past year . GBM also have higher rates of mental health issues than their heterosexual counterparts . In a review of 10 studies, Meyer found that gay men were twice as likely to have experienced a mental disorder during their lives as heterosexual men. More specifically, gay men were approximately two and a half times more likely to have reported a mood disorder or an anxiety disorder than heterosexual men. A review by King and colleagues found that lesbian, gay, and bisexual individuals were more than twice as likely as heterosexuals to attempt suicide over their lifetime and one and a half times more likely to experience depression and anxiety disorders in the past year,vertical grow rack as well as over their lifetime.Few Canadian studies have explored population-based estimates for mental health outcomes among GBM. In one cross-sectional study of Canadian gay/“homosexual” and bisexual men using 2003 Canadian Community Health Survey data, Brennan and colleagues found participants were nearly three times as likely to report a mood or anxiety disorder than heterosexual men. Pakula & Shoveller conducted a more recent cross-sectional analysis that used 2007–2008 Canadian Community Health Survey data and found again that GBM were 3.5 times more likely to report a mood disorder compared with heterosexual males. These analyses used government-run population-based study data, which may limit self-disclosure of sexual minority status, and further relied on a single identity variable to measure sexual orientation, which ignores same-sex sexual behaviors. There is an inextricable yet varied relationship between an individual’s mental health and substance use. Substance use may lead to poorer mental health or, inversely, poor mental health may lead to increased substance use . A variety of substances have been shown to be associated with negative mental health events or symptoms. For example, Clatts, Goldsamt, and Li found that a third of young MSM who used club drugs on a regular basis reported having attempted suicide, and almost half of those who had attempted suicide, did so multiple times over their lifetime. They also found that more than half of regular club drugs users had high levels of depressive symptoms. McKirnan and colleagues found that GBM who showed signs of depression were nearly twice as likely to smoke. Stall and colleagues identified a “dose-response” relationship between self-rated mental well being and alcohol related problems: GBM who self-rated their mental well-being as low were approximately three times more likely to have alcohol related problems and those who rated it as moderate were nearly twice as likely to have alcohol related problems. Respondents who scored as depressed were also one and half times more likely to report using multiple drugs and nearly twice as likely to report weekly drug use.

Syndemics [clusters of mutually reinforcing epidemics that interact with one another to make overall burden of disease within a population worse ] has been used in research with GBM to explain how various psychosocial variables such as poly drug use, mental health conditions, and intimate partner violence increase the likelihood of acquiring HIV . However, nearly all of these studies have relied on convenience samples through online and venue-based recruitment; thus, they may not be representative of the larger underlying population of GBM. In order to address issues of representativeness and limitations of non-probability sampling in past research with GBM, we used respondent-driven sampling to estimate population parameters that are more representative than convenience samples . RDS is a type of chain-referral research technique in which participants are asked to recruit individuals from within their social networks in successive waves, and estimates population parameters using measures of network size and recruitment homophily. By utilizing RDS we sought to produce a more representative sample of the GBM population in Metro Vancouver in order to determine the prevalence of mental health issues and substance use as well as the association between these factors.We analyzed cross-sectional data from participants enrolled in the Momentum Health Study, a longitudinal bio-behavioral prospective cohort study of HIV-positive and HIV-negative GBM in Metro Vancouver, Canada. The overall aim of this study was to examine the impact of a biomedical intervention—increased access to highly active antiretroviral therapy for HIV— on HIV risk behaviors among GBM. The present analysis utilized data collected from participants’ first study visit that occurred between February 2012 and February 2014. We used RDS to recruit GBM in the Greater Vancouver area . Initial seeds were selected in person through partnerships with community agencies or online through advertisements on GBM socio-sexual networking mobile apps or websites . These seeds were then provided with up to six vouchers to recruit other GBM they knew. All participants were screened for eligibility and provided written informed consent at the in-person study office in downtown Vancouver. A computer-assisted, self-administrated questionnaire was used to collect socio-demographic, psychosocial, and behavioral variables. Subsequently, a nurse-administered structured interview collected information on history of mental health and substance dependence diagnosis and treatment, and participants provided blood samples to test for HIV and other sexually transmitted infections . Participants received a $50 honorarium for completing the study protocol and an additional $10 for each eligible GBM they recruited into the study. All project investigators’ institutional Research Ethics Boards granted ethical approval. Moore and colleagues have published additional detail on the Momentum Health Study protocol.Independent variables included socio-demographics, sexual behaviors, substance use behaviors, Alcohol Use Disorders Identification Test categorical scores , and the Hospital Anxiety and Depression Scale categorical scores of anxious and depressive symptoms . Socio-demographic characteristics include: age, sexual identity , ethnicity , immigration status , residence , highest formal education attained, current student status, annual income, being out as gay, HIV serostatus, and current regular partnership status. Sexual behaviors included engaged in sex work in the past 6 months and number of male anal sex partners in the past 6 months. Participants reported whether they had used a variety of substances in the past six months: cigarettes, cannabis, erectile dysfunction drugs, poppers , steroids , cocaine, ecstasy, ketamine, gamma-hydroxybutyrate , hallucinogens , crystal methamphetamine , crack, other stimulants , heroin, morphine, other opioids , benzodiazepines, and other prescription drugs .

Rates have remained at least 2.5 times higher among males since 2016 . This is among the first national investigations to examine reasons for fentanyl exposure in a nuanced manner. With respect to route of administration, dermal use decreased, and injection and inhalation in particular increased. Inhalation not only increased over four-fold, but this route was a risk factor for patients experiencing a major effect or death. This is the first national report on the increase in inhalation as a route of illicit fentanyl use. These results are difficult to compare to various other studies that queried route of administration but only reported injecting behavior . In addition, a limitation of Poison Control data is that we often cannot differentiate types of use that constitute inhalation; specifically, we cannot determine whether the patients insufflated, i.e., snorted, or smoked the substance. Our results appear to add to a national cross-sectional study of fentanyl-related deaths in 2016 which found evidence for snorting and smoking the drug in 52.4% and 17.9% of cases, respectively . A recent study in San Francisco found that there was a shift between injecting heroin to smoking fentanyl . This shift appeared to be largely rooted in harm reduction behavior; e.g., avoiding injection related risks of skin and soft tissue infections. Further, injection is associated with increased risk of overdose , although in our multi-variable model, injection only approached significance as a risk factor for a major adverse outcome or death. Deaths involving opioids as recorded by the State Unintentional Drug Overdose Reporting System in the first half of 2019 suggest that among deaths with a reported specific route of administration, injection was most common, followed by ingestion , snorting/sniffing , and smoking . Indeed, snorting or smoking fentanyl is less common than injecting , but these methods appear to be becoming more prevalent among those who want to avoid injection or its associated risks . As such,how to cure cannabis research needs to continue to monitor shifts in route of administration as well as real or perceived changes in risk related to route.

Many Poison Control studies that examine drug exposures combine “abuse” and misuse into a single category, but we chose not to aggregate these reasons, which resulted in a more nuanced analysis. The proportion of cases involving “abuse” increased over time and represented the majority of cases in 2021. “Abuse” was also a major risk factor for patients experiencing a major effect or death. Misuse, which implies improper use of a legitimate medication, slightly decreased over time, and was actually inversely associated with patients experiencing a major effect or death. We believe this suggests higher call volume indicating use of illicitly manufactured fentanyl as opposed to use of pharmaceutical product. These results demonstrate the complexity of reasons for use which cannot be delineated in other datasets. Also, with respect to reasons for use, suspected suicide attempts decreased, although these cases were associated with higher risk of a major effect or death, possibly due to intentional high doses. Therapeutic error and adverse reactions decreased which we believe suggests stricter or more careful medical oversight of prescribed fentanyl in recent years. With regard to polydrug use, the proportion of cases involving methamphetamine and cocaine increased from 669.0% and 374.0%, respectively. This corroborates literature suggesting that co-use of fentanyl with stimulants is becoming more common , so much that it has been suggested that co-use of fentanyl and stimulants is now the “fourth wave” of the opioid overdose crisis . Despite increased co-use of methamphetamine, we found that this was actually a protective factor against experiencing a major adverse effect or death. The extent to which the drugs were directly combined, used en tandem, or merely used within the same day, is unknown. Given that some people use methamphetamine in attempt to prevent or reverse effects of opioids or other depressants and others use in attempt to alleviate opioid withdrawal , more research is needed to determine contexts of such co-use in relation to severity of overdose risk. While the proportion of patients co-using heroin increased, we found that co-use of prescription opioids decreased.

This finding adds to findings from mortality data which suggests that while deaths involving both prescription opioids and synthetic opioids increased from 2013 to 2017, deaths then leveled off from 2017 to 2019 . This decrease may be indicative of the decline of the “first wave” of the opioid crisis which was largely driven by prescription opioid use . Further, nationally, non-medical prescription opioid use and misuse has also been decreasing in the US . Although recent studies have found increasing rates of benzodiazepine use being involved in fentanyl-related deaths , we found that co-use of benzodiazepines actually decreased. A recent finding of a serious rise in seizures of counterfeit pills containing fentanyl highlights concern about unbeknownst co-use. The highest proportion of exposures occurred in the West, which is in contrast with other studies finding that most related deaths have occurred in the Northeast . With regard to the origin of calls, the proportion of calls to Poison Control centers increased from hospital centers and the proportion of calls made “on site,” typically referring to where the poisoning occurred, decreased. This suggests that it is primarily medical staff that call PCCs regarding fentanyl exposures, not patients or their caretakers. This perhaps demonstrates that while 911 emergency services are often called to respond to fentanyl overdoses, the public rarely calls PCCs for such cases. We also found that on site cases were less likely to experience a major outcome or death, although SUDORS data from the first half of 2019 suggest that the majority of fentanyl-related deaths occur at the decedent’s home followed by someone else’s home . Therefore, on site calls appear to be lacking using these data so more research is needed to focus on circumstances of nonfatal overdoses that occur in homes. The increase in poisonings found in this study highlight the rising risk environment due to illicitly manufactured fentanyl and point to the need for better prevention efforts. Improved drug supply surveillance is needed to better elucidate exposure risk and this could include crime lab data , or data from the High Intensity Drug Trafficking Areas Performance Monitoring Program .

The goal is timely data that can serve as an early warning system. Likewise, PCC data, with potentially timelier outcome data, can complement mortality data and aid in surveillance efforts. Drug checking for fentanyl, an intimate form of drug surveillance, is being explored to reduce the risk imposed by fentanyl . Further, wider distribution of naloxone is needed for more rapid response to fentanyl related overdose. For better household coverage, the US Food and Drug Administration is working on over-the-counter status for naloxone . We do not know definitively which cases involved prescribed, unprescribed, and/or illicitly manufactured fentanyl, although misuse tends to be associated with prescribed fentanyl . We did not present data on form of fentanyl reportedly used as this variable was missing for 64% of cases. However, results from a sub-analysis do indicate that 87.7% of patients who reported dermal use used fentanyl in patch form, suggesting that the vast majority of dermal use was in fact via patches. These data rely on caller or other contact information which may or may not include the patient. Some cases may rely on secondhand reporting, though this is not likely to have changed significantly over time and unlikely to have significantly biased trend estimates. Toxicology testing was not always conducted to confirm exposure to fentanyl or its analogs. Relatedly, given that fentanyl is a common adulterant in or replacement for drugs such as heroin, fentanyl exposures were likely underreported when people were unknowingly exposed. In fact, reporting of poisonings related to fentanyl is relatively rare compared to mortality studies. This is because calls to Poison Control are dependent on a patient or medical professional calling to report the poisoning or to ask for medical advice to treat a case. As such, these data are not generalizable to all poisonings; they are however, useful in informing other national studies. Exposures are also not generalizable to use or nonfatal overdose in the population as most cases reported involve adverse effects related to exposure and reporting exposures to PCCs is only voluntary. Finally,trimming cannabis it is possible for medical outcomes to be misclassified, but in at least three quarters of cases involving fentanyl, exposure information is obtained from medical facilities that monitor patients and PCC staff follows up on cases to obtain the most accurate information possible before closing a case .However, HIV-associated neurocognitive disorders remain highly prevalent, particularly in milder forms and even in PWH on suppressive ART . The most prominent neurocognitive deficits in the ART era tend to be observed in the domains of learning and executive function, though many PWH are also impaired in delayed recall, processing speed, working memory, and motor skills . Significant heterogeneity exists with regard to severity and profile of neurocognitive impairment in PWH and this is also reflected in neuroimaging and neuropathological studies. One explanation for this heterogeneity is that there may be subtypes of HAND with distinct underlying mechanisms, risk factors,and consequences. Identifying sub-types of HAND may improve our understanding of the etiology, nature, course, and treatment of HAND.

Multiple factors contribute to NCI in virally suppressed PWH , including viral persistence in the CNS , cellular and epigenetic factors , ART toxicity , comorbidities, and coinfections. A unifying factor across these mechanisms is chronic immune activation and inflammation. ART reduces, but does not normalize immune activation, in most PWH. Soluble biomarkers of immune activation and inflammation are elevated in PWH despite viral suppression and in PWH with HAND . This persistent level of low-grade chronic immune activation and inflammation, which induces neuroinflammation and neurovascular complications , is considered a key element of pathogenesis of NCI in ART-treated PWH. Chronic inflammation in ART-treated PWH can also lead to endothelial dysfunction , which is a key mechanism underlying the development of atherosclerosis and subsequent cardiovascular disease . During the immune response to infection, pro-inflammatory cytokines released from immune cells activate endothelial cells, triggering the expression of cellular adhesion molecules . Cell adhesion molecules interact with other molecules to promote the recruitment, adherence, and migration of leukocytes to and across the vascular endothelium . Chronic and sustained activation of immune and endothelial cells leads to increased adhesion molecule expression, vascular permeability, and immune cell migration, which further propogates the inflammatory response and can lead to endothelial dysfunction or damage . CVD is among the most prevalent of age-associated non-infectious conditions in PWH , may occur at earlier ages relative to age-matched people without HIV , and is further exacerbated by the increased incidence of traditional and non-traditional risk factors . In the general population, CVD, particularly in mid-life, is among the strongest risk factors for vascular, Alzheimer’s, and mixed dementia types . Studies of PWH, including those who are virally suppressed, have found adverse independent effects of CVD and/or its risk factors on NCI , brain inflammation, vascular abnormalities, and neural injury . As the HIV population grows older, CVD and its risk factors are increasingly recognized for their role in HAND. Recent studies have also found evidence of endothelial dysfunction and blood-brain barrier impairment in ART-treated and virally suppressed PWH . The BBB, composed of specialized endothelial cells and tight junctions and surrounded by a basement membrane, pericytes, astrocytes, microglia and neurons , is a primary target of HIV-associated neural injury and a central neuropathological factor underlying HAND . The BBB is also altered by CVD, further contributing to dysfunction . Increased BBB permeability is a key mechanism in cognitive impairment due to cerebrovascular disease, which is similar to HAND in terms of risk factors and often has similar underlying pathological processes given evidence of overlapping neuroimaging and neurocognitive phenotypes . Cerebrovascular-related cognitive deficits depend on the location and characteristics of the particular lesion, though these lesions are often distributed throughout fronto-subcortical and fronto-parietal white matter tracts important for processing speed and executive functioning . These domains are also linked to subclinical CVD and atherosclerosis in PWH , and similar patterns of diffuse white matter pathology are found in HAND .

This pattern highlighting the effectiveness of TES was evident across diverse groups of patients, including those with stimulant, cannabis and alcohol use disorders , those with and without criminal justice involvement those with and without Internet access , and across both males and females and diverse racial and ethnic groups . TES was also found to have promising cost-effectiveness . This CTN trial built on a prior body of NIDA-funded single site trials showing, for example, that adding TES to buprenorphine treatment produces synergistic treatment effects; that replacing part of counselor-delivered treatment with TES treatment in methadone treatment systems greatly improves patients’ treatment outcomes, and that TES offered to incarcerated individuals can produce comparable treatment outcomes to those produced by exclusively clinician-delivered care . By conducting a national, highly rigorous multi-site trial, the CTN study was well-poised to demonstrate the safety and effectiveness of the TES digital intervention when reviewed by the FDA, leading to the very first FDA-authorized prescription digital therapeutic in the U.S. . This reflects a new category of FDA-regulated devices and allows for digital therapeutics to be prescribed by clinicians, in a manner similar to FDA-approved medications. This is a compelling example of how CTN research can change the landscape of care to scale-up access to evidence-based treatments for SUDs. This work led to several ancillary CTN studies focused on enhancing TES to be modified for American Indians and Alaskan Natives . And, several mobile digital therapeutics will be included in a new national CTN trial that will test strategies to improve treatment retention in medication treatment for OUD and to improve outcomes among individuals who are stabilized on OUD medications but wish to discontinue such medications .

Although treatments for SUDs,cannabis grow room including OUD, have been shown to be life-saving , many communities across the nation are challenged by not having sufficient clinician capacity to conduct universal screening and medication induction and maintenance to the large population who may need it. This is particularly challenging in rural contexts which have lower capacity for evidence-based opioid treatment, including fewer waivered buprenorphine prescribers, behavioral health clinicians, and opioid treatment programs and often lack of a widespread public transportation system. To address this challenge, the CTN is launching a large multi-site trial to evaluate the effectiveness of a telehealth model of care for the medication treatment of OUD , designed to help ensure sufficient and sustainable capacity to offer evidence-based opioid treatment in rural communities . This cluster-randomized, comparative effectiveness trial will examine the utility of adding tele-MOUD to outpatient MOUD treatment compared to outpatient MOUD treatment alone in rural areas highly impacted by the U.S. opioid crisis. Tele-MOUD will flexibly offer patients remote access to a core team of OUD experts who can assess and prescribe medications to individuals with OUD, provide therapy, and/or provide remote urine and/or saliva drug testing. Another new primary care-based CTN trial , which seeks to identify an effective strategy to address unhealthy opioid use and prevent escalation to an opioid use disorder, will also offer remote telecounseling to participants to enhance onsite care centrally led by a nurse care manager. The collective learning from this research will inform innovative models that can scale access to a suite of evidence-based treatment for OUD in high need, low resource settings. The first of these studies developed and evaluated the ability of a wrist-worn sensor suite to detect cocaine use . This work builds on prior promising work demonstrating that a chest band with electrodes can detect cocaine use via a computational model that uses heart rate and physical activity data .

The present study seeks to evaluate whether similar cocaine detection algorithms will work, that have been modified for use with sensor data collected via a less obtrusive, more user-friendly smartwatch that can be worn in daily life. Data from the smartwatch is compared to chest band data as well as EMA reports of cocaine use of cocaine use. Cocaine use is often measured via self-report, which can be inaccurate, and/or use is measured via urine drug tests which can be intrusive and may not capture the temporal granularity of cocaine use patterns . If smartwatch sensing is determined to be an acceptable and accurate way to measure cocaine use, it may offer rich information about the precise timing and duration of use events and could allow us to glean new insights into contextual factors that may serve as triggers for use events. Additionally, detecting cocaine use with greater precision may enhance our outcomes measurement in clinical trials that evaluate potential therapeutics for cocaine use disorder. The second of these CTN studies is, to our knowledge, the first study to employ passive mobile sensing, social media data, and active responses to queries on mobile devices using EMA to obtain moment-by-moment quantification of individual-level data that may lead to opioid use events, medication non-adherence and/or MOUD treatment dropout/retention in a population of persons with OUD in buprenorphine treatment. In this study, participants are asked to wear a smartwatch and carry a smartphone continuously for a period of 12 weeks. The smartwatch passively collects data regarding location and distance traveled, physical activity , sleep, and heart rate. Participants are also prompted to respond to questions through a smartphone multiple times per day. Questions assess sleep, stress, pain severity, pain interference, pain catastrophizing, craving, withdrawal, substance use risk context, mood, location, substance use, self-regulation, and MOUD adherence. In addition to the EMA prompts, individuals are asked to self-initiate EMAs if substance use occurred.

App usage, audio/conversation, call/text, GPS, screen on/off, phone lock/unlock, phone notification information, Wi-Fi & Bluetooth logs, sleep, ambient light, and proximity are passively collected via smartphone. Participants are also asked if they are willing to share their social media data from any social media platforms they may use . Sharing social media data is an optional component of study participation. The primary objective of the study is to evaluate the feasibility of utilizing digital health technology with OUD patients as measured by a 12-week period of continuous assessment using EMA and digital sensing. A secondary objective of this study is to examine the utility of EMA, digital sensing, and social media data in predicting OUD treatment retention and buprenorphine medication adherence. Overall, this line of research may inform which subset of digitally-derived data may be most useful to employ as part of outcome measurement in future clinical trials research. Digital data that capture the richness of clinical status and clinically trajectories as individuals go about their daily lives may greatly complement and enhance the learning from standardized, clinical outcomes assessment. And predicting OUD treatment retention and medication adherence via continuous digital assessments may be used to identify early those participants who show signs of non-adherence and trigger additional intervention to prevent ultimate non-response to treatment. In addition to the CTN-0084-A2 study referenced above which includes social media data as part of a broader set of digitally-derived data, the CTN supports a trial that centrally evaluates the relative utility of various social media platforms in recruiting a national sample from a hard-to-reach population. Specifically, this trial compares the relative effectiveness of using social media sites vs. online informational sites vs. online dating sites to promote HIV self-testing and seamless linkage to pre-exposure prophylaxis medication among young , racial/ethnic minority,grow trays high-risk men who have sex with men . In this study, individuals in the targeted sample who click on culturally tailored study advertisements and who provide online consent will be offered a free HIV self-test kit to be discreetly sent to their home with seamless linkage to PrEP for those who test HIV-negative, and linkage to HIV care resources for those who test positive. Among other outcomes, the primary outcome is the monthly rate by promotional platform . The modifying role of substance use on observed outcomes will also be examined. Online recruitment strategies allow for targeted recruitment of select audiences. The CTN-0083 study will target recruitment in the states that have hard-to-reach, high risk populations and limited availability of risk reduction services . This study illustrates how a targeted national sample can be recruited for clinical trials participation and how all intervention delivery and data collection in a clinical trial can be conducted remotely online.

This manuscript provides an overview of the breadth and impact of research conducted within the U.S. National Drug Abuse Treatment Clinical Trials Network in the realm of digital health. This work has included the CTN’s efforts to systematically embed digital screeners for SUDs into general medical settings to increase the diagnosis and treatment of SUDs across the nation. This work has also included a pivotal multi-site clinical trial conducted on the CTN platform, whose data led to the very first “prescription digital therapeutic” authorized by the U.S. Food and Drug Administration for the treatment of SUDs. Further CTN research includes the study of telehealth to increase capacity for science-based SUD treatment in rural and under-resourced communities. In addition, the CTN has supported an assessment of the feasibility of detecting cocaine-taking behavior via smartwatch sensing. The CTN has also supported the conduct of clinical trials entirely online . Further, the CTN is conducting innovative work focused on the use of digital health technologies and data analytics to identify digital biomarkers and understand the clinical trajectories of individuals with OUD in buprenorphine medication treatment for OUD. Given its unique national research infrastructure and access to a broad array of community and healthcare partners, the CTN is uniquely poised to accelerate the scope and impact of its work applying digital health to the assessment and treatment of SUDs. Among these opportunities, the CTN is positioned to evaluate the role of digital technologies in SUD care transitions. For example, offering persons with SUDs access to a digital therapeutic and/or telehealth when they transition from a period of incarceration, hospitalization, or inpatient SUD care to the community would provide them with 24/7 access to therapeutic support as they reintegrate into the community and/or community-based care. Digital tools may also be offered directly to individuals recruited online who are not engaged, and do not wish to engage in SUD care within the health care system. Given that only about 10% of persons with SUDs are engaged in treatment, there is tremendous opportunity to creatively use digital technology to provide the other 90% with evidence-based SUD resources . The CTN is optimally poised to conduct national implementation science trials and/or hybrid implementation-effectiveness trials to evaluate optimal strategies to implement and sustain digitally-enhanced models of care. Such trials could integrate the various digital health tools and approaches that the CTN has previously studied in separate studies to instead embed a suite of complementary digital tools spanning an entire model of care within an integrated implementation strategy. That is, a digitally-enhanced model of care could include digital screeners and assessments in medical settings, linkage to electronic clinical decision support tools to enhance providers’ ability to deliver state-of-the-science care, as well as provision of digital therapeutics that are available directly to patients to ensure evidence-based care is available to them anytime and anywhere and can complement the care they receive in the healthcare sector. Importantly, digital therapeutics offered to patients do not need to reflect static models of behavioral treatment that work exactly the same way with every end user. Rather, these tools can be adaptive and flexibly offer evidence-based therapeutic resources to individuals that are responsive to their changing clinical needs, preferences, and goals. There is tremendous opportunity to integrate the science of digital assessment and digital therapeutics for SUDs to help us understand when individuals may be most receptive to health promotion interventions. They can, in turn, inform optimal delivery of “Just-in-Time Adaptive Interventions” or in-the-moment interventions for SUDs that provide the right type/amount of therapeutic support at the right time . The large and diverse samples that can be recruited within the CTN offer many opportunities to conduct novel experimental approaches to systematically investigate who would benefit from which intervention and when , as well as to apply novel statistical machine learning methods to personalize SUD interventions at the individual level .