Two hospitals could insert central venous catheters and gain intraosseous access, which is important in shock management. In terms of resources, only two of the four had a separate triage area for emergency patients. All four hospitals had an isolation room, an obstetric/gynecologic area, and a decontamination room. We surveyed hospitals on their reasons for non-compliance with signal functions, asking them to choose from among five possible causal factors. The first was training issues, taking the form of a lack of education. The second factor was related to the lack of availability of appropriate supplies, equipment, and/ or drugs. The third pertained to management issues, such as the staff being unfamiliar with the functions, and cases where other equivalent procedures could have handled the conditions. The fourth factor was policy issues, referring to cases where the government or the facility itself does not allow for compliance with the signal functions. The fifth factor was designated as “no indication,” meaning that there was no patient group who needed this function. Supplemental Table 4 describes the reasons respondents provided on the survey for each unavailable signal function. Inappropriate supplies/equipment/drugs was the most common reason, as might be expected, and shortage of human resources was another causal factor. One intermediate hospital did not agree with the use of emergency signal functions for sentinel conditions, and answered “no indication” as their reason for non-compliance.It is widely recognized that there is a huge burden caused by trauma and non-communicable diseases in LMICs, where capability for emergency care is believed to be suboptimal.Many studies have tried to assess the state of emergency care in the health facilities of LMICs. Due to the accessibility issue,vertical farming racks most studies examined teaching hospitals located in urban areas. Assessment tools were not standardized and were usually developed by the researchers themselves.

Domains for assessment were usually related to the availability of resources, and functional aspects were surveyed with qualitative measures, if any. To our knowledge, this study is the first to survey urban and rural Myanmar hospitals using ECAT, the newly developed objective tool for assessing emergency care in health facilities. Our study demonstrated that the performance of emergency signal functions in Myanmar hospitals is inadequate, especially in trauma care. Trauma care in LMICs has been regarded as a role for large hospitals, and direct referral to upper-level facilities is a common practice. Burke et al. found that lack of readily accessible equipment for trauma care and shortage of skilled staff were the main reasons for poor quality trauma care in lower-level health facilities in LMICs.Another study pointed out the limited training opportunities for trauma management in LMICs.We found similar obstacles to trauma care in Myanmar hospitals, including the unavailability of items necessary for signal functions. Unlike other LMICs, Myanmar faces a singular geographic and demographic situation. Road conditions are poor. Almost 20 million people live in areas not connected by basic roads. The roads that do exist are unpaved and narrow, contributing to the overall lack of accessibility. The cause of this problem might be found in continuous armed conflicts. Since the independence of Myanmar in 1948, a continuing civil war has devastated the population and infrastructure of the rural areas, which has led to the deterioration of the health status of the country. In areas dominated by violence, residential zones are located away from road access, and the level of medical care is behind the times. Financial support is also lacking.For example, a referral and transport from Matupi Hospital to an adjacent upper-level facility takes as long as 16 hours during rainy seasons due to road damage . In this situation, timely management of patients in a critical condition is virtually impossible, and demands for higher levels of emergency care in basic-level facilities can be raised. Moreover, the results of our study show that some intermediate-level hospitals could not provide resuscitation for critical patients due to the lack of advanced airway management, mechanical ventilators, and defibrillation. Imbalances in the quality of emergency care in both basic- and intermediate-level facilities should be addressed carefully.

However, in Myanmar’s special situation where highway infrastructure is lacking and there are problems with long transport times, the ability to administer emergency medical care at a large hospital should be established based on skilled labor and resources. Ouma et al. emphasized that all countries should reach the international benchmark of more than 80% of their populations living within a two-hour travel time to the nearest hospital.20 Although it cannot be realized in the near future, measures to alleviate accessibility problems can be applied. Thorough gap analyses to address existing challenges in remote regions will be helpful for planning. In this regard, ECAT should be validated to include a time factor, such as the referral time to the nearest upper-level facility. We identified the following urgent issues in need of remediation: 1) improvement of trauma-related signal functions in basic-level facilities; 2) improvement of trauma and critical care-related signal functions in intermediate level facilities; and 3) implementation of a comprehensive nationwide survey to uncover emergency care deficiencies in rural areas, with emphasis on the time required for referral to higher-level facilities. Our suggestions to address the issues identified in our study can be summarized as relating to the reinforcement of infrastructure and human resources within each level of facility. In addition, prehospital care and care during inter-facility transportation should receive special attention considering the unique context of Myanmar, with its dispersed residences and extremely long transport times. There has been an effort to establish formal EM in Myanmar. In 2014, the Emergency Medicine Postgraduate Diploma course provided by Australia graduated Myanmar medical officers.8 These emergency providers will be an imperative asset to setting up a modern emergency medical care delivery system in Myanmar, although most of them will practice in advanced-level facilities. Measures to build the capacity to respond to medical emergencies in rural areas should be pursued in Myanmar. There have already been efforts to improve first-aid skills among local healthcare workers who have a high degree of understanding of the local context, and to employ them as community emergency responders.

These local healthcare workers are well informed about the population, hygiene, disease distribution, and the geographical and cultural characteristics of the area; thus, they are able to provide essential first aid and find appropriate health facilities for referrals. This practice has been expanded to the concept of out-of-hospital emergency care . It refers to a wide range of emergency treatments, from the process of recognizing an emergent care situation, to the initial emergency treatments outside the hospital, and transport to the hospital.The establishment of OHEC has played a role particularly in LMICs by reducing mortality rates by 80%, especially in trauma cases.Since 2000, several organizations have implemented the trauma training course program with non-physician clinicians in Eastern Myanmar.The program comprises various skills for carrying out the initial treatment of trauma, taught through simple simulations and feedback. The findings indicated that survival rates improved significantly among major trauma patients following the implementation of this program. We recognize that some skills covered in the TTC, such as surgical airway management, would be relatively dangerous for health workers to perform in the field, and believe that development and implementation of a training program focused on the operation of emergency signal functions would be more practical for the rural context. Those who are trained in this program could act as prehospital emergency care providers, and also aid basic-level facilities to fill the functional gaps identified in this study. In addition to the above suggestions, a national or provincial strategic plan for reinforcing emergency care in rural areas of Myanmar should be established and implemented. Following a thorough investigational survey,vertical racking system essential resources for each level of health facility should be supplemented. Public education to recognize emergency conditions is another area to be strengthened. In many LMICs, including Myanmar, folk remedies are still commonly attempted before people seek medical attention, especially in the field of obstetrics and gynecology.Recognizing the need for emergency care is crucial because it is the first step leading the patient to the emergency medical care system. Community education should play an important role in preventing delays in the detection of emergency situations.Traditional medicine providers have been the first to participate in this training thus far, and it has been reported to be effective.Point-of-care ultrasound has emerged as an essential diagnostic tool in emergency medicine .Several studies have demonstrated that a structured curriculum is both feasible and effective in training emergency physicians to obtain and accurately interpret images with test characteristics approaching or even exceeding those of dedicated radiology-performed scans.However, less is known about the penetrance of POCUS into daily EP practice.

The emergency department poses unique challenges to implementation of diagnostic POCUS not present in other specialties with broad adoption of POCUS such as cardiology, critical care, and obstetrics: 1) the time spent with an individual patient is limited compared to other specialties; 2) ED settings vary dramatically between academic, community, rural, and urban practices, and each environment has its own unique challenges with respect to availability of POCUS and training of clinicians in ultrasound and 3) the breadth of POCUS applications in the ED is considerably greater than in other specialties. Guidelines from the American College of Emergency Physicians endorse 12 core applications. The degree of experience necessary to obtain competency in image acquisition and interpretation, while not clear, appears to be highly variable between these applications.As a result, few EPs maintain competency in all 12 applications without further postgraduate fellowship training. This leads to a general reluctance to perform and rely on some POCUS exams, as EPs question the need to maintain competency in certain applications.9 Indeed, a survey of EPs in California found that most EPs do not use POCUS, and that EPs in academic environments use POCUS more regularly than their community counterparts.The challenges posed above apply both to established EPs and residents in training who are establishing practice patterns. Despite near-universal incorporation of ultrasound into resident training,a survey of recent residency graduates found limited use in daily clinical practice.This suggests that dedicated ultrasound training in most EM residency programs in North America progresses residents to the intermediate level, where they are able to effectively acquire and interpret images, but not to the level of the expert who is able to seamlessly incorporate the procedural skill into practice. We hypothesized that a number of perceived barriers may be leading to a gap in deliberate, on-shift practice, which is preventing trainees from advancing to expert levels. The goal of this study was to assess and address relevant barriers to POCUS performed on shift by residents at a single, three-year EM residency program. As such, the study had two phases. We first performed a voluntary residency-wide survey to address perceived attitudes and barriers to on-shift use of POCUS. Next we performed an intervention to address the primary barrier, namely the perceived lack of a proper charting and reporting policy.We conducted the study at an ED with an annual volume of 65,000 patients, which hosts a three-year EM residency program. The residency trains a total of 36 residents, with 12 residents per year. The study site uses the HealthLink/ EPIC electronic medical record , and all point-of-care ultrasounds are wirelessly uploaded to a middleware product . Quality assurance of all scans submitted for review is performed by ultrasound fellowship-trained EPs who rotate on a weekly basis. At the time of study performance, ultrasound training consisted of a four-hour introductory ultrasound course at the start of residency training, a four-week mandatory ultrasound rotation during the first year, and quarterly didactics with simulation and hands-on training during regularly scheduled mandatory conference. In addition, ultrasound fellowship trained faculty offered three-hour sessions, biweekly, which consisted of didactics, image review, and bedside scanning. These sessions were mandatory for the first-year resident who was on the dedicated POCUS rotation, as well as two second and third-year residents who were on a dedicated month of community ED practice. The study was performed as part of ongoing quality improvement program, not requiring institutional review board review at the study institution.At the beginning of the study, a departmental best practice, systematic, ultrasound documentation workflow was disseminated to faculty attending physicians. This workflow included saving ultrasound examinations performed or supervised by a faculty member credentialed in the relevant application.

For each threshold number of visits in the preceding six months, the unadjusted risk of return visit was more than double among frequent visitors as compared to non-frequent visitors. The remainder of the analysis uses two or more previous visits as the threshold defining frequent visitor, unless otherwise specified. This retrospective analysis of almost seven million patient visits found that recent previous ED visits was the strongest predictor of an ED return visit. This finding held true across multiple cutoffs defining frequent use, and also under both univariate analysis and a multivariate model including patient, visit, hospital, and county characteristics. Along with recent frequent use, public insurance and three diagnoses were associated with an increased risk of a return visit. This suggests that our understanding of short-term revisits could be informed by considering frequency of ED use. A parallel thread in the literature has investigated frequent users and interventions designed to decrease ED use.Previous studies have evaluated predictors of ED revisit using patient-level data such as age, sex, race, insurance status, and diagnosis at initial ED visit, as well as hospital-level data. Surprisingly, the relationship between frequent ED use and risk of revisit after discharge is poorly characterized.Further, there is no consensus on what defines “frequent,” with definitions ranging from 2–12 visits per year.We had the striking finding that even one previous visit increased risk of return by a clinically-significant margin. This finding held true even when accounting for patient, visit, hospital, and community characteristics. Our definition focused on visits within the previous six months because other work has shown that episodes of frequent ED use are usually self-limited,4×4 grow tray which suggests that the recent past is more relevant to current health and risk of short-term return visit.

A second, related finding is that the threshold used to define frequent visitors is arbitrary with respect to risk of return visit. In the hope of informing the wide range in the literature on the number of visits or length of time used to define frequent users, we considered our definition of frequent user in relation to risk of return visit. We had the surp finding that any number of previous visits used to define frequent vs non-frequent ED users predicted an increased risk of revisit. Given that the reason to label certain patients as frequent visitors is often in order to identify them for interventions, future work may consider an outcome-based definition of frequent users and define the term “frequent” with a qualifier – eg, with respect to propensity to revisit after a visit, risk of becoming a persistent frequent user, or risk of death. As with existing literature, we transformed the number of previous visits from a continuous variable to a binary one. This has the disadvantage of losing some information, but is standard in the literature regarding frequent ED use, and can easily be applied in the midst of clinical practice.Our sensitivity analysis demonstrated that any threshold was significantly associated with return visits, suggesting that knowing whether a patient had four vs three previous visits would provide marginally more information than simply knowing the patient had more than two previous ED visits. As with the definition of frequent user, the time to return visit defining a return visit is somewhat arbitrary. While the risk of return visit is highest on the first day following the ED visit, the risk gradually decreases and, as found previously by Rising et al., there is no clear timeline that defines a return visit.This finding may suggest something other than inadequate care at the index visit is the driving factor for most short-term revisits, and that both frequent use and revisits may simply be proxies for certain patients with increased healthcare-seeking behavior. Further complicating this issue is that patients may be instructed to return to the ED for a re-evaluation.

Thus, an ED in a setting with limited outpatient resources might appear to give poor care as measured by revisits when in fact it serves to provide followup care that patients otherwise would not obtain. Despite the variation in the literature and thus our broad range of models, we consistently found that the strongest predictor of a revisit is a high number of previous visits. This finding held true in our sensitivity analysis using different thresholds for number of previous visits and also days after index visit. The observation that previous visits predicts future visits may seem obvious or mechanical, but it does not necessarily follow that a patient with one or two visits in the prior six months would be at double the risk of a revisit within three days. Further, that this relationship was stronger than any other patient, hospital, or community characteristic is an important finding that has been overlooked in the literature regarding revisits. In fact, it appears that the literature on frequent visitors and the literature regarding revisits have to this point largely functioned in parallel and have not yet begun to inform each other. Whether frequent users are merely frequently-ill people, and whether sicker patients are at increased risk of short-term revisits deserves future research. Likewise, future work should investigate the extent to which patients are frequent users because they received poor care or face limitations in their ability to obtain outpatient resources, the extent to which revisits are avoidable, and the degree to which frequent use persists over time. Understanding the extent to which follow-up with primary care, referrals to specialists, and ability to obtain further evaluation such as advanced imaging, cardiac stress test, or even a wound check is essential to understanding why patients return to the ED. The data for this study were obtained from a single multi-state physician partnership and do not necessarily generalize to other providers or provider groups, or to other populations. However, the sample size was large and spans many cities and rural areas across several states, includes a broad set of hospital owner types, a large range of hospital sizes, and both teaching and non-teaching hospitals. This source of data may lead to a biased sample with respect to patient population, hospital characteristics, and provider characteristics. In particular, the income distribution is narrower than the distribution for the entire U.S., so the patient population could have a lower proportion of low- and high income patients than typical for the U.S.

We addressed these potential sources of bias by controlling for patient demographics, patient insurance, and local income; hospital characteristics including volume and a performance metric, and clinician degree. Second, because not all hospitals within a region were observed, measures of frequent visitors and repeat visits may underestimate the actual numbers of frequent visitors and repeat visits, as patients may have gone to another ED either prior to or after the observed index visit. This limitation is typical of this research,and in this dataset patients were linked across hospitals, although this was limited to the hospitals served by this company. Thus, it is unknown whether patients had an unobserved revisit at another ED, or whether what was considered an index visit actually represented a revisit after an initial visit at another ED. Next, we were unable to distinguish between planned and unplanned return visits. Thus, a patient who is instructed to return for a check over the weekend to ensure their illness is improving, for example, would appear to be a revisit, but this should not imply that their initial treatment was inadequate or inappropriate in any way. Research using administrative datasets, such as HCUP, likewise suffers from this limitation. Finally, as with related research, this study does not identify the extent to which high rates of frequent visits and revisits are driven by patient factors, ED care, or non-ED healthcare resources. This analysis was limited in its ability to examine patient psychosocial attributes or local resources, which are likely to contribute to ED visits and revisits, although we did consider proxies for access to care: patient insurance and community-level factors such as income and number of hospitals in the county. The condition covers a large spectrum of disease, ranging from mild exacerbations with gradual increases in edema to cardiogenic shock. HF affects close to six million people in the United States and increases in prevalence with age.6-11 Currently, the emergency department initiates the evaluation and treatment of over 80% of patients with AHF in the U.S.As the population ages, increasing numbers of patients with HF will present to the ED for evaluation and management. However,greenhouse racking making the correct diagnosis can be challenging due to the broad differential diagnosis associated with presenting symptoms and variations in patient presentations. Over one million patients are admitted for HF in the U.S. and Europe annually.In the U.S. population, people have a 20% risk of developing HF by 40 years of age.HF is more common in males until the age of 65, at which time Brooke Army Medical Center, Department of Emergency Medicine, Fort Sam Houston, Texas University of Texas Southwestern Medical Center, Department of Emergency Medicine, Dallas, Texas Rush University Medical Center, Department of Emergency Medicine, Chicago, Illinois males and females are equally affected.Patients with HF average at least two hospital admissions per year.

Among patients who are admitted with AHF, over 80% have a prior history of HF, referred to as decompensated heart failure.De novo HF is marked by no previous history of HF combined with symptom appearance after an acute event.Mortality in patients with HF can be severe, with up to half of all patients dying within five years of disease diagnosis.Other studies have found that post-hospitalization mortality rates at 30 days, one year, and five years are 10.4%, 22%, and 42.3%, respectively.AHF expenditures approach $39 billion per year, which is expected to almost double by 2030.Normal cardiac physiology is dependent on appropriately functioning ventricular contraction, ventricular wall structural integrity, and valvular competence.At normal functional status, a person’s stroke volume is approximately one milliliter per kilogram for every heartbeat.SV is dependent upon the preload , after load , and contractility . In patients with HF, left ventricular dysfunction can be due to impaired LV contraction and ejection , impaired relaxation and filling , or a combination of both.An alternate way of defining this would be by the effect on ejection fraction . HF with preserved EF refers to patients with an EF > 50%, while HF with reduced EF refers to patients with an EF < 40%. Borderline preserved EF is defined by HF with an EF of 41-50%.The most common form is HF with reduced EF, which is primarily related to a decrease in the functional myocardium .Additional causes include excessive pressure overload from hypertension, valvular incompetence, and cardiotoxic medications. HF with preserved EF occurs due to impaired ventricle relaxation and filling, which accounts for 30-45% of all HF cases. This form of HF results in increased end-systolic and diastolic volumes and pressures and is most commonly associated with chronic hypertension, coronary artery disease, diabetes mellitus, cardiomyopathy, and valvular disease. Both systolic and diastolic HF can present with similar symptoms due to elevated, left-sided intracardiac pressures and pulmonary congestion.Right ventricular failure most commonly results from LV failure. As the right side of the heart fails, increased pressure in the vena caval system elevates pressure in the venous system of the gastrointestinal tract, liver, and extremities, resulting in edema, jugular venous distension, hepatomegaly, bloating, abdominal pain, and nausea.High-output HF is associated with normal or greater-than-normal cardiac output and decreased systemic vascular resistance.The associated decrease in after load reduces arterial blood pressure and also activates neurohormones, which increase salt and water retention. Diseases that may result in high-output HF include anemia, large arteriovenous fistula or multiple small fistulas, severe hepatic or renal disease, hyperthyroidism, beriberi disease, and septic shock.In AHF, peripheral vascular flow and end-organ perfusion decrease, causing the body to compensate by neurohormonal activation , ventricular remodeling, and release of natriuretic peptides. These mechanisms are chronically activated in HF, but worsen during acute exacerbations, resulting in hemodynamic abnormalities leading to further deterioration. Continued progression can result in a critical reduction to end-organ blood flow, leading to severe morbidity and mortality.Patients with HF are classified into one of four classes, primarily determined by daily function, using the New York Heart Association, American College of Cardiology/American Heart Association, or European Society of Cardiology Guidelines .

Past 30-day HSD use at follow-up was significantly lower for intervention patients . While the control group reported no change in HSD use over time , the intervention group reported a significant unadjusted mean reduction of 4.4 days from baseline to follow-up . Among the 47 participants who provided urine samples, those in the intervention group were less likely than controls to test positive for their HSD . A logistic regression analysis for testing HSD positive that controlled self-reported baseline HSD use confirmed that intervention group participants were less likely than those in the control group to test HSD positive at follow-up . In the intent-to-treat linear regression model with multiple imputation of missing values , intervention patients reduced their HSD use an average of 4.5 more days in the past month than did controls, controlling for baseline HSD use, high school graduation, number of children under 18 living with them, and having been sexually assaulted before they were 18 years old. The complete sample regression with the same covariates for the 51 patients with follow-up data produced similar results , with intervention patients reducing their HSD use an average of 5.2 more days than controls . Finally, among the 32 patients in the complete sample who reduced their HSD use by a day or more, 28 patients who reported risky alcohol use reduced that use by an average of 0.3 days and 17 patients who disclosed smoking reduced their tobacco use by an average of 2.5 days . Neither change was significant . In this study of mostly Latino primary care patients of an FQHC, the QUIT brief intervention group reported a 40% decline in mean HSD use, corresponding to an adjusted 4.5-day reduction in reported past month HSD use by 3-month follow-up compared to controls ; there was no compensatory increase in use of alcohol or tobacco. This degree of drug use reduction is meaningful clinically according to norms for reductions in marijuana use in clinical trials . The trial has clinical significance as its findings could apply to 12% of our study clinic patients that screen positive for risky drug use ,drying room and represents significant potential public health impact for the 20 million risky drug users in the US if replicated in other clinic populations , 2012; U.S.

Department of Health and Human Services Office of the Surgeon General, 2016. The findings are important given the limited number of randomized trials of screening and brief intervention for risky drug use in primary care, and notable in that the findings affirm the positive findings of the QUIT trial. Some distinctive characteristics of the QUIT intervention that may contribute to its greater success than other brief intervention protocols designed to address risky drug use in primary care include: use of primary care clinicians to deliver brief advice messages about drug use; regular weekly “learning community” meetings among health coaches and the study team; incorporation of quality of life issues patients spontaneously raised as barriers to drug use reduction into telephone coaching sessions; embedding of drug use consent and patient assessment questions within a larger behavioral health paradigm to conceal the study’s drug focus and minimize potential contamination of the control group; and patient self-administered assessment of drug use on tablet computers. The original QUIT study, showed a significant reduction in HSD in 30-day risky drug use , 3.5 day reduction in the completer analysis in intervention compared to control patients . The positive outcomes in all of these different clinics bolstered by positive outcomes from this pilot replication suggest that QUIT may prove effective and implementable in a variety of settings and across a variety of patient demographics. Limitations of the study include: generalizability of the sample to other Latino populations, potential for social desirability bias to influence the primary outcome of self-reported drug use reduction which we tried to minimize by patients’ self-administration of survey items on a tablet computer, loss to follow-up, and small sample size which limits subgroup analysis. Over three million refugees have been resettled in the United States since Congress passed the Refugee Act of 1980.1 In 2015, there were nearly 70,000 new refugee arrivals, representing 69 different countries.1 Refugees undergo predeparture health screening prior to arrival in the U.S., and are typically seen by a physician for an evaluation shortly after arrival.

Refugees are resettled in areas with designated resettlement agencies that assist them with time-limited cash assistance, enrollment in temporary health coverage, and employment options. Refugees are initially granted six to eight months of dedicated Refugee Medical Assistance, which is roughly equivalent to services provided by a state’s Medicaid program.Following this period, refugees are subject to the standard eligibility requirements of Medicaid.3 It is important to highlight the differences between a refugee, an asylum seeker and a migrant, as this study focuses specifically on refugees. A refugee is an individual who has been forced to leave his or her home country due to fear of persecution based on race, religion, nationality, membership in a social group, or policital opinion. Refugees undergo robust background checks and screening prior to receiving designated refugee status. They are relocated only after undergoing this screening process, and have legal protection under the Refugee Act of 1980 given their status as a refugee. An asylum seeker, on the other hand, is an individual who has fled his or her home country for similar reasons but has not received legal recognition prior to arrival in the U.S. and may only be granted legal recognition if the asylum claim is reviewed and granted. As a result, asylum seekers do not have access to services such as Refugee Medical Assistance, time-limited cash assistance, or similar employment opportunities. Migrant is a general term and refers to an individual who has left his or her home country for a variety of reasons.Prior studies have shown differences in utilization of the emergency department by refugees in comparison to native-born individuals.In Australia, refugees from non-English speaking countries are more likely to use ambulance services, have longer lengths of stay in the ED, and are less likely to be admitted to the hospital.A study conducted in the U.S. evaluated refugees one year post-resettlement and demonstrated that language, communication, and acculturation barriers continue to negatively affect their ability to obtain care. These data suggest that there may be unidentified opportunities for improving the acute care process for refugee populations; however, little is known about how refugees interface with acute care facilities. Therefore, the goal of this study was to use in-depth qualitative interviews to understand barriers to access of acute care by newly arrived refugees, and identify potential improvements from refugees and community resettlement agencies. The refugee clinic was located at a tertiary care hospital in a city in the Northeast U.S. The clinic has been in operation for approximately five years and has cared for approximately 200 refugee patients yearly. At the time of the study,vertical farming units the clinic received referrals from one of the three resettlement agencies in the city. Refugee patients were seen within 30 days of arrival. Most refugees were seen for screening evaluations and transitioned to clinics near their homes after twoto three clinic visits. Refugee patients were eligible for this study if they were over 18 years of age, had capacity to consent, and had no hearing difficulties. We excluded refugees if they were deaf, unable to answer questions from an interpreter, or had acute medical or psychiatric illnesses. In the city in which the study was performed, there are three main resettlement agencies and approximately three well-known post-resettlement agencies. Resettlement agencies are responsible for receiving new refugee arrivals and assisting individuals with support for three to six months after arrival.

Resettlement employees assist refugees with establishing housing, employment, transportation, primary care, and language services. After three to six months, refugees are able to seek additional assistance at post-resettlement agencies. Post-resettlement agencies provide additional support in terms of support groups, language services, cultural activities, and case management. Employees were eligible for this study if they worked at a resettlement or post-resettlement agency, were over 18 years of age, and had no hearing difficulties. This was an in-depth interview study using semi-structured, open-ended interviews. Separate interview guides for refugees and resettlement agency employers were developed by all members of the study team. Study team members included the following: an emergency physician and investigator with expertise in qualitative methodology ; an internal medicine physician with many years of experience working at the refugee clinic ; a third-year emergency medicine resident with three years of experience working bimonthly at the refugee clinic ; a second-year EM resident with no experience at the refugee clinic , an MD/PhD student with three years of experience working at the refugee clinic and content expert on refugee studies ; and an undergraduate student with two years of experience working at the refugee clinic . The study team composition allowed for a range of expertise with individuals who had experience working with refugees and those who did not. Questions were vetted among the all members of the study team and revised to ensure that content reflected the goals of the study. Prior to interviewing resettlement and post-resettlement employees, a resettlement/post-resettlement employee interview guide was developed using the same process. Refugee interviews were conducted in person at a refugee clinic, and refugees were recruited during the study period when an interviewer was present during clinic hours. Refugees were asked to participate if a room and interpreter were available. If the aforementioned conditions were met, all refugees awaiting clinic appointments or available after their appointment were asked to participate. All of the refugees who were asked agreed to consent and participated. Interviews with refugees were conducted by two members of the study team using the Refugee Interview Guide and lasted approximately 30 minutes. A phone interpreter was used for verbal consent prior to participation and for the interview. Demographic information was collected about each participant . After interviews were completed for refugee patients, a second phase of semi-structured, open-ended, interviews were conducted in person at local resettlement and post-resettlement agencies in the region. We obtained a list of employees involved in case management, health coordination, and program development for refugees/immigrants from resettlement healthcare teams. These employees were contacted via email with information regarding the study and consent form. Of 13 employees contacted, 12 participated. Employee interviews were conducted at their respective agencies, and verbal consent was obtained prior to participation. Interviews with resettlement employees were conducted by two members of the study team using the Resettlement/Post-resettlement Employee Interview Guide and lasted approximately 20 minutes. This study was approved by the institutional review board at the University of Pennsylvania.A total of 16 interviews were completed with refugees. Participants had a mean age of 34 and 50% had completed high school. Countries of origin were Syria , Bhutan , Democratic Republic of the Congo , Burma , Sudan , Iraq , Iran and the Central African Republic . Most refugees seen at this refugee clinic undergo medical screening within one to two months of arrival. A few of the patients remained at the clinic for long-term follow-up. All refugees required an interpreter and all interpretation was done with phone interpreters. A total of 12 interviews were completed for resettlement and post-resettlement agencies. Resettlement employees interviewed represented two resettlement agencies and two post-resettlement agencies. We identified several barriers to access of acute care facilities by newly arrived refugees . The process by which refugees seek care and barriers at each step can be visualized in Figure 1.Our principal findings identify barriers throughout the process of accessing acute care for newly arrived refugees. Overall, refugees face uncertainty when accessing acute care services because of prior experiences in their home countries and limited understanding of the complex U.S. healthcare system. The unfamiliarity with the U.S. healthcare system drives refugees to rely heavily on resettlement employees as an initial point of triage or, if they are very sick, to call 911. At the resettlement agency, employees express concern about identifying the appropriate level of care to which to send a refugee client.

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, took the world by surprise in early 2020 and resulted in unprecedented disruptions to normal life throughout the world as measures were put in place to control the spread of the deadly virus . Across North America, COVID-19 swept across the United States and Canada overwhelming health services and health infrastructure as cases exploded, hospitalizations exceeded capacity, and businesses and public programs like schools were forced to shut their doors, go online, or on hiatus . The physical and social impact was enormous – death rates grew exponentially and the healthcare system was pushed to exceed capacity in the face of enormous caseloads and a virus that spread rapidly . As schools, clinics, social venues, and otherwise non-essential businesses shut their doors, the most vulnerable in our society including those marginally housed, those experiencing substance use and/or those with mental health issues were even further marginalized as a result of lost services and support . Early in the pandemic, signs of increases in substance use raised concerns that substance use would skyrocket . Overdoses and particularly overdose deaths hit unprecedented levels and partially because of the reduced availability of emergency medical services . People living with HIV and particularly those who are not virally suppressed, were considered to be at heightened risk for COVID-19 serious consequences because of being immunocompromised and experiencing high prevalence of comorbidities . Among such individuals are people who use drugs and those with mental health problems . Therefore, understanding patterns of who did not obtain COVID-19 testing among PWUD and PLWH provides insight into how those with intersectional challenges may have experienced systematic exclusion from public health initiatives during the COVID-19 pandemic. This may shed light on strategies that may help us enhance access to testing among marginalized populations who experience health inequities in a future public health crisis.

To assess the impact of the COVID-19 pandemic among those confronting multiple challenges such as substance use and HIV,cannabis drying trays a consortium of NIDA funded cohorts entitled the Collaborating Consortium of Cohorts Producing NIDA Opportunities launched a specially designed survey administered three times during the pandemic. The C3PNO COVID-19 survey module contained specific measures for PWUD and PLWH. These data provide insight into the compelling questions of change in the levels of substance use among those enrolled in the cohorts many of whom have been using long term, been in substance use treatment, and have heavy use . Moreover, the results may demonstrate the extent to which critical COVID-19 public health interventions such as testing for the virus reached PWUD and PLWH. The C3PNO consortium was uniquely positioned to identify impacts of the COVID-19 pandemic on PWUD and PLWH as its cohorts following large numbers of such individuals across North America. The analyses described herein focus on the prevalence and factors associated with COVID-19 testing among PWUD and PLWH who participated in the first two rounds of the C3PNO COVID-19 module. C3PNO was established in 2017 by the National Institute on Drug Abuse to enhance data sharing opportunities and mechanisms to facilitate collaborative research efforts among NIDA-supported cohorts that examine HIV/AIDS in the context of substance misuse. Details of the participating cohorts and other methodology have been previously described but in sum, the C3PNO consortium is comprised of nine NIDA cohorts located in major cities throughout North America with a combined sample size of up to 12,000 active participants. Some cohorts had initial enrollment criteria that participants be people who inject drugs while other cohorts are young men who have sex with men. The consortium links a wide range of behavioral, clinical, and biological data from diverse individuals at high-risk for HIV or living with HIV participating in the cohorts. Starting in May 2020, the consortium launched a survey to examine patterns of substance use, substance use disorder treatment, and utilization of HIV prevention and care services in the midst of the COVID-19 pandemic.

Specific domains collected as part of the survey included overall impact of the COVID-19 pandemic and related governmental/societal restrictions on day-to-day life, adoption of COVID-19 prevention practices, COVID-19 testing and symptomatology, changes in substance use behaviors as well as reports of pandemic impact on access, quality, and pricing of illicit substances. The survey also included various measures of mental health including anxiety as well as access to medical care and substance use treatment. At the time of this study COVID-19 testing was available and recommended mostly for those with symptoms defined by the CDC at the time as the most predictive of COVID-19 infection including: fever, feeling feverish, chills, repeated shaking with chills, muscle aches or pain, runny nose, sore throat, new or worsening cough, shortness of breath, nausea or vomiting, headache, abdominal pain, diarrhea, and sudden loss of taste or smell. In the survey module current symptom reports were collected. Eight of the nine C3PNO cohorts participated in both of the first rounds of data collection but one was unable to share its data – all nine cohorts joined for later rounds. Each participating cohort contacted a minimum of 200 of their cohort members to participate in the survey eligible if they: were previously enrolled in one of the eight participating C3PNO cohorts; participated in a recent study visit ; were English and/or Spanish speaking; and willing and able to complete the survey remotely. Cohort investigators were encouraged to enroll participants who had a recent history of substance use as determined by self-report at their most previous visit. The survey was either self-administered through a web based survey for participants that had computer and internet access or interviewer administered by telephone for those participants without online access. The survey took approximately 20 min to complete and participants were remunerated for their time. The study was approved by the institutional review boards of the consortium cohorts and each participant provided informed consent for their study participation. There were 4035 responses to the survey across all eight cohorts that participated in both of the first two rounds and collected fully analyzable data; 3762 were available for this analysis because the Canadian cohorts confronted restrictions with sending data and were not able to be included.

The analyzed data for this manuscript includes data from 2331 individuals who completed one or both of the first two rounds of the C3PNO COVID-19 module. Participants were offered participation in each round of the survey regardless of participation in first round. This resulted in 1431 from individuals responding to both rounds. The first round was conducted from May-November 2020 and the second round from October 2020 through April 2021. Median time between surveys for participants who completed both rounds of the survey was 4.1 months . The time to implement the survey was a window period starting from when the programmed survey was made available for each round . Intervals are overlapping because some cohorts had not finished their first round when the first cohorts to implement started their second round. The survey was implemented in a very challenging time of research administration with entire components of universities shut down for months delaying aspects of survey conduct such as reviews of research and procedures for compensation. Therefore, the cohort research teams did the best they could to administer the survey when available and to reach the requested minimum number of participants and there was a range in time as to how long it took them to be able to collect data. Moreover,heavy duty propagation trays the implementation of the survey resulted in different time frames required by cohort research teams to complete the data collection. Those that sent links to web-based questionnaires and had participants who were responsive to these completed the rounds relatively quickly . Other cohorts had many older participants who had to be interviewed by telephone . These teams required much more time to reach participants and conduct the interviews. We implemented and conducted this research in a unique and challenging time in history that required some flexibility and innovations in data collection. This means because of the geographic range captured in these surveys, participants in different cities responded during different phases of the pandemic. Finally, given the burdens on the cohort staff to implement this study in addition to their other work, systematic data on refusal rates were not able to be collected. Specifically, participants were asked if they were tested for COVID-19 and if yes, if they have ever tested positive. Participants were also asked if they had symptoms of COVID-19. Participants were considered to have recent substance use if they reported using any of the following substances in the past month: methamphetamine, cocaine, heroin, fentanyl, or misused prescription opioids.

Alcohol, tobacco, and cannabis use were also assessed but are not the focus of these analyses. Univariate analyses provided descriptive statistics for the sample overall and by COVID-19 testing status. Comparisons of demographics, substance use and frequency of use, as well as HIV-status by COVID-19 testing status were based on t-tests, chi-square methods, and other non-parametric tests as appropriate while adjusting for the effect of the subject . Factors associated with the outcome of interest were assessed using regression analysis with generalized estimating equations in order to account for the within-subject correlations. This large survey of COVID-19 testing experience among cohorts that follow people living with HIV and people who use drugs across North America provides a snapshot of how the COVID-19 pandemic in its first year may have impacted those who live on the margins of society. This sample included those among the most socially vulnerable in North America – over half were unemployed before the pandemic, about one third food insecure, many people of color almost half of whom were living with HIV. Many of these individuals are not in the formal economy that may partially explain why only half of them were tested for COVID-19 – the entry point into COVID-19 prevention . It is also of concern that across surveys those reporting having COVID-19 symptoms did not have higher testing rates than those who didn’t report symptoms, although the recommendation and priority for COVID-19 was testing of those symptomatic early in the pandemic when testing was limited by supply of tests. Testing continues to be a pillar of COVID-19 control; especially before vaccine availability when these surveys were implemented . Our findings show that lack of COVID-19 testing was associated with markers of social marginalization such as unemployment. As many workplaces began offering testing to their employees, this can explain why unemployed had less opportunity for testing. Fewer Black participants reported testing, and this parallels what has been seen in studies of the more general population . This may be related to historical mistrust with the healthcare system and negative experiences of Black individuals with public health interventions that have previously exploited or misled them . Another key finding was that fewer PLWH reported COVID-19 testing than people HIV negative in these cohorts. That may be because our PLWH were older, more were Black, and more reported frequent substance use representing intersectional marginalization that may have kept them from accessing a COVID-19 test . The finding that fewer PLWH accessed COVID-19 testing suggests that COVID-19 services may have been less available in places they mostly access care such as their HIV treatment clinics because early in the pandemic there was less in-person HIV care. Moreover, it is possible that because PLWH have weakened immune systems they may been aware of their heightened vulnerability so vigilantly practiced masking and social distancing. While the substance use reported in the month before the survey does not seem high among cohorts of people who use drugs, it must be clarified that our study defined substance use by use of highly addictive, i.e. “hard” or street drugs such as methamphetamine, heroin, cocaine, fentanyl and prescription opioids. Use only of alcohol, tobacco and cannabis were not included in this analysis as the focus was on how the pandemic affected those who use highly addictive illicit substances that usually becomes a dominant part of their lives.

The simplest hypothesis being that B cell activation is associated with a down-regulation of the surface CB2 receptor. Alternatively, it has been reported that CB2 can form heterodimers with the CXCR4 chemokine receptor and has chemotactic properties that result in the selective homing of CB2 + and CB2 – B cells to different regions of lymphoid follicles [Basu 2013, Coke 2016]. We addressed the potential linkage between B cell activation and CB2 expression using two different approaches. CB2 is known to be expressed by B cell lymphomas and has been described as an oncogene [Jorda 2003, Perez-Gomez 2015]. We therefore examined a human B cell lymphoma cell line, SUDHL-4, that had been described to express an activated B cell phenotype. Consistent with a linkage between activation state and CB2 expression pattern, this cell line and two other lymphoma lines that exhibited an “activated” phenotype were found to exhibit high intracellular CB2 but no surface staining. In order to more directly test the linkage between B cell activation and CB2 expression pattern, we employed an in vitro model in which naïve mature human B cells obtained from umbilical vein cord blood were activated with a combination of receptor signaling and supporting cytokines [Ettinger 2005]. After 5 days in culture, the initial homogeneous population of naïve B cells had evolved into two obvious subsets: one that retained the naïve B cell phenotype and the other that exhibited an activated B cell phenotype . When examined for the expression of CB2, there was a clear distinction between these two subsets with a loss of extracellular CB2 only on the activated subset. Collectively,microgreen grow rack the evidence presented in this report points to a clear linkage between the acquisition of an “activated” B cell phenotype and specific regulation of CB2 protein expression.

With limited information regarding the nature of intracellular CB2, we employed a combination of confocal microscopy and marker co-localization studies to evaluate the distribution and location of intracellular CB2. It exhibited a diffuse but punctate pattern within the cytoplasm. This appearance was the same regardless of the type of cells studied – primary peripheral blood B cells, the SUDHL-4 cell line, or the 293T/CB2-GFP line that we had previously described [Castaneda 2013]. Using the 293T/CB2-GFP line, we compared the distribution of CB2 staining to the staining of mitochondrial and lysosomal markers. The sparse and well defined features of lysosomal staining did not match and were not pursued further. On the other hand, the punctate but diffuse pattern of mitochondrial staining shared some similarities to the pattern observed with CB2. This represented an interesting observation given our prior findings that THC can disrupt cell energetics and mitochondrial transmembrane potential in airway epithelial cells in a CB2- dependent manner [Sarafian 2008]. Along the same lines, Bernard and associates identified a similar effect on neuronal cells but ascribed this effect to intracellular CB1, which localized to mitochondria in their studies. However, there was no obvious co-localization between the CB2 receptor and mitochondrial markers when directly examined by dual staining and confocal microscopy. In summary, we can conclude that the expression of CB2 in human leukocytes appears to be specifically regulated with respect to the cellular location , the cell lineage being studied , and the state of B cell activation and differentiation . The presence of an activated phenotype on B cells is specifically associated with down-regulation of the surface CB2 receptor, a feature identified in B cells recovered from human tonsils and also observed in vitro when naïve B cells were stimulated to acquire an activated phenotype. Given the capacity for cell surface CB2 to form heterodimers with chemokine receptors and promote migration and homing and given the location of CB2 + and CB2 – B cells in different compartments within lymphoid follicles [Basu 2013, Coke 2016], it is possible that modulating surface CB2 during B cell activation plays an important role in trafficking.

The capacity for T cells, dendritic cells, and malignant B cells to respond to cannabinoids in a CB2-dependent manner has been well characterized [McKallip 2002, Roth 2015, Yuan 2002], yet these cells do not express CB2 on the cell surface. The logical conclusion is that intracellular CB2 must also be capable of mediating ligand-induced signaling and biological consequences. With the recent report byBrailoiu et al , there is now direct evidence for this. Given the high membrane solubility of cannabinoids, we hypothesize that the presence of CB2 at different locations within a cell provides a mechanism for cells to link receptor activation to different signaling and biologic consequences, resulting in an expanded functional heterogeneity of cannabinoids. The intracellular location of CB2 and the specific role of different receptors on biologic function remains to be determined but will likely be very informative in understanding cannabinoid biology. Adolescence is a time of subtle, yet dynamic brain changes that occur in the context of major physiological, psychological, and social transitions. This juncture marks a gradual shift from guided to independent functioning that is analogized in the protracted development of brain structure. Growth of the prefrontal cortex, limbic system structures, and white matter association fibers during this period are linked with more sophisticated cognitive functions and emotional processing, useful for navigating an increasingly complex psychosocial environment. Despite these developmental advances, increased tendencies toward risk-taking and heightened vulnerability to psychopathology are well known within the adolescent milieu. Owing in large part to progress and innovation in neuroimaging techniques, appreciable levels of new information on adolescent neurodevelopment are breaking ground. The potential of these methods to identify biomarkers for substance problems and targets for addiction treatment in youth are of significant value when considering the rise in adolescent alcohol and drug use and decline in perceived risk of substance exposure . What are the unique characteristics of the adolescent brain?

What neural and behavioral profiles render youth at heightened risk for substance use problems, and are neurocognitive consequences to early substance use observable? Recent efforts have explored these questions and brought us to a fuller understanding of adolescent health and interventional needs. This paper will review neurodevelopmental processes during adolescence, discuss theinfluence of substance use on neuromaturation as well as probable mechanisms by which these substances influence neural development, and briefly summarize factors that may enhance risk-taking tendencies. Finally, we will conclude with suggestions for future research directions.The developmental trajectory of grey matter follows an inverted parabolic curve, with cortical volume peaking, on average, around ages 12–14, followed by a decline in volume and thickness over adolescence . Widespread supratentorial diminutions are evident, but show temporal variance across regions . Declines begin in the striatum and sensorimotor cortices , progress rostrally to the frontal poles, then end with the dorsolateral prefrontal cortex , which is also late to myelinate . Longitudinal charting of brain volumetry from 13–22 years of age reveals specific declines in medial parietal cortex, posterior temporal and middle frontal gyri, and the cerebellum in the right hemisphere, coinciding with previous studies showing these regions to develop late into adolescence . Examination of developmental changes in cortical thickness from 8–30 years of age indicates a similar pattern of nonlinear declines, with marked thinning during adolescence. Attenuations are most notable in the parietal lobe,ebb and flow flood table and followed in effect size by medial and superior frontal regions, the cingulum, and occipital lobe . The mechanisms underlying cortical volume and thickness decline are suggested to involve selective synaptic pruning of superfluous neuronal connections, reduction in glial cells, decrease in neuropil and intra-cortical myelination . Regional variations in grey matter maturation may coincide with different patterns of cortical development, with allocortex, including the piriform area, showing primarily linear growth patterns, compared to transition cortex demonstrating a combination of linear and quadratic trajectories, and isocortex demonstrating cubic growth curves . Though the functional implications of these developmental trajectories are unclear, isocortical regions undergo more protracted development and support complex behavioral functions. Their growth curves may reflect critical periods for development of cognitive skills as well as windows of vulnerability for neurotoxic exposure or other developmental perturbations.In contrast to grey matter reductions, white matter across the adolescent years shows growth and enhancement of pathways . This is reflected in white matter volume increase, particularly in fronto-parietal regions .

Diffusion tensor imaging , a neuroimaging technique that has gained widespread use over the past decade, relies on the intrinsic diffusion properties of water molecules and has afforded a view into the more subtle micro-structural changes that occur in white matter architecture. Two common scalar variables derived from DTI are fractional anisotropy , which describes the directional variance of diffusional motion, and mean diffusivity , an indicator of the overall magnitude of diffusional motion. These measures index relationships between signal intensity changes and underlying tissue structure, and provide descriptions of white matter quality and architecture . High FA reflects greater fiber organization and coherence, myelination and/or other structural components of the axon, and low MD values suggest greater white matter density .These trends continue through early adulthood in a nearly linear manner , though recent data suggest an exponential pattern of anisotropic increase that may plateau during the late-teens to early twenties . Areas with the most prominent FA change during adolescence are the superior longitudinal fasciculus, superior corona radiata, thalamic radiations, and posterior limb of the internal capsule . Other projection and association pathways including the corticospinal tract, arcuate fasciculus, cingulum, corpus callosum, superior and mid-temporal white matter, and inferior parietal white matter show anisotropic increases as well . Changes in sub-cortical and deep grey matter fibers are more pronounced, with less change in compact white matter tracts comprising highly parallel fibers such as the internal capsule and corpus callosum . Fiber tracts constituting the fronto-temporal pathways appear to mature relatively later , though comparison of growth rates among tracts comes largely from cross-sectional data that present developmental trends. The neurobiological mechanisms contributing to FA increases and MD decreases during adolescence are not entirely understood, but examination of underlying diffusion dynamics point to some probable processes. For example, decreases in radial diffusivity , diffusion that occurs perpendicular to white matter pathways, suggests increased myelination, axonal density, and fiber compactness , but have not been uniformly observed to occur during adolescence. Similarly, changes in axial diffusivity , diffusion parallel to the fibers’ principle axis, show discrepant trends, with some studies documenting decreases , and others increases in this index . Decreases in AD may be attributable to developing axon collaterals, whereas increases may reflect growth in axon diameter, processes which are both likely to occur during adolescence. Technical and demographic differences such as imaging parameters, inter-scan intervals, age range, and gender ratios may account for divergent findings. Both grey matter volume decreases and FA increases in frontoparietal regions occur well into adolescence, suggesting a close spatiotemporal relationship . Changes in tissue morphometry are attributable to synaptic proliferation and pruning as well as myelination. Diminutions in gray matter density and concomitant brain growth in dorsal parietal and frontal regions suggest an interplay between regressive and progressive changes , and the coupling of these neurobiological processes is associated with increasingly economical neural activity .The increasing divergences in male and female physiology during adolescence are observed in sex-based differentiation of brain structure. Male children and adolescents show larger overall brain volumes , and proportionally larger amygdala and globus pallidus sizes, while females demonstrate larger caudate nuclei and cingulate gyrus volumes . Although cortical and sub-cortical grey matter volumes typically peak 1–2 years earlier in females than males , male children and adolescents show more prominent grey matter reductions and white matter volume increases with age than do females . The marked increase in white matter that occurs during adolescence is most prominent in the frontal lobe for both genders , though male children and adolescents have significantly larger volumes of white matter surrounding the lateral ventricles and caudate nuclei than females . Adolescent males also demonstrate a significantly higher rate of change in white matter volume particularly in the occipital lobe . Despite steeper white matter volume changes in males, maturation of white matter micro-structure may occur earlier in female than male adolescents .

Marijuana is a term that describes the dry leaves, stems, flowers, and seeds of the Cannabis sativa plant. It has been prohibited in the United States by federal law since the 1937 Marijuana Tax Act and the US Drug Enforcement Agency has classified it as an illegal schedule I drug . Schedule I drugs are considered the most dangerous class of drugs with potential for severe psychological and physiological dependence. Other schedule I drugs include heroin, ecstasy, and lysergic acid diethylamide . Marijuana can be smoked in hand-rolled cigarettes , in cigars that have been emptied out of its contents and refilled with marijuana , through vaporizers to avoid inhaling smoke, consumed in edibles, or brewed as tea. While the use of marijuana for medicinal, religious, and recreational purposes dates back 5000 years, the discovery of cannabinoid molecules and our understanding of how they interact with our endogenous human cannabinoid signalingsystem represents a relatively recent area of investigation [Aizpurua-Olaizola 2016, Herring 1998, Pertwee 2006]. Marijuana is composed of over 400 different compounds, including more than 100 different cannabinoids [Aizpurua-Olaizola 2016, Greydanus 2013]. Cannabinoids are the primary bioactive constituents of marijuana and the main psychoactive cannabinoid is delta-9-tetrahydrocannabinol . The THC content in the average illicit marijuana cigarette is reported by the Potency Monitoring Project to comprise approximately 12% by weight [ElSohly 2014]. Other cannabinoids also found in the Cannabis sativa plant include cannabidiol , cannabigerol , and cannabinol , but these are not considered to play a role in the psychoactive effects associated with marijuana consumption. Upon combustion and smoking, marijuana also liberates an array of polycyclic aromatic hydrocarbons including the known carcinogens benzopyrene and benzanthracene,grow rack which are components of the particulate phase of smoke [Roth 2001]. Toxic substances such as carbon monoxide, hydrogen cyanide, and nitrosamines are also released as part of the gas phase of marijuana smoke.

While all of these released constituents may have biologic and/or toxic consequences, the focus of this thesis work is on the cannabinoid constituents and specifically on the biology of the human type 2 cannabinoid receptor. The development of synthetic cannabinoids eventually led to the discovery of a human endogenous cannabinoid system that is comprised of at least two arachidonic acid-derived endocannabinoids, 2-arachidonoylglycerol and anandamide , their biosynthetic and degradative enzymes, and two cannabinoid receptors, CB1 and CB2. [Bisogno 2005, Cabral 2015]. The endocannabinoid system has been found to play a role in immunomodulation, metabolic regulation, bone growth, pain, cancer, and psychiatric disorders [Aizpurua-Olaizola 2016, Kleyer 2012]. Endocannabinoids are thought to be enzymatically produced and released “on demand” [Cabral 2015]. They bind and activate seven-transmembrane G protein-coupled receptors type I and type II and are linked to intracellular signaling cascades including adenylyl cyclase, cAMP, mitogen-activated protein kinase, and intracellular calcium [Howlett 2002, Maccarrone 2015]. Cannabinoid receptors, CB1 and CB2, share 44% amino acid homology and bind THC with relatively equal affinity [Cabral 2015, Shire 1996]. They are expressed in most organ systems, and their activation by marijuana smoke can have wide-ranging health effects [Grotenhermen 2003, Volkow 2014, Turcotte 2016]. The CB1 receptor is mostly found in the central nervous system and mediates the psychoactive components associated with cannabinoids. CB1 has been described to play a role in memory, pain regulation,stress response, and the regulation of metabolism [Busquets Garcia 2016, Cabral 2015]. More specifically, the highest concentration of CB2 is found in immune cells in addition to lower concentrations found in bone cells, keratinocytes, adipocytes, and renal tissue [Basu 2011, Mackie 2006]. The CB2 receptor is suggested to play a role in immunomodulatory mechanisms that regulate inflammation and also play a role in host defense [Basu 2011, Herring 1998, Turcotte 2016]. Despite the widespread use of marijuana and its increasing legalization across multiple states in the U.S., there is relatively little information known about the effects of cannabinoids on human immunity.

Cannabinoids have been described to have anti-inflammatory effects on leukocytes. [Cabral 2015, Roth 2015, Volkow 2014]. In mouse studies, the CB2 receptor has been found to play a role in the responsiveness to infectious pathogens and play a role in immune homeostasis [Newton 1994, Newton 2009]. In human studies, alveolar macrophages from the lungs of marijuana smokers have been found to be deficient in the production of cytokines, nitric oxide, and mediation of bacteria killing [Baldwin 1997, Roth 2002, Shay 2003]. Human T cells activated in the presence of THC have also been found to result in a T helper type 2 -skewed pattern of cytokine production with limited proliferation [Yuan 2002]. With the highest levels of expression on immune cells, the CB2 receptor is suggested to mediate the immune regulating effects of cannabinoids [Cabral 2015, Roth 2015, Volkow 2014, Turcotte 2016]. In support of this statement, there are several studies done with animal models, including CB2 knock-out mice [Liu 2009, Turcotte 2016, Ziring 2006]. Although murine CB2 and human CB2 share 82% amino acid homology of the coding regions, there are significant differences in non-coding regions of their respective genes, suggesting that some inter-species differences likely exist with respect to regulation and expression [Liu 2009]. This potential difference argues that a combination of both animal models and human studies are required to understand the regulation and function of the CB2 receptor with respect to the immune system. Nonetheless, CB2 knock-out mice have been reported to exhibit higher levels of leukocyte recruitment and an over-production of pro-inflammatory cytokines [Buckley 2008]. While these mice do not exhibit obvious morphological differences they have also been noted to have abnormalities in the formation of several T cell and B cell subsets within lymphoid organs, making the CB2 receptor vital for the formation of T cell and B cells subsets involved in immune homeostasis [Turcotti 2016, Ziring 2006]. An increase in IgE production and allergic diseases would be expected in a model that is driven towards Th2 skewing [Agudelo 2008].

Surprisingly, THC treated CB2 knockout mice showed increased levels of IgE serum production, suggesting a role for CB2 receptor in the regulation of IgE [Newton 2012]. Immune suppression was also observed when THC was administered to tumor-bearing mice, which promoted tumor growth in a CB2-dependent manner [Zhu 2000]. Translating in vivo and in vitro experiments performed in animal or cell line models into an understanding of the biology in humans is also challenging because of the route of consumption, amount of exposure, and the pattern of use in marijuana users is entirely different, and there are often concurrent exposures of humans to tobacco, alcohol, and other substances that might affect the immune system in an additional or different manner.The previously described work suggests that cannabinoid receptors may be centrally involved in immune function, and therefore, the CB2 pathway may represent an attractive target for cannabinoid-based drugs. Cannabinoids have been promoted as a new class of drugs with the potential for beneficial anti-inflammatory, immunoregulatory, and anti-fibrotic effects [Atwood 2012, Pacher 2011, Turcotti 2016]. CB2 agonists have already been shown to reduce inflammation through the p38-MK2 pathway [Turcotti 2016]. There are currently multiple FDA-approved cannabinoid based medications. Marinol and Cesamet have been prescribed for the treatment of chemotherapy induced nausea and vomiting. Marinol has also been prescribed as an appetite stimulant and as a treatment for glaucoma by lowering intraocular pressure. Recently in July of 2016, SyndrosTM , an orally administered liquid formulation of dronabinol,greenhouse tables has also received FDA approval. It has been prescribed to treat anorexia associated weight loss in AIDS patients and chemotherapy induced nausea and vomiting. Also, Sativex, a sublingual spray that is composed of equal concentrations of THC and CBD, has received FDA approval to proceed with phase III clinical trials for the treatment of pain in patients with advanced cancer. It is also prescribed for the treatment of spasticity due to multiple sclerosis. CBD is of great therapeutic interest since it has been shown to have anti-emetic, anti-inflammatory, and anti-psychotic effects [Bergamaschi 2011, Cabral 2015, Turcotti 2016]. There have also been no effects observed on blood pressure, pulse, body temperature, or gastrointestinal and psychological function [Bergamaschi 2011]. Another cannabinoid formulation that contains only CBD, Epidiolex, is also undergoing phase III testing for the treatment of a rare genetic seizure disorder . Despite the Schedule I DEA classification assigned to marijuana , there is obvious evidence that strategies focused on regulating CB2 signaling might represent promising treatments for autoimmune or chronic inflammatory diseases. Understanding the expression and function of the human CB2 receptor may provide an important key to unlocking further cannabinoid-based drug development. The CB2 receptor has traditionally been described as a cell surface GPCR. GPCRs respond to a wide variety of stimuli and play crucial roles in neurotransmission, cellular metabolism, secretion, differentiation, growth, inflammation, and immune responses. GPCR activation is initiated by ligand binding, an event that usually occurs at the cell surface. Ligand binding induces a conformational change that activates heterotrimeric G-protein signaling and a subsequent cascade of events leading to internalization of the receptor and linkage with other signaling pathways [Jean-Alphonse 2011, Syrovatkina 2016]. The CB2 receptor has been reported to exhibit a complex pharmacology , signaling and trafficking pattern [Aizpurua-Olaizola 2016, Basu 2011, Howlett 2005]. The characterization of THC has led to the synthesis of cannabinoid analogs classified as synthetic cannabinoids, which are used to study structure-activity relationships, characterize cannabinoid-mediated bioactivity, and contribute to the understanding of mechanism of action by which endocannabinoids and phytocannabinoids exert their effects on the immune system [Cabral 2015].

The development of new ligands that can mimic the protective effects of cannabinoids has proven particularly difficult due to the constant discovery of multiple endogenous ligands, targets, and sites of interaction. Further research is needed to understand the mechanism of action of cannabinoids since the patterns of activation and induction of intracellular signaling differs with each compound. As demonstrated in CB2 transfected CHO cells, human HL-60, human bronchial epithelial cells, murine microglial cells, and a murine macrophage cell line, CB2 signaling is initiated through its interaction with heterotrimeric Gi-proteins and the inhibition of adenylyl cyclase [Turcotte 2016]. CB2 signaling has been linked to phosphorylation of MAP kinase, phosphorylation of AKT, modulation of intracellular calcium, and generation of intracellular ceramide [Basu 2011, Brown 2012, Chen 2012, Cudaback 2010, Howlett 2005, Turcotte 2016]. The mechanisms responsible for this signaling diversity have not been adequately explained. In studies with other GPCRs, it is often the process of receptor internalization that allows the receptor to become associated with an array of adaptor and signaling molecules [Calebiro 2010, Jean-Alphonse 2011]. The finding that CB1 receptor is expressed at intracellular sites and can mediate signaling adds further support for CB2 to play a role in mediating intracellular signaling [Rozenfeld 2011]. Rab proteins direct receptor trafficking to specific intracellular organelles, and CB2 receptors have been suggested to internalize via Rab-mediated endocytosis and initiate downstream intracellular signaling [Calebiro 2010, Grimsey 2011]. In artificial cell constructs, CB2 has been observed to undergo both constitutive and ligand-based internalization and traffic through endosomal and lysosomal compartments [Atwood 2010, Grimsey 2011, Kleyer 2012]. Blocking internalization or shifting the use of adaptor proteins has been observed to shift intracellular versus extracellular GPCR distribution [Grimsey 2011]. The dynamic balance between CB2 receptors at the cell surface and at possible intracellular sites might play a vital role in understanding cannabinoid receptor biology. The availability of cell surface receptors for ligand interaction can determine the responsiveness of a cell and further induction of intracellular signaling. Receptor availability for ligand binding is a very important feature in order to understand drug action and how the CB2 receptor can be exploited for therapeutic purposes. There is great diversity in the trafficking of GPCRs, and it is vital to understand the specific pathways involved with CB2. Localization of receptors at the cell membrane has been described to determine signaling via G protein pathways. Kleyer and associates also describe that the amount of cannabinoid receptor on the surface can directly determine receptor function. Interestingly, they also describe that cannabinoid receptors in primary human cells do not only internalize upon agonist interaction. They describe movement of the receptors between cytoplasm and cell membranes by ligand independent trafficking mechanisms, such as triggering by hydrogen peroxide that is present during inflammation and triggering by nonspecific protein tyrosine phosphatase inhibitors [Kleyer 2012].

Whereas our initial models tested the relationship between interdependent substance use behavior, they assumed that these effects are symmetric: that is, usage of one substance equally increases or decreases usage of another substance. In our next set of models, we relax this assumption and test whether usage of one substance increases behavior of another substance or decreases behavior , or both . These models were estimated separately as the combined model exhibited extreme collinearity. As shown in Table 3, there is a significantly positive creation function from marijuana use to drinking in both samples, implying that respondents’ marijuana use increased their odds of drinking initiation. Thus, one unit higher marijuana use made a nondrinker 62% and 60% more likely to start drinking rather than stay as a non-drinker at the next time point in Sunshine High and Jefferson High, respectively. On the other hand, the endowment function from marijuana use to drinking is not statistically significant at either school, implying that marijuana use does not affect the likelihood of stopping drinking behavior. The impact of marijuana use on smoking behavior differs across the two schools. We detect a statistically significant creation function in Sunshine High: a one unit increase in marijuana use increases the odds 62% that adolescent non-smoker will initiate smoking rather than stay as a non-smoker. There was no evidence of a statistically significant endowment function in Sunshine High. On the other hand, the pattern is reversed in Jefferson High with a statistically significant endowment function but a statistically insignificant creation function. Thus, in Jefferson High although marijuana use does not impact respondent’s likelihood of smoking initiation, one unit higher marijuana use made smokers 27% more likely to stay as smokers rather than quit smoking at the next time point.To understand the magnitude of these effects , we engaged in a small simulation study in which we omitted some of the effects from the SAB model shown in Table 2 and assessed the consequences for the level of substance use behavior in the schools. That is,grow rack we changed a particular parameter value from the one estimated in the model to zero, and then simulated the networks and behaviors forward 1000 times.

We then assessed the average level of smoking, drinking, and marijuana use in the network at the end of the simulation runs. To save space, we only present the results for Sunshine High; see S2 File for the Jefferson High results, which were similar.The highest level of smoking is observed when we set to zero the influence effect of friends on smoking behavior, as the percentage of non-smokers drops from 72% in the original model to 63%, and the percentage of heavy-smokers increases from 11% to 18% . The pattern was similar in Jefferson High, with analogous values of 48% to 42%, and 31% to 35%. This corroborates the findings in previous simulation research that peer influence has a protective effect on smoking and drinking adoption. The lowest levels of smoking are observed in the hypothetical scenario in which marijuana use has no effect on one’s own smoking behavior, as the percentage of non-smokers rises from 72% to 81%, and the percentage of heavy-smokers decreases from 11% to 5%. The analogous values in Jefferson High were 48% to 54%, and 31% to 25%. Regarding drinking behavior, we see that the effect of one’s own marijuana use is particularly important as setting this effect to zero results in a decrease in drinking behavior . In the scenario of no effect of marijuana use on drinking behavior the percentage of nondrinkers rises from 50% to 59% and the percentage of heavy drinkers falls from 13% to 7%. The analogous values in Jefferson High were 35% to 42% and 16% to 10%. It is notable that setting the influence effect of friends’ drinking on one’s own drinking behavior to zero reduces drinking somewhat . In Jefferson High, the number of heavy drinkers rises from 16% to 20%. For marijuana usage, very pronounced strong effects are observed for friends’ influence . Setting this influence effect to zero results in a sharp decrease in non-marijuana users from 62% to 47%, and a parallel large increase in heavy users from 19% to 32%. In Jefferson High, the analogous values were 61% to 43% and 18% to 33%. In sum, when the effect from marijuana use to cigarette use is turned off, more non-smokers and fewer heavy-smokers are expected in both schools. When the peer influence effect with regard to each substance use is turned off, fewer non-users and more heavy-users of each substance are expected in both schools.

In the scenarios in which we set other parameters to zero, the simulation results indicated that the substance use distribution was not altered in either school.Overall, our findings indicate some evidence of sequential substance use, as adolescent marijuana use increased subsequent smoking and drinking behavior in our two school samples. Whereas some existing research has found evidence that marijuana use leads to use of these substances, an important contribution of our study was simultaneously taking into account the substance use behavior of adolescents’ peer networks and other social processes occurring in networks. We found that marijuana use resulted in more smoking and drinking in both samples. Our findings are partially consistent with Pearson et al. , who found that that marijuana users smoked cigarettes more over time. Our findings are suggestive that marijuana use increases both alcohol and cigarette use. In addition, we made a distinction between whether interdependent substance use going from marijuana to cigarettes and alcohol results in initiation, cessation, or both. We found that marijuana use resulted in drinking initiation in both samples, and smoking initiation in Sunshine High. In contrast, marijuana use decreased the likelihood of smoking cessation in Jefferson High. Previous literature suggests that alcohol use is not a prerequisite for the initiation of marijuana use and the effect of alcohol use on the onset of marijuana use has declined while that of marijuana use on the onset of alcohol use has increased since 1965 , and our findings are consistent with this prior literature. Moreover, we tested cross-substance influence effects, which assessed whether the substance use behavior of one’s friends on a particular substance affected an individual’s own use of the other two substances. We found no evidence that such effects exist in our samples. We did, however, find peer influence effects for each specific substance, which is consistent with multiple past studies. Note, however, that whereas one implication is that having more friends who use marijuana, for example, results in greater marijuana use behavior on the part of the individual, another implication is that having more friends who do not use marijuana results in less marijuana use behavior. This relative symmetry of influence effects is sometimes overlooked when interpreting influence results, and our simulation results confirmed that this influence effect is in fact more likely to have a negative effect on substance use behavior.

These results are similar to an earlier simulation study that found that increasing the amount of peer influence in two high schools diminished school level smoking and drinking behavior . These results are consistent with theoretical insights from the Dynamic Social Impact Theory, which would predict that youth in friendship networks would adopt the same substance use behaviors through peer influence pathways, likely through social proximity and consolidation of youths’ attitudes and behaviors in adolescent networks. This highlights that the presumption that influence effects will always increase behavior is not necessarily accurate. In fact, we might expect that the dominant norms in a context will drive the direction of influence effects: in a school with little substance use, the greater number of non-users will push adolescents towards non-use, whereas in a school with high levels of substance adolescents are more likely pushed towards greater use. Given the complexity of our agent-based network models,greenhouse grow tables we demonstrated the relative magnitude of the effects by combining a small-scale simulation with a strategy in which we constructed hypothetical models that set certain key effects to zero and simulated the networks and behaviors forward. A key finding was that in a simulated world in which one’s own marijuana use did not affect smoking or drinking behavior, there would be a notable decrease in overall levels of smoking and alcohol usage in these schools, even controlling for the complexity of these models. We also saw that marijuana use operates as a mechanism between friends’ marijuana use and one’s own smoking and drinking behavior, as adolescents’ use of marijuana is impacted by their friends’ marijuana use, and this then affects the adolescent’s level of cigarette and alcohol use. Furthermore, one of the strongest effects detected was the influence effect of friends’ marijuana usage, as this has a particularly strong relationship to adolescents’ own marijuana use. Our findings highlight the importance of understanding interdependence in the use of multiple substances in adolescence, particularly those which operate through peer influence effects within friendship networks. Another notable finding was that depressive symptoms increased smoking behavior in Jefferson High. This high school has a relatively high average level of substance use compared to Sunshine High. Perhaps in a social milieu with a high average level of drug use, adolescents reporting higher levels of depressive symptoms may be more likely to display higher levels of cigarette smoking as compared to those who report lower level of depressive symptoms, given that past studies link depression and adolescent smoking. There are some limitations to note in this study. First, the time lags between the two sets of waves are not equal . Although it is preferable to have equal time periods, we performed a post hoc time heterogeneity test to ensure that the co-evolution of substance use behaviors and friendship networks was not significantly different across the three waves, or two time periods. Second, our SAB model specification is data intensive and can only be estimated for the two large schools among the 16 saturated schools in Add Health which are feasible for this type of analysis.

This limits generalizability and does not allow assessing why the interdependent effect from marijuana use to smoking is different across the two schools. Third, we had indirect information about marijuana use at time one, for a large percentage of the sample. Using this indirect information allowed us to avoid discarding a large amount of information at t1, however with a relatively small amount of potentially misclassified cases. Fourth, while the data are relatively old, we are aware of no evidence that the mechanisms of in person friendship formation, as captured in these Add Health network data,have changed significantly since the mid-nineties. In the current study, friendship networks were constructed through name generator items instead of real-time communication technology such as cell phone use. While future studies are needed to leverage existing technology such as cell phone usage for collecting adolescent social network data, these in person network data are likely still meaningful. Moreover, research suggests that cell phones help reinforce and reproduce existing social roles and structures rather than alter them. That said, future studies are needed to collect nationally representative contemporary data from US adolescents and investigate how the findings herein would be different if such technology was considered.Our findings have important implications for future studies. First, our findings suggest both feasibility and merit in exploring concurrent or sequential substance use behaviors across multiple time periods. Interdependence in substance use should be studied within one single model framework with multiple simultaneous on-going processes to reduce the risk of over-estimation of each process due to the auto correlation among them. Second, further explication of the interdependent effects from marijuana use to smoking and drinking is a useful direction for future research. Third, given smoking rates among adolescent youth have decreased significantly since the mid-1990s, more recent data are required to test whether our findings from these two Add Health large schools can be replicated in future research. Our findings also have practical implications for health behavior change interventions targeting adolescent substance use. Moreover, other research indicates that social networks can be leveraged for health behavior change interventions and may even be superior to non-network based interventions . Peer network based interventions targeting adolescent substance use might address the possibility that marijuana use increases alcohol and cigarette use.

It is also important to highlight the complexity of poly substance use in the context of a cross-sectional, retrospective study. Despite this, lifetime MA use disorder was retained in the multiple regression model, while the other substances did not. Due to limited data on participants who met criteria for a current substance use disorder or other measurements of current substance use parameters, our finding cannot speak to other potential factors associated with poly substance use that may explain differences in sleep between MA+ and MA− groups. Future studies to formally investigate poly substance use in more detail is needed to futher confirm our findings. In addition, we did not find associations between age, sex, or sexual orientation on sleep quality, which is contrary to well established literature on these topics . We suspect that the presence of other clinical risk factors for poor sleep, including those identified in this study , may be masking the detection of these variables traditionally known to impact sleep quality. There also remains the possibility that other unmeasured factors such as homelessness and/or SES may account for the observed relationship that MA was related to sleep in PWH that should be explored further in future studies. Lastly, the PSQI questionnaire is based on self-report, which is subject to recall and reporting bias. While there is merit in characterizing perceived sleep quality in vulnerable populations, as even the perception of poor sleep can influence mood and physical health , subjective measurements are just one facet of sleep quality and the inclusion of objective measurements such as actigraphy would enhance understanding of sleep in PWH and substance using populations. Importantly,cannabis dry rack the global PSQI score demonstrates strong sensitivity and specificity in distinguishing good from poor sleepers among the general population . While the sensitivity in detecting an insomnia diagnosis in PWH remains high , the specificity drops considerably .

This suggests that the PSQI may not just be capturing sleep quality in PWH and raises the question as to whether items such as “trouble staying awake during the day” or “trouble keeping enthusiasm” are purely a function of poor sleep or a result of HIV-infection, prescribed medications, and/or associated psychosocial factors. Studies investigating the quality of the PSQI sub-components in capturing sleep quality within PWH using factor analyses may be a natural next step for future research.For people with substance use disorders, denial of untoward consequences from their actions is common and can affect commitment to treatment. In 2019, 96% of untreated individuals with a substance use disorder in the previous year denied needing treatment.Psychodynamic approaches toward addiction encourage accountability and minimizing denial; and 12-step programs, such as Alcoholics Anonymous, target denial by encouraging clients to acknowledge that they have lost control over addictive behavior, with a focus on accountability-centered goals. Among participants who had poly substance misuse and attended Alcoholics Anonymous or Narcotics Anonymous, the number of days in attendance was associated with decreased self-deception measured in a followup assessment.The transtheoretical model of behavior change likewise posits that changing addictive behavior relies on a transition from lack of recognition that a problem exists to increased awareness and motivation to change.The rostral anterior cingulate cortex , which participates in self-related processing, including self-awareness, has been implicated in personal relevance of drug-related stimuli, as is the ventromedial prefrontal cortex, which contributes to decision making.In an fMRI study, denial of methamphetamine-related problems was negatively related to resting-state connectivity between the rACC and precuneus. Among participants who met diagnostic criteria for Methamphetamine Dependence ,denial of methamphetamine-related problems correlated negatively with overall cognitive function and with rACC connectivity to frontal lobe regions, including the precentral gyri, left ventromedial prefrontal cortex, and left orbitofrontal cortex.These data implicate the rACC and its connections in a person’s ability to acknowledge problematic aspects of their substance use.

One of the most important clinical measurements, the diagnosis of a substance use disorder, involves clinical judgment, but self-reports are very important. Structured diagnostic interviews, such as the Structured Clinical Interview for DSM-IV or Mini-International Neuropsychiatric Interview , query self-reports of symptoms indicating craving, tolerance, withdrawal, and interference with activities of daily living. Although interview guidelines encourage the use of referral notes, records, and observations of friends and family,diagnosis often relies on interview with the client alone. In these interviews, denial of problems related to substance use is common and can alter diagnosis. This study sought to clarify how a diagnostic measure of Methamphetamine Dependence that relies on self-report is related to a participant’s denial of his or her addiction problem. Participants comprised a sample of 69 individuals who acknowledged enough symptoms on the SCID to meet criteria for the diagnosis of Methamphetamine Dependence. They also completed the University Rhode Island Change Assessment Scale , which assesses motivation for change by providing scores on 4 stages of change: Precontemplation, Contemplation, Action and Maintenance. The Precontemplation score measures the respondent’s denial that their drug problem warrants change,and is based on a transtheoretical model of addiction.In a prior study, the Precontemplation score was positively related to years of heavy methamphetamine use and arrests for drug offenses,supporting the notion that high scores reflect denial rather than the absence of problems. We hypothesized the Precontemplation score would correlate negatively with symptom severity, confounding the diagnosis.It is estimated that homelessness affects 3.5 million youth between the ages of 18 to 25 annually in the United States. Sexual and gender minority youth are over represented in homeless populations, with research indicating that between 30% and 40% of service-using homeless youth identify as SGM, within the context of approximately 6.4% of youth aged 18 to 29 identifying as SGM nationwide.

SGM youth include individuals who identify as lesbian, gay, bisexual, and transgender as well as gender queer, non-binary, agender, asexual, or another sexual or gender identity that is either or both non-heterosexual or non-cisgender . Previous studies examining pathways into homelessness among youth have repeatedly demonstrated that SGM youth are more likely to enter homelessness as a result of family members who are unaccepting of their gender identity and sexuality compared to heterosexual cisgender peers, demonstrating how SGM status is itself a risk factor for becoming homeless. In addition to disproportionately high representation among all unstably housed youth, SGM youth experiencing homelessness also face increased health risks compared to their heterosexual cisgender peers. With regards to mental health, lesbian, gay, bisexual, and transgender youth who are homeless are more likely to experience substance use and use a greater number of substances than heterosexual cisgender peers experiencing homelessness. Given these documented disparities, SGM homeless youth may be at higher risk for negative health outcomes related to substance use, such as HIV and viral hepatitis, which can further serve as a barrier to maintaining stable housing. Sexual and gender minority youth experiencing homelessness also report worse mental health outcomes, including increased suicidal ideation and more severe depressive symptoms, increased anxiety, and higher rates of post-traumatic stress disorder. One proposed model for conceptualizing these observed health disparities among SGM youth is the minority stress model, which acknowledges that SGM communities face an excessive burden of daily stigma and discrimination from living in a heterosexist, transphobic society, resulting in detrimental effects to their emotional, psychological, and physical health. These experiences of stigma and discrimination among SGM youth have been documented to occur in a wide variety of settings, including family rejection, homophobic bullying in community settings such as schools, and discrimination from clients and staff in emergency shelters. In addition to the violence and discrimination faced due to their sexual orientation or gender identity, SGM youth experiencing homelessness often hold multiple identities that place them into further marginalized groups, such as their racial and ethnic backgrounds. Youth of color, particularly Black youth, are more likely to experience homelessness compared to white peers. Furthermore, SGM youth of color face more difficult exits from homelessness compared to their white, heterosexual, cisgender peers.

Black LGBT youth experiencing homelessness are more likely to experience harassment from police and community members,trimming tray as well as increased sexualization and invisibility, which collectively make LGBT youth of color more vulnerable to various mental health disparities, such as increased substance use and prevalence of mood disorders. Policy agendas aimed at addressing the health disparities faced by SGM youth experiencing homelessness have emphasized the need to understand SGM youth as non-homogenous micro-communities with unique experiences, risk factors, and social environments. Previous studies of youth experiencing homelessness in San Francisco, the location of this study, have revealed high burdens of substance use and mental health conditions in line with national trends. In the San Francisco 2019 Homeless Unique Youth Count & Survey, one in five homeless individuals on a single night was under the age of 25. Of these unstably housed youth, nearly half identified as LGBTQ+. One in three surveyed youth reported ongoing drug or alcohol use, and 13% reported substance use as a cause of their homelessness. Mental health was another commonly reported cause of homelessness, with 30% of all San Francisco homeless youth indicating that their mental health was a contributing cause of homelessness. Symptoms of depression, PTSD, and anxiety among service-seeking San Francisco youth experiencing homelessness are correlated with increased prevalence of opioid and stimulant use, demonstrating the inter-connectedness of substance use and mental health outcomes. The high health burden of substance use and mood disorders is also tied to increased mortality among San Francisco youth experiencing homelessness, who experience mortality rates 10 times in excess of their stably housed, age-matched peers, with a majority of deaths resulting from substance use or suicide. While the disparities in the prevalence of substance use and negative mental health outcomes among SGM youth experiencing homelessness compared to heterosexual cisgender peers are well-described in the literature, a comparative understanding of downstream harms associated with use of specific substances between SGM and heterosexual cisgender youth experiencing homelessness remains poorly characterized. In this study, we employ a tool that quantifies the burden of negative impacts associated with use of a specific substance. Using a cross-sectional analysis of a racially diverse group of service-seeking youth experiencing homelessness ages 18 to 24 in a dense, urban environment, we examine risks of harmful use associated with specific substances among SGM youth experiencing homelessness compared to their heterosexual cisgender peers. Alongside substance use, we examined whether symptoms of depression, anxiety, and PTSD differed between SGM and heterosexual cisgender youth who sought services at a community-based site. We expected that SGM youth would exhibit greater health risks associated with substance use across all substances surveyed, as well as more severe symptoms of mental illness when compared with their heterosexual cisgender peers. All data were collected from a capacity-building initiative at a partnering multi-site, non-profit community based organization in San Francisco, California.Our study was designed as a cross-sectional investigation of youth aged 18 to 24 who utilized services from Larkin Street Youth Services, a community-based organization in San Francisco. Each year, Larkin Street serves 2,500 to 3,000 youth aged 12 to 24 years old. Clients include individuals who live outside or in a car, a shelter, a transitional living program, permanent supportive housing, a single-room occupancy hotel, a unit partially paid for using subsidies, or who are otherwise unstably housed. The organization also offers a wide array of programming, including emergency and transitional housing, basic needs services such as access to food, showers, laundry, and harm reduction supplies, educational and employment training programs, medical care, behavioral health services, case management, street outreach, and a youth leadership development program. Larkin Street also offers resources and programming specifically for SGM youth, and staff members undergo LGBTQ cultural competency trainings. In order for participants to qualify for our survey, they needed to be between 18 and 24 years of age and utilize services at Larkin Street. Recruitment strategies included posting flyers within the CBO’s residential and clinical spaces, referrals of participants from frontline workers, case managers, counselors, and group facilitators, and presentations at community housing meetings. Of note, a small subset of participants were surveyed at a service site that only serves youth living with a HIV diagnosis, but the majority of participants were recruited from Larkin Street’s other sites that serve all youth, including daytime drop-in centers, health clinics, and transitional housing spaces.

We examined correlations between number of observations provided by each participant and all other study variables to assess whether attrition across waves was associated with levels of any of our study variables of interest. While socioeconomic status was correlated with greater retention in the sample , no other study variables were associated with attrition across waves. Data were structured treating age as time, and were analyzed in the 5-year span from age 17 to age 21.1 Moreover, noting positive skew in our binge drinking outcome, we further employed robust estimator that provided more accurate and robust parameter estimation for models of non-normal data compared to the standard maximum likelihood estimation and alternatives . Latent curve models with structured residuals were used to address primary hypotheses and were conducted separately for depression and anxiety. A schematic of the LCM-SRs employed are provided in Figure 1. LCM-SRs are an integration of random effects and cross-lagged panel models aimed at estimating lagged effects in longitudinal panel data at the within-person level. In contrast to standard cross-lagged methodologies, LCM-SRs can estimate temporally lagged associations between depression and binge drinking that are partitioned of between-person differences in these associations. This is achieved by specifying a latent curve model to account for between-person differences in level and change in longitudinal data while estimating auto-regressive and cross-lagged effects of time-dependent residuals, which have a purely within-person interpretation. In these models, we evaluated model fit using the adjusted χ2 difference test, where a non-significant result was an indication of adequate model fit. We supplemented this test with a number of alternative fit indices , including scaled variants of the comparative fit index and root mean square error of approximation . We included socioeconomic status and sex at baseline as covariates to control for between-person demographic factors that may be influencing levels of internalizing symptoms and binge drinking.

Socioeconomic status was measured using a modified version of the MacArthur Sociodemographic Questionnaire . In sensitivity analyses,cannabis vertical farming we replicated each LCM-SR separately for males and females to explore whether effects differed across sexes.2 All analyses were conducted in R using ‘lavaan’ . A significance threshold of 0.05 or better was required across analyses. Analyses were supplemented with post-hoc power simulations conducted using the pwrSEM application to determine whether LCM-SRs employed were sufficiently powered to detect targeted autoregressive and cross-lagged effects. Power was computed using the Monte Carlo method following steps provided in Wang and Rhemtulla, 2021 and Hancock and French, 2013. Namely, we specified a population LCM-SR based on the standardized variances and covariances between variables included within our model. Assuming this covariance structure, we modified effect sizes for target parameters within these models across a range of magnitudes to assess the minimum effect size needed to detect each target parameter. Then, we generated 1,000 samples assuming 831 observations for this model, fit our LCM-SR to each, and recorded the proportions in which the target parameters were different from 0 based on a significance threshold of α = 0.05. Results are summarized in Table 2. Between-person effects indicated socioeconomic status was associated with greater growth in HED over time, and that women reported higher depression and anxiety and more growth in HED than men. Auto regressive path parameters indicated that HED was positively associated with levels at the subsequent time point, indicating moderate year-to-year stability over the five-year study window. Addressing within-person effects, binge drinking marginally predicted depression among females . No other effects were significant. We note that confidence intervals for within-person effects were narrow for the associations between depression and anxiety symptoms and subsequent HED , demonstrating high precision in these null associations in the sample. We examined lagged associations between adolescent binge drinking, anxiety, and depression symptoms over five years in a large, diverse, prospectively followed sample of participants from the NCANDA study. While the self-medication hypothesis suggested that binge drinking behaviors may follow the presence of internalizing symptoms as a means of coping with negative affect, other theories have suggested binge drinking may disrupt social and cognitive functioning and may serve as a metabolic insult that predisposes youth towards the occurrence of depression and anxiety.

One underlying mechanism of the impact of binge drinking on the development of depression and anxiety has been explained in the literature as related to systemic and CNS inflammation that develops with increasing alcohol use and leads to subsequent psychiatric symptoms . Alternatively, shared between-person factors, such as environmental and peer influences, may drive relations between these co-developing constructs. We used latent curve models with structured residuals to test these hypotheses concurrently. Given equivocal evidence that internalizing symptoms and binge behaviors are linked in adolescence, we supported our findings with post-hoc power analyses to determine whether the NCANDA sample was sufficiently powered to detect these effects if they were present in our target population. Results demonstrated trending evidence that binge drinking predicted subsequent depression and anxiety among females, and no direct evidence that internalizing symptoms predicted later binge drinking. This suggests that although binge behaviors may increase later internalizing risk for females, it is likely that binge behaviors may develop largely independently from internalizing factors across this developmental period . Since we found a small and unidirectional relation between binge drinking and adolescent depressive or anxiety symptoms, results provided slight evidence favoring substance induced anxiety and depression models of internalizing risk . As such, results highlight that efforts aimed at preventing early initiation and hazardous or harmful alcohol use may have significant downstream effects on incidence of internalizing symptoms for females within the adolescent period. By contrast, we found little direct evidence of a self-medication model when analyzed at the within-person level. Though links between internalizing symptoms and binge drinking have been observed for adults , present findings may therefore indicate that early-onset internalizing symptoms represent a different developmental pathway unique from adult-onset symptoms that confer elevated substance use risk , or relatedly, that stronger associations have been found with more severe levels or extended histories of substance use and internalizing disorder .

Alternatively, consistent with the common-factor model, the effect sizes observed in this study may also imply minimal direct relation between these two conditions, such that associations observed between internalizing symptoms and binge behaviors may be better explained by common factors giving rise to each. For instance, a number of groups including Goodwin et al. found that after controlling for confounding factors , anxiety disorder was unrelated to all measures of substance use , and support by similar findings for confounding factors have been seen in a number of family and twin studies . In addition, several groups have proposed that genetic contributors and anxiety sensitivity render individuals susceptible to co-occurring anxiety and alcohol misuse ; similarly, common genetic factors have been identified as predisposing towards depression and alcohol dependence . While prior studies controlled for these between-person environmental and genetic factors directly, we analogously used a within-person design to partition factors that may be confounding associations. Employing this statistical approach provided evidence largely consistent with these prior findings, adding that we find only modest and unidirectional associations when sequenced over time. While the NCANDA study has major strengths of being a large, diverse, and prospectively followed sample, we note several limitations. First, episodic variation and measurement may be necessary to more accurately capture self-medication processes, such as in the application of weekly ecological momentary assessment methods ; the CDDR monthly binge drinking and Achenbach depressive symptom metrics from NCANDA may not have had the temporal sensitivity to capture these nuanced levels of association. Relatedly, some evidence suggests that while self-reported recall methods are reasonably accurate for adolescents and young adults at moderate levels , younger populations may under-estimate their alcohol consumption at higher levels of consumption . Thus, the present findings may reflect an underestimation of true binge drinking in the sample and may have tempered effect sizes observed in the present study. Second, it is also possible that other forms of substance use might have stronger links with internalizing pathology across this developmental period. Though our analyses focused primarily on testing theories of alcohol misuse in adolescence and young adulthood,drying cannabis examination of these effects across a wider range of substance outcomes may be a crucial extension of this research. Third, we note that several constraints were imposed on the estimated LCM-SRs in this study, including fixing cross-lagged and autoregressive parameters to equivalence across time.

As such, we encourage results to be replicated in future analyses, ideally in larger national samples of adolescent substance use such as the Adolescent Brain Cognitive Development Study . Fourth, the Youth and Adult Self-Report scales offer several advantages and limitations. Self-report intrinsically allows data to be gathered more easily since participants can describe their own symptoms, thus avoiding the need to meet or speak with a staff member. However, such reported symptoms can be less objective than reported symptoms from a trained, clinician staff member. Clinical scales such as the ASR/YSR capture a range of anxiety and depression symptoms that typically necessitate mental health intervention. This is both a strength and weakness in that we can capture lower level of symptoms, but are also gathering information on participants experiencing lesser symptoms than those having DSM-5 diagnostic criteria for a disorder such as major depressive disorder or generalized anxiety disorder. The ASR/YSR anxiety questionnaire as described in detail in the methods highlights that several different types of anxiety are probed in a mixed fashion, limiting generalizability and specificity to differentiate between types of anxiety disorders such as panic, specific phobias, separation, or generalized anxiety disorders using the results from this NCANDA study. Ferdinand et al. found that YSR anxiety scores predicted DSM-IV disorders only moderately while YSR depressive scores corresponded closely to DSM-IV major depressive disorder and dysthymia . Finally, very limited data was available for the NCANDA study for the context of each episode of binge drinking ; given social drinking factors may play a large role in predicting binge drinking engagement , drinking context could have an important impact on understanding our findings for the depression-binge drinking relationship. Our work provides an investigation of the interrelation between depression or anxiety and binge drinking in the large, diverse, and prospectively followed NCANDA sample. Our work is in line with other studies that have found minimal associations between depression or anxiety and binge drinking , and suggest that binge drinking may modestly predict later internalizing symptoms or that common factors may better explain links between these facets throughout adolescence. This may highlight the importance of simultaneous treatment of binge drinking and co-morbid depressive or anxiety disorders for both males and females. Future larger studies such as ABCD will be able to build on the early findings identified here. Mid-adolescence is a vulnerable developmental period for cigarette smoking uptake, the onset of mental health conditions, and the emergence of comorbid tobacco use and mental health problems . The over-representation of smoking among adolescents with mental health problems generalizes across various conditions , remains robust after controlling for confounders, and is mediated by theoretically-relevant factors suggesting a causal relation . The rapid emergence and appeal of novel tobacco and nicotine products such as electronic cigarettes raises the question as to whether the same adolescent subgroup with mental health problems is at risk for using these products . This is important to address because this population may be particularly vulnerable to nicotine addiction, given that neural plasticity during adolescence and neuropathology in psychiatric conditions can enhance the brain’s sensitivity to nicotine . E-cigarettes—electronic devices that deliver inhaled nicotine emulate the sensorimotor properties of conventional cigarettes—are gaining popularity among adolescents. According to 2014 estimates, past 30 day use of e-cigarettes is more common than conventional cigarettes among U.S. 8th- and 10th- graders, and many adolescent e-cigarette users have never tried conventional cigarettes . E-cigarettes may be an attractive alternative to conventional cigarettes among youth because of beliefs that they are less harmful, addictive, malodorous, and costly than conventional cigarettes . Furthermore, e-cigarettes come in flavors appealing to youth and may be easier to obtain than conventional cigarettes because of inconsistent enforcement of restrictions against sales to minors . Such factors may facilitate e-cigarette initiation in adolescents who would not otherwise smoke conventional cigarettes and may perhaps have fewer risk factors for smoking —including mental health problems.

Classification methods are often utilized to build toward categorical variables, however methods like neural networks are also designed for predicting continuous variables . Regression models are often used for the prediction of continuous measures or in the case of canonical approaches this can be with multiple dependent variables predicted simultaneously . Finally, in the case where there is no existent or optimal category or variable that the biomarkers seek to predict unsupervised approaches can be useful. With all these approaches variables can either be approached as linear or non-linear, although transformations and feature reduction approaches can mitigate these differences. It is important, regardless of approach, to understand the biological mechanisms being modeled by defining a model that best reflects the underlying systems to optimize prediction. Two key methods for statistical reduction of variables are selecting top ranking variables and creation of composite variables by factor or component-based analysis. Random Forest, as depicted in Figure 2, can be utilized to determine importance scores by evaluating the hierarchical functionality of a given variable as a bifurcator for optimizing classification . Random Forest is not alone in its utility to provide variable importance ranking but provides a nice mechanism for this analysis. The statistical creation of composite variables can be done through principal component analysis such that novel values are calculated for a set of variables that account for large swaths of variance with a single value vector . This can substantially increase the efficiency of a model and serve to highlight a robust latent feature. A summary of pain biomarkers discussed in this review article are provided in Table 1. Non-imaging pain biomarkers include opioid pain biomarkers: Beta-endorphin, B-cell opioid receptors, composite genetic, Mu-opioid receptor A118G polymorphisms, migraine opioid PET, and endogenous opioid function. Inflammatory pain biomarkers include cytokines, sICAM-1, cytokines related to back pain,cannabis grow racks cytokines related to peripheral neuropathy, substance P, and neuropeptides. Endocannabinoid pain biomarkers include: AEA in CRPS, 2-AG in optic neuromyelitis, AEA and 2-AG in headaches, ECB elements in multiple non-neuropathic pain conditions, ECB elements in endogenous opioid function, and ECB elements in gut-brain interactions.

There are pain biomarker genes related to neuropathic pain risk. MICRO-RNA dysregulation pain biomarkers are found in neuropathic pain, peripheral neuropathic pain, CRPS, migraine, and non-neuropathic pain conditions. Stress related pain biomarkers include allostatic load, Cortisol, DHEA, and allopregnanolone. Measuring saliva contains potentially particularly accessible pain biomarkers. Other pain biomarkers can be accessed via QST, skin conductance, pupil dilation, fatty acid pain biomarkers , neurotrophic factors, and serum neurotransmitters. Brain imaging pain biomarkers for measuring pain can be evaluated using three different MRI brain methods: gray matter structural imaging, white matter diffusion tensor imaging, and functional brain activation. Brain circuits related to pain mechanisms include an ascending brain circuit, a descending pain modulation circuit, the default mode circuit, the executive network brain circuit, and finally the salience network. Pain mechanisms in the brain can be measured via modulation in brain circuits: acute pain machine learning measures of chronic pain, pain rumination, pain mind wandering, placebo mechanisms, pain traits and states, and resilience. HIV peripheral neuropathy changes in the brain include reduced total cortical gray matter and reduced posterior cingulate cortex volume in particular, white matter degeneration, altered resting state networks, and aberrant expectation of pain relief. By focusing on a broad array of mechanisms and biomarkers, we can uncover important mechanistic connections and interactions across systems. Assessment and understanding in an appropriately comprehensive approach are challenging due to the vast and diverse literature and the complexity measurement. This review aims to facilitate navigation of this literature and the appropriate selection of biomarkers for future research. Health professional shortage areas are communities identified by the U.S. Human Resources and Services Administration in which there is a shortage of primary care health professionals.These shortages are accompanied by an absence of a consistent source of care, difficulty accessing care when needed, and a lack of outpatient preventative care, leading to increased hospitalizations.Multiple interventions have been attempted to increase access to care in HPSAs, including increased use of nonphysician providers. During the opioid epidemic, increasing access to naloxone furnishing has been viewed as critical in rural areas where opioid misuse is disproportionately high, including California’s Central Valley.

In the United States, pharmacists at community pharmacies are one of the most accessible points of care, with 90% of Americans living within 5 miles of a pharmacy.People seeking care have expressed interest in services at pharmacies not only because of ease of accessibility but also the availability of multilingual staff and extended hours that make it possible to access care on evenings and weekends.Previous studies have also shown that pharmacy-based care can extend services for patients in medically under served rural areas to reduce inappropriate prescribing, improve disease management, and enhance medication adherence and knowledge.In 2013, the California legislature passed SB 493, known as the Pharmacy Practice Bill, which expanded the role of pharmacists by giving them authority to furnish naloxone, hormonal contraception, nicotine replacement therapy, and travel medications, specifically prescription drugs and immunizations that are recommended by the Centers for Disease Control and Prevention to prevent or treat disease when travelling outside of the United States.California uses the term “furnish” to describe pharmacist-initiated prescription of medications.Expansion of pharmacist furnishing capabilities provides access to those in need, including people who use opioids.Past studies have sought to determine rates of pharmacist furnishing given its potential impact on access to care. However, these studies have focused on urban areas;previous studies of pharmacist furnishing of naloxone in California sampled primarily urban pharmacies ; previous studies on naloxone, hormonal contraception, and postexposure prophylaxis/preexposure prophylaxis furnishing were conducted in the San Francisco Bay Area only.As of the date of this study, there has been no prior research assessing furnishing rates in California’s Central Valley, a largely rural area, with a shortage of primary care physicians.However, understanding furnishing in these communities and those like it, particularly for naloxone, is critical given the disproportionate impact of the opioid epidemic in rural communities. For example, the age-adjusted rate of opioid-related overdose deaths in Fresno, one of the Central Valley’s largest counties, increased by 46%, from 48.6 per 100,000 residents in 2019 to 71 per 100,000 residents in 2020.This study sought to address this existing gap in research by assessing the extent of pharmacist furnishing, with a focus on naloxone, in the Central Valley. Research focused on the Central Valley due to the high potential impact of furnishing to increase access to care. It first assessed the extent of naloxone furnishing through a phone survey, then identified barriers and facilitators to implementation through interviews with a subset of furnishing pharmacists identified in the phone survey. We expected that rates of naloxone furnishing would be lower in disproportionately rural Central Valley pharmacies than in urban pharmacies evaluated in previous research, given the effects of high out-of-pocket costs in an area where people have lower incomes and social stigma surrounding opioid use disorders in more politically conservative communities.

The first step of data collection was a telephone survey of all pharmacies with the potential to furnish naloxone in the Central Valley,cannabis drying racks to identify overall furnishing rates. Four authors who were PharmD students, in collaboration with undergraduate researchers at the University of California Merced Nicotine & Cannabis Policy Center , first contacted all pharmacies that met inclusion criteria using the telephone number listed in the Board of Pharmacy license database. Using an existing screening question from previously published research on naloxone furnishing, upon initial contact an interviewer posed the question, “I heard that you can get naloxone from a pharmacy without a prescription from your doctor. Can I do that at your pharmacy?” Contact with each pharmacy was attempted up to 3 times. To identify potential interview contacts in the second step of data collection, interviews of furnishing pharmacists, each person at a pharmacy who that indicated it furnished naloxone was asked whether a furnishing pharmacist at the store would be interested in being interviewed for the study. If a pharmacist expressed interest, they received a cover letter, consent forms to sign by email or fax, and a list of interview questions. Researchers scheduled a time to interview after receiving this written consent. Pharmacies that did not furnish naloxone were not asked for interviews on the grounds that they would be unable to identify facilitators to furnishing naloxone at their store.Participants were interviewed in a semi-structured manner using an interview instrument used in previously published research to study furnishing of other medications and modified to address naloxone .This instrument included a list of questions, however each interview was conducted in a semi-structured format that allowed for a natural flow of discussion and gave participants opportunities provide additional information that may not have been specifically addressed in the prepared questions.Topics included the following: characteristics of the pharmacy and staff ; description of the furnishing process; perceptions regarding the effectiveness, advantages, disadvantages, facilitators, and barriers to furnishing; whether respondents also furnished other medications; and recommendations for reproducibility or improvement. Participants were interviewed via video or audio call except in one case, where responses were collected by e-mail. With permission, calls were recorded and transcribed. The interviewers took additional notes during and after the interview.The analysis began with calculation of descriptive statistics, including the percentage of pharmacies that furnished naloxone identified in the telephone survey. For interviews with the subset of naloxone furnishing pharmacists, descriptive analysis summarized the extent of furnishing for medications other than naloxone. Transcripts of each interview conducted, as well e-mail responses, were uploaded to Atlas.ti software for qualitative data analysis and deidentified by numbering each interview. Beginning with codes developed from past research on furnishing practices as a preliminary guide, as well as inductive methods to identify potential novel concepts, the investigators developed a code book classifying statements as referring to barriers or facilitators, then further subdivided them by type in Atlas.ti. Complete sentences were the minimum unit of analysis coded in the transcripts to identify common themes.To ensure validity and consistency across interviews and coding, each interview was conducted by a minimum of 2 researchers, and coding was completed simultaneously by all of the researchers who had conducted interviews. Disagreements were resolved by discussion until the group reached consensus. Transcripts, findings, and key quotations used to illustrate them were summarized in drafts circulated to the entire research team. Findings were triangulated based on reviews of previous studies of furnishing. Only findings identified as relevant by the group were included in the final analysis.The second step of data collection was interviewing furnishing pharmacists in the region for interviews about barriers and facilitators to furnishing. Among the contacted pharmacies that furnished naloxone, 8 furnishing pharmacists agreed to be interviewed. The stores where these pharmacists worked represented 5 of the 11 counties in the Central Valley . Of these, 5 were associated with a chain pharmacy, while the remaining 3 were independent. Although previous research on furnishing rates is limited, it suggests that naloxone furnishing is more common than furnishing of other medications. Interview participants were asked whether they also furnished other medications; as some of the factors that discourage or encourage furnishing may be consistent across medications. Six respondents indicated that the stores where they worked also furnished hormonal contraception, 3 respondents that their stores also furnished nicotine replacement therapy , and 1 that their store also furnished preexposure prophylaxis/post exposure prophylaxis. Respondents indicated that the pharmacies where they worked filled between 250 and 1000 prescriptions per day, averaging approximately 500. The time that respondents had held their positions ranged from 5 months to 20 years, and none had completed a residency. Results are provided in Table 2. With respect to barriers to furnishing, all interview participants listed cost to patients as the primary barrier. They noted that insurance did not necessarily cover naloxone, and when it did not, patients would not purchase it. As one stated, “The biggest barrier to this is first of all money. If it’s zero copay, they probably will take it. If there’s any copay, they’re just normally not going to pay for it.” . Other barriers to furnishing included time, cost, stigma, and lack of a shared language.