Cannabis Grow

Favazza provided cases of extreme and highly unusual forms of self-mutilation in excruciating detail, with an attempt to classify types based on severity. With the provisional emergence of non-suicidal self-injury disorder criteria in the fifth version of the Statistical and Diagnostic Manual of Mental Disorders DSM-V ,the distinction between self-harm as within a normative or pathological range remains equivocal. This is illustrative of the manner in which conceptualizations of self-cutting continue to be embedded in a complex cultural history of changes in the incidence, popular awareness, and social conditions in which such phenomena occur.While it is possible to find clinical, psychometric, survey, and historical approaches to the phenomenon of self-cutting, we lack an ethnographic account with a substantive locus in the interactions of individuals, grounded in the specificity of bodily experience and the immediacy of struggle in the face of existential precarity . In this article, we take a step toward such an account with a discussion situated at the intersection of two anthropological concerns. First is the ethnographic understanding of experiential specificity through anthropological adaptation of phenomenological method . Drawing on this approach, we understand experience as meaningful sensory perception in temporal context and within particular cultural, social, and interpersonal settings and subjectivity as the more or less enduring structure of experience. With respect to mental illness, this approach invites anthropological recognition of struggle as a fundamental human process that comes to light in the context of lived experience . Second is the ongoing anthropological concern with adolescence as a stage in the life course at which identity is consolidated and people approach full cultural membership but which is also fraught with challenges to well-being that anthropology can contribute to understanding in a way relevant to mental health policy and practice .

The contemporary anthropological approach to childhood is strongly influenced by child standpoint theory that aims at an account of society from where children are socially positioned and in which they are not passive social “others” but agentive participants in social life,cannabis grow set up hence co-constructors of social knowledge and by extension of knowledge generated by research. In particular, anthropologists have taken up the idea that “children have agency and manifest social competency” . Guided by these concerns, we will focus specifically on self-cutting among a group of adolescents who have been psychiatric inpatients; by attending to experience and subjectivity articulated in the youth’s own voices, we will come to understand self-cutting as a crisis of agency enacted on the terrain of their own bodies. There is scant literature on how young people conceive and understand mental health , let alone experiential accounts of adolescent mental illness from the standpoint of the child . In addressing the experience of cutting among a clinically defined and diagnosed group of youth, our stance is not to fall prey to accepting a false dichotomy between ethnographic and clinical sensibilities; that a young person is following a regimen of psychotropic medication is as much an ethnographic as a clinical fact, and that a young person lives in a fragmented family environment may have clinical as well as ethnographic implications. Self-cutting can be understood as a troubling symptomatic behavior or as a creative struggle for agency and may exhibit elements of both pathological obsession and ritual transformation, but in either case it is an enactment of a vexed relation between body and world.This discussion is based on SWYEPT, our study of youth in New Mexico who were inpatients in the state’s flag ship Children’s Psychiatric Hospital at the University of New Mexico . New Mexico is a state whose total population according to the 2010 United States Census was 2,059,179. In 2010, according to the US Census Bureau’s categories, by race the largest population proportions were designated “white” and American Indian/Alaska Native , with 23 federally recognized Indian tribes in the state comprising various groups of Pueblos, Navajos, and Apaches; other racial categories were minimally represented.

By ethnicity, Hispanics or Latinos accounted for the largest single block , while among non-Latinos the largest blocks identified themselves as generically white or American Indian . New Mexico is one of the poorest states in the nation. According to the US Statistical Abstract, as of 2008 the median household income was $43, 508 or 44th among the 50 states, and the proportion of persons living below the poverty level was 17.1% or 5th in rank among the states. New Mexico ranks as one of two states within the United States hardest hit by child poverty, with the rate of 30% in New Mexico . Relatedly, home foreclosures have also been inordinately high. Along with poverty comes a serious drug problem, with parts of the state severely afflicted by heroin and methamphetamine use, and the presence of violent gangs, with one anti-gang website listing 178 in the Albuquerque area. The SWYEPT study examines cultural meaning, social interaction, and individual experience among adolescent patients and their families, with the long-term goal of producing knowledge of broad use to those concerned with the treatment of adolescents suffering from mental illness in the context of significant cultural differences. The aspects of this knowledge include: types of problem, illness, or psychiatric disorder experienced by afflicted adolescents; trajectories of adolescent patients from the community into treatment and back into the community; patient experience of therapeutic process and family response to that process; alternative and complementary resources brought into play by families on behalf of patients; difference between the experience of afflicted adolescents and that of counterparts who have not been diagnosed or treated for emotional disturbance. Notably for present purposes, ours was not explicitly a study of self-cutting or self-harm, but cutting emerged within the ethnographic interviews as a theme deserving of the particular attention we devote to it here. We recruited participants for the study with the assistance of three clinicians at Children’s Psychiatric Hospital who referred to us patients aged 12–18 they judged as not so severely cognitively disabled or developmentally impaired as to be unable to participate in interviews and not so emotionally fragile or clinically vulnerable that their participation would be unduly stressful. We obtained informed consent from youth and their parent or primary guardian based on these referrals, grow rack systems recognizing the ethical responsibility of respecting the vulnerabilities of individual patients and the need for continued rapport in the relationship between therapists and families, as well as the importance of our respect as researchers for the clinical expertise of the referring therapists.

All participants entered the project as inpatients at CPH. Assisted by a team of graduate student ethnographers and clinically trained diagnostic interviewers, we conducted ethnographic interviews covering life history and experience with illness and treatment with the young people and their primary parent/guardian three times at approximately six months’ intervals.During this period, we also conducted the child version of the Structured Clinical Interview for DSMIV , a clinician-administered research diagnostic interview , the Adolescent Health Survey , and the Youth Self Report and Child Behavior Check List for children and their parent/guardian respectively. Although initial interviews occasionally took place in the hospital, it was rare for a participant still to be there at the time of the second and third ethnographic interviews. Yet it was not always the case that they were at home, since it was not uncommon for them to be placed instead at another treatment facility of in-treatment foster care. This often led us far a field from the hospital in Albuquerque, such that our ethnography ranged across the entire state of New Mexico and occasionally beyond. In this respect, our work was not strictly speaking a clinical ethnography in the sense of ethnography primarily situated in a clinical context that focuses on the institutional cultural milieu and interactions among patients and staff . Our focus was instead on the experience and subjectivity of the troubled youth along their trajectory back to their families, back again to the hospital, to other institutions, or to treatment foster care. Whenever possible we conducted interviews in participants’ homes both for their convenience and so that interviewers could conduct ethnographic observation of the domestic environment and neighborhood setting. Our primary ethnographic locus was thus the family rather than either the clinic or the community, following the methodological premise that families are the principal formative inter subjective locus for adolescents and for the mentally ill, no less for mentally ill adolescents . Given these caveats, our work could be described as clinical ethnography in a different sense, insofar as it synthesizes clinical and ethnographic sensibilities and approaches . This means not only a balanced attention to diagnostic profile and life experience, but recognition that narrative data generated by diagnostic and ethnographic interviews can be complementary by identifying different kinds of experientially relevant events and themes . The participants constituted an ethnically diverse group including New Mexican Hispanics and Latinos of Mexican descent, Anglo-Americans, and Native Americans. While an ethnically diverse group of youths whose economic and residential conditions vary, the life situations of most are shaped by features of structural violence . Of the 47 adolescents who participated in the research, 57% reported having cut or harmed themselves at some time, comparable to 61% among adolescents hospitalized for psychiatric problems in a previous study by DiClemente, Ponton, and Harley in another North American location. This rate can be understood against the background of a reported rate of 1–4% of self-injurious behavior in the general population , while the rate among adolescents has been placed by various researchers as ranging between 1 and 39% . Let us now take a closer look at cutting among several of these young people in order to get a sense of how they talk about it and what it means to them, its place in the overall configuration of their experience, and the similarities and differences among them that might allow us to characterize cutting as a crisis of agency.SWYEPT participants represent a wide range of diagnostic profiles from a clinical standpoint and a diversity of life experiences from an ethnographic standpoint , but our purpose here is to present a series of vignettes that summarize the range of experiences and utterances centered around the phenomenon of cutting. Lacking space to present full case studies, we briefly examine how they describe their own cutting behavior and what that behavior means in the context of their troubled lives and in the constitution of their subjectivity. We have selected these instances and interview excerpts based on the young person’s relative ability and/or willingness to elaborate on how cutting has been a part of their lives. Each profile includes the biographical and ethnographic context of the young person’s experience, their diagnostic and functional status, medication history, their own experiential commentary, and a brief interpretative commentary. We first met Maria, a Hispanic 17-year-old female, when she was living in a ranch style home in a lower-income neighborhood that was bustling with the activities of her extended family and infant son. During the course of the study, she later lived in an apartment with her son, boyfriend and mother, moving again two years later into a very small apartment with her toddler. Maria was the youngest of three daughters to a single mother with multiple boyfriends and father figures. She bore the physical and emotional marks of a major arm injury in mid-childhood from a car accident in which her extremely drunk mother was driving, as well as enduring severe and catastrophic stressors related to abuse, neglect, and sustained psychosocial instability in her early life. While Maria is close to her older sisters, they were not a significant source of personal or financial support and held an anti-psychiatric opinion about how Maria did not need medication. She relayed that she had to “grow up fast” since her mother had severe problems with alcohol. Indeed, her mother’s alcohol abuse severely affected their relationship. Maria was sexually assaulted at the age of 11 by her mother’s ex-boyfriend, which disturbed her greatly; she marks this as a time of pain and confusion. She grew up believing her adoptive father was her biological father, but when Maria was 15, her father went to fight in Iraq. While in Iraq, he wrote her two letters saying that she was not his biological daughter, and he was getting remarried and could not support her financially or otherwise. She said she was devastated by this, by the fact that he would “cut me out of his life.”

In contrast to the 36-year-old waiver policy that preceded it, GBR guarantees a hospital’s annual revenue by calculating global budget based on market share. Adjustments in global budgets are tied to changes in market share and the state’s gross domestic product. In some ways, GBR is an extension of TPR. However, GBR is not a voluntary program; it requires every Maryland hospital to participate. The main difference is that TPR was implemented in geographically isolated areas of the state where catchment areas are clear. Hospitals under GBR operate in more competitive market environments.In the online appendix, Table A1 lists the names of the Maryland hospitals that are under the GBR program. In the past, hospital revenue was directly linked to the number of medical services that the hospital provided. In contrast, under GBR and TPR, each hospital’s total annual revenue is defined by the HSCRC and known at the beginning of each fiscal year. The hospital margin is the difference between the global budget and annual cost. As a result, hospitals are motivated to control costs while maintaining or growing market share.In this study, we used the difference-in-differences method , which is widely used in healthcare management and policy analysis.DID determines two differences and calculates the treatment or policy effect by determining the difference of the two differences. Examples of studies using DID include that work by Tiemann and Schreyogg on the impact of privatization on hospital efficiency in Germany.

Buchner et al. used DID to study the impact of health system entry on hospital efficiency and profitability.In our study,vertical hydroponic system the first difference is the comparison of a GBR, hospital’s performance before and after GBR implementation. The second difference is the comparison of scores from a group of control hospitals in the same time frame. Finally, we used the second difference from the control group to rule out the part of the first score difference that is not influenced by GBR. This allowed us to estimate the treatment effect within the treatment group. More precisely, GBR adoption was considered the treatment, the hospitals implementing GBR constituted the treatment group, and hospitals not implementing GBR but otherwise similar were considered the control group. This allowed us to identify the treatment effect due to the impact of GBR as opposed to Medicaid expansion or other industry-wide trends. The treatment group was all Maryland hospitals that adopted GBR on January 1, 2014, but did not participate in the TPR program. According to the Annual Report on Selected Maryland General and Special Hospital Services Fiscal Year 2016,10 Maryland has 46 EDs located in general hospitals. Of those 46 hospitals, 10 rural hospitals have participated in the TPR program since July 2010 and are, therefore, excluded from the analysis. The control group includes hospitals from WV, RI, and DE. These three states adopted the original Medicaid expansion on January 1, 2014, at the same time as Maryland, but did not implement the GBR or TPR programs. The main reason that we chose these three as our control group is that Medicaid expansion might have caused and been accompanied by some unmeasurable changes in patient behavior. For example, people who were newly eligible for Medicaid after the expansion would have had different strategies for choosing healthcare providers. We assumed that people from the four states exhibited similar patterns in their reactions to Medicaid expansion. The online appendix section A2 provides the logic behind the selection of the control group.We formatted the final dataset into an unbalanced panel dataset and implemented a mixed-effects, linear regression model with a state-level fixed effect, a hospital-level random effect, and state-level heterogeneity to investigate the impact of GBR implementation on the ED1b scores of Maryland hospitals.

The variables considered in our model are listed in Table 2 .At the patient level, GBR implementation correlates with longer ED LOS for patients being admitted to the hospital. We believe that this implies that GBR has fundamentally changed the way emergency physicians and hospital staff approach the hospitalization decision. The Evaluation of the Maryland All Payer Model Second Annual Report funded by CMS in 2017 emphasized that GBR targeted both healthcare cost and quality.The model has encouraged more workup and interface with case managers in the ED; the objective is to ensure patient safety and high-quality care in the community in lieu of admission for appropriate patients. These changes were likely contributing factors to the increase in the total time span for the care of an ED patient. Future work includes a study on whether and how Maryland hospital EDs adopted new strategies or modified their procedures for healthcare service delivery in response to the implementation of GBR. It remains to be seen if the changes in Maryland hospital EDs had or will have a substantial impact on Maryland’s healthcare system. We found significant differences among the three Medicaid expansion states to which Maryland was compared.Delaware’s score was slightly longer. After applying sensitivity analysis using three alternative control groups, we found that the difference between Maryland’s ED1b and those different control groups remained significant. GBR, a state policy, is correlated with longer LOS for admitted patients. In our study, the state-level fixed effect is significant. Nevertheless, there may well be unidentified confounders that influenced our results. According to Benjamin C. Sun, professor of emergency medicine at Oregon Health and Science University in Portland, “It’s not really fair to compare, say, a public teaching hospital in the middle of New York City that sees 120,000 patients with one that is in a rural area that sees 5,000 patients.”Similarly, it may not be fair to simply compare ED scores across states. Our comparison across states assumes similar demographics and disease burdens, both of which could affect hospital utilization. Also, we are assuming similar admission practices across states.

More particularly, we assume the changes in Maryland inpatient census other than affected by the implementation of Medicaid expansion and GBR can be controlled by our control group. In February 2017, a news report stated that “Maryland ER wait times are the worst in the nation,” a conclusion derived by simply comparing the ED scores published by CMS Hospital Compare.Viewed in this light, interpreting the significant state-level fixed effect obtained in our study without clarifying factors that may be unique or particular to each state, cannabis grow set up might confuse, rather than clarify, perceptions of hospital ED performance. We acknowledge several other limitations in our study. The GBR policy was adopted on January 1, 2014, 10 days after Maryland began Medicaid expansion. The control group hospitals then had to come from neighboring states that also implemented traditional Medicaid expansion at the same time, thus, limiting our control group to WV, RI, and DE. Of these states, RI and DE have few hospitals. Another limitation was the incomplete report data. Overall, the reporting rate of the control group is 75%. According to KFF Total Hospital Reports,31 there should be 290 Hospital Compare data reports from CMS. However, we found only 218 complete reports. It is possible that the missing data might have some impact on our results. Another limitation is the possibility that unmeasured confounding factors may have affected ED LOS. Factors such as hospital closures, demographics, or shifts in access to care could have affected our results. To eliminate the effect of those possible confounding factors, the ideal measure would be the volume of each hospital’s ED visits. CMS started to collect volume data on January 22, 2015. However, some states in our study only started to report this measure on November 10, 2016. Therefore, we selected features other than volume data and note that we might not have been able to eliminate all effects. We were also limited in our choice of performance measure ED1b, which reflects the total time inpatients spend in the ED. Ideally our study would examine both ED1b and the corresponding outpatient measure, OP18. However, CMS only maintains Maryland State OP18 reports going back to January 1, 2014. As there is no data for the pre-treatment period, we cannot study the impact of GBR on the OP18 measure. Our design assumed that residents living in the four geographically close states shared similar reaction patterns to the Medicaid expansion. Then, from an aggregate point of view at the hospital level, we assumed that our control group could rule out the impact of Medicaid expansion on Maryland ED LOS. It is possible that not every hospital was affected by Medicaid expansion at the same proportion, which might have affected the estimates. Also, our secondary finding, the significant difference in time spent in EDs across the four states, should be further investigated by analyzing data from the Nationwide Emergency Department Database.Breaking bad news is considered to be one of the most important, stressful, and challenging responsibilities of a physician.Trainees and experienced physicians alike report being uncomfortable with this task, notably due to a lack of prior training.

For patients, the acknowledgment of this information and their comprehension and perception are of paramount importance to facilitate their psychological adjustment and a long-term quality relationship with medical caregivers.The BBN process has changed drastically over the past decades, moving from a paternalistic medical approach to one of greater patient empowerment, which acknowledges the need for information and results in a greater awareness and clearer understanding of their diagnosis and prognosis.Patients prefer to receive individualized, comprehensive information communicated with warmth and honesty.Patient and family expectations regarding the exact content of news have been shown to be highly variable,making it difficult for healthcare professionals to tailor the information to suit each patient.Bad news in an emergency department may consist in announcing that a relative has been admitted to the ED or in sharing with patients or their families news concerning the need for hospitalization or conditions that might lead to a life-threatening situation sooner or later.BBN in the ED is a particular challenge because the patient is generally meeting the emergency physician for the first time and neither of them enter into the relationship by choice. A recent survey revealed that 78.1% of BBN occurred without previous contact between the patient and the physician. Moreover, history taking, diagnosis, and the acknowledgment of bad news are usually accomplished within a very short time frame during which the physician is confronted with distractions, stress, or time constraints.EP training in communication skills to notify family members of a patient’s death has been reported to be poor at best,leading medical students, residents and young physicians to adopt inappropriate communication behaviors,which in turn significantly increase their stress levels.Inappropriate communication behavior does not take into account the needs of patients or their families. Several guidelines have been developed in oncology to help physicians deliver bad news.One of the most widespread BBN protocols is the SPIKES protocol.28 BBN training in the ED has scarcely been studied to date.The studies undertaken have included a limited number of participants,no validated assessment tools or control group, or were limited to death notification only.In this study, we assessed the effects of incorporating a four-hour ED BBN simulation-based training on self-efficacy, the BBN process, and communication skills among medical students and junior residents who rotated in the ED. We hypothesized that BBNSBT has the potential to increase self-efficacy, the BBN process, and communication skills. BBN skills were assessed in simulation exercises involving two standardized family members played by actors. A randomly selected BBN scenario was used to assess each participant in both pre- and post-test. The scenarios were as follows: 1) a life-threatening situation after a motorcycle accident; 2) a life threatening cardiogenic shock; and 3) brain damage after a fight. Each trainee performed in one random scenario. The scenarios for the pre-test and the post-test were different in order to avoid memorization bias. The BBN skills assessments were video recorded and anonymized. Two blinded raters assessed participants by using two assessment tools. The SPIKES competence form,with 14 items, assessed the participants’ compliance with the SPIKES protocol. Each item was scored as “yes” or “no,” resulting in an overall score . The experts determined a cut-off score using the modified Ang off method.A passing score was 11 and above, and a failing score was below 11. We used the modified Breaking Bad News Assessment Schedule to evaluate communication.

Although we suspect that reducing the number of required questions would free nurses to spend more time on direct patient care and improve efficiency of ED throughput, additional research will be required to study this hypothesis. Studies evaluating ED screening questions often praise their ability to detect at-risk groups without looking at patient oriented outcomes or cost. Cost-benefit analyses should be considered prior to mandating additional nurse screening questions as even a few seconds spent on a question adds up to a significant amount of time.Further studies are needed to determine cost effectiveness of required ED screenings, including questions included as public health screens. Other potential time saving measures, such as self-completed triage questionnaires on kiosks, could be researched as well. Dr. Roberts has delivered an excellent review of many medical aspects of cannabis use and the effect of cannabis legalization on emergency medicine in Colorado.As emergency physician researchers in Colorado, we echo many of his concerns. As he notes, since legalization, we have identified an increase in accidental pediatric exposures, an increase in emergency department visits for hyperemesis ,an increased number of visits attributable to cannabis edibles,a disproportionate increase in adult and adolescent mental health visits related to cannabis, and an increased number of visits for cannabis toxicity.These effects are measurable, and while the direct attribution of these changes to cannabis legalization are limited to observational data that is subject to temporal trends, selection bias, and confounding, we believe the links between these changes and cannabis legalization are plausible, consistent and relevant. While much of the focus in Colorado has been on recreational cannabis drainage system, it is important to note that many of the issues identified began before recreational cannabis was available in 2014. In Colorado, medical cannabis was legalized in 2000 and has been widely available since 2009.

In Colorado, the qualifying medical conditions for cannabis use include the following: cancer, glaucoma HIV, severe pain, seizures, nausea, muscle spasm, post-traumatic stress disorder , autism spectrum disorder, and cachexia.As of June 2019, almost 84,000 patients have an active medical marijuana registration, 337 less than 18 years of age.As with any therapy, the adverse effects we have identified must be balanced against the potential benefits to patients and society. However, there are few high-quality evidenced based studies to support these recommendations. Without clinical trials the measurement of the positive effects of cannabis remain largely anecdotal. There are additional concerns for reported cannabinoid content and claims on treatment for disease. The United States Food and Drug Administration has issued numerous warning letters to various cannabidiol manufacturers for false claims in relation to disease diagnosis and treatment.The medical utility of cannabis is further limited by insufficient training provided to medical professionals and trainees, in addition to the reliance of many users on non-medical providers to guide therapeutic choices. For example, many dispensaries will recommend cannabis to pregnant women despite various national guidelines cautioning against this practice.The medical benefits of cannabis should have been evaluated using accepted clinical standards prior to providing legal status as medical treatments.While some have suggested that it may increase relaxation and reduce stress, there are no clinical studies to support those claims. One plausible health benefit is the substitution of cannabis for other more dangerous recreational drugs; however, this is also not studied. Unfortunately, in Colorado we see that cannabis is also often combined with alcohol and other drugs and the relative increase in adverse effects may outweigh this potential benefit. Despite the observed increase in cannabis related driving fatalities in Colorado, 55% of cannabis users believed it was safe to drive under the influence of cannabis.There have been mixed results on how marijuana legalization has affected medical and non-medical opioid use and prescribing.

The discussion around the impact of cannabis on the healthcare system is not absolute. When we speak to cannabis supporters we often hear the justification that it is safer than alternatives, and there are no real adverse effects. We believe our work has clearly demonstrated that cannabis legalization has measurably impacted the delivery of emergency care in Colorado. However, it is important to put the magnitude of this impact in perspective. Since 2006, more than 2000 Coloradans have died from opioid overdose, and tobacco use-associated healthcare costs in Colorado are almost 2 billion dollars per year. While it is disingenuous to say that cannabis legalization has not impacted emergency medicine in Colorado, it is important to recognize that there are many greater threats to public health and to provide appropriate focus to each of these conditions. A legitimate discussion around the health effects of cannabis in Colorado requires a fair assessment of the risks and benefits by advocates and critics alike. Continued surveillance on both the positive and negative effects on marijuana legalization, and evidence based research is needed as more states continue to pass medical and recreational marijuana. The long-term effects of increased availability of high-THC-cannabis are still to be determined. It is critical for public health officials, healthcare providers and legislators, in conjunction with advocates and industry representatives, to work toward regulations aimed at minimizing the public health impact of cannabis legalization on society. Musculoskeletal injuries are a major cause of morbidity and mortality across the world that disproportionately affect those in low- and middle-income countries , which often lack trained healthcare providers who can properly treat such conditions.Approximately 90% of the five million annual deaths across the world due to injuries occur in LMICs such as Rwanda.The literature lacks an updated fund of knowledge regarding the prevalence, etiology, and treatment for MSIs in Rwanda to supplement previous studies. The growing number of Rwandan healthcare providers may incorporate this knowledge into educational programs when approaching MSI.

Injuries in Rwanda are associated with significant morbidity and mortality.Past studies in Rwanda have shown that most trauma victims are young men.Road traffic accidents , especially those involving motorcycles, were the most common mechanism for adults, while children were frequently injured as pedestrians.Approximately one-quarter of injured patients suffered a fracture.The overall mortality prevalence was 5.5% with approximately half of the hospital deaths occurring in the emergency department .Yet, these mortality figures do not paint a comprehensive picture of the burdens posed by MSIs and fractures in particular. MSIs resulting from trauma are frequently undertreated, causing difficulty for patients to resume normal work and life activities.This is related both to cost and a shortage of technology and supplies.In addition to a dearth of supplies,indoor cannabis grow system achieving health outcome targets without securing the appropriate human resources is difficult.One team in Namibia found that three out of the eight Millennium Development Goals concerning healthcare required appropriate human resources for success.A recent interrupted time-series study found that building Rwanda’s emergency medicine training program resulted in an absolute reduction of overall facilities-based mortality by 4% overall, which was twice as great a decline as the national trend.Such investments are vital to improving health in this region. While Africa contains approximately one-quarter of the world’s burden of diseases, it possesses 4% of its health staff.A recent systematic review found that of 59 LMIC emergency care programs, very few incorporated specialist emergency care training.The largest share of facilities was staffed either by physicians-in-training or by physicians whose level of training was unspecified. Data showed high patient loads and mortality, specifically in Africa where a substantial proportion of total deaths occurred in EDs.Compared to other LMIC regions, ED mortality is highest in Africa, with a median mortality rate of 3.4% compared to the average of 1.8% across all studied LMICs.A minority of LMIC EDs incorporate specialty-trained emergency physicians into the staffing paradigm, but availability is limited.The high volume and urgency of treatment make emergency care an important area of focus for interventions aimed at reducing mortality in these settings. Within a short period of time, Rwanda has made significant improvements to its healthcare system. Rwanda’s transformation of its health sector since the 1990s has helped to raise life expectancy from 27 years to 63 years of age, and nearly all Rwandans have health insurance.Although there have been significant improvements, Rwanda has just 0.84 health providers per 1000 population, the majority of whom are generalists. This number falls below the minimum 2.3 providers per 1000 population set forth by the World Health Organization.In 2011, the Rwandan Ministry of Health began a seven-year partnership with a U.S. academic consortium to train Rwandan providers to become future educators through medical residencies, creating the Human Resources for Health Program. Among the new medical residencies is the first EMTP in Rwanda.These trainees have introduced new emergency skills, such as triage and resuscitation, along with improvements to local protocols and systems.The training curriculum was in line with the American Board of Emergency Medicine 2013 Model of the Clinical Practice of Emergency Medicine.International faculty practicing EM were hired to implement EM training through the HRH program, a collaboration between academic medical centers in the U.S. and the Rwandan Ministry of Health.Within the EMTP curriculum, specific longitudinal educational trainings on the diagnosis and treatments of MSI and fractures were provided through lectures and workshops.

Research studies regarding the epidemiology of injuries and the impact of emergency training on patient outcomes have been conducted, although specific epidemiology regarding fractures and the impact of training on patient outcomes is lacking.The purpose of our research was twofold: 1) to understand the epidemiology of MSI fractures in Rwanda; and 2) to evaluate the progress of the country’s first EM residency program in treating MSI-related injuries by assessing ED mortality rates, length of stay, and complication rates.This was a pre-post study examining the characteristics and outcomes of MSIs before and after implementation of an EMTP at the University Teaching Hospital of Kigali in Kigali, Rwanda. UTH-K is an urban referral and tertiary-care teaching hospital with approximately 560 inpatient beds and 40 ED beds. UTH-K contains a 24-hour Accident and Emergency Department that serves adult patients with acute complaints, as well as pediatric and obstetric trauma patients. Resources at UTH-K include 24-hour surgical coverage, 24-hour access to radiologic services including radiograph, ultrasound, and computed tomography, as well as continuous access to general surgery, orthopedic and neurological specialists.The A&E department is covered by general practice physicians and EM residents. An EM post-graduate diploma program was initiated on November 1, 2013, and most physicians enrolled subsequently participated in the official EM residency, which began in September 2015. Both programs are herein formally referred to as the EMTP. Prior to initiation of these training programs, care was provided exclusively by GPs. Since initiation of EMTP, ED care has been provided jointly by GPs and EM resident-trainees who have oversight by board-certified emergency physicians. All patients who presented at UTH-K during the two data collection periods, from November 2012- October 2013 and August 2015-July 2016, were eligible for inclusion. These preand post-time periods for data collection were chosen to correspond with the absence of an EMTP and implementation of an EMTP, respectively. We identified cases and queried data from institutional records via protocolled methods, as previously described in prior studies.Briefly, using a multi-point composite index generated from an electronic hospital database, we identified all cases during each month of the accruement periods. Subsequently, all cases were coded with a unique identification number and were sampled at random until a sufficient number of records meeting inclusion criteria were identified . We then narrowed the dataset to those with MSI, either with open, closed, or mixed fractures. Next, we applied the following exclusion criteria: incomplete or erroneous evaluation documentation dates from the ED, comprising patients without admission dates, or patients with admission dates that preceded discharge dates. Measured variables included age, sex, mechanism of injury, injury type, hospital vital signs, hospital admissions, surgical interventions, medical treatments, discharge date, and disposition. If more than one anatomical region was indicated as injured, each region was recorded.We did not collect post-discharge outcomes, such as subsequent emergency visits, hospitalizations, or post-discharge death. General MSI epidemiological findings in our 691 patients are outlined in supplements. A total of 17 patients were excluded for incomplete documentation. Of these records, 279 occurred before the start of the EMTP on November 1, 2013, while 395 occurred on or after the start of the program. Thus, patients were divided into pre-EMTP and post-EMTP groups resulting in 674 available patient records .

This is partly due to the fact that poorer neighborhoods lack the social capital needed to resist open-air drug markets. But it also reflects the deleterious effects of our mandatory minimum sentencing policies, discussed below. Finally, drug problems are distributed over time. Musto argues that drug epidemics are dampened by a generational learning process in which new cohorts observe the harmful results of a drug on older users. Building on this idea, Caulkins and his colleagues have developed sophisticated models of how interventions may provide less or greater leverage at different points in a drug epidemic. They argue, for example, that supply reduction measures will be more effective in the early stages of an epidemic but relatively ineffective in a large, mature, established market. Conversely, prevention and treatment may have limited effectiveness early in an epidemic – prevention because its effects are so lagged, and treatment because it interferes with generational learning about drug harms. This work is necessarily fairly speculative at present; we lack enough long term time-series data to permit serious testing of such hypotheses. But their analyses are valuable in encouraging another dimension of more strategic thinking. In 2005, about 46 percent of Americans aged 12 and older had used an illicit drug at least once in their lifetime; 14 percent had done so in the past year, and 8 percent in the past month. Because illicit drug use is so often a fleeting encounter in adolescence,hydroponic system for cannabis drug policy analysts usually view past-month prevalence use as a more meaningful indicator than lifetime prevalence. The 2007 Monitoring the Future annual school survey has the longest running consistently measured time series for substance use in the US. Figure 1 shows trends in past-month prevalence for selected substances for 12th graders .

Several patterns are apparent. First, alcohol remains the most common psychoactive substance among high school seniors. Second, in the most recent year , monthly alcohol and cigarette use each reached their lowest recorded levels. Third, past-month marijuana use reached its peak around 1979, hit a low in 1992, and has stabilized near 20 percent for the past decade. Finally, recent use of cocaine, MDMA, or methamphetamine is fairly rare among high school seniors. MDMA use seems to have peaked at 3.6 percent in the year 2000, cocaine use has remained fairly stable at around 2 percent, and methamphetamine has dropped from 1.9 percent in 2000 to 0.9 percent in 2006. Table 1 shows past-month prevalence of various substances by age category, from the household-based 2006 National Survey on Drug Use and Health . For each substance, young adults were the most frequent recent users, with one exception – heroin. New heroin initiation is rare; the US heroin problem mostly involves an aging cohort of addicts who initiated use in their youth. The overall methamphetamine rates obscure the fact that prevalence remains considerably higher in the Western US than in the Midwest and South and the Northeast , and is higher among whites and Latinos than among African Americans . For a decade there have been claims that methamphetamine, originally a West Coast biker drug, is spreading east, but if so, the diffusion has been fairly slow, and there is no evidence that use is significantly increasing. The fact that someone has used a drug in the past month does not mean they use the drug frequently. As seen in Figure 2, cigarette users tend to be daily users, but most recent users of cocaine and the hallucinogens did so only once or twice in the past month. About a third of marijuana users use almost every day; surprisingly, only half as many alcohol users do so.The prevalence of drug use provides a distorted picture of the actual health and safety harms posed by psychoactive drugs. There are several reasons for this. First, because drug use is only probabilistically related to drug harm, most harms to self and others are attributable to heavy users, and for most substances , a minority of users account for a majority of the quantity consumed. Second, school- and household-based surveys under represent hard core users, who are more likely to be truants, school dropouts, homeless, or institutionalized.

To track the harmful consequences of drug use, analysts generally rely on three types of indicators: Drug mentions in emergency room records, treatment statistics, and drug use among recent arrestees and prisoners. Table 2 shows recent data on the relative impact of the major illicit drugs on these harm indicators. Another major category of drug-related harm is the transmission of HIV. Injection drug use accounts for about a third of all AIDS cases in the US , and non-injection use is associated with an elevated risk of unsafe sexual practices. But there is no reliable way to attribute some fixed percentage of AIDS cases to cocaine use, to marijuana use, and so on. In keeping with our general analytical framework, recall that total harm is the product of prevalence x quantity x average harm. Thus, marijuana – by far the most prevalent illicit – accounts for a sizeable share of all three harm indicators. But relative to their much lower prevalence, it is clear that heroin, cocaine, and methamphetamine are disproportionately harmful substances. A 2007 Lancet article by David Nutt and colleagues offers what is to date the most sophisticated attempt to rate psychoactive substances by their “intrinsic” health and behavioral harms. In decreasing order of harmfulness, the worst five drugs were heroin, cocaine, the barbituates, street methadone, and alcohol. Tobacco was ninth, cannabis eleventh, LSD fourteenth,cannabis drying racks and MDMA eighteenth. If one were starting a society from scratch, it is unclear where one might paint a bright line separating licit from illicit substances, but it is difficult to see why alcohol and tobacco would be more accessible than cannabis or MDMA. But of course, we are not starting a society from scratch. The data in Table 2 are misleading if one wants to rank the intrinsic psychopharmacological harms of drugs – marijuana looming too large – but they are valid indicators if one wants to know the contributions of different substances to social harm under the current regime and with current patterns of use. These kinds of indicators tells us little about how harmful each substance might be in a regime of regulated legal access. Average harm per use might approximate the rating levels in Nutt et al. , though heroin use would become a lot safer per dose. Total harm might differ, if for example legal LSD were to become massively popular. But this might be a short term effect; societies seem to learn from experience and scale back on drugs that are obviously dysfunctional .

The FY2008 national drug control budget allocates 36 percent of drug funding for interdiction and source-country controls, 28 percent for domestic drug law enforcement, 23 percent for treatment, and 12 percent for prevention . We can only offer a whirlwind tour of the empirical literature on these interventions. Readers can find comprehensive assessments in recent monographs by Boyum and Reuter and the National Academy of Sciences . The drug policy literature is enormous and yet remarkably thin, in that rigorous program evaluations are rare. There are some valuable cost-effectiveness analyses , but these are limited by the available descriptive data and some daunting problems of causal inference , and many of the available evaluations were conducted by program developers, raising concerns about intellectual and financial conflicts of interest. In a classic analysis, Reuter and colleagues explained why we should not expect big impacts of efforts to thwart drug production and trafficking. First, it is not possible to completely “seal the borders” against relatively small packages of chemicals that will be sold at very high prices; there are too many possible smuggling routes and tactics, and dealers are very adaptive. Second, the price structure of illicit markets is such that bulk drug products in source countries are “dirt cheap” compared to the high retail street prices in the US. At the source, the economic value is low by US standards but high by local standards. But most of the markup in US prices occurs in the last few links of the distribution chain, within US borders. For example, Caulkins and Reuter note that the wholesale price of cocaine or heroin in a source country is only about 1 percent of its US retail street price. For example $1500 of cocaine in Colombia may be worth $15,000 at the US border, and $110,000 in the US retail street market. Thus even very large seizures in other countries are unlikely to have big effects on local prices. In recent years, defense analysts have used time-series data to argue that interdiction and source-country campaigns actually do have a significant impact on street prices and US demand. But these analyses have been debunked by a National Academy panel , arguing that the apparent correlations are spurious and amplified by selective focus on certain source-country interventions that happened to precede short-term price drops. It does not follow, however, that we could eliminate these programs entirely without a detectable effect. Most analysts believe that interdiction risks do raise prices; it is just that there are probably steeply declining marginal returns to such efforts. Presumably, these programs serve other US political, diplomatic, and economic goals beyond drug policy, laudable or otherwise. But we could probably cut back significantly on these efforts without seeing an increase in US drug consumption. It is estimated that we now have about a half a million drug offenders in state and federal prisons . The staggering increase in the federal prison population, and the role that drug offenses played in that increase, are shown in Figure 3; state prisons show a similar pattern. Drug arrest rates have remained stable for in recent years, so much of the growth in the prison population has been fueled by declining parole rates. What has this massive social experiment bought us? Early in the growth period, around 1992, one could argue that it was correlated with a considerable drop in drug use relative to the late 1970s . But this period of optimism was short-lived. By 1996, about half of the gains were gone, and levels of use have remained fairly stable since then, even as the drug prison population continued to rise. In fact, illicit drug prices have plummeted during a period when massive law enforcement sought vigorously to make drugs more expensive . This is troubling, because prices do matter; contrary to widespread belief, even addicts have been shown to be sensitive to drug prices . From the perspective of prevalence and quantity reduction, falling prices are a serious problem. But conceivably, falling prices may be beneficial from the perspective of harm reduction, because addicts might be expected to conduct fewer income-generating crimes to feed their habit. This is another illustration of the need to confront hard trade offs in thinking about drug policies. The harshness of US marijuana enforcement has long received considerable criticism, and indeed it is difficult to defend . But Caulkins and Sevignywarn against exaggerated concerns about unlucky marijuana smokers rotting away in a prison cell. Although 38 percent of state and federal incarcerations for drug offenses involved simple possession, “for only 2 percent of imprisoned drug-law violators was there no reason whatsoever to suspect possible involvement in distribution…depending on how strict a definition one preferred, one might argue that anywhere from 5,380 to 41,047 people were in prison in the United States solely for their drug use.” On the other hand, many who avoid time in prison do spend time in jail – as much as a third of arrestees in a study of three counties in Maryland . More troubling is the disproportionate imprisonment of African American men.A major factor is the differential severity of mandatory minimum sentences for crack vs. powder cocaine. Under these laws, a dealer would have to sell 500 grams of powder cocaine but only 5 grams of crack cocaine to receive the same five-year sentence. Since crack is more likely to be sold in African American communities, this has greatly widened the racial gap in sentencing.

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,cannabis indoor greenhouse 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. Moreover, many of those who participated in this survey reported being on treatment including methadone, and given high rates of relapse of substance use among those in treatment this suggests many in our survey were at high risk of substance use. When critical services that helped PWUD survive overdose and keep their use under control such as group therapy and MOUD became only virtual during the pandemic, the use of such services declined . Virtual access to care may be particularly challenging for individuals who are unemployed and older as fewer may own and have access to the technology needed for this than younger and employed people. What should also be noted is that fewest of those reporting intermittent use of substances were tested for COVID-19, with more of the daily users getting tested. This may be because reduced social interaction during the pandemic may have lessened situations in which some people use drugs particularly affecting those who used at bars or parties and thereby had less exposure to COVID-19. Some substances are often use for social enhancement particularly by YMSM, and the less social opportunities the less they may have felt like or had opportunities to use drugs reflected in their COVID testing rates. The reduction in social use of substances may also reflect the high rates of overdose that were noted during the pandemic as more people may have used drugs alone without someone to help them or call for help if they did overdose .

Higher testing by those reporting daily use may be because these individuals may access services such as needle exchange or MOUD and may have been offered testing through these services.5 Medical marijuana legalization has become both a medical and legal issue. Papers range from casual discussion, passionate and involved such as those by Annas1 and Okie2 , to serious logical argument exemplified beautifully in Cohen’s3 work. Annas1 and Okie2 focused on California’s 1996 medical marijuana law and the 2005 Supreme Court trial Gonzales v. Raich respectively. Cohen3 had a larger scope, reviewing marijuana’s history in the United States from the colonial era to present-day. While the former sources made mention of some valuable scientific evidence, they did so amidst a great deal of personal appeal and anecdotes about those affected. Quotes from doctors, talking about their personal recommendations for patients to use marijuana, and, admittedly, evocative statements from politicians or newspapers frame the discussions. For instance, Annas quotes a Boston Globe writer’s question asking that if legalizing medical marijuana would send the terrible message to children that “If you hurry up and get cancer, you, too, can get high?”.Cohen’s argument did not lack pathos, but he presented his opinion in a strong logical argument, clearly referencing medical findings. All three papers argued, presuming that sufficient medical evidence exists to prescribe marijuana. They, instead, focused on the issue marijuana’s legality, rather than on analyzing the validity of the cited data. Drug abuse and dependence are important considerations for both FDA and Congressional policymakers. While marijuana is relatively non-addictive, especially when compared to FDA-approved opium, cocaine, and methamphetamine,cannabis growing equipment it remains the most abused drug in America.The authors of “Medical marijuana laws in 50 states: Investigating the relationship between state legalization of medical marijuana and marijuana use, abuse and dependence” analyzed use, abuse, and dependence statistics across the U.S. to measure variance caused by marijuana’s legal status.They concluded that rates of addiction, abuse, and dependence did not vary with overall use, but did not develop the idea much further. To expand upon the study the authors could have spent more time discussing why use rates varied with legality. The authors also could have discussed the consequences of the observed use, abuse, and dependence rates and how they should concern or placate readers. While ample research has been done on the cannabinoids thought to give marijuana its medical value, not all results have been conclusive or widely accepted.

“Endocannabinoids in nervous system health and disease: the big picture in a nutshell” provides a broad yet detailed overview of the endocannabinoid system, which is the biochemical pathway that delta-9-tetrahydrocannabinoland other cannabinoids act upon.Some of the sections within this article require more than a casual knowledge of biochemical pathways, or at least their terminology, to follow. Though it occasionally delves into deeper discussion of biochemical pathways, the paper is not too difficult to follow and certainly delivers a “big picture in a nutshell.Borgelt, Franson, Nussbaum, and Wang and the Harvard Mental Health Letter article “Medical marijuana and the mind”put an emphasis on the pharmacology of marijuana and discuss both the current drug delivery methods and the side effects. These two articles differ drastically in their tone, however. Borgelt, Franson, Nussbaum, and Wang discuss, in detail, the mechanisms by which marijuana elicits its effects. “Medical marijuana and the mind”lists the effects of marijuana and discusses the drugs that contain THC, but doesn’t delve into the pharmacokinetics. Unlike most papers, emphasis was placed upon findings that indicate marijuana may increase psychotic episodes in those with schizophrenia and bipolar disorder. The debate on these findings continues to this day without a clear consensus. The author refrains from discussing precise biochemical pathways in favor of discussing the consequences of each mode of delivery or side effect. By keeping avoiding technical terms when possible, the author achieves a casual tone capable of reaching out to a broad audience. Both “Medical marijuana and the mind” and “The pharmacological and clinical effects of medical cannabis” agree that smoking constitutes the largest barrier to marijuana’s acceptance within the medical community.Should a viable alternative be developed, marijuana could become legal once again. With the exception of Cohen, these two articles have the most balanced discussion of both the pros and cons of medical marijuana in its current state. Increasing amounts of research have been performed on the effects of marijuana smoke and ways to replicate its efficient drug delivery without its harmful side effects. Owen, Sutter, and Albertson8 look exclusively at the harm of marijuana smoke on the lungs as it compares to tobacco smoke. They found that, like tobacco smoke, marijuana smoke increases the risk of “pulmonary symptoms such as wheeze, cough, and sputum production.”However, it may not lead to chronic obstructive pulmonary disease.Somewhat confusingly, the paper also discusses marijuana’s effect on the immune system and cancer cells, which doesn’t seem to be directly related to the title of the paper. Though they explain how marijuana smoke can harm the lungs quite thoroughly, there are often departures into less closely related subjects such as the immune system. As a result, it sometimes feels as though the paper is about the endocannabinoid system as a whole, rather than how marijuana smoke affects the lungs. Hazekamp, Ruhaak, Zuurman, Van gerven, and Verpoorte9 decided to analyze the dosage delivery of the “Volcano” vaporizer. Vaporizers attempt to circumvent the harm of smoke during marijuana inhalation by boiling the THC and cannabinoids into a vapor without actual combustion, which produces most of the harmful particles in smoke. The study discovered that the vaporizer delivered similar amounts of THC as traditional smoking, but with less variance. They state that they used one of the multiple heat settings on the device because, by their calculations, it was the most efficient. Not all users may be able to tolerate that temperature setting, so it would be worthwhile to see if the delivery method remains passably effective at other settings. The examiners pointed out that they only studied THC delivery and, while this is the most studied and well understood cannabinoid present in marijuana, it may not be wholly responsible for marijuana’s therapeutic effect. Consequently, research comparing the delivery of the other compounds is necessary. Uritsky, McPherson, and Pradel10 ran an online survey of hospice workers to determine attitudes towards medical marijuana in the industry. While they found that a majority of responders support medical marijuana, they highlighted several potential flaws with their own research. They only surveyed workers for one company, which may attract employees with particular viewpoints based on its policies. Because the survey was run through a website, responders could have submitted answers multiple times by using different computers. Additionally, a high proportion of workers are either volunteers or unlicensed, so their support might be simple personal opinion rather than the result of research and knowledge about the issue. The questions in the survey seemed appropriate for what the researches sought to discover. Perhaps the imprecision of survey-taking, in general, caused more problems than anything the researchers did.The legacy of the Great Recession, as well as longer term structural changes to the global economy, have disproportionately affected young people . Disengagement from the labour market in young adulthood is particularly concerning because it may lead to long-term negative economic consequences for the individual as well as social problems such as criminal offending . The effects of youth unemployment also inflict large economic costs on society . Research is needed to help governments minimize youth labour market disengagement . In the United Kingdom and Europe, social research and policy making around youth unemployment has focused on a particular subset of young people: Those who, in the transition out of compulsory schooling, find themselves not in education, employment, or training.

The only fentanyl analog detected in 2015 was acetyl fentanyl, which is more potent than heroin, but less potent than fentanyl. Eight new analogs appeared in 2016,12 six more appeared in 2017,13 and seven new analogs appeared in 2018.14 Other non-fentanyl synthetic opioids emerged as well: U-47700 in 2016 and U-48800, U-49900, and U-51754 in 2017.15 In addition, many crime lab samples contain more than one synthetic opioid. About 8 percent of samples with a synthetic opioid contained two or more in 2015 and 2016, 26 percent in 2017, and 19 percent in 2018. Most of these fentanyl analogs and non-fentanylsynthetic opioids have unknown potencies, exacerbating the asymmetric information problem in the illicit opioid market. That is, even if a consumer knew the exact chemical content of their drugs, they still would not be able to determine the potency.16 Comparing Figures 1 and 3, there is a clear positive correlation between the increase of fentanyl related mortality and the increase of fentanyl found in BCI lab tests. However, the aggregate annual state-level counts hide the complexity of the timing of drug seizures sent to BCI labs containing synthetic opioids and overdose deaths at the county-month level. We illustrate these county-level differences in graphs of two counties of similar population size , Montgomery County in southwest Ohio and Summit County in the northeast. Figure 4 shows the strong association between synthetic opioids found by the BCI crime labs and overdose deaths in Summit County. In 2014, the rise and fall in deaths begins to be correlated with the rise and fall in positive fentanyl tests. In mid-2016 there was a rapid increase in deaths at the same time as a rapid increase in positive carfentanil tests.

In 2017, even though deaths fell with carfentanil detections, the level of monthly deaths is generally higher than in 2015, rolling benches hydroponics with less fentanyl detections, but more positive tests for fentanyl analogs. The graph for Montgomery County in Figure 5 shows a very different timing of events. As in Summit County, there are apparent correlations between positive fentanyl tests and overdose deaths. However, the peak in overdose deaths comes a year later than in Summit County, at the same time as the crime labs find a large number of samples of carfentanil and, to a lesser extent, other fentanyl analogs. In addition, there was a large amount of fentanyl found in Summit County in 2015 and a rise in deaths, while fentanyl did not appear in large quantities in Montgomery County until 2016. The patterns in overdose deaths are similar in the two counties before 2014, with close to zero fentanyl-related deaths. Thus, it is unlikely that differences in pre-existing trends in overdose deaths can explain differences in the later timing of the emergence of different synthetic opioids. In addition, given how closely the pattern of drug seizures matches the pattern of drug deaths, the graphs illustrate the potential for county-specific rapid detection systems to more nimbly address the opioid crisis.The main estimates are presented in Table 1. Fentanyl, carfentanil, and other fentanyl analogs are positively correlated with overdose deaths at statistically significant levels. With all 87 counties included in column 1, every one additional observation of fentanyl in BCI crime lab tests in a county in a month predicts an extra 1.16 percent more deaths that month. In other words, if law enforcement finds 10 extra samples with fentanyl in a county with 20 monthly overdose deaths on average, we would expect an extra 2.4 deaths that month. Carfentanil positive tests are associated with more deaths than fentanyl: with 10 extra positive tests in a county with 20 monthly overdose deaths on average we would expect an extra 3.6 deaths that month. The coefficient for other fentanyl analogs is smaller than for fentanyl or carfentanil and has less statistical significance. 10 more positive tests of other fentanyl analogs in a county with 20 monthly overdose deaths on average is associated with an extra 1.8 deaths that month.

Summarizing, we find that changes in the presence of crime lab tests for synthetic opioids are useful as indicators of changes in the short-term risk of overdose deaths. Robustness tests are presented in Appendix B. To control for changes in over time in the number of tests, we also provide estimates using the fraction of tests that are positive in a county-month as independent variables instead of test counts Table B1. Heroin lab tests do not have a statistically significant relationship with drug deaths in the main specification. However, in Table B1, there is a negative relationship between the fraction of tests in a county-month that contain heroin and overdose deaths, statistically significant at the 1 percent level. We are unable to determine the specific underlying cause of this correlation. One possible explanation is that these estimates are picking up the shift from heroin to higher potency synthetic opioids. After 2014 the fraction of lab tests containing heroin not mixed with a synthetic opioid falls substantially while lab tests of heroin mixed with synthetic opioids and synthetic opioids in general increase. It is possible that drug sellers and consumers modify their behavior to reduce risk in response to an increasingly deadly illicit drug market, biasing the estimates towards finding a negative relationship between deaths and the amount of synthetic opioids in drug tests. However, given the short time-span of the observations, it is more likely that this negative effect is observed months later: counties with a relatively large amount of deadly synthetic opioids in month T, may observe a relative decline in deaths in later months as the drug market, consumer behavior, law enforcement,hydro tray or harm reduction services respond to reduce the risk of overdose death. To investigate the relationship between the timing of lab tests and overdose deaths we re-estimated the main Poisson regression changing the dependent variable to overdose death counts for the three months before and after the observed crime lab data, which is shown in Table 2.

Fentanyl tests are positively correlated with contemporaneous overdose deaths and with about half the magnitude and less statistical significance, are positively correlated with future overdose deaths as well. Carfentanil tests have a different pattern, with positive statistically significant coefficients in the prior three months, and a decrease in the correlation over the next three months with a reduction in the risk of overdose death three months later. There are several possible explanations for the lag and lead pattern for carfentanil. For example: 1. the illicit drug market responded to the high number of deaths by making drugs relatively safer, 2. there is an increase in harm reduction services, law enforcement presence, and reduction in risk taking by consumers, or 3. carfentanil killed illicit drug users who are the most likely to die from an overdose in general leaving a smaller population of risky drug users later and, thus, having little apparent effect on overdose deaths later on. Other fentanyl analogs have an opposite relationship over time relative to carfentanil. Other analogs are negatively correlated with deaths two or three months prior, while the positive correlation if anything increases for the three months after. These findings indicate that more rapid testing, particularly for carfentanil,may be needed to have a meaningful impact. Fentanyl and other fentanyl analogs, however, are persistent problems allowing more time to respond to the release of crime lab data. There are large differences across counties and including them all in the main estimates may hide risks, particularly in smaller counties with fewer deaths. To investigate the potential for heterogeneous effects across counties, we divide the sample into counties with populations under 50,000 , between 50,000 and 100,000 , and 100,000 and above.17 The estimates are presented in the estimation tables in columns 2 to 4. Perhaps unsurprisingly, the main estimates are driven by the largest counties, which also have the most overdose deaths. Interestingly, the coefficient for carfentanil is only statistically significant in large counties. In the smallest counties, other fentanyl analogs are the only drug that is statistically significantly correlated with overdose deaths. These estimates indicate that the newly evolving fentanyl analogs may be playing a particularly dangerous role in low-population areas, which is hidden in the aggregate statistics, although we have no a priori reason for this empirical finding and leave it to future research to investigate why this may be occurring. These differences across county sizes are reinforced by linear regression estimates in robustness Table B3 in Appendix B, where the overdose death rate per 100,000 adults is the dependent variable. The estimates in Table 6 should be read with some caution, as there are large standard errors when deriving death rates from small numbers of deaths, and these errors will be amplified in small counties.

In column 1, which includes all counties, the coefficients for fentanyl, carfentanil, and other fentanyl analogs are all statistically significant at the 1 percent level and the magnitude of the other fentanyl analogs coefficient is larger than that for carfentanil. Given that an extra death in a small county has a much larger impact on the death rate than in a large county, and other fentanyl analogs are particularly important for explaining overdose deaths in small counties, it makes sense that they would be more strongly correlated with the overdose death rate than the overdose death count. Aggregating all the different analogs together as if they were the same may be hiding the relatively high or low dangers of certain analogs. In Table B2, instead of aggregating, we in-clude separately the seven most common fentanyl analogs in the data as independent variables.18 The table includes estimates by county size as well. Only acryl fentanyl, similar in potency to fentanyl but much less potent than carfentanil, has a statistically significant positive coefficient regardless of county size. These results provide more evidence of the potential to use the crime lab data for a future early warning system: the data indicates an increased risk of deaths if acryl fentanyl is found in large quantities. Acetyl and 3-methyl fentanyl are only associated with more deaths in medium sized counties, and 4-FIBF and methoxyacetyl fentanyl are only associated with more deaths in small counties.19 Cyclopropyl and furanyl fentanyl have no statistically significant relationship with overdose deaths. However, this lack of statistically significant relationships may be due to the small numbers in the crime lab data, so one should not take these estimates to mean that we should be unconcerned about future increases in the availability of these fentanyl analogs or the emergence of new fentanyl analogs. Rather, they should be seen as part of ongoing research that should be updated to include new data to find new predictors of overdose death. The economic controls have some statistically significant correlations with overdose deaths: a higher poverty rate is associated with more overdose deaths, although a higher unemployment rate is associated with fewer deaths. The first finding is logical: an increase in poverty could increase the demand for illicit drugs, while the second finding is less intuitive. Unemployment rates were trending down over the period. Counties that had large drops in unemployment over the time period happened to be smaller counties on average with few overdose deaths. Those with a smaller decrease in unemployment happened to be larger counties on average with many more deaths. Thus, the coefficient for the unemployment rate may be picking up population size differences. More or fewer MEDs of prescription opioids per capita do not have a statistically significant relationship at the 5 percent level with overdose deaths exceptin the restricted sample of medium sized counties in column 3 of the estimation tables, where they have the expected signs: an increase of non-Suboxone opioids is associated with more overdose deaths while an increase in Suboxone is associated with fewer overdose deaths. The coefficient for positive tests of non-opioid drugs generally either lack statistical significance or have inconsistent relationships with overdose deaths across specifications. For example, lab tests finding benzodiazepines have a negative and statistically significant correlation with overdose deaths in Table 1, columns 1 and 4, at the 5 percent level. However, there is positive correlation under OLS estimates, and statistical significance disappears in Tables B1 and B3. Thus, although we think the estimates indicate the potential value of further research into the role of these drugs, we caution against reading too much into any specific coefficient for non-opioids.

The brain of an adolescent, much like teenage behavior, undergoes significant developmental changes. This neurodevelopment continues after adolescence, typically until around age 25.The maturational processes in the brain occur in stages, with more basic functions maturing first and areas such as the lateral temporal and frontal lobes, which are responsible for higher cognitive function , developing later in adolescence.Its rate of change does not plateau until the third decade of life, in concert with typical developmental trajectories of cognitive abilities, such as decision-making, attention, and cognitive control.The late maturation of the prefrontal cortex has been linked to risky behavior during adolescence, particularly if the limbic subcortical system develops earlier.Executive functioning typically matures during this developmental stage,coincident with gray matter reductions and white matter growth.Functional magnetic resonance imaging studies of executive behaviors have demonstrated increasing prefrontal activity and better inhibitory control with adolescent age.Challenges in executive functioning have been observed in adolescents with a family history of alcohol use disorder ,repeated childhood trauma experiences,and poor sleep,all of which also have been identified as risk for adolescent binge drinking and AUD.Deficits in control circuitry have been linked to impulsivity, sensation seeking, and alcohol use into early adulthood.One of the studies investigating adolescent alcohol use and its effects is coordinated by the National Consortium on Alcohol and Neurodevelopment in Adolescence , which is conducting a multisite longitudinal study supported by funding from NIAAA and other National Institutes of Health partner institutes. Launched in 2012,4×8 grow table with wheels this five-site consortium recruited a community cohort of 831 diverse adolescents ages 12 to 21 from five U.S. regions. Half the sample was enriched for key characteristics conveying risk for heavy drinking among adolescents. 

Most of the sample reported very limited alcohol use at project entry; the remaining 15% exceeded typical age thresholds for alcohol at project entry in this cohort-sequential design.At project entry and annually thereafter, participants received neuroimaging , neurocognitive testing, detailed substance use and mental health interviews; provided urine samples for drug testing as well as saliva samples for genetics and pubertal hormone assays; and completed various self- and parent reports on personality, behaviors, and environment.NCANDA will continue to examine the interactive effects of typical development as well as adolescent alcohol use and executive dysfunction into early adulthood. Resting-state fMRI findings from NCANDA and other studies have shown that intrinsic functional networks sub-serving cognitive control and limbic circuitry develop across adolescence and may be influenced by adolescent heavy drinking.Moreover, the adverse effects of alcohol may be more prominent in girls than in boys.Being able to identify youth at higher risk for alcohol misuse could lead to early intervention and ultimately help reduce the significant personal and public health burden of AUD; however, relatively few studies have explored individual-level precursors of adolescent alcohol use. Prospective longitudinal studies of substance-naïve youth are uniquely positioned to identify factors predating the onset of alcohol use. Squeglia et al. identified several markers of alcohol initiation by age 18 in 137 adolescents.These markers included demographic and behavioral factors , lower executive functioning, thinner cortices, and less brain activation in diffusely distributed brain regions. NCANDA seeks to expand on these findings using a greater number of measurements in a large sample to lead to more accurate individual-level forecasting. The consortium is employing machine learning models, which can avoid multiple-comparison correction and reduce measures to a single, individual-level prediction.NCANDA developed a model that distinguished youth who drink heavily from those who drink little or no alcohol, based on patterns of macrostructural and microstructural imaging metrics in multiple brain regions.The analyses suggested delayed development of white matter connectivity among the older youth in the sample who drank heavily, as well as increased risk of subsequent heavy drinking in youth with more externalizing symptoms.

These findings fit closely with those from the IMAGEN Consortium, which found that variability in personality, cognition, life events, neural functioning, and drinking behavior features predicted Alcohol Use Disorders Identification Test scores at ages 14 and 16.Unlike white matter, gray matter volume peaks in the primary school-age years, around age 10.Squeglia et al. reported that youth who drank heavily showed accelerated reductions in gray matter volumes in cortical lateral frontal and temporal areas compared to those who drank no or little alcohol.39 These results were largely unchanged with co-use of marijuana and other drugs; also, similar patterns of developmental trajectory abnormalities existed in males and females. This finding was replicated in the NCANDA cohort, which examined the influence of alcohol use on gray matter structure in 483 adolescents ages 12 to 21 both before and 1 to 2 years after the onset of heavy drinking.For youth with no or low alcohol consumption, gray matter volumes declined throughout adolescence, with rates slowing in many brain regions in later adolescence. However, youth who initiated heavy drinking exhibited a steeper decline in frontal gray matter volumes. For both youth with no or low alcohol consumption and those with heavy drinking, cannabis use did not influence gray matter volume trajectories. These findings were confirmed in a recent analysis spanning five time points in the NCANDA study and using linear mixed effects models.A greater number of past-year binge drinking episodes was linked to greater decreases in gray matter volumes in 26 of 34 bilateral Desikan-Killiany cortical parcellations tested. The strongest effects were noted in frontal regions as well as among younger adolescents; moreover, the effects largely attenuated in later adolescence. The gray matter volumes decreased most for individuals with greater numbers of binge drinking episodes and recent binge drinking. These findings provide yet more evidence that adolescent binge drinking is linked to a greater risk of more prominent gray matter reductions during adolescence.Functional MRI studies further suggested that adolescents with histories of heavy drinking showed aberrant patterns of activation in response to cognitively challenging tasks, including tasks of working memory and inhibition. In adolescents with a history of 1 to 2 years of heavy drinking,grow tray stand the aberrant activation was not linked to detectable deficiencies in task performance.

However, if heavy drinking persisted longer, reduced task performance was often evident in the adolescents.This pattern of results suggested that the brain may be able to compensate for subtle neuronal insults for a period of time, but if drinking patterns persist and become heavier, the brain may no longer be able to compensate and may be vulnerable to the effects of repeated and sustained heavy doses of alcohol.Throughout adolescence, white matter volume increases and matures, resulting in myelination that increases speed of neuronal transmission and modulates the timing and synchrony of neuronal firing patterns that convey meaning in the brain.Squeglia et al. reported that adolescents who drank heavily showed attenuated white matter growth of the corpus callosum and pons relative to adolescents who did not drink.Pfefferbaum et al. indicated that among those in the NCANDA sample who consumed no or little alcohol, white matter regions grew at faster rates in younger age groups and slowed toward young adulthood.To examine the potential for a neurotoxic effect of alcohol use on adolescent development of white matter, Zhao et al. conducted a whole-brain analysis of fractional anisotropy of NCANDA participants ages 12 to 21 at baseline.For 63 adolescents who initiated heavy drinking, the researchers examined white matter quality before and after drinking onset and compared it to the white matter maturation trajectory of 291 adolescents with no or low alcohol consumption. Results showed deterioration of white matter integrity in youth who drank heavily compared with age- and sex-matched controls. Moreover, the slope of this reduction over time corresponded with days of drinking since the study entry.Within-subject analyses contrasted developmental trajectories of youth before and after they initiated heavy drinking. These analyses suggested that drinking onset was associated with, and appeared to precede, disrupted white matter integrity. This disruption was greater in younger adolescents than in older adolescents, and was most pronounced in the genu and body of the corpus callosum.It is possible that these brain structure changes may occur concomitantly with modifications in certain neurotransmitter and hormone secretion systems, which markedly influence the refinement of certain brain areas and neural circuits.Along with altered development and maturation of gray and white matter, studies have reported neurocognitive consequences of underage drinking, such as impairments in attention,verbal learning,visuospatial processing,and memory.Neurocognitive deficits linked to moderate to heavy drinking during this critical developmental period may lead to direct and indirect changes in neuromaturational course, with effects that may extend into adulthood. Squeglia et al. examined neurocognitive function in adolescents who drank heavily, moderately, or not at all, based on the Cahalan classification system.

Their findings suggested that initiation of moderate to heavy alcohol use and incurring hangovers during adolescence may adversely influence neurocognitive functioning. For females, more drinking days in the past year predicted a greater reduction in performance on visuospatial tasks, in particular visuospatial memory, from baseline to follow-up. For males, a tendency was seen for more hangover symptoms in the year before follow-up testing to predict a relative worsening of sustained attention.Another set of studies demonstrated that youths who drank heavily exhibited greater brain activation while viewing alcohol advertisements than while viewing ads for nonalcoholic beverages. Adolescents are exposed to alcohol advertising materials on a daily basis in many countries. As studies in adults with AUD have shown atypical responses to alcoholrelated materials,Tapert and colleagues used fMRI analyses to determine whether similar response patterns existed in adolescents who drink.The study included 15 adolescents ages 14 to 17 with AUD and 15 demographically similar adolescents who drank infrequently. The participants were shown pictures of alcoholic and nonalcoholic beverage advertisements during neuroimaging. Adolescents with histories of heavy drinking showed greatly enhanced neural activation while viewing the pictures of alcoholic beverages compared with pictures of nonalcoholic beverages. The extent of alcohol-related activation was greatest for those with the highest levels of monthly alcohol intake. In contrast, youth with limited drinking histories showed similar levels of activation while viewing the two beverage picture types. These results demonstrated pronounced alcohol cue reactivity in heavy drinking teens, particularly in reaction to alcohol advertising materials. Studies examining longer-term impacts of adolescent alcohol misuse have yielded mixed results. Some studies reported a maturing-out without significant consequences in adulthood, while others found ongoing effects on mental health, physical health, and social functioning, as well as higher levels of alcohol use and AUD.Analyses using data from the National Longitudinal Alcohol Epidemiologic Survey determined that 40% of those initiating alcohol use before age 15 were diagnosed with AUD at some point in their lives compared to only 10% of those who delayed the onset of drinking until age 21 or later.The first study of adolescents to assess the association between age of adolescent drinking onset and neurocognitive performance found that earlier age of drinking onset predicted poorer performance on tasks requiring psychomotor speed and visual attention. Similarly, an earlier age of onset of regular drinking predicted poorer performances on tests of cognitive inhibition and working memory.This study suggested that early onset of drinking increased risk for subsequent neuropsychological dysfunction.Several studies have reported that the associations between alcohol and brain structure and function differ by sex, especially in adolescents engaging in binge drinking. While not conclusive across the literature, female adolescents who engaged in binge drinking appeared to show effects such as blunted activation in frontal, temporal, and cerebellar cortices compared to females who did not drink, whereas male adolescents who engaged in binge drinking showed the opposite activation pattern.Female adolescents ages 15 to 17 meeting criteria for AUD showed larger prefrontal cortex volumes than female controls, while male adolescents with AUD had smaller prefrontal cortex volumes than male controls.A similar finding was observed for white matter.Adolescence is the peak time for both onset of substance misuse and emergence of mental illness, including anxiety disorders, bipolar disorder, major depression, eating disorders, and psychosis.The National Survey on Drug Use and Health estimated that 20% of adolescents had a mental illness that persisted into adulthood.Moreover, adolescents with a past-year major depressive episode were more likely to be current binge alcohol users.However, it remains unclear how comorbid mental health problems contribute to and exacerbate the neurobiological effects of alcohol misuse.

A Canadian trans woman working at a grocery store described the need to advocate for herself in response to negative encounters in the washroom: “There have been a few times when we’ve had new people come into the store, new employees, and they’ve had a problem with me using the woman’s washroom. That is just something that I will not stand for. I just go straight to whoever is the manager on duty, and I don’t leave it as optional. It’s like, “You will talk with this person now.” Although she had been successful in getting management to quickly respond to problems with coworkers, sharing bathrooms with customers raised an additional set of anxieties and challenges. One grocery worker from the West Coast spoke about wanting to use the men’s room but not feeling comfortable using a facility that was shared with customers.Local unions are playing an active role in ensuring access to gender-neutral bathrooms as a basic working condition.Guaranteeing access to proximate, single-occupancy, gender-neutral bathrooms is a structural solution that not only increases safety and dignity for transgender and nonbinary workers but can also help address a range of other bathroom privacy needs.Chemotherapy-induced nausea and vomiting can be classified into three categories: acute onset, occurring within 24 h of the initial chemotherapy administration; delayed onset, occurring 24 h to several days after the initial treatment; and anticipatory nausea and vomiting. Anticipatory nausea develops in response to chemotherapy treatments,indoor plant table in which cytotoxic drugs are delivered in the presence of a novel context. Developing in approximately 30% of patients by their fourth treatment , AN has traditionally been understood in terms of classical conditioning.

After one or more treatment sessions, a conditional association develops between the distinctive contextual cues of the treatment environment and the unconditioned stimulus of chemotherapy treatment that results in the unconditioned response of post-treatment illness experienced by the patient. Subsequent exposure tothe treatment environment results in the patient experiencing a conditioned response of nausea and/ or vomiting before initiation of chemotherapy treatment. Once it develops, AN has been reported to be especially refractive to anti-emetic treatment. The evaluation of potential treatments for AN would be accelerated by the establishment of a reliable rodent model of nausea. Although rats are incapable of vomiting, they display characteristic gaping reactions when exposed to a flavoured solution previously paired with lithium induced nausea. In fact, this gaping reaction in the rat requires the same orofacial musculature as that required for vomiting in other species. Only drugs that produce emesis in species capable of vomiting produce conditioned gaping in rats, although many nonemetic drugs produce conditioned taste avoidance. Furthermore, anti-emetic drugs interfere with the establishment of conditioned gaping reactions elicited by a nausea-paired flavor, presumably by interfering with the nausea. Not only are flavor cues capable of eliciting conditioned gaping reactions when paired with lithium chloride – induced nausea in rats, but recently Limebeer et al. have demonstrated that re-exposure to LiCl-paired contextual cues also elicit conditioned gaping reactions in rats. This paradigm more closely resembles that reported to produce AN in chemotherapy patients. Rats were injected with LiCl or saline before placement in a vanilla-odor laced chamber with lights and texture different than their home cage on each of four trials, separated by 72 h. To equate both groups for experience with illness, the rats in group unpaired were injected with LiCl and those in group paired were injected with saline 24 h after each conditioning trial but were then simply returned to their home cage. When the rats were returned to the conditioning context, 72 h after the final conditioning trial, rats in group paired showed the conditioned gaping reaction, as a measure of AN.

Although classical anti-emetic treatments such as the 5- hydroxytryptamine-3 antagonist, Ondansetron , effectively reduce unconditioned nausea and vomiting, they are ineffective in the alleviation of conditioned nausea once it develops in humans. Indeed, OND also did not suppress the conditioned gaping reactions displayed during re-exposure to the LiCl-paired context. Furthermore, using the emetic species, Suncus murinus as an animal model for AN, pre-treatment with a dose of OND that was shown to alleviate acute vomiting , did not reduce the display of conditioned retching reactions during re-exposure to a nausea-paired context. Thus, although OND has proven effective in the reduction of acute post-treatment nausea and vomiting, it does not appear to relieve conditioned nausea when it does develop. The psychoactive component in marijuana— delta-9-tetrahydrocannabinol —has been shown to interfere with the expression of vomiting in shrews and ferrets and conditioned gaping reactions elicited by a lithium-paired flavor in rats. The Δ9 -THC-induced suppression of conditioned nausea could be reversed by a CB1 receptor antagonist/reverse agonist , implicating the CB1 receptor in this effect. Limebeer et al. demonstrated that, unlike OND, Δ9 -THC also interfered with the expression of conditioned gaping elicited by the LiCl paired contextual cues in rats. This finding was consistent with the demonstration that Δ9 -THC, unlike OND, also suppressed the expression of conditioned retching in shrews when returned to a LiCl-paired context. The primary non-psychoactive compound found in marijuana, cannabidiol , has also been shown to suppress nausea and vomiting. In shrews, vomiting elicited by LiCl is suppressed by low doses of CBD, while higher doses were found to facilitate vomiting, rather than reducing its expression. Additionally, CBD reduced conditioned retching in shrews elicited by a lithium-paired context. In rats, a dose of 5 mg/kg CBD interfered with the establishment of conditioned gaping elicited by a LiClpaired flavor, as well as its expression. Because CBD has not been shown to bind with known CB receptors,plant growing stand this suppression of nausea and vomiting does not appear to be linked to activity of the CB1 or CB2 receptors. 

These results suggest that the primary nonpsychoactive compound found in marijuana may be a useful treatment for conditioned nausea. Arachidonylethanolamide or anandamide is an endogenous agonist for cannabinoid receptors which is rapidly degraded by the fatty acid amide hydrolase that is distributed throughout the brain and periphery. The action of AEA can be prolonged by inhibiting its degradation, through the use of URB597 , an FAAH enzyme inhibitor, that can increase basal levels ofAEA in the rat brain. URB administration has been shown to reduce the establishment of conditioned gaping elicited by LiCl-paired saccharin solution in rats. Thus, prolonging the action of AEA with the FAAH inhibitor URB has been shown to suppress the establishment of conditioned nausea in rats. The experiments described below evaluated the potential of the non-psychoactive component of marijuana, CBD, and the FAAH inhibitor, URB, to interfere with conditioned gaping elicited by a LiCl-paired chamber in rats. On each of four conditioning trials, rats were injected with LiCl-paired immediately before placement in a distinctive context laced with the odor of vanilla extract. After the conditioning trials, the rats were injected with CBD or URB before placement in the distinctive CS context. Additionally, experiment 2 evaluated the potential of the CB1 antagonist/ inverse agonist, SR141716A , to reverse the suppression of conditioned gaping produced by URB. Finally, in experiment 3, the ability of URB to interfere with the establishment of conditioned gaping was also assessed. In each experiment, to ensure that the suppression of conditioned gaping was not merely an artefact of drug-induced suppression of general activity, the number of seconds that the rats remained immobile was recorded as a measure of activity. The doses of CBD were selected on the basis of our previous work demonstrating that these lower doses suppressed lithiuminduced vomiting in the shrew, but higher doses potentiated vomiting. Furthermore, a dose of 5 mg/kg of CBD interfered with the establishment and the expression of conditioned gaping elicited by a lithiumpaired flavour. The doses of URB were chosen based upon results showing that in vivo FAAH activity is blocked with a half-maximal inhibitory dose of 0.15 mg/kg ip with concurrent increase in brain AEA. Additionally, a dose of 0.3 mg/kg has been shown to attenuate the establishment of conditioned gaping elicited by a flavored stimulus.When re-introduced to a context previously paired with LiCl, rats display conditioned gaping ,a measure of conditioned nausea. The expression of this gaping reaction is not reduced by pre-treatment with a classic anti-emetic agent, OND, as has been reported by human chemotherapy patients; however, the psychoactive component in marijuana, Δ9 -THC, did suppress conditioned gaping elicited by a LiCl-paired chamber. 

In agreement with the gaping data with rats, Parker et al. reported that shrews display a conditioned retching reaction when re-introduced to a chamber previously paired with LiCl and this conditioned retching reaction was suppressed by pre-treatment with Δ9 -THC or CBD, but not OND. The present findings provide additional support for the potential of cannabinoid treatments to suppress AN on the basis of results with the rat gaping model. Experiment 1 demonstrated that low doses of CBD that suppressed LiCl-induced vomiting and conditioned retching in the shrew as well as the establishment and the expression of gaping elicited by a LiCl-paired flavor in the rat , also suppressed the expression of gaping elicited by LiCl-paired context in the rat. A low dose of 5 mg/kg CBD has also been reported to serve as an effective anti-inflammatory agent , as well as a neuroprotective antioxidant. As CBD is a non-psychoactive component in marijuana, the ability of CBD to suppress conditioned gaping is promising for its use in the suppression of AN. The effective anti-nausea range of CBD appears to be narrow because at the highest dose tested , CBD did not suppress the expression of gaping elicited by a LiCl-paired context. Our previous work with the Suncus murinus revealed that although doses of 1–10 mg/kg CBD reversed LiCl-induced vomiting, higher doses potentiated LiCl-induced vomiting. It is possible, that CBD also produces a biphasic effect on the expression of conditioned gaping with lower doses reducing the expression of conditioned gaping, but higher doses enhancing the expression of gaping elicited by a LiCl-paired context. Experiments 2 and 3 demonstrated that the FAAH inhibitor, URB, also suppressed the display of AN as measured by gaping in rats. Presumably, prolonging the action of endogenous AEA produced an anti-nausea effect when rats were re-exposed to the LiCl-paired context. The effect of URB on the expression of conditioned gaping was dose-dependent, with 0.3 mg/kg serving as the effective dose. The suppression of gaping by URB was reversed by pre-treatment with the CB1 antagonist/inverse agonist, SR141716A, suggesting a CB1 mechanism of action. URB also interfered with the establishment of conditioned gaping when administrated before each pairing of the contextual stimuli with LiCl. This finding was consistent with that recently reported by Cross-Mellor et al. demonstrating that URB interfered with the establishment of conditioned gaping elicited by exposure to a LiCl-paired flavor. Presumably, URB reduced the nausea produced by the LiCl resulting in weaker conditioning. The potential of CBD or URB to suppress the gaping reactions during re-exposure to the context previously paired with LiCl-induced nausea might also be accounted for by interference with memory for the previously established association, rather than by interference with conditioned nausea per se. The design of the present experiments cannot discriminate between these two potential mechanisms; however, a memory deficit explanation is less tenable in light of the finding in experiment 1 that the highest dose of CBD did not modify the expression of gaping. Furthermore, at a dose of 5 mg/kg CBD neither affected the acquisition nor retrieval of a floor-amphetamine association in a conditioned place preference task or of a flavor-lithium association in a conditioned taste avoidance task. Finally, Varvel et al. reported that mice pre-treated with the FAAH inhibitor, OL-135, as well as FAAH knockout mice with elevated central AEA levels, did not display memory impairment or motor disruption in a spatial memory task ; in fact, the FAAH knockouts displayed a significant increase in acquisition rate. The unpleasant experience of AN reported by chemotherapy patients may impact the patient’s resolve to continue treatment. Because classic anti-emetics such as OND have proven ineffective in the alleviation of AN, there is a need to develop effective pharmacotherapies. The current findings, along with past research provide support for the role of the EC system in the suppression of nausea to a context previously paired with illness.

Acquired and hereditaryperipheral neuropathies are associated with increased functional connectivity of the left precuneus/posterior cingulate cortex in the default mode network. This increased connectivity in the default mode network is correlated with duration of peripheral neuropathy and severity of clinical total neuropathy score. As discussed in the introduction, if used in combination, biomarkers related to pain mechanisms offer the possibility to develop objective pain-related indicators that may help diagnosis, treatment, and understanding of pain pathophysiology. One possible application of such an approach might be to determine if a patient who is not communicative is experiencing pain. Another example may be to help guide selection of treatment for neuropathy, such as whether transcranial magnetic stimulation may alter network activity among those with neuropathy. Modeling pain brain mechanisms can be achieved using multi-modal brain imaging including functional magnetic resonance imaging, structural magnetic resonance imaging, diffusion tensor magnetic resonance imaging, electroencephalography, EMG, and PET. As we have reviewed here, in addition to using imaging biomarkers, composite pain biomarkers can be investigated using a multitude of non-imaging biomarkers. Multiple analytic approaches have been used to investigate composite pain biomarkers: composite algorithms have been investigated , unsupervised and supervised multivariate analyses have been used to distinguish pain groups and non-pain groups , supervised pattern recognition have been used to cluster diagnostic groups for different pain conditions , mechanism-based pharmacokinetic-pharmacodynamic modeling has been used to identify biomarkers that help diagnose pain and predict pain treatment , principal component analysis has been applied to biochemical markers to create distinct pain profiles ,vertical agriculture patterns of inflammatory blood cytokines and chemokines have been used to differentiate pain and non-pain groups , multi-variable data analysis using simultaneous analysis of 92 inflammation-related proteins with pain intensity and pain thresholds were used to identify protein patterns which distinguish pain and non-pain groups , metabolomics have been applied to chronic pain. 

As detailed above, chronic pain and neuropathic pain impact multiple organ systems. Advancing the value of pain biomarkers depends on selection of measurements and metrics that are the most mechanistically valid and informative, and combining the selected measurements such that they mechanistically and statistically maximize accurate classification. Advancement of measurement accuracy is vital and the subsequent steps of the approach are entirely contingent upon the success of this step.In the above reviewed literature, we attempted principally to focus on which biological systems and which biomarkers should be the focus of measurement. For effective application of measurements of these domains it is important to discuss approaches for measurement selection. In Figure 2, we provide a significantly abbreviated schematic of key available statistical approaches to handling multi-modal datasets in building composite biomarkers. We have highlighted four general areas of statistics/machine learning: feature reduction , classification , regression , and clustering. Feature reduction can occur during or prior to classification, regression, or clustering. Feature reduction primarily focuses on two primary approaches: integration of measurements toward creation of a composite variable to simplify and enhance model performance, and effective feature reduction through variable selection to use optimal variables. Thus, feature reduction can represent the effective combining of strong measurements to a meaningful and robust latent variable or elimination of unnecessary, or statistically weak, measurements. Some methods, such as random forest, has built in feature reduction. 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, 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,hydroponic flood table 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. Neuropathic pain is a debilitating condition that has primary, and cascading affects across body 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. Although tobacco use has declined in the general population it remains high among people experiencing homelessness ; prevalence of tobacco use among PEH is five times that of the general population. Cancer and heart disease caused by smoking are the leading causes of death among PEH over age 50, and the incidence of these conditions among PEH under 50 is higher than in the age-matched general population.Smoking prevalence among individuals with SMI is 44%-64% compared to 13% in the general population. While population smoking prevalence has decreased, rates have not declined among individuals with SMI. Smoking cessation is particularly challenging among persons living with SMI who may have high levels of nicotine dependence. Persons living with severe depression may experience an increase in depressive symptoms after cessation, increasing relapse to smoking. Nicotine mitigates the neurocognitive deficits associated with schizophrenia; smoking cessation worsens these deficits. Environmental cues to smoking, including the presence of cigarette litter or smoke breaks can create a culture of tobacco use in homeless service settings, negatively impacting quit attempts. Partial smoke-free policies, meaning smoking is not permitted indoors but allowed outdoors on shelter grounds, are acceptable to residents and associated with increased interest in smoking cessation. Tobacco product marketing to PEH and inadequate access to smoking cessation treatment may also contribute to tobacco use and lower quit rates. Although PEH make quit attempts at the same rate as housed populations they are less successful at achieving abstinence. Ten randomized controlled trials of smoking cessation interventions for PEH have included behavioral counseling, pharmacotherapy, and adjunctive treatments like contingent reinforcements. RCTs that used behavioral counseling and pharmacotherapy reported abstinence rates of 9%-17% at 6 months follow-up. Studies using contingent reinforcements for smoking cessation reported higher abstinence rates: 22% at 4 weeks follow-up and 48% at 8 weeks followup. Although these studies established that engaging PEH in cessation trials is feasible, none were integrated with homeless service providers nor did they utilize ancillary staff, such as pharmacists, to provide access to medications or counseling. A recent systematic review of 11 studies explored healthcare professional delivery interventions for PEH outside clinical settings. Only two studies in the UK and Scotland involved pharmacists. In the Scotland PHOENIx study, hospitalized PEH were referred to a pharmacist upon discharge to receive medications, health checks, and referrals. Pharmacist outreach was associated with increased prescribing of medications including anti-hypertensives, diabetes medications, antidepressants, and wound dressings; however, no study involved pharmacists delivering smoking cessation services. In California and other US states, pharmacists can prescribe NRT; in some states pharmacists can also prescribe bupropion and varenicline.Care models for PEH that include pharmacists could increase access to cessation services and medications. In this study, we developed and tested a community pharmacy linked smoking cessation program integrated within two homeless shelters in San Francisco, California. The program included the provision of ad-hoc brief cessation counseling by shelter staff, a cessation counseling session with a pharmacist, and provision of a 3-month supply of NRT delivered on-site. We hypothesized that engagement in the pilot program would increase quit attempts and reduce daily cigarette consumption. This uncontrolled trial was divided into three phases that took place sequentially at each site: 1) training shelter staff how to provide cessation counseling, 2) training shelter staff to become Cessation Champions, 3) and pilot testing medication assistance programs in two shelters in San Francisco, California. Shelter staff included anyone that interfaced with clientele, including case managers, program managers, peer counselors, eligibility workers, and mental health specialists. Phase 1 took place between September 2019 and February 2020. We partnered with eight shelters in San Francisco that collectively housed nearly 1000 PEH nightly. Shelters that agreed to participate selected a time that worked for their staff to receive an in-person training session. At each site, we conducted a 1-hour training with shelter staff who interfaced with clients on how to provide smoking cessation counseling to PEH. The training for shelter staff was provided by a Masters-level Tobacco Treatment Specialist. The training for the shelter staff was developed by the PI and adapted from prior capacity building interventions to increase shelters’ and permanent supportive housing’s capacity to provide smoking cessation services. The training focused on how to provide cessation counseling, relying on the clinical practice guidelines for smoking cessation. Topics included tobacco use among PEH, nicotine addiction, tobacco cessation counseling using the ask, advise, and refer model as well as the 5A’s for smoking cessation, a brief introduction to tobacco cessation medications, local cessation resources and tobacco policy initiatives. Shelter staff were not compensated for attending the training. From the eight sites in Phase 1, we identified two shelters willing to participate in Phase 2. Phase 2 took place between February 2020 and January 2021 and involved training a case manager to be a Cessation Champion at each of the two shelter sites. The Cessation Champion at the first site attended the training during Phase 1 and 2; however, in the second site, the Champion was a newer employee who attended the training only in Phase 2. The Cessation Champion training was provided by the study’s co-investigator, a Doctor of Pharmacy pharmacist with expertise in smoking cessation.

Medication will be stopped based on pre-specified criteria for discontinuation of study medication: development of agitation, hostility, depressed mood, or changes in behavior or thinking not typical of alcohol use or withdrawal severe nausea and vomiting; have a systolic blood pressure greater than 160, or a diastolic blood pressure greater than 100 , or a heart rate greater than 70% of the maximum heart rate expected for their age [0.70]; females who become pregnant; > 50% increase in AST/ALT at any of the LFT assessments ; and any circumstances that, in the opinion of the investigators, compromise participant safety. Four weeks after medication is terminated a follow-up safety visit will be conducted and will consist of clinical labs and ECG, which will be reviewed by the study physician.To assist with adherence to intervention protocols, participants receive a detailed medication log that lists the date, study day blister pack number, and AM/PM tablet number for everyday of the study in order for the participant to keep track of medication consumption. In addition, participants are provided a document with tips on how to remember to take medication twice a day. Compliance will be monitored by the study staff using the pill count method at each follow-up visit. Finally, participants will work with the same research staff member throughout the trial and will complete regular check-ins with that staff member.In the event that significant medical problems are encountered, the blind will be broken and appropriate medical treatment will be provided. Significant medical problems are defined as any of the following severe adverse events defined per the US FDA as any fatal event, any immediately life-threatening event, any permanent or substantially disabling event, any event that requires or prolongs inpatient hospitalization,cannabis grow set up or any congenital anomaly, or any unexpected adverse drug experiences that have not previously been observed.

In addition, any other important medical event that a study investigator judges to be severe because it may jeopardize the subject’s health in some manner or require intervention to prevent one of the above outcomes, or which would suggest a significant hazard, contraindication, side effect, or precaution. The PI will promptly report all severe adverse events or unexpected adverse drug experiences as required by the UCLA Institutional Review Board , the NIAAA Program Officer, the study’s DSMB, and the FDA. A decision to break the blind will be determined by the severity of the medical problem and its relevance to study medication.A battery of measures designed to provide a comprehensive assessment of medical safety, alcohol and cigarette use, other drug use, and psychological measures are included. In order to substantially decrease the task of managing the data stream, most self-reported study measures will be collected using Qualtrics. The following interviews and self-report measures will be administered during the initial screening visit for the purposes of assessing eligibility and measuring relevant individual differences: The 30-day timeline follow-back interview measures quantity and frequency of drinking; the Structured Clinical Interview for DSM-5 will be performed by a master’s level clinician using under the supervision of the PI. The SCID-5 will be used to assess current AUD diagnosis as well as exclusionary diagnoses ; Clinical Institute Withdrawal Assessment for Alcohol is a brief 10-item measure that assesses for the emergence of alcohol withdrawal symptoms. The CIWA-AR has been used both in clinical and research applications and has demonstrated both reliability and validity; the Columbia Suicide Severity Rating Scale, interview assess suicide ideation, intensity of ideation, and suicidal behavior.

C-SSRS is intended for use by trained administrators who have completed the required online training certification and who will be supervised by the PI; smoking is assessed by number of cigarettes per day/any form of tobacco and the Fagerstrom Test for Nicotine Dependence; Cannabis Use Disorder Identification Test to identify persons with hazardous and harmful patterns of cannabis consumption; the Graded Chronic Pain Scale , a 7- item measure used to evaluate an individual’s overall severity of chronic pain from pain that has lasted at least 6 months; the Profile of Mood States for measuring dimensions of mood; the Beck Anxiety Inventory a self-report assessment to measure anxiety and depression levels used widely in clinical trial; The Beck Depression Inventory, Revised captures depressive symptomatology ; the Adverse Childhood Experience Questionnaire , a 10-item self-report measure developed to identify childhood experiences of abuse and neglect; information on family history of alcohol problems will be collected using the Family Tree Questionnaire ; the Penn Alcohol Craving Scale will provide an assessment of tonic levels of craving for alcohol; the Alcohol Dependence Scale , a scale measuring alcohol dependence symptoms over the past 12 months; the Alcohol Purchase Task , a 16-item scale that uses hypothetical situations regarding alcohol purchases and consumptions at varying prices in order to generate several indices of alcohol-related reinforcement; the Alcohol Use Disorders Identification Test to identify persons with hazardous and harmful patterns of alcohol consumption; Readiness to Change ladder is a measure with 11 responses items to assessmotivation to reduce or cut back on drinking; the Reward-Relief Drinking Scale is a 4-item scale that measures an individual’s reward drinking tendencies; the Insomnia Severity Index measures sleep quality; and the ImBIBe is a 15-item questionnaire in which the subject responds on a 5-point scale responses to questions on the consequences of alcohol use. Breath alcohol concentration , urine drug screen, and pregnancy test will be administered at each study visit.

A BrAC = 0.00 g/dl will be required for participation in each study visit. Medical eligibility will be determined by the study physicians using the following assessments: review of participant’s medical history; laboratory tests , glucose, drug screen, chemistry screen, and pregnancy test); physical examination, including vital signs, weight, and review of systems; and electrocardiogram. For safety reasons,grow rack systems clinical lab tests will be repeated at weeks 4, 8, and 12. And the ECG will be repeated at week 12. Lastly, participants will return 1 month post medication discontinuation to repeat all clinical labs and ECG as a final safety check. Several individual differences measures obtained during the initial screening visit will be repeated during randomization visit as well as the monthly assessments to allow for analyses of change overtime and as a function of study medication. The TLFB interview will be conducted by telephone on weeks 2, 6, and 10 to complement the in-person assessments on weeks 4, 8, and 12 and to shorten the duration between drinking outcomes assessment. This will improve data quality and maintain contact with research participants on a more frequent basis in order to prevent dropout. In addition to the measures testing the study outcomes, measures of neuroinflammation and brain imaging will be collected. Serum samples will be collected at randomization and at 4, 8, and 12-week follow-ups to address exploratory aim 2. Due to the diurnal rhythm of cytokine production, samples will be collected at the same time of day for all subjects. Assayed markers will include innate immune receptors , cytokines , chemokines , and other inflammatory signaling molecules. The neuroimaging session, completed during the week 4 follow-up visit, includes 2 neuroimaging paradigms: the alcohol cues task and the Montreal Imaging Stress Task. The neuroimaging paradigms will be presented in counterbalanced order between participants.Neuroimaging will be conducted using a 3-T Siemens Prisma Fit MRI scanner at the UCLA Center for Cognitive Neuroscience. Scanning parameters for functional magnetic resonance imaging scanning will be as follows: TR, 2 s; TE, 30 ms; flip angle, 90°; FOV, 192 mm; matrix, 64 × 64; voxel size, 3 × 3 × 4mm3 ; slice thickness, 4 mm; and 34 slices. A T2-weighted, high resolution, matched bandwidth, anatomical scan , and a magnetization-prepared rapid-acquisition gradient echo will be acquired to enable registration. The orientation for MBW and functional scans will be oblique axial to maximize brain coverage. During data acquisition, head restraints will be placed using a foam pillow. The alcohol cues task is well-validated, with strong reliability and within-participant stability. There are four types of cues: alcoholic beverages, non-alcoholic beverages, blurred images, and a fixation cross. Stimuli are presented in six 120-s epochs , with each epoch consisting of four 24-s blocks. During each 24-s block, 5 individual pictures will be displayed for ~ 4.8 s each. Alcohol blocks will be specific to beverage type , with 2 blocks of each beverage type. Each block will be followed by a 6-s washout period.

The MIST is a block design fMRI paradigm in which participants solve mental arithmetic problems. There are three conditions: stress induction, control, and rest, which are presented pseudo-randomly. During the control and stress induction conditions, participants are asked to solve mental arithmetic problems of varying degrees of difficulty and are given feedback on their performance. During the stress induction condition, 2 performance indicators are displayed on a colored bar to induce social evaluative threat: the participant’s overall performance and the “average” performance of all participants. In the stress induction condition, the time limit, represented by a blue progress bar, is dynamically modulated to be 10% shorter than the participant’s average time required to complete previous trials. In the control condition, participants complete arithmetic problems of a comparable difficulty level without the time restriction or social evaluative performance displays. During the rest condition, the visual interface is displayed but no arithmetic problems are presented. The task is administered in three 5-min runs consisting of six 50-s blocks. After each run, participants are given scripted, negative feedback of their performance. After the task is complete, participants are debriefed and informed that the task was designed to increase their stress level. Participants who participate in the neuroimaging session will complete subjective and biological measures of stress response immediately prior to and following the fMRI paradigm as described in exploratory aim 4. The Subjective Distress Units Scale is a scale of 0 to 10 for measuring the subjective intensity of disturbance or distress currently experienced by an individual. The short-form Spielberger State-Trait Anxiety Inventory has 6 items assessing state anxiety. Salivary cortisol samples will be collected at 3 time points during the week 4 visit.Source documents include but are not limited to original documents, data, and records such as hospital/ medical records , clinic charts, laboratory results, data recorded in automated instruments, and pharmacy records, etc. This study will use an electronic data capture eCRF system and paper source documents. Data will be transcribed from source documentation directly into a statistical program such as SPSS and will be subsequently double checked by another member of the research staff. Only questionnaire data will be entered directly into eCRF. Paper copies of the eCRFs will be available in the event that the EDC is not accessible at the time the questionnaire is being completed. The transcribed data will be consistent with the source documents, or the discrepancies will be explained. All entries, corrections, and alterations will be made by the investigator or other authorized study personnel. Subjects will be identified on eCRFs and paper source documents by a unique subject number. The subject number will be used if it becomes necessary to identify data specific to a single subject. Regulatory bodies, such as the study sponsor, Food and Drug Administration , and Institutional Review Board , are eligible to review medical and research records related to this study as a part of their responsibility to protect human subjects in clinical research. Personal identifiers will be removed from photocopied or electronic medical and research records. To maintain subject confidentiality, research and clinical records will be stored in a locked cabinet. Only research staff, sponsor officials, and other required regulatory representatives will have access to the records. Subject information will not be released without written permission. The PI has received a Certificate of Confidentiality for this study. In order to ensure compliance with protocol and regulatory guidelines, the PI will review study documents to verify their accuracy, completeness, and timeliness of collection and will provide feedback to staff on findings and on how to correct any errors found during the review. The PI will also designate appropriately qualified personnel to periodically perform quality assurance checks during and after the study.