A microcomputer controlled the delivery of fluids, presentation of auditory and visual stimuli, and recording of the behavioral data. Rats were trained to self-administer 10% ethanol , 0.2% saccharin or water in 30 min daily sessions on a fixed-ratio 1 schedule of reinforcement, where each response resulted in delivery of 0.1 mL of fluid as previously described Briefly, for the first 3 days of training, water availability in the home cage was restricted to 2 h ⁄ day in order to facilitate acquisition of operant responding for a liquid reinforcer. During this time, rats were permitted to lever-press for a 0.2% saccharin solution. At this point, water was made freely available and saccharin self-administration training continued for another 3 days. The rats were then trained to self-administer ethanol by using a modification of the sucrose-fading procedure that used saccharin instead of sucrose . During the first 6 days of training rats were allowed to lever-press for a 5.0% ethanol solution containing 0.2% saccharin . Starting on day 7, the concentration of ethanol was gradually increased from 5.0 to 8.0% and finally to 10.0% , while the concentration of saccharin was correspondingly decreased to 0%. At the beginning of the saccharin-fading procedure a second but inactive lever was introduced. Responses at this lever were recorded during all training and testing phases as a measure of non-specific behavioral activation but they had no programmed consequences.At completion of the fading procedure, animals were trained to discriminate between 10% ethanol and water in 30 min daily sessions. Beginning with self-administration training at the 10% ethanol concentration, discriminative stimuli predictive of ethanol vs. water availability were presented during the ethanol and water self administration sessions, respectively. The discriminative stimulus for ethanol consisted of the odour of an orange extract , whereas water availability was signaled by an anize extract . The olfactory stimuli were generated by depositing six to eight drops of the respective extract into the bedding of the operant chamber. In addition,hydroponic grow table each lever-press resulting in delivery of ethanol was paired with illumination of the chamber’s house light for 5 s . The corresponding cue during water sessions was a 5 s tone .

Concurrently with the presentation of these stimuli, a 5 s time-out period was in effect, during which responses were recorded but not reinforced. The olfactory stimuli serving as S+ or S– for ethanol availability were introduced 1 min before extension of the levers and remained present throughout the 30 min sessions.The rats were only given ethanol sessions during the first 3 days of the conditioning phase. Subsequently ethanol and water sessions were conducted in random order across training days, with the constraint that all rats received a total of 10 ethanol and 10 water sessions.Reinstatement tests began the day after the last extinction session. These tests lasted 30 min under conditions identical to those during the conditioning phase, except that alcohol and water were not made available. Sessions were initiated by the extension of both levers and presentation of either the ethanol S+ or water S– paired stimuli. The respective discriminative stimulus remained present during the entire session and responses at the previously active lever were followed by activation of the delivery mechanism and a 5 s presentation of the CS+ in the S+ condition or the CS– in the S– condition. Animals were tested under the S+ ⁄ CS+ condition on day 1 and under the S– ⁄ CS– condition on day 2. Subsequently, reinstatement experiments were conducted every fourth day , in which AM404 was administered 30 min prior to the sessions. Responding at the inactive lever was constantly recorded to monitor possible non-specific behavioral effects.Pre-treatment with the anandamide transport inhibitor AM404 30 min prior to the ethanol self-administration session significantly reduced the operant response for ethanol in a dose-dependent manner . This effect was not due to a decrease in the reinforcing value of ethanol because progressive ratio experiments resulted in similar break points for animals treated with vehicle or AM404 . They were not derived or a motor inhibition induced by AM404 as the 2 mg ⁄ kg dose did not affect locomotion at the time of operant behavior testing . The effects were selective for ethanol because pre-treatment with AM404 did not modify operant responding for saccharin .

In addition, administration of AM404 did not alter food motivation and thus, food intake in rats deprived of food for 24 h . These results suggest that the pharmacological effects of the anandamide transport inhibitor are not related to a devaluation of the motivational state or a devaluation of motivational properties of natural reinforcers.In a subsequent experiment, we tested the efficacy of AM404 as a modulator of not only the operant responses for ethanol but also the operant responses elicited by the contextual stimuli associated with alcohol. As the highest dose tested resulted in significant inhibition of locomotion, we did not administer it in this context. Once a stable extinction baseline was observed, we induced relapse by presenting cues associated with ethanol delivery during training. Ethanol-related contextual stimuli elicited ethanol-seeking behavior, as operant responses induced by ethanol-associated stimuli were more intense and significantly higher than those observed on the last day of extinction . When AM404 was injected 30 min prior to cue presentation, it failed to alter the responses for ethanol seeking , indicating that anandamide uptake inhibition was not effective in preventing cue-induced relapse.The major finding of the present study is the demonstration that acute administration of the anandamide transport inhibitor AM404 reduce sethanol self-administration under an operant conditioning schedule. This compound does not affect the relapse induced by contextual cues associated with ethanol. The effects of AM404 seem to be selective for ethanol, as it was unable to suppress responding for other reinforcers, such as saccharin or food intake, suggesting that this effect is not related to a decrease in a general motivational state. This is confirmed by the lack of action of AM404 on the motivational properties of ethanol, as measured in the progressive ratio paradigm. This suppressive effect of AM404 on ethanol self-administration seems to be independent of the already known anandamide-induced motor impairment, as the lowest effective dose tested did not alter motor behavior in the open field. Moreover, the actions of AM404 were found to be independent of a potentiation of the sedative effects of ethanol.

Finally, neither experiments with cannabinoid CB1 receptor agonists nor with cannabinoid CB1 and CB2 receptor antagonists allowed us to obtain a direct pharmacological confirmation of the role of known cannabinoid receptors on the effects of AM404. The finding of a similar profile of effects using ACEA, a selective cannabinoid CB1 receptor ligand that shares the arachidonoyl moiety with both anandamide and AM404, suggests a common unknown target responsible for the effects of AM404 on ethanol self-administration. The lack of effects of WIN 55,212-2 and HU-210 at doses devoid of motor side-effects suggests that AM404 does not exert its actions through a CB1 receptor-mediated mechanism. AM404 was the first synthetic inhibitor of anandamide uptake and it has been shown to potentiate many effects elicited by anandamide in vitro and in vivo . As AM404 does not activate cannabinoid receptors , the effects of this drug were suggested to result from the elevation of endogenous anandamide levels . However, recent findings suggest that AM404 also directly activates the vanilloid VR1 receptor , complicating the identification of its mechanism of action on ethanol self-administration. However, the effect of AM404 was not reversed or enhanced by pre-treatment with the competitive vanilloid VR1 receptor antagonist capsazepine, indicating that the inhibitory action of AM404 is not mediated through VR1 stimulation and may be derived from other targets in the endocannabinoid system. Following this rationale we studied the involvement of the cannabinoid CB1 receptor, the natural target of anandamide. In order to confirm its participation we first studied whether the cannabinoid receptor antagonist SR141716A reversed the actions of AM404. This pharmacological test was complicated by the inhibitory actions of SR141716A on ethanol self-administration that precluded the observation of a reversal of the actions of AM404. A second strategy was to compare the actions of AM404 with those of selective cannabinoid CB1 receptor agonists belonging to three of the four main classes of cannabinoid agonists: eicosanoids ,flood tray aminoalkylindoles and classical cannabinoids . The effects of these compounds in ethanol self-administration are not similar to those of AM404. ACEA and WIN 55,212-2 reduced ethanol self-administration, although the component of motor inhibition of WIN 55,212-2 might be responsible for this effect. However, the classical cannabinoid receptor agonist HU-210 did not affect ethanol self-administration . We replicated this finding in a separate study in Marchigian Sardinian alcohol-preferring rats . These results indicate that the contribution of the CB1 receptors to AM404 cannot be supported. The similar profile of actions observed after systemic administration of either cannabinoid CB1 receptor agonists or antagonist seems to be challenging. It has been reported that both cannabinoid CB1 receptor agonists, such as tetrahydrocannabinol, CP55 940 and WIN 55,212-2, and cannabinoid receptor antagonist ⁄ inverse agonists, such as SR141716A, suppress operant behavior . These reports stress the pleiotropic spectrum of actions found after the interference with endocannabinoid signaling. The complex roles of the endocannabinoid system on the regulation of GABA and glutamate synapses throughout the brain circuits processing the appetitive ⁄ motivational properties of ethanol might explain these findings .

As an example, we have recently described that intracerebral injections of SR141716A only affect ethanol selfadministration in rats when the CB1 antagonist is infused in the prefrontal cortex but not in the hippocampus or dorsal striatum . Moreover, in this study, local blockade of fatty acid amidohydrolase, the main enzyme that degrades anandamide, enhances ethanol self-administration when injected into the prefrontal cortex. However, we cannot exclude additional targets such as noncloned cannabinoid-like receptors on which anandamide and WIN 55,212-2 may act. Thus, the present study stressed the need to clarify the growing complexity of endocannabinoid pharmacology, especially in the field of motivated behaviors. Although the present results exclude VR1, CB1 and CB2 receptors as the targets of the effects of AM404, we cannot exclude the contribution of endocannabinoids elevated by AM404 to the present actions, especially because the endocannabinoid system has been recently implicated in the neuroadaptations that occur during acute alcohol exposure, alcohol dependence and abstinence. Several studies have documented that endocannabinoid transmission is acutely inhibited by ethanol and becomes hyperactive during chronic ethanol administration, as revealed by the increase in the levels of endocannabinoids and the down-regulation of CB1 receptors . Thus, it is tempting to imagine that those compounds that increase endocannabinoid transmission, such as AM404, might be useful in reducing operant responses for ethanol. With the precautions derived from the non-CB1 profile of the effects of AM404, we propose that the increased levels of endogenous cannabinoids occurring during chronic ethanol administration contribute to facilitate the action of AM404; the neuroadaptations in the central nervous system associated with chronic ethanol intake lead to an increase in anandamide levels and this event could enhance the action of AM404 acting through the increased endogenous anadamide. However, we also demonstrate that the acute administration of AM404 was not able to suppress the relapse response for ethanol, i.e. the reinstatement of ethanol responding induced by the presentation of contextual cues associated with ethanol after a period of extinction. The differential response to AM404 in self-administration and relapse conditions may have a neuropharmacological basis in the recently described changes in endocannabinoid levels after chronic ethanol exposure . A possible explanation for these differences may reside in the probable alterations induced by chronically consumed ethanol in the functionality of the receptor systems mediating the central effects of ethanol that sustain ethanol-drinking behavior in rats. These neuroadaptation processes might result in a decreased potency and efficacy of the ligands. The increased levels of anandamide observed during ethanol consumption may return to basal levels or even disappear and thereby AM404 could not be acting in such a situation.This hypothesis is supported by the results obtained recently by Gonzalez et al. who showed that the levels of endocannabinoids underwent significant changes in reward-related areas during relapse, showing the lowest values in this phase.

Similar to findings in studies involving alcohol and brain injury, substance abuse was associated with poorer neuropsychological and functional outcomes . Literature reviews also support this finding, with findings indicating that almost 40% of TBI patients had a positive toxicology screen, or had reported using drugs, with marijuana use accounting for more than half of the drug use . Similar to the large percentage of missing data for alcohol screen, the variable presence of other drugs also had a large percentage of missing data . This is important to consider, as a large percentage of missing data may cause bias. Yet, in this study, even with the large percentage of missing data, the presence of other drugs was found to have a negative influence on TBI severity as indicated by lower GCS scores compared to those who did not have other drugs present on admission. It is important to consider that both alcohol and drug use at the time of injury can confound GCS assessment in trauma patients. Although findings from this study corroborate findings from TBI literature examining substance use, it may be judicious to acquire GCS scores after any intoxicating substances have worn off, perhaps hours or even up to a few days post injury. The GCS score is often assessed numerous times in a trauma patient’s hospital stay, however, the NTDB data set does not include other GCS scores, only the first one on arrival at the hospital. Finally, the large percentage of missing data for both alcohol screen result and presence of other drugs should be considered and addressed. Because blood alcohol and drug measurements in emergency departments are likely biased towards intoxicated and incoherent patients. This can help explain the large percentage of missing data when it comes to these two variables. As mentioned previously, clinicians often will forget to draw a blood sample for alcohol and or drugs, and even if they do, these results may not be entered into the medical record or the registry in a timely and accurate manner. These variations in practice create a large proportion of missing data as it relates to alcohol and toxicology screens performed and documented. For purposes of this study,vertical grow rack alcohol screen results were imputed, but as helpful as imputation can be to an analysis, it can also misrepresent the actual number of participants with a positive alcohol result thereby biasing the results.

Participants with a known history of substance abuse were found to have slightly higher GCS scores when compared to patients who did not. For every participant who had a history and a diagnosis of substance abuse, GCS scores increased by .075 units. Higher GCS scores indicated better neurological function and a less severe TBI. The study by Nguyen et al. and Leskovan et al. explore the relationship between marijuana use, and alcohol, on mortality. The effect of marijuana on TBI severity is far less studied than alcohol, though preclinical studies have shown that the presence of marijuana is associated with some neuroprotective effects, including attenuated cell apoptosis, alleviation of cerebral edema, and improved cerebral blood flow . Further studies are needed to investigate the effects of marijuana on TBI severity alone, not when combined with alcohol or other substances. These findings cannot be discussed without addressing the issue of missing data. Variables that influence GCS scores and TBI severity, such as alcohol screen result, sex, presence of drugs, history of cancer, history of mental and personality disorder, and history of alcohol abuse all had some element of missing data. All the aforementioned variables had less than 6% of the data missing, with some of them having less than 1% missing data . Similarly, history of comorbid conditions all had less than 3% missing data. The two variables that had a large percentage of data missing were the presence of THC and the presence of other drugs . Despite the missing data, both those variables were found to have a statistically significant influence on GCS scores, hence, TBI severity. Though statistically significant, the validity of those findings should be cautiously interpreted within the context of such large percentage of missing values for these hypothesized explanatory variables. One of the leading causes of injuries resulting in TBI incidence are collision related, such as motor vehicle or motorcycle crashes. Furthermore, almost half of the US states have legalized marijuana for medical use with some states allowing recreational use of marijuana. Therefore, collision type mechanism of injuries was examined to see if there was any mediating influence on TBI severity in the presence of THC.

It was determined that motor vehicle collisions did not influence, or mediate, the relationship between THC and TBI severity. However, motorcycle collisions suggested a partial influence on TBI severity. This was an expected result as studies have shown that head injuries are the leading cause of death in fatal motorcycle crashes . It is therefore not surprising to see that GCS scores were reduced when motorcycle collisions were examined for mediating influences on TBI severity in the presence of THC. In one study by Steinemann et al. , THC positivity among road traffic collisions in one US state tripled, with the number of THC positive patients presenting to the highest-level trauma center doubling. However, this data should be interpreted cautiously within the context of such large percentages of missing values for hypothesized explanatory variables. Finally, it is important to note the surprising finding that only 22 participants were found to have been involved in a motor vehicle collision, and only 16 were involved in a motor cycle crash. In the original data set, only 16,324 of 997,970 were involved in a motor vehicle collision, and 12,826 of 997,970 were involved in a motor cycle collision. In 2015, the CDC reported that more than 2.3 million people presented to the emergency department with motor vehicle-related injuries. Because not every single motor vehicle collision warrants a trauma activation or for the patient to be seen by a trauma surgeon, the number represented in the trauma registries would be much less. Hence, this may somewhat explain the lower numbers presented in the 2017 NTDB data set . Several limitations of this study should be noted. Primarily, this study was a retrospective cohort study, therefore it may be missing potentially relevant data. Retrospective cohort studies,though time efficient and cost effective, can be limited due to the nature of data collected. Missing data on several important predictor variables represents another drawback. The patient population in this study was heavily skewed towards moderate and severe TBI patients from one year of available data. A more evenly distributed sample over a longer time period with a larger number of moderate and severe TBI patients would provide more sensitive analyses. The retrospective nature of this study limits the conclusions that can be determined as the methodology was not able to ascertain any measure of acute versus chronic marijuana use. Urine toxicology screens, such as those used in the ED, detectable levels of THC can be present for up to 4.6 days after the last noted use for individuals who do not use marijuana frequently, or up to 15.4 days after last use for those who are frequent users .

Therefore,vertical farming racks the presence of marijuana at the time of exposure may not correlate with recent use. Timing of exposure may be a factor and is an important limitation in this study. Additionally, study findings are based on patients with TBI that have had a urine THC test performed. Since not all patients with moderate or severe TBI were tested for the presence of THC, bias is thus introduced. There was a large percentage of study participants who were not tested or had missing test results for THC . Consequently, a more accurate analysis of THC prevalence and association was not possible as there was no way to determine which of those cases that were not tested or had no results documented were positive for THC. It is important to note that despite there being a small percentage of THC prevalence, this study reflects only one year worth of data, from 2017, and that establishing previous prevalence rates for comparison from the NTDB cannot be calculated. This is because the presence of THC was never abstracted nor documented in the data set prior to 2017. Future studies examining prevalence rates for a series of years is warranted. Observational research has been shown to provide mis-estimations of the outcome of interest. Data analyzed from the NTDB is extracted from various trauma registries across the United States and Canada. Each hospital employs its own registry abstractors who input the data collected from the electronic medical record into the registry which then feeds into the NTDB. This is an important limitation as the documentation and accuracy of data inputted may be inaccurate, incomplete, or inconsistent. This can result in information bias. Furthermore, systematic under reporting of data by participating hospitals can result in selection bias and create an inconsistent database. An example of this was the lack of consistency in the measurement and documentation of blood alcohol levels at time of hospital admission, and the missed opportunities for urine testing. This contributed to a large percentage of missing data which may have also introduced informational bias. Additionally, this variation in reporting results in incomplete data, as seen in this study, as well as conflicting data. There were two occasions where participants were documented as having not being tested for any substances yet were each found to have been positive for THC and/or cocaine. Outcomes of such practices and variations between trauma registries leads to a lack of confidence regarding data accuracy and resulting analyses. Traumatic brain injury is a significant public health concern and a leading cause of death and disability. Many TBI patients have substance use exposure at the time of injury. This study aimed at examining the relationship between marijuana exposure at the time of injury and TBI severity in moderate and severely injured TBI patients. The study findings are timely as the number of states legalizing marijuana for both medical and recreational use increases. This retrospective cross-sectional design study analyzed a large data set retrieved from the National Trauma Data Bank of patients with traumatic brain injury and the association between the presence of THC and brain injury severity, as defined by the GCS score. This is the first known study to examine the presence of THC at the time of injury and its effect on brain injury in a large demographic from a national dataset. The NTDB dataset captures 65% of all trauma hospitals capture; so, with some confidence the claim can be made that moderate and severe TBI, in this data set, are representative of the TBI population in North America. This study found a smaller prevalence rate of THC presence in a purposive sample of TBI patients, but further studies are needed to estimate more accurate prevalence rates now that future datasets from the NTDB will delineate the types of substances tested. This will also allow for larger datasets to be analyzed which may yield different results. As is, the current dataset is not sufficient to establish strong analyses due to the large percentage of missing data, inconsistencies within the data itself, and limited to one dataset as previous datasets did not have the necessary drug information needed for analysis. Despite the limitations inherent to retrospective studies and to databases such as the NTDB, findings from this study suggest an important link between the presence of a positive THC results and GCS score, hence TBI severity. Only one research study at the time of when the systematic literature review for this present study was done investigated the effects of THC presence in TBI patients and its influence on mortality. To date, there has been one identified study that investigated the influence of marijuana on TBI mortality . When examining the differences between participants who tested positive for THC and those who did not, it was found that GCS scores were lower for those who tested positive, indicating a more serious TBI. Additionally, participants who had a had a current diagnosis, or history of, cancer or substance abuse, were more likely to have tested positive for THC. This study found that the presence of THC was significantly associated with lower GCS scores and a potentially more severe TBI; this relationship was significant without controlling for other predicting variables.

The treatment phase of identified erroneous data involves correcting, deleting or leaving the error unchanged . For purposes of this study, if impossible or missing values are observed, they will have to be deleted, as there would be no way of correcting that value related to the retrospective and secondary nature of the data. For data points that are true extremes, further examination on the influence of these data points, individually and collectively, on analysis will be made prior to determining whether or not that data point will be deleted or left unchanged . It is important to deal with missing data because missing data can create bias. First, an exploratory analysis will be performed to look at frequencies or percentages of missing data, and to help identify how much data is missing. Next, an analysis of the mechanisms, or types, of missingness will be performed to identify whether the missing data is missing completely at random , missing at random , or not missing at random using statistical tests, such as Little’s test for MCAR. Following this, an analysis for patterns of missingness will be performed using a missing pattern value chart. There are two patterns that may be potentially observed: 1) a monotone pattern where data is missing systematically, or 2) an arbitrary pattern where data are missing at random . While the analyses are not definitive, they can bring attention to blatant anomalies in the missingness of data and help to make decisions on the missing data handling procedures.There are a variety of methods that can be utilized to deal with missing data. The type of method utilized will depend on the percentage of missing data present and cannot be specified beforehand. Simple methods, such as list wise or pairwise deletion are helpful when the percentage of missing data is less than 5%. Listwise deletion, also known as complete-case analysis,vertical growing systems removes all data for a case with one or more missing values. In other words, that case is omitted completely.

A disadvantage when using listwise deletion is that it can reduce the sample size. On the other hand, pairwise deletion, also known as available-case analysis, aims at minimizing the loss of other potential data incurred with listwise deletion. Pairwise deletion still uses that case when analyzing other variables with non-missing values; it just excludes that one value with a missing data. However, pairwise deletion does have its disadvantages in that most software packages use the average sample size across analyses which can create over or underestimation. If the percentage of missing data is greater than 5%, then more advanced methods of dealing with missing data can be utilized, such as imputation. Imputation methods will depend on the pattern of missingness identified and the type of variable requiring imputation . In patterns where missing data is systematic or monotone, methods such as regression, predicted mean matching or propensity scoring are helpful. In patterns where missing data is arbitrary or at random, methods such as multiple imputation using maximum likelihood regression methods to predict missing values based on observed values and sensitivity analyses that simulate the results based on a range of plausible values can be used. Aim 1. For Aim 1, the objective is to determine the prevalence of marijuana exposure in patients with moderate or severe TBI. Analyses will be conducted using the Statistical Package for the Social Sciences software. The proportion of TBI patients who have marijuana present on admission will be reported. Unadjusted prevalence will be determined through a 2×2 table. Prevalence rates will be calculated for total number of TBIs. Aim 2. For Aim 2, the objective is to determine the correlates associated with the presence of marijuana exposure at the time of injury. The correlates included in Aim 2 will be also collected for the sample of participants without marijuana exposure at time of injury. Measures of central tendency, including range, means, proportions and standard deviations will be calculated. These basic summary statistics will be calculated for continuous variables and binary categorical variables . Continuous variables will be plotted to assess for normality; tests to assess for normality will include kurtosis and skewness.

If data is normally distributed, then parametric statistics will be utilized. If data is not normally distributed, then non-parametric statistics will be utilized. Frequency distributions, including numbers and percentages, will be generated for each of the categorical variables/correlates; scatterplots will be created so that outliers can be identified. All correlate variables presented in table 6 will be examined; all the variables but one are categorical variables. Categorical variables will be mapped against presence of marijuana exposure and TBI severity to determine if significant differences are present across each of the categories. Tests to determine significant differences across categories include chi-square test or Fisher’s exact test based on the data. Variables that are identified as significant will be used as covariates in the adjusted prevalence rates. The variable of age is a continuous variable. The literature suggests that the relationship between age and drug exposure is not linear so we will test this relationship in this study. For this study a bar plot graph plotting age against marijuana exposure will be used to determine if a linear relationship exists. If there is not a linear relationship, the variable will be categorized. Correlates that are identified as significant will become covariates in the adjusted prevalence analysis. Prior to the adjusted prevalence analysis, these covariates will be examined for multi-collinearity. Aim 3. For Aim 3, the objective is to determine the relationship between marijuana exposure at the time of injury, the mechanism of injury, and TBI severity. The null hypothesis is that a relationship between marijuana at the time of injury, the mechanism of injury, and severity of TBI does not exist. As illustrated in the conceptual framework , mechanism of injury is considered a mediating variable; it potentially mediates the relationship between marijuana exposure at time of injury and TBI severity . First an estimate of the effect between marijuana exposure and TBI severity will be obtained without the mediator variable of mechanism of injury. To test for mediation, several regression analyses will be conducted that include the mediator variable and significance of the coefficients will be examined in each step to assess for direct and indirect effects. First, I will test for a direct relationship between marijuana exposure and TBI severity. Assuming there is a significant relationship between the two variables, I will then conduct an analysis to determine if marijuana exposure affects mechanism of injury. Assuming there is a significant effect, I will then conduct an analysis to determine if mechanism of injury affects TBI severity, and whether the mediation effect is complete or partial . To determine if the mediation effect is statistically significant I will use either the Sobel test or bootstrapping methods .

All analyses will be conducted unadjusted and then adjusted for covariates and confounders identified a priori and via aim 2 . The analyses will use logistic regression modeling because the dependent variable, TBI severity, is a dichotomous variable with only two choices, moderate or severe TBI. While TBI severity can be considered a continuous variable if using the number scoring of the GCS scale, a binary variable will be used as it is easier to interpret for clinicians using a numerical score: clinicians treat not on subtle degrees of TBI severity,pruning cannabis but whether it is a moderate or severe one based on GCS threshold cut-offs. Dummy variables will be used to input non-binary categorical variables into the analysis. However, with the predicted large sample size, and understanding the potentially significant confounding effects of certain variables such as other drugs, I hope to create binary variables for each drug listed in the NTDB database . But if this is unable to be done another approach would be to code all drug use into 3 categories: a value of 0 assigned for ‘no drug use’, a value of 1 for ‘stimulants’ only . Observational studies offer valuable methods for studying various problems within healthcare where other study design methods, such as randomized controlled designs , may not be feasible or even unethical. High quality observational studies can render invaluable and credible results that positively impact healthcare when studying clinically relevant topics in patient populations of interest to practicing clinicians. Despite this, observational studies can be subject to a few potential problems within the design and analytical phases rendering results highly compromised. Potential problems that will be encountered in this study design are selection bias, information bias and confounding. Possible countermeasures to address these problems will be discussed in this section. A potential problem regarding selection bias is present in the current study. The target study population is comprised of a purposive sample of patients registered in the NTDB. The NTDB is a centralized national trauma registry developed by the American College of Surgeons with the largest repository of trauma related data and metrics reported by 65% of trauma centers across the U.S. and Canada. The main advantage to utilizing such a registry for this study is that it constitutes the largest trauma database in the U.S. Furthermore, the NTDB allows for risk-adjusted analyses which can be important when evaluating outcomes in trauma . Despite its incredible potential in informing trauma related research, the selection of participants from the NTDB is not without its own biases. The reporting of data into the NTDB is done on a voluntary basis by participating trauma centers, rendering a convenience sample that may not be representative of all trauma patients, and may also not be representative of all trauma centers across the U.S. . This creates the problem of selection bias. Furthermore, the NTDB is subject to the limitations of selection bias is that it includes a larger number of trauma centers with typically more severely injured patients potentially under representing patients with milder traumatic injuries and injury scores . Additionally, patients who may be traumatically injured and who are not admitted to a participating trauma center will not be included in the NTDB, nor will trauma patients who died on scene before being transported. Another consideration to note is that participating hospitals may differ in their criteria of which patients to include in the database, specifically patients who are dead on arrival or those who die in the Emergency Department . This discrepancy in inclusion and exclusion criteria between hospitals regarding specific injuries makes representative comparisons potentially difficult.

Lastly, it is important to mention that large databases such as the NTDB are subject to missing data or disparate data. This is often due a multitude of factors, a few of which various demographic data points, test results and other key information, such as procedures, that may not be documented in the health record and therefore omitted in the database . Missing data often contributes to information bias; however, it can also contribute to selection bias because one of the methods in dealing with missing data is excluding participants for which data is missing thereby creating potential selection bias. Missing data may undermine the ability to make valid inferences, therefore, steps will be taken throughout the design and operational stages and methods within this study to avoid or minimize missing data. Methods to reduce information bias that can lead to selection bias will be discussed in the analysis section of this paper. Due to the methods by which data are collected and inputted into the NTDB, potential problems are encountered in terms of data accuracy. Under reporting of variables obtained from the NTDB has often been noted as a problem due to the reliability of data extraction by participating hospitals . The data is self-reported and often inputted by staff dedicated to data collection. A major variance between participating hospitals is that hospitals with more resources are more likely to have dedicated staff to data collection. This can lead to informational bias in those hospitals that are more compliant in reporting data metrics when compared to others that are not. For example, hospital data registries that have incomplete data on complications may appear to deliver better care than hospitals that consistently record all complications.

Unlike MWH, WWH demonstrated a global impairment profile with spared verbal recognition. Consistently, previous findings regarding memory impairment among PWH found this impairment to be more dependent on frontal and subcortical structures with relatively normal memory retention but impaired memory retrieval . Even in the female-specific profile of relative weakness in learning and memory, recognition was less impaired compared to learning and recall. We can only speculate as to why the sparing of recognition in the global impairment profile was specific to WWH and to verbal vs. visual memory. It is possible that, in the context of cognitive impairment in HIV, the female advantage in verbal memory may be most salient for the least cognitively taxing memory component, recognition performance, and this advantage is not fully adjusted for in our demographically corrected T-scores. Despite the heterogeneity in cognitive profiles by sex, the sociodemographic/clinical/biological factors associated with these cognitive profiles were similar for MWH and WWH suggesting that, although the same factors confer increased vulnerability to cognitive dysfunction, the adverse effects of these factors impact brain function differently in men and women. In both MWH and WWH, WRAT-4 had the greatest discriminative value of profile class followed by HIV disease variables , depressive symptoms, age, race/ethnicity and years of education. WRAT-4 scores have been consistently identified as an important determinant of cognitive function among PWH, with lower WRAT-4 scores conferring risk for cognitive impairment . WRAT-4 performance may be particularly salient in this population, given that reading level may reflect education quality, above and beyond years of education, especially in lower socioeconomic populations because of the many factors impacting education quality . Additionally,vertical farming systems reading level is associated with health outcomes including hospitalizations and outpatient doctor visits and, thus, may be a proxy for bio-psychosocial factors underlying general health . HIV disease variables were also strong determinants of cognitive profiles in both men and women.

Aside from some instances of a shorter duration of HIV disease relating to more cognitive impairment in WWH and in the total sample, the more biologically-based HIV disease variables were associated with cognitive impairment in the expected direction; higher current and nadir CD4 count and lower viral load were protective against cognitive impairment. It is curious that the global weakness with spared verbal recognition profile in women was associated with more severe HIV-related variables yet with shorter duration of HIV infection. We speculate that the shorter HIV infection in WWH may reflect CNS effects of untreated and/or early course HIV infection. Alternatively, the self-reported shorter duration of infection may not have been accurate, to the extent that WWH lived longer with untested/undetected infections. Findings are consistent with a wealth of literature relating proxies of HIV disease burden and severity to cognitive function and suggests that, even in the era of effective ART when viral suppression is common, HIV disease burden can have adverse effects on the brain possibly due to poor penetration of ARTs into the CNS, ART resistance, poor medication adherence , and/or the establishment of viral reservoirs in the CNS reservoir . In line with hypotheses of mental health factors relating to cognitive impairment profiles more strongly in women, current diagnosis of MDD was a predictor of cognitive profiles only among WWH. Although the prevalence of a current or lifetime diagnosis of MDD did not differ between WWH and MWH, MDD was an important risk factor of demonstrating Global weaknesses with spared verbal recognitioncompared to the profile demonstrating only Weakness in motor function . Our work indicates that HIV comorbid with depression affects certain cognitive domains including cognitive control, and that these effects are largest in women. Specifically, WWH with elevated depressive symptoms had 5 times the odds of impairment on Stroop Trial 3, a measure of behavioral inhibition, compared to HIV-uninfected depressed women, and 3 times the odds of impairment on that test compared to depressed MWH. In a recent meta-analysis, small to moderate deficits in declarative memory and cognitive control were documented not only in individuals with current MDD but also in individuals with remitted MDD, leading to the conclusion that these deficits occur independently of episodes of low mood in individuals with “active” MDD .

Together these lines of work suggest that MDD would exacerbate cognitive difficulties in PWH, particularly in the cognitive domains of declarative memory and cognitive control in WWH. Our study has limitations. Although we were adequately powered within both WWH and MWH , the magnitude of power was discrepant by sex considering that women represented 20% of our sample. Larger-scale studies in WWH only are currently underway. The generalizability of our findings also warrant additional study as the profiles identified here may not represent the profiles among all PWH. Due to the unavailability of data, we were unable to explore certain psychosocial factors as potential determinants of cognitive profiles. Our analyses were cross-sectional which allows us to identify determinants associated with cognitive profiles but precludes us from determining the temporal relationships between these factors and cognitive function. Although many of the related factors may be risk factors for cognitive impairment, reverse causality is possible with some of the factors resulting from cognitive impairment . Additionally, interpretation of the machine learning results should be done with care as RF is an ensemble model that is inherently non-linear in nature. This means that the importance and predictive power of every variable is specified in the context of other variables. This can lead to situations where an important predictive variable in the RF model has no significant difference in the overall comparison but has dramatic differences when included with other variables in the model. As such, this model should be interpreted as hypothesis-generating and identifies variables in need of further investigation. Lastly, because our study was focused on sex differences in cognitive profiles within PWH, we did not include a HIV-seronegative comparison group. Thus, we cannot determine the degree to which HIV contributes to sex differences in cognitive profiles. However, the independent HIV-related predictors does suggest that HIV has a role. Despite these limitations, we selected RF over linear models such as lasso and ridge regression because RF models had more predictive power and higher accuracy in this data compared to the linear models, even linear models with tuning parameters such as ridge and lasso that can used for feature selection. The results from these models mirror the P-values for the univariate comparisons , which is expected since analysis of variance and t-tests are also linear models. Moreover, RF models are more optimal for handling missing data, the inclusion of categorical predictor variables, and the use of categorical outcome measures which was the case in the present study.

RF models also account for the complexity in the data that can arise from multi-collinearity often seen in large feature sets. In conclusion, our results also suggest that sex is a contributor to the heterogeneity in cognitive profiles among PWH and that cognitive findings from MWH or male-dominant samples cannot be wholly generalized to WWH. Whereas, MWH showed an unimpaired profile and even a cognitively advantageous profile, WWH only showed impairment profiles that included global and more domain-specific impairment,cannabis grow room which supports previous findings of greater cognitive impairment in WWH than in MWH . Although the strongest determinants of cognitive profiles were similar in MWH and WWH including WRAT- 4, HIV disease characteristics, age and depressive symptoms, the direction of these associations sometimes differed. This suggests that the effects of certain biological, clinical, or demographic factors on the brain and cognition may manifest differently in MWH and WWH and that sex may contribute to heterogeneity not only in cognitive profiles but in their determinants although studies with larger numbers of WWH areneeded to more definitively test these hypotheses. It is important to detect these differing cognitive profiles and their associated risk/protective factors as this information can help to identify differing mechanisms contributing to cognitive impairment and whether these mechanisms are related to HIV disease, neurotoxic effects of ART medications, and/or comorbidities that are highly prevalent among PWH . Given the longer lifespan of PWH in the era of effective antiretroviral therapy, cognitive profiling will also inform aging-related effects on cognition in the context of HIV and perhaps early clinical indicators of age-related neurodegenerative disease. By identifying cognitive profiles and their underlying mechanisms, we can ultimately improve our ability to treat by tailoring and directing intervention strategies to those most likely to benefit. Overall, our results stress the importance of considering sex differences in studies of the pathogenesis, clinical presentation, and treatment of cognitive dysfunction in HIV. Traumatic brain injury is a significant public health concern as it is a leading cause of mortality, morbidity and disability in the United States. According to the World Health Organization, TBI is expected to become the third leading cause of death and disability in the world by 2020. In the United States TBI contributes to a third of all injury-related deaths. The leading causes of injuries resulting in TBI prevalence are traffic related, such as motor vehicle crashes, or non-traffic related, such as falls. Notably, up to 51% of all TBI patients have substance use exposure at the time of injury. Substance use includes alcohol and drugs such as marijuana. Current existing research suggest that in general, substance-exposed patients may have worse TBI outcomes, including greater rates of mortality and severity of injury. Research has also shown that substance use exposed TBI patients suffer worse functional outcomes, which can result in socioeconomic burden to patients and the nation at large. This healthcare burden has been calculated to be approximately $76.5 billion in 2010 alone. There is a substantial body of research elucidating the role alcohol plays in injuries that lead to TBI prevalence and outcomes. Specifically, alcohol use results in impairments such as diminished motor control, blurred vision, and poor decision making, which has been shown to increase the risk of traffic related injury.

This research has been used to create public health policies and prevention programs that have made a significant health impact, such as reducing the number of alcohol-impaired drivers. Other substances have not been as well studied. For example, marijuana is a drug that despite being federally and legally regulated, remains the most widely used drug in the U.S. Marijuana use has been shown to result in similar cognitive impairments as alcohol use, such as lack of coordination, inability to pay attention, and decision-making abilities, suggesting marijuana users are similarly at increased risk for TBI. There is some indirect evidence of this, in that it has been shown that marijuana users in general are about 25% more likely to be involved in a motor vehicle crash and that the older adult marijuana users have a greater risk for falls. However, concrete data linking marijuana exposure at time of injury and TBI prevalence and severity is scarce. Adding to the concern, national surveys on drug use and health have documented an increase in individual daily marijuana use over the last 5 years. As the number of states legalizing marijuana for both medical and recreational use increases, it is imperative to resolve the ambiguity within the research available regarding the relationships between marijuana exposure at time of injury, mechanism of injury, and TBI prevalence and severity. This study found that the presence of THC was significantly associated with lower GCS scores and a potentially more severe TBI, but this relationship was significant without controlling for other predicting variables. Furthermore, a significant relationship was found between GCS scores, age, and blood alcohol levels at the time of presentation in the ED. Older participants were found to have higher GCS scores, indicating a less serious brain injury. Study participants who had higher blood alcohol levels were found to have lower GCS scores, indicating a more serious brain injury. Age and higher blood alcohol levels were found to be associated, with higher blood alcohol levels noted in younger patients. A linear regression showed different results when examining the relationship between the presence of THC and GCS scores, hence TBI severity. When controlling for all other variables, the presence of THC was not found to be an independent predictor of TBI severity.

In the oldest age decade, the H+/D− group had the highest positive psychological factors, suggesting an important relationship between these positive psychological factors and being able to live a relatively long, non-depressed life as a person living with HIV. Hence, positive psychological factors may be protective for PLWH. Individuals’ subjective health ratings may provide valuable insight to their overall well-being, as previous studies have shown an association between reported worse health ratings and an increased risk of mortality . This finding may also reflect a potential “survivor effect” given that these older individuals have had HIV for longer and as long-term survivors, may view living with HIV more positively compared to prior expectations. This study has strengths in its multi-cohort design methodology that allows us to examine the combined effects of HIV and depression on HRQoL across age cohorts; there are also some limitations, however. For example, we were not able to address questions regarding the onset of depressive symptoms in relation to HRQoL or the positive psychological factors. For instance, depression may lead to less resilience and grit or vice versa. Like prior studies , we found a higher proportion of elevated depressive symptoms among PLWH, and individuals with elevated depressive symptoms reported lower HRQoL and positive psychological factors. There may be other factors related to depression and acquiring HIV not captured by our present variables that may account for the difference in depressive symptoms by HIV status. Another limitation is the small sample size per group, especially within the H−/D+ group. Furthermore, the sample, particularly the within the PLWH groups, was predominantly male and these results may not be generalizable to females. However, within the United Sates the majority of middle-aged to older PLWH are male; thus, our study cohort is similar to the broader characteristics of PLWH in the U.S. . Given the negative consequences of depression in PLWH, it is important to identify those in greatest need of treatment.

Prior work has highlighted the usefulness of cognitive behavioral therapy for depression treatment among PLWH,rolling grow benches even in those with advanced HIV disease . Furthermore, meta-analytic work has shown psychotherapeutic interventions reduce depressive symptoms in PLWH, which in turn may lead to improved psychiatric and medical outcomes . With this said, older PLWH are less likely to be engaged in behavioral health treatment for depression than younger PLWH, highlighting the need to address underlying factors contributing to the lack of adequate mental health treatment among older PLWH . However, increasing or improving positive psychological factors may provide one potential avenue to mitigate depressive symptoms.Neisseria gonorrhoeae and Chlamydia trachomatis are the two most common bacterial sexually transmitted infections worldwide, estimated to have caused 87 and 127 million infections, respectively, in 2016. Men who have sex with men are disproportionately affected by STIs, including N. gonorrhoeae and C. trachomatis. Infections by N. gonorrhoeae and C. trachomatis can increase the risk of HIV transmission and acquisition, mediated through ulceration and mucosal inflammation. Extragenital chlamydia and gonorrhea infections are common among MSM and are of public health importance. Recent rectal gonorrhea or chlamydia infections have been associated with increased risk for HIV acquisition. Pharyngeal N. gonorrhoeae infections are also important, as they can serve as a reservoir for antimicrobial resistance. Extragenital infections are commonly asymptomatic and screening is necessary to make a diagnosis. The U.S. Centers for Disease Control and Prevention recommends at least annual screening for rectal and pharyngeal infections among sexually-active MSM. The World Health Organization guidelines also support periodic screening for rectal and urethral infections among MSM. Data regarding extragenital N. gonorrhoeae and C. trachomatis infections are primarily from high-resource settings. A recent meta-analysis of STIs in PrEP users found nearly one in four had chlamydia, gonorrhea, or syphilis at PrEP initiation. However, few reports from low resource settings were included in that meta-analysis, highlighting the need for additional data from these settings. In low-resource settings, there are significant infrastructure and cost barriers that limit the widespread availability of diagnostic tests needed to screen for extragenital N. gonorrhoeae and C. trachomatis.

Understanding the burden of gonorrhea and chlamydia in low-resource settings is also important for HIV prevention, as it can often be an entry point into HIV pre-exposure prophylaxis programs that are being scaled up worldwide. In Vietnam, the 2013 HIV/STI Integrated Biological and Behavioral Surveillance sampled 1587 MSM across the country and found a 5% prevalence of urethral chlamydia and <3% of urethral gonorrhea. That report found a 10% prevalence of rectal chlamydia and <3% of rectal gonorrhea, but oropharyngeal testing was not performed. Aside from that report, data regarding the prevalence and risk factors for extragenital chlamydia and gonorrhea infections among MSM in Vietnam are scarce. A better understanding of the prevalence and correlates of N. gonorrhoeae and C. trachomatis infections among MSM in Vietnam is needed to effectively plan for STI screening, diagnosis, and prevention programs in the setting of limited resources, especially in the context of the rapid scale-up of HIV PrEP programs. The objectives of this study were to determine the baseline prevalence of urethral, rectal, and pharyngeal N. gonorrhoeae and C. trachomatis infections within a cohort of HIVnegative MSM in Hanoi, the capital and second-largest city in Vietnam, and to examine the factors associated with N. gonorrhoeae and C. trachomatis infections. Between July 2017 and April 2019, MSM were recruited to participate in the Health in Men -Hanoi study, a prospective, observational cohort designed to investigate the prevalence and incidence of HIV and STIs, as well as the social and behavioral characteristics within this population. Participants were recruited from concurrent HIV and STI surveys among MSM that utilized time-location sampling, respondent-driven sampling, and internet-based sampling methods. Recruited individuals presented to the Sexual Health Promotion Clinic at Hanoi Medical University where informed consent and study enrollment were completed. Cohort inclusion criteria were: assigned male sex at birth, aged ≥ 16 years, having oral or anal sex with another man or transgender woman in the prior 12 months, living in Hanoi continuously for the prior 3 months and without a plan to move in the next two years, and serologically confirmed to be HIV-negative at baseline. At the time of the study, no participants were enrolled in a PrEP program, as PrEP was not available in Vietnam. Data collected at baseline in the sub-sample of HIV-negative MSM were used for this study.

Socio-demographics, substance use, sexual practices, history of STIs, and history pertaining to HIV counseling, testing, treatment, and care services, were collected through audio computer-assisted self-administered interviewing . Group sex was defined as more than one partner in a sexual encounter in the prior six months. Participants were asked about any rectal and genitourinary symptoms in the prior 6 months. Rectal symptoms were classified as any of the following: dyschezia, pruritis, bleeding, discharge, or ulcers. Genitourinary symptoms were classified as any of the following: dysuria, discharge, bleeding, pruritis, or ulcers. All participants received client-centered HIV and STI risk-reduction counseling. Urine samples, rectal swabs, and pharyngeal swabs were collected using cobas PCR urine sample kits and cobas PCR female swab collection kits and were tested for N. gonorrhoeae and C. trachomatis by NAAT on the cobas 4800 CT/NG v2.0 system . Blood was collected for HIV testing and was performed on the ARCHITECT HIV Ag/Ab Combo . Serologic testing for syphilis was done using the Architect Syphilis TP assay , with positive samples undergoing rapid plasma reagin testing and Treponema pallidum hemagglutination , as indicated . All participants with a positive NAAT for C. trachomatis or N. gonorrhoeae were considered to have an infection. Test results for C. trachomatis or N. gonorrhoeae were classified as missing if a specimen was not available for testing or if the testing had inconclusive results. Those with a positive T. pallidum-specific antibody and a measurable RPR were considered to have a syphilis infection. Descriptive statistics were applied to socio-demographic, behavioral,drying cannabis and clinical data. Predictive logistic regression modeling was used to evaluate factors associated with N. gonorrhoeae and C. trachomatis infections separately and the combined outcome of having either infection. Variables for consideration were selected a priori using an approach that included variables based on biologic basis, as well as known risk factors and confounders. The variables included in the bivariate analyses were: age, education, income, ATS use for sex, group sex, meeting sexual partners via mobile apps, prior diagnosis of STIs, and genitourinary orrectal symptoms. Symptom status was dichotomized for the logistic regression models. All variables in the bivariate analyses were also included in the multivariate analysis, with the exception of any substance use in the prior 3 months and amphetamine-type stimulantuse in the prior 3 months, which were excluded from the multivariate analysis due to high collinearity with ATS use to enhance sexual performance in the prior 6 months. Records with missing variable data were excluded from the logistic regression models. All data analyses were done using R version 3.61. There were 1498 participants in the baseline survey. Nine did not have any samples for N. gonorrhoeae and C. trachomatis testing and were excluded from the analysis. Among the remaining 1489 participants, the median age was 22 years . Income in the prior month was less than 5 million VND for 40.5% of participants and 30.8% had completed university education. Substance use in the prior 3 months was reported by 8.3% of participants and 6.5% reported using ATS to enhance sexual performance in prior 6 months. Among those reporting anal sex in the prior 6 months, 32.1% had insertive sex, 30.0% had receptive sex, and 29.5% had both.

Condomless anal intercourse in the prior 6 months was reported by 57.6% of participants. Anal sex with two or more partners in the prior month was reported by 31.8% of participants. Group sex in the prior 6 months was reported by 24.9% of participants. Over half of participants reported meeting sexual partners via websites or mobile apps in the prior 6 months. There were 841 participants who did not have genitourinary or rectal symptoms in the prior 6 months. There were 235 participants with a prior diagnosis of chlamydia, gonorrhea, or syphilis. The prevalence of syphilis was 18.3% . There were 1378 participants included in the analyses of factors associated with N. gonorrhoeae, C. trachomatis, or either N. gonorrhoeae or C. trachomatis infection, excluding those with missing variable data . In the multi-variable analysis of the combined N. gonorrhoeae or C. trachomatis outcome, those aged 25-34 years had lower odds of infection compared to those with ages 16-24 years . This was largely contributed to by C. trachomatis infection . Other independent factors associated with having either N. gonorrhoeae or C. trachomatis infections included having two or more recent sex partners , condomless anal intercourse in the prior six months , which was driven by C. trachomatis , and meeting sexual partners via mobile apps or the internet , which was driven by N. gonorrhoeae . Genitourinary or rectal symptoms in the prior 6months and group sex were associated with infections in bivariate analysis, but not in the multivariate model. A prior STI diagnosis and ATS use to enhance sexual performance were not associated with any infections in the multi-variable models. .In this study of young, HIV-negative MSM in Hanoi, Vietnam, we found a high prevalence of N. gonorrhoeaeand C. trachomatisinfections with more than one in four participants having one of these infections at baseline. Rectal infections occurred in 73.9% of those with chlamydia and 70.5% of gonorrhea infections occurred in the oropharynx. Limiting testing to the urethral site would have missed nearly three-quarters of C.trachomatis or N. gonorrhoeae infections within this cohort, as 27.4% of infections occurred in the urethra. Half of all persons with chlamydia or gonorrhea were asymptomatic, and reporting genitourinary or rectal symptoms were not associated with infections, highlighting the need for routine screening in this population. Prior surveys of urethral chlamydia or gonorrhea in Vietnam found a similar prevalence of C. trachomatisand N. gonorrhoeae , compared to the overall urethral prevalence of 7.1% and 1.3%, respectively, we reported here. While data on extragenital chlamydia and gonorrhea within Vietnam are very limited, surveys from Ho Chi Minh City, Hanoi, and Nha Trang including urethral, rectal, and pharyngeal testing among HIVnegative male sex workers, many of whom are MSM, found a high overall prevalence of N. gonorrhoeae, up to 29%, and up to 17% for C. trachomatis, although data stratified by anatomical site were not reported.

The potential applicability of the interest group mechanism identified in this paper across policy domains also has implications for fundamental models of lawmaking in American politics. Standard models conceive of lawmakers as primarily driven by the preferences of the median voters in their districts, which are generally taken as exogenous . Alternative perspectives suggest that lawmakers are primarily responsive to the pressures of organized interests seeking to advance policy goals, and moreover, that the ability of competing groups to influence politics is structured by the existing policy-scape . Findings presented here support the notion that existing policy, in part by shaping interest group capacities, affects congressional representation. This paper therefore provides quantitative empirical grounding for the difficult-to-test arguments in favor of the policy-focused approach— and one empirical framework for scholars working in this vein.Wealthy foundations have taken on increasingly prominent roles influencing education policy in the U.S. This paper uses a mix of qualitative and quantitative evidence to study the drivers and implications of the engagement of major foundations in the politics of charter schools. I show that states that adopted favorable charter laws, in addition to empowering charter schools as political actors, also drew wealthy foundations into the charter policy space by enabling them to make investments in developing new schools. Foundations later sought to protect those investments, leveraging strategic grant-making to drive the growth of a pro-charter advocacy network with national scope. Findings underscore the importance of state policy experimentation in catalyzing new interest group coalitions,commercial racks with implications for ideas about policy reform in American federalism.

In recent years, contests over policies governing charter schools have generated some of the most hard-fought battles in state politics. In 2016, Massachusetts voters rejected a ballot initiative that would have lifted the state’s cap on charter schools to allow 12 new schools each year after a $33 million campaign—at that point the most expensive in the state’s history. A few years later, in 2019, on the other side of the country, California Governor Newsom signed legislation adding restrictions to new charter schools after a big-money campaign pitting teachers unions against charter advocates. That teachers unions and other incumbent organized interests in the K-12 education sector would resist charter schools makes good sense. Teachers unions are some of the most active and well-resourced organized interests in American politics, particularly at the state and local levels where most education policy is made . Teachers at charter schools are much less likely to be unionized , so the rise of charter schools poses an acute threat to their continued strength. And while funding formulas vary across the states, broadly speaking, the more students enroll in charters the less funding is available to district schools, so the growth of charter schools also threatens union jobs in the long run. What is somewhat more surprising is the emergence of a well-resourced pro-charter advocacy coalition battling to defend and expand chartering. This coalition often includes charter schools themselves, who also are sometimes able to drum up grassroots support among the parents of their students. But, as of 2017, charter schools only enrolled about 6 percent of all public-school K-12 students . Even large charter networks like The Knowledge is Power Program do not have the resources to go toe-to toe with teachers unions in the political sphere. And charter school parents are usually lower income people of color—not a group seen as particularly powerful in American politics. More fundamental to the pro-charter political coalition than the schools themselves are wealthy philanthropists and the advocacy groups they fund.

For instance, Great Schools, which spent $23.6 million in 2016 to try to raise a cap on the number of charter schools in Massachusetts was bank-rolled primarily by the Walton family and Michael Bloomberg . Indeed, existing research has documented how the coordinated engagement of wealthy foundations has been fundamental to the emergence of a pro-charter coalition of interest groups combining a national scope with local on-the-ground presence . This paper traces the emergence and growth of this pro-charter coalition and studies its implications for the politics of education. I argue that the rise of the pro-charter education coalition depended fundamentally on early policy victories during a particular “window of opportunity” for the charter school movement. Advocates took advantage of the broad attention to education reform in the 90’s and early 2000’s to pass “charter laws” across a wide range of states. These laws provided a legal framework for new charter schools to be authorized. I show that, even though a majority of states adopted charter laws in this period, charter sector growth depended fundamentally on a smaller set of states with highly pro-charter policies. This growth, I argue, was essential for building a broader political coalition supported by foundations. In the 90’s and early 2000’s, foundations’ primary role was to provide financial and technical support to charter schools to get up-and-running. But the involvement of these foundations in directly supporting schools and other charter operations planted the seeds for subsequent political engagement. As charter schools grew and came under increasing pressure from hostile teachers unions, foundations recognized that the continued growth and viability of the charter school sector depended not just on their operational support— but also on the development of a pro-charter political coalition. Drawing on data submitted to the IRS by non-profit organizations , I document a shift in foundation grant-making towards greater political advocacy. Elite interviews suggest that key foundations recognized the importance of building political capacity through grant-making to defend earlier investments in the charter movement. The consequences of the rise of this foundation-funded, nationally scoped, political coalition have been profound.

Exploring several mini-cases, I show how foundation-funded groups have been fundamental to efforts to expand charter schools to new locales—and seek to defend charter schools in places where they have gained a foothold. This analysis has implications for our understanding for how reforms challenging incumbent vested interests can unfold over time. As Finn, Manno, and Wright write: “Aside, perhaps, from mayoral control, chartering is by far the most significant manifestation of structural and governance innovation in public education…” . What is interesting about this case for the literature on public policy reform is that, unlike other durable reforms , the advent of charter schools—except in some extreme cases like New Orleans —has largely failed to dislodge incumbent education interests. While charter school policy reforms have, to an extent, politically empowered charter schools and charter networks themselves,greenhouse rolling benches these interests have been less important to the broader pro-charter coalition than foundations. More so than generating their own interest group supports by conferring benefits , early charter laws changed the politics by drawing previously sidelined political actors—in this case, foundations—into the charter coalition. The role of philanthropists in politics is a growing and important topic of study in political science . With greater inequality concentrating wealth at the top of society, foundations have developed ever-greater financial resources . In addition, a growing cadre of living donors have sought to leverage strategic grant-making and political engagement to accelerate structural change by driving policy shifts . But this paper shows the relationship also goes in the other direction: how foundations engage in politics is shaped by prior policy decisions through policy feedback dynamics . The paper unfolds as follows. I first provide background on the growth of charter schools in the U.S. and discuss the importance of state policy decisions for the charter school sector. I then trace the emergence of a pro-charter political coalition, highlighting the role of state experimentation with charter laws in building this coalition. I proceed to present several minicases that underline the importance of this pro-charter political coalition to expanding and defending charter laws. Finally, I discuss implications for understandings of policy reform over time in American federalism and conclude. Laws allowing for the establishment of public charters schools were adopted in 40 states in the 90’s and early 2000’s. The first to adopt was Minnesota, which passed its charter law in 1991. The federal government also adopted new charter school policy in this period. The Federal Charter School Program, initiated in 1994 by amendments to the Elementary and Secondary Education Act, directed critical funding to support the growth of charter schools in states that allowed them . The expansion of charter schools generally coincides with greater choice in K-12 education. Where charters have become established, parents can opt to send their children to either publicly funded charter schools or district schools tuition-free. Charter schools are publicly funded, but privately operated. Governance from authorizers under state jurisdiction, versus local school districts, generally allows them greater autonomy than traditional public schools Charter schools’ political momentum came in part from renewed attention to education policy in the 80’s and 90’s. Several reports were published in the early 1980’s highlighting major issues in the American K-12 education system.

The most famous of these was A Nation at Risk , which famously claimed that: “Our society and its educational institutions seem to have lost sight of the basic purposes of schooling, and of the high expectations and disciplined effort needed to attain them” . The report’s call for politicians to pay greater attention to education was heeded, even as the analysis underpinning its key findings were later disputed . In the 1980’s, the states and the federal government experimented with a wide range of education reforms ranging from teacher certification standards to more standardized testing to school-based management. Most of the reforms adopted in this period operated within the highly bureaucratic system established by progressives in the early 20th century. Indeed, new policies on standards and testing were designed to further bureaucratize and centralize the education system. These types of reforms, Chubb and Moe argued in their influential Politics, Markets, and America’s Schools, were destined to fail, since they failed to address the institutional problems underlying K-12 education’s woes. The most important factor determining a school’s performance, they proposed , was its level of autonomy. And a top-down bureaucratic management structure was anathema to holding schools accountable while maintaining school autonomy. Market control, versus democratic control, they argued, would allow for greater school autonomy and, as a result, improved academic performance. Chubb and Moe thus pushed for an alternative set of reforms aimed at decentralizing the education system, instilling choice, and leveraging market competition to achieve improvements. Similar ideas were also being promoted on the left side of the political spectrum. In 1988, University of Massachusetts professor Ray Budde released Education by Charter: Restructuring School Districts.Budde advocated for allowing innovative teachers to apply for special charters to create new programs, thus devolving authority down to teachers and enhancing their autonomy. American Federation of Teachers president Al Shanker latched onto the chartering concept and promoted it as a way for teachers and their unions to maintain their central role in the face of seemingly inevitable education reforms. Chartering thus emerged in this period as a “middle-path” between the highly rigid existing system and a privatized system of vouchers promoted by those on the far right of the political spectrum . Policy entrepreneurs first took chartering from concept to law in the state of Minnesota. The effort was led by Joe Nathan, a former Minnesota teacher who had written a book promoting the charter school concept and then worked for the National Governors Association’s education reform group commissioned by Lamar Alexander and Bill Clinton. Nathan partnered with Ted Kolderie from Citizens League, a moderate “good government” Minnesota think-tank, and former State Senator Ember Reichgott Junge to develop and enact a bill that would put in place a process for schools to apply for charters to operate independently of school districts. The Minnesota bill was ultimately supported by a minority of the Democratic party , but by enough Republicans to pass. Bipartisan support within the “window of opportunity” generated from attention to education reform was critical to overcoming opposition from teachers unions and school boards in Minnesota, and later, elsewhere . Contrary to Al Shanker’s hopes, charter laws generally did not establish a role for teachers unions in the chartering process, instead generally specifying that new charter schools could operate outside of negotiated collective bargaining contracts.

The model includes a linear time variable to account for broader trends like growth in lobbying from distributed solar. I estimate multilevel models with random effects at the firm, state, and year levels to account for the hierarchical structure of the data. In column of Table 2, the outcome variable is a binary measure of whether a firm lobbied in a particular state-year .In column , the outcome variable is the total number of lobbying registrations attributed to a particular firm . For this specification, I estimate a negative binomial model since the outcome is an over dispersed count variable . Finally, in column , the outcome is logged lobbying expenditures for the limited sample of states for which these data are available. Across specifications, results, presented in Table 2, indicate that firm lobbying in a state is increasing in its installed TPO capacity in that state and its installed capacity in other states . The coefficients in column indicate that a doubling of in-state capacity is associated with an 8-percentage point increase in the likelihood of an installer lobbying, while a doubling of out-of-state capacity is associated with a 5-percentage point increase likelihood of an installer lobbying in any particular state. Results from the negative binomial model also indicate that both in-state and out-of-state capacity matter for lobbying. The coefficient of .47 in column suggests that a 1 percent increase in in-state capacity installed for a firm is associated with a .47 percent increase in number of retained lobbyists in that state ; the coefficient of .48 indicates that a 1 percent increase in out-of-state capacity is associated with a .48 percent increase in number of retained lobbyists in a given state . I recover consistent results in the limited sample of states using logged lobbying expenditures as the outcome in a linear model. The coefficients suggest that a doubling of in-state capacity is associated with a 71 percent increase in lobbying expenditures,hydroponic shelf system while a doubling of out-of-state capacity is associated with an 85 percent increase in lobbying expenditures in any particular state.

By showing that firm lobbying in any particular state depends on firm economic strength both within that state and across the states, these findings also suggests that policy in one state affects lobbying in another. That’s because state policy affects installer business growth , which in turn drives installer lobbying across the states due to the horizontal mobilization of firms. A particularly important case of cross-state feedback is where firms apply growth in states with favorable policy environments to seek to shape policy in potential new markets. To examine this dynamic, I track the economic and political presence across the states over time for the two largest and most politically active rooftop solar firms over the period: Sunrun and SolarCity. As illustrated by Table 3, both firms significantly expanded their political and economic presence from 2014 to 2016. While there is certainly significant overlap in the states where the firms were economically and politically active, both firms hired lobbyists in a number of states in which they were not selling systems. In 2016, for instance, SolarCity lobbied in 10 states in which it was not actively selling systems; Sunrun lobbied in 11 states where it did not have an economic presence. In many cases, these firms hired lobbyists in advance of economic expansion to particular states . To summarize, I have shown that: 1) favorable rooftop solar policy leads to rooftop solar industry growth, 2) rooftop solar industry growth leads to greater lobbying from rooftop solar industry both in the states where growth takes place as well as in other states, 3) rooftop solar firms have in a number of cases sought to influence policy in states where they are not yet active, and 4) installer lobbying is associated with more favorable policy, particularly in places where the industry has less of an economic presence. Taken together, the empirical analyses trace out a causal process whereby adoption of favorable rooftop solar policies in leading states affected the interest group politics—and ultimately policy decisions—in other states. Of course, the empirical analysis is not without its limitations. In particular, establishing causal inference in policy feedback and interest group influence research is a major challenge . In this case, neither policy enactment nor interest group lobbying is randomly assigned, nor are there apparent natural experiments to leverage.

Yet, by bringing together a multitude of both state- and firm-level data, this paper provides evidence in support of the proposed theoretical framework, and an empirical setup on which scholars working across different policy areas can build. In addition, the evidence presented does not rule out that traditional diffusion mechanisms of learning and competition have also shaped state-level rooftop solar policy and politics. It clearly demonstrates, however, that these traditional mechanisms are not the whole story. An analysis of interdependent policy making in this case that failed to consider the effects of state policies on the resources installers had at their disposal to engage politically in other states would be incomplete. Moreover, it is likely that the dynamics of cross-state policy feedback on interest group politics studied here can also serve to facilitate mechanisms of learning and competition. For instance, when installers lobbied in states where they had yet to establish an economic presence, they likely initiated a learning process among state lawmakers. Future research building on this paper might seek to refine methods for distinguishing the types of policy feedback spillovers explored here from traditional diffusion mechanisms. The standard policy diffusion designs are limited in their ability to parse mechanisms , and the feedback dynamics studied here will not always lead to diffusion in a strict sense. Broadly speaking, studying intergovernmental policy feedback in a federal context requires close attention not just to patterns of policy adoption in different units, but also to the political engagement of organized interests across the federal system. Scholars might pay particularly attention to two particular types of groups: first, groups with federated structures that can swiftly leverage resources from one jurisdiction to influence policy in another; and second, business interests seeking to expand. Studying the intergovernmental effects of policies on interest group politics also likely requires examinations over longer periods of time than conventional policy diffusion approaches. Diffusion mechanisms like learning and competition might manifest quickly—since they depend only on the beliefs of lawmakers—while the intergovernmental feed backs studied here depends on long-run shifts to interest group systems.

Indeed, the case of rooftop solar examined here is likely an outlier in the speed by which state policies gave rise to new interests. By adopting this empirical approach, scholars can further extend the theoretical framework developed in this paper. A natural extension is vertical policy feedback . The organized interests that benefit from, and are strengthened by, particular state-level reforms might, in addition to advocating for the propagation of those reforms across the states, advocate for the national-level adoption of those or aligned reforms. These effects have likely been limited in the case of distributed solar, where key decisions are made at the state level. Indeed, while SolarCity, Sunrun, Vivint, SunPower, and SunEdison spent just under 9 million dollars lobbying in the 15 states that collected expenditure data between 2015 and 2017, they collectively spent just 2.25 million dollars lobbying the federal government over the same period . But there is some anecdotal evidence that the growth of the distributed solar lobby, driven in part by state-level decisions,cannabis drying racks commercial has been important to the national politics of issues like tariffs on solar panels and the Solar Investment Tax Credit . Future research might also consider the conditions under which strategic actors intentionally leverage state policy as a political tool in building a political coalition for broader reform—or seeking to dismantle opposing organized interests . Importantly, politicians often face a collective action problem in their efforts to use policy for political gain. Even when a broader party or interest group benefits from a particular policy, individual lawmakers can have incentive to defect . This collective action problem is particularly pronounced for politicians seeking to use state policy for national-level political gain . As a result, we might expect federated groups with political operations across sites and levels of government to be most equipped to strategically harness dynamics of intergovernmental policy feedback . While this paper demonstrates the force of intergovernmental feed backs on interest group politics, these mechanisms are likely more limited in other cases. The aggressive growth strategy of installers, combined with the crucial role of state policy in driving growth, provided a strong incentive for installers to mobilize politically across the states. At the same time, even as rooftop solar firms have mobilized, incumbent electric utilities have been able to prevent pro-solar reforms across a number of states, and in some cases, roll them back . Forward looking incumbents engaged across sites and levels of government in the federal system can, in this way, use the political system to prevent competitors from gaining strength. Moreover, in policy areas like immigration or marriage equality, where sub-national policy decisions are less likely to engender major shifts in the broader interest group landscape, we are unlikely to observe strong policy feedback spillovers operating through organized interests. But at the same time, there are a broad swath of policy issues for which the mechanisms I explore here are likely quite relevant. Indeed, the emergence of supportive interests with a stake in new policy regimes is a fundamental feature of sustainable policy reforms .

These mechanisms are particularly relevant to the politics of the energy transition, where liberal leaning states have led the way, but where there are significantly more greenhouse gas emissions to be abated in conservative-leaning areas. While rooftop solar is just a small piece of the energy transition, similar ideas apply to other elements like utility-scale renewables and energy efficiency . In general, policy feed backs in energy governance tend to be quite powerful, since policies that replace fossil fuel infrastructure with clean energy infrastructure also replace fossil fuel interests with clean energy interests . More broadly, states play important regulatory roles across a number of policy areas, and their decisions can affect the political resources of organized interests active in other states. For instance, in the education system, state policy has been instrumental to the steady growth of charter schools in recent years, which in many states and districts now pose a meaningful challenge to the traditional public-school model—as well as to the teachers unions that draw strength from that model. As charter schools have grown, so has the charter school lobby, as wealthy foundations have allied with charter networks to push forward policies across the states, and also in local and federal politics . The general scope conditions for these types of effects are quite broad. Sub-national policies must give rise to new organized interests or significantly influence the capacities of existing interests. And the organized interests affected by sub-national policies must leverage newfound strength to mobilize horizontally across the federal system. Though this paper focuses specifically on the effects of state policies on business interests, elements of the proposed perspective also likely apply to other types of organized interests , as well as to sub-national jurisdictions apart from the US states .There are reasons to think, in addition, that these types of dynamics are at play even in some areas where we do not observe shifts to policy or interest group landscapes: they can be baked into the status quo. The period of rooftop solar policy and politics I study saw massive policy and interest group changes over a relatively short period of time, which renders the dynamics of policy feedback across the states highly visible. Similar mechanisms, though, can enforce policy stability across the federal system. Many powerful organized interests draw strength from policies in place in jurisdictions across the federal system and use their resources to block threatening policies at multiple sites and levels of government . These dynamics are difficult to study since they tend to lead to non-action. But studying policy areas in flux like rooftop solar can provide insight into forces of stability. Drawing on policy feedback literature and literature on congressional representation, I argue that, because of this institutional configuration, sub-national policy adoption can affect national representation.

The second core mechanism is competition . Because federal units compete for mobile businesses and residents, sub-national governments can be pressured to adopt attractive policies pursued in other units—or risk losing tax revenue and economic activity.The policy diffusion perspective has been highly fruitful. It has shed light on the degree to which policy decisions by governments are interdependent and explored several compelling mechanisms that drive this interdependence. But, I argue, this perspective is incomplete. It fails to fully account for the role of interest groups in the policy process—and how prior policy decisions across the federal system shape interest group politics. Policy diffusion scholarship focuses primarily on re-election motivated lawmakers who learn and compete because they, broadly speaking, want to produce good policy outcomes for their constituents. Yet, we know that much more goes into policy decisions besides lawmakers seeking good policy. Significant policy reforms usually represent just the final outcomes at the tail end of hard-fought political battles—which generally continue post-enactment in the implementation phase. These battles can draw a diverse array of interest groups like businesses, unions, and citizens groups, as well as government bureaucrats. Painting a complete picture of policy interdependence in American federalism therefore requires considering how prior policy decisions adopted across the federal system construct and empower political actors engaging across the federal system. That is the approach taken in this dissertation. I focus primarily on organized economic interests,indoor vertical garden system whose engagement is among the strongest drivers of policy decisions in American politics broadly , and who are particularly important in considering policy reforms that affect sectors of the economy.

Literature studying “policy feedback” has demonstrated the powerful ways in which the public policy landscape affects the representation of organized economic interests in the political system . For instance, the public policy landscape shapes the types of firms that grow and prosper—and as a result, which have the capacity to influence politics . Similarly, public policies like collective bargaining rules affect the ability of unions to grow and maintain membership, which in turn influences their political sway . Shifts 1 In the international sphere, Elkins and Simmons similarly categorize diffusion as either “adaptation to altered conditions” and learning. in policy, therefore, can affect the power of different organized economic interests in the political system. In a federal system of government in which states have significant authority and interest groups are active at multiple sites and levels of government, I argue that policy feedback effects on interest group politics can also generate powerful policy inter dependencies—in some cases driving the spread of policies across jurisdictions. More specifically, state-level reforms can increase the political power of interest group coalitions supporting the geographic and jurisdictional expansion of those reforms. These dynamics can play out, first, horizontally across the states. State-level reforms that benefit existing organized interests, or give rise to new ones, also tend to strengthen them politically. The groups that benefit from particular state-level reforms are likely to also benefit from the propagation of those reforms to other states. Thus, these groups might apply newfound strength to propagate reforms horizontally through lobbying and other political activities. The political implications of state-level reforms are not restricted to other states. The groups that benefit, and are politically strengthened, by a state-level reform might also leverage newfound strength to advocate for aligned reforms at the federal level. The geographic structure of representation in Congress provides a key avenue for this type of vertical, state-national feedback. Members of Congress represent geographically demarcated districts that are embedded in state policy landscapes.

Shifts to those landscapes precipitated by state policy reforms can in turn affect the political pressures that members face. More specifically, to the extent that state policy reforms influence state political economies, this can affect the ability of organized economic interests to engage in politics and make demands on their representatives. Finally, reforms achieved at the state level can affect the national interest group politics by drawing new actors into pro-reform coalitions. This dynamic is particularly relevant in considering the engagement of philanthropists, a growing topic of study in political science . State policy experiments can provide a proof-of-concept of the legitimacy of some set of reforms, and thus draw philanthropic investment. Once invested, foundations might use their financial resources to fund advocacy groups working to propagate those new policies. In the empirical portion of the dissertation, I apply this new theoretical perspective on policy interdependence in American federalism to three policy cases: rooftop solar policy, marijuana policy, and charter school policy. These are each areas in which state governments have taken the lead on driving forward policy reforms with major implications for sectors of the economy, and where, as I show, state government action has had implications for the interest group politics in the broader federal system.Even more so than in the case of rooftop solar, state actions have precipitated a major shift in marijuana policy over the past 20 years. Since California pioneered legalization of marijuana for medical use in 1996, 32 other states and Washington D.C. have followed suit. As of 2020, 15 states had also legalized marijuana for recreational use. This represents a profound shift from the policy regime associated with the War on Drugs that was initiated in the 1970’s. And, like in the case of rooftop solar, these policy shifts have also engendered shifts in the interest group politics. In particular, the advent of adult-use legalization, pioneered by Colorado and Washington in 2012, has driven rapid growth in the marijuana industry from just 3.5 billion dollars of revenue in 2014 to over 13.5 billion dollars of revenue in 2019.

This has led the industry to develop a greater political presence, both in the states and at the federal level. The costs from federal prohibition have led the industry, unlike in the case of rooftop solar, to focus to a greater extent on federal policy than propagating reforms across the states. Federal lobbying from marijuana industry rose from just $45,000 in 2012 to $6 million in 2019. And members of Congress representing legalizing states have, I show, become critical allies in efforts to liberalize federal marijuana policy and resolve costly state-federal legal tension. Take Cory Gardner , for instance. There is little in Gardner’s record prior to 2012 that would indicate he would become an important marijuana proponent. Yet, during his tenure in the Senate , Gardner became a central figure in federal marijuana policy. In 2018, Gardner vowed to block judicial nominees in the Senate until he received a commitment that the federal government would not prosecute marijuana industry . In the 116th Congress, Gardner sponsored core marijuana-related legislation including the SAFE Banking Act and the STATES Act. It is no coincidence that Gardner represents the state of Colorado,clone rack which has one of the strongest marijuana industries in the country. Indeed, interview evidence suggests that the sway of marijuana industry and marijuana voters in Jared Polis’s successful 2018 bid for governor was a major reason why Gardner, who anticipated a tough re-election in 2020 , made marijuana such a priority. To test whether the relationship between state-level legalization and representation in Congress generalizes, I leverage exogenous variation in likelihood of legalization generated by variation across the states in ballot initiative rules. This exogenous variation is necessary due to the inferential challenges in estimating the effects of state policy on national representation. Broadly speaking, to the extent that state policy decisions and representation in Congress are both shaped by factors like a state’s overall ideology, I would expect a correlation between state policy and national representation without any causal relationship. Variation in the availability of citizen initiatives across the states helps to overcome this causal identification problem in the case of marijuana policy. A number of states adopted procedures allowing citizens to enact statutes or constitutional amendments directly through statewide ballot initiatives in the Progressive era of the early 20th century. In the current era, ballot initiatives have been a critical tool for marijuana policy reform. The ability to bypass state legislatures is important because, as one advocate told me, citizens tend to be much more liberal on marijuana issues than their representatives in state legislatures. As a result, legalization efforts have been concentrated in states that allow ballot initiatives, and whether states allow initiatives strongly predicts legalization both for medical and recreational use. At the same time, whether states allow initiatives is not correlated with other factors generally associated with congressional behavior such as measures of ideology. And more importantly, whether states allow initiatives is not associated with member behavior on marijuana issues prior to the wave of state legalization initiated by California in 1996. This suggests that availability of the initiative is a valid instrument for estimating the effect of state legalization on national representation in the contemporary period.

I study the 116th Congress, which, as one journalist put it, was “the first Congress in history where, going into it, it seem[ed] that broad marijuana reforms [were] actually achievable” . Broadly speaking, I find evidence that state legalization affected national representation. Members of Congress representing legalizing states were more likely to sponsor or co-sponsor key pro-marijuana pieces of legislation. They were also more likely to cast certain pro-marijuana roll-call votes. Bringing quantitative evidence and elite interviews together to investigate mechanisms, I find the most support for the role of growing industry influence in legalizing states, but also find some support for the role of the initiative vote in signaling constituent preferences. I find little support for the potential alternative hypothesis that effects were driven by positive shifts to public favorability wrought by legalization. Like in the other two cases, state policy decisions regarding charter schools have driven major shifts to a sector of the economy and society: K-12 education. Charter schools, independent but publicly funded, have grown steadily since the early 2000’s. As Finn, Manno, and Wright write: “Aside, perhaps, from mayoral control, chartering is by far the most significant manifestation of structural and governance innovation in public education…” . In 1999, there were just 507 charter schools operating. By 2017, nearly 7000 charter schools were enrolling over 3 million students—about 7 percent of overall public K-12 enrollment. Charter schools owe their existence to the adoption of “charter laws” across 40 states between 1991 and 2003, which allowed new schools to form apart from the traditional district structure. Unlike in the case of marijuana policy, but like the rooftop solar case, charter school growth presents an existential threat to powerful organized economic interests—teachers unions. Charter schools generally have much lower rates of unionization than traditional public schools. The charter sector’s growth, despite opposition from unions and other incumbent education interests, is notable. It has depended in part, I argue, on the development of a nationally-scoped network of pro-charter advocacy groups—which have on several occasions gone toe-to-toe with powerful teachers unions. In the paper, I examine the role of prior state policy decisions in seeding this pro-charter interest group network. A key difference between the charter school policy case and the other cases studied is in the types of organized interests driving the sustainability and spread of reforms. In rooftop solar policy and marijuana policy, the story is relatively straightforward: state policy decisions gave rise to new industries that leveraged their economic growth to develop greater political influence. While charter growth precipitated by state policies has similarly generated new political interests in the form of large charter networks like Success Academy and KIPP, the political power of these organizations is highly limited. Since charter schools are mostly non-profits with limited revenue streams generally funneled into operations, the political activity of these charter networks has been modest compared to large marijuana and rooftop solar firms. Given that limitation, the financial backing of philanthropists like the Gates Foundation and the Walton Family Foundation has been crucial to building the pro-charter advocacy network. But foundations’ investments in charter advocacy did not arise in a vacuum. Drawing on elite interviews, I show that state policy decisions in the 90’s promoting charter growth in leading states like Minnesota and California were instrumental to generating support from philanthropists and building the pro-charter group coalition.

The timing of follow-up visits was anchored to the date of the participant’s baseline assessment . “Pre-pandemic” observations were any assessment occurring between study entry and March 19, 2020, the date of the first state-issued stay-at-home order, so each youth could contribute multiple assessments. Among youth contributing pre-pandemic data to analyses , there were an average of 3.0 pre-pandemic assessments . During the COVID-19 pandemic, participants were invited to complete three web-based surveys in June 2020 , December 2020 , and June 2021 . Of the 348 participants included in analyses, 237 completed the June 2020 survey, 213 completed the December 2020 survey, and 195 completed the June 2021 survey. Completers of the prepandemic and during-pandemic assessments were sociodemographically similar . Among the youth contributing during pandemic data to analyses , there were an average of 2.2 during-pandemic observations. Altogether, 60 youth contributed only pre-pandemic data, 67 youth contributed only during pandemic data, and 221 youth contributed both pre- and during pandemic data. Analyses were conducted in R v4.1.2 . We estimated the impact of the COVID-19 pandemic by comparing observations of same-age youth assessed at four different time points: prepandemic , June 2020, December 2020, and June 2021. Conceptually, we used the prepandemic data to construct a reference curve for the expected drinking or nicotine use as a function of age, then compared that reference curve to the observed drinking and nicotine use as a function of age at each survey wave during the pandemic. In this way, we sought to distinguish the effects of the pandemic from age-related changes in drinking or nicotine use that would have occurred even outside the pandemic context. We restricted the sample to participants ≤ age 15.8 years at study entry to reduce potential cohort effects on drinking and nicotine use introduced by study entry criteria or by secular changes in drinking or nicotine use among U.S. young adults between 2016 and 2021 . If cohort effects were present, they would be confounded with the effect of the COVID-19 pandemic .

Preliminary analyses showed date of birth was not predictive of drinking or nicotine use in the restricted sample after controlling for age,vertical farming equipment suppliers suggesting any remaining cohort effects were minimal . In addition, we restricted observations to those of participants ages 18.8–22.4 years old at each time point, to ensure we had observations covering the same age span at each of the four assessment time points and avoid extrapolation beyond the common region of support . Outcomes included the proportion of young adults drinking or using nicotine, the number of days drinking or using nicotine among those reporting any use, and the typical number of drinks per drinking day . Regressions were fit in the geepack package , clustering observations on participant, specifying an exchangeable correlation structure, and using robust standard errors. For dichotomous dependent variables, a logistic link function was used. Model specification included fixed effects for sex, race, ethnicity, study site, age at observation, age-at-observation-squared, and time point of assessment. Participant sex, race, ethnicity, and study site were included as covariates given previous work has established they predict alcohol and nicotine use . Age at observation was included to implement our age-based identification strategy ; both linear and quadratic effects were included to account for nonlinear developmental changes in alcohol and nicotine use across this age range . Time point of assessment was a four-level categorical variable , represented by dummy variables with prepandemic as the reference level. Follow-up models investigated whether the effect of the COVID-19 pandemic varied as a function the impact of the pandemic on participants’ financial security. We expanded the primary model described above by adding the main effect of financial impact and terms capturing the interaction of financial impact with time point. We then tested the statistical significance of the interaction via a Wald test .

Regression models compared drinking and nicotine use at the three during-pandemic time points to drinking and nicotine use pre-pandemic. Fig. 1, Panel A graphs the model-estimated means for a 20-year-old participant across time points, which are interpreted next. Compared to pre-pandemic , significantly fewer participants reported any past-month drinking in June 2020 and December 2020 , with the difference no longer being statistically significant in June 2021 . Compared to pre-pandemic, those reporting any past-month drinking drank on 1.83 more days in June 2020 , with the difference no longer being statistically significant in December 2020 or June 2021 . Compared to pre-pandemic, there were no significant differences at any of the three during-pandemic time points in the number of drinks on a typical drinking day or the binge drinking or nicotine use outcomes . Tables 2 and 3 reports the corresponding effect sizes. Compared to pre-pandemic, 4–5% fewer participants engaged in past month binge drinking in June 2020 and December 2020, though neither difference was statistically significant . We did not find evidence that the degree to which the pandemic impacted participants’ financial security moderated the pandemic’s impact on drinking outcomes . We found evidence that the degree to which the pandemic impacted participants’ financial security moderated the pandemic’s impact on the number of days using nicotine among past-month users but not the prevalence of past-month nicotine use . Fig. 1, Panel B graphs the interactions for the nicotine use outcomes. Among those reporting any past-month nicotine use, participants who experienced moderate-to-extreme financial impact increased the number of days using nicotine while those with no financial impact decreased the number of days using nicotine in June 2020 . We investigated changes in drinking and nicotine use from prepandemic baseline over the first 15 months of the COVID-19 pandemic in a sample of 348 emerging adults ages 18–22 years old. Compared to pre-pandemic, in June 2020, fewer young adults reported past-month drinking, but those who did were drinking on more days. Compared to pre-pandemic, in December 2020, fewer young adults reported past-month drinking, but those who did were no longer drinking on significantly more days. By follow-up in June 2021, on average, there were no significant differences from pre-pandemic patterns of alcohol and nicotine use.

Findings are consistent with previous short-term studies showing a pandemic related increase in the number of days drinking. In our data, this change reflected a different distribution of drinking across the population: compared to pre-pandemic, fewer young adults were drinking, but those who did drank more frequently. While two previous studies found decreases in binge drinking , we did not find a statistically significant change in the number of days of binge drinking at any time point in the current study. However, the non-significant reduction we observed in binge drinking in June and December 2020 was directionally consistent with these previous studies. In addition, the time frame of measurement may explain the discrepancy: those two previous studies focused on changes earlier during the pandemic, in March and April 2020, whereas another study focusing on changes in June and July 2020 also found no significant change in binge drinking. As in one previous study , we did not find an average effect of the pandemic on nicotine use. However, this appeared to obscure opposing changes among those who suffered vs. did not experience impacts on their financial security. Relative to pre-pandemic, in June 2020, those with past-month nicotine use had increased the number of days using if they experienced financial impact and had stable or decreased number of days using if they denied experiencing financial impact . Loss of job or reduction in work hours could increase smoking during periods of boredom at home or to cope with the attendant stress . This pattern is consistent with the larger literature documenting how the pandemic may exacerbate health disparities based on pre-existing socioeconomic advantage . However, moderation of multiple outcomes was tested, so the current findings should be regarded as preliminary and await replication. This study had limitations. First,grow lights shelves findings may not generalize beyond emerging adults ages 18–22 years old . Second, for nicotine use, we did not measure the quantity used each day, which could have changed. Third, we did not consider other substances such as cannabis. Fourth, the mode of assessment differed from the prepandemic to during-pandemic assessments, potentially introducing differences.Fifth, secular changes in the rates of alcohol or nicotine use among young adults between 2016 and 2021 could be confounding the effect of the pandemic, potentially introducing bias.Sixth, pre-pandemic responses on a free-response scale had to be mapped onto the discrete response options , potentially limiting precision. Seventh, we assessed the degree to which the pandemic impacted individuals’ financial security but not the form of this impact . Eighth, pre-pandemic observations were not anchored to the months of June and December, so seasonal effects could explain part of the observed differences. We reported here the most extended follow-up to date of pandemic related changes in drinking and nicotine use in emerging adults. The study had several further strengths. We used seven years of prepandemic assessments and a rigorous age-based design to identify the pandemic’s impact over and above typical developmental changes. We incorporated three assessments spanning the first 15 months of the pandemic to study whether early changes in drinking and nicotine use persisted. Participants spanned five sites across the U.S and multiple racial and ethnic backgrounds. Finally, we focused on a critical developmental period associated with elevated risk for problematic use . In summary, in a heterogeneous group of young adults, pandemic related changes in drinking patterns were no longer detectable in June 2021. Pandemic-related increases in nicotine use occurred only for participants who reported greater impact of the pandemic on their financial security—these subgroup effects were no longer statistically significant in June 2021, though a large effect size for past-month nicotine use remained. Thus, those whose financial security has been adversely impacted by the pandemic may reflect a vulnerable group worth targeting for supports to manage drinking and nicotine use.

Continued follow-up beyond summer 2021 is necessary to verify that the pandemic’s effects on drinking and nicotine use have indeed faded and understand the pandemic’s long-run impacts of substance use trajectories into adulthood. Parkinson’s Disease treatment has been based on dopamine replacement therapy for 35 years. Yet, side effects resulting from long-term use of DA agonists, namely dyskinesias and on–off responses, are prompting investigations of alternative neurotransmitter manipulations to modulate basal ganglia function and normalize motor activity. Dyskinesias often result from lesion or disturbance affecting the transcortical loop or indirect pathway, with disruption of balance between excitation and inhibition in the globus pallidus pars externa-subthalamic nucleus-globus pallidus pars interna circuit. Thus, dyskinesias reflect altered patterns of neuronal firing in this circuit, which result in the improper selection of specific motor programs and, eventually, in the development of hyperkinetic movements . Endocannabinoids, the endogenous ligands of cannabinoid receptors, are synthesized upon demand by neurons in response to depolarization , and, once released, diffuse backwards across synapses to suppress pre-synaptic GABA or glutamate release . Because of these properties, the endocannabinoid system may offer new pharmacological targets for the treatment of neurologic conditions characterized by abnormal firing patterns. One application of cannabinoidbased therapeutics would be for dyskinetic syndromes, hyperkinetic disorders characterized by changes in pattern, synchronization, mean discharge rates, and somatosensory responsiveness of neurons in the direct and indirect extrapyramidal motor circuits . Further applications of cannabinoid-based therapeutics may extend to treatment of seizure disorders, changes in behavioral or cognitive state resulting from hypersynchronous excessive neuronal discharges in other, for example, limbic, cortical or thalamic circuits. To test the hypothesis that endocannabinoids act as endogenous antidyskinetic agents with modulatory effects on abnormal basal ganglia circuits, we examined endocannabinoid production in specific areas of the basal ganglia of rats infected with Borna disease virus and how cannabinoid agonists and antagonists affect their motor behaviors. Borna disease virus is a negative strand RNA virus epidemiologically linked to patients with neuropsychiatric disorders and Parkinson’s-plus syndromes . After infection, BD rats develop an extrapyramidal disorder with spontaneous dyskinesias, hyperactivity, stereotypic behaviors, partial DA deafferentation, DA agonist hypersensitivity, and Huntington’s-type striatal neuropathology . Our investigations revealed elevations in the endocannabinoid anandamide in the subthalamic nucleus of BD rats, associated with increased metabolic activity in this key basal ganglia relay nucleus.

A higher score on our composite measure was associated with being female, being unemployed, having greater medication load and lower mania symptomatology. Similarly, studies in BD show that poor sleep is associated with worsening BD symptoms , among other correlates. Based upon LASSO regression, TST and NA most contributed to the correlation with medication load which may be reflective of the sedating properties of many psychotropic medications . PS contributed most to the correlations with employment, and mania symptoms, which may relate to sleep fragmentation and variability that has previously been shown to be associated with these variables . Because wrist actigraphy is easily administered and is less invasive compared to an inlab sleep evaluation and is easier to get longitudinal measures over the span of weeks, it is important for future research to identify other approaches that could reduce these voluminous data to actionable insights, especially for treating patients with BD where management of sleep is paramount. Clinicians could utilize a composite measure to identify patients with poor sleep overall and triage these patients to appropriate sleep treatment options based upon their individual sleep metrics. In the future, as such accelerometry data becomes available in many different populations, it may soon be possible to identify when poor sleep begins to emerge with the possibility of predicting a mood episode to offer just-in-time clinical interventions. More research is needed to develop tools using these data for future prediction of events for clinical monitoring. Our study has some limitations. First, our analysis was cross-sectional and retrospective. Research should explore ways that changes in sleep quality longitudinally may be incorporated in this composite measure. Second, we focused on the means of sleep parameters as our main purpose was to examine an intuitive composite score for poor sleep. Future studies may want to identify whether night-to-night variability in sleep or circadian patterns can improve a composite measure . Third, in the absence of published norms for actigraphic sleep measures for healthy individuals of comparable age to our BD sample, we used our own HC sample as the normative group.

To the extent that our HC sample was relatively small and participants were not selected on the basis of having no reported sleep abnormalities,grow trays 4×4 this may have introduced some bias into the composite scores. It may be important for future studies to compare this method to other approaches which do not use a normative sample . Fourth, our sample size was small and given the number of correlates assessed with the composite score, there is a possibility of significant findings due to chance alone. However, our study evaluates a potential way to combine actigraphic measurements, and future studies with larger samples may help examine this further. Finally, we did not have measures of sleep apnea which may contribute to disturbed sleep . However, sleep apnea is often undiagnosed , and in a clinical setting, clinicians may need to base their assessment of sleep on wrist actigraphy alone. In conclusion, we found that while a sleep composite measure based upon actigraphy measures was correlated with patient characteristics similar to that in other studies, it does not add more information beyond individual sleep metrics alone and future research might benefit from selecting individual sleep metrics based on theory rather than use a composite measure approach. While our approach may have limited utility in BD, it may be important for research to examine this in other clinical groups, including those with other serious mental illnesses. As sleep becomes more frequently measured by actigraphy, efforts to improve the use and applicability of these unique data will be important for understanding the dynamics of sleep in those with BD.With the introduction of combination antiretroviral therapy mortality among HIV-infected patients diminished significantly. However, some patient subgroups have different survival patterns, and have shown less decline in death rates.These include patients with psychiatric or substance use disorders, which are highly prevalent among patients treated for HIV/AIDS.There is also a high cooccurrence between psychiatric and substance use disorders among the HIV-infected,as in other populations; and severity is greater in each type of disorder when there is cooccurrence.Together they place individuals at elevated risk for poor health outcomes. Because psychiatric and substance use disorders frequently co-occur, it is important to examine the combined impact of these disorders among people with HIV infection. Research among HIV-infected patients has shown an association between depression symptoms, HIV disease progression and mortality; and mental illness and substance abuse are barriers to optimal adherence to combination antiretroviral regimens.

One study of U.S. veterans found that survival was associated with greater number of mental health visits.Yet few studies have examined survival patterns for HIV-infected individuals who use alcohol or illicit drugs, but are generally not injection drug users, and have been diagnosed with psychiatric or SU disorders from a private health plan; nor have studies examined both psychiatric and SU disorders in relation to mortality. Previous research has shown that access to psychiatric and SU disorder care among HIV-infected patients varies based on sociodemographic factors and HIV illness severity.The current study compares mortality in HIV-infected patients diagnosed with psychiatric disorders and/or SU disorders to patients without either diagnosis receiving medical care from a private, fully integrated health plan where access to care andability to pay for care are not significant factors. We also examine the effects of accessing psychiatric or SU treatment services. Improvement in depression has been associated with better adherence to combination antiretroviral therapy and increased CD4 cell counts.Therefore, we hypothesize that accessing services is associated with decreased mortality among patients with HIV infection.We conducted a retrospective observational cohort study for years 1996 to 2007 among HIV-infected patients who were members of the Kaiser Permanente Northern California health plan. The KPNC is an integrated health care system with a membership of 3.5 million individuals, representing 34% of the insured population in Northern California. The membership is representative of the northern California population with respect to race/ethnicity, gender, and socioeconomic status, except for some under representation of both extremes of the economic spectrum.HIV infected patients are seen at medical centers throughout the KPNC 17-county catchment region. The study population consisted of 11,132 HIV-infected patients who received health care at KPNC at some time between January 1, 1996 and December 31, 2006. The study sample included all HIV-infected patients who were 14 years of age or older on or after January 1, 1996 and had at least 6 months membership during the first year of study observation .

This minimum age was chosen because the KPNC membership has very few HIV patients under age 14, children are likely to receive different psychiatric diagnoses than adolescents and adults , diagnosis of SU problems generally occurs later than age 13, and children are likely to receive services for these disorders in pediatrics departments rather than in the health plan’s specialty psychiatry and SU treatment programs. Patients could enter the study until December 31, 2006. In the data analyses, we also excluded 83 patients whose SU disorder diagnosis status was unclear . This resulted in a study analysis sample of 9751 patients.Since 1988, the KPNC Division of Research has maintained a surveillance system of patients who are HIV-1– seropositive,horticulture products ascertained through monitoring electronic inpatient, outpatient, laboratory testing, and pharmacy dispensing databases for sentinel indicators of probable HIV infection. HIV-1 seropositivity is then confirmed through review of patient medical records. Ascertainment of HIV infected patients by this registry has been shown to be at least 95% complete. The HIV registry contains information on patient demographics , HIV transmission risk group , dates of known HIV infection, and AIDS diagnoses. KPNC also maintains complete and historical electronic databases on hospital admission/discharge/transfer data, prescription dispensing, outpatient visits, and laboratory tests results, including CD4 T-cell counts and HIV-1 RNA levels. Mortality information including date and cause of death are obtained from hospitalization records, membership files, California death certificates, and Social Security Administration databases. Mortality data were complete through December 31, 2007. Antiretroviral medication prescription data were obtained from KPNC pharmacy databases. Approximately 97% of members fill their prescriptions at KPNC pharmacies, including patients whose prescriptions are obtained through the Ryan White AIDS Drug Assistance Program. ARV medication data included date of first fill, dosage, and days supply, as well as data on all refills. Patients were classified as: currently receiving combination-ARV , current dual NNRTI/NRTI ARV use, past ARV use, or never users .Psychiatric diagnoses were assigned by providers. One or more diagnoses can be coded by ICD-9 in the KPNC administrative databases.Psychiatric diagnoses selected for this study were the most common and serious psychiatric disorders diagnosed among health plan members including schizophrenic disorders , major depressive disorder, bipolar affective disorder, neurotic disorders , hysteria, phobic disorders, obsessive-compulsive disorder, anorexia nervosa, and bulimia. We examined the impact of having one or more of these psychiatric disorders in aggregate, as in prior HIV studies.31 Within the health plan, psychiatry can be accessed directly by patients. Mild cases of depression and anxiety may be addressed in primary care with medication but moderate to severe cases are referred to psychiatry. Treatment in psychiatry includes assessment, psychotherapy and medication management. Patients diagnosed with a psychiatric disorder generally return to psychiatry for individual and/or group psychotherapy and/or medication evaluations. Our measure of psychiatric treatment was whether or not a patient had visits to a psychiatric clinic after a psychiatric diagnosis,obtained from automated databases.A diagnosis of ICD-9 substance dependence or abuse can be made by the patient’s clinician in primary care, SU disorder treatment, or psychiatry as a primary or secondary diagnosis.Diagnostic categories include all alcoholic psychoses, drug psychoses, alcohol dependence syndrome, drug dependence , alcohol abuse, cannabis abuse, hallucinogen abuse, barbiturate abuse, sedative/tranquilizer abuse, opioid abuse, cocaine abuse, and amphetamine abuse; as well as multiple substance abuse and unspecified substance abuse. In our analyses we classified patients as having one or more diagnoses of substance abuse and/or dependence versus no diagnosis.KPNC provides comprehensive outpatient SU treatment available to all members of the health plan. Services include both day hospital and traditional outpatient programs,both of which include eight weeks of individual and group therapy, education, relapse prevention, family therapy, with aftercare visits once a week for ten months. In addition to these primary services, ambulatory detoxification and residential services are available, as needed. A small proportion of patients engage in residential SU treatment, conducted by contractual agreement with outside institutions. These data are available in the KPNC referrals and claims databases. As with psychiatric treatment, in the current study SU treatment initiation was measured as having one or more visits to an outpatient program or a stay in a residential SU treatment unit following diagnosis.Analyses focused on diagnoses of psychiatric disorders with and without co-occurring SU diagnoses as the primary predictors of interest. The distribution of demographic, clinical and behavioral characteristics was compared between patients with and without a major psychiatric diagnosis; statistical significance was assessed using the w2 test. The distribution of cause of death was examined by psychiatric diagnostic status ; statistical significance was assessed using the w2 test or Fisher’s exact test where table cells were sparsely populated. Cox proportional hazards regression was used to obtain point and interval estimates of mortality relative hazards associated with psychiatric diagnosis/treatment status and SU problems diagnosis/treatment status, with each of these two time dependent covariates measured at three levels: no diagnosis, diagnosis with treatment, diagnosis without treatment. With the goal of examining the joint effects of these two covariates on mortality, results are expressed as hazard ratios for combinations of psychiatric diagnosis/treatment and SU diagnosis/treatment levels, with no diagnosis of either comorbidity as the referent. These estimates were adjusted for an a priori chosen set of available covariates, including age at entry into study, race/ethnicity, gender, HIV transmission risk group, CD4 T-cell counts and HIV RNA levels and ARV treatment modeled as time-dependent covariates, year of known HIV infection, AIDS diagnosis prior to entry into study, and evidence of hepatitis C viral infection. Initial modeling results demonstrated a significant interaction between psychiatric and SU diagnosis/treatment status in Cox regression models . Therefore, relative hazard estimates of interest were obtained via appropriate linear combinations of parameter estimates from a fully saturated model .