Behavioral Economic Analysis of Medical Marijuana Use in HIV+ Patients

描述（由申请人提供）：允许使用医用大麻的州法律，包括密歇根州医用大麻计划（MMMP），由于缺乏有关影响因素的科学数据而造成政策紧张：大麻使用模式，滥用潜力，寻求/更新医疗认证的决定，大麻使用对艾滋病毒风险行为的影响，以及健康结果。该提案将通过研究密歇根州最大的艾滋病毒初级保健诊所（底特律，1700名患者）的大麻使用者艾滋病毒/艾滋病感染者（PLWHA）来解决这些知识差距，具体目标：目标1中描述了前瞻性混合方法。在120名使用大麻的PLWHA（认证的医疗使用者，非认证的治疗使用者和娱乐使用者; 40/组）中，我们将（A）使用行为经济学模拟来评估大麻需求对实验操纵单价和收入的敏感性;（B）确定大麻价格弹性，与其他药物/治疗的交叉价格弹性以及收入弹性是否在大麻使用者群体中存在差异。目标二。在36名使用大麻的PLWHA（经认证的医疗、非认证的治疗和娱乐使用者;目标1中的12名/组）的子集中，进行基于实验室的、双盲、安慰剂对照的大麻吸烟评估（从3.5% δ 9-THC香烟中累积0、4、8和12次抽吸）。我们将（A）确定大麻使用组之间症状缓解和滥用倾向的大麻剂量效应曲线是否不同;（B）比较各组之间吸食大麻的需求;（C）比较实验（"金标准"）和自然主义吸烟效应的强度。目标3：在与目标1相同的120名使用大麻的PLWHA中，使用图表审查，尿液分析和访谈在基线时前瞻性地测量，并在一年内每季度测量一次，假设影响大麻使用和医疗认证的临床因素：社会经济变化，身心健康，物质使用，刑事司法参与，急性护理利用，艾滋病毒风险传播行为，以及吸食大麻的原因我们将单独使用临床数据，并结合模拟大麻需求（目标1）和吸食大麻的反应（目标2）来预测大麻和替代疗法使用的纵向模式。目标4。确定120例患者前瞻性样本中经认证的医用大麻使用、未经认证的治疗性使用和娱乐性使用的流行率是否普遍适用于整个HIV诊所。我们将调查300名PLWHA的随机样本，以（A）确定大麻使用模式是否具有代表性，在这个大型城市诊所位于艾滋病毒流行率高的地区，和（B）比较这个样本的特点，以前的横断面调查数据。在这个项目结束时，我们预计（1）这些数据将揭示这个人群中的不同模式;（2）我们将对医用大麻的使用有更深入的了解，（3）我们将能够预测哪些艾滋病患者子集可能受益或受到伤害。这些研究结果将传播给患者，提供者和社会，以促进公共卫生和知情的政策辩论。

DESCRIPTION (provided by applicant): State laws that allow medical marijuana use, including the Michigan Medical Marihuana Program (MMMP), create policy tension due to a paucity of scientific data about factors that influence: marijuana use patterns, abuse potential, decisions to seek/renew medical certification, impact of marijuana use on HIV risk behaviors, and health outcomes. This proposal will address these knowledge gaps by studying marijuana-using persons living with HIV/AIDS (PLWHAs) in Michigan's largest HIV primary care clinic (Detroit, 1700 patients) with a prospective mixed-method approach, as described in these Specific Aims: Aim 1. In 120 marijuana-using PLWHAs (certified medical users, non-certified therapeutic users, and recreational users; 40/group), we will (A) use behavioral economic simulations to evaluate marijuana demand sensitivity to experimental manipulation of unit price and income; and (B) determine whether marijuana price elasticity, cross-price elasticity with other drugs/therapies, and income elasticity differ across marijuana user groups. Aim 2. In a subset of 36 marijuana-using PLWHAs (certified medical, non-certified therapeutic, and recreational users; 12/group from Aim 1), conduct a laboratory-based, double blind, placebo-controlled, marijuana smoking evaluation (cumulative 0, 4, 8 and 12 puffs from 3.5% delta 9-THC cigarettes). We will (A) determine whether marijuana dose-effect profiles for symptom relief and abuse liability differ between marijuana-using groups; (B) compare smoked marijuana demand across groups; and (C) compare intensity of experimental ("gold standard") and naturalistic smoking effects. Aim 3. In the same 120 marijuana-using PLWHAs as Aim 1, use chart review, urinalysis, and interviews to measure prospectively at baseline, and at quarterly intervals for one year, clinical factors that are hypothesized to influence marijuana use and medical certification: socioeconomic changes, physical and mental health, substance use, criminal justice involvement, acute care utilization, HIV risk-transmission behaviors, and reasons for marijuana use. We will use clinical data alone and combined with simulated marijuana demand (Aim 1) and smoked marijuana responses (Aim 2) to predict longitudinal patterns of marijuana and alternative therapy use. Aim 4. Determine whether prevalence of certified medical marijuana use, non-certified therapeutic use, and recreational use in the 120-patient prospective sample generalizes to the entire HIV clinic. We will survey a random sample of 300 PLWHAs to (A) determine whether marijuana use patterns are representative within this large urban clinic located in the area with disproportionally high HIV prevalence, and (B) compare characteristics of this sample to prior cross-sectional survey data. At the conclusion of this project, we anticipate that (1) these data will reveal distinct patterns within this population; (2) we will have achieved a more sophisticated understanding of medical marijuana use, and (3) we will be able to predict which subsets of HIV patients are likely to benefit or be harmed. These findings will be disseminated to patients, providers and society to promote public health and informed policy debate.