Clobes Thomas A, Gagnon Matin
California State University Channel Islands, One University Dr., Camarillo, CA 93012, USA.
PEC Innov. 2022 Sep 14;1:100085. doi: 10.1016/j.pecinn.2022.100085. eCollection 2022 Dec.
This study aims to identify pertinent demographic characteristics that influence attitudes toward medical cannabis.
Survey respondents were recruited through social media posts, partnering with community organizations, and snowball sampling. Attitudes were measured with a modified version of the medical component of the Recreational and Medical Cannabis Attitudes Scale (MMCAS). Data were analyzed using a one-way ANOVA or one-way Welch ANOVA to determine differences within demographic characteristics. A Tukey-Kramer, or Games-Howell, post-hoc analysis was conducted to determine specific groups within the independent variables that significantly impacted medical cannabis attitudes.
A total of 645 participants completed the survey. Significant variation in MMCAS was noted between groups based on race, political party affiliation, political view, religion, state legal status, and past/current cannabis use. There were no significant variations noted in MMCAS for apolitical factors.
Political, religious, and legal demographic factors impact attitudes toward medical cannabis.
The use of health education targeted at the groups of people who continue to harbor antiquated attitudes toward medical cannabis will help to improve patient access and, thus, patient outcomes. Cannabis advocates can innovatively apply health education efforts to groups of people who are aligned with the demographic factors identified in this current work.
本研究旨在确定影响对医用大麻态度的相关人口统计学特征。
通过社交媒体帖子、与社区组织合作以及滚雪球抽样招募调查受访者。使用《娱乐性和医用大麻态度量表》（MMCAS）的医学部分修改版来衡量态度。使用单因素方差分析或单因素韦尔奇方差分析来分析数据，以确定人口统计学特征中的差异。进行了Tukey-Kramer或Games-Howell事后分析，以确定在自变量中对医用大麻态度有显著影响的特定群体。
共有645名参与者完成了调查。基于种族、政党归属、政治观点、宗教、州法律地位以及过去/当前大麻使用情况，各群体之间在MMCAS上存在显著差异。非政治因素在MMCAS上未发现显著差异。
政治、宗教和法律人口统计学因素会影响对医用大麻的态度。
针对对医用大麻仍持有过时态度的人群开展健康教育，将有助于改善患者获得医用大麻的机会，从而改善患者治疗效果。大麻倡导者可以创新性地将健康教育工作应用于与本研究确定的人口统计学因素相符的人群。
