Heloísa Scattone , Luís Eduardo Gauer , Julia Valle Pezzini , Luís Fernando Tófoli
{"title":"巴西因医疗原因使用大麻的模式:一项探索性潜在分类分析研究","authors":"Heloísa Scattone , Luís Eduardo Gauer , Julia Valle Pezzini , Luís Fernando Tófoli","doi":"10.1016/j.drugpo.2025.104906","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>Although cannabis has a long history of therapeutic use, it has been subject to prohibition and stigma, including in Brazil. Recent social movements and legislative changes have enabled legal access to medical cannabis, yet bureaucratic and financial barriers restrict its availability. Understanding patterns of medical cannabis use – based on treated conditions, usage behavior, access routes, and product types – may help overcome these barriers and improve patient care. This exploratory study aims to identify distinct patient typologies based on these indicators among individuals legally accessing medical cannabis in Brazil.</div></div><div><h3>Methods</h3><div>We conducted an anonymous online survey among individuals using medically prescribed cannabis, including patients and caregivers. Data were collected between March and April 2023 via social media and online groups. Latent Class Analysis (LCA) was performed using indicators that captured key aspects of medical cannabis use: prior cannabis experience, symptom categories (mental health, neurological, and pain-related), evidence-based cannabis use, access pathways (associations, importation, pharmacy, court-authorized cultivation), administration routes, treatment costs, and duration of use. Multinomial logistic regression was used to examine associations between class membership and participant characteristics, including sociodemographic factors (age, gender, ethnicity, religion, education, income, region, and marital status) and survey informant (patient vs. relative or caregiver).</div></div><div><h3>Results</h3><div>A total of 1335 individuals participated. Among the solutions generated by the LCA, the five-class model was selected as optimal, reflecting specific clinical conditions, usage patterns, and access characteristics: (1) Mental Health Patient Class (36 %); (2) Pain Relief Patient Class (24.3 %); (3) Neurological Patient Class (17.8 %); (4) Prior-Use Multi-Symptom Patient Class (11.6 %); and (5) Recently Initiated Multi-Symptom Patient Class (10.3 %). Significant associations were found between class membership and gender, religion or spiritual affiliation, and monthly household income.</div></div><div><h3>Conclusions</h3><div>The study revealed heterogeneity among Brazilian medical cannabis patients, identifying distinct typologies with specific needs. Findings highlight how sociodemographic factors shape use patterns and inform ongoing reflections on access and care within a shifting regulatory context.</div></div>","PeriodicalId":48364,"journal":{"name":"International Journal of Drug Policy","volume":"143 ","pages":"Article 104906"},"PeriodicalIF":4.4000,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Patterns of cannabis use for medical reasons in Brazil: An exploratory latent class analysis study\",\"authors\":\"Heloísa Scattone , Luís Eduardo Gauer , Julia Valle Pezzini , Luís Fernando Tófoli\",\"doi\":\"10.1016/j.drugpo.2025.104906\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>Although cannabis has a long history of therapeutic use, it has been subject to prohibition and stigma, including in Brazil. Recent social movements and legislative changes have enabled legal access to medical cannabis, yet bureaucratic and financial barriers restrict its availability. Understanding patterns of medical cannabis use – based on treated conditions, usage behavior, access routes, and product types – may help overcome these barriers and improve patient care. This exploratory study aims to identify distinct patient typologies based on these indicators among individuals legally accessing medical cannabis in Brazil.</div></div><div><h3>Methods</h3><div>We conducted an anonymous online survey among individuals using medically prescribed cannabis, including patients and caregivers. Data were collected between March and April 2023 via social media and online groups. Latent Class Analysis (LCA) was performed using indicators that captured key aspects of medical cannabis use: prior cannabis experience, symptom categories (mental health, neurological, and pain-related), evidence-based cannabis use, access pathways (associations, importation, pharmacy, court-authorized cultivation), administration routes, treatment costs, and duration of use. Multinomial logistic regression was used to examine associations between class membership and participant characteristics, including sociodemographic factors (age, gender, ethnicity, religion, education, income, region, and marital status) and survey informant (patient vs. relative or caregiver).</div></div><div><h3>Results</h3><div>A total of 1335 individuals participated. Among the solutions generated by the LCA, the five-class model was selected as optimal, reflecting specific clinical conditions, usage patterns, and access characteristics: (1) Mental Health Patient Class (36 %); (2) Pain Relief Patient Class (24.3 %); (3) Neurological Patient Class (17.8 %); (4) Prior-Use Multi-Symptom Patient Class (11.6 %); and (5) Recently Initiated Multi-Symptom Patient Class (10.3 %). Significant associations were found between class membership and gender, religion or spiritual affiliation, and monthly household income.</div></div><div><h3>Conclusions</h3><div>The study revealed heterogeneity among Brazilian medical cannabis patients, identifying distinct typologies with specific needs. Findings highlight how sociodemographic factors shape use patterns and inform ongoing reflections on access and care within a shifting regulatory context.</div></div>\",\"PeriodicalId\":48364,\"journal\":{\"name\":\"International Journal of Drug Policy\",\"volume\":\"143 \",\"pages\":\"Article 104906\"},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2025-07-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Drug Policy\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0955395925002063\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"SUBSTANCE ABUSE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Drug Policy","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0955395925002063","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SUBSTANCE ABUSE","Score":null,"Total":0}
Patterns of cannabis use for medical reasons in Brazil: An exploratory latent class analysis study
Background
Although cannabis has a long history of therapeutic use, it has been subject to prohibition and stigma, including in Brazil. Recent social movements and legislative changes have enabled legal access to medical cannabis, yet bureaucratic and financial barriers restrict its availability. Understanding patterns of medical cannabis use – based on treated conditions, usage behavior, access routes, and product types – may help overcome these barriers and improve patient care. This exploratory study aims to identify distinct patient typologies based on these indicators among individuals legally accessing medical cannabis in Brazil.
Methods
We conducted an anonymous online survey among individuals using medically prescribed cannabis, including patients and caregivers. Data were collected between March and April 2023 via social media and online groups. Latent Class Analysis (LCA) was performed using indicators that captured key aspects of medical cannabis use: prior cannabis experience, symptom categories (mental health, neurological, and pain-related), evidence-based cannabis use, access pathways (associations, importation, pharmacy, court-authorized cultivation), administration routes, treatment costs, and duration of use. Multinomial logistic regression was used to examine associations between class membership and participant characteristics, including sociodemographic factors (age, gender, ethnicity, religion, education, income, region, and marital status) and survey informant (patient vs. relative or caregiver).
Results
A total of 1335 individuals participated. Among the solutions generated by the LCA, the five-class model was selected as optimal, reflecting specific clinical conditions, usage patterns, and access characteristics: (1) Mental Health Patient Class (36 %); (2) Pain Relief Patient Class (24.3 %); (3) Neurological Patient Class (17.8 %); (4) Prior-Use Multi-Symptom Patient Class (11.6 %); and (5) Recently Initiated Multi-Symptom Patient Class (10.3 %). Significant associations were found between class membership and gender, religion or spiritual affiliation, and monthly household income.
Conclusions
The study revealed heterogeneity among Brazilian medical cannabis patients, identifying distinct typologies with specific needs. Findings highlight how sociodemographic factors shape use patterns and inform ongoing reflections on access and care within a shifting regulatory context.
期刊介绍:
The International Journal of Drug Policy provides a forum for the dissemination of current research, reviews, debate, and critical analysis on drug use and drug policy in a global context. It seeks to publish material on the social, political, legal, and health contexts of psychoactive substance use, both licit and illicit. The journal is particularly concerned to explore the effects of drug policy and practice on drug-using behaviour and its health and social consequences. It is the policy of the journal to represent a wide range of material on drug-related matters from around the world.