{"doi":"10.1111/add.16694","title":"Commentary on Pessar <i>et al</i> .: ‘Downscaling’ United States state cannabis policy to investigate environmental and social impacts on cannabis use","abstract":"Environmental and social contexts serve as key pathways by which U.S. state level cannabis policies influence individual level cannabis use behaviors. More granular research is needed on the differential impact of specific cannabis policies and interventions to best promote public health during a period of cannabis liberalization. Evidence of the negative health effects of cannabis legalization continues to accumulate. The research by Pessar and colleagues [1] joins a small, but growing body of research, which provides evidence that reducing legal restrictions on cannabis is associated with increases in not only adult, but also adolescent, cannabis use prevalence [2]. This is of key concern as long-term, frequent cannabis use among adolescents and young adults can affect brain development [3], potentially impacting cognitive function and the likelihood of developing psychiatric disorders [4]. Risk for cannabis use disorder (CUD) among those who use cannabis is especially high for adolescents [5, 6] and, of all age groups in the United States (US), young adults have the highest prevalence of CUD (16.6% of all young adults, 5.6 million people) [7]. Pessar and colleagues [1] offer a key scientific advance by treating state level cannabis policy as a continuous variable that reflects the degree of legal restrictions on cannabis use, cultivation, distribution, advertising and other characteristics [8]. This contrasts with the vast majority of cannabis policy impact studies that have used a simple, dichotomous classification of legal versus illegal. Pessar and colleagues' [1] approach, therefore, offers a more sensitive and precise measure of the variation in cannabis policies across the states and, consequently, a greater weight of evidence regarding the impact of liberalizing cannabis policy on the prevalence of cannabis use. The article raises several important additional questions: (1) how do increasingly liberal cannabis policies impact other outcomes besides past-month cannabis use, such as the frequency of use, prevalence of CUD and CUD treatment; (2) which specific cannabis policy changes are most impactful regarding problematic cannabis use, particularly among vulnerable populations such as adolescents and young adults; and (3) what are the mechanisms by which specific cannabis policies impact cannabis use behaviors? Answering these questions relies on understanding the environmental and social contexts that serve as key pathways by which state level cannabis policies influence cannabis use behaviors for individuals. For instance, legalization of commercial cannabis sales can increase not only access to cannabis but also environmental exposures to cannabis retailers and advertising, enhancing social acceptability of cannabis use and belief in its health benefits, while also reducing the perception of cannabis as harmful [9, 10]. These changes in attitudes can consequently influence behaviors such as cannabis use initiation, frequency of use and CUD treatment engagement and adherence. Analogous to Pessar and colleagues' [1] innovation in the precision of measurement of cannabis policy, recent advances in geospatial technologies and methods afford fine-scale measurement of individual level environmental exposures for modeling pathways from environmental and social contextual forces to cannabis use [11, 12]. Notably, the emphasis on environmental and social contexts aligns with theories in social ecology, health geography and exposomics as applied to drug addiction [13, 14], where individual substance use behaviors are understood to be rooted within nested layers of social, neighborhood and societal/policy contexts. Such theoretical frameworks and methodological approaches are key to extending the work of Pessar and colleagues to ‘downscale’ state level policy effects to the more granular neighborhood and family and peer social contexts through which policy impacts on individual behaviors typically occur. This approach facilit","journal":"Addiction","year":2024,"id":504761,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.955,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":921708,"name":"Gerald J. Stahler","orcid":"0000-0002-3049-2830","position":1,"is_corresponding":false},{"id":636903,"name":"Michael J. Mason","orcid":"0000-0002-3165-1450","position":2,"is_corresponding":false},{"id":921709,"name":"Jeremy Mennis","orcid":"0000-0001-6319-8622","position":0,"is_corresponding":true}],"reference_count":18,"raw_metadata":null,"created_at":"2026-07-19T02:10:39.578471Z","pmid":"39402865","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}