The Relationship Between Cannabis Use and Schizophrenia As a Risk Factor or For Its Therapeutic Potential: A Systematic Review of Evidence
Bibliographic record
Abstract
The rising use of cannabis in the medical field has prompted the revival of the global debate about its psychotropic effects, especially when it comes to schizophrenia, a debilitating mental disorder that afflicts approximately 20 million people around the globe. Although Δ9-tetrahydrocannabinol (THC) is commonly considered a risk factor for psychosis, cannabidiol (CBD) has been studied for its potential therapeutic use. This review aims to clarify the central controversy surrounding the question of whether cannabis worsens schizophrenia symptoms by presenting a selective analysis of the available scientific literature. A systematic review was performed according to PRISMA 2020 guidelines. PubMed, PubMed Central, Cochrane Library, and Google Scholar were searched for peer-reviewed studies published between 2017 and 2025. A total of 112 records were obtained in the first phase of the research process, and after an intense screening process, eight high-quality studies meeting the inclusion criteria were included based on rigorous quality evaluation (A MeaSurement Tool to Assess systematic Review 2 or AMSTAR 2, Cochrane Risk of Bias Tool, Newcastle-Ottawa Scale, and scale for the quality assessment of narrative review articles (SANRA)). Data were extracted and systematically synthesized across three analytical domains: THC as the cause of schizophrenia, the influence of THC on the course of symptoms, and the potential therapeutic effects of CBD. The results provided strong evidence that the risk of developing schizophrenia was significantly higher with the use of high-THC-content cannabis, particularly when used by patients with family vulnerability and by those who used cannabis regularly during adolescence. THC was also demonstrated to exacerbate not only positive and negative psychotic symptoms but also cognitive disturbances in subjects with established schizophrenia. Conversely, there was evidence for the antipsychotic and neuroprotective properties of CBD and its therapeutic potential. However, clinical evidence for CBD was still limited; most studies were small, and few had long-term follow-up. This review emphasizes the importance of distinguishing the components of cannabis in psychiatric discussions. Although THC has potent schizophrenia liability, CBD is still a novel but promising candidate for treatment. Large controlled clinical trials need to be a priority for future research to determine the therapeutic and mechanistic limits of cannabis in mental health. These implications are very important for the clinical arena, public health policy, and research agenda on the topic of cannabis use and schizophrenia treatment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".