Association Between Alcohol Consumption and Psoriasis: Exploratory Analysis of Crowdsourced Web Search Data in Sweden
Bibliographic record
Abstract
BACKGROUND: The nature of the relationship between psoriasis and alcohol consumption has been the topic of discussion for many years. Some studies have found that a higher intake of alcohol may be associated with a more severe manifestation of the disease. At the same time, patients with psoriasis often demonstrate elevated levels of alcohol consumption. It has not yet been fully established whether alcohol abuse serves as a trigger for psoriasis or if patients with psoriasis are simultaneously more prone to alcohol abuse. OBJECTIVE: The objective of this study was to employ Google Trends as a tool for crowdsourcing data on a national level to explore the relationship between psoriasis and the consumption of alcohol in Sweden. METHODS: This study examines crowdsourced web search data related to psoriasis and other skin disease-related search terms (such as utslag [rash]) as well as search interest in different types of alcohol. The analysis covers a 5-year period from 2018 to 2023 in Sweden, focusing on search behavior and correlations across this period. RESULTS: The search behavior regarding psoriasis and alcohol-related search terms showed seasonal variations throughout the year. The relative search volume for psoriasis peaked in February, while alcohol-related searches, particularly Systembolaget and vodka, peaked in December and June. Our statistical analysis revealed relationships between the search interest regarding psoriasis and terms related to alcohol consumption, with disparities between different types of alcohol. The term "psoriasis" was negatively correlated with "Systembolaget" (r=-0.210), "vitt vin" (r=-0.224), and "vodka" (r=-0.220) (all P<.001), while the term "utslag" showed positive correlations with these same alcohol-related terms (r=0.278-0.347; P<.001). CONCLUSIONS: Crowdsourced data can offer valuable insights into population-level behavior. The observed negative correlations between psoriasis and alcohol-related searches suggest complex interactions, possibly reflecting reduced disease awareness or care during periods of higher alcohol consumption. The direction and strength of the correlations with psoriasis were not consistent across the different types of alcohol investigated in this study, which poses the question whether the relationship might be influenced by the type of beverage consumed. Further research is warranted to explore underlying mechanisms and validate these findings in clinical populations.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".