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Record W4389086750 · doi:10.2196/43850

Public Interest in Psilocybin and Psychedelic Therapy in the Context of the COVID-19 Pandemic: Google Trends Analysis

2023· article· en· W4389086750 on OpenAlexvenueno aff
George Danias, Jacob M. Appel

Bibliographic record

VenueJMIR Formative Research · 2023
Typearticle
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPsilocybinContext (archaeology)PsychiatryAnxietyMedicinePandemicPopulationCannabisDepression (economics)HallucinogenPsychologyCoronavirus disease 2019 (COVID-19)Internal medicineEnvironmental healthDiseaseGeography

Abstract

fetched live from OpenAlex

BACKGROUND: Psychedelic substances have demonstrated promise in the treatment of depression, anxiety, and substance use disorders. Significant media coverage has been dedicated to psychedelic medicine, but it is unclear whether the public associates psilocybin with its potential therapeutic benefits. The COVID-19 pandemic led to an increase in depression, anxiety, and substance abuse in the general population. OBJECTIVE: This study attempts to link increases in interest in these disorders with increases in interest in psilocybin using Google Trends. METHODS: Weekly interest-over-time Google Trends data for 4 years, from the week of March 11, 2018, to the week of March 6, 2022, were obtained for the following terms: "psilocybin," "psychedelic therapy," "cannabis," "cocaine," "antidepressant," "depression," "anxiety," and "addiction." Important psilocybin-related news and the declaration of the pandemic were noted. Trends data for each of the queried terms were plotted, and multiple regression analysis was performed to determine the slope of the prepandemic and postpandemic data with 95% CIs. Nonparametric Tau-U analysis was performed correcting for baseline trends. Results from this test were used to make inferences about the pre- and postpandemic trends and inferences about the change in overall level of searches between the 2 groups. RESULTS: Tau values for prepandemic data were significant for stable trends, all ranging -0.4 to 0.4. Tau values for postpandemic data showed positive trends for "psilocybin," "psychedelic therapy," and "antidepressant." All other trends remained stable in the range of -0.4 to 0.4. When comparing Tau values for pre- and postpandemic data, overall increases in relative search volume (RSV) were seen for "psilocybin," "psychedelic therapy," and "anxiety," and overall decreases in RSV were seen for "depression," "addiction," and "cocaine." Overall RSVs for "cannabis" and "antidepressant" remained stable as Tau values ranged between -0.4 and 0.4. In the immediate aftermath of the declaration of the pandemic, drop-offs in interest were seen for all terms except for "anxiety" and "cannabis." After the initial shock of a global pandemic, "psilocybin" and "psychedelic therapy" groups demonstrated increases in interest trends and overall RSV. CONCLUSIONS: These data suggest that overall interest in "psilocybin" and "psychedelic therapy" increased at higher rates and to higher levels after than before the declaration of the pandemic. This is consistent with our hypothesis that interest increased for these treatments after the pandemic as incidence of depression, anxiety, and addiction increased. However, there may be other drivers of interest for these topics, since interest in antidepressants-the typical pharmacologic treatments for depression and anxiety-followed the expected pattern of drop-off and accelerated interest back to prepandemic levels. Interest in "psilocybin" and "psychedelic therapy" may have also been partially driven by popular culture hype and novelty, explaining why interest increased at a higher rate post pandemic and continued to grow, surpassing prior interest.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.237
Threshold uncertainty score0.723

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.008
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.543
GPT teacher head0.549
Teacher spread0.006 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2023
Admission routes1
Has abstractyes

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