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Enregistrement 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 sur OpenAlexvenueno aff
George Danias, Jacob M. Appel

Notice bibliographique

RevueJMIR Formative Research · 2023
Typearticle
Langueen
DomainePsychology
ThématiquePsychedelics and Drug Studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPsilocybinContext (archaeology)PsychiatryAnxietyMedicinePandemicPopulationCannabisDepression (economics)HallucinogenPsychologyCoronavirus disease 2019 (COVID-19)Internal medicineEnvironmental healthDiseaseGeography

Résumé

récupéré en direct d'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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,005
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,237
Score d'incertitude au seuil0,723

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0050,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0020,008
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,543
Tête enseignante GPT0,549
Écart entre enseignants0,006 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations13
Publié2023
Routes d'admission1
Résumé présentoui

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