Associations Between Online Search Trends and Outpatient Visits for Common Medical Symptoms in the United States from 2004 to 2019: Time Series Ecological Study
Notice bibliographique
Résumé
Background: The seemingly endless amount of information available on the internet at the touch of a few buttons has increasingly served as a resource for individuals to find health information over the last 20+ years. Previous research in the field of infodemiology suggests that this change in use of the internet by the public to find health information has an impact on their interaction with the health care system. However, to this date, no study has directly juxtaposed the growth of internet searching and the number of visits to ambulatory care centers for the same concerns over the last two decades of internet growth. Objective: This study aimed to explore the relationship between online searches for three common primary care concerns and ambulatory visits for those same concerns during 2004-2019. Methods: The National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey data were searched between the years 2004 and 2019 in order to estimate the number of annual ambulatory care visits for cough, sore throat, and abdominal pain. Google Trends data were explored to analyze the number of people searching for information about the same complaints over the same years. Cross correlation, time series regression, and Granger causality analysis were performed to analyze patterns and causality. Results: Google Trends data showed that the number of searches for the common primary care symptoms "cough," "sore throat," and "stomach pain" in the United States grew by 208%, 290%, and 490%, respectively, between 2004 and 2019. However, over the same time, United States population-adjusted outpatient visits for cough and sore throat decreased by 41.5% and 40%, respectively, and stomach pain visits remained unchanged. According to conservative estimation, analysis concluded that an increase in internet searches for cough can predict a decline in ambulatory visits for that symptom. Conclusions: This supports that, on a population level, exploring online health information about some common, acute symptoms did not lead to increase in care seeking, but instead, suggests that a substantial portion of the population found the information to be reassuring or informative enough to not feel the need to seek care from a primary health care provider. With the rapid evolution and availability of more detailed and personalized information from various large language models, it is likely that internet search habits of users will continue to grow, and with it, continue to transform interactions with the health care system.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».