Factors Influencing the Use of Online Symptom Checkers in the United Kingdom: Cross-Sectional Study
Notice bibliographique
Résumé
Background: The National Health Service (NHS) faces increasing strain. Concurrently, demand for health information, consumer empowerment, and health awareness continues to grow. These trends, coupled with the ubiquity of smartphones and internet access, are positioning online symptom checkers (OSCs) as promising tools for preliminary diagnosis and triage. While there is increasing data on the demographics, motivations, and perspectives of current and potential users of OSCs globally, no study has yet quantified or ranked the various factors associated with the use of OSCs in the United Kingdom. Objective: This study aimed to assess key trends and user perceptions on the usability and effectiveness of OSC in the United Kingdom. We also sought to identify concerns related to the privacy, security, and accuracy of OSCs and to quantify the weight of these various factors on the use of OSCs. Methods: A cross-sectional survey of UK adults was conducted using an electronic questionnaire. A convenience sample was recruited between February and March 2024 through web-based platforms and personal networks. The survey included questions on awareness, use, perceptions, and concerns regarding OSCs, as well as respondents' demographics. Responses were pseudo-anonymized and analyzed using univariable and multivariable logistic regression models to assess relationships between demographic factors; perceived usability, reliability, and risks; and OSC use. Results: The survey collected responses from 634 participants. The majority (543/634, 85.7%) had used OSCs, primarily the NHS 111 service (498/634, 78.6%). Younger age (<46 years old), being female (adjusted odds ratio [aOR] 1.79, 95% CI 1.05-3.06), and having children (aOR 3.19, 95% CI 1.56-6.51) were associated with higher odds of using OSCs. Key motivations for using OSCs included understanding symptoms (501/634, 79.0%) and determining the need for medical care (491/634, 77.4%). Key concerns negatively impacting use related to privacy (aOR 0.58, 95% CI 0.35-0.97) and fear of replacing traditional, face-to-face consultations (aOR 0.47, 95% CI 0.26-0.87). The most important factor found to affect the decision to use OSCs was the perceived ease of use (aOR 8.17, 95% CI 4.25-15.71), followed by the perceived helpfulness in decision-making (aOR 2.96, 95% CI 1.62-5.42), and respondents' trust in their diagnostic accuracy (aOR 2.24, 95% CI 1.32-3.79). Conclusions: OSCs are widely used in the United Kingdom, particularly the NHS 111 service, driven primarily by ease of use and perceived helpfulness in decision support. However, privacy and security concerns, as well as fears of OSCs replacing traditional consultations, pose significant barriers. Addressing these concerns is crucial for enhancing user trust and maximizing the benefits of OSCs in supporting self-care and improving health care efficiency.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».