Quality of Web-Based Sickle Cell Disease Resources for Health Care Transition: Website Content Analysis
Notice bibliographique
Résumé
Background: Adolescents and young adults with sickle cell disease (SCD) transitioning from pediatric to adult health care face a high-risk period associated with increased use of acute health care services and mortality. Although 59% of American citizens report using the internet for health care information, the quality of web-based, patient-facing resources regarding transition in SCD care has not been evaluated. Objective: This study aimed to evaluate the quality and readability of web-based health information on SCD, especially as it pertains to the transition to adulthood for inidividuals with SCD. The study also compared the readability and content scores of websites identified in 2018 to those from 2021 to assess any change in quality over time. Methods: Keywords representing phrases adolescents may use while searching for information on the internet regarding transition in SCD care, including "hydroxyurea" and "SCD transition," were identified. A web-based search using the keywords was conducted in July 2021 using Google, Yahoo, and Bing. The top 20 links from each search were collected. Duplicate websites, academic journals, and websites not related to SCD health care transition were excluded. Websites were categorized based on the source: health department, hospital or private clinician, professional society, and other websites. Websites were assessed using Health On the Net Foundation code of conduct (HONcode), Flesch Reading Ease (FRE), Flesch-Kincaid Grade Level (FGL), Ensuring Quality Information for Patients (EQIP), and a novel SCD content checklist (SCDCC). EQIP and SCDCC scores range from 0- to 100. Each website was reviewed by 2 research assistants and assessed for interrater reliability. Descriptive statistics were calculated. Results: Of the 900 websites collected, 67 (7.4%) met the inclusion criteria: 13 health department, 7 hospital or private clinician, 33 professional society, and 14 other websites. A total of 15 (22%) out of 67 websites had HONcode certification. Websites with HONcode certification had higher FRE and EQIP scores and lower FGL scores than those without HONcode certification, reflecting greater readability. Websites without HONcode certification had higher SCDCC scores, reflecting greater clinical content. Only 7 (10%) websites met the National Institutes of Health recommendation of a seventh-grade or lower reading level. Based on EQIP scores, 6 (9%) websites were of high quality. The mean SCDCC score was 20.60 (SD 22.14) out of 100. The interrater reliability for EQIP and SCDCC ratings was good (intraclass correlation: 0.718 and 0.897, respectively). No source of website scored significantly higher mean EQIP, FRE, FGL, or SCDCC scores than the others (all P<.05). Conclusions: Although seeking health care information on the web is very common, the overall quality of information about transition in SCD care on the internet is poor. Changes to current web-based health care information regarding SCD care transitions would benefit transitioning youth by providing expectations, knowledge, skills, and tools to increase self-efficacy.
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 | 0,010 | 0,049 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,010 | 0,009 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 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 ».