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Enregistrement W2793475491 · doi:10.1093/jcag/gwy008.149

A148 SMARTPHONE APPS FOR IBD DISEASE MANAGEMENT: A QUANTITATIVE EVALUATION

2018· article· en· W2793475491 sur OpenAlex

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

affAu moins un auteur déclare une institution canadienne dans l'instantané OpenAlex épinglé.

Notice bibliographique

RevueJournal of the Canadian Association of Gastroenterology · 2018
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueBiological Research and Disease Studies
Établissements canadiensRegina Qu'Appelle Health RegionUniversity of Saskatchewan
Organismes subventionnairesnon disponible
Mots-clésLikert scaleInflammatory bowel diseaseMedicineSmartphone appApp storeRating scaleMobile appsSmartphone applicationAndroid (operating system)DiseaseComputer scienceWorld Wide WebMultimediaPsychologyInternal medicine

Résumé

récupéré en direct d'OpenAlex

Smartphone Apps for inflammatory bowel disease (IBD) are becoming increasingly popular. However, there is paucity of data on the function and quality of these applications. The lack of systemic investigation on IBD Apps prevents further comparative analysis with clinically validated scoring systems. This makes it difficult for patients to choose and for physicians to recommend the most appropriate App to help manage their disease. To identify and quantitatively evaluate smartphone Apps for patient management of IBD. Systematic search of smartphone Apps were carried out in Apple App Store for iOS operating system and Google Play Store for Android operating system using the following keywords: “IBD”, “inflammatory bowel disease”, “colitis”, “ulcerative colitis” and “crohn’s”. Title inclusion (relating to management of Inflammatory Bowel Disease and in English) and exclusion criteria (only offers educational information or Conference App) were applied to all results. Apps that passed title screening were review independently by two reviewers using the validated Mobile Application Rating Scale. An App’s quality was assessed based on engagement, functionality, aesthetics and information quality. Each item in MARS scoring tool was rated on a 5 point Likert scale. Each subcategory was averaged, then added to give an overall 5 point rating for the App. The two raters’ data were presented as aggregated means and standard deviations. Spearman’s bivariate analyses were used to assess correlation between overall rating and other App characteristics. App features were represented in a table format. Fifteen smartphone Apps for IBD management were included in the analysis. The top 3 Apps were IBD Health Storylines (4.9 ± 0.53), GutCheckTM (4.78 ± 0.18), and MyGiHealth (4.63 ± 0). The information quality score of an App was most strongly correlated with the overall score (Spearman’s rho=0.87, p=0.012), while functionality score, engagement score and aesthetics scores were less correlated with the overall score (Spearman’s rho=0.61, 0.59 and 0.53 respectively). Number of features offered by an App was strongly correlated with the overall score (Spearman’s rho=0.74, p=0.012) while cost and user ratings were poorly correlated with the overall score (Spearman’s rho=0.06, 0.04 respectively). This study provides a list of IBD disease management smartphone Apps with their associated features, ranked by order of quality by a validated scoring system. Information quality and features offered by an App appear to be most closely related to the overall quality of an App. This will allow physicians to recommend and patients to choose high quality Apps to support IBD management. Future studies will explore correlation between clinical validated scoring systems and information collected by high quality IBD management Apps identified in this study. None

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.

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)0,001
score de la tête « metaresearch » (Gemma)0,002
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 enseignants0,147
Score d'incertitude au seuil0,963

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
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 Opus0,021
Tête enseignante GPT0,301
Écart entre enseignants0,279 · 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