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Enregistrement W3144546964 · doi:10.2196/24065

A Smartphone App Designed to Empower Patients to Contribute Toward Safer Surgical Care: Qualitative Evaluation of Diverse Public and Patient Perceptions Using Focus Groups

2021· article· en· W3144546964 sur OpenAlexvenueno aff
Stephanie Russ, Nick Sevdalis, Josephine Ocloo

Notice bibliographique

RevueJMIR mhealth and uhealth · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueSurgical Simulation and Training
Établissements canadiensnon disponible
Organismes subventionnairesKing's Health PartnersKing's College LondonGuy's and St Thomas' CharityNational Institute for Health and Care ResearchMaudsley CharityKing's College Hospital NHS Foundation TrustDepartment of Health and Social CareNational Institute for Health Research Applied Research Collaboration South LondonSouth London and Maudsley NHS Foundation Trust
Mots-clésFocus groupThematic analysisTransgenderMedicineEthnic groupUsabilityNursingSAFERQualitative researchPsychologyMedical education

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: MySurgery is a smartphone app designed to empower patients and their caregivers to contribute toward safer surgical care by following practical advice to help reduce susceptibility to errors and complications. OBJECTIVE: The aim of this study is to evaluate service users' perceptions of MySurgery, including its perceived acceptability, the potential barriers and facilitators to accessing and using its content, and ideas about how to facilitate its effective implementation. The secondary aim is to analyze how the intended use of the app might differ for diverse patients, including seldom-heard groups. METHODS: We implemented a diversity approach to recruit participants from a range of backgrounds with previous experience of surgery. We aimed to achieve representation from seldom-heard groups, including those from a Black, Asian, and minority ethnic (BAME) background; those with a disability; and those from the lesbian, gay, bisexual, transgender, queer (LGBT+) community. A total of 3 focus groups were conducted across a 2-month period, during which a semistructured protocol was followed to elicit a rich discussion around the app. The focus groups were audio recorded, and thematic analysis was carried out. RESULTS: In total, 22 individuals participated in the focus groups. A total of 50% (n=11) of the participants were from a BAME background, 59% (n=13) had a disability, and 36% (n=8) were from the LGBT+ community. There was a strong degree of support for the MySurgery app. The majority of participants agreed that it was acceptable and appropriate in terms of content and usability, and that it would help to educate patients about how to become involved in improving safety. The checklist-like format was popular. There was rich discussion around the accessibility and inclusivity of MySurgery. Specific user groups were identified who might face barriers in accessing the app or acting on its advice, such as those with visual impairments or learning difficulties and those who preferred to take a more passive role (eg, some individuals because of their cultural background or personality type). The app could be improved by signposting further specialty-specific information and incorporating a calendar and notes section. With regard to implementation, it was agreed that use of the app should be signposted before the preoperative appointment and that training and education should be provided for clinicians to increase awareness and buy-in. Communication about the app should clarify its scientific basis in plain English and should stress that its use is optional. CONCLUSIONS: MySurgery was endorsed as a powerful tool for enhancing patient empowerment and facilitating the direct involvement of patients and their caregivers in maintaining patient safety. The diversity approach allowed for a better understanding of the needs of different population groups and highlighted opportunities for increasing accessibility and involvement in the app.

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)0,001
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: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,757
Score d'incertitude au seuil0,566

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
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 Opus0,140
Tête enseignante GPT0,448
Écart entre enseignants0,308 · 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

Citations28
Publié2021
Routes d'admission1
Résumé présentoui

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