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Enregistrement W7162009744 · doi:10.82308/29740

Development of a patient-reported outcome measure of recovery after abdominal surgery: A conceptual framework

2019· dissertation· en· W7162009744 sur OpenAlexaboutno aff
Roshni Alam

Notice bibliographique

Revuenon disponible
Typedissertation
Langueen
DomaineMedicine
ThématiqueEnhanced Recovery After Surgery
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésConceptual frameworkPromContext (archaeology)Patient-reported outcomeDelphi methodConceptual modelInternational Classification of Functioning, Disability and HealthQualitative researchProcess (computing)The Conceptual Framework

Résumé

récupéré en direct d'OpenAlex

Background: The use of patient-reported outcome measures (PROMs) are central for delivering high-quality patient-centered care to postoperative patients. However, the evidence underpinning the measurement properties of PROMs currently in use to measure recovery after abdominal surgery is weak. To bridge this knowledge gap, we initiated a research program to develop a conceptually relevant and psychometrically sound recovery-specific PROM. In compliance with best-practice recommendations for PROM development, this thesis project aimed to develop a conceptual framework representing the health domains relevant to the process of recovery after abdominal surgery. Methods:This study was conducted in two parts: Part 1 (Manuscript 1): A hypothesized conceptual framework of recovery was developed based on literature review and expert opinion. Firstly, a systematic review was undertaken to identify PROMs currently used in the context of recovery after abdominal surgery. All items contained in the PROMs were categorized into health domains covered by the International Classification of Functioning, Disability and Health (ICF). To acquire expert input, 35 perioperative care experts from major surgical societies in North America and Europe were invited to participate in a 2-round Delphi study in which they rated their agreement with each domain. Domains deemed as relevant (>75% agreement) were organized into a diagram comprising a hypothesized conceptual framework of recovery after abdominal surgery. Part 2 (Manuscript 2): A final conceptual framework of recovery was developed based on patient input. Patients from 4 different countries (Canada, Italy, Brazil and Japan) participated in qualitative interviews focusing on their lived experiences of recovery after abdominal surgery. Interviews were guided by the previously developed hypothesized framework. Interviews were analyzed according to a modified grounded theory approach and transcripts were coded according to the ICF. Codes for which thematic saturation was reached were classified into domains of health that are relevant to the process of recovery after abdominal surgery. These domains were organized into a structured diagram. Results:Part 1 (Manuscript 1): The systematic review identified 19 PROMs covering 66 ICF domains. 23 experts (66%) participated in the Delphi process. After Round 2, experts agreed that 22 ICF health domains are potentially relevant to the process of recovery after abdominal surgery. Part 2 (Manuscript 2): 30 patients with diverse demographics and surgical characteristics were interviewed (50% male, age 57±18 years; 66% major or major extended surgery). 39 unique domains of recovery emerged from the interviews, 17 falling under the ICF category of "Body Functions" and 22 under "Activities and Participation". These domains constitute the final conceptual framework of recovery after abdominal surgery.Conclusion:The research reported in this thesis provides comprehensive insight into the health domains that are relevant to the process of recovery after abdominal surgery. This conceptual framework will support content validity and provide the pivotal basis for the development of a novel PROM to inform patient-centered research and quality improvement initiatives in abdominal surgery

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)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
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 enseignants0,471
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,028
Tête enseignante GPT0,282
Écart entre enseignants0,254 · 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.

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

Citations0
Publié2019
Routes d'admission1
Résumé présentoui

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