RecoverEsupport: A Pilot Randomised Controlled Trial of a Digital Health Intervention for Recovery After Breast Cancer Surgery (Feasibility and Acceptability outcomes). (Preprint)
Notice bibliographique
Résumé
Background: Optimizing recovery following breast cancer surgery is critical for restoring usual function, minimizing complications, and enabling timely initiation of adjuvant therapies. Enhanced Recovery After Surgery protocols are internationally endorsed recommendations and include patient-led behaviors such as early mobilization, early oral intake of fluids and food, postoperative rehabilitation exercises, and multimodal pain management. However, adherence to these behaviors is often suboptimal, and strategies to support patients are limited. Digital health interventions (DHIs) may offer scalable solutions. Objective: The aim of the study is to assess the acceptability of the RecoverEsupport Breast DHI, designed to increase adherence to patient-led Enhanced Recovery After Surgery recommendations across the perioperative period for breast cancer surgery, and to assess the feasibility of conducting a randomized controlled trial to evaluate it. Methods: In this single-site, 2-arm randomized pilot trial, conducted at a major cancer hospital in New South Wales, Australia, between July 2024 and October 2025, participants were consecutively recruited from the surgical list at the study site, supplemented by referrals from surgeons' private rooms, and included individuals having a mastectomy with or without implant-based reconstruction. Participants were allocated to usual care (control) or usual care plus the RecoverEsupport DHI (intervention). Trial feasibility outcomes included participant recruitment, retention, data completeness, and postoperative safety (adverse events). Intervention acceptability was assessed via the System Usability Scale, participant engagement rates, and willingness to recommend the intervention to others undergoing surgery. Descriptive analyses were conducted, and outcomes were compared to prespecified targets and progression criteria. Results: In total, 23 participants were recruited (control: n=12, intervention: n=11), which was below the target of 70, while participant retention and data completeness were 100% (23/23), both exceeding the targets. No grade 3+ adverse events occurred; minor grade 2 events occurred in both groups. Acceptability outcomes exceeded targets: usability was high (mean System Usability Scale score 83.2, SD 17.7; target >68), 100% (11/11; target >75%) of participants logged in to the DHI at least once, and 88% (10/11; target >75%) would recommend the program to others undergoing surgery. According to prespecified progression criteria, 3 of 4 feasibility targets were met, indicating that a revised recruitment strategy would be required before proceeding. The restrictive eligibility criteria may have contributed to the lower than expected recruitment rate. All 3 acceptability targets were met. Conclusions: The RecoverEsupport intervention was acceptable and safe and had high participant engagement. The trial processes were feasible; however, recruitment barriers, including restrictive eligibility criteria, highlight the need for more robust and integrated recruitment strategies to enable progression to a fully powered randomized controlled trial.
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 | 0,006 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,001 | 0,003 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,025 | 0,002 |
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 ».