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Enregistrement W2461733401 · doi:10.1186/s40900-016-0039-6

Including patients in core outcome set development: issues to consider based on three workshops with around 100 international delegates

2016· editorial· en· W2461733401 sur OpenAlexaboutno aff
Bridget Young, Heather Bagley

Notice bibliographique

RevueResearch Involvement and Engagement · 2016
Typeeditorial
Langueen
DomaineSocial Sciences
ThématiqueDelphi Technique in Research
Établissements canadiensnon disponible
Organismes subventionnairesMedical Research Council
Mots-clésSet (abstract data type)Outcome (game theory)Process (computing)StakeholderCore (optical fiber)Clinical trialMedicinePsychologyMedical educationComputer sciencePublic relationsPolitical science

Résumé

récupéré en direct d'OpenAlex

Plain English summary This commentary article describes three interactive workshops that explored how patients can contribute to decisions about what outcomes are measured in clinical trials across the world. Outcomes like quality of life, side-effects and pain are used in trials to measure whether a treatment is effective. Here, we outline how research groups are increasingly coming together to develop ‘core outcomes sets’ for particular conditions. Core outcome sets are lists of agreed outcomes. Their use will help in identifying which treatments are effective by enabling people to compare the findings of different clinical trials in the same condition. Currently, it is often very difficult to make these comparisons because different studies often measure different outcomes. Delegates attending the workshops included patients, clinicians and researchers. They discussed ways of making core outcome set development more meaningful and accessible for patients, and ensuring that they have a genuine say in the development process. This article summarises these discussions and concludes by identifying three distinctive challenges in securing patient input to core outcome set development: the process and objectives can seem far removed from the immediate concerns of patients, difficulties can arise in securing patient input on an international scale, and difficulties can also arise in bringing multiple stakeholder groups together to achieve consensus. While patient participation, involvement and engagement in core outcome set development can draw on lessons from other research areas, these distinctive challenges point to the need for distinctive solutions to enable meaningful patient input to core outcome set development. Abstract Background This article describes three workshops that explored how patients can contribute to decisions about what outcomes are measured in clinical trials. People need evidence about what treatments are best for particular health conditions. The strongest evidence comes from systematic reviews comparing outcomes across different studies of treatments for a particular condition. However, it is often difficult to do these comparisons because the different studies—even though they have all investigated the same condition—often measure different outcomes. To tackle this problem, research teams are increasingly coming together to develop core outcome sets (COS) for particular conditions or treatments. The goal is that across the world, all the research teams working on the same condition or treatment will then use the COS in their research. Main body We report on three interactive workshops that explored how patients and the public can contribute to decision making about what outcomes should be included in a COS. About 100 international delegates, including researchers, clinicians and patients, attended the workshops. The workshops were held in the United Kingdom, Italy and Canada as part of the COMET (Core Outcome Measures in Effectiveness Trials) Initiative annual meetings. Patients who had some experience as research advisors, collaborators, partners or co-ordinators facilitated the workshops together with a researcher. Notes made during each workshop informed the preparation of this article. Workshop discussion focussed on ways of making core outcome set development more meaningful and accessible for patients. Delegates wanted patients to have a genuine say, alongside other stakeholders, in what outcomes are included in COS. Delegates felt that key to ensuring this is recognising that patient participation in COS development alone is not enough, and that patients will also need to be involved in the design of COS development studies. Conclusion We conclude by pointing to some distinctive challenges in including patients in COS development. While the COS development community can draw on the lessons learnt from other research areas about patient participation, involvement and engagement, the distinctive challenges that arise in COS development point to the need for some distinctive solutions too.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,146
score de la tête « metaresearch » (Gemma)0,190
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: Méthodes · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: Qualitatif
GenreSignal candidat: Éditorial · Signal consensuel: aucune
Score de désaccord entre enseignants0,854
Score d'incertitude au seuil0,770

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,1460,190
Méta-épidémiologie (sens strict)0,0020,002
Méta-épidémiologie (sens large)0,0020,003
Bibliométrie0,0010,001
Études des sciences et des technologies0,0160,016
Communication savante0,0160,017
Science ouverte0,0080,035
Intégrité de la recherche0,0160,045
Charge utile insuffisante (le modèle a refusé de juger)0,0080,003

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 Opus0,499
Tête enseignante GPT0,549
Écart entre enseignants0,050 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeQualitatif
DomaineMéthodes
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations128
Publié2016
Routes d'admission1
Résumé présentoui

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