WikiBuild: A New Application to Support Patient and Health Care Professional Involvement in the Development of Patient Support Tools
Notice bibliographique
Résumé
Active patient and public involvement as partners in their own health care and in the development of health services is key to achieving a health care system that is responsive to patients' needs and values. It promotes better use of the health care system, and improves health outcomes, quality of life and patient satisfaction. By involving patients and health care professionals as partners in the creation and updating of patient health support tools, wikis--highly accessible, interactive vehicles of communication--have the potential to empower users to implement these support tools in daily life. Acknowledging the potential of wikis, and recognizing that they capitalize on the free and open access to information, scientists, opinion leaders and patient advocates have suggested that wikis could help decision-making constituencies improve the delivery of health care. They might also decrease its cost and improve access to knowledge within developing countries. However, little is known about the efficacy of wikis in helping to attain these goals. There is also a need to know more about the intention of patients and health care workers to use wikis, in what circumstances and what factors will influence their use of wikis. In this issue of the Journal of Medical Internet Research, Gupta et al describe how they developed and tested a new wiki-inspired application to improve asthma care. The researchers involved patients with asthma, primary care physicians, pulmonologists and certified asthma educators in the construction of an asthma action plan. Their paper--entitled "WikiBuild: a new online collaboration process for multistakeholder tool development and consensus building"--is the first description of a wiki-inspired technology built to involve patients and health care professionals in the development of a patient support tool. This innovative study has made important contributions toward how wikis could be generalized to involve multiple stakeholders in the development of other knowledge translation tools such as clinical practice guidelines or decision aids. More specifically, Gupta et al have uncovered potential action mechanisms toward increasing usage of these tools by patients and health care professionals. These are decreasing hierarchical influences, increasing usability and adapting a tool to local context. More research is now needed to determine if the use of the resulting wiki-developed plan will actually be higher than a plan developed using other methods. Furthermore, there is also a need to assess the intention of participants to continue using wiki-based processes on an ongoing basis. It is in this dynamic and continuous retroaction loop that the support tool users--both patients and health care professionals--can adapt and improve the product after its real-life shortcomings are revealed and as new evidence becomes available. As such, a wiki would be more than a simple patient support development tool, but could also become a dynamic and interactive repository and delivery tool that would facilitate ongoing and sustainable patient and professional engagement.
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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 | 0,004 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,005 |
| Science ouverte | 0,002 | 0,007 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,004 |
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 ».