Corrigendum: A critical reflection on using the Patient Engagement In Research Scale (PEIRS) to evaluate patient and family partners' engagement in dementia research
Notice bibliographique
Résumé
Corrigendum: A Critical Reflection on Using the Patient Engagement in Research Scale (PEIRS) to Evaluate Patient and Family Partners’ Engagement in Dementia Research* Correspondence: joey.wong@ubc.caKeywords: same as original articleCorrigendum on: Wong J, Hung L, Bayabay C, Wong KLY, Berndt A, Mann J, Wong L, Jackson L and Gregorio M (2024) A critical reflection on using the Patient Engagement In Research Scale (PEIRS) to evaluate patient and family partners' engagement in dementia research. Front. Dement. 3:1422820. doi: 10.3389/frdem.2024.1422820 Error in Figure/TableIn the published article, there was an error in [Figure 1. The online PEIRS-22 survey with the addition of emojis and comment boxes.] as published. The figure is removed entirely.The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.Reminder: Figures, tables, and images will be published under a Creative Commons CC-BY licence and permission must be obtained for use of copyrighted material from other sources (including re-published/adapted/modified/partial figures and images from the internet). It is the responsibility of the authors to acquire the licenses, to follow any citation instructions requested by third-party rights holders, and cover any supplementary charges.Text CorrectionIn the published article, there was an error including the scale items. A correction has been made to Section 3.2, Subsection 3.2.1, Paragraph 1. This sentence previously stated:“For example, the question under the subtheme “Procedural Requirements”—“The project was worth the time I spent on it” and the subtheme “Contributions”—“My contributions were a good use of my time” sounds similar. Another set of identical questions is “I made an impact on the decisions in the project” under the subtheme “Benefits” and “I participated in making decisions about the project” under the subtheme “Procedural Requirements.””The corrected sentence appears below:“For example, the questions under the subthemes ‘Procedural Requirements’ and ‘Contributions’ regarding the use of time by our partners sound similar. Another set of identical questions are related to our partners’ decision making in the project under the subthemes ‘Benefits’ and ‘Procedural Requirements.’”Text CorrectionIn the published article, there was an error including the scale item.A correction has been made to Section 3.3, Sub-section 3.3.3, Paragraph 2. This sentence previously stated:“One example regarding MG's comments is the question under the subtheme “Convenience”—“Throughout the project, I had sufficient time to complete my tasks for the project.””The corrected sentence appears below:“One example regarding MG’s comments is the question under the subtheme ‘Convenience’ about the time allowed for completing his assigned tasks in the project.”The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.Text CorrectionIn the published article, there was an error including the scale item.A correction has been made to Section 3.3, Sub-section 3.3.3, Paragraph 2. This sentence previously stated:“For example, the question under “Procedural Requirements”—“In general, I had sufficient opportunities to contribute to the project.””The corrected sentence appears below:“One question LW mentioned regarding her contributions is under the subtheme ‘Procedural Requirements.’”The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,031 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,004 | 0,003 |
| Études des sciences et des technologies | 0,003 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,013 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
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 tête enseignante, 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 ».