Corrigendum: A critical reflection on using the Patient Engagement In Research Scale (PEIRS) to evaluate patient and family partners' engagement in dementia research
Bibliographic record
Abstract
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.031 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.013 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".