Challenges in achieving uptake and journal endorsement of the ACcurate COnsensus Reporting Document (ACCORD) guideline
Bibliographic record
Abstract
Christopher C. Winchester,<sup>1</sup> Mark J. Rolfe,<sup>1</sup> William T. Gattrell,<sup>2</sup> Patricia Logullo,<sup>3</sup> Keith Goldman,<sup>4</sup> Amy Price,<sup>5</sup> Paul Blazey,<sup>6</sup> Esther J. van Zuuren,<sup>7</sup> Niall Harrison<sup>8</sup> <h4>Objective </h4> The ACcurate COnsensus Reporting Document (ACCORD) guideline supports the reporting of biomedical studies involving any consensus method.<sup>1</sup> We evaluated its uptake by bibliometric analysis and qualitative and quantitative assessment of implementation activities 1 year post publication. <h4>Design</h4> An implementation plan<sup>2</sup> was established by the ACCORD Steering Committee before guideline publication, including developing an explanation and elaboration (E&E) document, writing journal editorials, presenting at congresses, and encouraging journals and publishers to include ACCORD in author instructions. Guideline views and downloads (via <i>PLOS Medicine</i>,<sup>1</sup> the publishing journal) and citations (Dimensions, plus additional references from the Steering Committee’s reference libraries) were obtained for the period from January 23, 2024, to January 22, 2025. Likely journal and publisher beneficiaries of ACCORD were identified by a literature search to determine the 10 journals that published the most consensus studies (Web of Science for 2020-2023) and other publications at the discretion of the Steering Committee. Relevant journal and publisher stakeholders were contacted directly or indirectly (eg, via journal websites). Activities were evaluated against the implementation<i> </i>plan<sup>2</sup>; journal and publisher responses were described. <h4>Results</h4> In the 1 year following publication, the ACCORD guideline was viewed 13,752 times, downloaded (full-text PDF) 3790 times, and cited 105 times (5 citations [4.8%] were in articles by ACCORD authors, including the ACCORD E&E<sup>3</sup>). Sources of guideline citations included consensus studies (67.6% [71 of 105]), reviews (11.4% [12 of 105]), study protocols (8.6% [9 of 105]), other reporting standards and guidelines (6.7% [7 of 105]), and editorials (3.8% [4 of 105]). Of the journals contacted by ACCORD Steering Committee members (between August 24, 2023 [preprint publication], and January 22, 2025), <i>BMJ Open</i>, <i>British Journal of Dermatology</i>, and <i>Journal of Clinical Epidemiology </i>mandated the use of ACCORD for consensus studies, while the <i>British Journal of Sports Medicine</i>,<i> Internal Medicine Journal</i>, and <i>Pragmatic and Observational Research </i>encouraged its use. <i>PLOS </i>has confirmed its intention to include the guideline in their author instructions. Although a further 4 journals have expressed interest in ACCORD and 1 publisher has offered to raise awareness via a webinar, they are yet to commit to its inclusion in author instructions; 2 journals and publishers have not responded to inquiries. <h4>Conclusions </h4> One year after publication, the ACCORD guideline has been cited and used to inform the design and reporting of consensus-based research. However, journal and publisher adoption has been limited, which may affect long-term uptake. Given the resources invested in developing reporting guidelines and their potential to improve reporting, the role of biomedical journals and publishers in their adoption warrants wider discussion. <h4>References</h4> 1. Gattrell WT, Logullo P, van Zuuren EJ, et al. ACCORD (ACcurate COnsensus Reporting Document): a reporting guideline for consensus methods in biomedicine developed via a modified Delphi. <i>PLOS Med</i>. 2024;21:e1004326. doi:10.1371/journal.pmed.1004326 2. Gattrell WT, Hungin AP, Price A, et al. ACCORD guideline for reporting consensus-based methods in biomedical research and clinical practice: a study protocol. <i>Res Integr Peer Rev</i><span lang="de-DE">. 2022;7:3. doi:10.1186/s41073-022-00122-0</span> <span lang="de-DE">3. Logullo P, van Zuuren EJ, Winchester CC, et al. </span>ACcurate COnsensus Reporting Document (ACCORD) explanation and elaboration: guidance and examples to support reporting consensus methods. <i>PLOS Med</i>. 2024;21:e1004390. doi:10.1371/journal.pmed.1004390 <sup>1</sup>Oxford PharmaGenesis, Oxford, UK, chris.winchester@pharmagenesis.com; <sup>2</sup>Independent Medical Communications Professional, Oxfordshire, UK; <sup>3</sup>Bodleian Libraries, University of Oxford, Oxford, UK; <sup>4</sup>Medical Affairs + Health Impact, AbbVie, North Chicago, IL, US; <sup>5</sup>Dartmouth Institute for Health Policy & Clinical Practice (TDI), Geisel School of Medicine, Dartmouth College, Hanover, NH, US; <sup>6</sup>School of Kinesiology, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada; <sup>7</sup>Leiden University Medical Centre, Leiden, the Netherlands; <sup>8</sup>OPEN Health Communications, London, UK. <h4>Conflict of Interest Disclosures </h4> Christopher C. Winchester is an employee, director, and shareholder of Oxford PharmaGenesis; a director of Oxford Health Policy Forum CIC; a trustee of the Friends of the National Library of Medicine; and an associate fellow of Green Templeton College, University of Oxford. Mark J. Rolfe is an employee of Oxford PharmaGenesis. William T. Gattrell was an independent medical communications professional at the time of this study and is currently an employee of Bristol Myers Squibb. Keith Goldman is an employee of AbbVie. Niall Harrison is an employee of OPEN Health Communications. <h4>Funding/Support </h4> Medical writing, editorial, and project management support for this abstract were provided by Oxford PharmaGenesis. <h4>Acknowledgments</h4> Medical writing support was provided by Alison Chisholm, with editorial support from Jenny Thorp, and administrative support was provided by Mehraj Ahmed, Ryan Gamble, and Jessica Miller. <h4>Additional Information </h4> No authors were reimbursed for participating in the initiative.
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 | 0.039 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".