Author Responses to Editorial Guidance on Reporting of Sex, Gender, Race and Ethnicity Data
Notice bibliographique
Résumé
Mabel Chew,<sup>1</sup> Taissa Vila,<sup>2</sup> Jashelle Caga-Meller,<sup>3</sup> Zoë Mullan,<sup>4</sup> Diana Samuel<sup>5</sup> <h4>Objective</h4> As part of The Lancet<i> </i>Group’s commitment to advancing equity, diversity, and inclusion, we implemented the Sex and Gender Equity in Research (SAGER) guidelines<sup>1</sup> in 2023, and <i>The Lancet</i> guidance on reporting race and ethnicity<sup>2</sup> in June 2024 across 24 Lancet Group journals. Although data exist on the reporting of race and ethnicity in published articles after similar guidelines were launched,<sup>3</sup> less is known about how authors view and engage with guidelines, which is crucial to implementing and refining editorial policy. Thus, we aimed to examine authors’ awareness of and responses to these guidelines and identify challenges to guideline implementation. <h4>Design</h4> Corresponding authors of research or review articles submitted to a <i>Lancet</i> journal, who had received a request for revision between July and December 2024, were invited to participate in an online survey in January 2025. The survey asked authors about their awareness of the guidelines, changes they made to their manuscripts in response to editorial advice, the ease with which they made those changes, any challenges encountered, and how these guidelines might influence their next project. <h4>Results</h4> <i> </i>The survey response rate was 22% (484 of 2185 invitations). The largest proportion of respondents was from the US (68 [14%]), followed by China (65 [13%]), the UK (59 [12%]), Australia (30 [6%]), the Netherlands (27 [6%]), Germany (21 [4%]), Canada (19 [4%]), and Sweden (17 [4%]). Fifty-four percent identified as a man (n=262), 41% as a woman (n=197), 1% as non-binary or gender diverse (n=5), and 4% preferred not to say (n=20); (64%) were involved in research and/or development, and 191 (40%) were senior researchers or in middle management. Of the 484 respondents, 193 (40%) and 220 (46%) were aware of the sex and gender and race and ethnicity reporting guidelines before submitting, respectively. A total of 246 respondents (51%) and 266 (55%), respectively, were not required to collect these data, and 9 (2%) and 33 (7%) were not permitted to collect these data. Among 153 respondents (32%) who amended their manuscript as a result of the sex and gender guidance, 104 found this easy or very easy to do. Fewer respondents (90 [19%]) made changes in response to the race and ethnicity guidance, with 55 finding this easy or very easy. <b>Box 25-1122</b> includes open-text responses on challenges in addressing these guidelines. Approximately one-half of respondents said they were likely or very likely to do things differently in their next project as a result of these guidelines (255 [53%] and 221 [46%] for each guidance, respectively). <h4>Conclusions</h4> Less than one-half of the authors surveyed reported awareness of sex and gender or race and ethnicity reporting guidelines before submission, suggesting that increasing awareness could enhance engagement. Most authors who amended their manuscript in response to these guidelines found this to be easy. The challenges identified provide opportunities for journals to refine editorial processes. https://assets.underline.io/markdown_image/1/image/f556edaec2af5850b8b81ae3c23ff545.png <h4>References</h4> 1. Heidari S, Babor TF, De Castro P, Tort S, Curno M. Sex and gender equity in research: rationale for the SAGER guidelines and recommended use. <i>Res Integr Peer Rev</i>. 2016;1:2. doi:10.1186/s41073-016-0007-6 2. Chew M, Samuel D, Mullan Z, Kleinert S; Lancet Group for Racial Equity (GRACE). The Lancet Group’s new guidance to authors on reporting race and ethnicity. <i>Lancet</i>. 2024;403(10442):2360-2361. doi:10.1016/S0140-6736(24)01081-X 3. Flanagin A, Cintron MY, Christiansen SL, et al. Comparison of reporting race and ethnicity in medical journals before and after implementation of reporting guidance, 2019-2022. <i>JAMA Netw Open</i>. 2023;6(3):e231706. doi:10.1001/jamanetworkopen.2023.1706 <sup>1</sup><i>The Lancet, </i>Elsevier Australia, Chatswood, Sydney, Australia, mabel.chew@lancet.com; <sup>2</sup><i>The Lancet Regional Health—Americas, </i>Rio de Janeiro, Brazil; <sup>3</sup><i>The Lancet Regional Health—Western Pacific</i>, Sydney, Australia; <sup>4</sup><i>The Lancet Global Health</i> London, UK; <sup>5</sup><i>The Lancet Digital Health</i>, London, UK. <h4>Conflict of Interest Disclosures</h4> Mabel Chew is a member and former co-chair of The Lancet Group for Racial Equity and has received funding for conference travel expenses from the World Conference on Research Integrity, Committee on Publication Ethics, and Nuffield Department of Primary Care Health Sciences. Taissa Vila is co-chair of and a member of The Lancet Group for Racial Equity. Jashelle Caga-Meller is honorary clinical senior lecturer at the Faculty of Medicine and Health, University of Sydney, Australia, and a member of The Lancet Group for Racial Equity. Diana Samuel is a member and former co-chair of The Lancet Group for Racial Equity, and a member and former Chair of the European Association of Science Editors’ (EASE) EDI Committee. <h4>Acknowledgments </h4> We thank all authors who responded to the survey; Marco Conforti for database support; Louise Hall and Adrian Mulligan for their help in conducting the survey and in preliminary reporting and analysis; Pooja Jha, Rupa Sarkar, Lan-Lan Smith, Richard Horton, and members of the <i>Lancet’s</i> Group for Racial Equity (GRacE) for advice and support.
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 | 0,051 | 0,161 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,000 |
| Bibliométrie | 0,004 | 0,007 |
| Études des sciences et des technologies | 0,001 | 0,006 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,007 | 0,009 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».