[Sex and gender issues in the organisation of tomorrow's medicine]. / Enjeux de sexe et de genre dans l'organisation de la médecine de demain.

Medicine is evolving with increasing feminization and the rise of part-time work. Women now outnumber men among graduates but are underrepresented in leadership roles and in the highest-paid specialties. To meet these economic and organisational challenges, this article proposes a number of courses of action. In addition to an overall increase in the number of medical training places to compensate for retirement and the development of interprofessional integrated care structures, support for academic promotion and management positions for women, as well as an increase in the financial value of professional and non-remunerated activities, are all solutions to be considered. These changes will ensure that medicine is inclusive, efficient and of high quality.

La médecine évolue avec une féminisation croissante et l'émergence de nouveaux modes de travail. Les femmes sont majoritaires parmi les diplômé-es mais sous-représentées aux postes de cadres et dans les spécialités à plus haut revenus. Pour répondre à ces défis économiques et organisationnels, cet article propose des pistes d'actions. En plus d'une augmentation globale des places de formation médicale pour pallier les départs en retraite et du développement de structures interprofessionnelles de soins intégrés, un soutien aux promotions académiques et aux positions de cadres pour les femmes ainsi qu'une revalorisation financière des activités professionnelles et non rémunérées sont autant de solutions à envisager. Ces changements assureront une médecine inclusive, de plus grande efficience et de qualité.

Feasibility and acceptability of a primary care mentoring programme for undergraduate students.

Mentoring plays a crucial role in increasing the attractiveness of primary care careers for medical students. Based on a literature review and structured group discussions, the authors developed a primary care mentoring platform centred on undergraduate medical students' needs. All second- to sixth-year students were invited to enrol into the programme by choosing a mentor from an online platform, which was pilot tested during one academic year (2021-2022) with 16 mentors. Fifteen mentees enrolled into the pilot programme. The evaluation assessed the procedures' feasibility as well as the student-centeredness and acceptability of the programme. Mentees completed a quantitative survey evaluating satisfaction and the mentoring relationship's personal and content aspects. Mentors' feedback was collected during focus groups discussing the programme's acceptability and practical aspects. Both mentees and mentors expressed high levels of satisfaction with the programme. Mentees rated their mentoring relationships highly across most aspects. Mentees' content-related needs included postgraduate training, meeting an inspiring person, work-life balance, and questions about running a private practice. Mentors described the programme as a rewarding experience. They enjoyed the flexible structure that allowed them to adapt to the mentees' individual needs. Maintaining the relationship was mostly the mentors' responsibility. Further structured guidance from the programme coordinators was identified as potentially beneficial for future implementation. The findings highlight the feasibility and the advantages of a flexible, student-centred mentoring programme. The programme attracted students interested in primary care from all levels of undergraduate education. Such programmes may contribute to fostering students' interest in primary care careers.

Performance of machine translators in translating French medical research abstracts to English: A comparative study of DeepL, Google Translate, and CUBBITT.

BACKGROUND: Non-English speaking researchers may find it difficult to write articles in English and may be tempted to use machine translators (MTs) to facilitate their task. We compared the performance of DeepL, Google Translate, and CUBBITT for the translation of abstracts from French to English. METHODS: We selected ten abstracts published in 2021 in two high-impact bilingual medical journals (CMAJ and Canadian Family Physician) and used nine metrics of Recall-Oriented Understudy for Gisting Evaluation (ROUGE-1 recall/precision/F1-score, ROUGE-2 recall/precision/F1-score, and ROUGE-L recall/precision/F1-score) to evaluate the accuracy of the translation (scores ranging from zero to one [= maximum]). We also used the fluency score assigned by ten raters to evaluate the stylistic quality of the translation (ranging from ten [= incomprehensible] to fifty [= flawless English]). We used Kruskal-Wallis tests to compare the medians between the three MTs. For the human evaluation, we also examined the original English text. RESULTS: Differences in medians were not statistically significant for the nine metrics of ROUGE (medians: min-max = 0.5246-0.7392 for DeepL, 0.4634-0.7200 for Google Translate, 0.4815-0.7316 for CUBBITT, all p-values > 0.10). For the human evaluation, CUBBITT tended to score higher than DeepL, Google Translate, and the original English text (median = 43 for CUBBITT, vs. 39, 38, and 40, respectively, p-value = 0.003). CONCLUSION: The three MTs performed similarly when tested with ROUGE, but CUBBITT was slightly better than the other two using human evaluation. Although we only included abstracts and did not evaluate the time required for post-editing, we believe that French-speaking researchers could use DeepL, Google Translate, or CUBBITT when writing articles in English.