Laylla Galdino-Santos

Gender inequalities persist in the scientific community, including dentistry, affecting key aspects such as representation, success, and recognition. Despite progress in increasing women's participation in research, disparities remain, particularly in publication rates, citation impact, funding acquisition, and leadership positions. This opinion article examines the systemic and structural barriers that impede women's academic advancement, introduces the Tree of Gender Inequality in Science model, and discusses potential interventions to promote gender equity in science. Gender disparities in academia are deeply rooted in systemic biases and institutional structures. Women are consistently underrepresented among highly cited researchers, editorial boards, and grant recipients. Implicit biases, discriminatory hiring practices, and limited access to mentorship further hinder their career progression. However, interventions such as unconscious bias training, mentorship programs, and equity-based institutional reforms have the potential to address these inequalities. In conclusion, addressing gender disparities in academia requires a multifaceted approach that combines policy reforms, institutional commitment, and cultural shifts. Achieving gender equality is essential for scientific innovation and progress. Immediate action is needed to dismantle barriers and create inclusive environments that enable all researchers to thrive.

This study evaluated the methodological quality and presence of spin in systematic reviews with meta‐analyses comparing single‐visit and multiple‐visit endodontic treatment, and investigated factors associated. Systematic reviews of randomised clinical trials were included without restrictions on language or publication year. Narrative reviews, reviews without meta‐analysis, non‐randomised or non‐clinical studies, and conference abstracts were excluded. A comprehensive search was conducted in PubMed, Scopus, Web of Science, the Cochrane Library and grey literature in January 2025. Spin was classified using the Yavchitz et al. framework, and methodological quality was assessed with AMSTAR 2. Data extraction and spin assessment were performed independently and in duplicate. Thirteen systematic reviews were included. Spin was identified in 12 studies of abstracts and 10 of full texts, mainly as a misleading interpretation. Most reviews were rated as low or critically low quality. Positive results and absence of risk‐of‐bias assessment were associated with increased spin in full texts.

To investigate the prevalence and types of spin, assess reporting quality and risk of bias, and identify factors associated with spin in systematic reviews with meta-analyses of nonrandomized studies in restorative dentistry. Five databases were searched through October 2025. Eligible systematic reviews compared at least two restorative materials or interventions for permanent teeth and reported restoration longevity, survival, or success/failure. Spin was assessed in abstracts and main texts using the classification by Yavchitz et al. Reporting quality and risk of bias were evaluated using AMSTAR 2 and ROBIS. Associations with spin were explored using Poisson and ordinal logistic regression. Twenty-six systematic reviews were included. Spin was identified in 92.3% of abstracts and 96.15% of main texts. In abstracts, the most frequent strategies were failure to declare conflicts of interest (34.61%) and failure to consider differences in study designs (34.61%). In the main text, common strategies included inadequate consideration of reporting bias (80.76%), insufficient consideration of risk of bias of primary studies (34.61%), and conclusions claiming equivalence despite nonsignificant results with wide confidence intervals (26.31%). Most reviews were rated as critically low quality by AMSTAR 2 (73.08%), and 38.46% had high risk of bias by ROBIS. Exceeding the abstract word limit (prevalence ratio [PR = 1.69; 95%CI: 1.19–2.42), failure to report funding sources (PR = 2.10; 95%CI: 1.22–3.59), and absence of a structured abstract (PR = 1.56; 95%CI: 1.18–2.07) were associated with spin. Spin is prevalent in systematic reviews of nonrandomized studies in restorative dentistry and is associated with inadequate reporting practices.

Aim: This prognostic study aims to develop a machine learning (ML) survival model for estimating the longevity (success and survival rate) of restorations in endodontically treated teeth (ETT). Methodology: Data were consolidated from four controlled clinical trials conducted in the Netherlands and Brazil, involving 424 patients and 618 restorations with up to 17 years of follow‐up. The evaluated predictive models included Gradient Boosting Survival, Random Survival Forests and Survival Support Vector Machine. The dataset was split into 70% for training and 30% for testing. Hyperparameter tuning was optimised via 10‐fold cross‐validation with 50 iterations using hyperopt. Performance was assessed through the time‐dependent area under the ROC curve (AUC), concordance index (C‐index), inverse probability of censoring weights (IPCW C‐index) and time‐dependent Brier score. Results: The Gradient Boosting Survival model achieved the highest AUC mean (0.83, 95% confidence interval [CI], 0.81–0.78), C‐index (0.80), IPCW C‐index (0.78) and Brier score (0.06) for survival rate predictions, maintaining predictive stability over time. For success rate, the Random Survival Forest model outperformed others (AUC = 0.73, 95% CI [0.70–0.75]), C‐index (0.66), IPCW C‐index (0.64) and Brier score (0.14). SHAP analysis identified patient age and tooth type as having the highest variable importance for survival, while the dentist's experience was critical for success outcomes. Fairness analysis revealed performance disparities across sexes and countries in the models. Conclusions: The models demonstrated high predictive performance, mainly in survival rate prediction. ML models show promise for developing a robust, data‐driven framework to evaluate success and survival outcomes in ETT.

Purpose: To assess the knowledge and use of reporting guidelines among research group leaders in the health sciences in Brazil. Methods: A cross-sectional study was conducted with leaders of research groups registered on the CNPq platform in health sciences disciplines. Participants were invited to complete an electronic survey comprising 70 questions across five sections, addressing scientific integrity practices within graduate programs and research groups. The estimated response time was 15 minutes. The questionnaire was pilot-tested by two reviewers. This report adheres to the STROBE and CHERRIES checklists from the EQUATOR Network. Results: The survey was sent to 5,576 researchers, yielding 430 responses after three contact attempts (response rate: 7.7%). Most respondents were female (55.5%) and had over 11 years of leadership experience (34.6%). Approximately 56.4% reported being unaware of the EQUATOR Network, although 64.3% stated they followed an appropriate reporting guideline in their most recent study. Additionally, 45.8% emphasized the importance of adherence to reporting guidelines by other research groups; 53.2% highlighted their relevance to their own groups; and 54.6% considered such adherence to be extremely important on a personal level. Conclusions: Although respondents reported adherence to scientific integrity practices, potential selection and cognitive biases must be acknowledged. These findings underscore the need for strategies to enhance the implementation of reporting guidelines and promote completeness and transparency in research reporting. Initiatives led by information science professionals may support this goal. Further investigation is warranted to explore these complexities and foster integrity in academic research.

Aim: The present study aimed to investigate if cannabis use can be associated with gingival bleeding and caries experience among Brazilian students. Methods: A cross-sectional study was performed in 2016 with first-semester university students in Pelotas. Data was collected via a self-administered questionnaire. Self-reported gingival bleeding and caries experienced were collected. Cannabis use was assessed using a modified version of the Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST). We define cannabis users as individuals who report using cannabis at least once a month. A Poisson regression model with robust variance was used to analyze the data. Results: A total of 2,058 (64.5% of eligible students) students were assessed. The prevalence of caries experience was 68.2% and gingival bleeding was 50.8%. The prevalence of cannabis use was 11.7%. After controlling (sex, skin color, age, family income, depressive symptoms, oral health self-perception tobacco use), individuals who use cannabis present a prevalence of gingival bleeding 2.51 (CI95%[1.42–4;53]) higher than individuals who did not use cannabis. The association was maintained even when the individuals who used tobacco were excluded from the sample (PR=2.24, CI95%[1.16 – 4.31]). Cannabis use did not show an association with the experience of dental caries in both crude (PR 0.91 CI95%[0.82 – 1.01]) and adjusted models (PR 0.93 CI 95%[0.83 – 1.05]). Conclusion: Cannabis use was associated with the presence of gingival bleeding among the students of a public university in the south of Brazil. However, the experience of dental caries did not present an association with cannabis use.