Exposing women and girls to female role models is considered essential to break down gender-stereotypical beliefs on STEM interest and engagement. However, evidence remains controversial regarding the efficacy of these interventions. Here, we provide a scoping review of fifty-seven empirical studies that considers information about: (1) research type, (2) target, (3) type of intervention, (4) role models’ characteristics, (5) variables of interest and (6) effects of the study. Our findings show that research is considerably heterogeneous in terms of role models, interventions, variables of interest and effects. Role models are frequently female STEM professionals or a mixed-gender group of STEM workers. Interventions mainly consist of asking participants to read a brief article about the role model and the effect of being exposed to a role model is mostly tested on participants’ characteristics, e.g. attitudes toward STEM and performance. This heterogeneity comes at a price, i.e. it is difficult to understand the effectiveness of role models’ exposure. Future research should focus on whether and how the heterogeneous characteristics of role models influence the efficacy of these interventions.

Depression is a common mental health condition among older adults, while social networks offer protection. This meta-analysis quantifies the relationship between the structural aspects of social networks and depression in this population. Seven electronic databases were searched from inception until July 2023. Eligible studies focused on community-dwelling older adults (mean age ≥60), defined depression, referenced social networks in the abstract, and were published in English. Random-effects meta-analyses combined standardized beta coefficients for continuous depression outcomes and log odds for binary outcomes. Study quality, heterogeneity and potential publication bias were evaluated. Sixty-one studies met the inclusion criteria. Larger network size, frequent contact, and higher network scale scores were linked to lower depression levels, though effect sizes were modest. Network scales, incorporating structural and functional aspects, showed the strongest association with reduced depression, though this finding was rather suggestive. The distinction between family and friend networks was less significant, with combined measures and family ties showing stronger associations. Gender did not significantly influence the association, and continuous depression measures provided more nuanced insights than binary ones. Social networks offer modest protection against depression in older adults. Future research should standardize depression measures, further investigate gender and network differences, and explore long-term effects.

The rise of adult content creation platforms is triggering a deep revision of the social acceptability of new habits and the relations between the human body and marketing practices. However, academic research on this phenomenon is still scarce. This scoping review aimed to summarize and discuss the studies about content creators sharing adult content on subscription-based digital platforms. Based on the protocol established a priori, we selected 17 studies. Of these, we reported the field of academic research, the definition used for the content creators, the topic of interest, the results and the suggestions for future research. The current literature is mainly qualitative and focuses on the experiences of the creators of OnlyFans. While most authors used the label of content creator when referring to them, participants mainly defined themselves as sex workers. Some of the recurrent themes in the interviews were those that characterize traditional sex workers.

Gender stereotypes are often viewed as one of the root causes of the gender gap in STEM. According to Eccles’ model, they would indirectly influence major choices by shaping expectations of success and values attached to the viable options. However, empirical findings on the link between implicit gender-science stereotypes and college major intentions are limited. To fill this gap, the current study examines this association in a mixed-gender sample of 302 Italian high-school students. Logistic regression analysis revealed that implicit gender stereotypes were directly associated with females’ intention of majoring in STEM. Unlike previous findings, the mediation analysis could not confirm that other relevant factors, i.e., interest in the subject, performance at school, identification with the subject, and value attributed to the job’s salary and social utility, moderated this association.

Stereotypes do not have a unique definition, being mostly considered a generalized belief on the quality and characteristics of members of specific groups or social categories. Hence, various scales and measurements have been proposed to assess the endorsement of beliefs on the association of gender and scientific/language-related skills. The aim of the paper was to summarize, compare and discuss those measures, distinguishing between explicit, implicit and indirect measures. The review of the literature highlighted a huge but unrecognized heterogeneity in the constructs of gender stereotypes, especially for explicit measures. This can hamper findings comparability, reduce scales’ validity, affect the correlation between implicit and explicit measurements, and bias their interpretations due to ambiguous terminologies.