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Teams across a wide range of contexts must look beyond task performance to consider the affective, cognitive and behavioral health of their members. Despite much interest in team health in practice, consideration of team health has remained scant from a research perspective. The purpose of this paper is to address these issues by advancing a definition and model of team health.

The authors review relevant literature on team stress, processes and emergent states to propose a definition and model of team health.

The authors advance a definition of team health, or the holistic, dynamic compilation of states that emerge and interact as a team resource to buffer stress. Further, the authors argue that team health improves outcomes at both the individual and team level by improving team members’ well-being and enhancing team effectiveness, respectively. In addition, the authors propose a framework integrating the job demands-resources model with the input-mediator-output-input model of teamwork to illustrate the behavioral drivers that promote team health, which buffers teams stress to maintain members’ well-being and team effectiveness.

This work answers calls from multidisciplinary industries for work that considers team health, providing implications for future research in this area.

As rural nonfarm activities grow in developing countries, less attention is being paid to the opportunities they may provide for women. The purpose of this study is to examine the gender-differentiated impact of nonfarm diversification strategies in rural Senegal.

This study uses data collected from the Senegalese poverty monitoring survey and employs an instrumental variable (IV) approach and a multinomial endogenous treatment model to investigate the extent to which diversification strategies lead to improved outcomes for rural women and their households.

While nonfarm diversification is a male-dominated livelihood strategy, rural women make the most of it, regardless of whether they diversify into low- or high-return nonfarm activities. At the individual level, diversification improves rural women’s well-being through large income-increasing effects and higher empowerment but has no effect on rural men’s well-being. At the household level, the authors find that, when only women diversify, households have lower per capita income but are less likely to be food insecure than when only men or both genders diversify.

This study is based on cross-sectional data, making it impossible to examine the dynamic effects of nonfarm diversification strategies on well-being outcomes.

This study contributes to the current literature on rural livelihood diversification. While much attention has been paid to the feminization of agriculture, remarkably little is known about the expanding role of rural women in the nonfarm sector.

This paper aims to determine the impact of mentorship on the development of self-directedness among beginner teachers in their initial years of teaching.

The researcher adopted a positivist paradigm to explore the situation of concern. Quantitative research was conducted, involving the collection and analysis of numerical data. Two closed-ended structured questionnaires were utilised, derived from the 40-item self-directed learning readiness scale (SDLRS) developed by Fisher and King, and a pre-determined questionnaire by Glazerman focused on the first-year teaching experience, induction and mentoring of beginner teachers.

Beginner teachers merely relying on the knowledge obtained from their studies is insufficient to achieve a satisfactory level of self-directedness when starting a teaching career. Most beginner teachers faced significant challenges in their early years of teaching due to the absence of mentoring support. In addition, most indicated that they resume their teaching duties and rely on their district for general support, guidance and orientation. Finally, the results have shown that mentoring positively impacts beginner teachers’ self-directedness.

The first limitation was that this study was narrowed to one South Africa University part-time B.Ed honours students working as beginner teachers in different provinces at primary and secondary schools. As a result, the findings of this research might be interpreted by some critics as one-sided and not representative of the views of most beginner teachers in South Africa who are working. The second limitation of this study is the sample size. In this study, 222 responses were received. As a result, the findings of this research might be considered not representative of the target sample size.

The presence and effective implementation of mentoring programmes in schools can positively impact beginner teachers' professional development and retention during their first years of teaching.

We contend that our research holds significance for international readership as it aims to garner attention towards potential research endeavours in diverse settings concerning mentorship programs for beginner teachers, specifically promoting self-directed learning. Our research offers opportunities to compare our findings with studies conducted in more comprehensive, comparative contexts and foster research possibilities in broader, contrasting contexts.

Based on the findings of this research, the availability and effective use of mentoring programmes would significantly affect beginner teachers' self-directedness, improve their retention rate and alleviate their teaching challenges. This study was the first research on the perceptions of the influence of mentoring on the self-directedness of beginner teachers.

As public health professionals strive to promote vaccines for inoculation efforts, fervent anti-vaccination movements are marshaling against it. This study is motived by a need to better understand the online discussion around vaccination. The authors identified the sentiments, emotions and topics of pro- and anti-vaxxers’ tweets, investigated their change since the pandemic started and further examined the associations between these content features and audiences’ engagement.

Utilizing a snowball sampling method, data were collected from the Twitter accounts of 100 pro-vaxxers (266,680 tweets) and 100 anti-vaxxers (248,425 tweets). The authors are adopting a zero-shot machine learning algorithm with a pre-trained transformer-based model for sentiment analysis and structural topic modeling to extract the topics. And the authors use the hurdle negative binomial model to test the relationships among sentiment/emotion, topics and engagement.

In general, pro-vaxxers used more positive tones and more emotions of joy in their tweets, while anti-vaxxers utilized more negative terms. The cues of sadness predominantly encourage retweets across the pro- and anti-vaccine corpus, while tweets amplifying the emotion of surprise are more attention-grabbing and getting more likes. Topic modeling of tweets yields the top 15 topics for pro- and anti-vaxxers separately. Among the pro-vaxxers’ tweets, the topics of “Child protection” and “COVID-19 situation” are positively predicting audiences’ engagement. For anti-vaxxers, the topics of “Supporting Trump,” “Injured children,” “COVID-19 situation,” “Media propaganda” and “Community building” are more appealing to audiences.

This study utilizes social media data and a state-of-art machine learning algorithm to generate insights into the development of emotionally appealing content and effective vaccine promotion strategies while combating coronavirus disease 2019 and moving toward a global recovery.

The peer review history for this article is available at https://publons.com/publon/10.1108/OIR-03-2022-0186