Research Questions Research Articles

A guide for planning triangulation studies to investigate complex causal questions in behavioural and psychiatric research.

At the basis of many important research questions is causality - does X causally impact Y? For behavioural and psychiatric traits, answering such questions can be particularly challenging, as they are highly complex and multifactorial. 'Triangulation' refers to prospectively choosing, conducting and integrating several methods to investigate a specific causal question. If different methods, with different sources of bias, all indicate a causal effect, the finding is much less likely to be spurious. While triangulation can be a powerful approach, its interpretation differs across (sub)fields and there are no formal guidelines. Here, we aim to provide clarity and guidance around the process of triangulation for behavioural and psychiatric epidemiology, so that results of existing triangulation studies can be better interpreted, and new triangulation studies better designed. We first introduce the concept of triangulation and how it is applied in epidemiological investigations of behavioural and psychiatric traits. Next, we put forth a systematic step-by-step guide, that can be used to design a triangulation study (accompanied by a worked example). Finally, we provide important general recommendations for future studies. While the literature contains varying interpretations, triangulation generally refers to an investigation that assesses the robustness of a potential causal finding by explicitly combining different approaches. This may include multiple types of statistical methods, the same method applied in multiple samples, or multiple different measurements of the variable(s) of interest. In behavioural and psychiatric epidemiology, triangulation commonly includes prospective cohort studies, natural experiments and/or genetically informative designs (including the increasingly popular method of Mendelian randomization). The guide that we propose aids the planning and interpreting of triangulation by prompting crucial considerations. Broadly, its steps are as follows: determine your causal question, draw a directed acyclic graph, identify available resources and samples, identify suitable methodological approaches, further specify the causal question for each method, explicate the effects of potential biases and, pre-specify expected results. We illustrated the guide's use by considering the question: 'Does maternal tobacco smoking during pregnancy cause offspring depression?'. In the current era of big data, and with increasing (public) availability of large-scale datasets, triangulation will become increasingly relevant in identifying robust risk factors for adverse mental health outcomes. Our hope is that this review and guide will provide clarity and direction, as well as stimulate more researchers to apply triangulation to causal questions around behavioural and psychiatric traits.

Therapeutic resources used by traditional communities of the Brazilian Amazon: a scoping review.

The traditional communities of the Brazilian Amazon possess significant knowledge regarding the huge therapeutic arsenal available from natural sources that can be used to care for their health problems. This study aimed to identify, map and synthesize the scientific evidence on the use of traditional medicine as a therapeutic resource when used by traditional communities of the Brazilian Amazon. This is a scoping review, which is a method used to map the main concepts of a research area, the available evidence and its sources. It is developed in five steps: (1) identification of the research question; (2) identification of relevant studies; (3) selection of studies; (4) data analysis; and (5) grouping, synthesis and presentation of data. Medicinal plants, vertebrates and invertebrates, among other medicinal products, are elements that are widely used by traditional populations. Plant stems, bark, leaves, flowers, fruits, seeds, roots, tubers and even the whole plant are prepared in various forms, such as teas, infusions, smoke for rituals, baths, macerations, oils, ointments, concoctions, dressings, incenses and exfoliants, among others. The main structures and forms used from animals are lards, fats, viscera, horns, cocoons, nests, feathers and beaks of birds, eggs and roes. These therapeutic practices are often carried out using endogenous, wild and domesticated natural resources present in the biodiverse environments of traditional populations. They involve magical-religious beliefs to treat all types of illnesses, including cultural syndromes that affect children, young people, adults and the elderly. This scoping review has an important role to disseminate and expand the discussion of traditional medicine practices, inviting readers - whether they are health professionals, community members, managers or decision-makers - to a continuing debate using an intercultural dialogue necessary to improve approaches. From this perspective, it is essential to consider the comprehensive legal and legal framework that guides the public policies of national health systems.

Failing successfully with dance in physical education teacher education

ABSTRACT Background Studies underline physical education teacher education (PETE) students’ unfamiliarity and discomfort with dance in physical education (PE) and PETE and place dance outside students’ comfort zones. At the same time, research highlights PETE students’ athletic background and how this continues to be rewarded in PE. Hence, many students enter the PETE programme without any experience of failing – not mastering – activities done in PE. When students enter the PETE programme, they are faced with the expectation of being able to teach dance as future PE teachers, and many students experience unfamiliarity with the content and teaching and working methods in PE for the first time. This unfamiliarity creates emotional tension and uneasiness among the students. Purpose In this project, we borrow Nancy Stark Smith’s concept of failing successfully to investigate how students’ worries about failure can be turned into more successful achievements and considered valuable for learning processes in higher education. The research question guiding this article is: How can risk-taking and fear of failing become significant assets for gaining teacher competence in PETE? Methods This paper is a combined teaching and research project focusing on PETE students’ experiences as they were given the task of developing and performing breaking series. All students participated in two dance lessons. The data material consists of the PETE educator’s notes, Post-it notes from an emotional poll and the students’ subsequent written reflections. Findings Our analysis shows that all students were worried and even dreaded performing their breaking series. The students’ written reflections revealed that they were challenged on a personal and emotional level. For most students, the assignment changed from being perceived as (almost) impossible to becoming an experience of mastery that exceeded their expectations. The study underlines the importance of risk, conceptualises challenging situations, and makes the process of learning a common concern. Conclusion This study emphasises that dreading failure and the experience of failing can be turned into success, and such understandings not only allow examining students’ experiences in new ways but also redirect dance teaching in PETE and PE in new, more challenging, and expanded directions.

Teacher epistemic curiosity: how principal–teacher conversation supports it

PurposeThe purpose of this study was to introduce teacher epistemic curiosity for student learning into the leadership literature and to determine if school principals can support it. The inquiry was organized by the following research question: In what ways can principal–teacher conversations support teacher epistemic curiosity for student learning? The research question guided the review of literature on epistemic curiosity, eventually leading to the leadership practice of transformative leadership conversation (TLC). A hypothesized model on the relationship between TLC and epistemic curiosity for student learning was advanced from research on student and employee curiosity and self-determination theory.Design/methodology/approachThe hypothesized model was tested with a correlational research design. Teacher survey data were collected in December 2023 from a random sample of certified public school teachers from a metropolitan area in a southwestern state of the USA. Usable survey responses were received from 2,022 teachers, resulting in a 55% response rate. The hypothesized model was tested with structural equation modeling in AMOS 28 using robust maximum likelihood estimation. The latent models include measurement and structural components.FindingsResults confirm the hypothesized relationships among TLC, need-satisfaction and teacher epistemic curiosity. TLC and need-satisfaction both had strong, direct relationships with teacher epistemic curiosity for student learning. TLC explained approximately 20% of the variance in teacher curiosity and need-satisfaction explained approximately 18%. The combined model accounted for approximately 55% of the variance in teacher epistemic curiosity.Originality/valueThe study emerged from robust evidence on the essential function of curiosity for knowing, learning, performance and life well-being, as well as limited research on social processes that leaders can leverage to stimulate teachers’ motivation to understand how their students learn. Curiosity is an inner energy behind learning; it fuels an innate drive to explore, know, create, design and adapt to our surroundings. Schools and classrooms come to life when teachers and students engage in learning from a place of curiosity, making this motivational resource worthy of leadership attention.

APPROACHES ON SANITATION AND HEALTH IN THE LEGAL AMAZON

The objective of this article is to understand and analyze the approaches employed in study of the relationship between sanitation and health in the Legal Amazon from 2013 to 2023. This article conducts an integrative review of the literature drawing upon the works available in the Scientific Electronic Library Online, Virtual Health Library, and Capes Periodicals. 64 out of 185 studies are analyzed, in line with the research question and after applying the eligibility criteria. The studies are clustered into four thematic categories: (i) occurrence of diseases and injuries; (ii) environmental analysis, which includes studies on the risks of elements present in the soil, water and animals; (iii) technology assessment and proposal of methodologies; and (iv) impact of capitalist expansion. More than half of the studies (56%) refer to the more classic approach, which establishes a relationship between sanitation conditions and the occurrence of diseases and injuries. At the same time, an expansion of theoretical-conceptual approaches to the topic was identified, including a focus on human rights and environmental justice, especially in studies about the impact of capitalist expansion. The results of this research point to the need of improving the critical reflection on the political, economic, and sociocultural determinants inherent to the connections between sanitation and health in Brazil.

Integrating historical approaches of university ecosystems: reviewing the literature streams and future directions

AbstractIt is practically consensual that universities contribute to economic and social growth; therefore, they nowadays need to play a more active role in answering the changing needs of society. In addition, universities hold the potential to promote regional innovation through their influence over the ecosystems they participate in. This article aims to identify, analyse and integrate the historical approaches of university ecosystems and university roles through a systematic literature review. The findings identify four different periods: (i) University-Industry collaboration (until 2000); (ii) changing the university model into a triple-helix model (2001–2010); (iii) from the triple to the quadruple-helix model in the knowledge society (2011–2020); and (iv) ecosystem complexity and the Neo Triple-Helix Model (from 2021). The study contributes to the literature on universities and the ecosystem by providing a unified perspective on the importance of the university’s role in the economic and social growth of the knowledge business and the evolution of the ecosystem. These results provide an overview of the trends in university ecosystems, including an integrative framework, research themes, and research questions able to guide future studies.

Public attitudes toward athlete activism in sport: utilizing a multivariate list experiment to address social desirability bias in survey responses

ABSTRACT Research Question: This study investigates the degree of hidden racial hatred towards athlete protests within the Black Lives Matter (BLM) movement by correcting for the Social Desirability Bias (SDB) in survey responses. Research Methods: Employing a multivariate list experiment on a nationally representative sample (n = 1,075), it assesses the extent of SDB and explores variations in support for on-field kneeling protests based on the race of the athlete, respondent demographics, and sport fan identification. Results and Findings: Findings reveal underreported disapproval for BLM-supportive athlete activism, particularly when the protesting athlete is identified as Black. Further analyses highlight hidden biases influenced by respondents’ race, region, political affiliation, and fan identification. Implications: Our findings offer valuable insight on applying list experiments to reduce social desirability biases in surveys, ensuring more accurate reflections of public opinion on contentious topics.

A systematic review on robot-assisted language learning for adults

In the 21st-century era of globalization, language proficiency is a pivotal connector across cultures, with artificial intelligence (AI) revolutionizing educational paradigms through Robot-Assisted Language Learning (RALL). This systematic review examines the role of RALL in adult second language acquisition, focusing on its pedagogical strategies and learner engagement. Unlike the previous systematic reviews that explore the multifaceted roles of robots in language learning, including as teachers, tutors, assistants, and peer learners, we identify explicit and implicit instructional strategies within RALL, highlighting the unique learning landscape of adult learners characterized by self-regulation and self-direction. We assess the latest advancements in RALL for adult learners through three research questions, compare the effectiveness of explicit versus implicit instructions, and investigate affective factors enhancing RALL performance. Our review contributes a comprehensive status analysis, in-depth exploration of interaction modes, and insights for future research directions, providing a roadmap for academic research and practical guidance for educators and robot developers. This study aims to optimize RALL strategies to better meet the needs of adult learners, fostering a more efficient and engaging language learning experience.

Social media quality in undergraduate medical education: A reconceptualisation and taxonomy.

Social Media (SoMe) as a learning tool, though ubiquitous in society and popular within medical education, is often criticised as superficial. Its limitless output has been blamed for encouraging shorter attention spans and shirking in-depth reflection. The evidence base is itself superficial and lacking rigour or meaning. We aimed to consider a theoretical basis for how 'quality' learning may happen on such platforms. Our findings then informed the construction of a taxonomy for SoMe learning. We conducted a qualitative interview study of United Kingdom (UK) medical students using a theory-informed inductive study design. The research question was: 'How do medical students conceptualise quality of learning on social media?'. We purposively sampled participants from responses to a short survey collecting demographic and SoMe usage data. Interview data were analysed using framework analysis and informed by Blooms taxonomy, connectivism and communities of practice (CoP) theories. We received survey responses from 118 medical students across 25 UK medical schools. From these, 13 participants were recruited to individual semi-structured interviews. We constructed three themes through framework analysis of interview data: cognitive hacking, professional identity reflection and safety, control and capital. Quality SoMe learning may be conceptualised as a socially connected process, built upon constantly evolving networks but inexorably influenced by fluctuating hierarchy within learner-centric CoP. Educators and institutions may support high-quality learning for students through engagement which promotes community development, and safe, listening environments which foster professional identity formation.

Relationship between personality and music preference: Psychometric adaptation of the music preference scales in a Chinese sample

Individuals evidently have different tastes in and preferences for music. The purpose of this study was to develop two scales for measuring music preference based on genres (text-based) and excerpts (clip-based), using a Chinese sample to explore the relationship between music preference and personality. Specifically, we collected measures of people’s self-reported preferences for a wide range of music genres for further analysis in Study 1. In Study 2, we developed two music preference scales based on the genres identified in Study 1, one text- and the other clip-based. The results of two principal component analyses suggest three-dimensional psychological structures of music preference using both versions of the scale: (1) Traditional and Retro, (2) Exotic and Complex, and (3) Intense and Rebellious. Correlation and regression analyses of music preferences and personality also indicated that music preference is a relatively stable construct that reflects personality traits. Moreover, the three factors identified from the results of studying music preferences in a Chinese sample differ from those identified in studies of music preference in Western countries, suggesting that music preference is influenced by culture. The two scales yielded similar but slightly different outcomes reflecting their discrete emphases and characteristics; they can be used separately or together, depending on the research topic and question. In this study we verified the structure of music preference among a Chinese sample. It provides a reference point for theoretical research on music preference and personality and has practical applications.

Mapping design stages and methodologies for developing STEM concept inventories: a scoping review

BackgroundConcept inventories (CIs) have become widely used tools for assessing students’ learning and assisting with educational decisions. Over the past three decades, CI developers have utilized various design approaches and methodologies. As a result, it can be challenging for those developing new CIs to identify the most effective and appropriate methods and approaches. This scoping review aimed to identify and map key design stages, summarize methodologies, identify design gaps and provide guidance for future efforts in the development and validation of CI tools.MethodsA preliminary literature review combined theoretical thematic analysis (deductive, researcher-driven) focusing on specific data aspects, and inductive thematic analysis (data-driven), using emerging themes independent of specific research questions or theoretical interests. Expert discussions complemented the analysis process.ResultsThe scoping review analyzed 106 CI articles and identified five key development stages: define the construct, determine and validate content domain; identify misconceptions; item formation and response processes design; test item selection and validation; and test application and refinement. A descriptive design model was developed using a mixed-method approach, incorporating expert input, literature review, student-oriented analysis, and statistical tests. Various psychometric assessments were employed to validate the test and its items. Substantial gaps were noted in defining and determining the validity and reliability of CI tools, and in the evidence required to establish these attributes.ConclusionThe growing interest in utilizing CIs for educational purposes has highlighted the importance of identifying and refining the most effective design stages and methodologies. CI developers need comprehensive guidance to establish and evaluate the validity and reliability of their instruments. Future research should focus on establishing a unified typology of CI instrument validity and reliability requirements, as well as the types of evidence needed to meet these standards. This effort could optimize the effectiveness of CI tools, foster a cohesive evaluation approach, and bridge existing gaps.

Psycho-Emotional Aspects of Pregnant Women Diagnosed with a Rare Disease: A Systematic Review

Background: Psycho-emotional aspects as a cross-cutting theme have gained relevance and scientific interest in recent years. Pregnant women diagnosed with a rare disease constitute a vulnerable population, experiencing psycho-emotional challenges due to their specific circumstances. It is essential that this group is informed and receives the proper to manage the physical, emotional, and psychological challenges linked to their condition. Objectives: The aim of this review is to understand how the diagnosis of a rare disease affects the psycho-emotional aspects of a pregnant woman. Methods: The research question posed is how does the diagnosis of a rare disease affect the psycho-emotional aspects of a pregnant woman? This systematic review has been carried out following the PRISMA model and has been registered in PROSPERO with registration number CRD42024558523. A literature search was conducted in the databases of Scopus, PubMed, Cinahl, Scielo, and the Cochrane Library. Articles were selected on the basis of the following inclusion criteria: publication in the last twenty years and all languages. Results: In the end, 28 articles were selected. The main results highlight that there is a negative impact on the psycho-emotional level in these patients, altering aspects such as anxiety, stress, social rejection, and self-stigma. Conclusion: The role of nursing in addressing this psycho-emotional dimension as a mediator between families and other branches of the health sciences environment stands out.

Emissions from air travel and major football tournaments

ABSTRACT Research Question This paper explores the environmental impact of air travel during two international football tournaments – the Mens FIFA World Cup and UEFA European Championships – by estimating CO2 emissions from the movements of competing teams. Specifically, we consider how travel associated with major international football tournaments has evolved over time. Research Methods We access data for 895 international football matches (June 1990–July 2024). Our data focuses on the travel associated with players and management travelling to, and within, host countries and includes the movement of more than 16,000 people. Estimates of CO2 emissions per passenger (per kilometre) are used to examine the environmental impact of travelling to host countries, and competing, during the tournament. Results and Findings Our findings are the first attempt to demonstrate the CO2 emissions from team travel to and within major football tournaments. Despite improvements in aeroplane fuel efficiency, the carbon footprint from team travel has generally not been reduced. The decision to expand these tournaments, locate matches across large geographic areas, and use co-host countries has exacerbated this issue. Implications Our findings can support sustainability initiatives and could be adopted by both federations to curb CO2 emissions which appear to undermine genuine attempts to become more environmentally friendly.

The language of gratitude: An empirical analysis of acknowledgments in German medical dissertations

Abstract Acknowledgment sections are a rich but underused resource for understanding how language is used for social purposes (such as expressing gratitude and communicating social relations networks), and how conventions and patterns emerge in this process. This paper presents a usage-based case study combining qualitative and quantitative methods for analyzing a dataset of >300 acknowledgment sections from medical dissertations written in German. In our quantitative analysis, we gauge keywords and key n-grams and assess the relative position of recurrent words in each text. Our analysis shows that this text type has developed clear conventions, with acknowledgments in the professional domain being followed by a usually smaller set of expressions of gratitude associated with the private domain. In addition, our quantitative analysis suggests recurrent patterns that can be linked to specific socio-pragmatic functions. For instance, an analysis of n-grams attested in text segments associated with the professional vs. the private domain shows some differences with regard to the typical patterns chosen in those segments. Our analysis also raises a number of future research questions, thus showing that acknowledgment sections are a highly interesting object of study that deserve to be investigated in more detail.

Organisational coaching to improve workplace resilience: a scoping review and agenda for future research

In an increasingly demanding and pressured work environment, employee resilience is acknowledged as a critical element to navigate adversity. There has been increased focus and interest in studying the nature of resilience in the workplace, however the mechanisms of developing and sustaining resilience are still under debate. Coaching is a promising method organisations use to improve employee resilience and provides employees with support to deal with the challenging working environment. There has been significant interest in coaching for resilience in recent years, however there is no overarching, consolidated view on the nature and dynamics of resilience coaching. This scoping review seeks to fill this gap by making three contributions. Firstly, we present details on various types of coaching approaches used to improve resilience. Secondly, we review the specific coaching elements and processes that lead to improved resilience and finally, we provide an overview on the efficacy of resilience coaching interventions. We conclude this scoping review with a roadmap for future research to help position and strengthen organisational coaching as a pillar of resilience development. This scoping review followed a five-stage PRISMA-ScR methodology which entails formulating research questions; identifying studies; choosing studies; extracting and charting data; and summarising the findings.

Enhancing IoT Security in Vehicles: A Comprehensive Review of AI-Driven Solutions for Cyber-Threat Detection

Background: The Internet of Things (IoT) has improved many aspects that have impacted the industry and the people’s daily lives. To begin with, the IoT allows communication to be made across a wide range of devices, from household appliances to industrial machinery. This connectivity allows for a better integration of the pervasive computing, making devices “smart” and capable of interacting with each other and with the corresponding users in a sublime way. However, the widespread adoption of IoT devices has introduced some security challenges, because these devices usually run in environments that have limited resources. As IoT technology becomes more integrated into critical infrastructure and daily life, the need for stronger security measures will increase. These devices are exposed to a variety of cyber-attacks. This literature review synthesizes the current research of artificial intelligence (AI) technologies to improve IoT security. This review addresses key research questions, including: (1) What are the primary challenges and threats that IoT devices face?; (2) How can AI be used to improve IoT security?; (3) What AI techniques are currently being used for this purpose?; and (4) How does applying AI to IoT security differ from traditional methods? Methods: We included a total of 33 peer-reviewed studies published between 2020 and 2024, specifically in journal and conference papers written in English. Studies irrelevant to the use of AI for IoT security, duplicate studies, and articles without full-text access were excluded. The literature search was conducted using scientific databases, including MDPI, ScienceDirect, IEEE Xplore, and SpringerLink. Results were synthesized through a narrative synthesis approach, with the help of the Parsifal tool to organize and visualize key themes and trends. Results: We focus on the use of machine learning, deep learning, and federated learning, which are used for anomaly detection to identify and mitigate the security threats inherent to these devices. AI-driven technologies offer promising solutions for attack detection and predictive analysis, reducing the need for human intervention more significantly. This review acknowledges limitations such as the rapidly evolving nature of IoT technologies, the early-stage development or proprietary nature of many AI techniques, the variable performance of AI models in real-world applications, and potential biases in the search and selection of articles. The risk of bias in this systematic review is moderate. While the study selection and data collection processes are robust, the reliance on narrative synthesis and the limited exploration of potential biases in the selection process introduce some risk. Transparency in funding and conflict of interest reporting reduces bias in those areas. Discussion: The effectiveness of these AI-based approaches can vary depending on the performance of the model and the computational efficiency. In this article, we provide a comprehensive overview of existing AI models applied to IoT security, including machine learning (ML), deep learning (DL), and hybrid approaches. We also examine their role in enhancing the detection accuracy. Despite all the advances, challenges still remain in terms of data privacy and the scalability of AI solutions in IoT security. Conclusion: This review provides a comprehensive overview of ML applications to enhance IoT security. We also discuss and outline future directions, emphasizing the need for collaboration between interested parties and ongoing innovation to address the evolving threat landscape in IoT security.

An Introduction to Longitudinal Synthetic Cohorts for Studying the Life Course Drivers of Health Outcomes and Inequalities in Older Age

Abstract Recent Findings Research on the drivers of health across the life course would ideally be based in diverse longitudinal cohorts that repeatedly collect detailed assessments of risk factors over the full life span. However, few extant data sources in the US possess these ideal features. A “longitudinal synthetic cohort”—a dataset created by stacking or linking multiple individual cohorts spanning different but overlapping periods of the life course—can overcome some of these challenges, leveraging the strengths of each component study. This type of synthetic cohort is especially useful for aging research; it enables description of the long-term natural history of disease and novel investigations of earlier-life factors and mechanisms shaping health outcomes that typically manifest in older age, such as Alzheimer’s disease and related dementias (ADRD). Purpose of Review We review current understanding of synthetic cohorts for life course research. We first discuss chief advantages of longitudinal synthetic cohorts, focusing on their utility for aging/ADRD research to concretize the discussion. We then summarize the conditions needed for valid inference in a synthetic cohort, depending on research goals. We end by highlighting key challenges to creating longitudinal synthetic cohorts and conducting life course research within them. Summary The idea of combining multiple data sources to investigate research questions that are not feasible to answer using a single cohort is gaining popularity in epidemiology. The use of longitudinal synthetic cohorts in applied research—and especially in ADRD research—has been limited, however, likely due to methodologic complexity. In particular, little guidance and few examples exist for the creation of a longitudinal synthetic cohort for causal research goals. While building synthetic cohorts requires much thought and care, it offers tremendous opportunity to address novel and critical scientific questions that could not be examined in a single study.

Pet Ownership and Family Involvement in Sports and Other Activities

ABSTRACT The impact that companion animals may have on adolescent engagement in sports and other activities is currently unclear. This study included participant data gathered from the Adolescent Brain Cognitive Development (ABCD) Study®, a longitudinal study of brain development and youth health outcomes in the United States (n = 8,489). This study aimed to clarify the extent to which companion animal type impacts family involvement in sports and other activities. Additionally, it is framed within the bioecological model of human development, which provides a useful framework for human–animal interaction researchers going forward. This study utilized multiple logistic and linear regressions in answering the research questions posed. The results indicate that, when adjusting for context- and person-level covariates, there does not appear to be a meaningful relationship between companion animal type and family involvement in sports and other activities, physical activity, or screen time. This study serves as a guidepost for human–animal interaction researchers as to the importance of including contextual variables in their studies before making claims regarding the impact of companion animals on youth, especially when details about the companion animal relationship are unavailable.

AI in business research

AbstractArtificial intelligence (AI) has emerged as a pivotal force in modern business transformation, garnering widespread attention from both practitioners and academics. With a notable exponential increase in AI‐related studies, we provide a research framework aiming to synthesize the existing literature on AI in the business field. We conduct a comprehensive review of AI research spanning from 2010 to 2023 in 25 leading business journals according to this review framework. Specifically, we review the literature from three research perspectives: (i) AI applications, (ii) human perceptions of AI, and (iii) AI behavior. We also identify five principal research questions and offer suggestions for future research directions.

Current Context in Brazil and in The State of Pará Regarding Studies on Electro-Electronic Waste Integrated Into Reverse Logistics: A Systematic Literature Review (SLR)

Objective: This study aims to contextualize the management of electronic waste (EW) in Brazil, with an emphasis on the state of Pará. It also seeks to identify the main environmental impacts and mitigating actions related to the inadequate disposal of this waste. Theoretical Framework: The research is based on concepts of sustainability and reverse logistics (RL) applied to the management of EWE, with a focus on mitigating environmental impacts and identifying actors responsible for implementing public policies. Method: The methodology adopted involves conducting a systematic literature review (SLR) in the Capes Periodicals database, covering publications from the last 10 years. Ten articles were selected for analysis, in addition to 4 articles specific to Pará. The analysis was guided by three research questions related to environmental impacts, mitigating actions and actors involved in RL. Results and Discussion: The main results indicate that the inadequate disposal of EW causes significant damage to the environment and human health. RL was identified as the main mitigating action, with the government being the most relevant actor in the implementation of public policies. Research Implications: This research contributes by providing a comparative overview between Brazil and Pará, offering support for improvements in EW management and sustainability policies. Originality/Value: The originality of the study lies in the comparative analysis of national and regional data, highlighting the relevance of public policies in the context of RL.