Rigorous Method Research Articles

Understanding how Artificial Intelligence Affects Leadership: Exploring Opportunities and Challenges through Bibliometrics

The aim of the article is to identify opportunities and challenges in the specialized literature regarding the impact of artificial intelligence on leadership. The work is based on a bibliometric analysis of papers published on the Scopus platform in 2019-2023 and was conducted starting from an advanced search using the keywords „artificial intelligence”, „AI”, „leader”, „digital” and „leadership”. We started from the research question: What is the situation regarding the specialized literature on how artificial intelligence affects leadership? To answer this question, we proposed the following objectives: identifying the number of publications regarding the impact of artificial intelligence on leadership, determining the evolution of the number of publications, establishing the most common types of published works, highlighting bibliometric maps with the opportunities and challenges regarding the effects of AI on leadership. The bibliometric analysis served as a rigorous and objective method to understand how artificial intelligence affects leadership. This analysis was conducted in December 2023, using Microsoft Excel for graphical representations and the VOSviewer for visualizing the connections between the representative keywords of the selected articles. The main findings refer to the fact that the article sheds light on the opportunities and challenges arising from the integration of AI into management practices, thus providing valuable insights for the development of relevant strategies and policies in organizational contexts.

A case study of a bispecific antibody manufacturability assessment and optimization during discovery stage and its implications.

The manufacturability assessment and optimization of bispecific antibodies (bsAbs) during the discovery stage are crucial for the success of the drug development process, impacting the speed and cost of advancing such therapeutics to the Investigational New Drug (IND) stage and ultimately to the market. The complexity of bsAbs creates challenges in employing effective evaluation methods to detect developability risks in early discovery stage, and poses difficulties in identifying the root causes and implementing subsequent engineering solutions. This study presents a case of engineering a bsAb that displayed a normal solution appearance during the discovery phase but underwent significant precipitation when subjected to agitation stress during 15L Chemistry, Manufacturing, and Control (CMC) production Leveraging analytical tools, structural analysis, in silico prediction, and wet-lab validations, the key molecular origins responsible for the observed precipitation were identified and addressed. Sequence engineering to reduce protein surface hydrophobicity and enhance conformational stability proved effective in resolving agitation-induced aggregation. The refined bsAb sequences enabled successful mass production in CMC department. The findings of this case study contribute to the understanding of the fundamental mechanism of agitation-induced aggregation and offer a potential protein engineering procedure for addressing similar issues in bsAb. Furthermore, this case study emphasizes the significance of a close partnership between Discovery and CMC teams. Integrating CMC's rigorous evaluation methods with Discovery's engineering capability can facilitate a streamlined development process for bsAb molecules.

Discovery of potent CSK inhibitors through integrated virtual screening and molecular dynamic simulation.

Oncogenic overexpression or activation of C-terminal Src kinase (CSK) has been shown to play an important role in triple-negative breast cancer (TNBC) progression, including tumor initiation, growth, metastasis, drug resistance. This revelation has pivoted the focus toward CSK as a potential target for novel treatments. However, until now, there are few inhibitors designed to target the CSK protein. Responding to this, our research has implemented a comprehensive virtual screening protocol. By integrating energy-based screening methods with AI-driven scoring functions, such as Attentive FP, and employing rigorous rescoring methods like Glide docking and molecular mechanics generalized Born surface area (MM/GBSA), we have systematically sought out inhibitors of CSK. This approach led to the discovery of a compound with a potent CSK inhibitory activity, reflected by an IC50 value of 1.6 nM under a homogeneous time-resolved fluorescence (HTRF) bioassay. Subsequently, molecule 2 exhibits strong growth inhibition of MD anderson - metastatic breast (MDA-MB) -231, Hs578T, and SUM159 cells, showing a level of growth inhibition comparable to that observed with dasatinib. Treatment with molecule 2 also induced significant G1 phase accumulation and cell apoptosis. Furthermore, we have explored the explicit binding interactions of the compound with CSK using molecular dynamics simulations, providing valuable insights into its mechanism of action.

Paradigm Conflict: Village Health Volunteers and Public Health in Thailand

Reformist doctors in Thailand have combined to create a primary health care system in rural areas in which village health volunteers play a major role. Consistent with the WHO whole-of-society approach, these doctors have envisaged a decentralised system that emphasises volunteers as community oriented, self-reliant agents of change. Our ethnographic research in Chiang Mai, Thailand, reveals that these ideals of village health volunteer empowerment have not been realised. Rather, village health volunteers have become entrapped in a hierarchical, top-down health bureaucracy that affords them limited deliberative agency. We argue that this predicament reveals a conflict of paradigms between, on the one hand, an idealised holistic, spiritual dimension of health with village health volunteers as dedicated, self-sacrificing agents of local communities and, on the other hand, the imperatives of state authoritarian interventions in the avian influenza and COVID-19 pandemics, including rigorous public health protocols and epidemiological methods.

Comparative study of some rigorous and approximate methods for calculating the energy loss straggling

Some exact and approximate methods commonly used to calculate corrections to the Bethe stopping formula are modified and adapted by the authors to the calculation of the energy loss straggling (ELS). An intercomparison is carried out for results of approaches developed in the present work. An excellent agreement obtained between the results for ELS, calculated with an exact method previously proposed by one of the authors and the results of the Lindhard–Sørensen method for moderate relativistic energies. It is shown that some modified by authors approximate methods for the ELS calculating have the higher accuracy than the conventional approximate method of Lijian−Qing−Zhengming (LQZ). So, in all the cases considered, the accuracy of the twice modified LQZ method in the ELS calculations is higher than the accuracy of the usual LQZ method. The velocity averages of the relative error for Z = 92–118 of LQZ varies from 0.08% to 0.33%, and of LQZm2 – from 0.03% to 0.09%. A thrice modified LQZ method was also suggested in this work. The average error of LQZm3 becomes lower than the average error of LQZ, starting from Z = 99, and lower than the error of LQZm2, starting from Z = 109. A number of shortened LQZ methods for the ELS calculating have been proposed and developed too.

Improving Micro-EDM Machining Efficiency for Titanium Alloy Fabrication with Advanced Coated Electrodes.

Enhancing the operational efficacy of electrical discharge machining (EDM) is crucial for achieving optimal results in various engineering materials. This study introduces an innovative solution-the use of coated electrodes-representing a significant advancement over current limitations. The choice of coating material is critical for micro-EDM performance, necessitating a thorough investigation of its impact. This research explores the application of different coating materials (AlCrN, TiN, and Carbon) on WC electrodes in micro-EDM processes specifically designed for Ti-6Al-4V. A comprehensive assessment was conducted, focusing on key quality indicators such as depth of cut (Z), tool wear rate (TWR), overcut (OVC), and post-machining surface quality. Through rigorous experimental methods, the study demonstrates substantial improvements in these quality parameters with coated electrodes. The results show significant enhancements, including increased Z, reduced TWR and OVC, and improved surface quality. This evidence underscores the effectiveness of coated electrodes in enhancing micro-EDM performance, marking a notable advancement in the precision and quality of Ti-6Al-4V machining processes. Among the evaluated coatings, AlCrN-coated electrodes exhibited the greatest increase in Z, the most significant reduction in TWR, and the best OVC performance compared to other coatings and the uncoated counterpart.

Defining the transition from new to normal: a qualitative investigation of the clinical change process.

Understanding how and when a new evidence-based clinical intervention becomes standard practice is crucial to ensure that healthcare is delivered in alignment with the most up-to-date knowledge. However, rigorous methods are needed to determine when a new clinical practice becomes normalized to the standard of care. To address this gap, this study qualitatively explores how, when, and why a clinical practice change becomes normalized within healthcare organizations. We used purposive sampling to recruit clinical leaders who worked in implementation science across diverse health contexts. Enrolled participants completed semi-structured interviews. Qualitative data analysis was guided by a modified version of the Normalization Process Theory (NPT) framework to identify salient themes. Identified normalization strategies were mapped to the Expert Recommendations for Implementation Change (ERIC) project. A total of 17 individuals were interviewed. Participants described four key signals for identifying when a novel clinical practice becomes the new normal: 1) integration into existing workflows; 2) scaling across the entire organizational unit; 3) staff buy-in and ownership; and 4) sustainment without ongoing monitoring. Participants identified salient strategies to normalize new clinical interventions: 1) taking a patient approach; 2) gaining staff buy-in and ownership; and 3) conducting ongoing measurement of progress towards normalization. The results offer valuable insight into the indicators that signify when a novel clinical practice becomes normalized, and the strategies employed to facilitate this transition. These findings can inform future research to develop instruments that implementation leaders can use to systematically measure the clinical change process.

An international interdisciplinary approach to developing video educational materials promoting mental health literacy among adolescents in the Philippines.

Adolescent mental ill-health is a common international challenge affecting both high- and lower-middle-income countries. The Republic of the Philippines enacted its first mental health law in 2019, underlining the importance of the promotion of adolescent mental health education in schools. In Japan, course instructions about mental ill-health were formulated in a Course of Study that reflects governmental curriculum guidelines. Embedded since 2022, the Course of Study aimed to promote an understanding of current issues of adolescent health. The National Center for Global Health and Medicine in Japan has been sharing experience of promoting public health practices and advancing medical technology in low- and middle-income countries, especially in the Western Pacific region. This paper describes the development process and content of these resources by an interdisciplinary team from Japan and the Philippines. The interdisciplinary team created an embedded mental health education programme using animated videos for the Philippine school curriculum to improve mental health literacy in adolescents. Two six-minute animated videos of age-relevant stories were created. The animation scenarios illustrate: 1) mental health problems and recovery; and 2) major symptoms of mental illnesses, including depression, anxiety, and schizophrenia. Each animated video presents several items for discussion among students and/or teachers, both in class and online for students unable to attend school. Our efforts may provide good opportunities for enhancing adolescents' mental health activities in the Philippines. In the following steps, we should investigate the effectiveness of school-based MHL using these animated videos with rigorous evaluation methods.

VIRTSI: A novel trust dynamics model enhancing Artificial Intelligence collaboration with human users – Insights from a ChatGPT evaluation study

The rapid integration of intelligent processes and methods into information systems in the Artificial Intelligence (AI) era has led to a substantial shift towards autonomous software decision-making. This evolution necessitates robust human oversight, especially in critical domains like Healthcare, Education, and Energy. Human trust in AI plays a vital role in influencing decision-making processes of users interacting with AI.This paper presents VIRTSI (Variability and Impact of Reciprocal Trust States towards Intelligent systems), a novel rigorous computational model for human-AI Interaction. VIRTSI simulates human trust states, spanning from overtrust to distrust, through user modelling. It comprises: 1. A trust dynamics representational model based on Deterministic Finite State Automata (DFAs), illustrating transitions among cognitive trust states in response to AI-generated replies. 2. A trust evaluation model based on Confusion Matrices, originating from machine learning and Accuracy Metrics, providing a quantitative framework for analysing human trust dynamics. As a result, this is the first time that trust dynamics have been thoroughly traced in a representational model and a method has been developed to assess the impact of possibly harmful states like overtrust and distrust.An empirical study on the recently launched Large Language Model of generative AI, ChatGPT (version 3.5), provides a radical underexplored AI-generated platform for evaluating the human-AI interaction through VIRTSI. The study involved 1200 interactions of real users as well as AI experts together with experts in two very different domains of evaluation, namely software engineering and poetry. This study traces trust dynamics and the emerging human-AI interaction, in concrete examples of real user synergies with generative AI. The research reveals the vital role of maintaining normal trust states for optimal human-AI interaction and that both AI and human users need further steps towards this goal. The real-world implications of this research can guide the creation and evaluation of user interfaces with AI and the incorporation of functionalities in the development of generative AI chatbots in terms of trust by providing a new rigorous DFA representational method of trust dynamics and a corresponding new perspective of confusion matrix evaluation method of the dynamics’ impact in the efficiency of human-AI dialogues.

PROTOCOL: Abortion and mental health outcomes: A systematic review and meta-analysis.

This is a protocol for a systematic review and meta-analysis of research on mental health outcomes of abortion. Does abortion increase the risk of adverse mental health outcomes? That is the central question for this review. Our review aims to inform policy and practice by locating, critically appraising, and synthesizing empirical evidence on associations between abortion and subsequent mental health outcomes. Given the controversies surrounding this topic and the complex social, political, legal, and ideological contexts in which research and reviews on abortion are conducted, it is especially important to conduct this systematic review and meta-analysis with comprehensive, rigorous, unbiased, and transparent methods. We will include a variety of study designs to enhance understanding of studies' methodological strengths and weaknesses and to identify potential explanations for conflicting results. We will follow open science principles, providing access to our methods, measures, and results, and making data available for re-analysis.

Quantitative Structure‐Property Relations for Polyester Materials via Statistical Learning

AbstractStatistical learning is employed to present a principled framework for the establishment of quantitative structure‐property relationships (QSPR). Property predictions of industrial polymers formed by multiple reagents and at varying molecular weights are focused. A theoretical description of QSPR as well as a rigorous mathematical method is developed for the assimilation of experimental data. Results show that these methods can perform exceptionally well at establishing QSPR for glass transition temperature and intrinsic viscosity of polyesters.

Categorization of precipitation for predicting combined sewer overflows. Application to the City of Montréal

Combined sewer systems are widespread in America and Europe. They often face limitations in transport or treatment capacity, especially during heavy rain events or thaw periods, resulting in combined sewer overflows (CSOs). Predictive modeling for CSOs is essential in a risk management context, and some studies have presented methods to categorize precipitations based on their potential to generate overflows. However, the precipitation classification is usually based on a few characteristics, and its predictive power is limited. The objective of this study is to present a simple yet powerful method to categorize precipitation for predicting CSO occurrences. A prediction model, based on an optimized classification tree, is proposed to predict CSO occurrences as a function of publicly accessible precipitation data. We fit the model on 9 overflow outlets in Montréal city from 2013 to 2019 and use this model to predict CSOs in 2020. The results showed a very good predictive power of overflows, with a prediction rate of 89%, a sensitivity rate of 83%, and a specificity rate of 91%. The method is also more accurate than the 5-category classification currently used by the City of Montréal. The proposed method could be easily applied to another region where CSO data are available, providing a simple and rigorous method for predicting CSOs across urban drainage networks containing many overflow outlets.

Analysis of Soil Slope Stability under Underground Coal Seam Mining Using Improved Radial Movement Optimization with Lévy Flight

Underground coal seam mining significantly reduces the stability of slopes, especially soil slopes, and an accurate evaluation of the stability of soil slopes under underground mining conditions is crucial for mining safety. In this study, the impact of coal seam mining is considered as the additional horizontal and vertical stresses acting on the slope, and an equation for calculating the safety factor of soil slopes under underground mining conditions is derived based on the rigorous Janbu method. Then, the Improved Radial Movement Optimization (IRMO) algorithm is introduced and combined with Lévy flight optimization to conduct global optimization searches, obtaining the critical sliding surface and corresponding safety factor of the soil slope under underground coal seam mining. Through comparisons with the numerical simulation results in three different case studies, the feasibility of applying the IRMO algorithm with Lévy flight to analyze the stability of soil slopes under underground mining is demonstrated. This ensures the accuracy and stability of the calculation results while maintaining a high convergence efficiency. Furthermore, the effects of the mining thickness and mining direction on slope stability are analyzed, and the results indicate that a smaller mining thickness and mining along the slope are advantageous for slope stability. The method proposed in this study provides valuable insights for preventing the slope instability hazards caused by underground coal seam mining.

Authenticity and Dependability of The Volleyball Serve Precision Examination

Background: Assessing the precision of a volleyball overhead serve is essential for understanding players' skill levels and development. Existing methods may lack consistency and perceptiveness, warranting further investigation into a more reliable assessment tool. Objectives: This study aimed to scrutinize the substance, facade, perceptiveness, and consistency of a volleyball overhead serve for precision assessment. Specifically, it sought to evaluate the validity and reliability of the assessment tool across different skill levels, ranging from novice to experienced players. Method: To achieve these objectives, a multi-faceted approach was employed. Fifty-five volleyball mentors, instructors, and athletes participated in the facade validity examination, while six academic experts assessed the substance validity. Additionally, thirty-eight university students, comprising both seasoned and inexperienced players, were involved to gauge the test's capability to differentiate between performance tiers. Perceptiveness was evaluated by comparing disparities in service precision across skill levels using the t-test for independent samples. A hierarchical clustering analysis was conducted using the Euclidean quadratic distance metric and the among-groups linkage method. Furthermore, the consistency of repeated testing was analyzed using standard error and intraclass correlation coefficients. Result: The study yielded promising results regarding the validity, reliability, and perceptiveness of the volleyball overhead serve precision assessment. Facade validity demonstrated high agreement among participants, with consensus ranging from 81% to 88%. The test's substance validity and reliability were strong, as shown by good results in the evaluations by academic experts and high intraclass correlation coefficients for repeated testing (ICC = 0.85 for experienced participants and ICC = 0.82 for novices). Significant differences in performance were observed between experienced and novice players, further affirming the tool's ability to differentiate skill levels effectively. Conclusion: The volleyball serves precision assessment emerged as a reliable and valid tool for evaluating players' performance across different skill levels. Its ability to discern skill nuances and provide consistent results makes it suitable for educational contexts, particularly in assessing novice players' development and guiding instructional strategies. This study emphasizes the importance of rigorous assessment methods in improving volleyball skills comprehension and advancement.

Exploring Legal Dynamics in Contemporary Migration with a Focus on Refugee and Migrant Rights

The phenomenon of migration poses a pressing quandary within the context of the global legal framework, heightened by persistent political instability and the repercussions of climate change. These factors compel a significant populace to seek alternative habitats, where they encounter varying degrees of success in the process of societal integration. The purpose of the article was to explore the legal aspects of migration processes in the modern world viewed through the lens of delineating the rights of refugees and migrants. With the use of rigorous scientific methods such as content analysis and comparison, this study elucidated the fundamental aspects of the migration dilemma. It demonstrated that the development of sound migration policies is of paramount importance in navigating this complex terrain. While initial international resolutions made general declarations, contemporary conventions provide detailed frameworks that, alongside national laws, establish the foundation for the assimilation of non-citizens into host societies. It was demonstrated that the increase in the number of migrants and displaced persons has led to a more detailed legal framework. While the initial international resolutions, such as those from the United Nations, primarily took a declarative stance, contemporary conventions exhibit a significantly more detailed approach. In conjunction with the legal norms of individual nations, these modern frameworks establish the foundation for the assimilation of recently arrived non-citizens into their host society. The results pointed out that this process took place according to the scheme of considering international standards and conventions on the migrants' and refugees' rights protection, which become the basis for the development of relevant provisions of national legislation. Consequently, in order to address migration comprehensively, the findings underscored the need to promote inter-state legal cooperation. The global community can progress towards achieving a fairer and more sustainable resolution of migration challenges by embracing a framework centered on inter-state legal cooperation. In addition to highlighting the current state of the law, the study argued for the development of innovative solutions to address the complexity of migration in the interconnected world.

Analysis of three-dimensional slope stability combined with rainfall and earthquake

Abstract. In the current context of global climate change, geohazards such as earthquakes and extreme rainfall pose a serious threat to regional stability. We investigate a three-dimensional (3D) slope dynamic model under earthquake action, derive the calculation of seepage force and the normal stress expression of slip surface under seepage and earthquake, and propose a rigorous overall analysis method to solve the safety factor of slopes subjected to combined with rainfall and earthquake. The accuracy and reliability of the method is verified by two classical examples. Finally, the effects of soil permeability coefficient, porosity, and saturation on slope stability under rainfall in a project located in the Three Gorges Reservoir area are analyzed. The safety evolution of the slope combined with both rainfall and earthquake is also studied. The results indicate that porosity has a greater impact on the safety factor under rainfall conditions, while the influence of permeability coefficient and saturation is relatively small. With the increase of horizontal seismic coefficient, the safety factor of the slope decreases significantly. The influence of earthquake on slope stability is significantly greater than that of rainfall. The corresponding safety factor when the vertical seismic action is vertically downward is smaller than that when it is vertically upward. When considering both horizontal and vertical seismic effects, slope stability is lower.

Informing the recruitment crisis in policing: Evaluating which incentives can entice the best candidates among college students

AbstractResearch SummaryScrutiny over the quality of police work continues to increase, at the same time that a recruitment crisis may hinder policing services. Moreover, this crisis exists despite numerous work incentives for officers, which are potentially competitive salaries, early pensions, and legal protections. Using a sample of 604 undergraduate students—a natural recruiting pool for police agencies—this study explores the predictors of students’ interest in a career in policing. In addition, we conducted a randomized survey experiment to identify the effect of work incentives on students’ willingness to apply to be a police officer upon graduation. Specifically, we manipulated the starting salary, years of service until pension eligibility, and the protection afforded against lawsuits. Finally, we tested whether the effect of these incentives differs across the quality of applicants (i.e., grade point average [GPA], ability to pass existing application criteria, and subjective qualities that comprise honesty, teamwork, and compassion) and their preexisting interest in a career in policing. We found that students are generally uninterested in becoming police officers, particularly when their GPA is high. Though the starting salary was the most impactful of all incentives, some lawsuit protection is key for enticing the best students. In contrast, conditions for pension had only modest if any effects.Policy ImplicationsRecruiting is key to improving the quality of policing, particularly when many potential candidates are overlooking the career. However, research on the causes and consequences of police recruitment strategies is limited. This study implements rigorous research methods to investigate how to increase the pool of high‐quality applicants to police agencies. Findings support sensible and potentially cost‐effective policy decisions in regard to police recruiting, which should focus on increasing the starting salary, and on more effectively communicating the value of other existing benefits of the career that comprise lawsuit protection and attractive pension plans.

Benefits of Time Spent Outdoors in Early Childhood Education: A Systematic Review

Several studies have provided evidence that time spent in nature (i.e., in natural environments or the outdoors) plays a beneficial role in child development by positively influencing children’s cognitive processes and states (Bowler et al., 2010; Bratman et al., 2012; 2014; Cameron-Faulkner et al., 2018; Kaplan, 1995; Mitchell et al.). However, to date, no study has looked systematically at the overall literature addressing the benefits nature plays in early childhood education, primarily through outdoor learning or time spent outside in natural environments. The purpose of the current study is to provide a systematic review of the empirical literature evaluating outcomes linked to children spending time outdoors through outdoor play, forests, gardens, or school playgrounds. A systematic search of PsycINFO was conducted to identify critical studies linking the outdoors with outcomes during early childhood. Inclusion criteria were as follows: research studies conducted with children enrolled in early childhood education programs (age 2-5-year-olds) related to nature base experiences in the United States and peer-reviewed articles written in English. This search yielded 12 empirical studies. Codes were developed to examine a) what outcomes have been measured for children spending time outdoors in their early childhood education settings and b) what approaches were used to measure these outcomes. The two most measured outcomes included in studies were children’s behavior (N = 3; 25%) and educational or learning outcomes (N = 3; 25%). Most activities were child-led (N= 6, 50%) while children engaged in free-play (N = 5, 29%) and physical activities (N= 5, 29%). The most common method utilized was a quasi-experimental design (N=5, 29%), followed by secondary research designs (N=2, 16%). A few studies used rigorous methods to examine the links between children spending time outdoors and their specific beneficial outcomes. Implications for future research in this area are discussed.

A Hybrid Semi-Automated Workflow for Systematic and Literature Review Processes with Large Language Model Analysis

Systematic reviews (SRs) are a rigorous method for synthesizing empirical evidence to answer specific research questions. However, they are labor-intensive because of their collaborative nature, strict protocols, and typically large number of documents. Large language models (LLMs) and their applications such as gpt-4/ChatGPT have the potential to reduce the human workload of the SR process while maintaining accuracy. We propose a new hybrid methodology that combines the strengths of LLMs and humans using the ability of LLMs to summarize large bodies of text autonomously and extract key information. This is then used by a researcher to make inclusion/exclusion decisions quickly. This process replaces the typical manually performed title/abstract screening, full-text screening, and data extraction steps in an SR while keeping a human in the loop for quality control. We developed a semi-automated LLM-assisted (Gemini-Pro) workflow with a novel innovative prompt development strategy. This involves extracting three categories of information including identifier, verifier, and data field (IVD) from the formatted documents. We present a case study where our hybrid approach reduced errors compared with a human-only SR. The hybrid workflow improved the accuracy of the case study by identifying 6/390 (1.53%) articles that were misclassified by the human-only process. It also matched the human-only decisions completely regarding the rest of the 384 articles. Given the rapid advances in LLM technology, these results will undoubtedly improve over time.

Collaborative Skills Training Using Digital Tools: A Systematic Literature Review

The development of information and communication technologies has changed our way of working, emphasizing the need for individuals to develop collaborative skills. The aim of the present systematic review was to examine the extent to which these skills can be developed through the use of digital tools. A search of seven electronic databases, following PRISMA guidelines, yielded 18 relevant peer-reviewed articles. Analysis of the literature revealed that digital tools have the potential to enhance collaborative skills. However, the effects vary considerably, depending on which tools, methods, and measures are used. It also revealed that studies were conducted mainly in the social sciences, mostly among students, and half of them focused on short interventions. Another finding was that little is known about the features of the digital tools that actually contribute to these effects. Work on how digital tools contribute to the development of collaborative skills is still in its infancy, and more research based on rigorous methods and measures is needed.