Research Gaps Research Articles

User-centric AI: evaluating the usability of generative AI applications through user reviews on app stores

This article presents a usability evaluation and comparison of generative AI applications through the analysis of user reviews from popular digital marketplaces, specifically Apple’s App Store and Google Play. The study aims to bridge the research gap in real-world usability assessments of generative AI tools. A total of 11,549 reviews were extracted and analyzed from January to March 2024 for five generative AI apps: ChatGPT, Bing AI, Microsoft Copilot, Gemini AI, and Da Vinci AI. The dataset has been made publicly available, allowing for further analysis by other researchers. The evaluation follows ISO 9241 usability standards, focusing on effectiveness, efficiency, and user satisfaction. This study is believed to be the first usability evaluation for generative AI applications using user reviews across digital marketplaces. The results show that ChatGPT achieved the highest compound usability scores among Android and iOS users, with scores of 0.504 and 0.462, respectively. Conversely, Gemini AI scored the lowest among Android apps at 0.016, and Da Vinci AI had the lowest among iOS apps at 0.275. Satisfaction scores were critical in usability assessments, with ChatGPT obtaining the highest rates of 0.590 for Android and 0.565 for iOS, while Gemini AI had the lowest satisfaction rate at −0.138 for Android users. The findings revealed usability issues related to ease of use, functionality, and reliability in generative AI tools, providing valuable insights from user opinions and feedback. Based on the analysis, actionable recommendations were proposed to enhance the usability of generative AI tools, aiming to address identified usability issues and improve the overall user experience. This study contributes to a deeper understanding of user experiences and offers valuable guidance for enhancing the usability of generative AI applications.

Human Factors Considerations in Artificial Intelligence Applications for Nuclear Power Plants

In recent years, there has been a wave of artificial intelligence (AI) technologies that offer to solve problems from shopping habits to mortgage approvals to critical systems operations. The rapidity of the development of these systems has led to both excitement and apprehension about the roles these systems should play in our modern societies. This paper focuses on the critical infrastructure industry, in general, and nuclear power generation, in particular, and seeks to scrutinize how we can leverage these novel technologies in human-centered ways to maintain or enhance the established high levels of reliability and resilience in these industries. First, we discuss the broader aspects of cognitive systems and activities that are critical to understanding the human-AI space. Then we explore different approaches to explainability in AI and the notions of trust. We then move on to discuss several human factors concepts and methods and how they can support the design of human-AI teams. We then explore recent research related to nuclear power that has been undertaken and evaluate the current industry and regulatory landscapes. Finally, we discuss identified research gaps and recommendations for solving these for the critical infrastructure space.

Characterization of drought propagation over the Tibetan Plateau

Study regionThis study was carried out on the Tibetan Plateau (TP), which contains multiple important ecosystems, is the source of many rivers in China, and is experiencing significant climate change. Study focusClarifying drought propagation characteristics is crucial for understanding the mechanism of drought development and benefiting drought mitigation and early warning schemes. However, there is currently a notable lack of research on droughts on the TP and drought propagation characteristics on the TP have yet to be investigated. In this study, we investigated drought propagation time, probability, threshold, and the climatic factors associated with drought development based on the copula probability model and correlation, Bayesian network, and attribution analyses, allowing us to fill current research gaps. New hydrological insights for the regionThe research framework proposed in this study effectively reflected the characteristics of drought propagation. Our results showed that seasonality and aridity controlled the propagation time from meteorological drought (MD) to agricultural drought (AD), i.e., the time was shortest in summer (2.311.0 months) and in the humid zone (2.37 months); the same pattern was found for the propagation of MD to hydrological drought (HD), with the propagation time being 2.33.0 months in summer and 2.36 months in humid zones. The propagation probability for both AD and HD generally increased synchronously with the severity of MD, and also exhibited seasonal patterns, with the highest probability values in summer (0.590.90 for AD and 0.510.82 for HD). The highest propagation thresholds were also found in summer (−1.68 to −1.09 for AD and −1.68 to −1.36 for HD). The trends of both propagation time and probability were significant, and the probability of HD exhibited significant downward trends (−0.074 to −0.030/decade) across the TP. Precipitation was the dominant factor controlling the development of drought in most cases; however, other climatic factors, such as maximum temperature, solar radiation, and specific humidity, contributed 14.0 %43.9 % of the variances of AD and HD.

Digital Storytelling for People With Cognitive Impairment Using Available Mobile Apps: Systematic Search in App Stores and Content Analysis.

Growing evidence suggests cognitive and social health benefits can be derived from digital storytelling for older adults with cognitive impairment. Digital storytelling apps offer the potential to serve as an on-demand, easy-to-access platform for enhancing cognitive abilities and promoting social well-being. Yet, despite the increasing quantity of such apps being available on the market, there is a gap in research investigating their quality. This app review aims to assess the digital storytelling apps available in the Chinese market and evaluate them in accordance with the Mobile Application Rating Scale (MARS). The goal was to identify key features and evaluate the overall quality in the context of cognitively impaired users. A systematic search was conducted in both the Google Play store (Google LLC) and iTunes store (Apple Inc), using English and Chinese keywords. Apps were chosen according to specific criteria that included features, including (but not limited to) memory capture, story saving, cue-based reminiscing, and the ability to share stories or memories with others. The MARS was used by 3 individual researchers to independently assess app quality across several domains, such as engagement, functionality, aesthetics, and information quality, for both Android and iOS apps. From an initial screening of 297 apps, only 9 (3%) met the criteria for detailed evaluation using MARS. The reviewed apps featured capture memory, save, reminisce, and share functions, which are critical in supporting cognitive functions and enhancing user engagement. The analysis revealed patterns in platform diversity and geographical distribution of developers, with apps available on both iOS and Android. Memoirs of Life and Memorize: Diaries, Memories, Notes, Ideas, Timelines, Categories (Fair Apps Mobile) had the highest mean MARS scores of 3.35, indicating strong engagement, functionality, and information quality, while the lowest score was 2.33. The overall mean score across all apps was only 3.03 (SD 0.60), highlighting significant variation, particularly in information quality. User feedback also showed considerable variability, ranging from 0 comments for apps such as Grand Storyteller (VarIT Inc) and PWI Storyteller (Project World Impact, LLC) to as many as 5361 comments for FamilySearch, which received extensive positive reviews. This wide range of user feedback underscores the importance of continuous improvement and user-centered design, particularly in enhancing information quality and content accuracy. The systematic search and evaluation highlight the diverse capabilities yet variable quality of digital storytelling apps available within the Chinese market, reflecting user experiences, satisfaction levels, and efficacy in supporting cognitively impaired users. While some apps excel in engagement and functionality, others need significant improvements in information quality and user interface design to better serve those with cognitive impairments. Future research is recommended to investigate regional limitations and features that would result in more inclusive and effective digital storytelling apps.

Regional variations in energy efficiency: Modifying China's industrial approaches to meet sustainability goals

China has devoted much attention to the “carbon peaking” and “carbon neutrality” objectives, the related research focuses on renewable energy, carbon removal, electrification, and hydrogen technologies. Yet, energy efficiency, especially in resource-based and older industrial cities continue to be a research gap in this regard. This study fills this research gap by assessing the role of China's national Industrial Transformation and Upgrade Demonstration Zones (ITUDZ) in energy conservation from 2010 to 2021. In this paper, applying the time-varying Difference-in-Differences (DID) method, we confirm that ITUDZ effectively decreases the energy utilization of these cities. These tests are reliable based on the results obtained above. Mechanism assessments show that the ITUDZ does so through enhancing green innovation and adjusting industrial patterns and that marketization enhances the energy-saving impacts. Geographical heteroscedasticity tests also show that the effects are significant for multi-urban areas and eastern China but weaker for central-western and single-urban city areas. Therefore, this study serves to add to the existing knowledge regarding place-based industrial policies and their contribution towards the realization of China's sustainable development agenda.

Targeted Development and Validation of Clinical Prediction Models in Secondary Care Settings: Opportunities and Challenges for Electronic Health Record Data.

Before deploying a clinical prediction model (CPM) in clinical practice, its performance needs to be demonstrated in the population of intended use. This is also called "targeted validation." Many CPMs developed in tertiary settings may be most useful in secondary care, where the patient case mix is broad and practitioners need to triage patients efficiently. However, since structured or rich datasets of sufficient quality from secondary to assess the performance of a CPM are scarce, a validation gap exists that hampers the implementation of CPMs in secondary care settings. In this viewpoint, we highlight the importance of targeted validation and the use of CPMs in secondary care settings and discuss the potential and challenges of using electronic health record (EHR) data to overcome the existing validation gap. The introduction of software applications for text mining of EHRs allows the generation of structured "big" datasets, but the imperfection of EHRs as a research database requires careful validation of data quality. When using EHR data for the development and validation of CPMs, in addition to widely accepted checklists, we propose considering three additional practical steps: (1) involve a local EHR expert (clinician or nurse) in the data extraction process, (2) perform validity checks on the generated datasets, and (3) provide metadata on how variables were constructed from EHRs. These steps help to generate EHR datasets that are statistically powerful, of sufficient quality and replicable, and enable targeted development and validation of CPMs in secondary care settings. This approach can fill a major gap in prediction modeling research and appropriately advance CPMs into clinical practice.

Research on the evaluation method for safety cognitive ability of workers in high-risk construction positions

PurposeSafety cognitive ability is a key factor influencing unsafe behavior. However, the existing achievements have not yet involved the division of the hierarchical relationship of factors influencing safety cognition and lack a quantitative evaluation system of safety cognitive ability. The purpose of this paper is to find out the deficiencies in the safety cognition of workers in high-risk construction positions and to provide practical suggestions for improving their safety cognitive ability and reducing unsafe behavior.Design/methodology/approachBased on the iceberg model, the factors influencing the safety cognitive ability of workers in high-risk construction positions and their hierarchical relationship were determined, and an evaluation index system consisting of four primary indicators and 20 secondary indicators was constructed. The game theory algorithm was used to optimize the subjective and objective weights of the indicators calculated by the sequential analysis method (G1) and the entropy weighting method (EWM) to obtain the optimal combination weight value. The Matlab software was used for cloud mapping and similarity calculation to determine the safety cognitive ability level of the object to be evaluated.FindingsThe research results indicate that the comprehensive level of safety cognitive ability of scaffolders in this construction project is at “Level III”, the fundamental factors and compliance factors are at “Level IV”, the auxiliary factors and driving factors are at “Level III”. This conclusion aligns with the situation learned from the previous field investigation, which validates the feasibility and scientificity of the proposed evaluation method.Research limitations/implicationsConsidering that the safety cognitive ability of construction workers is constantly changing, this study has not yet delved into the specific impacts of various influencing factors on the level of safety cognitive ability. Future research can utilize simulation software, such as MATLAB and Vensim, to construct dynamic simulation models that accurately simulate the changing rules of construction workers’ safety cognitive ability under the influence of different factors.Practical implicationsThis research broadens the application scope of the iceberg model, enriches the analysis model of the factors influencing the safety cognitive ability of workers in high-risk construction positions and provides a novel perspective for similar research. The safety cognitive ability evaluation method proposed in this paper can not only accurately evaluate the safety cognitive ability level of workers in high-risk positions such as scaffolders but also provide practical suggestions for improving the safety cognitive ability of workers, which is of great significance to improve the safety management level and reduce unsafe behavior in the construction field.Originality/valueThis research fills the research gap of workers in high-risk construction positions and the quantification of safety cognitive ability. The iceberg model is used to realize the hierarchical division of the factors influencing safety cognitive ability. Additionally, an evaluation method for the safety cognitive ability of workers in high-risk construction positions based on the game theory combination weighting method and cloud model is proposed, which realizes the quantitative evaluation of safety cognitive ability.

Green Light for Bidirectional Charging? Unveiling Grid Repercussions and Life Cycle Impacts

Bidirectional charging, such as Vehicle-to-Grid, is increasingly seen as a way to integrate the growing number of battery electric vehicles into the energy system. The electrical storage capacity can be enhanced by using electric vehicles as flexible storage units. However, large-scale applications of Vehicle-to-Grid may require significant expansion of distribution grids. Previous studies lack a comprehensive environmental assessment of related impacts. Contributing to this research gap, this article combines techno-economic grid simulations with scenario-based Life Cycle Assessments. The case study focuses on rural distribution grids in Southern Germany, projecting the repercussions of different charging scenarios by 2040. Besides a Vehicle-to-Grid scenario, a mixed scenario of Vehicle-to-Home, Vehicle-to-Grid, and direct charging is investigated. Results indicate that Vehicle-to-Grid charging increases grid impacts due to higher charging simultaneities and power losses, especially when following spot market prices. Despite these challenges, the secondary use of battery electric vehicles as storage units can offset adverse environmental effects. Bidirectional charging allows for higher use of volatile renewable energies and can accelerate their integration into the power system. When considering these diverse environmental effects, bidirectional charging scenarios show overall lower impacts on climate change per battery electric vehicle compared to direct charging. The insights provided are valuable for researchers, industry, utilities, and policymakers to understand the potential positive and negative impacts of large-scale battery electric vehicle integration. The article highlights the most influential parameters that should be considered before large-scale penetration.

Performance and economic analysis of various geothermal power plant systems: Case study for the Chingshui geothermal field in Taiwan

Geothermal power plants are a source of sustainable energy. However, their performance is influenced by various factors, including production temperature and well locations, and few studies have investigated the relationships between these factors. To address this research gap, the present study developed integrated models of a geothermal reservoir and a variety of power plant systems. By using COMSOL and MATLAB, we conducted simulations for the Chingshui geothermal field in Taiwan to investigate the performance and economic feasibility of five common types of geothermal power plant systems over their operational lifetime under different well configurations. The key findings of this investigation are as follows. First, the locations of production wells are a primary factor influencing production temperature. Constructing wells in low-permeability zones results in considerable increases in the pressure differential in the injection pump; thus, wells should not be constructed in such zones. Second, as system flow rate and well depth decrease, production temperature remains relatively stable, net power output decreases, and system efficiency increases. This efficiency increase is caused by decreases in pumping power requirements at lower flow rates and shallower well depths. Finally, among the investigated systems, the organic Rankine cycle system had the lowest electricity production cost and shortest payback period within the enthalpy range of 500–1000 kJ/kg. Double-flash (DF) and DF–binary systems are also viable options when the mass flow rate is 10–20 kg/s and the enthalpy is 700–800 kJ/kg. Overall, the results of this study offer valuable insights for the design of geothermal power plants, thereby contributing to the optimization of renewable energy systems.

Towards the integrated study of the dialogical self and agency to research personal change in education / Hacia el estudio integrado del yo dialógico y la agencia para investigar el cambio personal en educación

Dialogical and sociocultural perspectives propose the dialogical self and agency, respectively, as privileged constructs to account for the processes of personal change in education. However, the integrated study between both phenomena has rarely been addressed systematically in education to understand in greater depth how students and teachers construct their identity as learners and teachers. This special issue seeks to contribute to this research gap through the theoretical advances and empirical evidence presented by eight original articles. This introduction identifies the main contributions to education of the developments on the dialogical self and agency and, furthermore, defines the conceptual scopes and implications of their integration. Then, the structure of the special issue is described and a brief summary is presented of the content of the eight articles. Altogether, this issue is an invitation to capture and explain in more detail the originality, innovation and relative autonomy in the activity of students and teachers as they situate and position themselves and participate in educational practices.

Exploring emotional dynamics: Word count effects in Facebook posts by sports shoe brands

This study examines the impact of word count in Facebook posts on user engagement and emotional responses, focusing on sports shoe brands. It addresses a research gap concerning the effects of post length on various emotional aspects and engagement metrics within social media marketing. Data were collected from January 1, 2024, to January 30, 2024, covering posts from January 2013 to December 2023 on official Facebook pages of several sports shoe brands. After cleaning an initial 723 posts, 636 were analyzed using statistical methods and Python libraries. Eight emotional aspects—fear, anger, sadness, trust, anticipation, joy, disgust, and surprise—were examined in relation to post length. Mean reaction values and emotional aspects were compared before and during the COVID-19 period. A structured equation model (SEM) in AMOS assessed these relationships. The analysis revealed that longer posts positively influenced trust (β = 0.208, ρ < 0.001), anticipation (β = 0.095, ρ < 0.05), joy (β = 0.259, ρ < 0.001), and surprise (β = 0.072, ρ < 0.05), but did not significantly affect fear (β = 0.065, ρ = 0.089), sadness (β = 0.054, ρ = 0.155), or disgust (β = 0.072, ρ = 0.116). During COVID-19, increased trust and anticipation were noted, while sadness and anger decreased. This study highlights that longer Facebook posts can enhance engagement through increased trust, anticipation, joy, and surprise, offering valuable insights for optimizing social media content strategies.

Safety Landscape of Therapeutic Nanozymes and Future Research Directions.

Oxidative stress and inflammation are at the root of a multitude of diseases. Treatment of these conditions is often necessary but current standard therapies to fight excessive reactive oxygen species (ROS) and inflammation are often ineffective or complicated by substantial safety concerns. Nanozymes are emerging nanomaterials with intrinsic enzyme-like properties that hold great promise for effective cancer treatment, bacterial elimination, and anti-inflammatory/anti-oxidant therapy. While there is rapid progress in tailoring their catalytic activities as evidenced by the recent integration of single-atom catalysts (SACs) to create next-generation nanozymes with superior activity, selectivity, and stability, a better understanding and tuning of their safety profile is imperative for successful clinical translation. This review outlines the current applied safety assessment approaches and provides a comprehensive summary of the safety knowledge of therapeutic nanozymes. Overall, nanozymes so far show good in vitro and in vivo biocompatibility despite considerable differences in their composition and enzymatic activities. However, current safety investigations mostly cover a limited set of basic toxicological endpoints, which do not allow for a thorough and deep assessment. Ultimately, remaining research gaps that should be carefully addressed in future studies are highlighted, to optimize the safety profile of therapeutic nanozymes early in their pre-clinical development.

Gender-Related Preferences for Learning by Tinkering: Updated Research is Needed

Imagine you open a new application on your computer for the first time, and a help wizard appears on the screen. Do you follow the step-by-step tutorial, or do you dismiss it and tinker with the interface? Previous studies show that designing for both types of users yields a more gender-inclusive design. This paper explores the question: if those studies were based on participants born several technology-generations earlier, does this research need an update? Children now have greater access to smartphones and STEM outreach opportunities than before, which may have shifted girls’ technology learning preferences. This research found that most studies about gender and tinkering were conducted before 2006, revealing a research gap about younger generations. Future work could explore whether preferences to learn by process or by tinkering are still disproportionately represented in different genders. This work has implications for how human factors professionals design gender-inclusive products and training.

Strategic collaboration between domestic and foreign firms on production outsourcing processes: Insights from a developing economy Firm's perspective

Worldwide fragmentation of production stages enable the developed and developing economies' firms to gain from ‘foreign outsourcing collaboration (FOC)’. Literature indicates that the majority of studies on foreign outsourcing are based on the perspective of developed countries. Nevertheless, a meager amount of literature is available from the perspective of developing countries. This study bridges the research gap by employing field survey based data collected from 217 textile and apparel firms located in Faisalabad-Pakistan, for the fiscal year 2022. This study mainly examines the impact of: (i) investment in information technology (IT) on FOC in the production process; (ii) strategic integration of outsourcing policies on FOC in the production process; and (iii) strategic policy firms' adopted on FOC in the production process. SmartPLS 4 has been utilized to estimate the partial least square structural equation model. The results signify that investment and utilization of IT induce a higher level of firm performance by enhancing firms' efficiency and improving product quality. Moreover, FOC in production processes increases product quality whereas investment in IT attracts FOC in production processes. The study concludes by offering specific policy recommendations.

Identification of research gaps to improve care for healthy ageing: a scoping review

ObjectiveSeveral research gaps affect the improvement of care for healthy ageing. Their identification is crucial to developing a specific research prioritisation agenda supporting progress at the micro (clinical), meso (service...

Exogenous Opioids and the Human Endocrine System: An Endocrine Society Scientific Statement.

The use and misuse of opioids are a growing global problem. Although the effects of these drugs on the human endocrine system have been studied for decades, attention on their related clinical consequences, particularly on the hypothalamic-pituitary system and bone health, has intensified over recent years. This Statement appraises research data related to the impact of opioids on the gonadal and adrenal function. Whereas hypogonadism is well recognized as a side effect of opioids, the significance of their inhibitory actions on the hypothalamic-pituitary-adrenal system and the occurrence of clinically relevant adrenal insufficiency is not fully elucidated. The often-inconsistent results of studies investigating how opioids affect the secretion of GH, prolactin, arginine vasopressin, and oxytocin are assessed. The accumulating evidence of opioid actions on bone metabolism and their negative sequelae on bone mineral density and risk of fracture are also reviewed. In each section, available data on diagnostic and management approaches for opioid endocrine sequelae are described. This Statement highlights a plethora of gaps in research associated with the effects and clinical consequences of opioids on the endocrine system. It is anticipated that addressing these gaps will improve the care of people using or misusing opioids worldwide. The Statement is not intended to serve as a guideline or dictate treatment decisions.

18 Past and current care practices for neonates with complex medical needs: A scoping review to support clinical program evaluation

Abstract Background Neonates with complex medical needs (NCMN) are a rapidly growing patient population internationally. Although NCMN are a relatively small proportion of all Neonatal Intensive Care Unit (NICU) admissions, they are high healthcare utilizers. Since 2018, a dedicated Neonatal Complex Care Team (NCCT) has cared for NCMN at a large quaternary care center. The NCCT cares for NCMN in a dedicated, single-family room, patient area within the NICU. This model of care has yet to be evaluated for its potential impact on healthcare outcomes. Objectives The objective of the scoping review is to determine the breadth of available literature on the care practices for the management of NCMN and to collate the available evidence to define outcome measures to be used in a formal program evaluation. Design/Methods The review followed the PRISMA extension for scoping reviews and utilized resources from the Joanna Briggs Institute. The two databases that were utilized include Medline via OVID and CINAHL. The dates for included publications are January 1st 1993, until July 15th 2023. Only studies published in English and primary research were included. Two independent reviewers performed the initial title and abstract screening, and the full text review. The data extraction was completed by one independent reviewer. Results 102 articles were included in the title and abstract screen, and 12 were considered for full text review. Four articles were included. Interventions discussed in the included articles ranged from discharge conferences with patient’s caregivers, to the implementation of an entirely new model of care. Multidisciplinary health care teams appear to be integral to the in-hospital care and smooth discharge of NCMN. We identified that caregiver involvement and satisfaction are important to the discharge process as they are primarily responsible for their infant’s care after discharge, and so it is important that the specifics of care are communicated and taught effectively. The outcomes of interest identified as most useful for clinical program evaluation were length of stay and readmission rate. Additionally there was limited data reported on long-term health outcomes of this patient population. Conclusion This scoping review identified few articles that reported new models of care, a lack of consistent outcomes used in evaluating existing care models and overall a gap in research in this rapidly growing patient population. There is more work to be done to improve care of NCMN and our findings will be used in designing future studies that evaluate care models.

From Analogue to Algorithm: The Metamorphosis of Music Production Techniques—An Integrated Literature Review

This research explores the transformation of music production (MP) from traditional to smart digital approaches. The background of the study is rooted in the rapid digital advancements in MP over the last few decades, leading to a more robust and compact MP progression. The research focuses on understanding the music industry’s process and the impact of technology on MP, particularly artificial intelligence (AI). The research methodology employed is an Integrative Literature Review, based on both Scopus and Web of Science databases. After thoroughly examining titles and abstracts, 745 documents were identified as bibliographic data. From these, 40 selected articles were synthesised and analysed to identify patterns, influential authors, prominent journals and countries, dominant intellectual themes in MP, literature clustering and research gaps. The study classifies MP into four clusters: humanistic, technological, social and cultural and industrial perspectives. Each lens offers a unique vantage point to understand the intricate tapestry of the musical landscape. The findings reveal that AI has revolutionised MP, contributing to the creation of novel sounds, genres and music arrangements. It has also facilitated cross-cultural collaborations and reshaped the music business model. These findings imply that the intersection of technology and the music industry has transformed music creation, consumption and monetisation, presenting both challenges and opportunities for stakeholders. The study concludes that the future of MP is a captivating fusion of human creativity and technological prowess, where tradition and innovation coalesce to propel musical revolution to new heights.

Correction: Superb microvascular imaging in tumour detection: global trends and research gaps

Correction: Superb microvascular imaging in tumour detection: global trends and research gaps

How mature is requirements engineering for AI-based systems? A systematic mapping study on practices, challenges, and future research directions

AbstractArtificial intelligence (AI) permeates all fields of life, which resulted in new challenges in requirements engineering for artificial intelligence (RE4AI), e.g., the difficulty in specifying and validating requirements for AI or considering new quality requirements due to emerging ethical implications. It is currently unclear if existing RE methods are sufficient or if new ones are needed to address these challenges. Therefore, our goal is to provide a comprehensive overview of RE4AI to researchers and practitioners. What has been achieved so far, i.e., what practices are available, and what research gaps and challenges still need to be addressed? To achieve this, we conducted a systematic mapping study combining query string search and extensive snowballing. The extracted data was aggregated, and results were synthesized using thematic analysis. Our selection process led to the inclusion of 126 primary studies. Existing RE4AI research focuses mainly on requirements analysis and elicitation, with most practices applied in these areas. Furthermore, we identified requirements specification, explainability, and the gap between machine learning engineers and end-users as the most prevalent challenges, along with a few others. Additionally, we proposed seven potential research directions to address these challenges. Practitioners can use our results to identify and select suitable RE methods for working on their AI-based systems, while researchers can build on the identified gaps and research directions to push the field forward.