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Fully Open Access Topical Journals

A Growing Collection of Gold Fully Open Access (OA) Options

IEEE offers more options than ever to authors with the launch of new gold fully open access journals spanning a wide range of technologies. These journals are significant additions to IEEE’s well-known and respected portfolio of fully open access journals. In addition, many of the journals featured here target an accelerated publication time frame of 10 weeks for most accepted papers to help get your research exposed faster. Visit the publication home page of each title for details.

The fully open access journals are accepting submissions. Please see each journal’s description below for more details. All of the titles are fully compliant with funder mandates including Plan S. All IEEE Open Access titles, current and new, will be hosted on the IEEE Xplore ® platform.

Call for Papers

Submit a paper to an ieee fully open access journal.

IEEE Open Journal of Antennas and Propagation

High-quality, peer reviewed research covering antennas, including analysis, design, development, measurement, standards, and testing; radiation, propagation, and the interaction of electromagnetic waves with discrete and continuous media.

This fully open access journal publishes high-quality, peer reviewed papers covering antennas, including analysis, design, development, measurement, standards, and testing; radiation, propagation, and the interaction of electromagnetic waves with discrete and continuous media; and applications and systems pertinent to antennas, propagation, and sensing, such as applied optics, millimeter-and sub-millimeter-wave techniques, antenna signal processing and control, radio astronomy, and propagation and radiation aspects of terrestrial and space-based communication, including wireless, mobile, satellite, and telecommunications at all frequencies. The journal peer-review process targets a publication period of 10 weeks from submission to online publication.

Editor-in-Chief: Konstantina (Nantia) Nikita Professor National Technical University of Athens, Greece

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Addresses the growing field of applications in Earth observations and remote sensing and provides a venue for the rapidly expanding special issues that are being sponsored by the IEEE Geosciences and Remote Sensing Society.

The IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing addresses the growing field of applications in Earth observations and remote sensing, and also provides a venue for the rapidly expanding special issues that are being sponsored by the IEEE Geosciences and Remote Sensing Society. The journal draws upon the experience of the highly successful “IEEE Transactions on Geoscience and Remote Sensing” and provide a complementary medium for the wide range of topics in applied earth observations. Papers should address current issues and techniques in applied remote and in situ sensing, their integration, and applied modeling and information creation for understanding the Earth. Applications are for the Earth, oceans and atmosphere. Topics can include observations, derived information such as forecast data, simulated information, data assimilation and Earth information techniques to address science and engineering issues of the Earth system. The technical content of papers must be both new and significant.

IEEE Open Journal of Circuits and Systems

Featuring high-quality peer reviewed research covering the theory, analysis, design, tools, and implementation of circuits and systems.

This fully open access journal publishes high-quality, peer-reviewed papers covering the theory, analysis, design, tools, and implementation of circuits and systems. This includes their theoretical foundations, applications, and architectures, as well as circuits and systems implementation of algorithms for signal and information processing. The journal peer-review process targets a publication period of 10 weeks from submission to online publication.

Editor-in-Chief: Gabriele Manganaro, Ph.D., FIEEE Technology Director Analog Devices, Inc., USA

IEEE Open Journal of the Communications Society

Featuring high-quality peer reviewed research covering science, technology, applications and standards for information organization, collection and transfer using electronic, optical and wireless channels and networks.

As a fully open access journal publishing high-quality peer reviewed papers,  IEEE Open Journal of the Communications Society  covers science, technology, applications and standards for information organization, collection and transfer using electronic, optical and wireless channels and networks, including but not limited to: Systems and network architecture, control and management; Protocols, software and middleware; Quality of service, reliability and security; Modulation, detection, coding, and signaling; Switching and routing; Mobile and portable communications; Terminals and other end-user devices; Networks for content distribution and distributed computing; and Communications-based distributed resources control. The journal peer-review process targets a publication period of 10 weeks from submission to online publication.

Editor-in-Chief: Octavia A. Dobre, Dipl.-Ing., Ph.D. Professor and Research Chair Memorial University, Canada

IEEE Open Journal of the Computer Society

Forum for rapid publication of open access articles describing high-impact results in all aspects of theory, design, practice, and application relating to computer and information processing science and technology.

The IEEE Open Journal of the Computer Society (OJ-CS) is a rigorously peer-reviewed forum for rapid publication of open access articles describing high-impact results in all areas of interest to the IEEE Computer Society. This new fully open access journal complements existing IEEE Computer Society publications by providing a rapid review cycle and a thorough review of technical articles. It is dedicated to publishing articles on the latest emerging topics and trends in all aspects of computing with a scope that encompasses all aspects of theory, design, practice, and application relating to computer and information processing science and technology. The journal peer-review process targets a publication period of 10 weeks from submission to online publication.

Editor-in-Chief: Dr. Song Guo Department of Computing The Hong Kong Polytechnic University

IEEE Open Journal of Control Systems

Publication of the IEEE Control Systems Society, this journal aims to publish high-quality papers on the theory, design, optimization, and applications of dynamic systems and control.

The IEEE Open Journal of Control Systems covers the theory, design, optimization, and applications of dynamic systems and control. The field integrates elements of sensing, communication, decision and actuation components, as relevant for the analysis, design and operation of dynamic systems and control. The systems considered include: technological, physical, biological, economic, organizational and other entities, and combinations thereof. The journal peer-review process targets a publication period of 10 weeks from submission to online publication.

Editor-in-Chief: Sonia Martínez University of California, San Diego United States

IEEE Data Descriptions

Now Accepting Submissions! This new publication is a peer-reviewed journal that publishes short articles on all aspects of data: data descriptors, data collections, and metadata.

IEEE Data Descriptions is a peer-reviewed journal that publishes short articles on all aspects of data: data descriptors, data collections, and metadata. Its overarching purpose is to promote publicly available datasets (open access or subscription-based access) in support of reproducible science while at the same time bringing insights into the associated dataset, data collection methods, and data quality. The metadata collected provides enhanced dataset discoverability and creates a foundation for future data science tools such as auto-discovery and mashups.

Datasets described in IEEE Data Descriptions must be findable, accessible, interoperable, and reusable. The dataset needs to be of a quality high enough that other researchers can use it for their research experimentation and have some permanence. Articles describing datasets must be comprehensive and follow the outlined sections listed in Author Information. The preference is for data to be stored within IEEE DataPort, however, IEEE Data Descriptions accepts submissions where data is stored at other persistent/permanent locations.

Editor-in-Chief: Stephen Makonin Simon Fraser University Vancouver, Canada

IEEE Journal of the Electron Devices Society

Featuring high quality research in the field of electron and ion devices ranging from fundamentals to applied research.

Featuring high-quality research in the field of electron and ion devices ranging from fundamentals to applied research, this journal provides authors an affordable outlet for rapid publishing and universal access, coupled with superior technical quality.

IEEE Open Journal of Engineering in Medicine and Biology

High-quality research covering the development and application of engineering concepts and methods to biology, medicine and health sciences.

As a fully open access journal publishing high-quality peer reviewed papers, IEEE Open Journal of Engineering in Medicine and Biology covers the development and application of engineering concepts and methods to biology, medicine and health sciences to provide effective solutions to biological, medical and healthcare problems. It encompasses the development of mathematical theories, physical, biological and chemical principles, computational models and algorithms, devices and systems for clinical, industrial and educational applications. The journal peer-review process targets a publication period of 10 weeks from submission to online publication.

Editor-in-Chief: Paolo Bonato Associate Professor Harvard University, USA

IEEE Journal on Exploratory Solid-State Computational Devices and Circuits

Multi-disciplinary research in solid-state circuits using exploratory materials and devices for novel energy efficient computation beyond standard CMOS (Complementary Metal Oxide Semiconductor) technology.

Multi-disciplinary research in solid-state circuits using exploratory materials and devices for novel energy efficient computation beyond standard CMOS (Complementary Metal Oxide Semiconductor) technology. Focus is on the exploration of materials, devices and computation circuits to enable Moore’s Law to continue for computation beyond a 10 to 15 year horizon (beyond end of the roadmap for CMOS technologies) with the associated density scaling and improvement in energy efficiency.

IEEE Open Journal on Immersive Displays

Now Accepting Submissions! New publication will be home to publications in display science and applications.

The IEEE Open Journal on Immersive Displays (OJID) will be home to publications in display science and applications. The field of displays is diverse, ranging from the science and engineering of materials and devices to their application in high definition, form-factor-independent displays featuring interactivity, virtual and augmented reality, and 3D content. Submissions on advanced fabrication processing, thin film active and passive devices, and lifetime and reliability evaluation are welcome when display is the focus or where there is a direct relationship to the nature of the display system. Tutorial and review papers extending the frontiers of immersive display technologies and novel applications are also published.

Editor-in-Chief: Arokia Nathan University of Cambridge Hertfordshire, U.K.

IEEE Journal of Indoor and Seamless Positioning and Navigation

Publishes original research in the fields of localization and tracking of people, robots, and objects.

IEEE Journal of Indoor and Seamless Positioning and Navigation (J-ISPIN) publishes original research in the fields of localization and tracking of people, robots, and objects. It covers all aspects of localization systems, including sensing, communications, location-based services, mapping, protocols, human interfaces and standards. The scope includes methods and systems addressing indoor environments as well as those enabling seamless transition between heterogeneous indoor contexts or between indoor and outdoor environments, for example where Global Navigation Satellites Systems are underperforming or unavailable.

Editor-in-Chief: Valérie Renaudin Senior Researcher University Gustave Eiffel, France

IEEE Open Journal of the Industrial Electronics Society

Featuring high quality research covering the theory and applications of electronics, controls, communications, instrumentation and computational intelligence to industrial and manufacturing systems and processes.

This fully open access journal publishes high-quality, peer-reviewed papers covering the theory and applications of electronics, controls, communications, instrumentation and computational intelligence to industrial and manufacturing systems and processes. The journal peer-review process targets a publication period of 10 weeks from submission to online publication.

Editor-in-Chief: Dr. Leopoldo Garcia Franquelo Professor, Electronics Engineering Universidad de Sevilla, Spain

IEEE Open Journal of Industry Applications

Covering the advancement of the theory and practice of electrical and electronic engineering in the development, design, manufacture and application of electrical systems, apparatus, devices, and controls to the processes and equipment of industry and commerce.

As a fully open access journal publishing high-quality peer reviewed papers, IEEE Open Journal of Industry Applications covers the advancement of the theory and practice of electrical and electronic engineering in the development, design, manufacture and application of electrical systems, apparatus, devices, and controls to the processes and equipment of industry and commerce; the promotion of safe, reliable, and economic installations; industry leadership in energy conservation and environmental, health, and safety issues; the creation of voluntary engineering standards and recommended practices; and the professional development of its readers. The journal peer-review process targets a publication period of 10 weeks from submission to online publication.

Editor-in-Chief: Professor Pericle Zanchetta Fellow IEEE Faculty of Engineering University of Nottingham, UK

IEEE Open Journal of Instrumentation and Measurement

Publication of the Instrumentation and Measurement Society, this journal publishes papers on the science, technology, and application of instrumentation and measurement.

The IEEE Open Journal of Instrumentation and Measurement publishes papers on the science, technology, and application of instrumentation and measurement. Instrumentation and measurement, in the current context of the IEEE IMS community, consists of methods, instruments, systems, and applications for measurement, detection, tracking, monitoring, characterization, identification, sensing, estimation, recognition, or diagnosis of a physical phenomenon; or metrology and measurement theory including measurement uncertainty, instrument precision, calibration, etc.

Editor-in-Chief: Shervin Shirmohammadi University of Ottawa Canada

IEEE Open Journal of Intelligent Transportation Systems

Featuring high-quality research covering the theoretical, experimental and operational aspects of electrical and electronics engineering and information technologies as applied to Intelligent Transportation Systems (ITS).

As a fully open access journal publishing high-quality peer reviewed papers, IEEE Open Journal of Intelligent Transportation Systems covers theoretical, experimental and operational aspects of electrical and electronics engineering and information technologies as applied to Intelligent Transportation Systems (ITS), defined as those systems utilizing synergistic technologies and systems engineering concepts to develop and improve transportation systems of all kinds. The journal peer-review process targets a publication period of 10 weeks from submission to online publication.

Editor-in-Chief: Dr. Bart van Arem Full Professor of Transport Modelling Delft University of Technology, The Netherlands

IEEE Transactions on Machine Learning in Communications and Networking

Featuring high-quality manuscripts on advances in machine learning methods for and applications to communications and networking.

The IEEE Transactions on Machine Learning in Communications and Networking publishes high-quality manuscripts on advances in machine learning methods for and applications to communications and networking. Furthermore, articles developing novel communication and networking techniques for distributed machine learning algorithms are of interest. Both theoretical contributions (including new theories, techniques, concepts, algorithms, and analyses) and practical contributions (including system experiments, prototypes, and new applications) are encouraged.

Editor-in-Chief: Walid Saad Professor Virginia Tech Research Center – Arlington, USA

IEEE Journal of Microwaves

Covering articles on the theory, techniques and applications of guided wave and wireless technologies and spanning the electromagnetic spectrum from RF/microwave through millimeter-waves and terahertz.

The IEEE Journal of Microwaves is a fully open access publication covering the complete scope of the Microwave Theory and Techniques Society which includes articles on the theory, techniques and applications of guided wave and wireless technologies and spanning the electromagnetic spectrum from RF/microwave through millimeter-waves and terahertz, covering the aspects of materials, components, devices, circuits, modules, and systems which involve the generation, modulation, demodulation, control, transmission, sensing and effects of electromagnetic signals.

Editor-in-Chief: Peter H. Siege THz Global, NASA Jet Propulsion Laboratory, California Institute of Technology Pasadena, California

IEEE Open Journal of Nanotechnology

Featuring high-quality, peer reviewed research covering the theory, design, and development of nanotechnology and its scientific, engineering, and industrial applications.

As a fully open access journal publishing high-quality peer reviewed papers, IEEE Open Journal of Nanotechnology covers the theory, design, and development of nanotechnology and its scientific, engineering, and industrial applications. The journal peer-review process targets a publication period of 10 weeks from submission to online publication.

Co-Editors-in-Chief: Professor Wen J. Li Chair Professor of Biomedical Engineering Associate Provost City University of Hong Kong, Hong Kong

Professor Jin-Woo Kim Professor of Biological Engineering and Nanoscience & Engineering University of Arkansas, USA

Professor Seiji Samukawa Director of Innovative Energy Research Center, Institute of Fluid Science (IFS) Principal Investigator of Advance Institute for Materials Research (AIMR) Tohoku University, Japan

IEEE Transactions on Neural Systems and Rehabilitation Engineering

Covering the rehabilitative and neural aspects of biomedical engineering, including functional electrical stimulation, acoustic dynamics, human performance measurement, and more.

Rehabilitative and neural aspects of biomedical engineering, including functional electrical stimulation, acoustic dynamics, human performance measurement and analysis, nerve stimulation, electromyography, motor control and stimulation; and hardware and software applications for rehabilitation engineering and assistive devices.

IEEE Photonics Journal

Dedicated to the rapid disclosure of research at the forefront of all areas of photonics and addressing issues ranging from fundamental understanding to emerging technologies.

Breakthroughs in the generation of light and its control and utilization have given rise to the field of Photonics: a rapidly expanding area of science and technology with major technological and economic impact. IEEE Photonics Journal is an online-only journal dedicated to the rapid disclosure of top-quality peer-reviewed research at the forefront of all areas of photonics. Contributions addressing issues ranging from fundamental understanding to emerging technologies and applications are within the scope of the Journal.

IEEE Open Access Journal of Power and Energy

High-quality, peer reviewed research covering the development, planning, design, construction, maintenance, installation, and operation of equipment, structures, power systems and usage of electric energy, including its measurement and control.

As a fully open access journal publishing high-quality peer reviewed papers, the IEEE Open Access Journal of Power and Energy publishes articles focused on the development, planning, design, construction, maintenance, installation, and operation of equipment, structures, and power systems for the safe, sustainable, economic, and reliable conversion, generation, transmission, distribution, storage, and usage of electric energy, including its measurement and control. The journal peer-review process targets a publication period of 10 weeks from submission to online publication.

Editor-in-Chief: Fangxing “Fran” Li The University of Tennessee Knoxville, TN 37996 USA [email protected]

IEEE Open Journal of Power Electronics

Covering the development and application of power electronic systems and technologies, which encompass the effective use of electronic components, the application of circuit theory and design techniques and the development of analytical methods and tools.

The IEEE Open Journal of Power Electronics covers the development and application of power electronic systems and technologies, which encompass the effective use of electronic components, the application of circuit theory and design techniques and the development of analytical methods and tools toward efficient electronic conversion, control and conditioning of electric power to enable the sustainable use of energy. As a fully open access journal publishing high-quality peer reviewed papers, the Society’s aim is to publish novel developments as well as tutorial and survey articles including those of value to both the R&D and practicing professionals in the field. The journal peer-review process targets a publication period of 10 weeks from submission to online publication.

Editor-in-Chief: Alan Mantooth, Ph.D., P.E., FIEEE Distinguished Professor of Electrical Engineering University of Arkansas, USA

IEEE Transactions on Privacy

Now Accepting Submissions! New publication will provide a multidisciplinary forum for theoretical, methodological, engineering, and applications aspects of privacy and data protection, including specification, design, implementation, testing, and validation.

The IEEE Transactions on Privacy provides a multidisciplinary forum for theoretical, methodological, engineering, and applications aspects of privacy and data protection, including specification, design, implementation, testing, and validation. Privacy, in this context, is defined as the freedom from unauthorized intrusion in its broadest sense, arising from any activity in information collection, information processing, information dissemination or invasion. The transactions publishes articles reporting significant advances in theoretical models and formalization as well as engineering tools supporting the above activities, design frameworks and languages, architectures, infrastructures, model-based approaches, study cases, and standards.

IEEE Transactions on Quantum Engineering

Publishing regular, review, and tutorial articles based on the engineering applications of quantum phenomena, including quantum computation, information, communication, software, hardware, devices, and metrology.

Publishes regular, review, and tutorial articles based on the engineering applications of quantum phenomena, including quantum computation, information, communication, software, hardware, devices, and metrology. Articles also address quantum-engineering aspects of superconductivity, magnetics, microwave techniques, photonics, and signal processing.

IEEE Journal of Selected Areas in Sensors

Now Accepting Submissions! New publication of the IEEE Sensors Council, this journal publishes papers in all areas of the field of interest of the IEEE Sensors Council.

The IEEE Journal of Selected Areas in Sensors publishes papers in all areas of the field of interest of the IEEE Sensors Council, i.e., the theory, design, simulation, fabrication, manufacturing and application of devices for sensing and transducing physical, chemical, and biological phenomena, with emphasis on the electronics, physics and reliability aspects of sensors and integrated sensor-actuators. The Journal is built exclusively from papers on selected topics of current interest to the Sensors community.

Editor-in-Chief: Chonggang Wang InterDigital, Inc. USA

IEEE Open Journal of Signal Processing

High-quality, peer reviewed research covering the enabling technology for the generation, transformation, extraction, and interpretation of information.

This fully open access journal publishes high-quality, peer-reviewed papers covering the enabling technology for the generation, transformation, extraction, and interpretation of information. It comprises the theory, algorithms with associated architectures and implementations, and applications related to processing information contained in many different formats broadly designated as signals. Signal processing uses mathematical, statistical, computational, heuristic, and/or linguistic representations, formalisms, modeling techniques and algorithms for generating, transforming, transmitting, and learning from signals. The journal peer-review process targets a publication period of 10 weeks from submission to online publication.

Editor-in-Chief: Brendt Wohlberg Los Alamos National Laboratory, USA

IEEE Open Journal of the Solid-State Circuits Society

High-quality, peer reviewed research covering the design, implementation, and application of solid-state integrated circuits.

As a fully open access journal publishing high-quality peer reviewed papers, IEEE Open Journal of the Solid-State Circuits Society covers design, implementation and application of solid-state integrated circuits. The journal peer-review process targets a publication period of 10 weeks from submission to online publication.

Editor-in-Chief: Jan Craninckx Distinguished Member of Technical Staff IMEC, Belgium

IEEE Open Journal of Systems Engineering

Provides a forum for practitioners, scientists, academics, and researchers engaged in the discipline of Systems Engineering.

The IEEE Open Journal of Systems Engineering (OJSE) is an open access journal that is sponsored by the consortium of IEEE Aerospace and Electronic Systems Society, IEEE Systems, Man, and Cybernetics Society, and the IEEE Systems Council. OJSE provides a forum for practitioners, scientists, academics, and researchers engaged in the discipline of Systems Engineering. Multidisciplinary aspects of systems engineering is a focus of this journal. Methodologies, tools, principles, and applied engineering aspects of the process of systems engineering for complex systems are of interest. The methodologies, tools, and principles include such elements as model-based systems engineering; digital thread; requirements generation, flowdown, tracking, needs analysis, validation/verification; integration and test; and full life cycle of the target system. OJSE deals primarily with the science, methodology, and tools of systems engineering, rather than the results of the application of systems engineering that is the focus of other IEEE journals.

Editor-in-Chief: W. Dale Blair Principal Research Engineer Georgia Tech Research Institute, USA

IEEE Systems, Man, and Cybernetics Letters

Now Accepting Submissions! New publication of the IEEE Systems, Man, and Cybernetics Society (SMC), this journal covers the ultimate aims and key strategies of the SMC society towards the next generation of symbiotic human and machine intelligence systems.

IEEE Systems, Man, and Cybernetics Letter (SMC-L) will cover the ultimate aims and key strategies of the SMC society towards the next generation of symbiotic human and machine intelligence systems. The feature of SMC-L is highlighted by its rapid publication of peer-reviewed short articles within 5 pages, which provide a timely and concise account of innovative research ideas, novel application results, and significant theoretical findings, as well as analyses of emerging trends and groundbreakingly work in SMC fields. SMC-L will provide a new means for members and readers to complement established SMC transactions.

Editor-in-Chief: Prof. Yingxu Wang Editor-In-Chief Univ. of Calgary, Canada

IEEE Journal of Translational Engineering in Health and Medicine

Bridges the engineering and clinical worlds, focusing on detailed descriptions of advanced technical solutions to a clinical need along with clinical results and healthcare relevance.

This journal bridges the engineering and clinical worlds, focusing on detailed descriptions of advanced technical solutions to a clinical need along with clinical results and healthcare relevance. Its aim is to provide a platform for state-of-the-art technology directions in the interdisciplinary field of biomedical engineering, embracing engineering, life sciences and medicine. The journal provides an active forum for clinical research and relevant state-of-the-art technology for members of all the IEEE societies that have an interest in biomedical engineering as well as reaching out directly to physicians and the medical community through the American Medical Association (AMA) and other clinical societies.

IEEE Open Journal of Ultrasonics, Ferroelectrics, and Frequency Control

Covering high-quality, peer reviewed research theory, technology, materials, and applications relating to the generation, transmission, and detection of ultrasonic waves and related phenomena.

OJ-UFFC covers theory, technology, materials, and applications relating to: the generation, transmission, and detection of ultrasonic waves and related phenomena; medical ultrasound, and associated technologies; ferroelectric, piezoelectric, and piezomagnetic materials; frequency generation and control, timing, and time coordination and distribution. This interest ranges from fundamental studies to the design and/or applications of devices, sensors, systems and manufacturing technologies within the general scope defined above. The journal peer-review process targets a publication period of 10 weeks from submission to online publication.

Editor-in-Chief: Steven Freear University of Leeds, School of Electronic and Electrical Engineering Leeds, United Kingdom

IEEE Open Journal of Vehicular Technology

Featuring high-quality, peer reviewed research on the theoretical, experimental and operational aspects of electrical and electronics engineering in mobile radio, motor vehicles and land transportation.

This fully open access journal publishes high-quality, peer-reviewed papers covering the theoretical, experimental and operational aspects of electrical and electronics engineering in mobile radio, motor vehicles and land transportation. (a) Mobile radio shall include all terrestrial mobile services. (b) Motor vehicles shall include the components and systems and motive power for propulsion and auxiliary functions. (c) Land transportation shall include the components and systems used in both automated and non-automated facets of ground transport technology. The journal peer-review process targets a publication period of 10 weeks from submission to online publication.

Editor-in-Chief: Dr. Sumei Sun Fellow of the IEEE Principal Scientist, Institute for Infocomm Research Adjunct Professor, National University of Singapore, Singapore

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Web-Scale Datacenters

This issue of Internet Computing surveys issues surrounding Web-scale datacenters, particularly in the areas of cloud provisioning as well as networking optimization and configuration. They include workload isolation, recovery from transient server availability, network configuration, virtual networking, and content distribution.

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Networking for Big Data

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Special Issue on Big Data

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Discover research from IEEE Standards

Effect of Data Characteristics Inconsistency on Medium and Long-Term Runoff Forecasting by Machine Learning

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In the application of medium and long-term runoff forecasting, machine learning has some problems, such as high learning cost, limited computing cost, and difficulty in satisfying statistical data assumptions in some regions, leading to difficulty in popularization in the hydrology industry. In the case of a few data, it is one of the ways to solve the problem to analyze the data characteristics consistency. This paper analyzes the statistical hypothesis of machine learning and runoff data characteristics such as periodicity and mutation. Aiming at the effect of data characteristics inconsistency on three representative machine learning models (multiple linear regression, random forest, back propagation neural network), a simple correction/improvement method suitable for engineering was proposed. The model results were verified in the Danjiangkou area, China. The results show that the errors of the three models have the same distribution as the periodic characteristics of the runoff periods, and the correction/improvement based on periodicity and mutation characteristics can improve the forecasting accuracy of the three models. The back propagation neural network model is most sensitive to the data characteristics consistency.

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Efficiency Optimization Design That Considers Control of Interior Permanent Magnet Synchronous Motors Based on Machine Learning for Automotive Application

Interior permanent magnet synchronous motors have become widely used as traction motors in environmentally friendly vehicles. Interior permanent magnet synchronous motors have a high degree of design freedom and time-consuming finite element analysis is required for their characteristics analysis, which results in a long design period. Here, we propose a method for fast efficiency maximization design that uses a machine-learning-based surrogate model. The surrogate model predicts motor parameters and iron loss with the same accuracy as that of finite element analysis but in a much shorter time. Furthermore, using the current and speed conditions in addition to geometry information as input to the surrogate model enables design optimization that considers motor control. The proposed method completed multi-objective multi-constraint optimization for multi-dimensional geometric parameters, which is prohibitively time-consuming using finite element analysis, in a few hours. The proposed shapes reduced losses under a vehicle test cycle compared with the initial shape. The proposed method was applied to motors with three rotor topologies to verify its generality.

Published in the IEEE Vehicular Technology Society Section

An Intelligent IoT Sensing System for Rail Vehicle Running States Based on TinyML

Real-time identification of the running state is one of the key technologies for a smart rail vehicle. However, it is a challenge to accurately real-time sense the complex running states of the rail vehicle on an Internet-of-Things (IoT) edge device. Traditional systems usually upload a large amount of real-time data from the vehicle to the cloud for identification, which is laborious and inefficient. In this paper, an intelligent identification method for rail vehicle running state is proposed based on Tiny Machine Learning (TinyML) technology, and an IoT system is developed with small size and low energy consumption. The system uses a Micro-Electro-Mechanical System (MEMS) sensor to collect acceleration data for machine learning training. A neural network model for recognizing the running state of rail vehicles is built and trained by defining a machine learning running state classification model. The trained recognition model is deployed to the IoT edge device at the vehicle side, and an offset time window method is utilized for real-time state sensing. In addition, the sensing results are uploaded to the IoT server for visualization. The experiments on the subway vehicle showed that the system could identify six complex running states in real-time with over 99% accuracy using only one IoT microcontroller. The model with three axes converges faster than the model with one. The model recognition accuracy remained above 98% and 95%, under different installation positions on the rail vehicle and the zero-drift phenomenon of the MEMS acceleration sensor, respectively. The presented method and system can also be extended to edge-aware applications of equipment such as automobiles and ships.

Code Generation Using Machine Learning: A Systematic Review

Recently, machine learning (ML) methods have been used to create powerful language models for a broad range of natural language processing tasks. An important subset of this field is that of generating code of programming languages for automatic software development. This review provides a broad and detailed overview of studies for code generation using ML. We selected 37 publications indexed in arXiv and IEEE Xplore databases that train ML models on programming language data to generate code. The three paradigms of code generation we identified in these studies are description-to-code, code-to-description, and code-to-code. The most popular applications that work in these paradigms were found to be code generation from natural language descriptions, documentation generation, and automatic program repair, respectively. The most frequently used ML models in these studies include recurrent neural networks, transformers, and convolutional neural networks. Other neural network architectures, as well as non-neural techniques, were also observed. In this review, we have summarized the applications, models, datasets, results, limitations, and future work of 37 publications. Additionally, we include discussions on topics general to the literature reviewed. This includes comparing different model types, comparing tokenizers, the volume and quality of data used, and methods for evaluating synthesized code. Furthermore, we provide three suggestions for future work for code generation using ML.

Combining Citation Network Information and Text Similarity for Research Article Recommender Systems

Researchers often need to gather a comprehensive set of papers relevant to a focused topic, but this is often difficult and time-consuming using existing search methods. For example, keyword searching suffers from difficulties with synonyms and multiple meanings. While some automated research-paper recommender systems exist, these typically depend on either a researcher’s entire library or just a single paper, resulting in either a quite broad or a quite narrow search. With these issues in mind, we built a new research-paper recommender system that utilizes both citation information and textual similarity of abstracts to provide a highly focused set of relevant results. The input to this system is a set of one or more related papers, and our system searches for papers that are closely related to the entire set. This framework helps researchers gather a set of papers that are closely related to a particular topic of interest, and allows control over which cross-section of the literature is located. We show the effectiveness of this recommender system by using it to recreate the references of review papers. We also show its utility as a general similarity metric between scientific articles by performing unsupervised clustering on sets of scientific articles. We release an implementation, ExCiteSearch (bitbucket.org/mmmontemore/excitesearch), to allow researchers to apply this framework to locate relevant scientific articles.

Novel Multi Center and Threshold Ternary Pattern Based Method for Disease Detection Method Using Voice

Smart health is one of the most popular and important components of smart cities. It is a relatively new context-aware healthcare paradigm influenced by several fields of expertise, such as medical informatics, communications and electronics, bioengineering, ethics, to name a few. Smart health is used to improve healthcare by providing many services such as patient monitoring, early diagnosis of disease and so on. The artificial neural network (ANN), support vector machine (SVM) and deep learning models, especially the convolutional neural network (CNN), are the most commonly used machine learning approaches where they proved to be performance in most cases. Voice disorders are rapidly spreading especially with the development of medical diagnostic systems, although they are often underestimated. Smart health systems can be an easy and fast support to voice pathology detection. The identification of an algorithm that discriminates between pathological and healthy voices with more accuracy is needed to obtain a smart and precise mobile health system. The main contribution of this paper consists of proposing a multiclass-pathologic voice classification using a novel multileveled textural feature extraction with iterative feature selector. Our approach is a simple and efficient voice-based algorithm in which a multi-center and multi threshold based ternary pattern is used (MCMTTP). A more compact multileveled features are then obtained by sample-based discretization techniques and Neighborhood Component Analysis (NCA) is applied to select features iteratively. These features are finally integrated with MCMTTP to achieve an accurate voice-based features detection. Experimental results of six classifiers with three diagnostic diseases (frontal resection, cordectomy and spastic dysphonia) show that the fused features are more suitable for describing voice-based disease detection.

*Published in the IEEE Electronics Packaging Society Section within IEEE Access .

Machine Learning Empowered Spectrum Sharing in Intelligent Unmanned Swarm Communication Systems: Challenges, Requirements and Solutions

The unmanned swarm system (USS) has been seen as a promising technology, and will play an extremely important role in both the military and civilian fields such as military strikes, disaster relief and transportation business. As the “nerve center” of USS, the unmanned swarm communication system (USCS) provides the necessary information transmission medium so as to ensure the system stability and mission implementation. However, challenges caused by multiple tasks, distributed collaboration, high dynamics, ultra-dense and jamming threat make it hard for USCS to manage limited spectrum resources. To tackle with such problems, the machine learning (ML) empowered intelligent spectrum management technique is introduced in this paper. First, based on the challenges of the spectrum resource management in USCS, the requirement of spectrum sharing is analyzed from the perspective of spectrum collaboration and spectrum confrontation. We found that suitable multi-agent collaborative decision making is promising to realize effective spectrum sharing in both two perspectives. Therefore, a multi-agent learning framework is proposed which contains mobile-computing-assisted and distributed structures. Based on the framework, we provide case studies. Finally, future research directions are discussed.

Harnessing Artificial Intelligence Capabilities to Improve Cybersecurity

Cybersecurity is a fast-evolving discipline that is always in the news over the last decade, as the number of threats rises and cybercriminals constantly endeavor to stay a step ahead of law enforcement. Over the years, although the original motives for carrying out cyberattacks largely remain unchanged, cybercriminals have become increasingly sophisticated with their techniques. Traditional cybersecurity solutions are becoming inadequate at detecting and mitigating emerging cyberattacks. Advances in cryptographic and Artificial Intelligence (AI) techniques (in particular, machine learning and deep learning) show promise in enabling cybersecurity experts to counter the ever-evolving threat posed by adversaries. Here, we explore AI’s potential in improving cybersecurity solutions, by identifying both its strengths and weaknesses. We also discuss future research opportunities associated with the development of AI techniques in the cybersecurity field across a range of application domains.

A Study on the Elimination of Thermal Reflections

Recently, thermal cameras have been used in various surveillance and monitoring systems. In particular, in camera-based surveillance systems, algorithms are being developed for detecting and recognizing objects from images acquired in dark environments. However, it is difficult to detect and recognize an object due to the thermal reflections generated in the image obtained from a thermal camera. For example, thermal reflection often occurs on a structure or the floor near an object, similar to shadows or mirror reflections. In this case, the object and the areas of thermal reflection overlap or are connected to each other and are difficult to separate. Thermal reflection also occurs on nearby walls, which can be detected as artifacts when an object is not associated with this phenomenon. In addition, the size and pixel value of the thermal reflection area vary greatly depending on the material of the area and the environmental temperature. In this case, the patterns and pixel values of the thermal reflection and the object are similar to each other and difficult to differentiate. These problems reduce the accuracy of object detection and recognition methods. In addition, no studies have been conducted on the elimination of thermal reflection of objects under different environmental conditions. Therefore, to address these challenges, we propose a method of detecting reflections in thermal images based on deep learning and their elimination via post-processing. Experiments using a self-collected database (Dongguk thermal image database (DTh-DB), Dongguk items and vehicles database (DI&V-DB)) and an open database showed that the performance of the proposed method is superior compared to that of other state-of-the-art approaches.

Machine Learning Designs, Implementations and Techniques

Submission Deadline: 15 February 2020

IEEE Access invites manuscript submissions in the area of Machine Learning Designs, Implementations and Techniques.

Most modern machine learning research is devoted to improving the accuracy of prediction. However, less attention is paid to deployment of machine and deep learning systems, supervised /unsupervised techniques for mining healthcare data, and time series similarity and irregular temporal data analysis. Most deployments are in the cloud, with abundant and scalable resources, and a free choice of computation platform. However, with the advent of intelligent physical devices—such as intelligent robots or self-driven cars—the resources are more limited, and the latency may be strictly bounded.

To address these questions, the focus of this Special Section in IEEE Access is on machine and deep learning designs, implementations and techniques, including both system level topics and other research questions related to the general use and framework of machine learning algorithms.

The topics of interest include, but are not limited to:

• Real time implementation of machine and deep learning,
• System level implementation, considering full pipeline from raw data until the decision layer
• Novel and innovative applications with strong emphasis on design and implementation
• Novel approaches for Temporal / Spatial/Spatio-Temporal Association analysis
• Pattern discovery from Time stamped Temporal and Interval databases
• High performance data mining in cloud
• Novel approaches for handling Uncertain and Imbalanced data
• Supervised/Unsupervised techniques for mining healthcare data
• Deep learning for translational bio-informatics
• Periodic/Sequential pattern mining
• Evolutionary algorithms
• Privacy-Preserving Data mining
• Time series similarity and Irregular temporal data analysis
• Mining Text Web and Social network data
• Imputation techniques for Temporal data
• Causality and Event Processing
• Applications of Data Mining in Anomaly and Intrusion detection
• Applications to medical informatics

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor:  Shadi A. Aljawarneh, Jordan University of Science and Technology, Jordan

Guest Editors:

• Oguz Bayat, Altinbas University, Turkey
• Juan A. Lara, Madrid Open University, Udima, Spain
• Robert P. Schumaker, University of Texas at Tyler, USA

Relevant IEEE Access Special Sections:

• Visual Analysis for CPS Data
• Emerging Approaches to Cyber Security
• Data-Enabled Intelligence for Digital Health

IEEE Access Editor-in-Chief:   Prof. Derek Abbott, University of Adelaide

Article submission: Contact Associate Editor and submit manuscript to: http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact:  [email protected] , [email protected] .

At a Glance

• Journal: IEEE Access
• Format: Open Access
• Frequency: Continuous
• Submission to Publication: 4-6 weeks (typical)
• Topics: All topics in IEEE
• Average Acceptance Rate: 27%
• Impact Factor: 3.4
• Model: Binary Peer Review
• Article Processing Charge: US $1,995

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Academic Databases

ERIC research database: complete tutorial

The ERIC database is the premier education literature database for scholarly research. This guide covers search types and strategies, filters, and full text options.

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PubMed is the most popular search engine for biomedical sciences. Learn how to use PubMed, basic and advanced search strategies, and about its limitations and alternatives in this ultimate guide.

Is Google Scholar a database or search engine? [Update 2024]

Google Scholar is the number one free resource to discover scientific literature, but is it an academic database or a search engine?

The best academic research databases [Update 2024]

Your research is stuck and you need to find new sources? Take a look at our compilation of academic research databases: Scopus, Web of Science, PubMed, ERIC, JSTOR, DOAJ, Science Direct, and IEEE Xplore.

The best academic search engines [Update 2024]

Your research is stuck, and you need to find new sources. Take a look at our compilation of free academic search engines: ✓ Google Scholar ✓ BASE ✓ CORE ✓ Science.gov

The best research databases for computer science [Update 2024]

The top 4 research databases specifically dedicated to computer science: ✓ ACM Digital Library ✓ IEEE Xplore ✓ dbpl ✓ Springer LNCS

The best research databases for healthcare and medicine [Update 2024]

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Title: research on color recipe recommendation based on unstructured data using tenn.

Abstract: Recently, services and business models based on large language models, such as OpenAI Chatgpt, Google BARD, and Microsoft copilot, have been introduced, and the applications utilizing natural language processing with deep learning are increasing, and it is one of the natural language preprocessing methods. Conversion to machine language through tokenization and processing of unstructured data are increasing. Although algorithms that can understand and apply human language are becoming increasingly sophisticated, it is difficult to apply them to processes that rely on human emotions and senses in industries that still mainly deal with standardized data. In particular, in processes where brightness, saturation, and color information are essential, such as painting and injection molding, most small and medium-sized companies, excluding large corporations, rely on the tacit knowledge and sensibility of color mixers, and even customer companies often present non-standardized requirements. . In this paper, we proposed TENN to infer color recipe based on unstructured data with emotional natural language, and demonstrated it.

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Perceived challenges in treatment decision-making for endometriosis: healthcare professional perspectives

Lynda fallon.

a School of Psychological Sciences, Macquarie University, Sydney, Australia

b Lifespan Health and Wellbeing Research Centre, Sydney, Australia

Annie Y.S. Lau

c Australian Institute of Health Innovation, Macquarie University, Sydney, Australia

Donna Ciccia

d National Institute of Complementary Medicine (NICM), Health Research Institute, Western Sydney University, Sydney, Australia

e Endometriosis Australia, Sydney, Australia

Tanya Jane Duckworth

f School of Biomedicine, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, Australia

g School of Health Sciences, Faculty of Medicine and Health, University of Sydney, Sydney, Australia

Chantelle Pereira

Valentina perica, kerry a. sherman, associated data.

Due to the sensitivity of the data, it is not publicly available.

Background:

Endometriosis, a systemic chronic inflammatory condition which has no cure, has a high symptom burden that can negatively impact every facet of life. Given the absence of a gold-standard treatment, the best symptom management regimen in endometriosis is heavily reliant on a patient's values and preferences, making shared decision-making (SDM) vital. However, a comprehensive patient decision aid (PtDA) intervention that could facilitate patient decision-making and promote SDM is lacking in endometriosis, and there is little research on the decisional support needs of individuals with this condition. This qualitative study aimed to explore healthcare professional (HP) perspectives of their clients’ decisional support needs when choosing treatments to manage endometriosis symptoms, with a view to evaluating the need for a PtDA.

Australian HPs identified as specialising in endometriosis care ( N  = 13) were invited to participate in a short interview over the Internet by phone. Questions focussed on perceived facilitators and challenges of decision-making when choosing treatments for endometriosis. Transcribed qualitative data were thematically analysed and verified by multiple coders, using the template approach.

Four themes were identified: (1) Identifying and setting priorities; (2) HPs’ lack of time and perceived lack of knowledge; (3) Patient-centred care and SDM, including patient capacity; and (4) Decision-making blinded by hope. This is the first known study to explore HPs’ perspectives on patient decision-making challenges in endometriosis.

Discussion:

Findings draw attention to the difficulties people with endometriosis experience when assessing and choosing treatments, highlighting the need for a comprehensive PtDA intervention to support this decision-making.

Endometriosis is a chronic inflammatory disease affecting one in seven biological women of reproductive age in Australia (Australian Institute of Health and Welfare [AIHW], 2023 ; Rowlands et al., 2021 ). Symptoms, including severe and chronic pelvic pain, dysmenorrhea and dyspareunia, can be debilitating (Sivajohan et al., 2022 ), negatively impacting quality of life, social and personal relationships, work, education and sexual functioning (Calvi et al., 2024 ; Chapron et al., 2019 ; Sullivan-Myers et al., 2023 ). Psychosocial impacts of endometriosis include heightened levels of fatigue, stress, anxiety and depression (Sullivan-Myers et al., 2023 ; Gambadauro et al., 2019 ; Pope et al., 2015 ).

There is no cure for endometriosis. Treatments aiming to manage symptoms (O’Hara et al., 2022 ) include medications (e.g. NSAIDs, hormonal), surgery to remove endometriotic lesions or affected organs (e.g. hysterectomy) (Chapron et al., 2019 ), and psychotherapies, and allied health and complementary therapies (D’Alterio et al., 2022 ). However, there is no gold-standard treatment; all options offer differing advantages and disadvantages, and varying effectiveness, depending on the individual (Colón-Caraballo et al., 2019 ; Nirgianakis et al., 2021 ). Consequently, optimal endometriosis treatment amalgamates clinical characteristics and the patient's informed preferences regarding each option (Geukens et al., 2018 ; Llewellyn-Thomas & Crump, 2013 ).

The lack of a single definitive treatment plan for endometriosis makes it an ideal candidate for shared decision-making (SDM), the preferred approach for health-related decision-making when multiple legitimate options exist (Stacey et al., 2020 ), and in chronic conditions where decision-making is ongoing (Wieringa et al., 2019 ). Although studies report that SDM leads to optimal choices that are more likely to be actioned (Barry & Edgman-Levitan, 2012 ), across a range of healthcare contexts clinicians frequently do not use SDM (Stalnikowicz & Brezis, 2020 ), and consumers do not feel empowered to participate in the process (Joseph-Williams et al., 2014 ; Keij et al., 2021 ). Furthermore, people living with endometriosis (PLWE) report challenges in communicating with healthcare professionals (HPs) (Sherman et al., 2022 ), and feel dissatisfied with how their symptoms are managed (Evans et al., 2022 ), alone in making treatment decisions, and overwhelmed when trying to navigate options (Handelsman et al., 2023 ; Metzemaekers et al., 2021 ). This suggests they could benefit from support in making these important and complex decisions (Geukens et al., 2018 ; Vercellini et al., 2018 ). A robust evidence base across different health screening or treatment contexts demonstrates the effectiveness of patient decision aids (PtDAs) in enhancing patient knowledge about their condition and providing clarity on their personal values (Stacey et al., 2017 ). Importantly, PtDAs enhance communication between PLWE and clinicians, facilitating SDM (Wieringa et al., 2019 ).

Best practice for creating a PtDA requires a codesign process with input from both sides of SDM: PLWE and HPs (Coulter et al., 2013 ; Witteman et al., 2021a , 2021b ). However, clinicians’ perspectives on the support required by PLWE when deciding on endometriosis treatments have not been canvassed. This study aimed to address that gap by qualitatively exploring HP perspectives on the challenges faced by their PLWE clients when making decisions about endometriosis treatments, with a view to determining whether a PtDA could be helpful. Due to the exploratory nature of this study, semi-structured interviews were deemed the best data collection method (Adeoye-Olatunde & Olenik, 2021 ; Busetto et al., 2020 ).

This study aimed to ascertain HP perspectives on: (1) Whether PLWE feel they can fully participate in SDM when choosing treatments for their endometriosis; (2) Which aspects of endometriosis treatment decision-making PLWE find most difficult; and (3) Whether a PtDA could support and facilitate the decision-making process.

Materials and methods

Participants.

In an attempt to gather a diversity of viewpoints, Australian-based HPs specialising in endometriosis treatments and management, including medical, surgical, psychological, and complementary and allied health options, were identified through: Australian Government specialist pelvic pain clinics (Australian Government [Internet], 2023 ); endometriosis consumer support organisations (i.e. Endometriosis Australia, EndoZone); and the research team's networks. An email was sent to 63 HPs inviting them to a 15- to 20-minute phone or Zoom interview. Sixteen HPs agreed to participate, but three could not find a suitable time, leaving N  = 13: 3 obstetrician-gynaecologists, 5 specialist clinic staffers (3 general practitioners (GPs), 1 practice manager, 1 practice nurse), 2 allied HPs (psychologist, physiotherapist), and 3 complementary medicine HPs (dietitian, naturopath and wellness coach), representing major healthcare options for endometriosis symptom management (Becker et al., 2022 ; Kalaitzopoulos et al., 2021 ). The HPs had specialised in endometriosis care for between 4 and 30 years ( M  = 14.5 years). The sample size was deemed sufficient to explore the topic (Hennink et al., 2019 ), which was confirmed when no new codes were raised from interview 11 onwards (Silverman, 2014 ).

Two telephone and 11 Zoom interviews were conducted between May and October, 2023, with each lasting 14-49 min, depending on the HP. Participants provided verbal consent to record the interview with LF (a middle-aged female student trained in psychology), and were all asked the same set of iteratively designed open-ended questions (Supplementary Materials A) about their perceptions of treatment decision-making by their PLWE clients. Prior to any interviews, the question set was piloted by the research team, including two consumer investigators (DC and TD), who are trained researchers with lived experience of endometriosis and who are affiliated with peak consumer body Endometriosis Australia. The study was approved by an institutional human research ethics committee (Reference no: 520231301346445).

Data analysis

Recorded interviews were uploaded to Microsoft Word's Transcribe function for transcription, and the accuracy of the transcripts was checked against the recordings by LF, EK and VP. Transcribed data were de-identified before analysis, with each participant referred to by their profession. No HP took up the offer of checking the transcript of their interview.

The template approach was used to assess these data, because this inductive method of thematic analysis enables a flexibility which is ideally suited to exploratory research (Brooks et al., 2015 ). The steps were (1) Dataset familiarisation: LF and CP read the transcripts. (2) Generation of initial codes: LF and CP independently identified meaningful clusters of data to derive initial codes from the transcripts of the first six interviews. (3) Initial theme formation: Following comparison and mutual agreement on preliminary themes, LF and CP proceeded to code the remaining interviews. (4) LF examined the commonalities and distinctions among coded items, consolidating them before seeking feedback from CP. KS oversaw this process to ensure uniformity across codes and coders. (5) LF and CP iteratively consolidated the themes, resulting in a final coding template of four themes with two subthemes. At this stage the focus of each theme was honed, labels were assigned, and the researchers deliberated about how each addressed the research questions. (6) The written report used the themes to communicate the findings, accompanied by pertinent quotes from participants.

This research is reported according to COREQ guidelines (Tong et al., 2007 ). A critical realist ontological perspective guided this study (Fletcher, 2017 ), coupled with an interpretive approach (Olmos-Vega et al., 2023 ). Due to the sensitivity of the data, it is not publicly available.

Four themes were identified from these data analyses: Identifying and Setting Priorities (sub-theme: Stepwise Approach to Treatment); HPs’ Lack of Time and Perceived Lack of Knowledge; Patient-Centred Care and SDM (sub-theme: The Effect of Patient Capacity on Decision-Making); and Patient Decision-Making Blinded by Hope. Salient HP quotes illustrate each theme and sub-theme. In recognition of the wide range of treatments used to manage endometriosis symptoms (Leonardi et al., 2020 ), and of the key role practice managers/nurses and non-medical clinicians can play in helping to guide PLWE (Norton & Holloway, 2020 ), effort was made to include HPs from disparate health fields to canvas as wide a range of viewpoints as possible. However, there was remarkable consistency in participants’ responses, reflecting the unanimous views of this sample to strive for patient-centred care and the need for a multi-disciplinary approach to endometriosis symptom management. Although the focus of this study was HP perspectives on treatment decision-making in PLWE, interviews frequently organically included discussions about how participants approached care provision. These insights enriched understanding of possible ways to support the decision-making process for PLWE, and thus have been included. Additional quotes are provided in Supplementary Materials B.

Theme 1: identifying and setting priorities

HPs were almost unanimous about the need for PLWE to prioritise which symptoms they wanted addressed, and/or what outcomes they hoped to achieve:

I think it's important for [PLWE] to understand what the goal of their treatment is … then they can align their treatment strategies with what the goal is. (Allied HP)

One highlighted that it took time and HPs’ guidance for PLWE to realise they had multiple goals:

All of [the PLWE clients] have at least 6 to 8 problems that they present with, and … [at the end of the consultation] they say, ‘OK, these are totally my goals, but I didn't know I had so many’. Part of it is that they have so many things on their mind … they get so overwhelmed that they don't even know where to start. (Specialist clinic manager)

Another clinician noted that for some PLWE, their goals precluded certain treatments:

Unfortunately, all the medical management things we have are contraceptives, essentially. So if your goal is to fall pregnant, then you're much more limited in what we can do to treat you. (Obstetrician-gynaecologist)

When working on goals, one HP stressed the importance of helping PLWE to take a longer-term view:

They have a working life, and their condition is getting in the way … so they choose a management option that maximises their ability to work. They don't think about that they won't always have such a high value on their working life. So their values can be changeable, but they don't realise it … they're not used to thinking about themselves in that way. (Complementary medicine practitioner)

One HP indicated that their clients wanted symptoms to be treated concurrently, rather than prioritising certain goals:

[My clients] feel like it minimises what's happening for them, that ‘actually, endo isn't just about one symptom, and I can't just pick one that I would want to treat well and have to put up with the rest’. (Allied HP)

Sub-theme 1a: stepwise approach to treatment

Starting with the most conservative, least invasive treatment that might address symptoms (i.e. nonsteroidal painkillers) before trying hormonal medications or surgery was a popular protocol among HPs in this study. One noted this approach was perceived as being palatable to PLWE:

The simpler and cheaper and more available and less problematic the intervention is, the more likely you are to have people take it up. (GP)

Another compelling reason to try new treatments sequentially was to enable PLWE to pinpoint what was responsible for any change in symptoms:

Do one thing at a time to make sure that we know that if there's a change it's because of this, not because of the myriad possible things. (Complementary HP)

For one obstetrician-gynaecologist, three months of medical management coupled with allied and complementary health services was generally ‘a way to minimise the surgery that people are getting'. Unfortunately, this stepwise approach was sometimes at odds with patient expectations, as explained by this HP:

I think [PLWE] have an idea in their head that they put up with things for as long as they can and then when they can't, the next option is surgery … they feel in their head like ‘I’ve waited … I’ve tried all these different things, now I need surgery’. So they feel a little bit frustrated if that's the start of a very long journey for them to actually access surgery. (GP)

Several HPs reported that some PLWE were reluctant to consider treatment options other than surgery.

Theme 2: HPs’ lack of time and perceived lack of knowledge

Every HP participant in this study specialised in endometriosis and its management, but many cited a lack of up-to-date knowledge about endometriosis as a concern across the general medical community:

Unfortunately, [PLWE] need to get a whole pile of education first so they can sort of almost interrogate the doctor. I’m somewhat ashamed to think that my profession is such that [PLWE] have to educate themselves before they come and see the doctors. (Obstetrician-gynaecologist)

HPs acknowledged this perceived lack of quality information from clinicians led to PLWE turning to social media communities for support and information, but reported that these communities could be a double-edged sword. On the positive side, reading about others’ experiences and connecting with fellow PLWE provided great support:

I think it normalises their symptoms, or it makes them feel like they’re not the only one. Facebook group forums … sometimes have more of an impact on what [PLWE] want than the people closest to them. (Obstetrician-gynaecologist)

However, concerns were raised about the sometimes negative skew of social media affecting people psychologically and physically:

There can be a negative spiral in some of those conversations … Anger doesn’t help pain, and pain is the main problem with endo. (Allied HP)

Furthermore, it was stated that popular overseas-based sites could mislead PLWE:

[Overseas website] doesn’t reflect the state of care that we receive in Australia or New Zealand … then we have a situation where people think that they’re getting sub-adequate care because they can’t access this [overseas] style of endometriosis surgery … to me it’s scaremongering. (Specialist practice nurse)

A lack of time in consultations was cited as a barrier to collaborative decision-making, with one GP criticising the public health system for financially rewarding shorter consultations over the longer appointments required for optimal SDM in a complex chronic condition like endometriosis:

[Doctors should not be] financially disadvantaged for having a long appointment … you need to take time [to treat endometriosis properly]. (Specialist clinic GP)

This problem was not limited to GPs, with one HP reporting:

Most specialists are very time-poor, their time limit is about 10-15 min … that would probably get you through them reading the notes and then making a decision for the [PLWE]. There's little time to actually explain all the benefits and the side effects. (Specialist clinic manager)

All HP participants in this study were very open to complementary and allied health therapies, however many described other doctors and specialists as being ignorant or closed off to potential treatments outside of their domain:

If your only solution is a hammer, then every problem becomes a nail. (Obstetrician-gynaecologist)

One HP clarified why a singular focus of some clinicians was problematic for decision-making:

[Some GPs and surgeons] can be quite negative to holistic diet and lifestyle measures, and I think that comes into the decision-making process for a person because they think, ‘well, that's not going to touch the sides if … the doctor's not recommending that’. (Complementary HP)

Theme 3: patient-centred care and SDM

Every HP in this study emphasised the need for patient-centred care and SDM to facilitate endometriosis treatment decision-making, with one obstetrician-gynaecologist noting this started by simply listening:

I can't tell you how many times people come to me saying they’ve been ignored for years. So actually listen to what they’re saying. (Obstetrician-gynaecologist)

Unfortunately, all HPs recalled seeing PLWE who felt they had not been heard by prior clinicians, making them cautious about trusting new HPs and trying different treatments:

I think about 90% of [PLWE] … have a history of being reluctant with any HP because [previous clinicians they have seen] make the decision on their behalf … they felt like they … weren't part of that shared decision-making … and then they have complications that they weren't informed of. (Specialist clinic manager)

In extreme cases, HPs noted that PLWE felt they had been removed entirely from the decision-making process:

They come to me and feel like they haven't had a decision. They feel like they’ve been pushed down a certain pathway without other choices. (Complementary medicine practitioner)

Participants unanimously described the need to empower PLWE to play their role in SDM:

[PLWE have to be] in charge, because often when people are in pain they feel like they have lost autonomy and efficacy. So we need to put them back in the middle. (Specialist clinic GP)

To this end, participants talked about facilitating decision-making, rather than leading the process:

We try to support them in their decision by not trying to persuade them in any direction and trying to help them recognise what matters to them. (Complementary medicine HP)

I think [PLWE] are astute and they don't want to be told, rightly, what to do – they want to make their own decisions. And we need to facilitate that. (Obstetrician-gynaecologist)

Sub-theme 3a: the effect of patient capacity on decision-making

All HPs reported that a key part of helping PLWE decide about treatments was recognising that resources (e.g. time, money, and physical and psychological capacity) were limited:

The less intervention, the less cost, the less effort, the more likely you are to get benefit from it, you’ll find probably more people will be willing to use it. [The use of painkillers] might be more common than physio and exercise programs, because [the latter] cost time and they cost money (Specialist clinic GP).

It was here that priorities played a key role:

It's a complex disease, so there's always going to be a list of things they maybe need to manage. But if, for example, the priority is to fall pregnant because they’ve been trying for three years, maybe their efforts need to be with the fertility doctors and not being at a physio. (Allied HP – physiotherapist)

The financial burden of treatments was reported to be hugely impactful on decision-making:

Cost is a very prohibitive barrier because it is a very expensive disease. (Allied HP).

Ongoing pain was also cited as significantly influencing PLWE's physical and mental capacity to engage with treatments:

Lifestyle stuff is obviously hard … Exercise is the cure of pain … but often people feel like they can't exercise because of their pain. (Specialist clinic GP)

One HP noted that it could be difficult to assess decisional readiness in PLWE:

I’ve been surprised by the amount of people who will see me, I’ll provide that advice, but they don't do it. You’d think if they’ve come to me they’re ready and they’re engaged. But the fact that they don't follow it through … you’re like, ‘OK, there were still barriers there’. (Specialist clinic nurse)

Theme 4: patient decision-making blinded by hope

Setting realistic expectations was cited as a key factor in sound decision-making for PLWE, but this required HPs to have an up-to-date understanding of the condition. One HP remarked that a widespread, but outdated, view of endometriosis could lead to misguided hope:

We should be regarding this disease as a chronic, systemic inflammatory problem … If you were a doctor and you just assumed that endometriosis is a few cells outside the uterus and you tell that to the patient, then the patient would think, ‘OK, well, why don't you just remove those cells? That should fix me’. But it just doesn't necessarily work that way. (Obstetrician-gynaecologist)

Another participant noted that the overwhelming nature of endometriosis could lead to PLWE shutting down:

You think everybody would want treatment, but some people don't. I think what they’re really wanting is a magic wand for you to just take it away. (Specialist clinic GP)

More than half the HPs interviewed reported that the hope for a cure that did not exist sometimes clouded effective decision-making. Misguided hope could lead PLWE to treatments which had no evidential backing:

People go into a therapy with a high level of hope, which is why some people are willing to take on therapies which are not evidence-based … That indicates a certain level of need, or desperation. (Specialist clinic GP)

A complementary medicine therapist noted this desperation could lead PLWE to blindly accept a treatment suggestion from HPs without questioning whether it was really the right solution for their individual case, then feeling ‘quite a lot of shock' if it did not work as hoped. Symptom management was the main aim for HPs, but a few stated that nothing other than surgery was acceptable to some PLWE, who believed hormonal medications were ‘Band-Aid solutions'. Similarly, one HP stated:

You can get very, very good management strategies that will control that aspect of your symptoms [pain] … but the endo is still there. Some people are fixated on the fact that there's this thing inside them that needs to be gone. (Specialist clinic nurse)

Every HP discussed the need to be honest about exactly what they could − and could not − offer, yet several stated that the uncertainty of treatment outcomes left PLWE dissatisfied:

I can tell you broadly that [the pill can have side effects of] nausea and vomiting, gastric upset and weight gain and breast tenderness and yadda yadda yadda yadda. But what is it going to do for you? I don't know. And I think [PLWE] really wrestle with that. (Obstetrician-gynaecologist)

Not being able to offer guarantees about outcomes was noted by another participant:

I think there is a perception in our society that we can just fix everything all the time … We can help, but this isn't an all or nothing question … there might need to be a certain amount of accepting of symptoms and managing symptoms to the best possible capacity. (Specialist clinic GP)

HP views on the potential value of a PtDA

HPs interviewed for this study were enthusiastic about the potential for a PtDA to empower PLWE:

It would help a lot to reduce their overwhelm, because you don't know what you don't know, so it’ll really help empower someone. And it probably will help the professional as well because it helps everyone in the end. (Complementary medicine HP)

A therapist noted that outlining the full range of treatments would be very helpful for those with doctors who did not have that information. One medical doctor said any knowledge that prompted discussion was a good thing:

I’m pro on people having lots of knowledge before coming in … using things online and coming to speak to me. (Obstetrician-gynaecologist)

One downside cited by a specialist clinic staffer was the lack of substantial evidence for many treatments in the endometriosis sphere, but a GP reflected the overall feeling of HP participants about a PtDA when they said:

Any structured approach is going to be useful and make sure that things are not missed, and if it helps [PLWE] … become more aware of what their needs or desires are, compared to what the possibilities might be, that might put them in a better position to ask the right questions. (Specialist clinic GP)

This is the first known study to explore HP perspectives of facilitators and barriers to decision-making of PLWE. Of the 13 HPs who were interviewed, 12 outlined Identifying and Setting Priorities as being a vital early step in decision-making, a view endorsed by researchers (Agarwal et al., 2019 ; Chapron et al., 2019 ; Royal Australian and New Zealand College of Obstetricians and Gynaecologists (RANZCOG), 2021 ). The alternative voice was an allied HP who reported their clients wanted endometriosis to be treated more holistically, taking all symptoms into account simultaneously. There is growing recognition of the need for multidisciplinary endometriosis care (Fang et al., 2024 ; Mechsner, 2023 ), with one qualitative study reporting that the lack of a holistic approach contributed to low satisfaction with symptom management in PLWE (Evans et al., 2022 ). However, the nature of endometriosis and its treatments necessitates a level of priority setting, depending on primary goals. For example, many hormonal treatments cannot be used by individuals with fertility-related concerns because these drugs are often contraceptives (Skorupskaite & Bhandari, 2021 ). Nevertheless, as understanding of the systemic nature of endometriosis develops (Taylor, 2019 ; Taylor et al., 2021 ), it is increasingly being recognised that PLWE need regimens that treat the condition as a whole rather than focusing on individual symptoms. This requires multidisciplinary teams that include allied health and complementary medicine practitioners alongside medical doctors such as GPs and obstetrician-gynaecologists (Agarwal et al., 2019 ; Fang et al., 2024 ).

Multi-disciplinary teams may be optimal, however accessing numerous therapies can be costly, and in The Effect of Patient Capacity on Decision-Making sub-theme, HPs’ views in this study reflected previous research documenting the considerable financial burden of holistic treatment for endometriosis (Armour et al., 2019a , 2019b ). Under Australia's hybrid public-private health system, PLWE can theoretically access medical care free of charge, but the reality is that long waiting lists for publicly-funded specialists (Armour et al., 2022 ; Frayne et al., 2023 ) and very limited subsidies for non-medical therapies (Avila et al., 2020 ; Rosenberg et al., 2022 ) leave them waiting months or years for treatment, or force those who can afford it to pay hefty out-of-pocket expenses (Armour et al., 2019a , 2019b ).

The Capacity theme did not focus solely on financial costs; HPs also reported the need for PLWE to have the physical and mental ability to engage with treatments. Decisional readiness has been extensively researched in other areas of healthcare (Pablos et al., 2020 ; Sherman et al., 2016 ; Witteman et al., 2021a , 2021b ), but has not been examined in endometriosis. There are four subdomains of decisional readiness: worry, knowledge, uncertainty about the decision, and decision-making preparation (Witteman et al., 2021a , 2021b ). PLWE have been found to experience a high degree of worry (Ruszała et al., 2022 ; Zarbo et al., 2022 ), report feeling uninformed about the condition and its treatments (Sherman et al., 2022 ), and experience high levels of uncertainty about potential treatment outcomes (Culley et al., 2013 ; Handelsman et al., 2023 ), suggesting decisional readiness is likely to be low in these individuals. Future research should explore decisional readiness in PLWE, and develop interventions that could boost this key component of SDM (Fisher et al., 2018 ; Keij et al., 2021 ). PtDAs have been shown to improve patient readiness to make a healthcare decision (Joseph-Williams et al., 2021 ).

HPs in this study also affirmed previous research outlining the complexity of understanding and treating endometriosis (van der Zanden & Nap, 2016 ; Zale et al., 2020 ), and pointed to a basic systemic barrier to providing optimal care. Patient-Centred Care and SDM were unanimously endorsed by all HP participants, but a few noted that the Australian public health system's predilection for short consultations served as a financial disincentive for doctors to take the time required to fully address PLWE's needs, reflecting prior research (Evans et al., 2022 ).

A further barrier to SDM was identified in the Stepwise Approach to Treatment sub-theme. HPs endorsed starting with the most conservative treatments and moving systematically through options before trying more invasive treatments. While this approach is endorsed by researchers and medical professionals worldwide (Mechsner, 2023 ; Vercellini et al., 2018 ), several HPs observed that PLWE new to them were sometimes fixated on surgery being the only option. The need for PLWE to self-educate (Holowka, 2022 ; Whelan, 2007 ) was reported, and lamented, by the HPs in this study, but it is vital that PLWE base their treatment decisions on the most up-to-date, valid information available (Omtvedt et al., 2022 ; Rowe et al., 2021 ). Latest endometriosis-related research recommends a move away from multiple surgeries because the operations carry inherent risks, such as adhesions, and bladder and bowel dysfunction (Armour et al., 2022 ; Saraswat et al., 2018 ), and the lesions frequently re-occur (Nirgianakis et al., 2021 ). However, a specialist clinic nurse said some popular overseas social media sites could be guilty of overstating the need for surgery, encouraging some Australian PLWE to dismiss consideration of other efficacious treatments.

Potentially misleading information aside, all HPs in this study touted the benefits of social media communities, mainly in giving PLWE support they lacked, as has been found previously (Holowka, 2022 ). However, one allied HP cautioned that the level of anger and negativity in some social media conversations could be problematic, pointing to the documented association between negative emotionality and increased pain (Yarns et al., 2022 ).

Another barrier to collaborative SDM cited by HPs in this study was what they perceived as a lack of education about endometriosis among the wider medical community, as described in the HPs’ Lack of Time and Perceived Lack of Knowledge theme. This has been raised in prior research, by both HPs (Grundström et al., 2016 ; van der Zanden & Nap, 2016 ) and PLWE (Navarria-Forney et al., 2020 ; Young et al., 2015 ), and has been reported as a key factor in eroding PLWE's trust in endometriosis healthcare providers (Mikesell & Bontempo, 2023 ). A good therapeutic alliance between HP and patient is essential for SDM (Santana et al., 2018 ), so it is unlikely PLWE who are sceptical about clinician expertise are engaging in a collaborative approach to decision-making. A decision support tool containing information reflecting the most up-to-date scientific knowledge could potentially improve HP's understanding of endometriosis and reset patient expectations, reducing conflict between the two and leading to more effective collaboration. However, a few HPs in this study observed that some PLWE would not accept anything other than surgery, even if their symptoms were managed by other treatments. The perceived need by some PLWE to be rid of ‘this thing inside them’ suggests a psychological barrier to optimal decision-making that warrants further investigation.

One striking finding from these data was the need for GPs and medical specialists to understand the potential of allied health and complementary medicine treatments in endometriosis symptom management. This sample included five practitioners from non-medical therapies and eight from medical practices, and all stressed the need for integrative care combining a range of medical, surgical and non-medical treatments for endometriosis. However, previous research shows that medical professionals are unwilling to recommend treatments outside of their specific expertise (Evans et al., 2022 ), and the HPs in this study confirmed this was often the case. While clinical trials are required to validate their effectiveness, initial studies indicate potential endometriosis symptom management using cannabis products (Carrubba et al., 2021 ), improving sleep (Li et al., 2022 ), physical exercise (Evans et al., 2019 ; Gonçalves et al., 2016 ), diet modification (Kumar et al., 2023 ), pelvic physiotherapy (Muñoz-Gómez et al., 2023 ; Wójcik et al., 2022 ) and mindfulness (Hansen et al., 2023 ; Moreira et al., 2023 ). It has been reported that 75% of Australian PLWE use self-management strategies such as these (Armour et al., 2019a , 2019b ), but very few are confident about their knowledge of such treatments (Adamietz et al., 2021 ); further underscoring the need for a decision support tool that could boost knowledge in PLWE and HPs of the full range of valid treatment options.

The final theme identified in these data was Patient Decision-Making Blinded by Hope , and this is a subject that has been under-researched in endometriosis. Positive emotions such as hope have been found to favourably affect people's intention to change their health behaviour (Nabi & Myrick, 2019 ), including in endometriosis screening (Worsdale & Liu, 2023 ). Research reports that optimal levels of hope, defined as the belief that personal goals can be achieved (Snyder et al., 1991 ), are associated with improved outcomes when people are sick (Musschenga, 2019 ), and help them adapt to chronic illness (de Andrade Alvarenga et al., 2021 ; Yücens et al., 2019 ). However, aiming for impractical goals that do not reflect realistic limitations can lead to worse psychological outcomes, as well as being financially costly as people try treatments unlikely to ease their symptoms (Eijkholt, 2020 ). PLWE frequently report feeling hopeless (Calvi et al., 2024 ; Cox et al., 2003 ; Whelan, 2007 ). However, many HPs in the current study discussed how misguided hope could interfere with sound decision-making. A specialist clinic GP pointed out that, despite all attempts at treatment, the unfortunate truth was that some PLWE would have to set realistic expectations, and simply manage their symptoms to the highest degree possible. Prior research has found that acceptance of their illness is associated with higher quality of life in PLWE (Bień et al., 2020 ; Márki et al., 2022 ).

Taken together, the themes identified from these qualitative analyses indicate that HPs believe individuals with endometriosis are not receiving the support they require when choosing treatments for symptom management. The complexity of the condition and the difficulty in finding an individualised treatment plan were acknowledged by all HPs, who advocated for patient-centred care, actively listening, and more time in consultations. The majority described trying to clarify goals to identify what was important for each individual, and recounted efforts they made to ensure PLWE had the required knowledge to make an informed decision. However, they were less than complimentary about the wider medical community, pointing to other clinicians’ perceived lack of attentiveness and lack of knowledge, including an inability or unwillingness to recommend allied health and complementary therapies. However, there are two sides to SDM, and while no HP said anything negative about PLWE, they did allude to issues that might hinder effective decision-making. The first factor was some PLWE's insistence on surgery, despite other potentially efficacious treatments being available. Related to this was PLWE's tendency to access information via social media communities, which provided them with a source of support but could potentially misinform. Lastly, PLWE's hope for a cure that did not exist was described as a factor that potentially obfuscated quality decision-making. These data confirmed that many PLWE do not currently have adequate resources and support to make complex decisions about their treatment, and the HPs welcomed the idea of a PtDA to help fill that gap, noting that it could be also used by clinicians.

This study has for the first time recorded HPs’ insights into the decision-making processes of PLWE, but some limitations must be acknowledged. Efforts were made to canvas a wide range of HP views, but not every area offering treatment to PLWE was represented (Becker et al., 2022 ; Kalaitzopoulos et al., 2021 ). In addition, the selection of potential participants was not random: firstly, invitations were sent to HPs known to be active in the endometriosis sphere; and secondly, only 20% of invited HPs volunteered and participated, which may have resulted in recruitment and volunteer biases potentially skewing results. Additionally, it is crucial to acknowledge the potential for researcher bias to affect data collection and/or analysis in qualitative research, therefore reflexivity statements from LF, CP and KS are provided in Supplementary Materials C. Lastly, the research team created and ran this study predicting that the endometriosis community would most probably benefit from a PtDA, and this could have inadvertently coloured data collection and interpretation.

The results of this study indicate a support tool such as a PtDA could significantly assist PLWE in treatment decision-making. The HPs in this study were enthusiastic about the potential utility of a PtDA, with some noting it could also be a good tool to guide less knowledgeable clinicians, and others predicting that it could streamline consultations by giving PLWE the knowledge to ask salient questions of their healthcare team. The results of this study will help to inform the development of a co-designed, consumer- and HP-informed PtDA to support and facilitate the treatment and management decision-making process for PLWE. This interactive online tool, based on global best-practice guidelines (Elwyn et al., 2006 ), will include easy-to-read information on the full range of evidence-based endometriosis treatments and guidance to help users decide what is the best choice for them (Geukens et al., 2018 ; Metzemaekers et al., 2021 ), with the aim of empowering PLWE with the knowledge and confidence to play their part in SDM.

Author contribution

All authors agree to be accountable for all aspects of the work, have approved the contents of this paper, and have agreed to the submission policies of the Health Psychology and Behavioral Medicine. Individual contributions of each author are as follows:

• Lynda Fallon: conception and design; data collection; analysis and interpretation of the data; drafting the paper; revising it critically for intellectual content; and final approval of the version to be published.
• Kerry A. Sherman: conception and design; analysis and interpretation of the data; drafting the paper; revising it critically for intellectual content; and final approval of the version to be published.
• Annie Y. S. Lau: conception and design; revising the paper critically for intellectual content; and final approval of the version to be published.
• Donna Ciccia (endometriosis consumer investigator): conception and design; revising the paper critically for intellectual content; and final approval of the version to be published.
• Tanya Jane Duckworth (endometriosis consumer investigator): conception and design; revising the paper critically for intellectual content; and final approval of the version to be published.
• Chantelle Pereira: analysis and interpretation of the data; revising the paper critically for intellectual content; and final approval of the version to be published.
• Emily Kopp: data curation and final approval of drafts.
• Valentina Perica: data curation and final approval of drafts.

Supplementary Material

Acknowledgements.

The research team would like to thank the HPs who so generously gave us their time and wisdom.

Funding Statement

LF's contribution to this research was supported by the Australian Government’s Research Training Program.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Conflict of interest statement

The authors have no conflicts of interest to declare.

Data availability statement

Informed consent statement.

All participants provided written and verbal consent to take part in the study, and for their interviews to be recorded.

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