Good Research Practice Research Articles

Predictive Maintenance in Semiconductor Manufacturing: Leveraging IoT Sensor Data for Equipment Reliability

Abstract—Predictive maintenance (PdM) has emerged as a transformative approach in semiconductor manufacturing, leveraging IoT sensor data to enhance equipment reliability and optimize production processes. This review explores the implementation of predictive maintenance strategies in semiconductor manufacturing, focusing on the role of IoT sensor networks, advanced analytics techniques, and integration with Manufacturing Execution Systems (MES). IoT sensor networks enable comprehensive real-time data collection on equipment performance and environmental conditions, thereby providing a foundation for predictive maintenance. Time series forecasting algorithms, such as ARIMA, exponential smoothing, and machine learning-based approaches, are employed to anticipate potential equipment failures. Anomaly detection techniques, including statistical methods and machine-learning algorithms, are used to identify unusual patterns or behaviors that are indicative of impending issues. The integration of predictive maintenance insights with MES allows for real-time decision making, process optimization, and improved overall equipment effectiveness. However, challenges persist in terms of data quality, scalability, and cybersecurity, requiring ongoing research and industry collaboration. Early adopters reported significant reductions in unplanned downtime, optimized maintenance schedules, and improved product quality. As the semiconductor industry continues to evolve, predictive maintenance is expected to play a crucial role in maintaining competitiveness and meeting the growing demand. Further research, standardization efforts, and development of best practices are essential to fully realize the potential of predictive maintenance in semiconductor manufacturing. Keywords—predictive maintenance (PdM), semiconductor manufacturing, IoT sensor data, equipment reliability, forecasting, anomaly detection, unplanned downtime, product quality

Improving Reproducibility in AI Research: Four Mechanisms Adopted by JAIR

Background: Lately, the reproducibility of scientific results has become an increasing worry in the scientific community. Several studies show that artificial intelligence research is not spared from reproducibility issues. Objectives: As a pioneer in open and transparent research published on the Internet, the Journal of Artificial Intelligence Research (JAIR) seeks to promote good research practices and close the feedback loop between the original researchers and those reproducing their research. Methods: Four different mechanisms will be adopted immediately by JAIR. These are: 1) reproducibility checklists, 2) structured abstracts, 3) reproducibility badges and 4) reproducibility reports. Results: All authors submitting articles to JAIR fill out a reproducibility checklist and are encouraged to use structured abstracts. Articles that fulfill certain criteria will receive reproducibility badges, and reproducibility reports can be submitted by anyone for any article published in JAIR. Conclusions: We believe that adopting the four mechanisms outlined in this paper will improve the reproducibility of research published in JAIR and thus make a contribution to addressing the broader reproducibility issue in artificial intelligence. We hope that JAIR’s reproducibility initiative will inspire similar efforts at other top-tier journals.

Best practices for disinfection in dental settings: insights from Italian and European regulations.

Disinfection practices in dental settings are fundamental to clinical safety, playing a pivotal role in preventing cross-infections and protecting the health of patients and healthcare professionals. This article examines the key components of effective disinfection, based on evidence-based protocols developed by international organizations such as the WHO and the U.S. CDC, alongside European and Italian regulatory standards. Dental instruments require stringent sterilization by autoclave or chemical methods, while high-level disinfection is essential for non-sterilizable items. Clinical surfaces require routine biocidal treatment tailored to microbial hazards and material compatibility. The European Biocidal Products Regulation and the Medical Devices Regulation provide critical oversight, ensuring product safety and effectiveness while preventing resistance. Antiseptics also play a vital role in oral care, with applications ranging from infection prevention to the treatment of periodontal disease, and are governed by strict regulatory frameworks. Disinfection effectiveness is significantly affected by factors such as microbial load, presence of biofilm, pH, temperature and biocide exposure time. Preventing bacterial resistance requires appropriate germicide selection, adherence to manufacturer protocols, robust sterilization and cleaning procedures. In addition, the increased use of disinfection during public health emergencies highlights the need for adaptability to mitigate evolving risks. Regular audits, biological tests, and training for healthcare personnel ensure the consistent application of these rigorous protocols. By integrating international and national standards, dental facilities achieve a uniform approach to hygiene and safety, advancing public trust and compliance. This article highlights the imperative for ongoing research and dissemination of best practices to enhance infection control in dental care environments.

Researchers’ Practice and Perception of Research Ethics and the Role of Institutional Support: Insights From a pan-European Researcher Survey

AbstractResearch Ethics is a key element of Responsible Research and Innovation (RRI). In spite of an increased interest in this topic there is little empirical evidence about scientists’ practice and perception of Research Ethics. Drawing on a large-scale survey among 4,180 European researchers we present unique insights into Research Ethics activities, researchers’ motivation for ethical behavior, the perceived barriers and benefits as well as the role of institutional support. According to the survey results, most researchers consider ethical issues in their research projects and see it as part of good research practice or are convinced that research must be ethical. Perceived benefits of Research Ethics are higher quality of scientific outputs, higher social relevance of research, increased societal impact and a changed approach to risk. Barriers to ethics activities are particularly seen in the absence of institutional support and incentives. With regard to institutional support, we show that offers and infrastructures of Research Performing Organisations for Research Ethics are not well known among the employed researchers in general. Through a regression analysis about the influence of institutional support on Research Ethics we see at the same time that the provision of an Ethics team that researchers can address and the existence of a policy for designing ethical values and principles into research practice have a positive influence on researchers to engage in Research Ethics activities. The results underlines the importance of low-threshold services and personal contacts for researchers with ethical questions.

Ten practical guidelines for microclimate research in terrestrial ecosystems

Abstract Most biodiversity dynamics and ecosystem processes on land take place in microclimates that are decoupled from the climate as measured by standardised weather stations in open, unshaded locations. As a result, microclimate monitoring is increasingly being integrated in many studies in ecology and evolution. Overviews of the protocols and measurement methods related to microclimate are needed, especially for those starting in the field and to achieve more generality and standardisation in microclimate studies. Here, we present 10 practical guidelines for ground‐based research of terrestrial microclimates, covering methods and best practices from initial conceptualisation of the study to data analyses. Our guidelines encompass the significance of microclimates; the specifics of what, where, when and how to measure them; the design of microclimate studies; and the optimal approaches for analysing and sharing data for future use and collaborations. The paper is structured as a chronological guide, leading the reader through each step necessary to conduct a comprehensive microclimate study. At the end, we also discuss further research avenues and development in this field. With these 10 guidelines for microclimate monitoring, we hope to stimulate and advance microclimate research in ecology and evolution, especially under the pressing need to account for buffering or amplifying abilities of contrasting microhabitats in the context of global climate change.

A child-centred research checklist to improve the design and reporting of paediatric research studies: A descriptive mixed methods study

BackgroundNo internationally developed child-centred research checklist is currently available to enhance the quality and transparency of the development, reporting and evaluation of research undertaken with children. ObjectiveTo develop an internationally relevant, expert informed child-centred research checklist. DesignA descriptive mixed methods study was undertaken in five sequential phases, including a Delphi component. Setting(s)Academic/international context. MethodsThis study involved five sequential stages:1. Literature review using four databases (CINAHL, MEDLINE, Scopus, PsycINFO) and analysis to identify key themes in child-centred research (January 2020).2. Generate a questionnaire based on the key themes for international experts in child research to provide their opinions on what should be included in a child-centred research checklist (March 2020).3. Inductive thematic analysis of the experts' responses to generate the initial draft checklist (June 2020).4. The checklist progressed through three rounds of Delphi study for a wider range of experts to provide their consensus on what a child-centred research checklist should contain (August 2020–February 2021).5. Refinement of the child-centred research checklist based on the Delphi study (March 2021–November 2022). ResultsA total of 160 articles met the inclusion criteria for review and were considered in the development of a 10-item open-ended questionnaire, adapted for four age-brackets (0-1 yrs., 2-4 yrs., 5-10 yrs., >11 yrs). Responses from 14 experts across 10 countries generated 205 generic statements and 76 examples to inform a child-centred research checklist. Following this, 158 experts from eleven disciplines across 18 countries participated in the three round Delphi study (38 % retention rate over the three rounds). The final checklist includes 11 statements and 17 examples represented under three categories of “child-parent consent, assent and dissent”, “code of conduct” and “child focused methods”. ConclusionThe child-centred research checklist was generated from a mixed methods study undertaken in five sequential phases, with input by 172 experts from 11 disciplines across 19 countries. The child-centred research checklist is the first international, expert informed tool to support good quality and transparent child-centred research. We call on researchers, clinicians, journal editors, organisations, and ethics committees to use this checklist for future research with children. The next phase of this project is engagement with children and their families to refine the checklist. Tweetable abstractNew checklist to support good quality child research practices @IFNAorg.

Introduction to the Benchmarking in Optical Networks Special Issue

The first part of this special issue contains five papers addressing different aspects of good benchmarking practices in optical network research. We start with a brief introduction, followed by an overview of the papers and an invitation to contribute to the second part.

Healthcare professionals’ preferences for the specialist pharmacy service medicines advice clinical enquiry service: a discrete choice experiment

Abstract Introduction The Specialist Pharmacy Service Medicines Advice (SPS-MA) service answers enquiries from primary care professionals in England. The preferences of service users for the way this service is provided (e.g. opening hours, speed and route of reply, amount of detail in answer etc.) are unknown. Such information would be useful to ensure the service meets the needs of users as well as possible within the constraints of available resources. Aim To determine healthcare professionals’ preferences for the Specialist Pharmacy Service Medicines Advice clinical enquiry service using a discrete choice experiment (DCE). Methods International Society for Pharmacoeconomics and Outcomes Research good research practices were used to conduct a DCE1. Previous literature2, documentary analysis of SPS-MA policies, and interviews with four SPS-MA enquirers and three SPS-MA service providers/managers identified seven key attributes of the clinical enquiry service. Each attribute could be defined using one of 2-3 descriptions (‘levels’). A D-efficient experimental design generated 20 pairs of potential clinical enquiry service variants, each described by one level linked to each of the seven attributes. These 20 pairs were blocked into two online surveys (10 pairs per survey), which asked participants to choose which service from each pair they would prefer to contact. The 1669 SPS-MA clinical enquiry contacts with a recorded email in the year to November 2023 were randomised to receive an email invitation to complete one of the survey variants. Preferences for each attribute level were estimated using conditional logit regression. Using the HRA decision tool, this project was not considered research by the NHS. It was given a favourable opinion by the University of Bath ethics review process on 27th November 2023 (reference 1153-2222). Results 236 participants completed a survey (52% GP pharmacists, 26% other pharmacists, 22% other professional; median 15 years’ experience). Weekend opening and opening hours did not significantly affect preferences (p≥0.226). All other attributes did significantly affect preferences (p≤0.015). An answer within one hour or two days was most valued (preference weightings (95%CI) relative to five days: 0.89 (0.76-1.03) and 0.58 (0.45-0.72), respectively). Communication by email was highly valued (preference weighting: 0.62 (0.47-0.77) relative to telephone only). The availability of a website of frequently asked questions was also valued (preference weighting: 0.48 (0.31-0.64) relative to no website). Answering the telephone within 20 seconds and a detailed response were valued, but to a lesser degree. Sub-group analysis found that participants qualified for <15 years valued email communication and detailed responses more strongly than other participants (p≤0.035). Discussion / Conclusion Where clinically appropriate, the SPS-MA clinical enquiry service should prioritise speed of reply, communication by email and a website of frequently asked questions. Longer opening hours are not required. This is the first study to use of a DCE to investigate professional enquirers’ preferences for a medicines information/advice service. This allowed analysis of the strength of preferences and how they were traded off. Due to the small number of non-pharmacist enquirers to the SPS-MA service, it was not possible to investigate how professional background influences preferences.

ESR Essentials: radiomics-practice recommendations by the European Society of Medical Imaging Informatics.

Radiomics is a method to extract detailed information from diagnostic images that cannot be perceived by the naked eye. Although radiomics research carries great potential to improve clinical decision-making, its inherent methodological complexities make it difficult to comprehend every step of the analysis, often causing reproducibility and generalizability issues that hinder clinical adoption. Critical steps in the radiomics analysis and model development pipeline-such as image, application of image filters, and selection of feature extraction parameters-can greatly affect the values of radiomic features. Moreover, common errors in data partitioning, model comparison, fine-tuning, assessment, and calibration can reduce reproducibility and impede clinical translation. Clinical adoption of radiomics also requires a deep understanding of model explainability and the development of intuitive interpretations of radiomic features. To address these challenges, it is essential for radiomics model developers and clinicians to be well-versed in current best practices. Proper knowledge and application of these practices is crucial for accurate radiomics feature extraction, robust model development, and thorough assessment, ultimately increasing reproducibility, generalizability, and the likelihood of successful clinical translation. In this article, we have provided researchers with our recommendations along with practical examples to facilitate good research practices in radiomics. KEY POINTS: Radiomics' inherent methodological complexity should be understood to ensure rigorous radiomic model development to improve clinical decision-making. Adherence to radiomics-specific checklists and quality assessment tools ensures methodological rigor. Use of standardized radiomics tools and best practices enhances clinical translation of radiomics models.

Enhancing Clinical Data Quality to Improve Patient Care in Rural Health Facilities

WHO recognizes that high-quality research is not just a scientific pursuit but a crucial factor in achieving global health, health equity, and economic development. It is not just about the numbers but about the lives we can save and improve. In this context, four research priority areas have been identified: prioritizing health needs, building research capacity, ensuring good research practice, and ensuring good evidence is translated into practice. Local health research tailored to local needs remains an important global health goal, with the potential to revolutionize patient care in rural health facilities. Researchers and policymakers in low- and middle-income countries have expressed serious concerns about the limited access to high-quality data, a fundamental requirement for reliable and valid research. The assessment of data quality is typically categorized into five key areas: availability, usability, dependability, relevance, and presentation quality. This concept is further clarified by demonstrating how a robust healthcare data environment can enhance patient management through research efforts. The term ‘health data environment' encompasses the entire process of gathering, storing, managing, analysing, and utilizing health-related data to improve patient care and healthcare policies through informed decision-making. In this context, we present the challenges that undermine the quality of research data and propose solutions. Specifically, we identify the lack of adequate human resources, reliance on paper-based records systems, and the high costs of internet connectivity as the primary barriers to collecting and sharing high-quality data for research in low-resource settings. To tackle these challenges, we advocate for governments and funding institutions to invest in data management and communication systems, recruit and train data management staff to support clinicians, and reduce connectivity costs. Furthermore, we propose the deployment of a decentralized system as a cost-effective and less labor-intensive solution that only requires data entry staff at health facilities in resource-limited settings. This article explores current data collection, storage, and interpretation challenges and proposes innovative improvement solutions. It emphasizes the transformative potential of digitization, standardization, and staff training to enhance data quality. It further addresses the impact of quality data on evidence-based practice, ultimately leading to improved health outcomes. Focusing on rural healthcare facilities sheds light on the unique barriers these settings face, proposing tailored strategies that can bridge the gap between urban and rural health service delivery. These insights offer valuable guidance for policymakers, healthcare administrators, and practitioners striving to improve patient care in rural areas through data-driven strategies.

How we approach steroid-induced affective disorder in pediatric oncology.

High-dose corticosteroids are an essential component of treatment for pediatric cancers. Yet, these agents often cause psychiatric disturbances including sleep disruption, steroid-induced psychosis, and steroid-induced affective disorder (SIAD). SIAD, identified as a specific form of substance/medication-induced mental disorder, can present with various psychiatric symptoms, including mania, depression, irritability, and inconsolability. SIAD's varied presentation can lead to underdiagnosis and complicates clinical care, research, and identification of best practices. Here we highlight three pediatric oncology cases involving SIAD and discuss recommendations for supporting patients with SIAD, while introducing a tiered intervention framework (modified from Kazak) that stratifies responses based on symptom severity.

The conceptualisation of cardiometabolic disease policy model in the UK

BackgroundDecision models are increasingly used to inform policy-making processes, and there is a need to improve their credibility. The estimation of health and economic outcomes generated from decision models is influenced by the development process itself. This paper aims to present the conceptual model development process of cardiometabolic disease (CMD) policy models in the UK setting.MethodsThis conceptual model followed the International Society of Pharmacoeconomics and Outcomes Research-Society of Medical Decision Making (ISPOR-SMDM) Modelling Good Research Practices Task Force-2.ResultsFirst, for the conceptualisation of the problem, the CMD disease staging, progression and current clinical guidelines were summarised, followed by a systematic review of published policy models. We critically appraised policy models such as cardiovascular disease and type 2 diabetes. Key messages from the review emphasised the importance of understanding various determinants influencing model development, including risk factors, model structure, models’ parameters, data utilisation, economic perspective, equality/equity consideration, transparency and validation process. Second, as a sequential process, is model conceptualisation, to determine which modelling types and their attributes best represent the defined problem. Expert opinions, including a clinician and experienced modellers, provided input on the state transition model to ensure the structure is clinically relevant. From this stage, the consideration and agreement to establish a disease state in a state transition model was discussed.ConclusionThis conceptual model serves as a basis for representing the systematic process for structuring a CMD policy model to enhance its transparency and credibility.

Shared Ideals, But Persistent Barriers: Improving Tribal‐University Research Engagement to Strengthen Native Nation Building and Rural Development☆

AbstractResearch partnerships between Tribal Nations and rural colleges and universities can support rural development and strengthen Tribal Nation building through reclamation of economic, political, cultural, and social affairs. However, Tribal Nation–University relationships have received little attention in rural sociology. While scholars identify best practices for research engagement in light of colonial harms, the ideal visions that Tribally and university‐affiliated people have for research partnerships and the barriers to achieving those ideals are poorly understood. Without identifying these visions and barriers, we risk making wrong assumptions about each party's needs and cannot implement appropriate policies. Semi‐structured interviews with Tribally‐affiliated (n = 20) and university‐affiliated (n = 20) people in rural southeastern Idaho suggest, contrary to literature on best practices for collaborative research, that participants in both groups viewed what we term “Tribally‐responsive research engagement” as ideal, though few projects met this goal. Tribally‐responsive research directly addressed Tribal priorities but did not necessarily involve close collaboration. The University's failure to acknowledge past or colonial harms, university‐affiliated researchers' historicization of those harms, and negative Native student experiences reinforced distrust, limiting desired research engagement. In sum, Tribally‐responsive research engagement could strengthen Native Nation building, but requires universities to acknowledge harms, create more welcoming campus environments, and prioritize Tribal benefits in research.

METACOGNITION AS A CATALYST FOR IMPROVED LEARNING OUTCOMES IN OPEN & DISTANCE EDUCATION

Challenges in open and distance education are unique to the learner and generally result in a gap between what is desired and what is realized. This paper explores how metacognition works wonders in bridging this gap and leading to improved learning outcomes within Open and Distance Education (ODE) environments. Metacognitive strategies foster self-regulated learning and assist students in properly planning, monitoring, and assessing their learning processes. In line with this, this paper discusses how metacognition could make a difference in improving academic achievement, promoting independent learning, and building lifelong learning skills within ODE. We demonstrate, from in-depth research and analysis of best practices, how the integration of metacognitive approaches into practice could go a long way in closing the achievement gap and optimizing the educational experience for distance learners. The findings underscore the critical role of metacognition in letting students rise above intrinsic ODE difficulties toward superior learning outcomes.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0715/a.php" alt="Hit counter" /></p>

Optimizing Pain Management in Emergency Departments: A Comprehensive Review of Current Analgesic Practices.

Effective pain management in Emergency Departments (EDs) is vital for improving patient comfort and clinical outcomes. This review provides a comprehensive analysis of current pain management practices in ED settings, focusing on the challenges and opportunities for optimization. The review examines pharmacologic and non-pharmacologic pain management strategies, evaluating their effectiveness and identifying inconsistencies and gaps in current practices. Key challenges in the ED environment include time constraints, variability in clinical protocols, and the need to address diverse patient needs, including those of paediatric, geriatric, and chronic pain patients. The review highlights the importance of standardized pain assessment tools and protocols to improve consistency in pain management. Innovations, such as technological advances and multimodal approaches, are explored for their potential to enhance pain management practices. Recommendations address identified challenges, including improved training for ED staff, the development of evidence-based protocols, and the integration of multimodal pain management strategies. By addressing these areas, the review aims to contribute to the development of more effective and uniform pain management practices in emergency care, ultimately leading to better patient outcomes and experiences. This review emphasizes the need for ongoing research and adaptation of best practices to meet the evolving needs of patients in emergency settings.

Provenance Information for Biomedical Data and Workflows: Scoping Review.

The record of the origin and the history of data, known as provenance, holds importance. Provenance information leads to higher interpretability of scientific results and enables reliable collaboration and data sharing. However, the lack of comprehensive evidence on provenance approaches hinders the uptake of good scientific practice in clinical research. This scoping review aims to identify approaches and criteria for provenance tracking in the biomedical domain. We reviewed the state-of-the-art frameworks, associated artifacts, and methodologies for provenance tracking. This scoping review followed the methodological framework developed by Arksey and O'Malley. We searched the PubMed and Web of Science databases for English-language articles published from 2006 to 2022. Title and abstract screening were carried out by 4 independent reviewers using the Rayyan screening tool. A majority vote was required for consent on the eligibility of papers based on the defined inclusion and exclusion criteria. Full-text reading and screening were performed independently by 2 reviewers, and information was extracted into a pretested template for the 5 research questions. Disagreements were resolved by a domain expert. The study protocol has previously been published. The search resulted in a total of 764 papers. Of 624 identified, deduplicated papers, 66 (10.6%) studies fulfilled the inclusion criteria. We identified diverse provenance-tracking approaches ranging from practical provenance processing and managing to theoretical frameworks distinguishing diverse concepts and details of data and metadata models, provenance components, and notations. A substantial majority investigated underlying requirements to varying extents and validation intensities but lacked completeness in provenance coverage. Mostly, cited requirements concerned the knowledge about data integrity and reproducibility. Moreover, these revolved around robust data quality assessments, consistent policies for sensitive data protection, improved user interfaces, and automated ontology development. We found that different stakeholder groups benefit from the availability of provenance information. Thereby, we recognized that the term provenance is subjected to an evolutionary and technical process with multifaceted meanings and roles. Challenges included organizational and technical issues linked to data annotation, provenance modeling, and performance, amplified by subsequent matters such as enhanced provenance information and quality principles. As data volumes grow and computing power increases, the challenge of scaling provenance systems to handle data efficiently and assist complex queries intensifies, necessitating automated and scalable solutions. With rising legal and scientific demands, there is an urgent need for greater transparency in implementing provenance systems in research projects, despite the challenges of unresolved granularity and knowledge bottlenecks. We believe that our recommendations enable quality and guide the implementation of auditable and measurable provenance approaches as well as solutions in the daily tasks of biomedical scientists. RR2-10.2196/31750.

Training, networking, and support infrastructure for ombudspersons for good research practice: A survey of the status quo in the Berlin research area

ABSTRACT Recent developments in the German academic landscape have seen a shifting approach to promoting research integrity. In 2019, the German Research Foundation (DFG) incentivized all research and higher education institutions to appoint ombudspersons who advise members of their institution in matters of good research practice or suspected research misconduct. These ombudspersons for good research practice, usually professors who act in this function on a voluntary basis, need institutional support to be prepared for and fulfill their diverse duties. The Ombuds-Modelle@BUA (2020) and OBUA – Ombudswesen@BUA (2021–2023) projects worked to advance the professionalization of ombudspersons in the Berlin research area by first investigating the current situation and then offering a meta-level of support in training, networking, and knowledge exchange. Furthermore, the OBUA project engaged in meta-research, investigating the status quo of local ombuds systems and demands for support. The project findings, discussed in this contribution, show that the professionalization of local ombuds systems has been evolving in past years, especially in the areas of training and networking. Infrastructural support measures, however, remain largely underdeveloped.

Data Management Plan for a rapid response sub-study of an existing cohort. The Irish Longitudinal Study on Ageing (TILDA) COVID-19 sub-study

A Data Management Plan (DMP) is a formal document that outlines the management and stewardship of data generated over the lifecycle of a research project from data collection, and governance structures, to the long-term preservation of data outputs. DMPs are an important feature of good research practice. Our aim is to provide details of the development of a DMP that others can learn from and adapt to their specific needs. Our DMP was developed as part of a COVID-19 sub-study of The Irish Longitudinal Study on Ageing (TILDA), titled “Altered lives in a time of crisis: preparing for recovery from the impact of the COVID-19 pandemic on the lives of older adults”. TILDA is a longitudinal study of community-dwelling older adults. In 2009/2010, an initial nationally representative sample of 8,500 adults aged 50 years and older were selected. The sample for the COVID-19 study were recruited from this existing sample. The objective of the sub-study was to document the lives and experiences of older adults during the COVID-19 pandemic to better understand the effect of the pandemic and public health responses on their well-being. This DMP describes the study design and objectives; data collection tools and procedures; data preparation; data storage and security; data sharing and preservation; and ethical and legal considerations within the European Union and Irish Health Research legislative context. Responsible data governance in Ireland is complex, requiring adherence to both European and Irish legislation. Implementation of the Health Information Bill (2023) may bring further complexities to this context. It is therefore crucial that researchers, data stewards, and other practitioners, share their expertise freely, as we have done here, so that others can learn from their experiences and the health research community can develop standards of best practice.

Involvement of children and young people in the conduct of health research: A rapid umbrella review.

Patient and public involvement and engagement (PPIE) have long been considered important to good research practice. There is growing, yet diverse, evidence in support of PPIE with children and young people (CYP). We must now understand the various approaches to involvement of CYP in research. This rapid umbrella review aimed to provide an overview of when, how and to what extent CYP are involved in the conduct of health research, as well as the reported benefits, challenges, and facilitators of involvement. We searched OVID Medline, Embase and PubMed. Published reviews were included if they reported meaningful involvement of CYP in the conduct of health research. Extracted data were synthesised using thematic analysis. The 26 reviews included were predominately systematic and scoping reviews, published within the last decade, and originating from North America and the United Kingdom. CYPs were involved in all stages of research across the literature, most commonly during research design and data collection, and rarely during research funding or data sharing and access. Researchers mostly engaged CYP using focus groups, interviews, advisory panels, questionnaires, and to a lesser extent arts-based approaches such as photovoice and drawing. Visual and active creative methods were more commonly used with children ≤12 years. The evidence showed a shared understanding of the benefits, challenges, and facilitators for involvement of CYP, such as time and resource commitment and building partnership. Overall, the review identified consistency in the range of methods and approaches used, and stages of research with which CYP are commonly involved. There is a need for more consistent reporting of PPIE in the literature, both in terminology and detail used. Furthermore, the impact of approaches to CYP involvement on research and community outcomes must be better evaluated. This review forms part of broader research initiatives being led by the authors. Together, these projects aim to support embedding of child voices in research practice and to explore the desirability and suitability of Young Persons Advisory Groups within birth cohort studies. The findings from this review, alongside public and stakeholder consultation, will inform development of resources such as practice recommendations to guide future involvement of CYP in health research undertaken at the author's respective institutions.

Establishing reliability and construct validity for the revised Emotional Social Screening Tool for School Readiness (E3SR-R)

School readiness assessments in South Africa still predominantly focus on the assessment of cognitive skills. The Emotional Social Screening Tool for School Readiness (E3SR) was developed to bridge the perceived gap in assessing emotional-social skills as a domain of school readiness. An emerging body of research reports exists on the psychometric properties and factor structure of the E3SR. An initial validation study recommended a 6-factor solution instead of the theoretical 9-factor model that was proposed in the development of the E3SR. The E3SR (Revised) was also reduced in length. We report here on a pilot study of which the aim was to establish the reliability and construct validity of the E3SR (Revised). A cross-sectional survey design was used to gather data from 9 pre-schools in Cape Town, South Africa. Pre-school teachers (n = 24) constituted the respondent group who completed the E3SR (Revised) screening questionnaires on Grade R learners (n = 394). Analysis was conducted on 321 completed screening questionnaires. With the data analysis we aimed to: a) summarise sample characteristics of teachers and children; b) establish reliability estimates; and c) establish construct validity and confirming the factor structure. Ethics clearance was given by the Humanities and Social Science Research Ethics Committee (HSSREC) of the University of the Western Cape. The study adhered to stipulated ethics requirements. Data failed to show multivariate normality; however, this violation of normality was expected and was theoretically supported. The sample size (n = 321) was sufficient for factor analysis of a 36-item scale. All subscales showed excellent reliability: Cronbach’s alphas ranged between .939 and .971. CFA results demonstrated a good model fit. The E3SR (Revised) was found to be reliable and valid for use. The use of a rigorous methodological process including the decision-making matrix represent good research practice that can be used in instrument development across cultures.