Accessible Format Research Articles

The Role of Data Visualization in Enhancing Patient Health Literacy

This paper examines how data visualization can serve as a powerful tool to improve patient health literacy by translating complex health information into accessible visual formats. Health literacy, a vital factor in effective healthcare, is influenced by diverse factors such as education, socioeconomic status, and culture. Data visualizations provide a bridge to understanding, allowing patients to more easily comprehend critical health information and, consequently, make informed decisions about their care. The paper investigated the various types of data visualizations used in patient education, discussing design principles for creating effective health-related visual content that can engage patients across health literacy levels. Furthermore, the study examined case studies illustrating successful applications of data visualizations in real-world healthcare settings. In conclusion, the paper addresses the ethical considerations and challenges in employing data visualization as a communication tool, emphasizing the need for culturally competent and inclusive design approaches to maximize comprehension and patient safety. Keywords: Data Visualization, Health Literacy, Patient Education, Healthcare Communication, Ethical Design.

PREDICTING HIGH FLOW ARTERIOVENOUS FISTULAS AND CARDIAC OUTCOMES IN HEMODIALYSIS PATIENTS.

Heart failure is common in patients receiving hemodialysis. A high flow arteriovenous fistula (AVF) may represent a modifiable risk factor for heart failure and death. Currently, no tools exist to assess the risk of developing a high flow AVF (>2000 mL/min). The aim of this study was to use machine learning to develop a predictive model identifying patients at risk of developing a high flow AVF and to examine the relationship between blood flow, heart failure, and death. Between 2011 and 2020, serial AVF blood flows were measured in 366 prevalent hemodialysis patients at two tertiary hospitals in Australia. Four prediction models (deep neural network, and 3 separate tree-based algorithms) employing age, first AVF flow, diabetes, and dyslipidemia were compared to predict high flow AVF development. Logistic regression was used to assess the relationship between AVF blood flow, heart failure, and death. High flow AVFs were present in 31.4% of patients. The bootstrap forest predictive model performed best in identifying those at risk of a high flow AVF (AUC 0.94, sensitivity 86%, specificity 83%). Heart failure prior to vascular access creation was identified in 10.2% of patients with an additional 24.9% of patients developing heart failure after AVF creation. Long-term mortality after access formation was 27%, with an average time to death after AVF creation of 307.5 ± 185.6 weeks. No univariable relationship using logistic regression was noted between AVF flow and incident heart failure after AVF creation or death. Age, flow at first measurement >1000 mL/min, time to highest AVF flow, and heart failure predicted death after AVF creation using a general linear model. Predictive modelling techniques can identify patients at risk of developing high flow AVF. No association was seen between AVF blood flow rate and incident heart failure after AVF creation. In those patients who died, time to highest AVF flow was the most important predictor of death after AVF creation.

De-Mystifying the Clone-Censor-Weight Method for Causal Research Using Observational Data: A Primer for Cancer Researchers.

Regulators and oncology healthcare providers are increasingly interested in using observational studies of real-world data (RWD) to complement clinical evidence from randomized controlled trials for informed decision-making. To generate valid evidence, RWD studies must be carefully designed to avoid systematic biases. The clone-censor-weight (CCW) method has been proposed to address immortal time and other time-related biases. The objective of this manuscript is to de-mystify the CCW method for cancer researchers by describing and presenting its core components in an accessible and digestible format, using visualizations and examples from cancer-relevant studies. The CCW method has been applied in diverse settings, including investigations of the effects of surgery within a certain time after cancer diagnosis, the continuation of annual screening mammography, and chemotherapy duration on survival. The method handles complex data wherein the treatment group to which an individual belongs is unknown at the start of follow-up. The three steps of the CCW method involve cloning or duplicating the patient population and assigning one clone to each treatment strategy, artificially censoring the clones when their observed data are inconsistent with the assigned strategy and weighting the cloned and censored population to address selection bias created by the artificial censoring. The CCW method is a powerful tool for designing RWD studies in cancer that are free from time-related biases and successfully, to the extent possible, emulate features of a randomized clinical trial.

Book review of Guskaroska, A., Zawadzki, Z., Levis, J., Challis, K., Prikazchikov, M. (2024). Teaching pronunciation with confidence. Iowa State University.

Teaching Pronunciation with Confidence is a comprehensive, open educational resource (OER, 2024) aimed at ESL/EFL teachers and learners, with a focus on effective pronunciation teaching. The book was conceptualized by lead author, Guskaroska, who had worked on a course created by Levis with fellow PhD students at that time, Zawadski and Challis. The purpose of the book was to create an online resource for future students in Levis’ pronunciation teaching course that could transform the course’s paper-based activities into interactive online activities, providing immediate feedback for students completing the activities. At the same time, an OER publication offered teachers seeking to integrate pronunciation teaching into their classroom practice an accessible resource that drew on up-to-date technological resources and pedagogical approaches. ESL/EFL teachers and students will appreciate its clear, accessible format and descriptions of research-informed classroom activities that are appropriate for most levels of instruction. Teacher educators of TESOL trainees will find that the book (particularly in Chapters 1 and 2) provides succinct but thorough summaries of the theoretical background and research to ESL/EFL pronunciation teaching. Teacher trainers could find it a useful resource to draw on when preparing professional learning sessions. This review briefly outlines and evaluates each of the book’s sections, including the foundational aspects of pronunciation instruction, segmentals (vowels, consonants), suprasegmentals (stress, rhythm, intonation), and assessment strategies.

A Novel Web App for Dietary Weight Management: Development, Implementation, and Usability Study.

Online weight loss programs have ambiguous efficacy. There is a growing body of evidence that weight loss programs when combined with apps have better outcomes; however, many apps lack an evidence-based approach to dietary changes for weight loss and do not rely on a theoretical framework for behavior change. This study aimed to describe the development and the preliminary usability and acceptability testing of a web app that uses behavior change techniques (BCTs) to support users of a comprehensive online weight loss program. The weight loss program intervention components were nutrient and weight tracking charts that needed a remotely accessible and online format. The app was designed by nutrition researchers and developers in a collaborative effort. A review of BCTs in weight loss and web apps was performed as well as an assessment of user needs to inform the initial prototype. A preliminary app prototype, version 1.0, was provided to participants of a weight loss trial (N=30) to assess for feasibility of its use. A full app prototype, version 2.0, was feasibility and acceptability tested by trial participants (n=11) with formal feedback by Likert-scale survey and open-ended questions. In the final round of testing, a user group of scientists and developers (n=11) was selected to provide a structured 3-month review through which the group met weekly for collective feedback sessions. The process resulted in a fully developed web app, MealPlot, by the Applied Research Institute, for meal planning and weight tracking that can be used by weight loss users and health professionals to track their patients. MealPlot includes a weight chart, a protein-fiber chart, and a chat feature. In addition, MealPlot has 2 distinct platforms, 1 for weight loss users and 1 for health professionals. Selected BCTs for incorporation into the app were goal setting, feedback, problem-solving, self-monitoring, and social support. Version 1.0 was used successfully to provide a functioning, online weight chart over the course of a 1-year trial. Version 2.0 provided a functional weight chart and meal planning page, but 8 out of 11 participants indicated MealPlot was difficult to use. Version 3.0 was developed based on feedback and strategies provided from user group testing. The web app, MealPlot, was developed to improve outcomes and functionality of an online weight loss program by providing a remote method of tracking weight, food intake, and connecting users to health professionals for consistent guidance that is not otherwise available in a traditional in-person health care setting. The final version 3.0 of the web app will be refined based on findings of a review study gathering feedback from health professionals and from actual weight loss users who are part of a clinical weight loss trial.

INTEGRATING INTERTEXTUAL AND COMMUNITY RESPONSE ANALYTICAL LENSES TO TURN SYAIR CENDAWAN PUTIH’S A CHILDREN'S STORY “THE ADVENTURE OF CENDAWAN PUTIH” INTO A SCIENCE LEARNING

This study explores the transformation of the Cendawan Putih poem into prose suitable for children's science learning, examining the adaptation process and public perception. Using a qualitative approach, the study employs intertextual theory to analyze textual transformations such as expansion, conversion, modification, and citation and community response theory to capture stakeholders’ views. The research investigates how the Cendawan Putih poem has been creatively adapted into the children’s story The Adventure of Cendawan Putih to enhance science learning while maintaining cultural and educational value. The findings reveal that adapting Cendawan Putih for children’s literature not only preserves core narrative elements but also integrates science concepts relevant to young readers. The adaptation utilizes techniques such as expansion and modification, enriching the original storyline to highlight nature, ecosystems, and environmental science in an accessible format for children. Public feedback, collected through Focus Group Discussions (FGDs) with cultural figures, educators, academics, and youth, shows broad support for this transformation. Stakeholders emphasize the story’s potential to foster cultural awareness and introduce foundational science concepts, making it an innovative tool for learning. This study highlights how traditional literary forms can be reimagined for children’s science learning, merging cultural heritage with modern educational needs. By presenting Cendawan Putih in a format that supports both cultural preservation and science education, this work positions the story as an intergenerational bridge and a valuable addition to literature-based science learning. It underscores the importance of community involvement in literary adaptation, providing new insights for literature, cultural education, and science pedagogy.

A Systematic Review of Parental Involvement in Digital Cognitive Behavioural Therapy Interventions for Child Anxiety.

Cognitive behavioural therapy (CBT) is an efficacious intervention for child anxiety that has been translated into accessible digital formats, many of which involve parents in treatment. However, the value of parental involvement in treatment is not clearly understood. This systematic review examined characteristics of parental involvement (i.e., format and content of sessions, level of therapist guidance, and parent session compliance) in digital CBT for child anxiety (mean child age ≤ 12years) and their relation to child outcomes (primary disorder remission, clinician-, parent-, and child-rated anxiety, and global functioning). Systematic searches in CINAHL, Embase, ERIC, PsychINFO, PubMed, and Scopus up to 14th August 2023, and citation searching, identified 27 articles (as 23 studies) assessing 14 interventions. Two were parent-only programmes for 3-6-year-old children, with the remaining being parent-child programmes targeting older children. Parents were actively involved as coaches/collaborators, assisting their children with anxiety management and exposure, and less often as co-clients working on their own difficulties. Benefits of treatment were observed across interventions, except for one, psychoeducation-based programme. Higher remission rates were more frequently observed in interventions delivered in controlled settings, those with fewer parent-only sessions, or those incorporating more parent- or therapist-led exposure sessions. Most studies were conducted with affluent samples, limiting generalisability, and several received a high risk of bias rating. Future research should examine parent and family related mechanisms of change and modify interventions for improved adherence, such as restricting the number of modules parents are required to complete and teaching key therapeutic strategies such as exposure early in the programme.

Solar Panel Light Intensity and Voltage Measurement System Using Atmega 328

This research explores the development of a real-time measurement system for light intensity and voltage in solar panels. It utilizes the ATmega328 microcontroller with an INA219 sensor for voltage measurement, a BH1750 sensor for light intensity measurement, and a logger module. The objective of this research is to assist and reduce losses in the use of solar panels. The research method is a simplified version of the 4D model, reduced to 3D: define, design, and develop. This system is designed to accurately collect data directly from solar panels, with a recorded data error rate of 23%. The gathered data is stored via an SD card on the logger module and converted into CSV text format. Test results indicate that this system can measure accurately and store data in a readily accessible and processable format. ATmega328, as the system's core, allows accurate real-time monitoring of solar panel conditions while storing data in CSV format, facilitating further analysis. Therefore, this system can be a valuable tool for monitoring and enhancing the energy efficiency produced by solar panels.

Simulating the Cellular Context in Synthetic Datasets for Cryo-Electron Tomography.

Cryo-electron tomography (cryo-ET) allows to visualize the cellular context at macromolecular level. To date, the impossibility of obtaining a reliable ground truth is limiting the application of deep learning-based image processing algorithms in this field. As a consequence, there is a growing demand of realistic synthetic datasets for training deep learning algorithms. In addition, besides assisting the acquisition and interpretation of experimental data, synthetic tomograms are used as reference models for cellular organization analysis from cellular tomograms. Current simulators in cryo-ET focus on reproducing distortions from image acquisition and tomogram reconstruction, however, they can not generate many of the low order features present in cellular tomograms. Here we propose several geometric and organization models to simulate low order cellular structures imaged by cryo-ET. Specifically, clusters of any known cytosolic or membrane-bound macromolecules, membranes with different geometries as well as different filamentous structures such as microtubules or actin-like networks. Moreover, we use parametrizable stochastic models to generate a high diversity of geometries and organizations to simulate representative and generalized datasets, including very crowded environments like those observed in native cells. These models have been implemented in a multiplatform open-source Python package, including scripts to generate cryo-tomograms with adjustable sizes and resolutions. In addition, these scripts provide also distortion-free density maps besides the ground truth in different file formats for efficient access and advanced visualization. We show that such a realistic synthetic dataset can be readily used to train generalizable deep learning algorithms.

Facilitating catalytic research via better data reporting and curation: A case study of propane dehydrogenation on Ga/H-ZSM-5

In the field of experimental heterogeneous catalysis, the generation, analysis, and curation of large-scale, high-quality datasets are crucial yet challenging. This work highlights the significance of proper data reporting and curation through a case study on propane dehydrogenation over Ga/H-ZSM-5 catalysts. We demonstrate the challenges and benefits of analyzing larger datasets across multiple publications in the identification of active structures and elucidation of reaction mechanisms. The findings highlight the need for reporting reliable datasets in accessible format to facilitate integration and comparison of catalytic data across different studies, potentially leading to novel scientific insights.

Assistive technology and daily living challenges among students with disabilities at University of Gondar, Ethiopia: a qualitative study

Background Disability influences activities of daily living, leading to unsafe conditions, poor quality of life, and dependence on others and assistive technologies. Despite limited access and unmet needs, assistive technology enables users to participate in education and be independent members of their community. Students with disabilities in higher education face many challenges in their day-to-day activities and evidence is limited in the study area. Therefore, this study aimed to explore assistive technology experience and daily living challenges among students with disabilities in higher education. Method A descriptive qualitative study design was employed at the University of Gondar, Gondar, Ethiopia, between December 20, 2022, and January 20, 2023. A purposive sampling method was employed to recruit 14 students with disabilities. An in-depth interview was employed using semi-structured questionnaires. Open Code version 4 software for coding and reflexive thematic analysis approach was employed for the analysis. Result A total of 14 students with disabilities were included in an in-depth interview. Four main themes emerged, which included activities of daily living, attitudes toward people with disabilities, barriers to accessibility, and access to assistive technology. Conclusion Barriers to activities of daily living among students with disabilities were poor accessibility of infrastructural facilities, lack of teaching/learning materials in an accessible format, and negative attitudes. The present study’s finding is needed to support students in higher education for their academic achievement and to design appropriate rehabilitation strategies and policies on the accessibility of physical infrastructures, inclusive education, and the provision of assistive technology

Near Real-Time Responsive Flood Event Representation: An Open-Source Interactive Web Application Architecture

Abstract. The adoption of accessible Digital Twin technology in flood applications has been impeded by a notable lack of practical examples. Arguably, the most distinguishing feature of Digital Twin technology is the integration of near real-time data analytics through IoT sensor connectivity, which has remained underutilised in flood applications and therefore indicates a critical research gap. This project endeavoured to develop a comprehensive and replicable open-source architecture framework, specifically tailored for near real-time responsive flood event representation. The resultant interactive web application integrated near real-time river height and rain fall data streams and performed on-demand data analytics. Key results include the establishment of a back-end spatial database, a coupled physical city and digital space model, and a functional holistic front-end user interface. Additionally, this research aligned with the Gemini Principles by emphasising data interoperability and maintaining an information feedback loop. The study also aimed to configure near real-time IoT sensor connections, implement event triggers, and deliver interactive visualisations in an easily accessible format. The research addressed key questions surrounding the effective integration of IoT sensor data, identification of crucial flood indicators and parameters, and rapid quantification of flood event impacts. Ultimately, this research project demonstrates how Digital Twin technology can swiftly provide decision-makers with crucial insights during flood disaster events.

The maternity dashboard is an effective tool for the improvement of maternal and neonatal care outcomes: a prospective observational study from Iraq

Background: The implementation of maternal dashboards in hospitals is both feasible and effective in improving healthcare quality. The dashboards provide rapid feedback on local outcomes in an accessible format and enable early detection of potential problems. They serve as a simple computerized tool that graphically presents the health facility’s clinical data, utilizing a traffic-light coding system so as to alert front-line staff about changes in the frequency of clinical outcomes. Aim: The aim of this study was to assess the effectiveness of the maternity dashboard in improving maternal health, reducing Neonatal Intensive Care Unit (NICU) admissions, as well as enhancing maternal and neonatal outcomes in an Iraqi hospital. Methodology: Data were collected over one year, from January 1st to December 30th, 2023. A prospective observational study (hospital-based record review) was conducted at the Obstetrics and Gynaecology Teaching Hospital in Kerbala, Iraq. Data were obtained from the medical records of all patients admitted to the obstetrical ward for labor, delivery, and the postpartum period during 2023. The maternal dashboard, a traffic light program (green, amber, red), was used in order to monitor outcomes. Data were collected manually from the outpatient department, the labor ward, the NICU registers, and the electronic records by using Excel. Results: A total of 136,519 women (who were either pregnant, in labor, or postpartum for up to 42 days) were admitted to the Obstetrics and Gynaecology Teaching Hospital in Kerbala during the study period, with 18,791 of them delivering. The implementation of the maternity dashboard resulted in significant changes: the normal vaginal delivery rate increased from 66% to 68% (p=0.0024), the caesarean section rate decreased from 33% to 31% (p=0.0001), the stillbirth monthly cases declined from 16±5 to 12±3 (p<0.05), the NICU admission monthly instances decreased from 96±14 to 71±17 (p<0.05), and early neonatal death monthly cases were reduced from 12±5 to 9±3 (p<0.05). Conclusion: The study results show that maternity dashboards are vital instruments for monitoring and improving the quality of maternity care. They effectively enhance maternal and neonatal care quality indicators when comparing results before and after their implementation.

Large-scale education in respiratory medicine: content versus delivery.

The respiratory literature, both written and in online formats, is growing exponentially. Capturing quality content, to meet the learning needs of those working in all fields of respiratory medicine and delivering it in a palatable, accessible format is challenging but paramount. In this article we discuss ways to determine the information content and review different methods of delivering this content to those who need it.

Enhancing Math education for visually impaired students: alternative text implementation in LATEX, MathJax, MathML and LAMBDA

Abstract This article outlines an innovative procedure to improve the accessibility of Mathematics for secondary school students with visual impairments. Using LATEX, a widely used typesetting system, a transformative approach is developed that converts traditional mathematical content into three accessible formats: PDF, MathJax and LAMBDA. Central to this system is the integration of alternative text, which offers full descriptions of images and mathematical formulae and promotes a richer understanding of its content. The broader implications of this project include the introduction of novel teaching models for educators, enhanced accessibility of Mathematics programmes, and the potential to encourage the enrolment of visually impaired students in science degree courses. Ultimately, this work contributes to the creation of the conditions for the development of an inclusive and barrier-free learning environment in Mathematics education.

Providing accessible health information for people with disability in a public health crisis: A qualitative study of the experiences of Australian accessible information provider organizations during the COVID-19 pandemic

BackgroundDuring the COVID-19 pandemic, people with disability had a right and an acute need to access accessible COVID-19 information, in formats such as sign language, Braille, large print and Easy Read/English. Yet such information was not always provided and many people with disability were without sufficient accessible information. ObjectiveThis paper explores the experiences of Australian accessible information provider organizations of producing accessible information during the pandemic. The intent is to understand why insufficient accessible information reached people with disability. MethodsIn-depth interviews were conducted with 17 accessible information provider organizations and one other stakeholder in Australia, and thematically analyzed. ResultsThe findings show that accessible information provider organizations felt an immense depth and breadth of responsibility for providing accessible information to people with disability during the pandemic. However, they were hampered by constantly changing information; workforce challenges; and a lack of financial, logistic and partnership assistance. Other notable difficulties included having no source of clear/accurate information to translate to accessible formats and not having medical/health expertise themselves. ConclusionThe findings have implications for better preparation for accessible information access in future public health crises. There should be greater funding and logistic support for accessible information provider organizations. Provision of clear/accurate information and subject matter checks of accessible products would be helpful. Responsibility for this should be scoped into existing outreach, education and communications roles – for example, in local health services, general practice clinics and government health departments.

TEMPORARY REMOVAL: Understanding gaps in early detection of and rapid response to invasive species in the United States: A literature review and bibliometric analysis

While concepts regarding invasive species establishment patterns and eradication possibilities have long been a topic of invasion biology, the specific terminology referring to early detection of and rapid response to (EDRR) invasive species emerged in scientific literature during the early 2000s. Since then, the EDRR approach has expanded to include a suite of detection, planning, and management tools. By conducting a systematic literature review, we attempt to characterize the field of EDRR in the United States and its territories as reflected by publication records. Specifically, we assessed publication data such as the number of publications per year, the most common journals where papers were published, and the relationship between author's keywords for studies focusing on aquatic and terrestrial habitats. For publications that used invasive species occurrence or abundance data (whether collected for the purposes of the respective publication or acquired from another data source), we manually vetted additional information such as focal taxa, data collection years and locations, sources of other data used, and whether data or code were deposited in open access formats. We also conducted network analyses for the author institutions that coauthored papers together most frequently and for the references most cited by EDRR publications. Overall, we found that silos existed in terms of which author institutions worked together, which existing literature was cited, and which topics were frequently explored. We also found evidence of substantial gaps in data access and use. For example, although a wide variety of data sources for invasive species occurrences are available, these sources were seldom cited by published literature, and newly collected data was not often deposited into invasive species databases or other open-source data repositories. Considering the continued advocation for a centralized national EDRR information system, our study suggests that facilitating access to data, decision support tools, and other informational resources represents a key opportunity for improving EDRR capabilities.

Enhancing Junior Doctors' Preparedness and Satisfaction in Trauma and Orthopaedics: A Quality Improvement Project With the Development of a Comprehensive Guidebook.

Junior doctors often feel underprepared for their trauma and orthopaedics (T&O) rotation due to limited exposure during medical school and inadequate support. This project aimed to enhance junior doctors' preparedness and satisfaction during their T&O rotation by developing a comprehensive guidebook that addresses key orthopaedic knowledge and logistical challenges. A quality improvement project (QIP) was conducted at Ysbyty Gwynedd Hospital. Initial surveys identified factors contributing to poor experiences during the trauma and orthopaedics rotation, including limited knowledge of orthopaedic emergencies and a lack of useful reference resources. A guidebook was developed and refined through multiple plan-do-study-act (PDSA) cycles. The guidebook covered topics such as orthopaedic emergencies, common injuries, referral pathways, and hospital logistics, presented in an accessible flowchart format. The primary objective of achieving 75% satisfaction among junior doctors was successfully met, with satisfaction increasing from four (40%) to eight (80%) doctors in the most recent survey. Secondary outcomes included a marked improvement in the understanding of quality improvement projects, rising from three (30%) to eight (80%) doctors. Orthopaedic knowledge also saw a significant enhancement, increasing from four (40%) to nine (90%) doctors. Confidence in handling night on-call duties improved dramatically, with all 10 doctors (100%) reporting increased confidence, compared to four (40%) doctors initially.Additionally, seven doctors (70%) expressed a greater interest in pursuing a career in orthopaedic surgery. The comprehensive guidebook significantly improved junior doctors' preparedness and satisfaction during their T&O rotation. While the guidebook is a valuable resource, ongoing mentorship and hands-on experience remain essential for long-term success. Replication of this project across other departments and hospitals is recommended to assess its broader applicability and impact.

Metroticket approach in a retrospective cohort study to predict overall survival after surgical resection for intermediate stage hepatocellular carcinoma.

Surgical resection is a curative therapy for early-stage hepatocellular carcinoma (HCC) patients meeting the Milan criteria as well as a widely used therapy in intermediate-stage HCC. However, intermediate-stage HCC encompasses a wide spectrum of disease and there is a lack of good predictive models for the long-term clinical outcome of HCC patients currently. Here, we adopt Mazzaferro's Metroticket 2.0 to create a robust survival prediction model for intermediate-stage HCC patients undergoing surgical resection. Our algorithm considers age, AFP levels, ALBI score, and nodule size/number to generate survival estimates in an accessible graph format. Importantly, our model surpasses the American Joint Committee on Cancer staging model and was validated with independent US patient data. We conducted a retrospective analysis of OS and RFS in early- and intermediate-stage HCC patients treated with liver resection, including a training cohort in Singapore and a validation cohort in North Carolina, USA. We recorded 278 deaths (35.0%) and 428 patients (53.9%) in the first 5-years after surgical resection; higher ALBI score, higher lnAFP, more advanced age and higher tumour burden index were identified as significant parameters. The overall predictive capability of our model, with the inclusion of AFP, is reflected with a UNO's C-statistic of 0.655, which is 1.11 times better than the 0.5895 C-statistic of the 8th AJCC TNM Staging model. Our modified Metroticket model allows for more granular and better-informed prognostication. This will help surgeons and patients make accurate comparisons between the clinical outcomes of surgical resection and other non-surgical treatments.

The moving project: exploring language, migration, and identity using participatory podcasting during the COVID-19 pandemic

Abstract I make Accentricity, a podcast exploring language and identity. After releasing series 1 in 2019, I began to plan ways to take a more participatory approach to the creation of a second series, involving contributors in the production process as co-creators. The result was The Moving Project: a podcasting course and mentorship programme designed to help people tell personal stories about language, migration, and identity. Over a period of six months, the participants developed their audio-recording, editing, and digital storytelling skills. Together we created a podcast series which tells diverse and complex stories about migration, language, and identity, from a range of different geographical, social, and historical contexts. Like the first series of Accentricity, The Moving Project provides information about language to a public audience in an accessible format. However, it goes much further than the first series in centring non-academic perspectives and in developing participatory and inclusive methods for knowledge co-production.