Accessible data collection methods in clinical trials: Do current best practices for the implementation of electronic patient-reported outcome measures (ePROMs) meet accessibility standards?

Accessible data collection methods in clinical trials: Do current best practices for the implementation of electronic patient-reported outcome measures (ePROMs) meet accessibility standards? | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Accessible data collection methods in clinical trials: Do current best practices for the implementation of electronic patient-reported outcome measures (ePROMs) meet accessibility standards? Florence Daisy Mowlem, Paul O'Donohoe This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5741400/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Apps and web browsers, whether on smartphones, tablets or laptops, have become the mainstream methods of capturing clinical outcome assessment (COA) data, and patient-reported outcome measures (PROMs) in particular, in clinical trials. There has long been concern around whether implementing traditionally paper-based questionnaires on electronic systems may impact the measurement properties of these carefully validated questionnaires, with migration best practices focusing predominately on this issue. In parallel, app and web-design best practices outside of clinical research have focused on the accessibility and usability of these electronic systems for the widest range of users. Methods This article evaluates how existing Web Content Accessibility Guidelines (WCAG 2.2) compare to electronic PROM (ePROM) design best practices, identifying where there is alignment or tension, where further evidence is needed to ensure both accessibility and the maintenance of the questionnaire measurement properties, and what accessibility practices can be incorporated into ePROM design best practices today. Results Many of the accessibility criteria can be applied to electronic clinical outcome assessment (eCOA) systems now without concern for the integrity of the measure, given their focus is on the software being programmed and built to support content being implemented in a way that enhances overall accessibility and its usability with assistive technologies. The main tensions identified between the accessibility success criteria and ePROM best practices concerned increasing content size and device orientation. Conclusions Many accessibility best practices can be adopted in ePROM implementations today , and we must strive to achieve a point where accessibility best practices are (e)PROM best practices to ensure electronic data capture is accessible and usable, leading to more representative trials that are lower burden for patients. accessibility ePRO eCOA diversity burden migration Figures Figure 1 Figure 2 Background Accessibility encompasses the extent to which products and services for a specific context of use can be used by individuals with the widest range of characteristics and capabilities possible 1 . It is a key element of supporting diversity, equity, and inclusion; without accessibility, these cannot truly be achieved as certain subgroups will be excluded from easily engaging with the products and services 2 . While accessibility of app- and web-based solutions for all potential users has long been a driving force of design outside clinical research, this article focuses on accessibility in the context of the electronic capture of data from patient-reported outcome measures (PROMs). In the last 20 years, electronic capture of clinical outcome assessments (COAs), in particular PROMs (ePROMs), utilizing web- and app-based systems, has become the mainstream method of data collection in clinical trials due to the benefits offered compared to pen-and-paper 3 . The importance of accessibility and usability in PROM development and implementation is starting to be recognized by regulators 4 , 5 . Specifically, in their most recent patient focused drug development (PFDD) guidance series, the US Food and Drug Administration (FDA) addresses the benefit of “universal design” for COAs and the importance of ensuring accessible data collection methods, with specific reference to electronic data capture and assistive technologies. This means ensuring the design and composition of a COA enable it to be accessed, understood, and used to the greatest extent possible by all people, including those with disabilities, and can facilitate broad inclusion in trials. 5 Patients, like the general population, may be impacted by impaired functioning in a range of domains that can affect their interaction with data collection methods, including impaired cognitive function, vision impairment, impaired fine motor control, low literacy, and learning difficulties. While such challenges may have been life-long and independent of their reasons for being engaged in clinical research, these patients face the additional challenge that such issues may be a symptom of their condition or a side-effect of treatment, and can impact their use of technology for completing PROMs 6 within the context of attempting to better understand that condition or treatment. To date, best practices for developing and implementing ePROMs has largely ignored accessibility as understood in the context of universal design, arguably to the significant detriment of clinical research and, more importantly, patients. In their PFDD Guidance, FDA direct the reader to review the World Wide Web Consortium (W3C) Web Accessibility Initiative (WAI) recommendations, as well as Section 508 of the US Government website (that requires Federal agencies to ensure that their Information and Communication systems are accessible to individuals with disabilities, in a way that is comparable to those without disabilities) to ensure a PROM will be accessible for individuals with certain impairments 5 . However, to date there has not been broad adoption, nor consideration of how this may create a tension with existing ePROM design best practices, which are also referenced in the same guidance. The aim of this article is to review the web accessibility success criteria through the lens of ePROM design and implementation best practices to identify points of alignment and points of incongruence. We begin by providing a brief description of web accessibility criteria and history of ePROM design best practices to set the context for the comparison between the two. Considerations will be provided for how accessibility success criteria might be incorporated into future ePROM best practices and where further research is recommended to demonstrate the maintenance of the measurement properties of the ePROM, pointing towards a future of clinical research solutions which not only ensure high quality data capture, but are also accessible and supportive for the greatest array of participants, ultimately giving us greater confidence in our understanding of novel treatments. Accessibility Guidelines Accessibility of web solutions is usually evaluated through a conformance assessment based on the W3C Web Content Accessibility Guidelines (WCAG 2.2) 7 , which list 13 guidelines organized around 4 principles (see Fig. 1.), with corresponding success criteria that are classified into 3 levels, from lowest to highest conformance (A, AA, AAA) 7 . All four principles must be true for users with disabilities to be able to readily use the web. These four principles are also outlined in EU legislation to ensure websites and mobile applications are accessible 8 . Figure 1. The four Web Accessibility Guideline principles from W3C 7 W3C acknowledge that whilst there are some slightly different considerations for accessibility on mobile devices (i.e., smartphones and tablet devices) as compared to desktop/laptop, there is no absolute divide and common features exist (e.g., both can include touchscreen control, the use of external keyboards, and responsive design), and so “Overall, WCAG 2.0 is highly relevant to both web and non-web mobile content and applications ”. 9 Nevertheless, W3C published discussion of mobile-related issues to support accessibility, with additional best practices where needed. This is relevant to ePROMs, which are predominately deployed using app and web on mobile devices, and to a lesser degree desktop/laptop. ePROM Best Practices Historically, best practices for the implementation of ePROMs has focused on the issue of “faithful migration” 10 , 11 and ensuring electronic implementations of originally paper-based questionnaires capture comparable data. This is generally a story of concern about minor changes in visual layout potentially leading to participants responding differently to questions about how they are feeling and functioning. This concern was largely driven by the 2009 FDA Guidance on the use of PROMs in medical product labelling 12 , which stated that “When a PRO instrument is modified, sponsors generally should provide evidence to confirm the new instrument’s adequacy” and explicitly referred to modification including “changing an instrument from paper to electronic format” (pp. 20). An ISPOR Task Force Report 13 expanded on this statement, recommending that testing is conducted to confirm the comparability between modes of administration. These recommendations had a lasting influence. In the 15 years since these seminal publications, large amounts of research have repeatedly demonstrated the comparability of PROMs when migrating from paper to electronic format for common item and response scale types 14 – 19 , in addition to measurement comparability between electronic formats for bring-your-own-device (BYOD) implementations 17 , 18 , 20 . This body of research has culminated in updated industry recommendations that further studies of measurement comparability are not needed in cases where modifications to the migrated questionnaire are minor-to-moderate, sufficient comparability evidence exists, and importantly, best practices for migration are followed 11 . The historical focus on mitigating the risk of non-comparability is understandable given these measures often support key endpoints in pivotal trials and play a role in the ultimate success (or otherwise) of bringing a new compound to market. However, this has incentivized the pursuit of a reduction in variability in layout and presentation of content, and has meant that, in general, electronic applications for capturing PROMs have remained staunchly inflexible in design and layout, and not prioritized (or considered at all) inclusive design principles. Shifting Focus Arguably, this historic focus has been at the expense of optimizing the user experience of interacting with the technology, and the industry has been slow to explore alternative ways of presenting PROMs on screen-based devices – presentations that are often very common in other contexts. For example, it is only recently the first investigation on the impact of scrolling on ePROM implementations was published 20 . Scrolling has long been used in non-ePROM contexts to allow for the presentation of content without having to reduce font size to an unusable degree, but has historically been advised against in ePROMs due to concerns that if users are required to scroll to see all response options it may bias their responses 21 . While Shahraz et al. 20 found scrolling did not negatively impact the measurement properties, they still conservatively recommended the avoidance of scrolling. More generally, measures developed in electronic format ab initio still tend to follow existing best practices despite their primary focus being on migration from paper format, rather than taking full advantage of their screen-based modes of data capture and the flexibility this allows in making content accessible for the widest range of users. As an industry, we must hold ourselves accountable and challenge ourselves to consider whether the desire to strictly control how PROMs are administered and implemented on electronic modes of data capture due to a fear of negatively impacting measurement properties, has actually led to suboptimal solutions which are not as user-friendly and accessible for a broad range of individuals. As a consequence, this raises the concern of whether we are collecting data in a suboptimal manner from non-representative populations, reducing the utility of data in a trial, and, ultimately, risking the success of bringing a new compound to market. It is worth noting that the adaptability of screen-based designs affords us the opportunity to make content more accessible and usable. Traditional paper-and-pen lack any of this flexibility and can be extremely difficult, if not impossible, for certain populations to use. However, moving from paper-and-pen to electronic capture of PROMS, while offering a wealth of benefits, can still create barriers for some individuals if not approached thoughtfully. Whilst the recent updated best practices for migration and electronic implementation paid greater attention to respondent usability and accessibility than previous iterations 11 , there is much more to be done. Without consideration of the functional, sensory, physical and cognitive abilities of users of technologies in clinical trials, electronic data capture methods can easily be implemented in ways that cause difficulties for certain populations or exclude them altogether. We cannot take it for granted that digital tools increase diversity, especially in the absence of due consideration to accessibility. Methods Each WCAG 2.2 success criteria, inclusive of mobile specific guidance, will be evaluated in relation to current ePROM best practices (from Mowlem et al. 11 ), to identify areas of alignment or incongruence. Consideration for how the success criteria might affect ePROM implementation, as well as possible future areas of research to better understand the impact on measurement properties, will also be provided. Given ePROM design best practices focus on the actual measure, its visual presentation, and ensuring the integrity and quality of the data captured, the criteria will be considered from the perspective of how the measure is displayed, rather than the broader eCOA system (i.e., the app or website users log into to access the ePROMs). However, where certain criteria are relevant to the electronic system more widely but would not have a direct impact on the actual measure, comment will be provided. Of note, the assumption is that the measure itself has been well-designed and is fit-for-purpose. Findings Table 1 lists the WCAG 2.2 accessibility success criteria that are relevant to screen-based ePROM data capture systems, compares them to current ePROM best practices, and provides considerations for incorporating accessibility success criteria into future ePROM best practices. Additional guidance relevant only to mobile devices is detailed in Table 2 . Note, a classification level has not been allocated to any of the mobile specific guidance. For all WCAG 2.2 success criteria, including those that are not applicable to ePROMs, see Supplementary Material Table 1. Many of the accessibility criteria address programming of the software to ensure content is implemented in a way that enhances overall accessibility and can be reliably interpreted by assistive technologies (e.g., screen readers, magnifiers), by accounting for them at the point of software development. Table 3 lists the accessibility practices that could be applied to eCOA systems now without concern for the integrity of the measure, given their focus is not on changing the measure content or the mode of administration, but the software being programmed and built in a way that enhances the overall accessibility and its usability with assistive technologies. Consistent testing of the system for compatibility with assistive technologies is encouraged, and the impact of the actual use of assistive technologies on measure integrity should be explored further. Beyond considerations for assistive technologies, the main tensions between accessibility success criteria and ePROM best practices identified in this evaluation concerned the ability to increase content size and device orientation. Increasing the size of content Current ePROM best practice is to enable vertical scrolling (horizontal is not recommended) instead of reducing text to a small enough size that it could cause reading difficulties. However, some still caution against the use of scrolling when implementing ePROMs 20 and some measure copyright holders do not allow scrolling. Further, the amount of scrolling required for a given item tends to be programmed as the same for all users (i.e, the text size is still dictated by the system as opposed to allowing the user to alter it or presenting content at the size set on the device), and so may still not satisfy the text size required by some users. Some have even recommended, with best intentions regarding the maintenance of measurement properties, that in BYOD scenarios the user should not be able to over-ride specific app display settings 20 , including font size 16 . The use of zoom has not yet been addressed in ePROM best practices and has only recently received attention in research 22 , with preliminary findings showing measurement comparability. In contrast, WCAG 2.2 success criteria indicate that it should be possible for users to increase text size up to 200% without the loss of content or functionality; that is, it reflows (wraps) with scrolling in one dimension (i.e., vertically). Given the reducing concern around scrolling on the impact of an ePROMs measurement properties 11 , 20 , and upcoming work extending this to zoom functionality 22 , it is worth considering if 200% text resizing or zooming should be possible for users, combined with the existing recommendations around how to implement scrolling functionality outlined in Mowlem et al. 11 Based on accessibility guidelines, it will be important that zooming does not lead to scrolling in two dimensions (i.e., vertically and horizontally). It is also recommended that further research on the impact of zooming and text resizing on the measurement properties of an ePROM is conducted, including understanding the most optimal method based on user preference. This should include the full item, inclusive of the response options for all response scale types (verbal rating scale, numeric rating scale, visual analogue scale), and not focus only on increasing the size of the item stem (i.e., the question text or statement to be rated). Orientation Current ePROM best practice is to keep the device orientation consistent, along with recommending that ePROMs are presented in portrait on smartphones, and that respondents should not be able to manually alter the orientation (e.g., through rotation of the device). Of note, this is not referring to changing the orientation of the response scale types themselves (e.g., an NRS being presented vertically rather than the traditional horizontal). In contrast, WCAG 2.2 success criteria states that users should be allowed to switch the orientation of their device between portrait and landscape as they wish, unless a certain orientation is deemed essential to the content. To date, there has been no published evidence that changing device orientation - or using one orientation over the other - would impact the measurement properties of the PROM. Therefore, it is difficult to argue that a given orientation is essential to the content being presented. The intent of the ePROM best practice recommending against allowing users to switch orientation is to facilitate standardization of the presentation of measures across respondents and eliminate the risk or formatting issues tied to changing orientation. However certain populations, such as those who have dexterity impairments, may benefit from a mounted device in a specific orientation, and so this ePROM best practice should be reconsidered. As system providers develop their software, the ability of content to function in either orientation and allowing users to switch to their preferred orientation, as well as the programmatic exposing of the orientation to assistive technologies, should be included and tested adequately. Conducting research on the measurement comparability between orientations could also help mitigate any concerns that the integrity of the measure could be impacted. Recommendations for further research In addition to the areas identified above (the impacts of assistive technology, orientation, zooming, and text resizing), it is recommended that the following are the subject of future studies to enable a clear understanding on whether meeting the accessibility criteria would impact the measurement properties of the PROM: horizontal vs vertical presentations of the NRS (this could extend to the VAS, but given this is not a recommended response type for an accessible measure, the NRS should be the focus) (related to 2.5.8 Target Size [Minimum], see Table 1 ) the impact of saving partially completed measures and completing them later on the reliability of the data, and potential time limits for this (related to 2.2.6 Timeouts, see Table 1 ) Implications for measure development As mentioned, the focus of this evaluation was on the implementation of the PROM in an electronic system, under the assumption that the measure itself has been well-designed and is fit-for-purpose. If the PROM itself (regardless of mode of administration) has not been developed in an accessible way, then this fundamental lack of accessibility is unlikely be resolved through electronic implementation (e.g., the VAS will be inherently difficult for vision-impaired individuals to complete in any mode). That said, the following are recommended to make existing PROMs accessible and ensure the accessibility of new measures. For existing measures: create and validate text alternatives for non-text content (e.g., image-based response options) that can be provided when the measure is licensed for electronic implementation if instructional text relies solely on sensory characteristics, create and validate versions that provide additional information to clarify instructions dependent on this kind of information if color is the only way to convey certain information, create and validate versions where this is not the case For new measures: create text alternatives for images at the time of measure creation do not use the VAS as a response type do not use content that relies solely on sensory characteristics do not use color as the only means to convey information Table 1 about here Table 2 about here Table 3 about here Discussion To date in the field of electronic capture of PROMs in clinical trials, there has been greater focus on the comparability of the electronic implementation to the paper format rather than to the general accessibility of these technology driven solutions. Best practices for ePROMs have largely been developed by individuals in the field of outcomes measurement and eCOA research who have different disciplinary priorities compared to those working in more general web- and app-based solutions, resulting in tensions between ePROM design best practices focused on maintaining measurement properties, and general web- and app-design best practices to provide solutions that are accessible to all. The clinical trial industry prides itself on being “patient-centric” yet has been slow in adopting relatively simple and widespread technologic solutions that can address common challenges for users of technologies. Recent ePROM best practices have brought stronger consideration to usability and accessibility but further progress is needed, with much to learn from the world of good web and app design. This article has outlined that many accessibility best practices can be incorporated into ePROM implementations today , most of which are focused on the programming of the software and criteria that will not alter the content of a PROM - it is urged that those who develop these data capture systems adopt these wherever possible. Recommendations for further research that may be required to support accessible approaches without impacting the measurement properties of the PROM were also outlined. The focus here was specifically on the accessibility of the ePROM implementation as opposed to the eCOA system more widely, given this is what is addressed by current ePROM best practices 11 . However, from the user perspective it is unlikely that they differentiate their interaction between the implementation of the actual measure and the wider system, such as the app or website users access the ePROM through. Whether this separation is a logical one should be considered when developing future best practices. Further, the actual use of assistive technologies for accessing and completing ePROMs and how this may impact measurement comparability was beyond the scope of this paper, but requires further thought and discussion; for example, understanding if completion of a measure by those using a screen-reader versus those who are not leads to measurement non-comparability. ePROM best practices have been largely focused on reducing variability between modes of administration, and so allowing users to engage with the content of a measure via an assistive technology, for example a screen reader, is a significant change in thinking for the industry. However, it is worth noting that from the earliest days of ePRO we have been displaying questions and response options on a single, relatively small screen, which is already a significant visual departure from the multiple questions and response options seen on paper. The evidence has consistently shown that PROMs are robust in regard to changes in mode of data collection, and even so called ‘significant’ changes in administration and visual layout have consistently shown to provide comparable data. However, considering the importance of the data being captured, increasing the evidence base will facilitate the development of increasingly user-centric solutions through which there is potential to improve data quality. Without data we can trust, we cannot bring safe and effective treatments to all individuals. This will also be key to having regulatory agency confidence in ePROM implementations that adopt accessible practices that could be deemed a significant departure from the paper format. It would be remiss to discuss ePROM implementation without reference to the authors and copyright holders of these measures, who often have their own requirements for implementation that are sometimes at odds with both ePROM best practices and accessibility best practices. This dynamic can present a challenge to improving the participant experience in clinical trials. For example, some require that the anchor text associated with the extremes of a horizontal NRS must not extend past the length of the highest and lowest numbers into the middle of the scale (i.e., the number 0 and number 10 on an 11-point scale); making the anchor text smaller, text-wrapping and/or splitting single words across lines to meet this requirement can run the risk of causing readability issues and fly in the face of accessibility guidelines (see Fig. 2 for examples). Given the time-sensitive nature of the trial set-up process, discussions with measure authors/copyright holders around electronic implementations that deviate from ‘the norm’ but are arguably more accessible (whilst maintaining the integrity of a measure) often fall by the wayside; this must change for us to progress. As an industry, the goal of all stakeholders involved should be to make electronic data capture more accessible and usable, leading to more representative trials that are lower burden for patients. We should ask ourselves if we have lost sight of the intention of these measures? They are developed for use in specific therapeutic populations, yet electronic implementation guidelines can oftentimes make them difficult to use for those exact populations. Finally, the criticality of consensus-based best practices was highlighted in Mowlem et al. (2024) 11 , and it is important to acknowledge that the aim of this article is not to recreate and dictate new best practices, as the WCAG and 508 accessibility success criteria already exist. Rather, it was to identify where existing accessibility guidelines may not currently be being met in ePROM design and where they should be applied, and where further evidence is required before they are more-formally integrated into ePROM best practices. It is important that best practices are updated as the evidence-base advances. Whilst this article focused on the electronic implementation as opposed to the instrument itself, it is clear that accessibility and universal design best practices start from the point of PROM development - whatever format that may be – to ensure a fit-for-purpose, valid, and accessible PROM. We must get to a point where accessibility best practices are (e)PROM best practices. Declarations Ethics approval and consent to participate: Not applicable Consent for publication: Not applicable Availability of data and materials: Not applicable Competing interests: FM is employed by uMotif. POD is employed by Medidata. Funding: Not applicable Author contributions: FM was responsible for conceptualization of the work. FM and POD were responsible for interpretation, drafting, and revising of the work. Acknowledgements: The author wishes to thank Bruce Hellman and James Fenlon for their insightful feedback and discussions during the creation of this manuscript. References International Organization for Standardization. ISO 26800:2011(En) Ergonomics — General Approach, Principles and Concepts. (2011). Integrating Accessibility into Agency Diversity. Equity, Inclusion and Accessibility (DEIA) Implementation Plans. https://www.section508.gov/manage/deia-guidance/ (2024). Coons SJ et al. Capturing Patient-Reported Outcome (PRO) Data Electronically: The Past, Present, and Promise of ePRO Measurement in Clinical Trials. Patient vol. 8 301–309 Preprint at https://doi.org/10.1007/s40271-014-0090-z (2015). European Medicines Agency. Guideline on Computerised Systems and Electronic Data in Clinical Trials. https://www.ema.europa.eu/en/documents/regulatory-procedural-guideline/draft-guideline-computerised-systems-electronic-data-clinical-trials_en.pdf (2021). U.S. Department of Health and Human Services Food and Drug Administration. Patient-Focused Drug Development: Selecting, Developing, or Modifying Fit-for-Purpose Clinical Outcome Assessments. (2022). Mowlem FD, Sanderson B, Platko JV, Byrom B. Optimizing electronic capture of patient-reported outcome measures in oncology clinical trials: lessons learned from a qualitative study. J Comp Eff Res 9, (2020). WAI (Web Accessibility Initiative). WCAG 2 Overview. https://www.w3.org/WAI/standards-guidelines/wcag/ The European Parliament and the Council of the European union. DIRECTIVE (EU) 2016/2102 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 26 October. 2016 on the Accessibility of the Websites and Mobile Applications of Public Sector Bodies. ( https://www.legislation.gov.uk/eudr/2016/2102/introduction#:~:text= (9)%20This%20Directive%20aims%20to,basis%20of%20common%20accessibility%20requirements., 2016). W3C. Mobile Accessibility: How WCAG 2.0 and Other W3C/WAI Guidelines Apply to Mobile. (2015). O’Donohoe P et al. Updated Recommendations on Evidence Needed to Support Measurement Comparability Among Modes of Data Collection for Patient-Reported Outcome Measures: A Good Practices Report of an ISPOR Task Force. Value in Health In press, (2023). Mowlem FD, et al. Best Practices for the Electronic Implementation and Migration of Patient-Reported Outcome Measures. Value Health. 2024;27:79–94. U.S. Food and Drug Administration. Guidance for Industry Patient-Reported Outcome Measures: Use in Medical Product Development to Support Labeling Claims. (2009). Coons SJ, et al. Recommendations on evidence needed to support measurement equivalence between electronic and paper-based patient-reported outcome (PRO) measures: ISPOR ePRO good research practices task force report. Value Health. 2009;12:419–29. Gwaltney CJ, Shields AL, Shiffman S. Equivalence of electronic and paper-and-pencil administration of patient-reported outcome measures: A meta-analytic review. Value Health. 2008;11:322–33. Muehlhausen W et al. Equivalence of electronic and paper administration of patient-reported outcome measures: A systematic review and meta-analysis of studies conducted between 2007 and 2013. Health Qual Life Outcomes 13, (2015). Muehlhausen W, et al. Standards for Instrument Migration When Implementing Paper Patient-Reported Outcome Instruments Electronically: Recommendations from a Qualitative Synthesis of Cognitive Interview and Usability Studies. Value Health. 2018;21:41–8. Byrom B, et al. Measurement Equivalence of Patient-Reported Outcome Measure Response Scale Types Collected Using Bring Your Own Device Compared to Paper and a Provisioned Device: Results of a Randomized Equivalence Trial. Value Health. 2018;21:581–9. Hudgens S et al. Comparability of a provisioned device versus bring your own device for completion of patient-reported outcome (PRO) measures by participants with chronic obstructive pulmonary disease (COPD): Quantitative study findings. Value Health 21, (2018). Byrom B et al. Measurement Comparability of Electronic and Paper Administration of Visual Analogue Scales: A Review of Published Studies. Therapeutic Innovation and Regulatory Science vol. 56 394–404 Preprint at https://doi.org/10.1007/s43441-022-00376-2 (2022). Shahraz S et al. Does scrolling affect measurement equivalence of electronic patient-reported outcome measures (ePROM)? Results of a quantitative equivalence study. J Patient Rep Outcomes 5, (2021). Eremenco S, et al. PRO data collection in clinical trials using mixed modes: Report of the ISPOR PRO mixed modes good research practices task force. Value Health. 2014;17:501–16. McDowell B et al. Accessibility Vs Standardization: A Study of Electronic Implementation of Patient-Reported Outcomes Measures with Vision-Impaired Participants. Value Health 26, (2023). U.S. Food and Drug Administration. Digital Health Technologies for Remote Data Acquisition in Clinical Investigations. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/digital-health-technologies-remote-data-acquisition-clinical-investigations (2022). Tables Tables 1 to 3 are available in the Supplementary Files section. Additional Declarations Competing interest reported. FM is employed by uMotif. POD is employed by Medidata. Supplementary Files MowlemODonohoe2024WCAGSupplementaryMaterial.docx Table13.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5741400","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":396841569,"identity":"c95573cd-1cb1-4e6e-a272-f60f73d53626","order_by":0,"name":"Florence Daisy Mowlem","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+0lEQVRIie3PMWrDMBSA4WcMzuIkWzAY7CvYGDKF9CpPCOQl3TsUIigoU/aYXCJTyCgQuEvmUtDiIySbO7TUdqGYYpt0y6B/kZ7QhxCAyXSHjTbtqQAImg0u+omr2hMCJNVicWT/IITXBIaIbeeX62kZwEzlHj4d08Obei0KhHA6kz3EoVl2pgn4jHl41o8HzQhHhDjbYyd5sN3EHgtJuL+avxNRk1XMSQkY6W7i1uRTyPUP+dJpVJPqlWFiCYnQEK7xBuJQaytoLHyWlpjrOKv+skP0ev/ijl4UfIhlOPWpii7POpxoKq8lLqqTbvKb82f2hq+bTCaTabBvy1hdB7YJyswAAAAASUVORK5CYII=","orcid":"","institution":"umotif","correspondingAuthor":true,"prefix":"","firstName":"Florence","middleName":"Daisy","lastName":"Mowlem","suffix":""},{"id":396841570,"identity":"5d6de656-a535-486d-becc-4461360ec381","order_by":1,"name":"Paul O'Donohoe","email":"","orcid":"","institution":"Medidata Solutions (United States)","correspondingAuthor":false,"prefix":"","firstName":"Paul","middleName":"","lastName":"O'Donohoe","suffix":""}],"badges":[],"createdAt":"2024-12-31 10:38:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5741400/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5741400/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":73079161,"identity":"90aca83c-830e-4bd0-b99c-fcf1b308e825","added_by":"auto","created_at":"2025-01-06 13:54:13","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":53731,"visible":true,"origin":"","legend":"\u003cp\u003eThe four Web Accessibility Guideline principles from W3C7\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5741400/v1/e971b6b35e970b5357378c62.jpg"},{"id":73079163,"identity":"138bfd57-eaac-4f9f-a779-cbd30687faad","added_by":"auto","created_at":"2025-01-06 13:54:13","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":37245,"visible":true,"origin":"","legend":"\u003cp\u003eIllustration of a numeric rating scale (NRS) in a paper format that has been migrated to electronic format with differing anchor text size and text wrapping\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5741400/v1/2cb7517b6968d4df0bf1ba27.jpg"},{"id":79359914,"identity":"090d3c7e-8320-451f-8374-64b927e35eda","added_by":"auto","created_at":"2025-03-27 12:08:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":670476,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5741400/v1/015045e0-3369-47e0-bf4e-c649c1812167.pdf"},{"id":73079162,"identity":"b26c59c9-790b-4cd7-a2bc-dff919d741b8","added_by":"auto","created_at":"2025-01-06 13:54:13","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":93796,"visible":true,"origin":"","legend":"","description":"","filename":"MowlemODonohoe2024WCAGSupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-5741400/v1/178eab9a490e24c27965079c.docx"},{"id":73079164,"identity":"ae40682e-482e-4bb5-8f17-7cc5d3cdf38e","added_by":"auto","created_at":"2025-01-06 13:54:13","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":96280,"visible":true,"origin":"","legend":"","description":"","filename":"Table13.docx","url":"https://assets-eu.researchsquare.com/files/rs-5741400/v1/cd30c96d8d97ee150b910c30.docx"}],"financialInterests":"Competing interest reported. FM is employed by uMotif. POD is employed by Medidata.","formattedTitle":"Accessible data collection methods in clinical trials: Do current best practices for the implementation of electronic patient-reported outcome measures (ePROMs) meet accessibility standards?","fulltext":[{"header":"Background","content":"\u003cp\u003eAccessibility encompasses the extent to which products and services for a specific context of use can be used by individuals with the widest range of characteristics and capabilities possible \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. It is a key element of supporting diversity, equity, and inclusion; without accessibility, these cannot truly be achieved as certain subgroups will be excluded from easily engaging with the products and services\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. While accessibility of app- and web-based solutions for \u003cem\u003eall\u003c/em\u003e potential users has long been a driving force of design outside clinical research, this article focuses on accessibility in the context of the electronic capture of data from patient-reported outcome measures (PROMs). In the last 20 years, electronic capture of clinical outcome assessments (COAs), in particular PROMs (ePROMs), utilizing web- and app-based systems, has become the mainstream method of data collection in clinical trials due to the benefits offered compared to pen-and-paper\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe importance of accessibility and usability in PROM development and implementation is starting to be recognized by regulators\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Specifically, in their most recent patient focused drug development (PFDD) guidance series, the US Food and Drug Administration (FDA) addresses the benefit of \u0026ldquo;universal design\u0026rdquo; for COAs and the importance of ensuring accessible data collection methods, with specific reference to electronic data capture and assistive technologies. This means ensuring the design and composition of a COA enable it to be accessed, understood, and used to the greatest extent possible by all people, including those with disabilities, and can facilitate broad inclusion in trials.\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003ePatients, like the general population, may be impacted by impaired functioning in a range of domains that can affect their interaction with data collection methods, including impaired cognitive function, vision impairment, impaired fine motor control, low literacy, and learning difficulties. While such challenges may have been life-long and independent of their reasons for being engaged in clinical research, these patients face the additional challenge that such issues \u003cem\u003emay\u003c/em\u003e be a symptom of their condition or a side-effect of treatment, and can impact their use of technology for completing PROMs\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e within the context of attempting to better understand that condition or treatment. To date, best practices for developing and implementing ePROMs has largely ignored accessibility as understood in the context of universal design, arguably to the significant detriment of clinical research and, more importantly, patients.\u003c/p\u003e\n\u003cp\u003eIn their PFDD Guidance, FDA direct the reader to review the World Wide Web Consortium (W3C) Web Accessibility Initiative (WAI) recommendations, as well as Section 508 of the US Government website (that requires Federal agencies to ensure that their Information and Communication systems are accessible to individuals with disabilities, in a way that is comparable to those without disabilities) to ensure a PROM will be accessible for individuals with certain impairments\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. However, to date there has not been broad adoption, nor consideration of how this may create a tension with existing ePROM design best practices, which are also referenced in the same guidance.\u003c/p\u003e\n\u003cp\u003eThe aim of this article is to review the web accessibility success criteria through the lens of ePROM design and implementation best practices to identify points of alignment and points of incongruence. We begin by providing a brief description of web accessibility criteria and history of ePROM design best practices to set the context for the comparison between the two. Considerations will be provided for how accessibility success criteria might be incorporated into future ePROM best practices and where further research is recommended to demonstrate the maintenance of the measurement properties of the ePROM, pointing towards a future of clinical research solutions which not only ensure high quality data capture, but are also accessible and supportive for the greatest array of participants, ultimately giving us greater confidence in our understanding of novel treatments.\u003c/p\u003e\n\u003ch3\u003eAccessibility Guidelines\u003c/h3\u003e\n\u003cp\u003eAccessibility of web solutions is usually evaluated through a conformance assessment based on the W3C Web Content Accessibility Guidelines (WCAG 2.2)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, which list 13 guidelines organized around 4 principles (see Fig.\u0026nbsp;1.), with corresponding success criteria that are classified into 3 levels, from lowest to highest conformance (A, AA, AAA)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. All four principles must be true for users with disabilities to be able to readily use the web. These four principles are also outlined in EU legislation to ensure websites and mobile applications are accessible\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eFigure\u0026nbsp;1. The four Web Accessibility Guideline principles from W3C\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eW3C acknowledge that whilst there are some slightly different considerations for accessibility on mobile devices (i.e., smartphones and tablet devices) as compared to desktop/laptop, there is no absolute divide and common features exist (e.g., both can include touchscreen control, the use of external keyboards, and responsive design), and so \u0026ldquo;Overall, \u003cstrong\u003eWCAG 2.0 is highly relevant to both web and non-web mobile content and applications\u003c/strong\u003e\u0026rdquo;.\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Nevertheless, W3C published discussion of mobile-related issues to support accessibility, with additional best practices where needed. This is relevant to ePROMs, which are predominately deployed using app and web on mobile devices, and to a lesser degree desktop/laptop.\u003c/p\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eePROM Best Practices\u003c/h2\u003e\n \u003cp\u003eHistorically, best practices for the implementation of ePROMs has focused on the issue of \u0026ldquo;faithful migration\u0026rdquo; \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e and ensuring electronic implementations of originally paper-based questionnaires capture comparable data. This is generally a story of concern about minor changes in visual layout potentially leading to participants responding differently to questions about how they are feeling and functioning. This concern was largely driven by the 2009 FDA Guidance on the use of PROMs in medical product labelling\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, which stated that \u003cem\u003e\u0026ldquo;When a PRO instrument is modified, sponsors generally should provide evidence to confirm the new instrument\u0026rsquo;s adequacy\u0026rdquo;\u003c/em\u003e and explicitly referred to modification including \u003cem\u003e\u0026ldquo;changing an instrument from paper to electronic format\u0026rdquo;\u003c/em\u003e (pp. 20). An ISPOR Task Force Report\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e expanded on this statement, recommending that testing is conducted to confirm the comparability between modes of administration. These recommendations had a lasting influence.\u003c/p\u003e\n \u003cp\u003eIn the 15 years since these seminal publications, large amounts of research have repeatedly demonstrated the comparability of PROMs when migrating from paper to electronic format for common item and response scale types\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e, in addition to measurement comparability between electronic formats for bring-your-own-device (BYOD) implementations\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. This body of research has culminated in updated industry recommendations that further studies of measurement comparability are not needed in cases where modifications to the migrated questionnaire are minor-to-moderate, sufficient comparability evidence exists, and importantly, best practices for migration are followed\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eThe historical focus on mitigating the risk of non-comparability is understandable given these measures often support key endpoints in pivotal trials and play a role in the ultimate success (or otherwise) of bringing a new compound to market. However, this has incentivized the pursuit of a reduction in variability in layout and presentation of content, and has meant that, in general, electronic applications for capturing PROMs have remained staunchly inflexible in design and layout, and not prioritized (or considered at all) inclusive design principles.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eShifting Focus\u003c/h3\u003e\n\u003cp\u003eArguably, this historic focus has been at the expense of optimizing the user experience of interacting with the technology, and the industry has been slow to explore alternative ways of presenting PROMs on screen-based devices \u0026ndash; presentations that are often very common in other contexts. For example, it is only recently the first investigation on the impact of scrolling on ePROM implementations was published\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Scrolling has long been used in non-ePROM contexts to allow for the presentation of content without having to reduce font size to an unusable degree, but has historically been advised against in ePROMs due to concerns that if users are required to scroll to see all response options it may bias their responses\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. While Shahraz et al.\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e found scrolling did not negatively impact the measurement properties, they still conservatively recommended the avoidance of scrolling. More generally, measures developed in electronic format ab initio still tend to follow existing best practices despite their primary focus being on migration from paper format, rather than taking full advantage of their screen-based modes of data capture and the flexibility this allows in making content accessible for the widest range of users.\u003c/p\u003e\n\u003cp\u003eAs an industry, we must hold ourselves accountable and challenge ourselves to consider whether the desire to strictly control how PROMs are administered and implemented on electronic modes of data capture due to a fear of negatively impacting measurement properties, has actually led to suboptimal solutions which are not as user-friendly and accessible for a broad range of individuals. As a consequence, this raises the concern of whether we are collecting data in a suboptimal manner from non-representative populations, reducing the utility of data in a trial, and, ultimately, risking the success of bringing a new compound to market.\u003c/p\u003e\n\u003cp\u003eIt is worth noting that the adaptability of screen-based designs affords us the opportunity to make content \u003cem\u003emore\u003c/em\u003e accessible and usable. Traditional paper-and-pen lack any of this flexibility and can be extremely difficult, if not impossible, for certain populations to use. However, moving from paper-and-pen to electronic capture of PROMS, while offering a wealth of benefits, can still create barriers for some individuals if not approached thoughtfully.\u003c/p\u003e\n\u003cp\u003eWhilst the recent updated best practices for migration and electronic implementation paid greater attention to respondent usability and accessibility than previous iterations\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, there is much more to be done. Without consideration of the functional, sensory, physical and cognitive abilities of users of technologies in clinical trials, electronic data capture methods can easily be implemented in ways that cause difficulties for certain populations or exclude them altogether. We cannot take it for granted that digital tools increase diversity, especially in the absence of due consideration to accessibility.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eEach WCAG 2.2 success criteria, inclusive of mobile specific guidance, will be evaluated in relation to current ePROM best practices (from Mowlem et al.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e), to identify areas of alignment or incongruence. Consideration for how the success criteria might affect ePROM implementation, as well as possible future areas of research to better understand the impact on measurement properties, will also be provided. Given ePROM design best practices focus on the actual measure, its visual presentation, and ensuring the integrity and quality of the data captured, the criteria will be considered from the perspective of how the measure is displayed, rather than the broader eCOA system (i.e., the app or website users log into to access the ePROMs). However, where certain criteria are relevant to the electronic system more widely but would not have a direct impact on the actual measure, comment will be provided. Of note, the assumption is that the measure itself has been well-designed and is fit-for-purpose.\u003c/p\u003e"},{"header":"Findings","content":"\u003cp\u003eTable \u003cspan\u003e1\u003c/span\u003e lists the WCAG 2.2 accessibility success criteria that are relevant to screen-based ePROM data capture systems, compares them to current ePROM best practices, and provides considerations for incorporating accessibility success criteria into future ePROM best practices. Additional guidance relevant only to mobile devices is detailed in Table \u003cspan\u003e2\u003c/span\u003e. Note, a classification level has not been allocated to any of the mobile specific guidance. For all WCAG 2.2 success criteria, including those that are not applicable to ePROMs, see Supplementary Material Table 1.\u003c/p\u003e\n\u003cp\u003eMany of the accessibility criteria address programming of the software to ensure content is implemented in a way that enhances overall accessibility and can be reliably interpreted by assistive technologies (e.g., screen readers, magnifiers), by accounting for them at the point of software development. Table \u003cspan\u003e3\u003c/span\u003e lists the accessibility practices that could be applied to eCOA systems now without concern for the integrity of the measure, given their focus is not on changing the measure content or the mode of administration, but the software being programmed and built in a way that enhances the overall accessibility and its usability with assistive technologies. Consistent testing of the system for compatibility with assistive technologies is encouraged, and the impact of the actual use of assistive technologies on measure integrity should be explored further.\u003c/p\u003e\n\u003cdiv\u003eBeyond considerations for assistive technologies, the main tensions between accessibility success criteria and ePROM best practices identified in this evaluation concerned the ability to increase content size and device orientation.\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eIncreasing the size of content\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCurrent ePROM best practice is to enable vertical scrolling (horizontal is not recommended) instead of reducing text to a small enough size that it could cause reading difficulties. However, some still caution against the use of scrolling when implementing ePROMs\u003csup\u003e\u003cspan\u003e20\u003c/span\u003e\u003c/sup\u003e and some measure copyright holders do not allow scrolling. Further, the amount of scrolling required for a given item tends to be programmed as the same for all users (i.e, the text size is still dictated by the system as opposed to allowing the user to alter it or presenting content at the size set on the device), and so may still not satisfy the text size required by some users. Some have even recommended, with best intentions regarding the maintenance of measurement properties, that in BYOD scenarios the user should not be able to over-ride specific app display settings \u003csup\u003e\u003cspan\u003e20\u003c/span\u003e\u003c/sup\u003e, including font size \u003csup\u003e\u003cspan\u003e16\u003c/span\u003e\u003c/sup\u003e. The use of zoom has not yet been addressed in ePROM best practices and has only recently received attention in research\u003csup\u003e\u003cspan\u003e22\u003c/span\u003e\u003c/sup\u003e, with preliminary findings showing measurement comparability.\u003c/p\u003e\n\u003cp\u003eIn contrast, WCAG 2.2 success criteria indicate that it should be possible for users to increase text size up to 200% without the loss of content or functionality; that is, it reflows (wraps) with scrolling in one dimension (i.e., vertically). Given the reducing concern around scrolling on the impact of an ePROMs measurement properties\u003csup\u003e\u003cspan\u003e11\u003c/span\u003e,\u003cspan\u003e20\u003c/span\u003e\u003c/sup\u003e, and upcoming work extending this to zoom functionality\u003csup\u003e\u003cspan\u003e22\u003c/span\u003e\u003c/sup\u003e, it is worth considering if 200% text resizing or zooming should be possible for users, combined with the existing recommendations around how to implement scrolling functionality outlined in Mowlem et al.\u003csup\u003e\u003cspan\u003e11\u003c/span\u003e\u003c/sup\u003e Based on accessibility guidelines, it will be important that zooming does not lead to scrolling in two dimensions (i.e., vertically and horizontally). It is also recommended that further research on the impact of zooming and text resizing on the measurement properties of an ePROM is conducted, including understanding the most optimal method based on user preference. This should include the full item, inclusive of the response options for all response scale types (verbal rating scale, numeric rating scale, visual analogue scale), and not focus only on increasing the size of the item stem (i.e., the question text or statement to be rated).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOrientation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCurrent ePROM best practice is to keep the device orientation consistent, along with recommending that ePROMs are presented in portrait on smartphones, and that respondents should not be able to manually alter the orientation (e.g., through rotation of the device). Of note, this is not referring to changing the orientation of the response scale types themselves (e.g., an NRS being presented vertically rather than the traditional horizontal). In contrast, WCAG 2.2 success criteria states that users should be allowed to switch the orientation of their device between portrait and landscape as they wish, unless a certain orientation is deemed essential to the content.\u003c/p\u003e\n\u003cp\u003eTo date, there has been no published evidence that changing device orientation - or using one orientation over the other - would impact the measurement properties of the PROM. Therefore, it is difficult to argue that a given orientation is essential to the content being presented. The intent of the ePROM best practice recommending against allowing users to switch orientation is to facilitate standardization of the presentation of measures across respondents and eliminate the risk or formatting issues tied to changing orientation. However certain populations, such as those who have dexterity impairments, may benefit from a mounted device in a specific orientation, and so this ePROM best practice should be reconsidered. As system providers develop their software, the ability of content to function in either orientation and allowing users to switch to their preferred orientation, as well as the programmatic exposing of the orientation to assistive technologies, should be included and tested adequately. Conducting research on the measurement comparability between orientations could also help mitigate any concerns that the integrity of the measure could be impacted.\u003c/p\u003e\n\u003ch3\u003eRecommendations for further research\u003c/h3\u003e\n\u003cp\u003eIn addition to the areas identified above (the impacts of assistive technology, orientation, zooming, and text resizing), it is recommended that the following are the subject of future studies to enable a clear understanding on whether meeting the accessibility criteria would impact the measurement properties of the PROM:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003ehorizontal vs vertical presentations of the NRS (this could extend to the VAS, but given this is not a recommended response type for an accessible measure, the NRS should be the focus) (related to 2.5.8 Target Size [Minimum], see Table \u003cspan\u003e1\u003c/span\u003e)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003ethe impact of saving partially completed measures and completing them later on the reliability of the data, and potential time limits for this (related to 2.2.6 Timeouts, see Table \u003cspan\u003e1\u003c/span\u003e)\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cdiv id=\"Sec8\"\u003e\n \u003ch2\u003eImplications for measure development\u003c/h2\u003e\n \u003cp\u003eAs mentioned, the focus of this evaluation was on the implementation of the PROM in an electronic system, under the assumption that the measure itself has been well-designed and is fit-for-purpose. If the PROM itself (regardless of mode of administration) has not been developed in an accessible way, then this fundamental lack of accessibility is unlikely be resolved through electronic implementation (e.g., the VAS will be inherently difficult for vision-impaired individuals to complete in any mode). That said, the following are recommended to make existing PROMs accessible and ensure the accessibility of new measures.\u003c/p\u003e\n \u003cp\u003eFor existing measures:\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003ecreate and validate text alternatives for non-text content (e.g., image-based response options) that can be provided when the measure is licensed for electronic implementation\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eif instructional text relies solely on sensory characteristics, create and validate versions that provide additional information to clarify instructions dependent on this kind of information\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eif color is the only way to convey certain information, create and validate versions where this is not the case\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n \u003cp\u003eFor new measures:\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003ecreate text alternatives for images at the time of measure creation\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003edo not use the VAS as a response type\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003edo not use content that relies solely on sensory characteristics\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003edo not use color as the only means to convey information\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n \u003cp\u003eTable \u003cspan\u003e1\u003c/span\u003e \u003cem\u003eabout here\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eTable \u003cspan\u003e2\u003c/span\u003e \u003cem\u003eabout here\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eTable \u003cspan\u003e3\u003c/span\u003e \u003cem\u003eabout here\u003c/em\u003e\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo date in the field of electronic capture of PROMs in clinical trials, there has been greater focus on the comparability of the electronic implementation to the paper format rather than to the general accessibility of these technology driven solutions. Best practices for ePROMs have largely been developed by individuals in the field of outcomes measurement and eCOA research who have different disciplinary priorities compared to those working in more general web- and app-based solutions, resulting in tensions between ePROM design best practices focused on maintaining measurement properties, and general web- and app-design best practices to provide solutions that are accessible to all. The clinical trial industry prides itself on being \u0026ldquo;patient-centric\u0026rdquo; yet has been slow in adopting relatively simple and widespread technologic solutions that can address common challenges for users of technologies. Recent ePROM best practices have brought stronger consideration to usability and accessibility but further progress is needed, with much to learn from the world of good web and app design.\u003c/p\u003e \u003cp\u003eThis article has outlined that many accessibility best practices can be incorporated into ePROM implementations \u003cem\u003etoday\u003c/em\u003e, most of which are focused on the programming of the software and criteria that will not alter the content of a PROM \u003cem\u003e-\u003c/em\u003e it is urged that those who develop these data capture systems adopt these wherever possible. Recommendations for further research that may be required to support accessible approaches without impacting the measurement properties of the PROM were also outlined.\u003c/p\u003e \u003cp\u003eThe focus here was specifically on the accessibility of the ePROM implementation as opposed to the eCOA system more widely, given this is what is addressed by current ePROM best practices \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. However, from the user perspective it is unlikely that they differentiate their interaction between the implementation of the actual measure and the wider system, such as the app or website users access the ePROM through. Whether this separation is a logical one should be considered when developing future best practices.\u003c/p\u003e \u003cp\u003eFurther, the actual use of assistive technologies for accessing and completing ePROMs and how this may impact measurement comparability was beyond the scope of this paper, but requires further thought and discussion; for example, understanding if completion of a measure by those using a screen-reader versus those who are not leads to measurement non-comparability. ePROM best practices have been largely focused on reducing variability between modes of administration, and so allowing users to engage with the content of a measure via an assistive technology, for example a screen reader, is a significant change in thinking for the industry. However, it is worth noting that from the earliest days of ePRO we have been displaying questions and response options on a single, relatively small screen, which is already a significant visual departure from the multiple questions and response options seen on paper. The evidence has consistently shown that PROMs are robust in regard to changes in mode of data collection, and even so called \u0026lsquo;significant\u0026rsquo; changes in administration and visual layout have consistently shown to provide comparable data.\u003c/p\u003e \u003cp\u003eHowever, considering the importance of the data being captured, increasing the evidence base will facilitate the development of increasingly user-centric solutions through which there is potential to improve data quality. Without data we can trust, we cannot bring safe and effective treatments to \u003cem\u003eall\u003c/em\u003e individuals. This will also be key to having regulatory agency confidence in ePROM implementations that adopt accessible practices that could be deemed a significant departure from the paper format.\u003c/p\u003e \u003cp\u003eIt would be remiss to discuss ePROM implementation without reference to the authors and copyright holders of these measures, who often have their own requirements for implementation that are sometimes at odds with both ePROM best practices \u003cem\u003eand\u003c/em\u003e accessibility best practices. This dynamic can present a challenge to improving the participant experience in clinical trials. For example, some require that the anchor text associated with the extremes of a horizontal NRS must not extend past the length of the highest and lowest numbers into the middle of the scale (i.e., the number 0 and number 10 on an 11-point scale); making the anchor text smaller, text-wrapping and/or splitting single words across lines to meet this requirement can run the risk of causing readability issues and fly in the face of accessibility guidelines (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e for examples).\u003c/p\u003e \u003cp\u003eGiven the time-sensitive nature of the trial set-up process, discussions with measure authors/copyright holders around electronic implementations that deviate from \u0026lsquo;the norm\u0026rsquo; but are arguably more accessible (whilst maintaining the integrity of a measure) often fall by the wayside; this \u003cb\u003emust\u003c/b\u003e change for us to progress. As an industry, the goal of all stakeholders involved should be to make electronic data capture more accessible and usable, leading to more representative trials that are lower burden for patients. We should ask ourselves if we have lost sight of the intention of these measures? They are developed for use in specific therapeutic populations, yet electronic implementation guidelines can oftentimes make them difficult to use for those exact populations.\u003c/p\u003e \u003cp\u003eFinally, the criticality of consensus-based best practices was highlighted in Mowlem et al. (2024)\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, and it is important to acknowledge that the aim of this article is not to recreate and dictate new best practices, as the WCAG and 508 accessibility success criteria already exist. Rather, it was to identify where existing accessibility guidelines may not currently be being met in ePROM design and where they should be applied, and where further evidence is required before they are more-formally integrated into ePROM best practices. It is important that best practices are updated as the evidence-base advances.\u003c/p\u003e \u003cp\u003eWhilst this article focused on the electronic implementation as opposed to the instrument itself, it is clear that accessibility and universal design best practices start from the point of PROM development - whatever format that may be \u0026ndash; to ensure a fit-for-purpose, valid, \u003cem\u003eand\u003c/em\u003e accessible PROM. We must get to a point where accessibility best practices \u003cem\u003eare\u003c/em\u003e (e)PROM best practices.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e FM is employed by uMotif. POD is employed by Medidata.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u003c/strong\u003e FM was responsible for conceptualization of the work. FM and POD were responsible for interpretation, drafting, and revising of the work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e The author wishes to thank Bruce Hellman and James Fenlon for their insightful feedback and discussions during the creation of this manuscript.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eInternational Organization for Standardization. ISO 26800:2011(En) Ergonomics \u0026mdash; General Approach, Principles and Concepts. (2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIntegrating Accessibility into Agency Diversity. Equity, Inclusion and Accessibility (DEIA) Implementation Plans. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.section508.gov/manage/deia-guidance/\u003c/span\u003e\u003cspan address=\"https://www.section508.gov/manage/deia-guidance/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoons SJ et al. Capturing Patient-Reported Outcome (PRO) Data Electronically: The Past, Present, and Promise of ePRO Measurement in Clinical Trials. Patient vol. 8 301\u0026ndash;309 Preprint at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s40271-014-0090-z\u003c/span\u003e\u003cspan address=\"10.1007/s40271-014-0090-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEuropean Medicines Agency. Guideline on Computerised Systems and Electronic Data in Clinical Trials. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ema.europa.eu/en/documents/regulatory-procedural-guideline/draft-guideline-computerised-systems-electronic-data-clinical-trials_en.pdf\u003c/span\u003e\u003cspan address=\"https://www.ema.europa.eu/en/documents/regulatory-procedural-guideline/draft-guideline-computerised-systems-electronic-data-clinical-trials_en.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eU.S. Department of Health and Human Services Food and Drug Administration. Patient-Focused Drug Development: Selecting, Developing, or Modifying Fit-for-Purpose Clinical Outcome Assessments. (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMowlem FD, Sanderson B, Platko JV, Byrom B. Optimizing electronic capture of patient-reported outcome measures in oncology clinical trials: lessons learned from a qualitative study. J Comp Eff Res 9, (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWAI (Web Accessibility Initiative). WCAG 2 Overview. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.w3.org/WAI/standards-guidelines/wcag/\u003c/span\u003e\u003cspan address=\"https://www.w3.org/WAI/standards-guidelines/wcag/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThe European Parliament and the Council of the European union. DIRECTIVE (EU) 2016/2102 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 26 October. 2016 on the Accessibility of the Websites and Mobile Applications of Public Sector Bodies. (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.legislation.gov.uk/eudr/2016/2102/introduction#:~:text=\u003c/span\u003e\u003cspan address=\"https://www.legislation.gov.uk/eudr/2016/2102/introduction#:~:text=\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e(9)%20This%20Directive%20aims%20to,basis%20of%20common%20accessibility%20requirements., 2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eW3C. Mobile Accessibility: How WCAG 2.0 and Other W3C/WAI Guidelines Apply to Mobile. (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eO\u0026rsquo;Donohoe P et al. Updated Recommendations on Evidence Needed to Support Measurement Comparability Among Modes of Data Collection for Patient-Reported Outcome Measures: A Good Practices Report of an ISPOR Task Force. \u003cem\u003eValue in Health\u003c/em\u003e In press, (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMowlem FD, et al. Best Practices for the Electronic Implementation and Migration of Patient-Reported Outcome Measures. Value Health. 2024;27:79\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eU.S. Food and Drug Administration. Guidance for Industry Patient-Reported Outcome Measures: Use in Medical Product Development to Support Labeling Claims. (2009).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoons SJ, et al. Recommendations on evidence needed to support measurement equivalence between electronic and paper-based patient-reported outcome (PRO) measures: ISPOR ePRO good research practices task force report. Value Health. 2009;12:419\u0026ndash;29.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGwaltney CJ, Shields AL, Shiffman S. Equivalence of electronic and paper-and-pencil administration of patient-reported outcome measures: A meta-analytic review. Value Health. 2008;11:322\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMuehlhausen W et al. Equivalence of electronic and paper administration of patient-reported outcome measures: A systematic review and meta-analysis of studies conducted between 2007 and 2013. Health Qual Life Outcomes 13, (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMuehlhausen W, et al. Standards for Instrument Migration When Implementing Paper Patient-Reported Outcome Instruments Electronically: Recommendations from a Qualitative Synthesis of Cognitive Interview and Usability Studies. Value Health. 2018;21:41\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eByrom B, et al. Measurement Equivalence of Patient-Reported Outcome Measure Response Scale Types Collected Using Bring Your Own Device Compared to Paper and a Provisioned Device: Results of a Randomized Equivalence Trial. Value Health. 2018;21:581\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHudgens S et al. Comparability of a provisioned device versus bring your own device for completion of patient-reported outcome (PRO) measures by participants with chronic obstructive pulmonary disease (COPD): Quantitative study findings. Value Health 21, (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eByrom B et al. Measurement Comparability of Electronic and Paper Administration of Visual Analogue Scales: A Review of Published Studies. Therapeutic Innovation and Regulatory Science vol. 56 394\u0026ndash;404 Preprint at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s43441-022-00376-2\u003c/span\u003e\u003cspan address=\"10.1007/s43441-022-00376-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShahraz S et al. Does scrolling affect measurement equivalence of electronic patient-reported outcome measures (ePROM)? Results of a quantitative equivalence study. J Patient Rep Outcomes 5, (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEremenco S, et al. PRO data collection in clinical trials using mixed modes: Report of the ISPOR PRO mixed modes good research practices task force. Value Health. 2014;17:501\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcDowell B et al. Accessibility Vs Standardization: A Study of Electronic Implementation of Patient-Reported Outcomes Measures with Vision-Impaired Participants. Value Health 26, (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eU.S. Food and Drug Administration. Digital Health Technologies for Remote Data Acquisition in Clinical Investigations. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.fda.gov/regulatory-information/search-fda-guidance-documents/digital-health-technologies-remote-data-acquisition-clinical-investigations\u003c/span\u003e\u003cspan address=\"https://www.fda.gov/regulatory-information/search-fda-guidance-documents/digital-health-technologies-remote-data-acquisition-clinical-investigations\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 3 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"accessibility, ePRO, eCOA, diversity, burden, migration","lastPublishedDoi":"10.21203/rs.3.rs-5741400/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5741400/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eApps and web browsers, whether on smartphones, tablets or laptops, have become the mainstream methods of capturing clinical outcome assessment (COA) data, and patient-reported outcome measures (PROMs) in particular, in clinical trials. There has long been concern around whether implementing traditionally paper-based questionnaires on electronic systems may impact the measurement properties of these carefully validated questionnaires, with migration best practices focusing predominately on this issue. In parallel, app and web-design best practices outside of clinical research have focused on the accessibility and usability of these electronic systems for the widest range of users.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis article evaluates how existing Web Content Accessibility Guidelines (WCAG 2.2) compare to electronic PROM (ePROM) design best practices, identifying where there is alignment or tension, where further evidence is needed to ensure both accessibility and the maintenance of the questionnaire measurement properties, and what accessibility practices can be incorporated into ePROM design best practices today.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eMany of the accessibility criteria can be applied to electronic clinical outcome assessment (eCOA) systems now without concern for the integrity of the measure, given their focus is on the software being programmed and built to support content being implemented in a way that enhances overall accessibility and its usability with assistive technologies. The main tensions identified between the accessibility success criteria and ePROM best practices concerned increasing content size and device orientation.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eMany accessibility best practices can be adopted in ePROM implementations \u003cem\u003etoday\u003c/em\u003e, and we must strive to achieve a point where accessibility best practices \u003cem\u003eare\u003c/em\u003e (e)PROM best practices to ensure electronic data capture is accessible and usable, leading to more representative trials that are lower burden for patients.\u003c/p\u003e","manuscriptTitle":"Accessible data collection methods in clinical trials: Do current best practices for the implementation of electronic patient-reported outcome measures (ePROMs) meet accessibility standards?","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-06 13:54:09","doi":"10.21203/rs.3.rs-5741400/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e91b0343-e539-417a-98b2-aedcf3a8624d","owner":[],"postedDate":"January 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-03-27T12:08:37+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-06 13:54:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5741400","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5741400","identity":"rs-5741400","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}