Bridging Expertise and Technology: A No-Code Platform for Developing Digital Psychometric Assessments

Abstract: Psychometric assessments are central to diagnostics, treatment planning and progress monitoring. They provide standardised, reliable measures of mental health, cognitive performance and patient-reported outcomes, making them essential for evidence-based healthcare. Despite their importance, developing digital psychometric diagnostics is highly resource-intensive. This process requires technical expertise and access to validation infrastructures, yet many domain experts lack adequate digital tools. Consequently, development processes are slowed, economic and intellectual value is often absorbed by external parties, and many assessments never reach the market, which hinders innovation and broader accessibility. This paper introduces a digital validation platform designed to enable non-technical experts to independently design, validate and deploy psychometric assessments. Developed through a co-design approach, the platform is based on qualitative insights gained from interviews with domain experts and an in-depth analysis of seven assessment development processes. The findings highlight current challenges and inform the platform's conceptual foundation and functional design. Emphasis is placed on usability, perceived value, and integrating established psychometric methods with novel digital innovations. By reducing technical barriers, the platform enables the more autonomous, timely and diverse development of assessments, thereby fostering innovation and strengthening knowledge ownershipThis paper presents a novel digital validation platform designed to address this gap by empowering non-technical experts to design, validate, and deploy psychometric assessments independently. We propose an innovation design paradigm that foregrounds domain expertise over technical know-how following the central research question: How can a no-code platform empower non-technical domain experts to design, validate and deploy digital psychometric assessments and accelerate the development and improve the accessibility? To investigate this question, the platform is developed following human-centered design principles, incorporating insights from interviews and co-design sessions with potential users. Various domain experts were interviewed, and seven assessment development processes were closely accompanied to capture processes, challenges, and needs. The resulting qualitative findings uncover critical points in current workflows and serve as the basis for both the platform’s conceptual foundation and its functional design. This paper presents these insights alongside the platform's concept and technical architecture as well as the methodological approach for its iterative development and evaluation. The focus lies on usability, perceived value, and the ability to meaningfully integrate both traditional psychometric logic and novel data sources. The paper outlines the envisioned impact on innovation workflows, knowledge ownership, and accessibility in psychometric assessment development. By demonstrating how digital tools can democratize a traditionally centralized and analogue process, this work contributes to the field of human factors in computing. Lowering technical barriers allows for more autonomous, diverse, and timely development of psychometric assessments, driven by those who best understand the target populations and research questions. It advocates for an open as possible, accessible ecosystem where psychometric assessments can be rapidly developed, iteratively improved, and responsibly validated. These innovations and the digitalization in the field of psychometric assessments will serve as the basis for integrating more intelligent digital solutions into the healthcare system in the future, such as digital twins and personalized medicine.

Keywords: Digital Diagnostics, Co-Design, Human-Centered Design, Psychometric Assessments, No-Code

DOI: 10.54941/ahfe1006969

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