Abstracts Track 2026

Area 1 - Blockchain Ethics by Design

Nr:	49
Title:	A Blockchain-Based Smart Contract Architecture for Electronic Informed Consent in Digital Health Research: Design, Implementation, and GDPR Compliance
Authors:	Pedro Dias, Rodrigo Antunes, Catarina Nunes-Da-Silva, Soraia Ferreira, Federico Guede-Fernández, Ermanno Pallaoro, Manuel Dias, Ricardo Correia, Salomé Azevedo and Ana Londral
Abstract:	1. Purpose To design, implement, and validate a GDPR-compliant blockchain-based smart contract architecture for eConsent in digital health research, and to evaluate its technical feasibility and regulatory compliance through a real-world pilot study. 2. Design/Methodology/Approach A design science research approach was adopted. Requirements were derived from ethical and regulatory frameworks and implemented in the Worthmed-BioGHP integration. Worthmed supports enrolment, communication, and PROM collection via WhatsApp; BioGHP provides the blockchain infrastructure for securely registering consent provision and withdrawal. The smart contract registers consent provision and revocation using pseudonymised identifiers, consent status, and timestamps. Personal data remain off-chain. Pilot validation is planned through a prospective study with 30+ participants. 3. Findings The demonstrator implements an end-to-end eConsent flow: participants receive a secure WhatsApp link, access a Worthmed-hosted consent form, provide explicit consent, and have their consent status registered on-chain. Revocation via WhatsApp triggers an on-chain status update and suspension of data collection. The implementation demonstrates feasibility, auditability, and GDPR compliance by design through on/off-chain segregation. 4. Research Limitations/Implications Findings reflect implementation and pre-pilot validation. Usability, acceptance, workload, and feasibility outcomes will be assessed during the pilot. This provides a model for blockchain-backed eConsent in digital health research. 5. Social/Technical Impact The architecture supports participant-centred consent management, transparent auditability, and practical revocation. It may reduce administrative burden and strengthen trust. 6. Final Comments/Originality/Value This work presents a functional, GDPR-aligned smart contract demonstrator for eConsent in pilot digital health research, offering an operational framework for future studies.

Area 2 - Regulatory and Policy Frameworks

Nr:	46
Title:	Challenges of the Use of AI in Psychology within Education: Implications for Cognitive Wellbeing and Critical Thinking
Authors:	SivaPriya Thirugnanarajah
Abstract:	The rapid integration of Generative Artificial Intelligence (GenAI) into higher education has produced both opportunities and emergent risks for student learning, with particular implications for psychology as a discipline that studies — and is studied through — the same cognitive processes. While tools such as ChatGPT, Google Gemini and Microsoft Copilot can scaffold learning by generating summaries, examples and practice problems, mounting empirical evidence raises concerns about shallow engagement, weakened critical thinking, and reduced self-regulated learning when students outsource cognitive effort to these systems. This position paper synthesises recent literature on GenAI use in higher education to characterise the principal cognitive and psychological challenges — plagiarism risk, overreliance, misinformation, low AI literacy, and the erosion of higher-order thinking — and argues that these challenges are simultaneously educational and healthcare concerns, since prolonged cognitive offloading and dependency patterns may interact with student wellbeing, anxiety, and metacognitive self-trust. We discuss the cognitive paradox by which GenAI can both enhance higher-order thinking via richly contextualised problem sets and undermine self-directed learning when use becomes habitual and unreflective. We close with a position on balanced integration: explicit AI literacy curricula, assessment redesign that rewards process and metacognition, and longitudinal monitoring of student cognitive and emotional outcomes. The work is offered as a late-breaking contribution to ABH 2026 to inform conversations on AI safeguards at the intersection of educational psychology and healthcare.