A human-centred, explainable digital system to support emotional self-regulation and everyday psychological well-being

Abstract Self-regulating emotions, thoughts, and behaviours is central to psychological well-being but often difficult to sustain without structured support, particularly under stress or cognitive overload. This study introduces a human-centred digital system designed to support everyday emotional self-regulation through personalised, explainable self-care guidance grounded in established models of emotion regulation and self-regulated behaviour. The system adapts to users’ reported emotional state, cognitive load, time and energy constraints, and personal preferences to generate actionable self-care plans accompanied by natural-language explanations that clarify the system’s reasoning and contrast alternative strategies, supporting user understanding and autonomy. The system is intended for non-clinical, self-care contexts and does not provide diagnosis or treatment. A formative scenario-based evaluation was conducted using three representative non-clinical user archetypes. The generated outputs were independently assessed using a structured rubric, producing mean scenario scores of 4.2–4.8 out of 5. Findings suggest that explainable digital systems can function as cognitive and emotional scaffolding, enhancing reflective engagement and supporting behaviour change in everyday contexts. This work contributes to research at the intersection of behavioural science and technology by demonstrating how explainability and personalisation can be operationalised in supportive digital systems, offering design insights for transparent, adaptive technologies that promote trust, autonomy, and sustained engagement in psychological well-being support.