For users, SENTIA Wellbeing apps promote psychological self-awareness, provide educational support related to mental health issues, reduce stigma associated with help-seeking, and provide immediate access to structured, evidence-based guidance.

For clinicians/psychologists, SENTIA dashboard standardizes psychometric data collection, reduces repetitive intake procedures, and enables more informed consultations through structured summaries. Automated risk alerts support early intervention without removing professional discretion.

The development of SENTIA Wellbeing is guided by the following objectives:

Components	Objectives	Boundaries
Self-Help Apps – Students – Women’s Health – Wellbeing	Provide self-help assistance and continuous well-being monitoring tailored to different populations. Capture psychological, contextual, lifestyle, and physiological data through validated instruments and user input. Enable users to understand their state, track evolution, and receive personalized, evidence-based guidance.	SENTIA does not diagnose or replace clinical evaluation. It interprets structured data using validated sources and encourages professional consultation when needed.
	Maintain a unified, dynamic representation of the user profile integrating psychometrics, symptoms, stressors, lifestyle, and health indicators. Track evolution over time using indices to identify trends, patterns, and risk levels.	All metrics are computed through deterministic rules. The generative AI component cannot modify or override these values.
	Provide accessible, medically validated information on mental health and wellbeing through natural language interaction. Support user understanding of symptoms, coping strategies, and lifestyle adjustments using curated knowledge sources.	Responses are strictly constrained to verified knowledge bases (e.g., WHO, NHS, NICE, institutional materials). No medication or clinical prescriptions are provided.
Advanced Monitoring and Decision Support Dashboard for Specialists – Longitudinal Monitoring – Linguistic Analysis – Phenotyping – PubMed Evidence Retriever – Paper Q&A	Deliver structured summaries of user trajectories, risk levels, contextual factors, and behavioral signals. Support efficient consultations, early intervention, and personalized care through data-driven insights.	All insights are assistive and require clinician validation before use in decision-making. SENTIA does not autonomously modify care plans.
	Aggregate data to identify trends, risk clusters, and periods of increased burden across the population. Support institutional planning, preventive strategies, and resource allocation.	Only aggregated and compliant data is used. Individual privacy and GDPR requirements are strictly enforced.
	Extract emotional tone, semantic patterns, and behavioral signals from user interactions to detect subtle changes in psychological state and complement psychometric data.	Linguistic signals are used as supportive indicators and are not interpreted independently of validated assessments.
	Identify patterns across symptoms, context, and behavior to generate phenotypes. Analyze relationships between influencing factors and outcomes and connect them to evidence from scientific literature to support clinical reasoning.	All generated hypotheses are exploratory, evidence-supported, and require professional validation.
	Transform clinician-provided case descriptions into structured clinical hypotheses. Automatically generate PubMed search queries for each hypothesis, retrieve highly relevant scientific publications, extract key claims, evidence, and reported interventions, and synthesize evidence-based recommendations to support clinical reasoning and decision-making.	Retrieved evidence is intended to support, not replace, professional judgment. Generated hypotheses, extracted claims, and recommendations are evidence-informed and require clinician review and validation before application in patient care.