[Virtual Mental Health Assistance: Online Platform for Psychiatric Assessment and Follow-Up].

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PubMedPublished 2026Mental Health & NeuroscienceNeuroscience
Journal
Neuropsychopharmacologia Hungarica : a Magyar Pszichofarmakologiai Egyesulet lapja = official journal of the Hungarian Association of Psychopharmacology
Record source
PubMed Research Library

Abstract / Description

A psychiatric diagnosis is necessary, but it does not by itself describe a patient's current clinical state in full. Digital assessment systems therefore need to link standardised measures with clinical exploration that develops according to the patient's responses and with repeated assessments. We describe the structure and initial clinical use of Virtual Mental Assistance (VMA), a rule-based, web-based psychiatric assessment and followup system developed by our group. The single-centre, non-randomised study included 28 outpatients. Their mean age was 43.0 years (SD = 2.8); 18 identified as women, 8 as men, and 2 did not provide this information. All participants completed the institutional assessment and at least part of one home assessment. Based on the responses provided, VMA activates the relevant modules from a set of 13. It combines DSM-5-TR-based structured questions, standardised measures, cognitive tasks, and repeated self-reports while retaining the source of each data point. The clinician interface presents a rapid overview, a detailed symptom- and scale-based breakdown, and time-series and contextual views. Risk and safety information is displayed separately. A distinctive feature of the system is the integration of response-dependent clinical exploration, standardised measurement, repeated follow-up, and multiple clinical views within a single patient profile with item-level traceability. The findings are limited to the technical and structural feasibility of this approach. This sample does not allow conclusions about diagnostic validity, psychometric performance, usability, or clinical utility. These questions require prospective validation of a stable system version using predefined reference standards and outcome measures. (Neuropsychopharmacol Hung 2026; 28(3): 187-198)
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