ReviewJournal of personalized medicine2026
Quantitative Electroencephalography as a Complement to Symptom-Based Psychiatric Diagnosis: A Narrative Review.
Review in Journal of personalized medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
3 authors.
Funding
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Abstract
backgroundPsychiatric assessments traditionally rely on the Diagnostic and Statistical Manual of Mental Disorders (DSM) for diagnostic guidance. This approach, however, is heavily based on the identification of cluster symptoms assessed through subjective interviews and questionnaires, without adequately controlling for overlapping symptoms or symptom specificity. This may lead to broad and often inaccurate diagnoses that overlook the patient's unique experience and underlying neurobiological imbalances. As mental healthcare strives to move towards personalized medicine, incorporating more objective and precise measures of neuropsychological distress, it is essential to reduce the diagnostic and treatment inaccuracies that may stem from relying solely on empirical guidelines. This narrative review examines the limitations of the current approach and considers the potential role of quantitative electroencephalography (qEEG) as an adjunctive method that may enrich existing diagnostic processes.
methodsA structured literature search was conducted in Europe PMC on 31 January 2026. Original human studies and clinical trials in English with available abstracts were thematically selected.
resultsThe search yielded 1934 records, from which a focused subset of studies was selected based on direct relevance to the review themes.
conclusionsIntegrating qEEG methods into traditional assessments could enhance diagnostic accuracy in psychiatric care and reduce patients' exposure to inadequate treatments, ultimately leading to improved treatment outcomes and patient satisfaction.
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