| Title: | Multimodal observable cues in mood, anxiety, and borderline personality disorders: a review of reviews to inform explainable AI in mental health |
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| Authors: | ID Močnik, Grega (Author)
ID Rehberger, Ana (Author)
ID Smogavc, Žan (Author)
ID Mlakar, Izidor (Author)
ID Smrke, Urška (Author)
ID Močnik, Sara (Author) |
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| Files: |  frai-8-1696448.pdf (835,67 KB)
MD5: 515B5BBA99C1A7518DE779DBD8B4BF8D
 https://www.frontiersin.org/articles/10.3389/frai.2025.1696448/full
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| Language: | English |
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| Work type: | Article |
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| Typology: | 1.02 - Review Article |
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| Organization: | FERI - Faculty of Electrical Engineering and Computer Science
MF - Faculty of Medicine
UM - University of Maribor
FF - Faculty of Arts
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| Abstract: | Mental health disorders, such as depression, anxiety, and borderline personality disorder (BPD), are common, often begin early, and can cause profound impairment. Traditional assessments rely heavily on subjective reports and clinical observation, which can be inconsistent and biased. Recent advances in AI offer a promising complement by analyzing objective, observable cues from speech, language, facial expressions, physiological signals, and digital behavior. Explainable AI ensures these patterns remain interpretable and clinically meaningful. A synthesis of 24 recent systematic and scoping reviews shows that depression is linked to self-focused negative language, slowed and monotonous speech, reduced facial expressivity, disrupted sleep and activity, and altered phone or online behavior. Anxiety disorders present with negative language bias, monotone speech with pauses, physiological hyperarousal, and avoidance-related behaviors. BPD exhibits more complex patterns, including impersonal or externally focused language, speech dysregulation, paradoxical facial expressions, autonomic dysregulation, and socially ambivalent behaviors. Some cues, like reduced heart rate variability and flattened speech, appear across conditions, suggesting shared transdiagnostic mechanisms, while BPD’s interpersonal and emotional ambivalence stands out. These findings highlight the potential of observable, digitally measurable cues to complement traditional assessments, enabling earlier detection, ongoing monitoring, and more personalized interventions in psychiatry. |
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| Keywords: | observable cues, mood disorders, anxiety disorders, borderline personality disorder, multimodal signals, facial expressions, speech patterns, physiological signals, explainable AI, mental health assessment |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 31.08.2025 |
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| Article acceptance date: | 24.11.2025 |
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| Publication date: | 09.12.2025 |
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| Publisher: | Frontiers Media S. A. |
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| Year of publishing: | 2025 |
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| Numbering: | Vol. 8 |
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| PID: | 20.500.12556/DKUM-96193  |
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| UDC: | 004.8:61 |
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| ISSN on article: | 2624-8212 |
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| eISSN: | 2624-8212 |
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| COBISS.SI-ID: | 260723459 |
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| DOI: | 10.3389/frai.2025.1696448 |
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| Copyright: | © 2025 Močnik, Rehberger, Smogavc, Mlakar,
Smrke and Močnik. |
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| Publication date in DKUM: | 05.01.2026 |
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| Views: | 159 |
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| Downloads: | 9 |
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| Metadata: |    |
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| Categories: | Misc.
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