Contextual insights from large language models in ambulatory assessment: Differential reactivity of affect and self-esteem to daily events in borderline personality disorder.

Authors

David Levi Tekampe, Tobias D Kockler, Ulrich W Ebner-Priemer, Angelica Mendes, Martin Bohus, Philip S Santangelo

Published in

Journal of psychopathology and clinical science. Jul 27, 2026. Epub Jul 27, 2026.

Abstract

Ambulatory assessment (AA) research often relies on closed-ended context checklists, whereas open-ended event descriptions preserve richer idiographic context but are rarely analyzed at scale. Borderline personality disorder (BPD) is characterized by marked instability, providing a clinically informative use case for testing scalable approaches to contextual dynamics in daily life. We investigated the association of event context and sentiment (i.e., emotional connotation) derived using a large language model (LLM) with self-reported momentary calmness, affective valence, and self-esteem in a sample of 265 women (131 individuals with BPD and 134 healthy controls) undergoing a 4-day high-frequency AA with 12 hourly assessments per day. We evaluated an automated LLM pipeline for classifying 10,844 free-text entries and for rating event-related sentiment, enabling quantitative modeling of context and appraisal in AA. The free-text entries were classified into five categories: daily routines and household, leisure and recreation, social and personal relationships, work and professional engagements, health and well-being, plus an indeterminate category. Results showed the BPD group had lower values across outcomes and reacted with significantly lower calmness and self-esteem during social/personal events, as well as significantly lower self-esteem during health- and well-being-related activities, compared with controls. When sentiment was modeled alongside event categories, more positive-than-usual sentiments were associated with higher calmness, valence, and self-esteem, whereas more negative-than-usual sentiments were associated with lower states, with larger sentiment reactivity in BPD for calmness, valence and self-esteem. By employing LLMs for automated text categorization and sentiment analysis of free-text entries within AA research, we have effectively incorporated contextual information into our analysis. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

PMID:
42507383
Bibliographic data and abstract were imported from PubMed on 27 Jul 2026.

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