RSPC: A Benchmark for Modeling Stress and Psychiatric Conditions in Digitally Mediated Relationships using Psychiatrist Annotations
Not on the map. Why?
Abstract (arXiv)
In NLP, mental health conditions are often modeled as isolated phenomena, without interpersonal context. We use Reddit posts about long-distance relationships to capture both mental health distress and associated relational triggers. We introduce the Relational Stress and Psychiatry Corpus (RSPC) containing 1,799 Reddit posts annotated by psychiatrists for diagnostic categories, including the most prevalent mood disorders (anxiety and depression), relational stressor triggers, and indications of relationship phase. We benchmark seven fine-tuned transformer models and five large language models across multi-label disorder classification, relational trigger detection, and temporal phase prediction tasks. We find clear task-dependent differences between model families, with Claude-3-Haiku achieving the best disorder classification performance (Macro-F1 = 0.538) and GPT-4o obtaining the strongest relational trigger detection performance (Macro-F1 = 0.519), suggesting distinct model capabilities. We further find strong associations between anxiety disorders and chronic relational uncertainty. Overall, RSPC establishes a benchmark for NLP tasks that consider relational context and supports a shift from individual-centric to context-aware mental health modeling that captures the social and temporal dynamics of distress.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 14 of its 41 references that are in the map. First posted on arXiv 25 Jun 2026.
Builds on
14 of 41 references.
References · 14
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
- 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
- 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,893
- 2020Longformer: The Long-Document Transformercited by 3,413
- 2020Big Bird: Transformers for Longer Sequencescited by 1,684
- 2019Publicly Available Clinical BERT Embeddingscited by 1,002
- 2023ChatGPT Outperforms Crowd-Workers for Text-Annotation Taskscited by 870
- 2017Depression and Self-Harm Risk Assessment in Online Forumscited by 84
- 2018SMHD: A Large-Scale Resource for Exploring Online Language Usage for Multiple Mental Health Conditionscited by 73
- 2020On the State of Social Media Data for Mental Health Researchcited by 32
- 2016Identifying Depression on Twittercited by 10
2 more
Built on by
Not cited yet.