Papers by Sverker Sikström
ALBA: Adaptive Language-Based Assessments for Mental Health (2024.naacl-long)
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| Challenge: | Adaptive language-based assessments require a substantial sample of words per person for accuracy. |
| Approach: | They propose an adaptive language-based assessment task that involves ordering questions and scoring latent psychological trait using limited language responses to previous questions. |
| Outcome: | The proposed methods improve over non-adaptive baselines, but are more accurate and scalable with fewer questions. |
MAQuA: Multi-outcome Adaptive Question-Asking for Mental Health using Item Response Theory (2026.eacl-long)
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Vasudha Varadarajan, Hui Xu, Rebecca Astrid Böhme, Mariam Marlen Mirström, Sverker Sikström, H. Andrew Schwartz
| Challenge: | Evaluations of large language models (LLMs) indicate that such assessments are inconsistent and in many cases less accurate than dedicated condition-specific models with established psychometric validity. |
| Approach: | They propose a multi-outcome modeling and adaptive question-asking framework for simultaneous, multidimensional mental health screening that integrates language responses with item response theory and factor analysis. |
| Outcome: | Empirical results show that MAQuA reduces the number of assessment questions required for score stabilization by 50–87% compared to random ordering. |