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        <title>Beyond Reflection: Affirmation as a Promising Behavioral Marker Associated with Quality in Text-Based Counseling</title>
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    <abstract>While AI-assisted text-based counseling is gaining attention, it remains empirically unclear which counselor behaviors are associated with higher dialogue quality. Existing research often focuses heavily on Reflection, borrowing frameworks from Motivational Interviewing. To address this gap, we conduct a multi-layered analysis using KokoroChat, a large-scale Japanese text counseling dataset conducted by professional counselors and trainees, newly annotated with counselor strategy tags and client distress levels. Our results show that, under the quality indicators used in this study, Affirmation is more consistently associated with session quality than Reflection among the analyzed strategies. Cross-dataset transfer experiments further suggest that this quality signal can be observed to some extent on ESConv, an English dataset with non-expert supporters. These findings provide empirical implications for counselor training and emotional support system design. We release the additional KokoroChat annotations and experimental source code at https://github.com/UEC-InabaLab/BeyondReflection</abstract>
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%0 Conference Proceedings
%T Beyond Reflection: Affirmation as a Promising Behavioral Marker Associated with Quality in Text-Based Counseling
%A Inaba, Michimasa
%Y Lee, Hung-Yi
%Y Dev, Sunipa
%Y Li, Jessy
%Y Elliott, Desmond
%S Findings of the Association for Computational Linguistics: EMNLP 2026
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-462-0
%F inaba-2026-beyond
%X While AI-assisted text-based counseling is gaining attention, it remains empirically unclear which counselor behaviors are associated with higher dialogue quality. Existing research often focuses heavily on Reflection, borrowing frameworks from Motivational Interviewing. To address this gap, we conduct a multi-layered analysis using KokoroChat, a large-scale Japanese text counseling dataset conducted by professional counselors and trainees, newly annotated with counselor strategy tags and client distress levels. Our results show that, under the quality indicators used in this study, Affirmation is more consistently associated with session quality than Reflection among the analyzed strategies. Cross-dataset transfer experiments further suggest that this quality signal can be observed to some extent on ESConv, an English dataset with non-expert supporters. These findings provide empirical implications for counselor training and emotional support system design. We release the additional KokoroChat annotations and experimental source code at https://github.com/UEC-InabaLab/BeyondReflection
%U https://aclanthology.org/2026.findings-emnlp.782/
%P 16557-16571

Markdown (Informal)

[Beyond Reflection: Affirmation as a Promising Behavioral Marker Associated with Quality in Text-Based Counseling](https://aclanthology.org/2026.findings-emnlp.782/) (Inaba, Findings 2026)

• Beyond Reflection: Affirmation as a Promising Behavioral Marker Associated with Quality in Text-Based Counseling (Inaba, Findings 2026)

ACL

• Michimasa Inaba. 2026. Beyond Reflection: Affirmation as a Promising Behavioral Marker Associated with Quality in Text-Based Counseling. In Findings of the Association for Computational Linguistics: EMNLP 2026, pages 16557–16571, Budapest, Hungary. Association for Computational Linguistics.