@inproceedings{qi-2026-roleethic,
title = "{R}ole{E}thic: Structured Prompting and Failure Analysis for Open-Ended Mental Health Ethics",
author = "Qi, Meiyi",
editor = "Wang, Zimu and
Jiang, Yiwen and
Shen, Yaling and
Zhao, Xiangyu and
Fong, Stephanie and
Sun, Xin and
Zhou, Yi and
Ji, Shaoxiong and
Desimone, Robert and
Nelson, Barnaby and
Dwyer, Dominic and
Ge, Zongyuan",
booktitle = "Proceedings of the 1st Workshop on Multimodal, Multilingual, and Multicultural Mental Health and Psychotherapy ({M}ulti{P}syche)",
month = nov,
year = "2026",
address = "Hengqin, Zhuhai, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.multipsyche-1.15/",
pages = "181--185",
ISBN = "979-8-89176-448-4",
abstract = "Open-ended mental health ethics questions require models to balance stakeholder interests, ethical constraints, and conflicting courses of action. We present RoleEthic, a fourteen-stage structured prompting framework for the Open-Ended Question (OEQ) track of the PsychEthicsEval shared task at MultiPsyche 2026. The stages organize reasoning around case facts, stakeholder relationships and perspectives, and the AI{'}s role; gather and classify ethical considerations, apply a bottom-line check, and prioritize concerns; and guide response drafting and review for ethical consistency, role consistency, unsupported high-impact claims, and risky details. The framework runs within a single Qwen3-30B-A3B model call without explicit role labels or external verification and returns only the final response. In the official Phase 2 evaluation, RoleEthic achieves ethical rates of 0.562 under the rule pre-filter plus ModernBERT classifier approach and 0.522 under the GPT-5-mini judge approach, placing third among three submissions under each approach. Output diagnostics identify verbosity and additional contact-like details, while three purposively selected cases illustrate unsupported jurisdictional claims and role inconsistency in final responses."
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<abstract>Open-ended mental health ethics questions require models to balance stakeholder interests, ethical constraints, and conflicting courses of action. We present RoleEthic, a fourteen-stage structured prompting framework for the Open-Ended Question (OEQ) track of the PsychEthicsEval shared task at MultiPsyche 2026. The stages organize reasoning around case facts, stakeholder relationships and perspectives, and the AI’s role; gather and classify ethical considerations, apply a bottom-line check, and prioritize concerns; and guide response drafting and review for ethical consistency, role consistency, unsupported high-impact claims, and risky details. The framework runs within a single Qwen3-30B-A3B model call without explicit role labels or external verification and returns only the final response. In the official Phase 2 evaluation, RoleEthic achieves ethical rates of 0.562 under the rule pre-filter plus ModernBERT classifier approach and 0.522 under the GPT-5-mini judge approach, placing third among three submissions under each approach. Output diagnostics identify verbosity and additional contact-like details, while three purposively selected cases illustrate unsupported jurisdictional claims and role inconsistency in final responses.</abstract>
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%0 Conference Proceedings
%T RoleEthic: Structured Prompting and Failure Analysis for Open-Ended Mental Health Ethics
%A Qi, Meiyi
%Y Wang, Zimu
%Y Jiang, Yiwen
%Y Shen, Yaling
%Y Zhao, Xiangyu
%Y Fong, Stephanie
%Y Sun, Xin
%Y Zhou, Yi
%Y Ji, Shaoxiong
%Y Desimone, Robert
%Y Nelson, Barnaby
%Y Dwyer, Dominic
%Y Ge, Zongyuan
%S Proceedings of the 1st Workshop on Multimodal, Multilingual, and Multicultural Mental Health and Psychotherapy (MultiPsyche)
%D 2026
%8 November
%I Association for Computational Linguistics
%C Hengqin, Zhuhai, China
%@ 979-8-89176-448-4
%F qi-2026-roleethic
%X Open-ended mental health ethics questions require models to balance stakeholder interests, ethical constraints, and conflicting courses of action. We present RoleEthic, a fourteen-stage structured prompting framework for the Open-Ended Question (OEQ) track of the PsychEthicsEval shared task at MultiPsyche 2026. The stages organize reasoning around case facts, stakeholder relationships and perspectives, and the AI’s role; gather and classify ethical considerations, apply a bottom-line check, and prioritize concerns; and guide response drafting and review for ethical consistency, role consistency, unsupported high-impact claims, and risky details. The framework runs within a single Qwen3-30B-A3B model call without explicit role labels or external verification and returns only the final response. In the official Phase 2 evaluation, RoleEthic achieves ethical rates of 0.562 under the rule pre-filter plus ModernBERT classifier approach and 0.522 under the GPT-5-mini judge approach, placing third among three submissions under each approach. Output diagnostics identify verbosity and additional contact-like details, while three purposively selected cases illustrate unsupported jurisdictional claims and role inconsistency in final responses.
%U https://aclanthology.org/2026.multipsyche-1.15/
%P 181-185
Markdown (Informal)
[RoleEthic: Structured Prompting and Failure Analysis for Open-Ended Mental Health Ethics](https://aclanthology.org/2026.multipsyche-1.15/) (Qi, MultiPsyche 2026)
ACL