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.