超越感觉好转：能力维持型情感对话作为纵向研究范式

摘要

情感对话研究包含两个具有影响力的策略传统。共情对话优先理解说话者的情感体验；情感支持对话则针对寻求支持者当前的诉求，选择和编排相应的支持策略。持续使用引入了又一重目标：有效的支持应当在整个交互生命周期中，维持用户在情绪调节、应对方式、自我认同决策及社会联结方面的能力。我们提出“能力维持型情感对话”（capability-sustaining emotional dialogue, CSED），将其作为一种纵向研究范式，使支持策略与该目标保持一致，并围绕重复使用、非使用、转换与终止来组织数据、模型、系统设计、评估与治理。一项针对文献与语料库的定向审计支撑了这一立场。在PRISMA-ScR指南引导的样本中，60篇系统构建论文里有95%追求以缓解情绪为导向的目标；没有一篇评估能力或纵向结果，仅有一篇考虑了依赖性、自主性或终止风险。在300条ESConv支持者话语中，能力相关功能出现于43.0%的语句，而泛化建议占22.0%；相比之下，重评占4.0%，自我效能支持占6.7%，边界行为仅占0.3%。我们发布了一项将审计扩展至模型行为的协议。一个示例性过程模型将潜在的用户能力与六项设计承诺、四个评估时间尺度及生命周期约束联系起来。由此形成的研究议程使CSED在数据、策略设计、训练、评估与治理等层面均可测试。

English

Emotional dialogue research includes two influential strategy traditions. Empathetic dialogue prioritizes understanding a speaker's emotional experience. Emotional support conversation selects and sequences support for the seeker's current needs. Sustained use introduces a further goal. Effective support should sustain users' capacities for emotion regulation, coping, self-endorsed decisions, and social connection across the interaction lifecycle. We propose capability-sustaining emotional dialogue (CSED) as a longitudinal research paradigm that aligns supportive strategy with this goal and organizes data, models, system design, evaluation, and governance around repeated use, non-use, transition, and termination. A targeted literature-and-corpus audit motivates this position. In a PRISMA-ScR-guided sample, 95% of 60 system-building papers pursue relief-oriented goals. None evaluates capability or longitudinal outcomes, and only 1 considers dependency, autonomy, or termination risk. In 300 ESConv supporter turns, capability-relevant functions appear in 43.0%, while generic suggestions account for 22.0%, compared with 4.0% reappraisal, 6.7% self-efficacy support, and 0.3% boundary behavior. We release a protocol for extending the audit to model behavior. An illustrative process model connects latent user capability to six design commitments, four evaluation timescales, and lifecycle constraints. The resulting agenda makes CSED testable across data, policy design, training, evaluation, and governance.