Future Me, a Prospection-Based Chatbot to Promote Mental Well-Being in Youth: Two Exploratory User Experience Studies.

IF 2 Q3 HEALTH CARE SCIENCES & SERVICES
Martin Dechant, Eva Lash, Sarah Shokr, Ciarán O'Driscoll
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引用次数: 0

Abstract

Background: Digital interventions have been proposed as a solution to meet the growing demand for mental health support. Large language models (LLMs) have emerged as a promising technology for creating more personalized and adaptive mental health chatbots. While LLMs generate responses based on statistical patterns in training data rather than through conscious reasoning, they can be designed to support important psychological processes. Prospection-the ability to envision and plan for future outcomes-represents a transdiagnostic process altered across various mental health conditions that could be effectively targeted through such interventions. We designed "Future Me," an LLM-powered chatbot designed to facilitate future-oriented thinking and promote goal pursuit using evidence-based interventions including visualization, implementation intentions, and values clarification.

Objective: This study aims to understand how users engage with Future Me, evaluate its effectiveness in supporting future-oriented thinking, and assess its acceptability across different populations, with particular attention to postgraduate students' stress management needs. We also seek to identify design improvements that could enhance the chatbot's ability to support users' mental well-being.

Methods: In total, 2 complementary studies were conducted. Study 1 (n=20) examined how postgraduate students used Future Me during a single guided session, followed by semistructured interviews. Study 2 (n=14) investigated how postgraduate students interacted with Future Me over a 1-week period, with interviews before and after usage. Both studies analyzed conversation transcripts and interview data using thematic analysis to understand usage patterns, perceived benefits, and limitations.

Results: Across both studies, participants primarily engaged with Future Me to discuss career or education goals, personal obstacles, and relationship concerns. Users valued Future Me's ability to provide clarity around goal-setting (85% of participants), its nonjudgmental nature, and its 24/7 accessibility (58%). Future Me effectively facilitated self-reflection (80%) and offered new perspectives (70%), particularly for broader future-oriented concerns. However, both studies revealed limitations in the chatbot's ability to provide personalized emotional support during high-stress situations, with participants noting that responses sometimes felt formulaic (50%) or lacked emotional depth. Postgraduate students specifically emphasized the need for greater context awareness during periods of academic stress (58%). Overall, 57% of requests occurred outside office hours, dropping from 40 on day 1 to 12 by day 7.

Conclusions: Future Me demonstrates promise as an accessible tool for promoting prospection skills and supporting mental well-being through future-oriented thinking. However, effectiveness appears context-dependent, with prospection techniques more suitable for broader life decisions than acute stress situations. Future development should focus on creating more adaptive systems that can adjust their approach based on the user's emotional state and immediate needs. Rather than attempting to replicate human therapy entirely, chatbots like Future Me may be most effective when designed as complementary tools within broader support ecosystems, offering immediate guidance while facilitating connections to human support when needed.

未来的我,一个基于前瞻性的聊天机器人,促进青少年心理健康:两个探索性的用户体验研究。
背景:数字干预已被提出作为满足日益增长的心理健康支持需求的解决方案。大型语言模型(llm)已经成为一种有前途的技术,用于创建更个性化和适应性更强的心理健康聊天机器人。虽然法学硕士基于训练数据中的统计模式而不是通过有意识的推理产生反应,但它们可以被设计为支持重要的心理过程。前瞻性——对未来结果的设想和计划的能力——代表了一种跨各种心理健康状况的跨诊断过程,可以通过这种干预有效地针对这些状况。我们设计了“未来的我”,这是一个llm驱动的聊天机器人,旨在促进面向未来的思考,并通过基于证据的干预措施(包括可视化、实施意图和价值观澄清)促进目标追求。目的:本研究旨在了解用户如何参与“未来我”,评估其在支持面向未来思维方面的有效性,并评估其在不同人群中的可接受性,特别关注研究生的压力管理需求。我们还试图确定设计改进,以增强聊天机器人支持用户心理健康的能力。方法:共进行2项补充研究。研究1 (n=20)调查了研究生在一次指导会话中如何使用Future Me,随后是半结构化访谈。研究2 (n=14)调查了研究生在一周内与Future Me的互动情况,在使用之前和之后进行了访谈。两项研究都使用主题分析分析了对话记录和访谈数据,以了解使用模式、可感知的好处和局限性。结果:在这两项研究中,参与者主要与Future Me讨论职业或教育目标、个人障碍和关系问题。用户认为Future Me能够提供清晰的目标设定(85%的参与者),它的非评判性,以及它的全天候可访问性(58%)。“未来的我”有效地促进了自我反思(80%),并提供了新的视角(70%),特别是对于更广泛的面向未来的关注。然而,这两项研究都揭示了聊天机器人在高压力情况下提供个性化情感支持的能力的局限性,参与者注意到,回应有时会让人觉得公式化(50%)或缺乏情感深度。研究生特别强调在学业压力期间需要更强的情境意识(58%)。总的来说,57%的请求发生在办公时间之外,从第1天的40个下降到第7天的12个。结论:未来的我证明了承诺是一个可访问的工具,通过面向未来的思维来促进前景技能和支持心理健康。然而,有效性似乎与环境有关,勘探技术更适合于更广泛的生活决策,而不是急性压力情况。未来的发展应该侧重于创造更多的适应性系统,这些系统可以根据用户的情绪状态和即时需求来调整它们的方法。“未来我”这样的聊天机器人不是试图完全复制人类的治疗方法,而是在更广泛的支持生态系统中作为补充工具来设计,提供即时指导,同时在需要时促进与人类支持的联系,这可能是最有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
JMIR Formative Research
JMIR Formative Research Medicine-Medicine (miscellaneous)
CiteScore
2.70
自引率
9.10%
发文量
579
审稿时长
12 weeks
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