Milagros C. Escoredo, Karin Mostovoy, Ross Schickler, Alexis Bechtel, Jennah Shagan, Eduardo L. Bunge
{"title":"通过基于人工智能的对话代理提高父母技能：PAT倡议","authors":"Milagros C. Escoredo, Karin Mostovoy, Ross Schickler, Alexis Bechtel, Jennah Shagan, Eduardo L. Bunge","doi":"10.1111/fare.13158","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Objective</h3>\n \n <p>We aim to describe the development of a conversational agent (CA) for parenting, termed PAT (Parenting Assistant platform), to demonstrate how artificial intelligence (AI) can enhance parenting skills.</p>\n </section>\n \n <section>\n \n <h3> Background</h3>\n \n <p>Behavioral problems are the most common issues in childhood mental health. Developing and disseminating scalable interventions to address early-stage behavioral problems are of high priority. Artificial intelligence (AI)-based CAs can offer innovative methods to deliver parenting interventions to reduce behavioral problems. CAs have the capability to interact through text or voice conversations and can undergo training using evidence-based parenting programs. However, research on CAs for parenting and behavioral problems is limited.</p>\n </section>\n \n <section>\n \n <h3> Experience</h3>\n \n <p>The development of PAT consisted of three phases: Phase 1 was purely rule-based, Phase 2 was hybrid (rule-based format plus large language models), and Phase 3 featured an agentic architecture. The latest version of PAT includes prompt engineering, guardrails, retrieval-augmented generation, few-shots learning, context, and memory management through agentic architecture. Although comprehensive empirical results are pending, the iterative development and enhancement of PAT indicate the potential for effective digital intervention. The agentic architecture of the latest version of PAT aims to provide robust, context-aware interactions to support parenting challenges.</p>\n </section>\n \n <section>\n \n <h3> Implications</h3>\n \n <p>CAs have the potential to reach a broader population of parents and deliver personalized interventions tailored to their specific needs. Moreover, CAs are structured to provide timely support, which can enhance family dynamics and contribute to improved long-term outcomes for both parents and children.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>AI-based CAs can be used as alternatives to waitlists; as digital cotherapists; and implemented in health care, mental health, and school settings. The potential benefits and risks of the different types of CA and features are discussed.</p>\n </section>\n </div>","PeriodicalId":48206,"journal":{"name":"Family Relations","volume":"74 3","pages":"1250-1265"},"PeriodicalIF":1.7000,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/fare.13158","citationCount":"0","resultStr":"{\"title\":\"Enhancing parental skills through artificial intelligence-based conversational agents: The PAT Initiative\",\"authors\":\"Milagros C. Escoredo, Karin Mostovoy, Ross Schickler, Alexis Bechtel, Jennah Shagan, Eduardo L. Bunge\",\"doi\":\"10.1111/fare.13158\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Objective</h3>\\n \\n <p>We aim to describe the development of a conversational agent (CA) for parenting, termed PAT (Parenting Assistant platform), to demonstrate how artificial intelligence (AI) can enhance parenting skills.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>Behavioral problems are the most common issues in childhood mental health. Developing and disseminating scalable interventions to address early-stage behavioral problems are of high priority. Artificial intelligence (AI)-based CAs can offer innovative methods to deliver parenting interventions to reduce behavioral problems. CAs have the capability to interact through text or voice conversations and can undergo training using evidence-based parenting programs. However, research on CAs for parenting and behavioral problems is limited.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Experience</h3>\\n \\n <p>The development of PAT consisted of three phases: Phase 1 was purely rule-based, Phase 2 was hybrid (rule-based format plus large language models), and Phase 3 featured an agentic architecture. The latest version of PAT includes prompt engineering, guardrails, retrieval-augmented generation, few-shots learning, context, and memory management through agentic architecture. Although comprehensive empirical results are pending, the iterative development and enhancement of PAT indicate the potential for effective digital intervention. The agentic architecture of the latest version of PAT aims to provide robust, context-aware interactions to support parenting challenges.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Implications</h3>\\n \\n <p>CAs have the potential to reach a broader population of parents and deliver personalized interventions tailored to their specific needs. Moreover, CAs are structured to provide timely support, which can enhance family dynamics and contribute to improved long-term outcomes for both parents and children.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusion</h3>\\n \\n <p>AI-based CAs can be used as alternatives to waitlists; as digital cotherapists; and implemented in health care, mental health, and school settings. 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Enhancing parental skills through artificial intelligence-based conversational agents: The PAT Initiative
Objective
We aim to describe the development of a conversational agent (CA) for parenting, termed PAT (Parenting Assistant platform), to demonstrate how artificial intelligence (AI) can enhance parenting skills.
Background
Behavioral problems are the most common issues in childhood mental health. Developing and disseminating scalable interventions to address early-stage behavioral problems are of high priority. Artificial intelligence (AI)-based CAs can offer innovative methods to deliver parenting interventions to reduce behavioral problems. CAs have the capability to interact through text or voice conversations and can undergo training using evidence-based parenting programs. However, research on CAs for parenting and behavioral problems is limited.
Experience
The development of PAT consisted of three phases: Phase 1 was purely rule-based, Phase 2 was hybrid (rule-based format plus large language models), and Phase 3 featured an agentic architecture. The latest version of PAT includes prompt engineering, guardrails, retrieval-augmented generation, few-shots learning, context, and memory management through agentic architecture. Although comprehensive empirical results are pending, the iterative development and enhancement of PAT indicate the potential for effective digital intervention. The agentic architecture of the latest version of PAT aims to provide robust, context-aware interactions to support parenting challenges.
Implications
CAs have the potential to reach a broader population of parents and deliver personalized interventions tailored to their specific needs. Moreover, CAs are structured to provide timely support, which can enhance family dynamics and contribute to improved long-term outcomes for both parents and children.
Conclusion
AI-based CAs can be used as alternatives to waitlists; as digital cotherapists; and implemented in health care, mental health, and school settings. The potential benefits and risks of the different types of CA and features are discussed.
期刊介绍：
A premier, applied journal of family studies, Family Relations is mandatory reading for family scholars and all professionals who work with families, including: family practitioners, educators, marriage and family therapists, researchers, and social policy specialists. The journal"s content emphasizes family research with implications for intervention, education, and public policy, always publishing original, innovative and interdisciplinary works with specific recommendations for practice.
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