Scholarlink

Mood disorders are highly heterogeneous conditions that are a leading cause of disability around the world. This is particularly important in perinatal mental health, where there is an increased incidence during the perinatal period and significant impact on child outcomes. Psychological interventions such as internet-based Cognitive Behavioural Therapy (iCBT) have the potential to treat depression and anxiety and address underlying vulnerabilities, however it is limited in its ability to address individual vulnerabilities. We describe a framework where computerized adaptive testing (CAT), that has conventionally been applied in education, can be used to efficiently profile individual vulnerabilities. These responses as well as information from medical records and cognitive task information are incorporated into a recommender system for selecting iCBT modules that would be most likely to address individual vulnerabilities.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Personalised Profiling in Mental Health: A CAT-Based Approach for Maternal Well-being and Mood Disorders

  • 章节

  • 发表日期：

    2026年

查看全文
  • Geoffrey Chern-Yee Tan,
  • Hong Ming Tan,
  • Nikita Rane,
  • Ethel Siew Ee Tan,
  • Nawal Hashim,
  • Chloe Wei En Teo,
  • Kah Vui Fong,
  • Malorie Rui Yi Yoong,
  • Rishabh Garg,
  • Shayaan Sultan,
  • Jussi Keppo,
  • Sharon Lu Huixian,
  • Peilun Dai

摘要

Mood disorders are highly heterogeneous conditions that are a leading cause of disability around the world. This is particularly important in perinatal mental health, where there is an increased incidence during the perinatal period and significant impact on child outcomes. Psychological interventions such as internet-based Cognitive Behavioural Therapy (iCBT) have the potential to treat depression and anxiety and address underlying vulnerabilities, however it is limited in its ability to address individual vulnerabilities. We describe a framework where computerized adaptive testing (CAT), that has conventionally been applied in education, can be used to efficiently profile individual vulnerabilities. These responses as well as information from medical records and cognitive task information are incorporated into a recommender system for selecting iCBT modules that would be most likely to address individual vulnerabilities.