Pre- and Post-COVID AI-Driven Mental Health Solutions for Informal Caregivers: A Scoping Review

作者：Simon Birhanu, Janisa Kabir, Kudiza Abdulswabul, Jean Claude Nahayo, Oliviya Manoj Naduvilpurakkal Manoj, Ping Zhu, Abdul Samad, Haddijatou Kadji Ceesay, Bindi Bennett, Dean McDonnell, Junaid Aḥmad, Barry Bentley, Ali Cheshmehzangi, Yu-Tao Xiang, Zhaohui Su · 发表于：Open MIND · 年份：2026 · DOI：10.17605/osf.io/zdnjx · 研究领域：Digital Mental Health Interventions、Family Caregiving in Mental Illness、Dementia and Cognitive Impairment Research

Informal caregivers provide care and support without payment to people with long-term illnesses, disabilities, cognitive impairments, and other long-term conditions. Although they are extremely essential for healthcare systems, informal caregivers often face mental challenges, including stress, anxiety, depression, caregiver burden, emotional strain, and reduced quality of life. Artificial intelligence (AI) technologies are continuously being developed to help with care through personal assistance, monitoring, communication, decision support, and emotional support. However, it is unclear how much AI technologies contribute to improving or affecting the mental health and well-being of informal caregivers. Therefore, this scoping review aims to map the existing evidence, identify the types of AI technologies used, summarize the mental health outcomes studied, and point out areas needing further research.