SynthesisJMIR mental health2026
AI-Driven Mental Health Support for Caregivers of Individuals With Alzheimer Disease: Systematic Literature Review and Development of a Conceptual Framework.
Synthesis in JMIR mental health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
6 authors.
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Abstract
backgroundCaregivers supporting individuals with Alzheimer disease and related dementias (AD/ADRD) frequently encounter prolonged emotional strain, psychological distress, and social isolation, yet their needs are largely overlooked in current technological and clinical interventions. The special routines and obligations of caregivers of individuals with AD/ADRD are frequently not well-suited to the many artificial intelligence-driven (AI-driven) mental health solutions that are currently available. This reveals a critical need for sophisticated, customized solutions created especially to help the mental health of caregivers for patients with AD/ADRD.
objectiveTo address the existing limitations of personalized mental health interventions, we aimed to identify existing literature on personalized mental health interventions using AI for specific purposes and to develop a new framework for the caregivers of individuals with AD/ADRD.
methodsWe followed an iterative approach to design the new framework. First, we did a systematic literature review of current literature to identify data analysis, AI methods, and personalized interventions. Second, we focused on the underlying gaps of this research, and by synthesizing our findings from the review, we proposed a conceptual framework.
resultsThe systematic literature review identified 73 unique results, and from external sources, we found 3 unique potential papers. Of these, 28 papers were eligible for inclusion, on which we performed our analysis. Based on the findings, we developed a new conceptual framework with 3 special features that are specifically for caregivers of patients with AD/ADRD. The 3 unique features are a personalized daily routine scheduler, which will take both patients with AD/ADRD and caregiver's information to make it personalized, a daily reward system to keep patients motivated, and an educational repository to get the bite-sized knowledge for the lesson of handling patients in an efficient manner and taking care of one's own mental health.
conclusionsThe proposed framework provides a chance for caregivers to receive mental health care, which will be personalized. The framework is developed with more updated methods than existing approaches, with a lack of personalization in this sector. This framework can be implemented with a goal of personalization and explainable approaches and can undergo further iterations to ensure it is appropriate for specific purposes.
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