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Consensus recommendations outline non-pharmacological strategies for agitation management in dementia, enhancing care quality.
Agitation is among the most disabling behavioral and psychological symptoms of dementia, contributing substantially to caregiver burden, institutionalization, and healthcare utilization. Considering the modest efficacy and significant adverse effects associated with psychotropic medications, person-centered approaches (PCAs) and non-pharmacological interventions are recommended as first-line management strategies. We conducted a comprehensive search on PubMed, Medline, Embase, PsycINFO, CINAHL, and the Cochrane Library for systematic reviews, meta-analyses, and randomized controlled trials evaluating PCA and non-pharmacological interventions for agitation in dementia published before September 30, 2025. The quality of evidence and strength of recommendations were evaluated using the Grades of Recommendation, Assessment, Development and Evaluation (GRADE) framework. Moderate-quality evidence supports the use of massage or touch therapy, particularly individualized music therapy, tailored activity programs, and multicomponent interventions. By contrast, sensory-based approaches such as aromatherapy and Snoezelen demonstrated inconsistent or low-quality evidence. The organizational-level implementation of PCA and structured need-driven assessments are associated with improved quality of life and appear to enhance the effectiveness of subsequent non pharmacological interventions. The most consistent and clinically meaningful benefits were observed when individualized strategies were preceded by systematic PCA- based assessment. Overall, PCA-guided, multifaceted non-pharmacological interventions provide the preferred foundation for managing agitation in dementia, reducing reliance on pharmacotherapy while promoting care quality, dignity, and overall wellbeing. Future efforts should focus on optimizing implementation through structured staff training, interdisciplinary collaboration, and technology-assisted assessment models to improve feasibility and scalability across diverse care settings.
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Chen et al. (2026) studied this question.
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