Artificial Intelligence and Physical Activity for Mental Health in Cognitively Impaired Older Adults

Recent shifts in psychiatric and mental health nursing reflect the growing need to integrate both technological innovations and evidence-based behavioural interventions to support vulnerable populations. Artificial intelligence (AI) has rapidly emerged as an influential tool in mental health care, prompting systematic evaluations of its effectiveness and clinical applicability. Evidence syntheses indicate that AI-driven approaches—such as machine-learning–based risk prediction, natural language processing for symptom detection and digital phenotyping—hold promise for improving early identification of mental health concerns and enhancing clinical decision-making (Fusar-Poli et al. 2022). Systematic reviews further suggest that AI technologies may strengthen screening accuracy for depression, suicide risk and cognitive impairment through advanced pattern recognition and large-scale data processing (Shatte et al. 2019). At the same time, the rising prevalence of cognitive impairment among older adults highlights the urgent need to identify interventions that protect psychological well-being in this growing population. A substantial body of evidence demonstrates that physical activity can offer meaningful benefits for cognitive and mental health outcomes. Longitudinal studies show that regular physical activity is associated with reduced risks of cognitive decline and depressive symptoms (Smith and Blumenthal 2016). These effects may result from enhanced neuroplasticity, improved cerebral blood flow and reduced neuroinflammation, mechanisms that also contribute to emotional regulation and cognitive resilience. Intervention trials further reveal that structured exercise programmes in individuals with dementia improve not only cognitive performance but also behavioural and psychological symptoms, including mood and anxiety (Lee et al. 2025). Recent systematic reviews similarly emphasize that aerobic and multicomponent training support executive functioning and emotional stability in older adults with mild to moderate impairment (Nuzum et al. 2020). These findings establish physical activity as a feasible and modifiable strategy for mental health preservation. For physical activity, barriers such as motivational decline, mobility limitations and caregiver dependence restrict participation among cognitively impaired older adults. Complexities underscore the need for psychiatric and mental health nurses to critically appraise evidence, tailor interventions to functional and contextual needs and ensure that AI-based tools or behavioural strategies complement patient-centred care rather than replace it. Strengthening the evidence base across both technological and behavioural domains will equip nurses with more comprehensive, evidence-informed approaches to support diverse mental health needs. Continued research integrating neurobiological, behavioural and data-driven perspectives will be essential for advancing practice and improving outcomes in psychiatric and mental health nursing. In conclusion, the integration of AI-driven technologies and physical activity–based interventions represents a promising, multifaceted approach to improving mental health outcomes, particularly among vulnerable populations such as cognitively impaired older adults. While AI enhances early detection and clinical decision-making, physical activity contributes to neurobiological and psychological resilience. The author declares no conflicts of interest. Data sharing is not applicable to this article as no new data were created or analysed in this study.