Efficacy and Efficiency of Computer-Assisted Cognitive Stimulation in the Rehabilitation of Patients with Psychiatric Disorders: A Retrospective Analysis of Training Strategies and Intervention Duration

In recent years, the integration of technology into mental health interventions has shown promising results. This retrospective study analyses the efficacy and efficiency of computer-assisted cognitive stimulation (CACS) among a group of 92 psychiatric patients, of whom 32 were randomly selected to benefit from a personalised intervention. Data were collected on demographic variables (age, education level, urban/rural area), psychiatric diagnoses, therapeutic regimens, and scores on validated psychometric scales, Mini Mental State Examination (MMSE), and Montreal Cognitive Assessment (MoCA), assessed before and after the intervention. Detailed metrics related to the training modules, such as the number of sessions, level achieved and duration of each session were also analysed. The results indicate statistically significant increases in MMSE (from 22.94 to 24.31, p < 0.001) and MoCA (from 22.06 to 24.22, p < 0.001) scores after CACS therapy, highlighting notable improvements in cognitive functions. The robust correlations between changes in scores suggest a positive impact of the intervention on cognitive performance. However, the retrospective nature of the study imposes certain limitations such as the potential influence of confounding variables, the lack of rigorous control of the intervention and the impossibility of establishing direct causal relationships. In addition, these results support the opportunity to integrate artificial intelligence (AI) components in the development of educational interventions in mental health, opening new directions for future research in the field.

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Journal
BRAIN BROAD RESEARCH IN ARTIFICIAL INTELLIGENCE AND NEUROSCIENCE
Published
2025-04-06
DOI
https://doi.org/10.70594/brain/16.s1/23
Primary Topic
Digital Mental Health Interventions
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article
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article

Efficacy and Efficiency of Computer-Assisted Cognitive Stimulation in the Rehabilitation of Patients with Psychiatric Disorders: A Retrospective Analysis of Training Strategies and Intervention Duration

Lucia Corina Dima-Cozma, Marius Bragaru, Irina Săcuiu, Romeo Dobrin et al.
BRAIN BROAD RESEARCH IN ARTIFICIAL INTELLIGENCE AND NEUROSCIENCE
Digital Mental Health Interventions
article

Efficacy and Efficiency of Computer-Assisted Cognitive Stimulation in the Rehabilitation of Patients with Psychiatric Disorders: A Retrospective Analysis of Training Strategies and Intervention Duration

Lucia Corina Dima-Cozma, Marius Bragaru, Irina Săcuiu, Romeo Dobrin, Ana-Maria Dumitrescu, Florin Dumitru Petrariu, Andreea Cătălina Moroșan, Roxana Chiriță, George-Cătălin Moroșan, Gabriel Dăscălescu, Daniela-Camelia Lepădatu
article en

Abstract

In recent years, the integration of technology into mental health interventions has shown promising results. This retrospective study analyses the efficacy and efficiency of computer-assisted cognitive stimulation (CACS) among a group of 92 psychiatric patients, of whom 32 were randomly selected to benefit from a personalised intervention. Data were collected on demographic variables (age, education level, urban/rural area), psychiatric diagnoses, therapeutic regimens, and scores on validated psychometric scales, Mini Mental State Examination (MMSE), and Montreal Cognitive Assessment (MoCA), assessed before and after the intervention. Detailed metrics related to the training modules, such as the number of sessions, level achieved and duration of each session were also analysed. The results indicate statistically significant increases in MMSE (from 22.94 to 24.31, p < 0.001) and MoCA (from 22.06 to 24.22, p < 0.001) scores after CACS therapy, highlighting notable improvements in cognitive functions. The robust correlations between changes in scores suggest a positive impact of the intervention on cognitive performance. However, the retrospective nature of the study imposes certain limitations such as the potential influence of confounding variables, the lack of rigorous control of the intervention and the impossibility of establishing direct causal relationships. In addition, these results support the opportunity to integrate artificial intelligence (AI) components in the development of educational interventions in mental health, opening new directions for future research in the field.

BRAIN BROAD RESEARCH IN ARTIFICIAL INTELLIGENCE AND NEUROSCIENCEVol. 16(1, Sup. 1)
Alexandru Ioan Cuza University (RO), South Essex Partnership University Foundation NHS Trust (GB), Grigore T. Popa University of Medicine and Pharmacy (RO), Centre Hospitalier Départemental Vendée (FR)
Openalex Percentile: Top 93%
Digital Mental Health Interventions
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