Computerized cognitive training in people with depression: a protocol for a systematic review and meta-analysis

Impact of AI-Powered Solutions in Rehabilitation Process: Recent Improvements and Future Trends

Rehabilitation is an important and necessary part of local and global healthcare services along with treatment and palliative care, prevention of disease, and promotion of good health. The rehabilitation process helps older and young adults even children to become as independent as possible in activities of daily life and enables participation in useful living activities, recreation, work, and education. The technology of Artificial Intelligence (AI) has evolved significantly in recent years. Many activities related to rehabilitation have been getting benefits from using AI techniques. The objective of this review study is to explore the advantages of AI for rehabilitation and how AI is impacting the rehabilitation process. This study aims at the most critical aspects of the rehabilitation process that could potentially take advantage of AI techniques including personalized rehabilitation apps, rehabilitation through assistance, rehabilitation for neurological disorders, rehabilitation for developmental disorders, virtual reality rehabilitation, rehabilitation of neurodegenerative diseases and Telerehabilitation of Cardiovascular. We presented a survey on the newest empirical studies available in the literature including the AI-based technology helpful in the Rehabilitation process. The novelty feature included but was not limited to an overview of the technological solutions useful in rehabilitation. Seven different categories were identified. Illustrative examples of practical applications were detailed. Implications of the findings for both research and practice were critically discussed. Most of the AI applications in these rehabilitation types are in their infancy and continue to grow while exploring new opportunities. Therefore, we investigate the role of AI technology in rehabilitation processes. In addition, we do statistical analysis of the selected studies to highlight the significance of this review work. In the end, we also present a discussion on some challenges, and future research directions.

Effect of cognitive retraining treatment in mild to moderate depressive disorders

Background

Cognitive retraining or remediation approaches dispense high levels of stimulation and new learning tasks, leading to an increased neural connections, which facilitate rapid recovery in patients with neurological as well as psychiatric conditions.

Objectives

The current study aimed to investigate the effect of cognitive retraining (CR) in depressive disorders. We assigned 40 patients with mild to moderate depression to two sample groups, with 20 participants each: CR alone and CR with medicine. A 6-week CR module was delivered, and participants’ scores on measures such as the Beck Depression Inventory-II, Metacognition Questionnaire 30, World Health Organization Quality of Life- Brief, and Global Assessment of Functioning were compared.

Results

Analysis using Stata/IC version 16 included descriptive statistics, paired and independent t-tests, analysis of covariance, and propensity score matching. Cohen's d was computed to determine the effect size. Within-group analysis revealed statistically significant differences in pre-post scores of the outcome measures (p  < .05) and large effect size (d  = 3.41; d  = 3.60) in both groups. The difference in scores of outcome measures between the groups was not significant (p  > .05) even when covariates were controlled, or nearest neighbor match analysis was carried out. CR is effective in alleviating symptoms and dysfunctional metacognitive beliefs in addition to enhancing functioning and quality of life.

Conclusions

CR-based interventions may be essential mental health services owing to growing research in psychotherapy via virtual modes such as tele- and video-conferencing. These interventions can substantiate both prevention and remedy.