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Neuropsychological Assessments of Patients With Acquired Brain Injury: A Cluster Analysis Approach to Address Heterogeneity in Web-Based Cognitive Rehabilitation.

ABSTRACT: We aimed to (1) apply cluster analysis techniques to mixed-type data (numerical and categorical) from baseline neuropsychological standard and widely used assessments of patients with acquired brain injury (ABI) (2) apply state-of-the-art cluster validity indexes (CVI) to assess their internal validity (3) study their external validity considering relevant aspects of ABI rehabilitation such as functional independence measure (FIM) in activities of daily life assessment (4) characterize the identified profiles by using demographic and clinically relevant variables and (5) extend the external validation of the obtained clusters to all cognitive rehabilitation tasks executed by the participants in a web-based cognitive rehabilitation platform (GNPT). We analyzed 1,107 patients with ABI, 58.1% traumatic brain injury (TBI), 21.8% stroke and 20.1% other ABIs (e.g., brain tumors, anoxia, infections) that have undergone inpatient GNPT cognitive rehabilitation from September 2008 to January 2021. We applied the k-prototypes algorithm from the clustMixType R package. We optimized seven CVIs and applied bootstrap resampling to assess clusters stability (fpc R package). Clusters' post hoc comparisons were performed using the Wilcoxon ranked test, paired t-test or Chi-square test when appropriate. We identified a three-clusters optimal solution, with strong stability (>0.85) and structure (e.g., Silhouette > 0.60, Gamma > 0.83), characterized by distinctive level of performance in all neuropsychological tests, demographics, FIM, response to GNPT tasks and tests normative data (e.g., the 3 min cut-off in Trail Making Test-B). Cluster 1 was characterized by severe cognitive impairment (N = 254, 22.9%) the mean age was 47 years, 68.5% patients with TBI and 22% with stroke. Cluster 2 was characterized by mild cognitive impairment (N = 376, 33.9%) mean age 54 years, 53.5% patients with stroke and 27% other ABI. Cluster 3, moderate cognitive impairment (N = 477, 43.2%) mean age 33 years, 83% patients with TBI and 14% other ABI. Post hoc analysis on cognitive FIM supported a significant higher performance of Cluster 2 vs. Cluster 3 (p < 0.001), Cluster 2 vs. Cluster 1 (p < 0.001) and Cluster 3 vs. Cluster 1 (p < 0.001). All patients executed 286,798 GNPT tasks, with performance significantly higher in Cluster 2 and 3 vs. Cluster 1 (p < 0.001).

SUBMITTER: Garcia-Rudolph A

PROVIDER: S-EPMC8380987 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundTraumatic brain injury (TBI) is a leading cause of disability worldwide. TBI is a highly heterogeneous disease, which makes it complex for effective therapeutic interventions. Cluster analysis has been extensively applied in previous research studies to identify homogeneous subgroups based on performance in neuropsychological baseline tests. Nevertheless, most analyzed samples are rarely larger than a size of 100, and different cluster analysis approaches and cluster validity indices have been scarcely compared or applied in web-based rehabilitation treatments.ObjectiveThe aims of our study were as follows: (1) to apply state-of-the-art cluster validity indices to different cluster strategies: hierarchical, partitional, and model-based, (2) to apply combined strategies of dimensionality reduction by using principal component analysis and random forests and perform stability assessment of the final profiles, (3) to characterize the identified profiles by using demographic and clinically relevant variables, and (4) to study the external validity of the obtained clusters by considering 3 relevant aspects of TBI rehabilitation: Glasgow Coma Scale, functional independence measure, and execution of web-based cognitive tasks.MethodsThis study was performed from August 2008 to July 2019. Different cluster strategies were executed with Mclust, factoextra, and cluster R packages. For combined strategies, we used the FactoMineR and random forest R packages. Stability analysis was performed with the fpc R package. Between-group comparisons for external validation were performed using 2-tailed t test, chi-square test, or Mann-Whitney U test, as appropriate.ResultsWe analyzed 574 adult patients with TBI (mostly severe) who were undergoing web-based rehabilitation. We identified and characterized 3 clusters with strong internal validation: (1) moderate attentional impairment and moderate dysexecutive syndrome with mild memory impairment and normal spatiotemporal perception, with almost 66% (111/170) of the patients being highly educated (P<.05); (2) severe dysexecutive syndrome with severe attentional and memory impairments and normal spatiotemporal perception, with 49.2% (153/311) of the patients being highly educated (P<.05); (3) very severe cognitive impairment, with 45.2% (42/93) of the patients being highly educated (P<.05). We externally validated them with severity of injury (P=.006) and functional independence assessments: cognitive (P<.001), motor (P<.001), and total (P<.001). We mapped 151,763 web-based cognitive rehabilitation tasks during the whole period to the 3 obtained clusters (P<.001) and confirmed the identified patterns. Stability analysis indicated that clusters 1 and 2 were respectively rated as 0.60 and 0.75; therefore, they were measuring a pattern and cluster 3 was rated as highly stable.ConclusionsCluster analysis in web-based cognitive rehabilitation treatments enables the identification and characterization of strong response patterns to neuropsychological tests, external validation of the obtained clusters, tailoring of cognitive web-based tasks executed in the web platform to the identified profiles, thereby providing clinicians a tool for treatment personalization, and the extension of a similar approach to other medical conditions.

Project description:BackgroundSince SCD (plus) was standardized, little is known about its demographic characteristics and its outcomes of neuropsychological assessments, including the SCD questionnaire 9 (SCD-Q9).ObjectiveTo characterize SCD (plus) by comparing the neuropsychological features among its subgroups and with normal controls (NC). Also, to explore its demographics and to understand the relation of the chief complaints and the scores of SCD-Q9.MethodsMultistage stratified cluster random sampling was conducted to select participants. As a result, 84 NC and 517 SCD (plus) were included. SCD (plus) was further classified into several subgroups (SCD-C: concerned cognitive decline; SCD-F: complaints about SCD within the past five years; SCD-P: feeling performance being not as good as their peers; SCD+: presented> 3 of SCD (plus) features; SCD-: presented ? 3 of SCD (plus) features (see the diagnostic criteria for the details)) and between-group comparisons of neuropsychological scores were conducted. Point-biserial correlation and binary logistic regression analyses were performed to investigate the demographic characteristics of its subgroups. Finally, Spearman correlation was used to better understand the relation of SCD (plus) to SCD-Q9.Results(1) Scores of AVLT-LR (AVLT-LR: Auditory Verbal Learning Test-Long Delayed Recall) and MoCA-B (MoCA: Montreal Cognitive Assessment-Basic) were lower in the SCD-P group than those in the NC group, and the SCD+ group scored lower in the MoCA-B and CDT(CDT: Clock Drawing Test) than the SCD- group. (2) Females were more concerned than male participants. Individuals with lower education level felt that their cognitive performance were worse than their peers. Also, younger people might express concerns more than the more elderly. People who had complaints of SCD-P might be more likely to report SCD-C, but less likely to report SCD-F. (3) Positive correlations were found between the chief complaints of SCD (plus) and some items of SCD-Q9.ConclusionsSCD (plus) may be related to demographic factors. Individuals with SCD (plus) already exhibited cognitive impairment, which can be detected by SCD-Q9.

Project description:ObjectiveThe present study explores the cross-cultural validation of neuropsychological assessments and their clinical applications in cognitive behavioral therapy (CBT), focusing on culturally adapted CBT (CA-CBT) across diverse populations and settings.MethodsFollowing the PRISMA guidelines, a comprehensive search was conducted in multiple academic databases, including PubMed, PsycINFO, Scopus, and Web of Science. Keywords related to cognitive behavioral therapy, cultural adaptation, and specific populations were used. The inclusion criteria encompassed randomized controlled trials (RCTs) and pilot studies that assessed CA-CBT for various mental health conditions.ResultsThe review included studies involving Chinese Americans, Latino caregivers, Syrian refugees, Jordanian children, Malaysian Muslims, Afghan refugees, Iraqi women, Japanese children and adolescents, and Tanzanian and Kenyan children. CA-CBT demonstrated significant effectiveness in reducing symptoms of depression, anxiety, PTSD, and psychosis. For instance, research has shown that CA-CBT is more effective than standard CBT in reducing depressive symptoms among Chinese Americans and in significantly lowering PTSD symptoms in Syrian refugee women. This method has been well-received and is feasible for use in diverse populations, such as Jordanian children and Afghan refugees. The long-term benefits are promising, with sustained improvements being reported in various studies. Additionally, digital and remote delivery methods have demonstrated potential for expanding the accessibility of CA-CBT.ConclusionsCA-CBT is a valuable and effective intervention for diverse cultural populations, significantly improving mental health outcomes. However, future research must address limitations such as small sample sizes, short follow-up periods, and variability in assessment tools. Future studies should include larger and more diverse sample sizes, longer follow-up periods, rigorous control groups, and comprehensive outcome measures to further validate and enhance the application of CA-CBT across different cultural contexts.

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Neuropsychological Assessments of Patients With Acquired Brain Injury: A Cluster Analysis Approach to Address Heterogeneity in Web-Based Cognitive Rehabilitation.

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