Automated Author ProfileAlqahtani, Reem
Alqahtani, Reem
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 1.3 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This study aimed to evaluate the diagnostic accuracy of Wisconsin Card Sorting Test–The Short Computerized Version (WCST-64:CV2) for children with Autism Spectrum Disorder (ASD), and differences based on gender (males and females) and classification (typically developing-TD and with ASD). The sample consisted of (N = 96) TD and (N = 48) ASD, Saudi children (aged 7–9 years). The diagnostic accuracy results showed that most (WCST-64:CV2) indicators have discrimination ability between TD and ASD children, for males and females. Accuracy differences based on gender were on three indicators (3, 4 & 5). There were no significant differences (p >.05) on indicators based on gender, however, there were significant differences (p < .01) based on classification on all indicators, except indicators (3 & 4). Interaction between gender and classification was significant (p < .05) for one indicator (5). It is recommended to use (WCST-64:CV2) to diagnose ASD children (7–9 years), based on eight indicators for males (1, 2, 3, 4, 6, 7, 8, & 9) and seven indicators for females (1, 2, 5, 6, 7, 8, & 9), and to take differences based on gender and classification into account, when using (WCST-64:CV2). The (WCST-64:CV2) could be relied on for clinical/neuropsychological assessment of ASD children.
Authors
- Darandari, Eqbal ;
- Alqahtani, Reem
This study aimed to evaluate the diagnostic accuracy of Wisconsin Card Sorting Test–The Short Computerized Version (WCST-64:CV2) for children with Autism Spectrum Disorder (ASD), and differences based on gender (males and females) and classification (typically developing-TD and with ASD). The sample consisted of (N = 96) TD and (N = 48) ASD, Saudi children (aged 7–9 years). The diagnostic accuracy results showed that most (WCST-64:CV2) indicators have discrimination ability between TD and ASD children, for males and females. Accuracy differences based on gender were on three indicators (3, 4 & 5). There were no significant differences (p >.05) on indicators based on gender, however, there were significant differences (p < .01) based on classification on all indicators, except indicators (3 & 4). Interaction between gender and classification was significant (p < .05) for one indicator (5). It is recommended to use (WCST-64:CV2) to diagnose ASD children (7–9 years), based on eight indicators for males (1, 2, 3, 4, 6, 7, 8, & 9) and seven indicators for females (1, 2, 5, 6, 7, 8, & 9), and to take differences based on gender and classification into account, when using (WCST-64:CV2). The (WCST-64:CV2) could be relied on for clinical/neuropsychological assessment of ASD children.
Authors
- Darandari, Eqbal ;
- Alqahtani, Reem