Alisha Patel
Biographic Data
| ID | 6030365 |
|---|---|
| NAME | Alisha Patel |
| GIVEN NAMES | Alisha |
| FAMILY NAME | Patel |
| SIGNATURE | PATEL A |
| AFFILIATIONS | Rutgers, the State University of New Jersey |
| ORCID | 0000-0002-0793-037X |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Machine learning analysis of a national sample of U.S. case law involving mental health evidence
Sentencing practices in cases involving defendants with mental disorders are often opaque, as data on case facts and sentencing decisions are not easily accessible. This paper reports findings from a national U.S. sample of appellate court cases across 46 states ( n = 710) that involved mental health evidence. We collected detailed data on judge and defendant characteristics, type and severity of mental disorders, state sociopolitical ideologies,…
A systematic appraisal of the information, engagement, aesthetic and functional quality of nutrition-related smartphone apps for children and adolescents
Objective: Nutrition-related smartphone applications (apps) could improve children’s nutrition knowledge and skills. However, little is known about the quality of nutrition-related apps for children. This study aimed to identify and evaluate the quality of nutrition-related smartphone apps designed for children ages 4–17. Design: This systematic appraisal is guided by the Protocol for App Store Systematic Reviews. Setting: Using Google’s Advanced…
No prominent works on this page.
A systematic appraisal of the information, engagement, aesthetic and functional quality of nutrition-related smartphone apps for children and adolescents
Objective: Nutrition-related smartphone applications (apps) could improve children’s nutrition knowledge and skills. However, little is known about the quality of nutrition-related apps for children. This study aimed to identify and evaluate the quality of nutrition-related smartphone apps designed for children ages 4–17. Design: This systematic appraisal is guided by the Protocol for App Store Systematic Reviews. Setting: Using Google’s Advanced…
Machine learning analysis of a national sample of U.S. case law involving mental health evidence
Sentencing practices in cases involving defendants with mental disorders are often opaque, as data on case facts and sentencing decisions are not easily accessible. This paper reports findings from a national U.S. sample of appellate court cases across 46 states ( n = 710) that involved mental health evidence. We collected detailed data on judge and defendant characteristics, type and severity of mental disorders, state sociopolitical ideologies,…
Psychology (2 works) · Alternative medicine (1 work) · App store (1 work) · Applied Psychology (1 work) · Autopsy Techniques and Outcomes (1 work) · Chemistry (1 work) · Child Development and Digital Technology (1 work) · Computer Science (1 work) · Critical appraisal (1 work) · Developmental psychology (1 work)