Interest and Skill Correlation Model for Career Aligning of Young Persons with Disabilities

Background: Persons with disabilities of working age often encounter unemployment rates 2-3 times higher than their non-disabled peers, primarily due to workplace biases and a lack of personalized career guidance. Traditional assessment methods often fail to capture the unique strengths of neurodiverse individuals, leading to job mismatches and underemployment. Objective: This study proposes an innovative framework using neuroscience-based assessments, specifically electroencephalography (EEG), to objectively evaluate the aptitude and strengths of persons with disabilities. The primary objective is to establish a data-driven model that correlates task-related brain activity patterns with suitable job opportunities and the necessary skill sets. Methodology: The methodology involves conducting EEG assessments during various cognitive tasks, analyzing the resulting data to identify individual strengths, and mapping these strengths to potential career paths. The model categorizes individuals into neurodiversity profiles based on their specific disability conditions and their neurological responses during these assessments. This approach allows for a more nuanced understanding of each individual's capabilities, moving beyond traditional assessment methods that may not fully capture the strengths of neurodivergent individuals. Conclusion: The EEG-based assessment model demonstrates the potential for more accurately identifying cognitive strengths in neurodiverse individuals compared to traditional methods. By utilizing neurotechnology to align individual capabilities with suitable employment paths, this approach aims to significantly boost workplace inclusion, personal autonomy, and social equality for persons with disabilities. This approach has the potential to revolutionize career guidance for persons with disabilities, leading to higher employment rates, improved job satisfaction, and better overall quality of life.