Stakeholder perception towards a machine‐learning‐based digital platform for detection and management of autism spectrum disorder

Author:

Kohli Manu1ORCID,Kar Arpan Kumar1,Sinha Shuchi1,Kohli Swati2

Affiliation:

1. Department of Management Studies Indian Institute of Technology Delhi Delhi India

2. Intervention SM Learning Skills Academy for Special Needs Gurugram India

Abstract

AbstractAutism spectrum disorder (ASD) affects approximately 1% of the population, presenting a significant healthcare challenge due to limited resources, particularly a shortage of clinicians, which impedes timely ASD detection and management in children. This study investigates stakeholder viewpoints regarding the effectiveness of integrating machine learning (ML) into the information and communications technology (ICT) platform for ASD detection and intervention. Primary stakeholders, including parents and clinicians, provide first hand experiences with this technology during and after the COVID‐19 pandemic. The research identifies critical technology adoption factors by synthesizing stakeholder input based on user experiences, technology design, technology utility, and its impact. Additionally, the study gathers insights from potential investors interested in assistive technologies. Stakeholders unanimously acknowledge the pivotal role of technology in enhancing current ASD detection and management. However, their attitudes toward technology adoption exhibit divergent trends during and after the COVID‐19 pandemic. The study highlights a shift toward a technology‐enabled, human‐centred framework, which gained prominence post‐pandemic. Various factors contributing to this shift in stakeholder perspective were identified, including caregiver stress, technostress, and pandemic‐induced environmental factors affecting stakeholders’ stress levels and motivating them to shift towards a human‐centric model. Stakeholders emphasize the paramount importance of human‐centred approaches in ASD detection and intervention, with technology serving as an empowering tool. Stakeholders also highlight the imperative ethical and legal considerations to foster trust and enhance the adoption of ML‐based technology. Consequently, future research should delve into stakeholder perspectives within the framework of fairness, accountability, transparency, and ethics (FATE) to ensure these technologies’ responsible development and implementation.

Publisher

Wiley

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Integrating AI tools for enhanced autism education: a comprehensive review;International Journal of Developmental Disabilities;2024-08-18

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3