PONT: A Protocol for Online Neuropsychological Testing

Author:

Saban William1,Ivry Richard B.1

Affiliation:

1. University of California, Berkeley

Abstract

Abstract A major challenge for neuropsychological research arises from the fact that we are dealing with a limited resource: the patients. Not only is it difficult to identify and recruit these individuals, but their ability to participate in research projects can be limited by their medical condition. As such, sample sizes are small, and considerable time (e.g., 2 years) is required to complete a study. To address limitations inherent to laboratory-based neuropsychological research, we developed a protocol for online neuropsychological testing (PONT). We describe the implementation of PONT and provide the required information and materials for recruiting participants, conducting remote neurological evaluations, and testing patients in an automated, self-administered manner. The protocol can be easily tailored to target a broad range of patient groups, especially those who can be contacted via support groups or multisite collaborations. To highlight the operation of PONT and describe some of the unique challenges that arise in online neuropsychological research, we summarize our experience using PONT in a research program involving individuals with Parkinson disease and spinocerebellar ataxia. In a 10-month period, by contacting 646 support group coordinators, we were able to assemble a participant pool with over 100 patients in each group from across the United States. Moreover, we completed six experiments (n > 300) exploring their performance on a range of tasks examining motor and cognitive abilities. The efficiency of PONT in terms of data collection, combined with the convenience it offers the participants, promises a new approach that can increase the impact of neuropsychological research.

Funder

National Institute of Health

Publisher

MIT Press - Journals

Subject

Cognitive Neuroscience

Reference42 articles.

1. Control of automated behavior: Insights from the discrete sequence production task;Abrahamse;Frontiers in Human Neuroscience,2013

2. Big data in psychology: A framework for research advancement;Adjerid;American Psychologist,2018

3. Gorilla in our midst: An online behavioral experiment builder;Anwyl-Irvine;Behavior Research Methods,2020

4. QRTEngine: An easy solution for running online reaction time experiments using Qualtrics;Barnhoorn;Behavior Research Methods,2014

5. Parsimonious mixed models;Bates,2015

Cited by 6 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

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