Large-Scale Online Studies of Early Motor Skill Learning

NCT ID: NCT03733080

Last Updated: 2025-04-15

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 2529 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2019-01-09
• Study Completion Date: 2019-10-17

Brief Summary

Background:

Our goal is to gain insight into early human motor skill learning by carrying out online substudies using online crowd-sourcing tools.

Objective:

To learn more about motor behavior in a large group of people using motor tasks, and questions.

Eligibility:

Adults ages 18 and older based in the U.S. who speak English

Design:

Participants will be recruited from a crowd-sourcing website like Amazon Mechanical Turk.

Participants will do online tasks. They can use their own computers anywhere with Internet access. They will not need to directly interact with researchers.

Participants will be asked for general data, like their age and gender. No personally identifiable data will be collected.

Participants will see a list of tasks on their computer screen. They will be able to choose tasks they wish to do. They will get a description of the experiment, how long it takes, and how much compensation they will get.

Participants will complete on their screen a motor behavioral task, a cognitive task, and/or a questionnaire. For example, they may be asked to press sequences of numbers on the keyboard or move the mouse when a stimulus appears on the screen. Experiments may last up to 1 hour.

Participants can complete as many experiments as they wish. They can quit at any point.

Detailed Description

Objective:

Our overall goal in this protocol has been to gain insight into early motor skill learning (micro-learning) in large-scale healthy volunteer cohorts using online crowd-sourcing. We have used a simple keyboard typing task to study micro-offline performance improvements during early motor skill learning. This online approach limits the burden on participants (who perform tasks in the comfort of their homes instead of traveling to NIH) and substantially reduces burden on in-house human, financial and technical resources. Results from this protocol contribute to a better understanding of factors relevant to human motor skill learning, with important implications for the design of better motor learning and neurorehabilitative strategies after brain lesions. We had completed data collection for four aims under this protocol at the time we were informed by the NIH IRB that they determined this to be a thematic protocol (September 23, 2019).

The four specific aims addressed under this protocol are:

1. Aim 1. To validate a motor skill learning task previously used by our group in lab-based studies {Bonstrup, 2019 #36} within an online, crowd-sourcing platform.

2. Aim 2. To compare the influence of an interfering task applied during early ("early interference") vs late ("late interference") rest periods on motor learning, thus evaluating resistance to interference, a feature of consolidation.

3. Aim 3. To evaluate the effects of a shorter practice period duration (i.e. - 5s vs. previously studied 10s duration) on micro-offline motor learning to gain insight into the impact of fatigue-related factors on learning.

4. Aim 4. To evaluate the effects of randomly variable practice period durations between 5-10s in length on micro-offline gains

As instructed, the purpose of this amendment is to request authorization to proceed with data analysis and publication. No new experiments will be carried out under this protocol.

Study Population:

U.S.-based English speakers aged 18 and above were recruited under this minimal risk protocol. Participants completed an online task in the comfort of their own homes using the internet, and did not need to directly interact with the investigators. All participants were given an anonymized random ID by the on-line site. We did collect general demographic information including age (needed to determine elegibility), and gender, race and ethnicity (per IRB reporting requirements, i.e. - Cumulative Inclusion Enrollment Report). However, we did not collect personally identifiable information (PII) about the participants.

Design:

Under this protocol, we have conducted experiments supporting four aims using Amazon Mechanical Turk (AMT). All experiments consisted of a brief keyboard typing task where participants were asked to repeatedly type a 5-key sequence (4-1-3-2-4) as fast and as accurately as possible for several seconds (i.e. - practice trial). Each practice trial was followed by a rest period lasting several seconds. Following the task, participants completed a short questionnaire designed to query compliance with task instructions, and collect general demographic data required for IRB reporting. The average total time for participation across all experiments was approximately 20 minutes.

Outcome Measures:

The primary outcome measures for the keyboard typing task were correct sequence typing speed and typing accuracy. Microlearning scores were derived by quantifying the speed change between the end of a previous practice trial and the beginning of the subsequent one (micro-offline learning) and the speed difference between the beginning and end of the same practice trial (micro-online learning). Information from the questionaires related to task instruction compliance was primarily used to exclude data from further analysis if needed.

Conditions

Healthy

Study Design

• Observational Model Type: CASE_ONLY
• Study Time Perspective: CROSS_SECTIONAL

Study Groups

1

ages 18 and older

No interventions assigned to this group

Eligibility Criteria

Inclusion Criteria

U.S.-based English speakers greater than 18 years of age are eligible to participate in the study.

Exclusion Criteria

Subjects are excluded if they are less than 18 years of age. NIH and NINDS employees are not excluded from the study, since participation is anonymous and personal identifiers unknown to the experimenters.

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 120 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

National Institute of Neurological Disorders and Stroke (NINDS)

NIH

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Leonardo G Cohen, M.D.

Role: PRINCIPAL_INVESTIGATOR

National Institute of Neurological Disorders and Stroke (NINDS)

Locations

National Institute of Neurological Disorders and Stroke (NINDS)

Bethesda, Maryland, United States

Countries

United States

Other Identifiers

19-N-N012

Identifier Type: -

Identifier Source: secondary_id

999919012

Identifier Type: -

Identifier Source: org_study_id