Improvement of Facial Recognition Ability and Multitasking

Not Applicable

• Conditions: Facial Discrimination; Multitasking

• Registration Number: NCT03832101
• Lead Sponsor: National University of Singapore

Brief Summary

This study aims to determine the efficacy of training on facial recognition and multitasking. The researchers hypothesize that participants who have undergone facial recognition and multitasking training will demonstrate an improved facial recognition ability and performance in multi-tasking. The researchers also hypothesize that measures of sustained and selective attention will predict performance on multitasking tasks. This work sets the ground work for future research into if and how facial recognition and multitasking ability can be improved.

Detailed Description

There has been evidence showing improvements on performance on various cognitive tasks after training, but evidence on multitasking and facial recognition is lacking. Both multi-tasking and facial recognition are crucial for military and law enforcement personnel, and the respective organizations can consider these abilities during their respective recruitment and training processes.

This study will test whether training on multi-tasking and facial recognition tasks can improve an individual's performance. Additionally, it will test whether their performance on other measures of attention and multitasking can predict changes post-training.

Participants will go through 5 testing sessions span over 5 days. For each session, participants will complete a multitasking task and a facial recognition task. Participants are hypothesized to improve in their performance after 5 consecutive days of training on these 2 tasks. Additionally, participants will also complete 2 attention tasks, 1 face memory task, and 1 other multi-tasking task only on the first day. Both multitasking tasks are expected to correlate at baseline, and performance on the attention tasks may predict performance on multitasking tasks as these tasks require sustained and selective attention. A face memory task will also be used to account for each individual's baseline facial recognition ability.

Study Timeline

• Study Start: 2018-02-13
• Status Verified: 2019-02
• Study First Submitted: 2019-02-02
• Study First Submitted QC: 2019-02-04
• Last Update Submitted: 2019-02-04
• Study First Posted: 2019-02-06
• Last Update Posted: 2019-02-06
• Primary Completion: 2020-12
• Study Completion: 2020-12

Recruitment & Eligibility

• Status: UNKNOWN
• Sex: All
• Target Recruitment: 100

Inclusion Criteria

• Participants must be over 21 if they are not from NUS or Yale-NUS. NUS or Yale-NUS students over 18 can also participate. All participants are expected to be fluent in English.

Exclusion Criteria

• Participants with a history of perceptual or memory deficit will be excluded.

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: PARALLEL

Primary Outcome Measures

Name	Time	Method
Facial recognition performance change during training	Day 1, 2, 3, 4, 5	The crucial measure is percent correct recognition of target faces learned on the first day. These faces are either presented in isolation (Is this a target face? Yes/No) or with other faces (Which is the target?). Performance is measured on each day of training to establish learning trajectories.
Multi-tasking performance change during training	Day 1, 2, 3, 4, 5	The crucial measures are speed and accuracy on each component task of the MATB (Multi-Attribute Task Battery; Comstock \& Arnegard, 1992). Performance is measured on each day of training to establish learning trajectories.

Trial Locations

Locations (1)

National University of Singapore; 🇸🇬 Singapore, Singapore