Can the Prediction Market Improve Predictions of COVID-19?

NCT04410692 | Completed

• 1 other identifier: SG-COVID
• Study Type: interventional
• Target: 560
• Locations: 1 country
• Sites: 1

Brief Summary

The goal of this study is to better understand how people predict the future risks of the novel Coronavirus (COVID-19). Specifically, the investigators will ask the following research questions:

• How well do participants predict the future risks of COVID-19?
• Can the predictions be improved by using a prediction market mechanism?
• Does the prediction market reduce people's fear of COVID-19?

Conditions

Health Knowledge, Attitudes, Practice

Outcome Measures

Primary Outcomes (1)

• Predictions of COVID-19 Cases and Deaths

  Participants are asked 16 questions of the following format: "What do you think will be the total cumulative number of cases in Singapore on 8th of June, at 12pm?" Each question has 5 answer options. Each answer option is a range of possible outcomes. The primary outcome measure is participants' perceived likelihood of each answer option. The 16 questions come from the following variations: 4 countries (Mexico, Singapore, Turkey, USA) x 2 outcome measures (cases, deaths) x 2 time periods (8th of June, 6th of July).

  24 hours

Secondary Outcomes (1)

• Fear

  24 hours (participants are required to submit post-experiment survey within 24 hours of completion of the main experiment)

Study Arms (2)

Control

NO INTERVENTION

Participants' COVID-19 predictions are elicited via a survey

Treatment

EXPERIMENTAL

Participants' COVID-19 predictions are elicited via a prediction market

Other: Prediction Market

Interventions

Prediction Market OTHER

Participants "bet" on likely future outcomes using a prediction market

Treatment

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• National University of Singapore students

You may not qualify if:

• N/A

Sponsors & Collaborators

• National University of Singapore: lead

Study Sites (1)

National University of Singapore

Singapore, Singapore

Location

Related Publications (1)

• Camerer CF, Dreber A, Holzmeister F, Ho TH, Huber J, Johannesson M, Kirchler M, Nave G, Nosek BA, Pfeiffer T, Altmejd A, Buttrick N, Chan T, Chen Y, Forsell E, Gampa A, Heikensten E, Hummer L, Imai T, Isaksson S, Manfredi D, Rose J, Wagenmakers EJ, Wu H. Evaluating the replicability of social science experiments in Nature and Science between 2010 and 2015. Nat Hum Behav. 2018 Sep;2(9):637-644. doi: 10.1038/s41562-018-0399-z. Epub 2018 Aug 27.

  PMID: 31346273 BACKGROUND

MeSH Terms

Conditions

Behavior

Study Officials

• Teck Ho, PhD

  National University of Singapore

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: OTHER
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Senior Deputy President & Provost

Study Record Dates

• First Submitted: May 27, 2020
• First Posted: June 1, 2020
• Study Start: May 15, 2020
• Primary Completion: May 16, 2020
• Study Completion: May 17, 2020
• Last Updated: June 2, 2020

Record last verified: 2020-05

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, ICF, ANALYTIC CODE
• Time Frame: After completion of all analysis. It will be made available in the supporting documentation.
• Access Criteria: It will be made available in the supporting documentation.

Locations

SG (1)