Can the Prediction Market Improve Predictions of COVID-19?
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?
調査の概要
詳細な説明
The proposed study is an online experiment. Students enrolled at National University of Singapore are recruited to participate in the study.
Participants will first complete a pre-experiment survey, which contains basic demographic questions. Then, participants will be randomly assigned to one of two conditions: "Survey" and "Prediction Market".
"SURVEY" CONDITION:
Participants in the "Survey" condition are asked 16 prediction questions in a survey format. The questions are 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 outcomes, e.g. "< 28,900", "between 28,900 and 33,899", "between 33,900 and 38,899", "between 38,900 and 43,899", and "> 43,899". Participants are required to enter their perceived likelihood of each answer option in %.
The 16 prediction 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).
Participants have 24 hours to submit their predictions.
After the 24-hour period, participants are requested to fill out a post-experiment survey, which includes questions about their subjective attitudes and fears towards COVID-19.
"PREDICTION MARKET" CONDITION:
For participants in the "Prediction Market" condition, the same 16 prediction questions are presented in the form of prediction markets. The prediction market is a well-established method of eliciting people's predictions. The method is briefly described below.
There are 16 prediction markets, one for each question. Participants are given 100 tokens per market, which can be used to buy "stocks" on possible outcomes. There are 5 possible outcomes per market (identical to the 5 answer options per question in the "Survey" condition).
Each stock (i.e., possible outcome) will have a price that is dynamically determined by the central marketplace, which is a function of real-time demand and supply of the option. If the option is popular, its price will become higher, and vice versa.
Participants can trade at any time, and as many times as they want, during a 24-hour period. Upon closure of the prediction market, participants will be rewarded proportional to the number of shares that they hold on options that later turn out to be true.
The final prices of stocks correspond to the group's predictions of COVID-19.
After the 24-hour period, participants are requested to fill out a post-experiment survey, which includes questions about their subjective attitudes and fears towards COVID-19.
=====
HYPOTHESES
The prediction market leads to better predictions about COVID-19. The investigators will compare the survey predictions and the prediction-market predictions with the actual realized outcome. The investigators hypothesize that the prediction-market predictions are more accurate than the survey predictions through information aggregation.
The prediction market reduces fear. Fear is measured by participants' responses to subjective attitude questions in the post-experiment survey.
研究の種類
入学 (実際)
段階
- 適用できない
連絡先と場所
研究場所
-
-
-
Singapore、シンガポール
- National University of Singapore
-
-
参加基準
適格基準
就学可能な年齢
健康ボランティアの受け入れ
受講資格のある性別
説明
Inclusion Criteria:
- National University of Singapore students
Exclusion Criteria:
- N/A
研究計画
研究はどのように設計されていますか?
デザインの詳細
- 主な目的:他の
- 割り当て:ランダム化
- 介入モデル:並列代入
- マスキング:なし(オープンラベル)
武器と介入
参加者グループ / アーム |
介入・治療 |
|---|---|
|
介入なし:Control
Participants' COVID-19 predictions are elicited via a survey
|
|
|
実験的:Treatment
Participants' COVID-19 predictions are elicited via a prediction market
|
Participants "bet" on likely future outcomes using a prediction market
|
この研究は何を測定していますか?
主要な結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
|
Predictions of COVID-19 Cases and Deaths
時間枠:24 hours
|
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
|
二次結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
|
Fear
時間枠:24 hours (participants are required to submit post-experiment survey within 24 hours of completion of the main experiment)
|
Fear is measured by participants' responses to subjective attitude questions in the post-experiment survey.
The questions are on a 5-point Likert scale.
|
24 hours (participants are required to submit post-experiment survey within 24 hours of completion of the main experiment)
|
協力者と研究者
捜査官
- 主任研究者:Teck Ho, PhD、National University of Singapore
出版物と役立つリンク
研究記録日
主要日程の研究
研究開始 (実際)
一次修了 (実際)
研究の完了 (実際)
試験登録日
最初に提出
QC基準を満たした最初の提出物
最初の投稿 (実際)
学習記録の更新
投稿された最後の更新 (実際)
QC基準を満たした最後の更新が送信されました
最終確認日
詳しくは
本研究に関する用語
その他の研究ID番号
- SG-COVID
個々の参加者データ (IPD) の計画
個々の参加者データ (IPD) を共有する予定はありますか?
IPD プランの説明
IPD 共有時間枠
IPD 共有アクセス基準
IPD 共有サポート情報タイプ
- STUDY_PROTOCOL
- ICF
- ANALYTIC_CODE
医薬品およびデバイス情報、研究文書
米国FDA規制医薬品の研究
米国FDA規制機器製品の研究
この情報は、Web サイト clinicaltrials.gov から変更なしで直接取得したものです。研究の詳細を変更、削除、または更新するリクエストがある場合は、register@clinicaltrials.gov。 までご連絡ください。 clinicaltrials.gov に変更が加えられるとすぐに、ウェブサイトでも自動的に更新されます。