Applying behavioural insights to online wagering
Last registered on February 21, 2020

Pre-Trial

Trial Information
General Information
Title
Applying behavioural insights to online wagering
RCT ID
AEARCTR-0005373
Initial registration date
February 20, 2020
Last updated
February 21, 2020 11:54 AM EST
Location(s)

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Primary Investigator
Affiliation
Behavioural Economics Team of the Australian Government
Other Primary Investigator(s)
PI Affiliation
Behavioural Economics Team of the Australian Government
PI Affiliation
Behavioural Economics Team of the Australian Government
PI Affiliation
Behavioural Economics Team of the Australian Government
Additional Trial Information
Status
In development
Start date
2020-03-02
End date
2020-07-17
Secondary IDs
Abstract
This study aims to assess the impacts of behavioural interventions on gambling behaviour of online wagerers. We will test the interventions through a framed-field online experiment with randomisation at the individual level.
External Link(s)
Registration Citation
Citation
Andersen, Katrina et al. 2020. "Applying behavioural insights to online wagering." AEA RCT Registry. February 21. https://doi.org/10.1257/rct.5373-1.0.
Sponsors & Partners

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Experimental Details
Interventions
Intervention(s)
Intervention details withheld until trial completion to avoid contamination.
Intervention Start Date
2020-03-22
Intervention End Date
2020-05-29
Primary Outcomes
Primary Outcomes (end points)
The amount gambled ($) over 84 gambles
Primary Outcomes (explanation)
This is a continuous measure. It is the total amount bet (lab $) over 84 gambles (gamble 13 to gamble 96) by each individual, averaged within each experimental group. The largest amount that can be gambled for each gamble is 10 lab dollars so the range of this variable will be 0 to 840 lab dollars.
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Three arm framed-field experiment, randomised at the individual level
Experimental Design Details
Not available
Randomization Method
Randomisation done on computer
Randomization Unit
Individual level
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
No clustering
Sample size: planned number of observations
1500
Sample size (or number of clusters) by treatment arms
Each participant will have a one-third chance of being allocated to each experimental arm. Therefore, we expect approximately 500 observations each in the control, treatment group 1 and group 2.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Power calculations are for alpha of 0.05, power 80% and a one-sided test. We are calculating power for a one-sided test because we are only interested in seeing if the interventions lead to a reduction in mean amount gambled compared to the control group. We are aiming to recruit 1,500 participants for the trial. With 500 participants for each arm with three arms, we will be able to detect a small standardized effect size (Cohen’s d) of 0.25 – if it exists – for both the mean amount bet and the mean number of bets made. If we are unable to recruit as many participants as hoped, we will only be able to detect larger effect sizes (e.g. Cohen’s d>0.25) if such an effect exists.
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Bellberry Limited
IRB Approval Date
2020-02-17
IRB Approval Number
2020-01-021
Analysis Plan

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