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Mindfulness and Wellbeing: The Role of Cognitive Biases
Last registered on August 06, 2020

Pre-Trial

Trial Information
General Information
Title
Mindfulness and Wellbeing: The Role of Cognitive Biases
RCT ID
AEARCTR-0006256
Initial registration date
August 06, 2020
Last updated
August 06, 2020 10:04 AM EDT
Location(s)

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Primary Investigator
Affiliation
University of Warwick
Other Primary Investigator(s)
PI Affiliation
University of Warwick
PI Affiliation
University of Warwick
PI Affiliation
ETH Zurich
Additional Trial Information
Status
In development
Start date
2020-08-10
End date
2020-12-31
Secondary IDs
Abstract
Two major causes of cognitive biases are insufficient levels of attention (i.e. miserly processing) and anticipatory utility. Mindfulness training, through its emphasis on developing greater levels of "awareness” and “presence”, could have the potential to diminish the influence of both these causes and improve individual decision-making and welfare. Our RCT design makes use of a mindfulness treatment intervention and an active control to analyse the effects of meditation on these two types of cognitive biases (measured using experimental methods on an online platform).
External Link(s)
Registration Citation
Citation
Ash, Elliott et al. 2020. "Mindfulness and Wellbeing: The Role of Cognitive Biases." AEA RCT Registry. August 06. https://doi.org/10.1257/rct.6256-1.0.
Experimental Details
Interventions
Intervention(s)
We will recruit from the online crowdsourcing platform Prolific, advertising a study that will investigate the effects of mood on decision-making. Half of the participants will be randomized to a mindfullness treatment intervention (14-day, 15 minutes a day of listening to guided meditations (designed to promote attention and presence)); the other half will be randomized to an active control intervention designed to control for the structual effects of the treatment and meditation's relaxing effects (14-day, 15 minutes a day of listening to relaxing music, with the same instructor as the treatment introducing the music). The participants will also take surveys online before and after the interventions to alllow us to measure the key outcome variables and various useful controls.
Intervention Start Date
2020-08-10
Intervention End Date
2020-09-30
Primary Outcomes
Primary Outcomes (end points)
"Attention"-related primary outcomes: inattentive inference; sunk cost effect. "Presence"-related primary outcomes: fantasy (lottery) task; information preference scale.
Primary Outcomes (explanation)
Inattentive inference: using a hint X+Y for two random variables X,Y, to guess X, where the distributions of X,Y are known (Graeber, T. (2020). Inattentive Inference. (Online Baseline Tasks))
Sunk cost effect: 8-item scale; for each item subjects are presented with a scenario involving a type of sunk cost and have to indicate on a 6-point Likert scale their preference between two hypothetical alternatives (one of which indicates a susceptibility to the sunk cost effect) (Ronayne, D., Sgroi, S., & Tuckwell, A. (2020). Evaluating the Sunk Cost Effect.)
Fantasy (lottery) task: choice of whether to earn £X, or a smaller amount £Y but be allowed to open an envelope which will display the result of a lottery early (rather than waiting until the end of the survey) (Ganguly, A. & Tasoff, J. (2016). Fantasy and Dread)
Information preference scale: 13-item scale; each item subjects are presented with a scenario where they are asked whether they would like to receive some (potentially-negative) information of some kind and have to indicate how willing they are to do so (Ho, E.H., Hagmann, D., & Lowenstein, G. (2020). Measuring Information Preferences).
Secondary Outcomes
Secondary Outcomes (end points)
Trait mindfulness; stress; risk preference; time preference.
Secondary Outcomes (explanation)
Trait mindfulness: FFMQ-15 (Gu, J., Strauss, C., Crane, C., Barnhofer, T., Karl, A., Cavanagh, K., & Kuyken, W. (2016). Examining the factor structure of the 39-item and 15-item versions of the Five-Facet Mindfulness Questionnaire)
Stress: Perceived Stress Scale (PSS-10) (Cohen, S. & Williamson, G.M. (1988): Perceived Stress in a Probabilitiy Sample of the US)
Risk preference: Staircase Risk and the self-reported willingness to take risk question in Falk, A., Becker, A., Dohmen, T. J., Huffman, D., & Sunde, U. (2016). The preference survey module: A validated instrument for measuring risk, time, and social preferences.
Time preference: Unincentivized Time Preference question in Ganguly, A., & Tasoff, J. (2017). Fantasy and dread: The demand for information and the consumption utility of the future. Management Science, 63(12), 4037-4060.
Willingness to give up for future question in Falk, A., Becker, A., Dohmen, T. J., Huffman, D., & Sunde, U. (2016). The preference survey module: A validated instrument for measuring risk, time, and social preferences.
Experimental Design
Experimental Design
Half of the participants are randomized to a mindfulness treatment intervention (14-day, 15 minutes a day of listening to guided meditations (designed to promote attention and presence)); the other half are randomized to an active control intervention designed to control for the structural effects of the treatment and meditation's relaxing effects (14-day, 15 minutes a day of listening to relaxing music, with the same instructor as the treatment introducing the music). The participants also take surveys online before and after the interventions to allow us to measure the primary and secondary outcomes.
Experimental Design Details
Not available
Randomization Method
Randomization by computer program
Randomization Unit
Individual
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
200-260
Sample size: planned number of observations
200-260
Sample size (or number of clusters) by treatment arms
100-130
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We will have a sample size of 200-260 (100-130 in each treatment). Our main outcome variable is the attention measure, which will be measured once before treatment and once after treatment. Using sampsi package in Stata, assuming ANCOVA as the analysis method, alpha=0.025 to take into account two outcome variables, autocorrelation=0.6, one-sided mean comparison, with a sample size of 200, to reach a power of at least 0.8, we need a minimum effect size (MDE) of 0.32; with a sample size of 260, we need MDE of 0.28; with a sample size of 260 and autocorrelation=0.7, we need MDE of 0.25. Referring to Boettcher et al. (2014), Bennike et al. (2017) and Bostock et al. (2018), which use similar designs of an online mindfulness treatment group compared to an active control group and before-after comparison, and also looking at the treatments in Graeber (2019) where we took the measure for the main outcome variable (a simple intervention like adding enforced deliberation or hint could achieve an effect size of 0.2-0.5), we find a MDE of 0.25-0.32 possible for our study. References: Bennike, I. H., Wieghorst, A., & Kirk, U. (2017). Online-based mindfulness training reduces behavioral markers of mind wandering Boettcher, J., Åström, V., Påhlsson, D., Schenström, O., Andersson, G., & Carlbring, P. (2014). Internet-based mindfulness treatment for anxiety disorders: a randomized controlled trial. Bostock, S., Crosswell, A. D., Prather, A. A., & Steptoe, A. (2019). Mindfulness on-the-go: Effects of a mindfulness meditation app on work stress and well-being. Graeber, T. (2020). Inattentive Inference.
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Humanities and Social Sciences Research Ethics Committee
IRB Approval Date
2020-07-21
IRB Approval Number
HSSREC 80/18-19 AM01