Culturally adapted behavioral narratives for promoting residential energy conservation in the Baltic Sea region

Last registered on January 22, 2025

Pre-Trial

Trial Information

General Information

Title
Culturally adapted behavioral narratives for promoting residential energy conservation in the Baltic Sea region
RCT ID
AEARCTR-0015227
Initial registration date
January 21, 2025

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
January 22, 2025, 8:53 AM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

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Primary Investigator

Affiliation
Vilnius University

Other Primary Investigator(s)

PI Affiliation
Södertörn University
PI Affiliation
Södertörn University

Additional Trial Information

Status
In development
Start date
2025-01-27
End date
2025-04-01
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
The specific aim of the project is to investigate how behavioural interventions in the form of culturally adapted information affect the willingness to receive information about energy peaks during critical periods and what energy saving measures participants would be ready to implement. The aim is to investigate to what extent citizens in Sweden, Estonia and Lithuania are willing to reduce their energy consumption at home during a few hours when the energy system is under stress.
External Link(s)

Registration Citation

Citation
Alvarsson-Hjort, Jesper, Andrius Kazukauskas and Mall Leinsalu. 2025. "Culturally adapted behavioral narratives for promoting residential energy conservation in the Baltic Sea region." AEA RCT Registry. January 22. https://doi.org/10.1257/rct.15227-1.0
Experimental Details

Interventions

Intervention(s)
The randomized controlled trial (RCT) involves randomizing participants into one of four groups, each receiving unique culturally adapted information.
Intervention Start Date
2025-01-31
Intervention End Date
2025-04-01

Primary Outcomes

Primary Outcomes (end points)
Answers to the following question in our online survey:
How likely that participant will reduce her energy consumption after our provided alert about critical peak hour in the electricity system;
Whether participants demand any compensation if they reduce their energy consumption at peaks/critical hours after receiving such alert;
What kind of actions participants would be prepared to do in the critical peak hours if they receive our provided alerts.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Data collection in the project will be conducted in collaboration with the company Norstat through a digital survey-based field experiment in Sweden, Estonia, and Lithuania. Participants will be individuals over 18 years old who own a detached house. The digital survey will contain about 32 questions. Invitations will be sent through Norstat's platform. The randomized controlled trial (RCT) involves randomizing participants into one of four groups, each receiving unique culturally adapted information. Combinations of values result in four groups that will receive different information as follows: Group 1) neutral energy information, Group 2) attitudes focused on security, Group 3) attitudes focused on environmental issues, and Group 4) attitudes focused on both security and environmental issues (with the order of security and environmental information randomized between individuals in the group). The information is a short text that includes key terms related to security and environmental concepts with a focus on energy savings.
Experimental Design Details
Not available
Randomization Method
Randomization done by specialized survey company (Norstat).
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
The goal is to have 2,000 participants per country.
Sample size: planned number of observations
A total sample size of 6,000 individuals.
Sample size (or number of clusters) by treatment arms
Group 1 - 1500 (neutral energy information),
Group 2 - 1500 (focused on security),
Group 3 - 1500 (focused on environmental issues),
and Group 4 - 1500 (focused on both security and environmental issues).
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Baysian method was used, and simulations based on a population model were employed to examine the effect of a sample size of 6000. The model was coded in the R package lavaan (v. 0.6-18). The simulations were conducted using a structural equation model where the two overarching cultural dimensions were modeled as latent variables with the same ten indicators. Factor loadings were determined based on previous research. The outcome measure was the self-reported probability of accepting notifications about critical peak events [0–100%]. The outcome was predicted by the latent cultural dimensions, a health index, and income, separately for the 12 different groups (information treatments 4 × 3 countries). Regression coefficients between -0.05 and 0.25 were used to distinguish effects between the groups. The simulation used standardized values with n=500 per group. A total of 20 independent samples were drawn from the population model and analyzed separately. The analysis of the simulated datasets was conducted using blavaan (v. 0.5-5). The same equation structure as in the simulation was used, but assumptions were altered to allow for more degrees of freedom, and diffuse priors were employed to make the analysis more conservative. The latent cultural variables were loaded onto only five indicators each, and the covariance between them was set to 0. Prior values for factor loadings were taken from previous research. Default values were used for the variances, Γ (3,3). Priors for the regressions were diffuse, normally distributed, and centered around 0. For each analysis, 5000 samples were drawn across three independent Hamiltonian Monte Carlo chains. Across the 20 analyses, the majority of parameter estimates yielded similar results within the highest posterior density interval (95%). The effect sizes that, in fewer than 80% of cases, had consistent result interpretations (direction, magnitude, crossing zero) were only those with population effects of 0.05 and 0. Population effects within this range may therefore be challenging to distinguish between groups in the actual dataset.
IRB

Institutional Review Boards (IRBs)

IRB Name
The Swedish Ethical Review Authority (Etikprövningsmyndigheten)
IRB Approval Date
2024-10-29
IRB Approval Number
Dnr 2024-06395-01
IRB Name
The Committee on Research Ethics in Economics at the Faculty of Economics and Business Administration at Vilnius University
IRB Approval Date
2024-10-29
IRB Approval Number
No EC2024_03
IRB Name
The Estonian Institute for Health Development's Human Research Ethics Committee (TAIEK)
IRB Approval Date
2024-11-13
IRB Approval Number
Nr 1391