Causal attribution of sex differences and attitudes toward women in STEM

Last registered on December 06, 2023

Pre-Trial

Trial Information

General Information

Title
Causal attribution of sex differences and attitudes toward women in STEM
RCT ID
AEARCTR-0012404
Initial registration date
December 04, 2023

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
December 06, 2023, 7:19 AM EST

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

Locations

Region

Primary Investigator

Affiliation
Università degli Studi di Milano

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2023-11-24
End date
2023-12-11
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Despite the significant increase in women working in traditionally masculine sectors, the presence of women in STEM (Science, Technology, Engineering and Math) fields, and thus in high-pay and high-status professions, is still scarce.
Previous experimental studies found that exposing individuals to theories of sex differences, attributing the cause of these differences to either biological or social factors, affects stereotype endorsement, self-stereotyping, interest in STEM and performance in a math-related task. However, the existing studies on the effect of essentialist beliefs on attitudes toward role models are too scarce to provide a clear picture of how the endorsement of fixed versus malleable theories of traits could mediate the efficacy of interventions using role models.
The study aims to test the effect of the endorsement of gender essentialist beliefs on attitudes toward and perceptions of women interested in STEM. It is hypotesized that people endorsing essentialist beliefs on gender would have worse attitudes toward women in STEM and would be more likely to see female counterstereotypical role models as exceptions (subtyping effect) compared to both people thinking that gender differences either do not exist or are due to social factors.
The hypotheses are tested using a randomized control trial with parallel design where essentialist beliefs are manipulated asking participants to read an article on gender (sex) differences in math abilities. Participants are recruited by a panel provider based in Italy and are paid for their participation. The experiment is conducted online. In study 1, 200 participants aged 16-20 are randomly assigned to an article either suggesting that gender differences do not exist, that exist but are due to social factors or that are due to biological differences. They are then asked to answer a questionnaire measuring attitudes toward women in science and gender stereotypes about science. In study 2, 150 participants aged 16-20 are randomly assigned to the same articles (biological differences or no differences), they are then exposed to counterstereotypical role models and asked their opinion on their gender typicality. Their gender bias is also measured.
External Link(s)

Registration Citation

Citation
De Gioannis, Elena. 2023. "Causal attribution of sex differences and attitudes toward women in STEM." AEA RCT Registry. December 06. https://doi.org/10.1257/rct.12404-1.0
Experimental Details

Interventions

Intervention(s)
Participants are asked to read an article on gender (sex) differences in math abilities.
Intervention (Hidden)
Intervention Start Date
2023-11-24
Intervention End Date
2023-12-11

Primary Outcomes

Primary Outcomes (end points)
Study 1:
- Attitudes toward women in science
- Endorsement of explicit gender-science stereotypes

Study 2
- perception of gender-typicality of stereotypical and counterstereotypical role models
- gender bias
Primary Outcomes (explanation)
Study 1:
- attitudes toward women in science: "Women possess characteristics which enable them to be successful in science careers" dimension from the "Women in science scale" (WISS, Erb & Smith, 1984)
- endorsement of gender-science stereotypes: instrument proposed by Schmader et al. (2004)

Study 2:
- perception of gender typicality: adaptation of the scales on self-perceived gender typicality (Krueger et al., 2003; Leaper & Van, 2008; Patterson, 2012)
- gender bias: adaptation of the instrument used to measure gender bias by De Gioannis et al. (2023)

Secondary Outcomes

Secondary Outcomes (end points)
Study 1:
- attitudes toward science
Secondary Outcomes (explanation)
Attitudes Toward Science Inventory in the modified version proposed by Tai et al. (2022)

Experimental Design

Experimental Design
Participants are first asked to read an article from a newspaper describing gender (sex) differences in math abillities. This is aimed to manipulate their gender essentialist beliefs. They are randomly assigned to read an article that either suggests that these differences exist and are due to biological factors (T1), that they exist but are due to social factors (C1) or that they do not exist (C2). In study 2, participants are either assigned to T1 or to C2.

Participants are first asked a few questions on the articles to reinforce the manipulation. They are then asked to answer a questionnaire including sociodemographic information and the questions measuring the outcomes of interest.
Experimental Design Details
Randomization Method
Block randomization based on sociodemographic chacteristics, e.g. gender, residence.
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Study 1: 200 individuals aged 16-20
Study 2: 150 individuals aged 16-20
Sample size: planned number of observations
Study 1: 200 individuals aged 16-20 Study 2: 150 individuals aged 16-20
Sample size (or number of clusters) by treatment arms
Study 1: 70 individuals for biological differences, 65 individuals for social differences, 65 individuals for no differences
Study 2: 75 individuals for biological differences, 75 individuals no differences
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Minimum detectable effect size: Study 1: small-to-medium effect size (f2 = 0.03) Study 2: medium effect size (f = 0.25)
IRB

Institutional Review Boards (IRBs)

IRB Name
Ethics Committee of the Università degli Studi di Milano
IRB Approval Date
2023-02-20
IRB Approval Number
15/23

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials