Referral Protocols for Achieving Gender Representation in Random Digit Dial Phone Surveys

Last registered on August 23, 2021


Trial Information

General Information

Referral Protocols for Achieving Gender Representation in Random Digit Dial Phone Surveys
Initial registration date
August 18, 2021

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
August 23, 2021, 4:32 PM EDT

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



Primary Investigator

Innovations for Poverty Action

Other Primary Investigator(s)

PI Affiliation
University of Hong Kong
PI Affiliation
Arizona State University

Additional Trial Information

On going
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
In many applications of empirical economics, sample frames are not available, so random digit dial (RDD) surveys are the only feasible method for obtaining telephone survey data. This creates a challenge when the study seeks to focus on or disaggregate data to a particular demographic group, such as adult women. In most Low- and Middle- Income Countries (LMIC), cellphone ownership is skewed towards men (Forenbacher et al., 2019). This impedes the ability to obtain gender-representative samples in RDD surveys. A survey that relies on women to own and use mobile phones may systematically exclude women who rely on other household members, such as a spouse, to use a mobile phone. On the other hand, a survey that relies on men's willingness to pass the phone to a female household member may systematically exclude women in households with specific cultural gender norms such as those that discourage women's self-expression. In both cases, there is insufficient published data to determine which method would yield the highest response rate, reduce coverage bias, and be most cost effective.

This trial seeks to test the hypothesis that rapport-building can increase the number of women and diversify the types of women who will take and complete an RDD survey when referred by a male household member. Specifically, we test how referral and screening designs produce samples of women. We consider the impacts of these referral protocol choices on not only completions and response rates, but on sample composition and on inferences of interest from the survey data themselves to balance potential bias-variance tradeoffs.
External Link(s)

Registration Citation

Glazerman, Steven, Karen Grepin and Valerie Mueller. 2021. "Referral Protocols for Achieving Gender Representation in Random Digit Dial Phone Surveys." AEA RCT Registry. August 23.
Sponsors & Partners


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Experimental Details


We will test two protocols for reaching women respondents: (A) referral design vs. (B) simple screening based on eligibility criteria. Each case is randomly assigned into one of these groups.

Protocol A, Referral design:
-If a woman answers the phone:
o We determine eligibility and ask all eligible women to complete the survey.
-If a man answers the phone:
o We ask the man if there is an eligible woman in his household or nearby, ask him if he is willing to pass his phone, and if so, we speak to the woman, determine her eligibility, and ask her to complete the survey

Protocol B, Screen Design
-If a woman answers:
o We determine eligibility and if woman is eligible, ask her to complete the survey.
-If a man answers:
o We determine eligibility and if man is eligible, ask him to complete the survey (no woman survey attempted for this household).
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
These protocols are expected to affects three sets of outcomes:
-Productivity for survey implementation (consent and completion)
-Sample composition (demographic characteristics)
-Sample outcomes (Coronavirus knowledge and practices, employment, access to health services, government support, and time use)
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
The referral design will also provide information on how successful referral to female respondents may be.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Telephone numbers will be contacted to determine if there is a potential respondent at that number. If a respondent picks up the phone, a script will be read to introduce the survey and the goals of the research study, they will be screened for eligibility (and for passing the phone if necessary), consent will be obtained, and then they will be asked if they can complete the survey.

Respondents will be automatically randomized into each group by the survey software based on 50% probability of assignment. Based on this randomization, the survey software will automatically direct enumerators to either pass the phone (Protocol A) or screen the respondent for eligibility (Protocol B). Enumerators are trained in both protocols and are prompted to complete the respective by the survey software.
Experimental Design Details
Randomization Method
Survey software (SurveyCTO) randomizes survey branching behavior.
Randomization Unit
Individual cases (phone numbers) are randomized
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
6,929 cases to attempt
Sample size: planned number of observations
6,929 cases to attempt Experiment is run conditional on eligible respondents, so sample size will be closer to 1,500.
Sample size (or number of clusters) by treatment arms
Eligibility is determined after randomization, so sample size by treatment arm cannot be pre-specified. Estimates:
Protocol A: 1000 women
Protocol B: 500 women
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
Simon Fraser University IRB
IRB Approval Date
IRB Approval Number
IRB Name
Maseno University Ethics Review Committee
IRB Approval Date
IRB Approval Number


Post Trial Information

Study Withdrawal

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Is the intervention completed?
Data Collection Complete
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials