Transparency for Development (T4D): Evaluating the impact of community transparency and accountability initiatives on Maternal and Neonatal Health outcomes
Last registered on November 19, 2018

Pre-Trial

Trial Information
General Information
Title
Transparency for Development (T4D): Evaluating the impact of community transparency and accountability initiatives on Maternal and Neonatal Health outcomes
RCT ID
AEARCTR-0000655
Initial registration date
November 09, 2015
Last updated
November 19, 2018 1:25 PM EST
Location(s)

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Primary Investigator
Affiliation
Harvard Kennedy School, Harvard University
Other Primary Investigator(s)
PI Affiliation
Harvard Kennedy School
PI Affiliation
Results for Development Institute
PI Affiliation
Results for Development Institute
PI Affiliation
Harvard Kennedy School
PI Affiliation
University of Washington
PI Affiliation
Harvard Kennedy School
Additional Trial Information
Status
On going
Start date
2015-02-09
End date
2019-09-30
Secondary IDs
Abstract
Recent decades have seen vast expansions of public health services across much of the developing world. But the quality of these services is often lacking, limiting their ultimate impact on the world’s poor. While many factors contribute to service delivery problems, one important factor is governance. The incentives that shape frontline service provider performance, training, oversight, and management all play an important role in the quality of healthcare provided by any health system. Transparency and accountability (T/A) techniques—such as social audits, public expenditure tracking surveys, citizen report cards, absenteeism studies, and community scorecards—are increasingly seen as one potential solution to some of these problems in that they allow communities to identify breakdowns and hold responsible agents or decision makers to account.

Yet the evidence about the effectiveness of these interventions is frustratingly mixed. Some studies of T/A interventions show tremendously positive effects on community empowerment and health and education outcomes, while others show no impact. Further, evidence on successful interventions provides few insights into why these interventions worked, what aspects of the context played a role, and whether they truly empowered poor communities or were largely irrelevant to the deeper problems of power inequity, institutional failure, or social conflict that often foster slow and uneven development. One consequence of this evidence gap is that reformers, policymakers, donors, and other practitioners lack clear guidance on whether any T/A interventions can ultimately empower poor populations and improve service delivery to them and on what sorts of T/A interventions should be pursued in different contexts.

The Transparency for Development (T4D) project is designed to investigate the questions of whether well-designed T/A interventions improve health outcomes and under what conditions. The overriding goal is to generate actionable evidence for practitioners, researchers, and other stakeholders working to improve health, accountability, and citizen participation.

The Transparency for Development project will:

1. Design, pilot, and rigorously evaluate a series of T/A interventions across several countries and contexts carefully selected to allow maximum potential for producing generalizable results about whether, where, and why T/A interventions improve development outcomes
2. Develop and widely disseminate the project’s findings along with concrete recommendations for donors, policymakers, practitioners, and other stakeholders on how to apply the findings to future work in transparency and accountability.
External Link(s)
Registration Citation
Citation
Arkedis, Jean et al. 2018. "Transparency for Development (T4D): Evaluating the impact of community transparency and accountability initiatives on Maternal and Neonatal Health outcomes." AEA RCT Registry. November 19. https://www.socialscienceregistry.org/trials/655/history/37499
Sponsors & Partners

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Experimental Details
Interventions
Intervention(s)
The intervention comprises four activities: (1) information gathering; (2) identification and development of community activists; (3) facilitation of community meetings to share information and develop an action plan; and (4) follow-up

The intervention is designed to give community members access to information related to MNH in order to motivate them to plan and conduct social action to improve maternal and neonatal health in their community.
Intervention Start Date
2015-08-17
Intervention End Date
2016-12-03
Primary Outcomes
Primary Outcomes (end points)
- Health service outcomes (increased utilization and improved facility interaction)
- Health outcomes
- Citizen empowerment and participation
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Two RCTs (one in Indonesia and one in Tanzania). Each includes 100 treatment and 100 control villages. See pre-analysis plan for a full description.
Experimental Design Details
Not available
Randomization Method
Randomization done by a computer
Randomization Unit
Indonesia: one eligible village is randomly selected per health facility catchment area. Within each village, subvillages are randomly selected. Eligible respondents are then randomly selected from these selected subvillages. Tanzania: one or two eligible villages are randomly selected per health facility catchment area. Within each village, subvillages are randomly selected. Eligible respondents are randomly selected from these subvillages.
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
200 villages per country for a total of 400 villages
Sample size: planned number of observations
Baseline = 5,400 women who have given birth in the past year (2,400 in Indonesia and 3,000 in Tanzania). Endline = 12,000 women who have given birth in the past year (6,000 in Indonesia and 6,000 in Tanzania).
Sample size (or number of clusters) by treatment arms
100 control villages and 100 treatment villages (per country), for a total of 200 control and 200 treatment villages
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Harvard University-Area Committee on the Use of Human Subjects
IRB Approval Date
2015-01-28
IRB Approval Number
IRB14-4613
Analysis Plan

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