scholarly journals Challenges and Lessons Learned From Providing Large-Scale Evaluation Technical Assistance to Build the Adolescent Pregnancy Evidence Base

2016 ◽  
Vol 106 (S1) ◽  
pp. S26-S28 ◽  
Author(s):  
Jean Knab ◽  
Russell P. Cole ◽  
Susan Goerlich Zief
2020 ◽  
pp. 0193841X2097527
Author(s):  
Jean Knab ◽  
Russell Cole

Purpose: This case study discusses Mathematica’s experience providing large-scale evaluation technical assistance (ETA) to 65 grantees across two cohorts of Teen Pregnancy Prevention (TPP) Program grants. The grantees were required to conduct rigorous evaluations with specific evaluation benchmarks. This case study provides an overview of the TPP grant program, the evaluation requirements, the ETA provider, and other key stakeholders and the ETA provided to the grantees. Finally, it discusses the successes, challenges, and lessons learned from the effort. Conclusion: One important lesson learned is that there are two related evaluation features, strong counterfactuals and insufficient target sample sizes, that funders should attend to prior to selecting awardees because they are not easy to change through ETA. In addition, if focused on particular outcomes (for TPP, the goal was to improve sexual behavior outcomes), the funder should prioritize studies with an opportunity to observe differences in these outcomes across conditions; several TPP grantees served young populations, and sexual behavior outcomes were not observed or were rare, limiting the opportunity to observe impacts. Unless funders are attentive to weaning out evaluations with critical limitations during the funding process, requiring grantees to conduct impact evaluations supported by ETA might unintentionally foster internally valid, yet underpowered studies that show nonsignificant program impacts. The TPP funder was able to overcome some of the limitations of the grantee evaluations by funding additional evidence-building activities, including federally led evaluations and a large meta-analysis of the effort, as part of a broader learning agenda.


2011 ◽  
Vol 26 (S1) ◽  
pp. s59-s59
Author(s):  
A.E. Piombino

This session offers an overview of the Strategic National Stockpile (SNS) and the Cities Readiness Initiative (CRI), including CHEM PACK. Managed by the US Department of Health and Human Services Centers for Disease Control and Prevention (CDC), “push-packs” of this critical federal cache of pharmaceuticals and medical materiel are at sites located throughout the country. The CDC's CRI is a federally funded program designed to compliment the SNS and enhance preparedness in the nation's largest cities and Metropolitan Statistical Areas (MSA) where more than 50% of the US population resides. Through CRI, state and large metropolitan public health departments continue refining plans to respond to a large-scale bioterrorism attack by dispensing antibiotics to the entire population of an identified MSA with 48 hours. The SNS Technical Assistance Review (TAR) will be reviewed, as well as best practices and lessons learned from successful public health emergency preparedness and response programs throughout the US.


2019 ◽  
Vol 43 (6) ◽  
pp. 396-425
Author(s):  
Monica Kothari ◽  
Dionne Mackison ◽  
Carolyn Hemminger ◽  
Sandrine Fimbi ◽  
Denise Lionetti ◽  
...  

The Nutrition Embedding Evaluation Programme (NEEP) was a global 4-year program (2013–2017) funded by the United Kingdom Department for International Development created to respond to gaps in the nutrition evidence base. The NEEP implementing agency—PATH—provided grants and evaluation technical assistance (ETA) to civil society organizations (CSOs) from 12 countries to conduct robust nutrition-related impact evaluations. The programmatic approach of having an intermediary agent to manage the funding and ETA mechanisms for nutrition impact evaluations is rare and therefore provides a unique opportunity to understand its effectiveness. Over the program duration, NEEP collected lessons learned that were analyzed and disaggregated into key themes considered critical for the completion of high-quality impact evaluations. From these lessons learned, NEEP provides an ETA program model that can be replicated or adapted to other international development sectors. This model highlights the key role of the three tiers (donor, ETA manager, and CSOs) in ensuring the best value for money and effective technical support for conducting impact evaluations and fostering the importance of knowledge uptake and evaluative culture for maximum knowledge diffusion. In this way, global research can be targeted to approaches that provide options to collaborate with the program implementers and contribute to a holistic evidence base to inform policy and programmatic decisions.


2009 ◽  
Author(s):  
Kristin M. Wieneke ◽  
Elizabeth M. Reed ◽  
Mary E. Walsh

2020 ◽  
Vol 29 (3S) ◽  
pp. 638-647 ◽  
Author(s):  
Janine F. J. Meijerink ◽  
Marieke Pronk ◽  
Sophia E. Kramer

Purpose The SUpport PRogram (SUPR) study was carried out in the context of a private academic partnership and is the first study to evaluate the long-term effects of a communication program (SUPR) for older hearing aid users and their communication partners on a large scale in a hearing aid dispensing setting. The purpose of this research note is to reflect on the lessons that we learned during the different development, implementation, and evaluation phases of the SUPR project. Procedure This research note describes the procedures that were followed during the different phases of the SUPR project and provides a critical discussion to describe the strengths and weaknesses of the approach taken. Conclusion This research note might provide researchers and intervention developers with useful insights as to how aural rehabilitation interventions, such as the SUPR, can be developed by incorporating the needs of the different stakeholders, evaluated by using a robust research design (including a large sample size and a longer term follow-up assessment), and implemented widely by collaborating with a private partner (hearing aid dispensing practice chain).


Water Policy ◽  
2003 ◽  
Vol 5 (3) ◽  
pp. 203-212
Author(s):  
J. Lisa Jorgensona

This paper discusses a series of discusses how web sites now report international water project information, and maps the combined donor investment in more than 6000 water projects, active since 1995. The maps show donor investment:  • has addressed water scarcity,  • has improved access to improvised water resources,  • correlates with growth in GDP,  • appears to show a correlation with growth in net private capital flow,  • does NOT appear to correlate with growth in GNI. Evaluation indicates problems in the combined water project portfolios for major donor organizations: •difficulties in grouping projects over differing Sector classifications, food security, or agriculture/irrigation is the most difficult.  • inability to map donor projects at the country or river basin level because 60% of the donor projects include no location data (town, province, watershed) in the title or abstracts available on the web sites.  • no means to identify donor projects with utilization of water resources from training or technical assistance.  • no information of the source of water (river, aquifer, rainwater catchment).  • an identifiable quantity of water (withdrawal amounts, or increased water efficiency) is not provided.  • differentiation between large scale verses small scale projects. Recommendation: Major donors need to look at how the web harvests and combines their information, and look at ways to agree on a standard template for project titles to include more essential information. The Japanese (JICA) and the Asian Development Bank provide good models.


2021 ◽  
Vol 51 (3) ◽  
pp. 9-16
Author(s):  
José Suárez-Varela ◽  
Miquel Ferriol-Galmés ◽  
Albert López ◽  
Paul Almasan ◽  
Guillermo Bernárdez ◽  
...  

During the last decade, Machine Learning (ML) has increasingly become a hot topic in the field of Computer Networks and is expected to be gradually adopted for a plethora of control, monitoring and management tasks in real-world deployments. This poses the need to count on new generations of students, researchers and practitioners with a solid background in ML applied to networks. During 2020, the International Telecommunication Union (ITU) has organized the "ITU AI/ML in 5G challenge", an open global competition that has introduced to a broad audience some of the current main challenges in ML for networks. This large-scale initiative has gathered 23 different challenges proposed by network operators, equipment manufacturers and academia, and has attracted a total of 1300+ participants from 60+ countries. This paper narrates our experience organizing one of the proposed challenges: the "Graph Neural Networking Challenge 2020". We describe the problem presented to participants, the tools and resources provided, some organization aspects and participation statistics, an outline of the top-3 awarded solutions, and a summary with some lessons learned during all this journey. As a result, this challenge leaves a curated set of educational resources openly available to anyone interested in the topic.


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