The Impact of College Outreach on High Schoolers’ College Choices – Results From Over 1,000 Natural Experiments

2019 ◽  
Author(s):  
Jessica Howell ◽  
Michael Hurwitz ◽  
Jonathan Smith
Keyword(s):  
Natural Experiments ◽  
College Choices ◽  
College Outreach ◽  
The Impact ◽  
High Schoolers

The Impact of College Outreach on High Schoolers’ College Choices - Results From Over 1,000 Natural Experiments

2020 ◽  
pp. 1-43
Author(s):  
Jonathan Smith ◽  
Jessica Howell ◽  
Michael Hurwitz
Keyword(s):  
First Generation ◽  
Natural Experiments ◽  
Underserved Students ◽  
Percentage Points ◽  
Contact Information ◽  
Search Service ◽  
College Choices ◽  
College Outreach ◽  
The Impact ◽  
Racial Ethnic

We estimate the impact of one of the largest college-to-student outreach efforts in the nation, the College Board's Student Search Service. In an oversubscribed “order”, colleges receive contact information of a randomly chosen subset of PSAT and SAT Exam takers who opted into the service and meet colleges’ search criteria from a larger set of students with identical backgrounds. We find that students who receive outreach enabled by Student Search Service (“licensed”) are 23 percent (0.1 percentage points) more likely to apply to the licensing college than students with similar backgrounds who did not receive outreach. Nearly 20% of students induced to apply to a college because of the Student Search Service also enroll, increasing the probability of enrolling in the college that licensed their contact information by 22 percent (0.02 percentage points). These impacts are twice as large for traditionally underserved students. Responsiveness to college outreach is larger for racial/ethnic minorities, first generation students, and lowand moderate-income students. Despite the fact that one additional license changes the specific institution to which students send scores and enroll, we cannot detect changes to the broad types of colleges in which students ultimately enroll.

scholarly journals Understanding and responding to COVID-19 in Wales: protocol for a privacy-protecting data platform for enhanced epidemiology and evaluation of interventions

BMJ Open ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. e043010
Author(s):  
Jane Lyons ◽  
Ashley Akbari ◽  
Fatemeh Torabi ◽  
Gareth I Davies ◽  
Laura North ◽  
...  
Keyword(s):  
Policy Development ◽  
Healthcare Utilisation ◽  
Population Data ◽  
Population Level ◽  
Risk Groups ◽  
Service Utilisation ◽  
Natural Experiments ◽  
Spread Of Infection ◽  
The Impact

IntroductionThe emergence of the novel respiratory SARS-CoV-2 and subsequent COVID-19 pandemic have required rapid assimilation of population-level data to understand and control the spread of infection in the general and vulnerable populations. Rapid analyses are needed to inform policy development and target interventions to at-risk groups to prevent serious health outcomes. We aim to provide an accessible research platform to determine demographic, socioeconomic and clinical risk factors for infection, morbidity and mortality of COVID-19, to measure the impact of COVID-19 on healthcare utilisation and long-term health, and to enable the evaluation of natural experiments of policy interventions.Methods and analysisTwo privacy-protecting population-level cohorts have been created and derived from multisourced demographic and healthcare data. The C20 cohort consists of 3.2 million people in Wales on the 1 January 2020 with follow-up until 31 May 2020. The complete cohort dataset will be updated monthly with some individual datasets available daily. The C16 cohort consists of 3 million people in Wales on the 1 January 2016 with follow-up to 31 December 2019. C16 is designed as a counterfactual cohort to provide contextual comparative population data on disease, health service utilisation and mortality. Study outcomes will: (a) characterise the epidemiology of COVID-19, (b) assess socioeconomic and demographic influences on infection and outcomes, (c) measure the impact of COVID-19 on short -term and longer-term population outcomes and (d) undertake studies on the transmission and spatial spread of infection.Ethics and disseminationThe Secure Anonymised Information Linkage-independent Information Governance Review Panel has approved this study. The study findings will be presented to policy groups, public meetings, national and international conferences, and published in peer-reviewed journals.

scholarly journals Conceptualising natural and quasi experiments in public health

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Frank de Vocht ◽  
Srinivasa Vittal Katikireddi ◽  
Cheryl McQuire ◽  
Kate Tilling ◽  
Matthew Hickman ◽  
...  
Keyword(s):  
Public Health ◽  
Study Design ◽  
Grey Literature ◽  
Public Health Research ◽  
Natural Experiments ◽  
Target Trial ◽  
Design Elements ◽  
Randomized Controlled ◽  
Study Designs ◽  
The Impact

Abstract Background Natural or quasi experiments are appealing for public health research because they enable the evaluation of events or interventions that are difficult or impossible to manipulate experimentally, such as many policy and health system reforms. However, there remains ambiguity in the literature about their definition and how they differ from randomized controlled experiments and from other observational designs. We conceptualise natural experiments in the context of public health evaluations and align the study design to the Target Trial Framework. Methods A literature search was conducted, and key methodological papers were used to develop this work. Peer-reviewed papers were supplemented by grey literature. Results Natural experiment studies (NES) combine features of experiments and non-experiments. They differ from planned experiments, such as randomized controlled trials, in that exposure allocation is not controlled by researchers. They differ from other observational designs in that they evaluate the impact of events or process that leads to differences in exposure. As a result they are, in theory, less susceptible to bias than other observational study designs. Importantly, causal inference relies heavily on the assumption that exposure allocation can be considered ‘as-if randomized’. The target trial framework provides a systematic basis for evaluating this assumption and the other design elements that underpin the causal claims that can be made from NES. Conclusions NES should be considered a type of study design rather than a set of tools for analyses of non-randomized interventions. Alignment of NES to the Target Trial framework will clarify the strength of evidence underpinning claims about the effectiveness of public health interventions.

scholarly journals Recruitment and Retention Strategies for Community-Based Longitudinal Studies in Urban, Minority Neighborhoods: Lessons Learned from the PARCS Study (Preprint)

2020 ◽  
Author(s):  
Emily B Ferris ◽  
Katarzyna Wyka ◽  
Kelly R. Evenson ◽  
Joan M Dorn ◽  
Lorna Thorpe ◽  
...  
Keyword(s):  
Longitudinal Studies ◽  
Low Income ◽  
Lessons Learned ◽  
Natural Experiments ◽  
Retention Strategies ◽  
Recruitment And Retention ◽  
Four Dimensions ◽  
Evaluation Approach ◽  
Measurement And Evaluation ◽  
The Impact

UNSTRUCTURED Longitudinal, natural experiments provide an ideal evaluation approach to better understand the impact of built environment interventions on community health outcomes, particularly heath disparities. As there are many recruitment and retention challenges inherent to the design of longitudinal, natural experiments, adaptive and iterative recruitment and retention strategies are critical to the success of a study. This paper documents lessons learned from the Physical Activity and Redesigned Community Spaces (PARCS) Study. The PARCS Study, while ongoing, has developed several approaches to improve the recruitment and retention protocols by prioritizing the following four dimensions: 1) building trust with communities; 2) adapting the study protocol to meet participants’ needs and to reflect their capacity for participation; 3) operational flexibility; and 4) measurement and evaluation systems. These strategies may help researchers more successfully recruit and retain participants, particularly in low-income, minority neighborhoods, into longitudinal studies.

scholarly journals 0386 Identification of Sleep Complaints Using Social Media: Effect of the Daylight Savings Time to Standard Time Transition

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A148-A148
Author(s):  
O J Veatch ◽  
D R Mazzotti
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Random Forest ◽  
The United States ◽  
Natural Experiments ◽  
Media Effect ◽  
Sleep Complaints ◽  
Standard Time ◽  
The Impact ◽  
Circadian Patterns

Abstract Introduction Transitions to and from daylight savings time (DST) are natural experiments of circadian disruption and are associated with negative health consequences. Yet, the majority of the United States and several other countries still adopt these changes. Large observational studies focused on understanding the impact of DST transitions on sleep are difficult to conduct. Social media platforms, like Twitter, are powerful sources of human behavior data. We used machine learning to identify tweets reporting sleep complaints (TRSC) during the week of the standard time (ST)-DST transition. Next, we evaluated the circadian patterns of TRSC and compared their prevalence before and after the transition. Methods Using data publicly available via the Twitter API, we collected 500 tweets with evidence of sleep complaints, and manually annotated each tweet to validate true sleep complaints. Next, we calculated term frequency-inverse document frequency of each word in each tweet and trained a random forest to classify TRSC using a 3-fold cross-validation design. The trained model was then used to annotate a collection of tweets captured between Oct. 30, 2019-Nov. 6, 2019, overlapping with the DST-ST transition, which occurred on Nov. 3, 2019. Results Random forest demonstrated good performance in classifying TRSC (AUC[95%CI]=0.85[0.82-0.89]). This model was applied to 3,738,383 tweets collected around the DST-ST transition, and identified 11,044 TRSC. Posting of these tweets had a circadian pattern, with peak during nighttime. We found a higher frequency of TRSC after the DST-ST transition (0.33% vs. 0.27%, p<0.00001), corresponding to a ~20% increase in the odds of reporting sleep complaints (OR[95%CI]=1.21[1.16-1.25]). Conclusion Using machine learning and Twitter data, we identified tweets reporting sleep complaints, described their circadian patterns and demonstrated that the prevalence of these types of tweets is significantly increased after the transition from DST to ST. These results demonstrate the applicability of social media data mining for public health in sleep medicine. Support NIH (K01LM012870); AASM Foundation (194-SR-18)

Changes in Hospital Financing and Organization and Their Impact on Hospital Performance

2019 ◽  
Author(s):  
Jonas Schreyögg
Keyword(s):  
Financial Performance ◽  
Financial Incentives ◽  
Hospital Performance ◽  
Unintended Effects ◽  
Natural Experiments ◽  
Cross Sectional ◽  
Trade Offs ◽  
Wide Range ◽  
Improve Hospital ◽  
The Impact

Since the 1980s policymakers have identified a wide range of policy interventions to improve hospital performance. Some of these have been initiated at the level of government, whereas others have taken the form of decisions made by individual hospitals but have been guided by regulatory or financial incentives. Studies investigating the impact that some of the most important of these interventions have had on hospital performance can be grouped into four different research streams. Among the research streams, the strongest evidence exists for the effects of privatization. Studies on this topic use longitudinal designs with control groups and have found robust increases in efficiency and financial performance. Evidence on the entry of hospitals into health systems and the effects of this on efficiency is similarly strong. Although the other three streams of research also contain well-conducted studies with valuable findings, they are predominantly cross-sectional in design and therefore cannot establish causation. While the effects of introducing DRG-based hospital payments and of specialization are largely unclear, vertical and horizontal cooperation probably have a positive effect on efficiency and financial performance. Lastly, the drivers of improved efficiency or financial performance are very different depending on the reform or intervention being investigated; however, reductions in the number of staff and improved bargaining power in purchasing stand out as being of particular importance. Several promising avenues for future investigation are identified. One of these is situated within a new area of research examining the link between changes in the prices of treatments and hospitals’ responses. As there is evidence of unintended effects, future studies should attempt to distinguish between changes in hospitals’ responses at the intensive margin (e.g., upcoding) versus the extensive margin (e.g., increase in admissions). When looking at the effects of entering into a health system and of privatizations, there is still considerable need for research. With privatizations, in particular, the underlying processes are not yet fully understood, and the potential trade-offs between increases in performance and changes in the quality of care have not been sufficiently examined. Lastly, there is substantial need for further papers in the areas of multi-institutional arrangements and cooperation, as well as specialization. In both research streams, natural experiments carried out using program evaluation design are lacking. One of the main challenges here, however, is that cooperation and specialization cannot be directly observed but rather must be constructed based on survey or administrative data.

Federal Policy Efforts to Simplify College-Going: An Intervention in Community College Enrollment and Borrowing

2017 ◽  
Vol 671 (1) ◽  
pp. 114-131 ◽  
Author(s):  
Kelly Ochs Rosinger
Keyword(s):  
Community College ◽  
Low Cost ◽  
Recent Effort ◽  
College Outcomes ◽  
College Costs ◽  
College Going ◽  
College Choices ◽  
Quasi Experimental ◽  
Informational Intervention ◽  
The Impact

Over the past decade, the federal government has made substantial efforts to simplify the college-going process and help students to evaluate college choices. These low-cost strategies aimed at improving college access and success by helping students to make informed decisions about college warrant assessment. This study examines the impact of a recent effort aimed at simplifying information that colleges provide to students about college costs, loan options, and college outcomes. Results from a quasi-experimental analysis indicate that the “informational intervention” in this study had limited influence on community college students’ enrollment and borrowing decisions. I discuss the limitations of this particular intervention and the potential impact that other related policy efforts designed to help students at various points in the college-going process may have.

Supporting women’s persistence in computing and technology

2019 ◽  
Vol 120 (5/6) ◽  
pp. 366-382 ◽  
Author(s):  
Joanna Weidler-Lewis ◽  
Wendy DuBow ◽  
Alexis Kaminsky ◽  
Tim Weston
Keyword(s):  
High School ◽  
Focus Groups ◽  
Young Women ◽  
Qualitative Interviews ◽  
Computational Thinking ◽  
Content Type ◽  
Qualitative Focus Groups ◽  
The Impact ◽  
Equity Perspective ◽  
High Schoolers

Purpose This paper aims to investigate what factors influence women’s meaningful and equitable persistence in computing and technology fields. It draws on theories of learning and equity from the learning sciences to inform the understanding of women’s underrepresentation in computing as it investigates young women who showed an interest in computing in high school and followed-up with them in their college and careers. Design/methodology/approach The mixed-methods approach compares data from quantitative surveys and qualitative focus groups and interviews. The sample comes from database of 1,500 young women who expressed interest in computing by applying for an award for high schoolers. These women were surveyed in 2013 and then again in 2016, with 511 women identifying themselves as high schoolers in 2013 and then having graduated and pursued college or careers in the second survey. The authors also conducted qualitative interviews and focus groups with 90 women from the same sample. Findings The findings show that multiple factors influence women’s persistence in computing, but the best predictor of women’s persistence is access to early computing and programming opportunities. However, access and opportunities must be evaluated within broader social and contextual factors. Research limitations/implications The main limitation is that the authors measure women’s persistence in computing according to their chosen major or profession. This study does not measure the impact of computational thinking in women’s everyday lives. Practical implications Educators and policymakers should consider efforts to make Computer Science-for-All a reality. Originality/value Few longitudinal studies of a large sample of women exist that follow women interested in computing from high school into college and careers particularly from a critical educational equity perspective.

Natural Experiments on the Impact of Financial Performance on Subsequent Changes in ESG Ratings

2021 ◽  
Vol 2021 (1) ◽  
pp. 14268
Author(s):  
Abbas Hejri ◽  
Dan Daugaard ◽  
Martina K. Linnenluecke ◽  
Thomas Martin Smith
Keyword(s):  
Financial Performance ◽  
Natural Experiments ◽  
The Impact
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