scholarly journals Evaluating Public Health Interventions: 5. Causal Inference in Public Health Research—Do Sex, Race, and Biological Factors Cause Health Outcomes?

2017 ◽  
Vol 107 (1) ◽  
pp. 81-85 ◽  
Author(s):  
M. Maria Glymour ◽  
Donna Spiegelman
Keyword(s):  
Public Health ◽  
Health Outcomes ◽  
Causal Inference ◽  
Health Research ◽  
Public Health Research ◽  
Health Interventions ◽  
Biological Factors ◽  
Public Health Interventions

scholarly journals Implications for public health research of models and theories of disability: a scoping study and evidence synthesis

2016 ◽  
Vol 4 (8) ◽  
pp. 1-166 ◽  
Author(s):  
Maria Berghs ◽  
Karl Atkin ◽  
Hilary Graham ◽  
Chris Hatton ◽  
Carol Thomas
Keyword(s):  
Public Health ◽  
Scoping Review ◽  
Health Research ◽  
Decision Aid ◽  
Public Health Research ◽  
Health Interventions ◽  
Evidence Based ◽  
Disabled People ◽  
Public Health Interventions ◽  
Models Of Disability

BackgroundPublic health interventions that are effective in the general population are often assumed to apply to people with impairments. However, the evidence to support this is limited and hence there is a need for public health research to take a more explicit account of disability and the perspectives of people with impairments.Objectives(1) To examine the literature on theories and models of disability; (2) to assess whether or not, and how, intervention studies of effectiveness could incorporate more inclusive approaches that are consistent with these theories and models; and (3) to use the findings to draw out implications for improving evaluative study designs and evidence-based practice.Review methodsThe project is a scoping review of the literature. The first stage examines theories and models of disability and reflects on possible connections between theories of disability and public health paradigms. This discussion is used to develop an ethical–empirical decision aid/checklist, informed by a human rights approach to disability and ecological approaches to public health. We apply this decision aid in the second stage of the review to evaluate the extent to which the 30 generic public health reviews of interventions and the 30 disability-specific public health interventions include the diverse experiences of disability. Five deliberation panels were also organised to further refine the decision aid: one with health-care professionals and four with politically and socially active disabled people.ResultsThe evidence from the review indicated that there has been limited public health engagement with theories and models of disability. Outcome measures were often insensitive to the experiences of disability. Even when disabled people were included, studies rarely engaged with their experiences in any meaningful way. More inclusive research should reflect how people live and ‘flourish’ with disability.LimitationsThe scoping review provides a broad appraisal of a particular field. It generates ideas for future practice rather than a definite framework for action.ConclusionsOur ethical–empirical decision aid offers a critical framework with which to evaluate current research practice. It also offers a resource for promoting more ethical and evidence-based public health research that is methodologically robust while being sensitive to the experiences of disability.Future workDeveloping more inclusive research and interventions that avoid conceptualising disability as either a ‘burden’ or ‘problem’ is an important starting point. This includes exploring ways of refining and validating current common outcome measures to ensure that they capture a diverse range of disabling experiences, as well as generating evidence on meaningful ways of engaging a broad range of disabled children and adults in the research process.FundingThe National Institute for Health Research Public Health Research programme.

scholarly journals Introduction to the Symposium: Causal Inference and Public Health

2019 ◽  
Vol 40 (1) ◽  
pp. 1-5 ◽  
Author(s):  
Allison E. Aiello ◽  
Lawrence W. Green
Keyword(s):  
Public Health ◽  
Causal Inference ◽  
Health Research ◽  
External Validity ◽  
Environmental Science ◽  
Social Epidemiology ◽  
Public Health Research ◽  
Health Problems ◽  
Research Findings ◽  
Internal And External Validity

Assessing the extent to which public health research findings can be causally interpreted continues to be a critical endeavor. In this symposium, we invited several researchers to review issues related to causal inference in social epidemiology and environmental science and to discuss the importance of external validity in public health. Together, this set of articles provides an integral overview of the strengths and limitations of applying causal inference frameworks and related approaches to a variety of public health problems, for both internal and external validity.

scholarly journals The Role of Implementation Science in Advancing Resource Generation for Health Interventions in Low- and Middle-Income Countries

2021 ◽  
Vol 14 ◽  
pp. 117863292199965
Author(s):  
Temitope Ojo ◽  
Laetitia Kabasele ◽  
Bethanny Boyd ◽  
Scholastica Enechukwu ◽  
Nessa Ryan ◽  
...  
Keyword(s):  
Public Health ◽  
Health Outcomes ◽  
Implementation Science ◽  
Health Workers ◽  
Contextual Factors ◽  
Health Interventions ◽  
Evidence Based ◽  
Public Health Interventions ◽  
Middle Income ◽  
Middle Income Countries

Low- and middle-income countries (LMICs) bear the brunt of communicable and non-communicable diseases and experience higher mortality and poor health outcomes compared to resource-rich countries. Chronic resource deficits in LMICs impede their ability to successfully address vexing health issues. Implementation science provides researchers with an approach to develop specific interventions that can generate and/or maximize resources to facilitate the implementation of other public health interventions, in resource-constrained LMIC settings. Resources generated from these interventions could be in the form of increased health workers’ skills, task shifting to free up higher-skilled health workers, increasing laboratory capacity, and using supply chain innovations to make medications available. Pivotal to the success of such interventions is ensuring feasibility in the LMIC context. We selected and appraised three case studies of evidence-based resource-generating health interventions based in LMICs (Zambia, Zimbabwe, and Madagascar), which generated or maximized resources to facilitate ongoing health services. We used a determinant implementation framework—Consolidated Framework for Implementation Research (CFIR) to identify and map contextual factors that are reported to influence implementation feasibility in an LMIC setting. Contextual factors influencing the feasibility of these interventions included leadership engagement, local capacity building and readiness for research and implementing evidence-based practices (EBPs), infrastructural support for multilevel scale-up, and cultural and contextual adaptations. These factors highlight the importance of utilizing implementation science frameworks to evaluate, guide, and execute feasible public health interventions and projects in resource-limited settings. Within LMICs, we recommend EBPs incorporate feasible resource-generating components in health interventions to ensure improved and sustained optimal health outcomes.

scholarly journals Can synthetic controls improve causal inference in interrupted time series evaluations of public health interventions?

2020 ◽  
Author(s):  
Michelle Degli Esposti ◽  
Thees Spreckelsen ◽  
Antonio Gasparrini ◽  
Douglas J Wiebe ◽  
Carl Bonander ◽  
...  
Keyword(s):  
Public Health ◽  
Time Series ◽  
Causal Inference ◽  
Interrupted Time Series ◽  
Health Interventions ◽  
Synthetic Control ◽  
Public Health Interventions ◽  
Control Series ◽  
Time Series Studies ◽  
Synthetic Controls

Abstract Interrupted time series designs are a valuable quasi-experimental approach for evaluating public health interventions. Interrupted time series extends a single group pre-post comparison by using multiple time points to control for underlying trends. But history bias—confounding by unexpected events occurring at the same time of the intervention—threatens the validity of this design and limits causal inference. Synthetic control methodology, a popular data-driven technique for deriving a control series from a pool of unexposed populations, is increasingly recommended. In this paper, we evaluate if and when synthetic controls can strengthen an interrupted time series design. First, we summarize the main observational study designs used in evaluative research, highlighting their respective uses, strengths, biases and design extensions for addressing these biases. Second, we outline when the use of synthetic controls can strengthen interrupted time series studies and when their combined use may be problematic. Third, we provide recommendations for using synthetic controls in interrupted time series and, using a real-world example, we illustrate the potential pitfalls of using a data-driven approach to identify a suitable control series. Finally, we emphasize the importance of theoretical approaches for informing study design and argue that synthetic control methods are not always well suited for generating a counterfactual that minimizes critical threats to interrupted time series studies. Advances in synthetic control methods bring new opportunities to conduct rigorous research in evaluating public health interventions. However, incorporating synthetic controls in interrupted time series studies may not always nullify important threats to validity nor improve causal inference.

scholarly journals Lessons from the first 6 years of an intervention-based field epidemiology training programme in Papua New Guinea, 2013–2018

2019 ◽  
Vol 4 (6) ◽  
pp. e001969 ◽  
Author(s):  
Barry Ropa ◽  
James Flint ◽  
Michael O'Reilly ◽  
Boris Igor Pavlin ◽  
Rosheila Dagina ◽  
...  
Keyword(s):  
Public Health ◽  
Health Outcomes ◽  
Papua New Guinea ◽  
New Guinea ◽  
Training Programme ◽  
Health Interventions ◽  
Public Health Workforce ◽  
Public Health Interventions ◽  
Independent State ◽  
Field Epidemiology

Papua New Guinea (PNG) faces a critical shortage of human resources to address pressing public health challenges arising from an increasing burden of communicable and non-communicable diseases. PNG is an independent State in the Pacific and home to 8.2 million people. Resource and infrastructure constraints due to the country’s challenging geography have made it difficult and expensive to deliver health services and implement health programmes. The National Department of Health and its partners developed a field epidemiology training programme of Papua New Guinea (FETPNG) to strengthen the country’s public health workforce. The training programme covers field epidemiology competencies and includes the design, implementation and evaluation of evidence-based interventions by Fellows. From 2013 to 2018, FETPNG graduated 81 field epidemiologists. Most FETPNG graduates (84%) were from provincial or district health departments or organisations. Many of their intervention projects resulted in successful public health outcomes with tangible local impacts. Health challenges addressed included reducing the burden of multi-drug resistant-tuberculosis (TB), increasing immunisation coverage, screening and treating HIV/TB patients, and improving reproductive health outcomes. FETPNG Fellows and graduates have also evaluated disease surveillance systems and investigated disease outbreaks. Early and unwavering national ownership of FETPNG created a sustainable programme fitting the needs of this low-resource country. A focus on designing and implementing effective public health interventions not only provides useful skills to Fellows but also contributes to real-time, tangible and meaningful improvements in the health of the population. The graduates of FETPNG now provide a critical mass of public health practitioners across the country. Their skills in responding to outbreaks and public health emergencies, in collecting, analysing and interpreting data, and in designing, implementing and evaluating public health interventions continues to advance public health in PNG.

Access to intervene. An ethnographic study of public health practices targeting health inequalities

2021 ◽  
pp. 136345932110328
Author(s):  
Mette Terp Høybye ◽  
Ditte Herring Holt ◽  
Morten Hulvej Rod
Keyword(s):  
Public Health ◽  
Health Inequalities ◽  
Theoretical Perspective ◽  
Economic Value ◽  
Public Health Research ◽  
Health Problems ◽  
Ethnographic Study ◽  
Health Interventions ◽  
Public Health Interventions ◽  
Target Groups

Much public health research has devoted attention to the question of how interventions aimed at reducing health inequalities can access so-called “hard-to-reach” populations. This work has generally reflected an instrumentalist approach, which implies the preexistence of particular target groups characterized by specific public health problems. The key research interests are to find ways to effectively alleviate health inequalities and to identify the best ways to intervene to address disparate health problems among certain groups of people. Based on ethnographic research with public health officers in four Danish municipalities, this article turns the issue on its head by examining how public health officers gain access to intervene in practice and, as part of this process, define and delineate target groups and public health problems. Through detailed descriptions of two ethnographic cases, we develop the argument that public health interventions carry with them moral differentiations that may contradict the overall intention of reducing health inequalities. We adopt a theoretical perspective developed by Lakoff and Collier, suggesting that public health interventions can be understood as “regimes of living.” This leads us to the conclusion that the practices of gaining access result in the production of unforeseen target groups and new moral configurations where the value of health becomes linked to other types of value, most importantly economic value. For public health officers, the complicated issue of gaining access to intervene is not simply a matter of finding practical solutions; it also defines and delineates the scope of public health itself.

scholarly journals 107 Can synthetic controls improve causal inference in interrupted time series evaluations of public health interventions?

2020 ◽  
Author(s):  
Michelle Degli Esposti ◽  
Thees Spreckelsen ◽  
Antonio Gasparrini ◽  
Douglas J Wiebe ◽  
Alexa R Yakubovich ◽  
...  
Keyword(s):  
Public Health ◽  
Time Series ◽  
Causal Inference ◽  
Interrupted Time Series ◽  
Health Interventions ◽  
Public Health Interventions ◽  
Synthetic Controls
Sign in / Sign up

Export Citation Format

Share Document