Effects Of Policy Changes Research Articles

Adolescent reproductive health in a post- Dobbs landscape: a review.

To summarize notable recent research in adolescent reproductive health, particularly with respect to a rapidly changing legal landscape surrounding health services that significantly impact adolescent health. Approval of the first over-the-counter contraceptive pill represented a major advance in adolescent reproductive health, which relied on research regarding its safety, efficacy, and potential to increase access for vulnerable groups. Despite this approval, disparities persist in equitable contraceptive access for adolescents of color and those from sexual and gender identity minorities. Legal changes in access to abortion care and parental involvement in reproductive health decision-making have presented significant challenges for young people across the U.S. Recent research points to the promise of telehealth abortion care and parental acceptance of confidentiality in adolescent reproductive healthcare. Misinformation remains a barrier to advancing adolescent reproductive health and points to continued opportunities for providers to create evidence-based online content. In this review, we discuss recent research regarding adolescent reproductive health and laws impacting the reproductive health of adolescents. As the legal landscape evolves, further research surrounding the effect of policy changes that both expand and restrict access to adolescent reproductive health services will be critical to advancing adolescent health.

Research on the Effectiveness of Policy Interventions in Illegal Wildlife Trade Based on System Dynamics and Logistic Regression Models

This study is dedicated to assessing the long-term impact of policy interventions on the illegal wildlife trade system. To this end, we have constructed a System Dynamics model capable of simulating the complex interactions between key variables such as illegal trade demand (D), supply (S), enforcement strength (E), public awareness (A), and project intervention (P). By understanding the dynamic relationships among these variables, we can predict the effects of policy changes on the illegal wildlife trade market. Furthermore, we have employed a Logistic Regression model to quantify the probability of project success, considering multiple dimensions including increased enforcement efforts, enhanced public awareness, project interventions, and external factors. The combination of these two models not only enhances our comprehension of the dynamics of illegal wildlife trade but also provides policymakers with a scientific framework for evaluating and optimizing strategies. Parameter estimation based on historical data and expert opinions, along with sensitivity analysis of the models, enables us to provide a basis for the effective allocation of resources and precise policy adjustments. The findings indicate that reasonable policy interventions can significantly reduce the incidence of illegal wildlife trade while raising public awareness of wildlife conservation.

Quasi-experimental methods for pharmacoepidemiology: difference-in-differences and synthetic control methods with case studies for vaccine evaluation.

Difference-in-differences and synthetic control methods have become common study designs for evaluating the effects of changes in policies, including health policies. They also have potential for providing real-world effectiveness and safety evidence in pharmacoepidemiology. To effectively add to the toolkit of the field, however, designs-including both their benefits and drawbacks-must be well understood. Quasi-experimental designs provide an opportunity to estimate the average treatment effect on the treated without requiring the measurement of all possible confounding factors, and to assess population-level effects. This requires, however, other key assumptions, including the parallel trends or stable weighting assumptions, a lack of other concurrent events that could alter time trends, and an absence of contamination between exposed and unexposed units. The targeted estimands are also highly specific to the settings of the study, and combining across units or time periods can be challenging. Case studies are presented for 3 vaccine evaluation studies, showcasing some of these challenges and opportunities in a specific field of pharmacoepidemiology. These methods provide feasible and valuable sources of evidence in various pharmacoepidemiologic settings and can be improved through research to identify and weigh the advantages and disadvantages in those settings. This article is part of a Special Collection on Pharmacoepidemiology.

Nancy Pelosis Visit to Taiwan and Stock Indices Responses: An Event Study and Panel Data Analysis for Asia-Pacific and Selected Markets

Traditional financial market-based analyses of the anticipated effects of policy changes have only ever been retrospective. In this study, we provide an example to illustrate how prediction markets enable markets to be used to estimate policy effects in the future. In this article, we use an event study approach to empirically study the effect of Nancy Pelosi’s visit to Taiwan on stock indices performance in the Asia-Pacific region, the United States, and selected indices in Europe. The observed window comprises 10 days post the Nancy Pelosi’s visit, and the estimation window consists of 150 days before the event date. We found that the effect of visit has not been significant on the stock indices except Hong-Kong and China that too for very short-term. Our analysis enables us to identify how not all the news would be having an impact on stock indices. The investment community and academics can predict stock return behaviour and the dynamics of the first two minutes during crises by observing how stock return behaviour changes in response to financial crises.

Dynamics between FinTech and financial market: Supply-driven or Demand-guided?

<p>This paper examined the dynamic relationship between FinTech development and financial development using the time-varying parameter structural vector autoregression (TVP-SV-VAR) model to analyze their impulse response relationship. The results showed that the impact of FinTech development on financial development varies across different periods. In China, before the first half of 2021, financial development mainly drove FinTech development through demand. Afterward, FinTech development promoted financial development by providing new technological tools and services. In the United States, FinTech innovation and application mainly influenced financial development through supply-driven mechanisms. After the second half of 2022, as FinTech infrastructure improved, its positive impact on the financial market strengthened. The study also found that the effects of policy changes and market fluctuations on impulse responses at specific time points differed even in countries with different systems. The findings of this paper provide valuable insights for policymakers to address the challenges and opportunities brought on by FinTech.</p>

The possible impact of the universal two-child policy on pregnancy outcomes.

The implementation of the universal two-child policy contributes to adverse pregnancy outcomes, but how the policy change leads to adverse pregnancy outcomes is not well elaborated. In this study, we aimed to compare maternal characteristics and complications, accessed the change in the proportion of maternal characteristics and maternal complications, and evaluated the mediation of maternal characteristics on maternal complications. Demographic and clinical data of three-level sample facilities were extracted from China's National Maternity Near Miss Obstetrics Surveillance System from Jan 1, 2012 to May 31, 2021. The associations between the universal two-child policy and maternal riskfactors, the universal two-child policy and maternal complications, and maternal risk factors and maternal complications were evaluated using multivariate logistic regression analyses, with odds ratios (ORs) and 95% confidence intervals (CIs). Mediation analysis was used to estimate the potential mediation effects on the associations between the policy and maternal complications. Population-attributable fractions (PAF) were conducted to quantify the maternal complications burden attributable to the implementation of the universal two-child policy. In the context of the universal two-child policy, the incidence of maternal near miss, antepartum or intrapartum complication, and post-partum complication increased at municipal- and county-level sample facilities. After adjusting for covariables, there were significant associations between the universal two-child policy and maternal risk factors (P < 0.001), the universal two-child policy and an increased risk of maternal complications (P < 0.001), and maternal risk factors and maternal complications(P < 0.001). The effects of the universal two-child policy on maternal near miss and medical disease were significantly mediated by maternal risk factors with mediation proportions of 19.77% and 4.07% at the municipal-level sample facility, and mediation proportions for 2.72% at the county-level sample facility on medical disease. The universal two-child policy contributed 19.34%, 5.82%, 8.29%, and 46.19% in the incidence of the maternal near miss, antepartum or intrapartum complication, post-partum complication, and medical disease at municipal-level sample facility, respectively. The corresponding PAF% at county-level sample facility was 40.49% for maternal near miss, 32.39% for the antepartum or intrapartum complication, 61.44% for post-partum complication, and 77.72% for medical disease. For provincial-level sample facility, the incidence of maternal near miss, antepartum or intrapartum complications, and medical diseases decreased (P < 0.05) and no statistically significant difference occurred in the incidence of post-partum complications. In the context of the universal two-child policy, the incidence of maternal near miss, antepartum or intrapartum complication, and post-partum complication increased at municipal- and county-level sample facility. Maternal risk factors may play a mediating role in the effect of policy change and maternal complications. Provincial hospitals have been able to improve the quality of perinatal health care and reduce adverse pregnancy outcomes by adjusting their obstetric service strategies in the context of the new birth policy.

Comprehensive evaluation of the effectiveness of endemic disease prevention and control in Jiangsu Province, China, 2013-2022.

As a strong economic and populous province in China, Jiangsu is home to four endemic diseases. Despite efforts in the past decade, the prevention and control of these four endemic diseases are not uniform because of the different etiological chains and influencing factors of these diseases. Among the evaluation methodologies for endemic disease control, only one method is currently available for each disease. In this study, we selected 14 indicators to comprehensively evaluate the effectiveness of endemic disease control in Jiangsu between 2013 and 2022. We improved the method for calculating the weights of the indicators and established a fuzzy comprehensive evaluation model based on the weighted Technique for Order Preference by Similarity to an Ideal Solution model and a weighted grey relational analysis model. The results of the comprehensive evaluation showed that the progress of endemic disease control in Jiangsu was not always in line with our expectations of improvement, with the top five years of better control occurring in 2015, 2013, 2021, 2022, and 2014. The results of the sensitivity analysis confirm the reliability and accuracy of these findings. We discovered that measures such as the reform of the salt industry, use of thyroid ultrasound, and new water supply projects for residents in Jiangsu affected the progress of endemic disease prevention and control. The tracking of endemic disease status should consider the potential effects of changes in policies implemented in other industries on endemic disease prevention and control. Additionally, the results of this study provide a theoretical basis for enhancing prevention and control practices in other regions of China.

Policies to reduce child poverty and child maltreatment: A scoping review and preliminary estimates of indirect effects

This study includes a scoping review of prior studies investigating the effects of policy changes on child poverty rates. It further conducts an empirical analysis to estimate the relationship between child poverty rates and child maltreatment report (CMR) rates, utilizing national county-level data. The study then calculates the indirect effects of policy changes on CMR rates, mediated through child poverty rates, by integrating information from previous studies with its own empirical findings. Among the policy changes explored in prior studies, those related to a child allowance and a fully refundable Child Tax Credit demonstrate the largest indirect effects but also the highest costs. The expansion of in-kinds and near-cash benefits, such as the Supplemental Nutrition Assistance Program benefits and housing vouchers, shows moderate effects with moderate costs. Tax credits like the Earned Income Tax Credit exhibit lower effects and costs when targeted at the lowest earners, and moderate effects and costs for broader expansion. Focused tax credits, such as the Child and Dependent Care Tax Credit, had lower effects and costs, even if made fully refundable. Despite certain limitations, the study's approach yields consistent estimates with a recent simulation study, indicating its potential validity. While some proposed policy changes may seem expensive, implementing them is anticipated to substantially reduce CMR rates, with the benefits outweighing the associated costs. Overall, the findings suggest that addressing child poverty to reduce CMRs is an attractive strategy with numerous potential benefits.

The effects of policy changes and human mobility on the COVID-19 epidemic in the Dominican Republic, 2020–2021

Recent advances in technology can be leveraged to enhance public health research and practice. This study aimed to assess the effects of mobility and policy changes on COVID-19 case growth and the effects of policy changes on mobility using data from Google Mobility Reports, information on public health policy, and COVID-19 testing results. Multiple bivariate regression analyses were conducted to address the study objectives. Policies designed to limit mobility led to decreases in mobility in public areas. These policies also decreased COVID-19 case growth. Conversely, policies that did not restrict mobility led to increases in mobility in public areas and led to increases in COVID-19 case growth. Mobility increases in public areas corresponded to increases in COVID-19 case growth, while concentration of mobility in residential areas corresponded to decreases in COVID-19 case growth. Overall, restrictive policies were effective in decreasing COVID-19 incidence in the Dominican Republic, while permissive policies led to increases in COVID-19 incidence.

Assessment of COVID-19-related medical device regulator policies on entry to market for prioritised devices: a case study

Background/Aims In response to the COVID-19 pandemic, medical devices were given exceptional use authorisations. Medical device regulators around the world modified their administrative approach to medical device approval to ensure that relevant devices and personal protection equipment would be available to healthcare professionals and patients. Using data from medical device regulators in the US and Australia, this study assessed the impact of COVID-19-related regulatory modifications implemented to allow quick market entry of relevant equipment, and how data science techniques can help to inform future policy. Methods Data from the US Food and Drug Administration's Global Unique Device Identification Database and the Australian Therapeutic Goods Administration's Australian Register of Therapeutic Goods were used as case studies to explore the effects of policy changes. All COVID-19-related devices and personal protective equipment were identified in the data using the Global Medical Device Nomenclature system and device descriptions. A 10-day and 20-day moving average was applied to assess how many of these devices reached the market between 30 July 2019 and 24 June 2020. Results In both the US and Australian datasets, the number of market entries increased after the pandemic began. However, the impact of the Australian policy appeared to be greater than that of the US, as there was a considerable increase in the number of personal protective equipment and COVID-19-related device registrations following the declaration of the pandemic in Australia, while the impact on the US data was relatively minimal. Conclusions In general, market entry of relevant equipment increased during the COVID-19 pandemic, indicating the possible impact of policy changes. The kind of data captured in national databases greatly influences the ability to accurately track performance of regulatory policy changes. This work shows the potential of using data science in a regulatory context to assess if a policy change creates the desired effect.

Predictors of recovery in a medium secure service: Influence of the Welsh Government's Mental Health (2010) Measure

BackgroundResearch to date has failed to examine the effectiveness of MSUs in facilitating recovery, or the influence that mental health policy may have on this process. Examining predictors of short-term clinical outcomes during inpatient admission and the effects of policy changes may inform future policy, treatment planning and may improve service user outcomes. AimsTo examine whether service user admission characteristics and length of stay predicted recovery status at discharge from medium secure care and whether a recovery-focused change in policy (introduction of the Mental Health (Wales) Measure (2010)) impacted either on recovery or the relationship between service user characteristics and recovery. MethodsThe study adopted a retrospective analysis of quantitative data obtained from healthcare records from a Welsh MSU between 2007 and 2017 (n = 198). The DUNDUM-4 scale assessed recovery whilst DUNDRUM-2 assessed security need at admission. Service user admission characteristics included HCR-20 subscale scores, previous security-level transitions, adverse childhood experiences, substance misuse histories. ResultsShorter inpatient stays and higher scores on the dynamic HCR-20 clinical subscale were associated with poorer recovery outcomes. The relationship between admission characteristics and recovery endured despite changes in policy. Implementation of recovery focused legislation was associated with improved recovery. ConclusionsThe findings suggest that treatment should focus on dynamic risk factors to improve service user outcomes and highlights the need for long-term medium-secure provision for some. Further research is needed to evaluate the success of MSUs and the validity of the DUNDRUM-4 across UK secure services.

The effectiveness and decay of public health policy actions on infection-control behaviour in the general public: Evidence from a low-COVID prevalence jurisdiction.

Public health policies designed to influence individuals' infection-control behaviour are a tool for governments to help prevent the spread of disease. Findings on the impacts of policies are mixed and there is limited information on the effects of removing restrictions and how policies impact behavioural trends. We use low-acuity emergency department visits from 12 hospitals in New Brunswick, Canada, (January 2017 -October 2021) as a proxy for infection-control behaviour and provide insight into the effects of the COVID-19 virus on a population with a low prevalence of cases. Quasi-experimental techniques (event studies) are applied to estimate the magnitude and persistence of effects of specific events (e.g., policy changes), to control for COVID-19 cases and vaccines, and to explore how the effectiveness of policy changes during the pandemic as more policies are introduced. Initial tightening of restrictions on March 11, 2020 reduced low-acuity emergency department visits by around 60% and reached a minimum after 30 days. Relaxing policies on social gatherings and personal services gradually increased low-acuity emergency department visits by approximately 50% after 44 days. No effects were found from policies lifting all restrictions, and reinstating a state of emergency on July 31, 2021, and September 24, 2021. These results suggest that policy interventions are less likely to be effective at influencing infection control behaviour with time and more policies introduced, and that tracking and publicly reporting case numbers can influence infection control behaviour.

Is Policy Greasing the Wheels of Global Palm Oil Trade?

Oil palm is the major source of edible oil and feedstock consumed in the world. This study examined the determinants of global palm oil trade with attention to the effects of trade policies using a gravity model, PPML estimator, and the data from 1988-2020. Palm oil’s dramatic trade growth in recent years can be attributed to the economic growth of large countries, the proximity of partners and policies. Trade agreements increased crude and refined palm oil trade by up to 8 and 4 percent of the global import value, respectively. Further, the effects of policy changes due to COVID-19 and the recent export ban in Indonesia are also quantified.

Care work in different arenas: Working conditions in Swedish eldercare and disability services

AbstractCare work is shaped by the context in which it is carried out. This study explored the context, content, conditions and consequences of work in two fields of social care in Sweden: eldercare and disability services. Policy documents and statistical sources were used to analyse the context. Job content, working conditions and consequences of work were analysed using survey data collected in 2015 and 2017 in eldercare and disability services (N = 1307). The analysis of the political and economic context showed that the disability sector is characterised by a higher ambition level in legislation and funding. The survey of care workers reflected this difference: the work content differs; and the working conditions and their consequences are significantly worse for the eldercare staff than for the disability service staff. Possible explanations for these differences are discussed in terms of policy‐framing, ageist notions and unintended consequences of policy changes.

Availability of healthy foods, fruit and vegetable consumption, and cognition among urban older adults

Background. Although prior studies have examined the associations between neighborhood characteristics and cognitive health, little is known about whether local food environments, which are critical for individuals’ daily living, are associated with late-life cognition. Further, little is known about how local environments may shape individuals’ health-related behaviors and impact cognitive health. The aim of this study is to examine whether objective and subjective measures of healthy food availability are associated with ambulatory cognitive performance and whether behavioral and cardiovascular factors mediate these associations among urban older adults.Methods. The sample consisted of systematically recruited, community-dwelling older adults (N = 315, mean age = 77.5, range = 70–91) from the Einstein Aging Study. Objective availability of healthy foods was defined as density of healthy food stores. Subjective availability of healthy foods and fruit/vegetable consumption were assessed using self-reported questionnaires. Cognitive performance was assessed using smartphone-administered cognitive tasks that measured processing speed, short-term memory binding, and spatial working memory performance 6 times a day for 14 days.Results. Results from multilevel models showed that subjective availability of healthy foods, but not objective food environments, was associated with better processing speed (estimate= -0.176, p = .003) and more accurate memory binding performance (estimate = 0.042, p = .012). Further, 14~16% of the effects of subjective availability of healthy foods on cognition were mediated through fruit and vegetable consumption.Conclusions. Local food environments seem to be important for individuals’ dietary behavior and cognitive health. Specifically, subjective measures of food environments may better reflect individuals’ experiences regarding their local food environments not captured by objective measures. Future policy and intervention strategies will need to include both objective and subjective food environment measures in identifying impactful target for intervention and evaluating effectiveness of policy changes.

An Explicit Spatial Approach to the Value of Local Social Amenities in Metro and Non-Metro Counties in the U.S.: Implications for Comprehensive Wealth Measurement

This study extends and reinterprets Roback’s general spatial equilibrium model by casting it within the comprehensive wealth framework. Considering the explicit spatial effects among regions, the analysis refines estimates of the contribution of natural, built, social, cultural, and human capital to residents’ wealth. We develop an empirical model and apply it to secondary data from 3109 counties in the United States. Our analysis provides a means of partitioning the sources of wealth in traditionally measured financial wealth and various types of amenities, while avoiding double counting the values of natural and publicly provided assets. Our findings indicate that rising property values are not simply an outcome of limited supply but are often an indicator of rising demand for improving amenities, suggesting different strategies for property and income taxation policy. There are apparently differences between the value of amenities in metro and non-metro counties. Our model explicitly estimates the spatial spillover and feedback effects of policy changes on local land values and wages. It also measures the differences in determinants of asset values and wages in metro from non-metro counties in the U.S.

Commentary on Luukkonen et al.: Policy possibilities for reducing public health harms related to pregnant people's alcohol consumption.

Commentary on Luukkonen et al.: Policy possibilities for reducing public health harms related to pregnant people's alcohol consumption.

Uncertain Malmquist productivity index: An application to evaluate healthcare systems during COVID-19 pandemic

Evaluation of healthcare systems, as a key organization providing different health services, is essential. This issue becomes more crucial when occurring crises such as a pandemic. They need to keep track of their success in the face of the crisis to assess the effects of policy changes and their capability to respond to new challenges. The Malmquist Productivity Index (MPI) is measured to analyze the causes of productivity change between two periods of time. The estimation of the traditional MPI requires reliable and detailed information on the inputs and outputs of decision-making units. However, there are a lot of situations where input and/or output may be imprecise. It is not manageable to reliably measure certain measurement indices, such as quality of treatment or system flexibility. For such cases, experts are invited to model their opinion. Uncertainty theory is a mathematical branch rationally dealing with belief degrees. The primary objective of this study is to apply MPI concept in the nonparametric approach of data envelopment analysis to calculate the efficiency of systems over different periods of time under uncertain conditions. Accordingly, we consider the MPI when inputs and outputs are belief degrees of experts. Furthermore, the sensitivity of the model is analyzed to determine the reliability of the results to the variation of variables. Finally, as an illustrative example, we explore longitudinal efficiency of healthcare systems during COVID-19 pandemic. According to the results of our model, the majority of the countries have improved in the second period which can be the result of efforts to improve pandemic preparedness. The decomposition of MPI into efficiency changes and technical changes indicates that the rise in productivity is entirely related to the progressive change of the production frontier related to policymaking. This application attempts to demonstrate how crucial it is to take uncertainties into account when comparing the performance of different systems over periods of time. The developed model enables us to consider the uncertainty existing in COVID-19 pandemic. The proposed model can handle more accurately the uncertainty during the pandemic. Thus, the result could be more reliable, which can benefit decision-makers in regard to performance improvement.

The Human Cost of Collusion: Health Effects of a Mexican Insulin Cartel

Abstract Despite recent attention to the role of competition in determining health outcomes in developed nations, little is known about how market power impedes access to quality care in lower-income countries. This paper studies the effects of policy changes that stopped collusion among firms supplying insulin to one of Mexico’s largest health care providers. I document increased insulin utilization and decreased diabetes complications and mortality following the sudden drop in insulin prices caused by the cartel’s collapse. These adverse health outcomes expand the assessment of damages caused by the cartel. The findings highlight the importance of market design policies in health markets, particularly for low- and middle-income countries.

Distributional Synthetic Controls

The method of synthetic controls is a fundamental tool for evaluating causal effects of policy changes in settings with observational data. In many settings where it is applicable, researchers want to identify causal effects of policy changes on a treated unit at an aggregate level while having access to data at a finer granularity. This article proposes an extension of the synthetic controls estimator that takes advantage of this additional structure and provides nonparametric estimates of the heterogeneity within the aggregate unit. The idea is to replicate the quantile function associated with the treated unit by a weighted average of quantile functions of the control units. This estimator relies on the same mathematical theory as the changes‐in‐changes estimator and can be applied in both repeated cross‐sections and panel data with as little as a single pre‐treatment period. It also provides a unique counterfactual quantile function for any type of distribution.