How to Suppress Turnout: Examining the Effects of Voter Identification Laws on Politically Disadvantaged Populations

2014 ◽  
Author(s):  
Lindsay Nielson
Keyword(s):  
Disadvantaged Populations ◽  
Voter Identification

User-Oriented Healthcare Translation and Communication

2020 ◽  
pp. 430-451
Author(s):  
Meng Ji ◽  
Kristine Sørensen ◽  
Pierrette Bouillon
Keyword(s):  
Health Literacy ◽  
Socioeconomically Disadvantaged ◽  
Disadvantaged Populations ◽  
Medical Translation ◽  
Medical Interpreting ◽  
Literacy Research

Healthcare translation provides a useful and powerful intervention tool to facilitate the engagement with migrants with diverse language, cultural, and health literacy backgrounds. The development of culturally effective and patient-oriented healthcare translation resources has become increasingly pressing. In this chapter, the authors explore, firstly, patient-focused and culturally effective healthcare and medical translation methodologies by integrating insights from health literacy research and corpus-based textual readability evaluation and, secondly, user-oriented criteria which can be used in the development and evaluation of new medical interpreting technologies with a view to enhancing the usability among patients from refugee, migrant, or other socioeconomically disadvantaged populations.

scholarly journals A Systematic Review and Meta-Analysis of Patient Decision Aids for Socially Disadvantaged Populations: Update from the International Patient Decision Aid Standards (IDPAS)

2021 ◽  
pp. 0272989X2110203
Author(s):  
Renata W. Yen ◽  
Jenna Smith ◽  
Jaclyn Engel ◽  
Danielle Marie Muscat ◽  
Sian K. Smith ◽  
...  
Keyword(s):  
Relative Risk ◽  
Health Inequalities ◽  
Data Extraction ◽  
Decision Aids ◽  
Mean Difference ◽  
Patient Decision Aids ◽  
Disadvantaged Populations ◽  
Socially Disadvantaged ◽  
Patient Decision ◽  
Intervention Trials

Background The effectiveness of patient decision aids (PtDAs) and other shared decision-making (SDM) interventions for socially disadvantaged populations has not been well studied. Purpose To assess whether PtDAs and other SDM interventions improve outcomes or decrease health inequalities among socially disadvantaged populations and determine the critical features of successful interventions. Data Sources MEDLINE, CINAHL, Cochrane, PsycINFO, and Web of Science from inception to October 2019. Cochrane systematic reviews on PtDAs. Study Selection Randomized controlled trials of PtDAs and SDM interventions that included socially disadvantaged populations. Data Extraction Independent double data extraction using a standardized form and the Template for Intervention Description and Replication checklist. Data Synthesis Twenty-five PtDA and 13 other SDM intervention trials met our inclusion criteria. Compared with usual care, PtDAs improved knowledge (mean difference = 13.91, 95% confidence interval [CI] 9.01, 18.82 [I2 = 96%]) and patient-clinician communication (relative risk = 1.62, 95% CI 1.42, 1.84 [I2 = 0%]). PtDAs reduced decisional conflict (mean difference = −9.59; 95% CI −18.94, −0.24 [I2 = 84%]) and the proportion undecided (relative risk = 0.39; 95% CI 0.28, 0.53 [I2 = 75%]). PtDAs did not affect anxiety (standardized mean difference = 0.02, 95% CI −0.22, 0.26 [I2 = 70%]). Only 1 trial looked at clinical outcomes (hemoglobin A1C). Five of the 12 PtDA studies that compared outcomes by disadvantaged standing found that outcomes improved more for socially disadvantaged participants. No evidence indicated which intervention characteristics were most effective. Results were similar for SDM intervention trials. Limitations Sixteen PtDA studies had an overall unclear risk of bias. Heterogeneity was high for most outcomes. Most studies only had short-term follow-up. Conclusions PtDAs led to better outcomes among socially disadvantaged populations but did not reduce health inequalities. We could not determine which intervention features were most effective. [Box: see text]

scholarly journals Do quality improvement initiatives for diabetes care address social inequities? Secondary analysis of a systematic review

BMJ Open ◽  
2018 ◽  
Vol 8 (2) ◽  
pp. e018826 ◽  
Author(s):  
Jacquie Boyang Lu ◽  
Kristin J Danko ◽  
Michael D Elfassy ◽  
Vivian Welch ◽  
Jeremy M Grimshaw ◽  
...  
Keyword(s):  
Systematic Review ◽  
Socioeconomic Status ◽  
Quality Improvement ◽  
Diabetes Care ◽  
Secondary Analysis ◽  
Place Of Residence ◽  
Disadvantaged Groups ◽  
Disadvantaged Populations ◽  
Patients With Diabetes ◽  
Race Ethnicity

BackgroundSocially disadvantaged populations carry a disproportionate burden of diabetes-related morbidity and mortality. There is an emerging interest in quality improvement (QI) strategies in the care of patients with diabetes, however, the effect of these interventions on disadvantaged groups remains unclear.ObjectiveThis is a secondary analysis of a systematic review that seeks to examine the extent of equity considerations in diabetes QI studies, specifically quantifying the proportion of studies that target interventions toward disadvantaged populations and conduct analyses on the impact of interventions on disadvantaged groups.Research design and methodsStudies were identified using Medline, HealthStar and the Cochrane Effective Practice and Organisation of Care database. Randomised controlled trials assessing 12 QI strategies targeting health systems, healthcare professionals and/or patients for the management of adult outpatients with diabetes were eligible. The place of residence, race/ethnicity/culture/language, occupational status, gender/sexual identity, religious affiliations, education level, socioeconomic status, social capital, plus age, disability, sexual preferences and relationships (PROGRESS-Plus) framework was used to identify trials that focused on disadvantaged patient populations, to examine the types of equity-relevant factors that are being considered and to explore temporal trends in equity-relevant diabetes QI trials.ResultsOf the 278 trials that met the inclusion criteria, 95 trials had equity-relevant considerations. These include 64 targeted trials that focused on a disadvantaged population with the aim to improve the health status of that population and 31 general trials that undertook subgroup analyses to assess the extent to which their interventions may have had differential impacts on disadvantaged subgroups. Trials predominantly focused on race/ethnicity, socioeconomic status and place of residence as potential factors for disadvantage in patients receiving diabetes care.ConclusionsLess than one-third of diabetes QI trials included equity-relevant considerations, limiting the relevance and applicability of their data to disadvantaged populations. There is a need for better data collection, reporting, analysis and interventions on the social determinants of health that may influence the health outcomes of patients with diabetes.PROSPERO registration numberCRD42013005165.

Understanding the Adoption of Voter Identification Laws in the American States

2017 ◽  
Vol 45 (4) ◽  
pp. 560-588 ◽  
Author(s):  
Daniel R. Biggers ◽  
Michael J. Hanmer
Keyword(s):  
Event History Analysis ◽  
Political Power ◽  
The State ◽  
Event History ◽  
Federal Legislation ◽  
The Past ◽  
Voter Identification ◽  
Extensive Analysis ◽  
American States ◽  
History Analysis

Recently, many states have reversed the decades-long trend of facilitating ballot access by enacting a wave of laws requesting or requiring identification from registrants before they vote. Identification laws, however, are not an entirely new phenomenon. We offer new theoretical insights regarding how changes in political power influence the adoption of identification laws. In the most extensive analysis to date, we use event history analysis to examine why states adopted a range of identification laws over the past several decades. We consistently find that the propensity to adopt is greatest when control of the governor’s office and legislature switches to Republicans (relationships not previously identified), and that this likelihood increases further as the size of Black and Latino populations in the state expands. We also find that federal legislation in the form of the Help America Vote Act seems to enhance the effects of switches in partisan control.

Data Mining Based Intelligent System for Voting Behavior Analysis

2013 ◽  
Vol 284-287 ◽  
pp. 3070-3073
Author(s):  
Duen Kai Chen
Keyword(s):  
Data Mining ◽  
Behavior Analysis ◽  
Voting Behavior ◽  
Intelligent System ◽  
Data Sets ◽  
Tree Model ◽  
Mining Technology ◽  
Identification Rate ◽  
Voter Identification ◽  
Election Studies

In this study, we report a voting behavior analysis intelligent system based on data mining technology. From previous literature, we have witnessed increasing number of studies applied information technology to facilitate voting behavior analysis. In this study, we built a likely voter identification model through the use of data mining technology, the classification algorithm used here constructs decision tree model to identify voters and non voters. This model is evaluated by its accuracy and number of attributes used to correctly identify likely voter. Our goal is to try to use just a small number of survey questions while maintaining the accuracy rates of other similar models. This model was built and tested on Taiwan’s Election and Democratization Study (TEDS) data sets. According to the experimental results, the proposed model can improve likely voter identification rate and this finding is consistent with previous studies based on American National Election Studies.

scholarly journals Memory: Looking back and looking forward

2018 ◽  
Vol 2 ◽  
pp. 239821281879483 ◽  
Author(s):  
John P. Aggleton ◽  
Richard G. M. Morris
Keyword(s):  
Neural Plasticity ◽  
Imaging Studies ◽  
Activation Patterns ◽  
Memory Research ◽  
Neuronal Ensembles ◽  
Disadvantaged Populations ◽  
Episodic Memories ◽  
Source Of Information ◽  
Looking Back

This review brings together past and present achievements in memory research, ranging from molecular to psychological discoveries. Despite some false starts, major advances include our growing understanding of learning-related neural plasticity and the characterisation of different classes of memory. One striking example is the ability to reactivate targeted neuronal ensembles so that an animal will seemingly re-experience a particular memory, with the further potential to modify such memories. Meanwhile, human functional imaging studies can distinguish individual episodic memories based on voxel activation patterns. While the hippocampus continues to provide a rich source of information, future progress requires broadening our research to involve other sites. Related challenges include the need to understand better the role of glial–neuron interactions and to look beyond the synapse as the sole site of experience-dependent plasticity. Unmet goals include translating our neuroscientific knowledge in order to optimise learning and memory, especially among disadvantaged populations.

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