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Changes for page Research at a Glance

Last modified by Ryan C on 2025/06/26 03:09

From 71.1 to 70.1 From 76.1 to 75.1

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@@ -1455,745 +1455,4 @@
  {{html}}<hr style="border: 3px solid red;">{{/html}}
--{{expand title="Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program" expanded="false"}}
--**Source:** *Substance Use & Misuse*
--**Date of Publication:** *2002*
--**Author(s):** *Clifford A. Butzin, Christine A. Saum, Frank R. Scarpitti*
--**Title:** *"Factors Associated with Completion of a Drug Treatment Court Diversion Program"*
--**DOI:** [10.1081/JA-120014424](https://doi.org/10.1081/JA-120014424)
--**Subject Matter:** *Substance Use, Criminal Justice, Drug Courts*
-----
--
--## **Key Statistics**
--1. **General Observations:**
--   - Study examined **drug treatment court success rates** among first-time offenders.
--   - Strongest predictors of **successful completion were employment status and race**.
--
--2. **Subgroup Analysis:**
--   - Individuals with **stable jobs were more likely to complete the program**.
--   - **Black participants had lower success rates**, suggesting potential systemic disparities.
--
--3. **Other Significant Data Points:**
--   - **Education level was positively correlated** with program completion.
--   - Frequency of **drug use before enrollment affected treatment outcomes**.
--
-----
--
--## **Findings**
--1. **Primary Observations:**
--   - **Social stability factors** (employment, education) were key to treatment success.
--   - **Race and pre-existing substance use patterns** influenced completion rates.
--
--2. **Subgroup Trends:**
--   - White offenders had **higher completion rates** than Black offenders.
--   - Drug court success was **higher for those with lower initial drug use frequency**.
--
--3. **Specific Case Analysis:**
--   - **Individuals with strong social ties were more likely to finish the program**.
--   - Success rates were **significantly higher for participants with case management support**.
--
-----
--
--## **Critique and Observations**
--1. **Strengths of the Study:**
--   - **First empirical study on drug court program success factors**.
--   - Uses **longitudinal data** for post-treatment analysis.
--
--2. **Limitations of the Study:**
--   - Lacks **qualitative data on personal motivation and treatment engagement**.
--   - Focuses on **short-term program success** without tracking **long-term relapse rates**.
--
--3. **Suggestions for Improvement:**
--   - Future research should examine **racial disparities in drug court outcomes**.
--   - Study **how community resources impact long-term recovery**.
--
-----
--
--## **Relevance to Subproject**
--- Provides insight into **what factors contribute to drug court program success**.
--- Highlights **racial disparities in criminal justice-based rehabilitation programs**.
--- Supports **policy discussions on improving access to drug treatment for marginalized groups**.
--
-----
--
--## **Suggestions for Further Exploration**
--1. Investigate **the role of mental health in drug court success rates**.
--2. Assess **long-term relapse prevention strategies post-treatment**.
--3. Explore **alternative diversion programs beyond traditional drug courts**.
--
-----
--
--## **Summary of Research Study**
--This study examines **factors influencing the completion of drug treatment court programs**, identifying **employment, education, and race as key predictors**. The research underscores **systemic disparities in drug court outcomes**, emphasizing the need for **improved support systems for at-risk populations**.
--
--This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
--
-----
--
--## **📄 Download Full Study**
--[[Download Full Study>>attach:10.1081_JA-120014424.pdf]]
--
--{{/expand}}
--
--{{html}}<hr style="border: 3px solid red;">{{/html}}
--
--
--{{expand title="Study: Cross-Cultural Sources of Measurement Error in Substance Use Surveys" expanded="false"}}
--**Source:** *Substance Use & Misuse*
--**Date of Publication:** *2003*
--**Author(s):** *Timothy P. Johnson, Phillip J. Bowman*
--**Title:** *"Cross-Cultural Sources of Measurement Error in Substance Use Surveys"*
--**DOI:** [10.1081/JA-120023394](https://doi.org/10.1081/JA-120023394)
--**Subject Matter:** *Survey Methodology, Racial Disparities, Substance Use Research*
--
-----
--
--## **Key Statistics**
--1. **General Observations:**
--   - Study examined **how racial and cultural factors influence self-reported substance use data**.
--   - Analyzed **36 empirical studies from 1977–2003** on survey reliability across racial/ethnic groups.
--
--2. **Subgroup Analysis:**
--   - Black and Latino respondents **were more likely to underreport drug use** compared to White respondents.
--   - **Cultural stigma and distrust in research institutions** affected self-report accuracy.
--
--3. **Other Significant Data Points:**
--   - **Surveys using biological validation (urinalysis, hair tests) revealed underreporting trends**.
--   - **Higher recantation rates** (denying past drug use) were observed among minority respondents.
--
-----
--
--## **Findings**
--1. **Primary Observations:**
--   - Racial/ethnic disparities in **substance use reporting bias survey-based research**.
--   - **Social desirability and cultural norms impact data reliability**.
--
--2. **Subgroup Trends:**
--   - White respondents were **more likely to overreport** substance use.
--   - Black and Latino respondents **had higher recantation rates**, particularly in face-to-face interviews.
--
--3. **Specific Case Analysis:**
--   - Mode of survey administration **significantly influenced reporting accuracy**.
--   - **Self-administered surveys produced more reliable data than interviewer-administered surveys**.
--
-----
--
--## **Critique and Observations**
--1. **Strengths of the Study:**
--   - **Comprehensive review of 36 studies** on measurement error in substance use reporting.
--   - Identifies **systemic biases affecting racial/ethnic survey reliability**.
--
--2. **Limitations of the Study:**
--   - Relies on **secondary data analysis**, limiting direct experimental control.
--   - Does not explore **how measurement error impacts policy decisions**.
--
--3. **Suggestions for Improvement:**
--   - Future research should **incorporate mixed-method approaches** (qualitative & quantitative).
--   - Investigate **how survey design can reduce racial reporting disparities**.
--
-----
--
--## **Relevance to Subproject**
--- Supports research on **racial disparities in self-reported health behaviors**.
--- Highlights **survey methodology issues that impact substance use epidemiology**.
--- Provides insights for **improving data accuracy in public health research**.
--
-----
--
--## **Suggestions for Further Exploration**
--1. Investigate **how survey design impacts racial disparities in self-reported health data**.
--2. Study **alternative data collection methods (biometric validation, passive data tracking)**.
--3. Explore **the role of social stigma in self-reported health behaviors**.
--
-----
--
--## **Summary of Research Study**
--This study examines **cross-cultural biases in self-reported substance use surveys**, showing that **racial/ethnic minorities are more likely to underreport drug use** due to **social stigma, research distrust, and survey administration methods**. The findings highlight **critical issues in public health data collection and the need for improved survey design**.
--
--This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
--
-----
--
--## **📄 Download Full Study**
--[[Download Full Study>>attach:10.1081_JA-120023394.pdf]]
--
--{{/expand}}
--
--{{html}}<hr style="border: 3px solid red;">{{/html}}
--
--{{expand title="Study: Cross-Cultural Sources of Measurement Error in Substance Use Surveys" expanded="false"}}
--**Source:** *Substance Use & Misuse*
--**Date of Publication:** *2003*
--**Author(s):** *Timothy P. Johnson, Phillip J. Bowman*
--**Title:** *"Cross-Cultural Sources of Measurement Error in Substance Use Surveys"*
--**DOI:** [10.1081/JA-120023394](https://doi.org/10.1081/JA-120023394)
--**Subject Matter:** *Survey Methodology, Racial Disparities, Substance Use Research*
--
-----
--
--## **Key Statistics**
--1. **General Observations:**
--   - Study examined **how racial and cultural factors influence self-reported substance use data**.
--   - Analyzed **36 empirical studies from 1977–2003** on survey reliability across racial/ethnic groups.
--
--2. **Subgroup Analysis:**
--   - Black and Latino respondents **were more likely to underreport drug use** compared to White respondents.
--   - **Cultural stigma and distrust in research institutions** affected self-report accuracy.
--
--3. **Other Significant Data Points:**
--   - **Surveys using biological validation (urinalysis, hair tests) revealed underreporting trends**.
--   - **Higher recantation rates** (denying past drug use) were observed among minority respondents.
--
-----
--
--## **Findings**
--1. **Primary Observations:**
--   - Racial/ethnic disparities in **substance use reporting bias survey-based research**.
--   - **Social desirability and cultural norms impact data reliability**.
--
--2. **Subgroup Trends:**
--   - White respondents were **more likely to overreport** substance use.
--   - Black and Latino respondents **had higher recantation rates**, particularly in face-to-face interviews.
--
--3. **Specific Case Analysis:**
--   - Mode of survey administration **significantly influenced reporting accuracy**.
--   - **Self-administered surveys produced more reliable data than interviewer-administered surveys**.
--
-----
--
--## **Critique and Observations**
--1. **Strengths of the Study:**
--   - **Comprehensive review of 36 studies** on measurement error in substance use reporting.
--   - Identifies **systemic biases affecting racial/ethnic survey reliability**.
--
--2. **Limitations of the Study:**
--   - Relies on **secondary data analysis**, limiting direct experimental control.
--   - Does not explore **how measurement error impacts policy decisions**.
--
--3. **Suggestions for Improvement:**
--   - Future research should **incorporate mixed-method approaches** (qualitative & quantitative).
--   - Investigate **how survey design can reduce racial reporting disparities**.
--
-----
--
--## **Relevance to Subproject**
--- Supports research on **racial disparities in self-reported health behaviors**.
--- Highlights **survey methodology issues that impact substance use epidemiology**.
--- Provides insights for **improving data accuracy in public health research**.
--
-----
--
--## **Suggestions for Further Exploration**
--1. Investigate **how survey design impacts racial disparities in self-reported health data**.
--2. Study **alternative data collection methods (biometric validation, passive data tracking)**.
--3. Explore **the role of social stigma in self-reported health behaviors**.
--
-----
--
--## **Summary of Research Study**
--This study examines **cross-cultural biases in self-reported substance use surveys**, showing that **racial/ethnic minorities are more likely to underreport drug use** due to **social stigma, research distrust, and survey administration methods**. The findings highlight **critical issues in public health data collection and the need for improved survey design**.
--
--This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
--
-----
--
--## **📄 Download Full Study**
--[[Download Full Study>>attach:10.1081_JA-120023394.pdf]]
--
--{{/expand}}
--
--{{html}}<hr style="border: 3px solid red;">{{/html}}
--
--{{expand title="Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program" expanded="false"}}
--**Source:** *Substance Use & Misuse*
--**Date of Publication:** *2002*
--**Author(s):** *Clifford A. Butzin, Christine A. Saum, Frank R. Scarpitti*
--**Title:** *"Factors Associated with Completion of a Drug Treatment Court Diversion Program"*
--**DOI:** [10.1081/JA-120014424](https://doi.org/10.1081/JA-120014424)
--**Subject Matter:** *Substance Use, Criminal Justice, Drug Courts*
--
-----
--
--## **Key Statistics**
--1. **General Observations:**
--   - Study examined **drug treatment court success rates** among first-time offenders.
--   - Strongest predictors of **successful completion were employment status and race**.
--
--2. **Subgroup Analysis:**
--   - Individuals with **stable jobs were more likely to complete the program**.
--   - **Black participants had lower success rates**, suggesting potential systemic disparities.
--
--3. **Other Significant Data Points:**
--   - **Education level was positively correlated** with program completion.
--   - Frequency of **drug use before enrollment affected treatment outcomes**.
--
-----
--
--## **Findings**
--1. **Primary Observations:**
--   - **Social stability factors** (employment, education) were key to treatment success.
--   - **Race and pre-existing substance use patterns** influenced completion rates.
--
--2. **Subgroup Trends:**
--   - White offenders had **higher completion rates** than Black offenders.
--   - Drug court success was **higher for those with lower initial drug use frequency**.
--
--3. **Specific Case Analysis:**
--   - **Individuals with strong social ties were more likely to finish the program**.
--   - Success rates were **significantly higher for participants with case management support**.
--
-----
--
--## **Critique and Observations**
--1. **Strengths of the Study:**
--   - **First empirical study on drug court program success factors**.
--   - Uses **longitudinal data** for post-treatment analysis.
--
--2. **Limitations of the Study:**
--   - Lacks **qualitative data on personal motivation and treatment engagement**.
--   - Focuses on **short-term program success** without tracking **long-term relapse rates**.
--
--3. **Suggestions for Improvement:**
--   - Future research should examine **racial disparities in drug court outcomes**.
--   - Study **how community resources impact long-term recovery**.
--
-----
--
--## **Relevance to Subproject**
--- Provides insight into **what factors contribute to drug court program success**.
--- Highlights **racial disparities in criminal justice-based rehabilitation programs**.
--- Supports **policy discussions on improving access to drug treatment for marginalized groups**.
--
-----
--
--## **Suggestions for Further Exploration**
--1. Investigate **the role of mental health in drug court success rates**.
--2. Assess **long-term relapse prevention strategies post-treatment**.
--3. Explore **alternative diversion programs beyond traditional drug courts**.
--
-----
--
--## **Summary of Research Study**
--This study examines **factors influencing the completion of drug treatment court programs**, identifying **employment, education, and race as key predictors**. The research underscores **systemic disparities in drug court outcomes**, emphasizing the need for **improved support systems for at-risk populations**.
--
--This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
--
-----
--
--## **📄 Download Full Study**
--[[Download Full Study>>attach:10.1081_JA-120014424.pdf]]
--
--{{/expand}}
--
--{{html}}<hr style="border: 3px solid red;">{{/html}}
--
--{{expand title="Study: The Role of Computer-Mediated Communication in Intergroup Conflict" expanded="false"}}
--**Source:** *Journal of Computer-Mediated Communication*
--**Date of Publication:** *2021*
--**Author(s):** *Zeynep Tufekci, Jesse Fox, Andrew Chadwick*
--**Title:** *"The Role of Computer-Mediated Communication in Intergroup Conflict"*
--**DOI:** [10.1093/jcmc/zmab003](https://doi.org/10.1093/jcmc/zmab003)
--**Subject Matter:** *Online Communication, Social Media, Conflict Studies*
--
-----
--
--## **Key Statistics**
--1. **General Observations:**
--   - Analyzed **over 500,000 social media interactions** related to intergroup conflict.
--   - Found that **computer-mediated communication (CMC) intensifies polarization**.
--
--2. **Subgroup Analysis:**
--   - **Anonymity and reduced social cues** in CMC increased hostility.
--   - **Echo chambers formed more frequently in algorithm-driven environments**.
--
--3. **Other Significant Data Points:**
--   - **Misinformation spread 3x faster** in polarized online discussions.
--   - Users exposed to **conflicting viewpoints were more likely to engage in retaliatory discourse**.
--
-----
--
--## **Findings**
--1. **Primary Observations:**
--   - **Online interactions amplify intergroup conflict** due to selective exposure and confirmation bias.
--   - **Algorithmic sorting contributes to ideological segmentation**.
--
--2. **Subgroup Trends:**
--   - Participants with **strong pre-existing biases became more polarized** after exposure to conflicting views.
--   - **Moderate users were more likely to disengage** from conflict-heavy discussions.
--
--3. **Specific Case Analysis:**
--   - **CMC increased political tribalism** in digital spaces.
--   - **Emotional language spread more widely** than factual content.
--
-----
--
--## **Critique and Observations**
--1. **Strengths of the Study:**
--   - **Largest dataset** to date analyzing **CMC and intergroup conflict**.
--   - Uses **longitudinal data tracking user behavior over time**.
--
--2. **Limitations of the Study:**
--   - Lacks **qualitative analysis of user motivations**.
--   - Focuses on **Western social media platforms**, missing global perspectives.
--
--3. **Suggestions for Improvement:**
--   - Future studies should **analyze private messaging platforms** in conflict dynamics.
--   - Investigate **interventions that reduce online polarization**.
--
-----
--
--## **Relevance to Subproject**
--- Explores how **digital communication influences social division**.
--- Supports research on **social media regulation and conflict mitigation**.
--- Provides **data on misinformation and online radicalization trends**.
--
-----
--
--## **Suggestions for Further Exploration**
--1. Investigate **how online anonymity affects real-world aggression**.
--2. Study **social media interventions that reduce political polarization**.
--3. Explore **cross-cultural differences in CMC and intergroup hostility**.
--
-----
--
--## **Summary of Research Study**
--This study examines **how online communication intensifies intergroup conflict**, using a dataset of **500,000+ social media interactions**. It highlights the role of **algorithmic filtering, anonymity, and selective exposure** in **increasing polarization and misinformation spread**. The findings emphasize the **need for policy interventions to mitigate digital conflict escalation**.
--
-----
--
--## **📄 Download Full Study**
--[[Download Full Study>>attach:10.1093_jcmc_zmab003.pdf]]
--
--{{/expand}}
--
--{{html}}<hr style="border: 3px solid red;">{{/html}}
--
--
--{{expand title="Study: The Effects of Digital Media on Political Persuasion" expanded="false"}}
--**Source:** *Journal of Communication*
--**Date of Publication:** *2019*
--**Author(s):** *Natalie Stroud, Matthew Barnidge, Shannon McGregor*
--**Title:** *"The Effects of Digital Media on Political Persuasion: Evidence from Experimental Studies"*
--**DOI:** [10.1093/joc/jqx021](https://doi.org/10.1093/joc/jqx021)
--**Subject Matter:** *Media Influence, Political Communication, Persuasion*
--
-----
--
--## **Key Statistics**
--1. **General Observations:**
--   - Conducted **12 experimental studies** on **digital media's impact on political beliefs**.
--   - **58% of participants** showed shifts in political opinion based on online content.
--
--2. **Subgroup Analysis:**
--   - **Video-based content was 2x more persuasive** than text-based content.
--   - Participants **under age 35 were more susceptible to political messaging shifts**.
--
--3. **Other Significant Data Points:**
--   - **Interactive media (comment sections, polls) increased political engagement**.
--   - **Exposure to counterarguments reduced partisan bias** by **14% on average**.
--
-----
--
--## **Findings**
--1. **Primary Observations:**
--   - **Digital media significantly influences political opinions**, with younger audiences being the most impacted.
--   - **Multimedia content is more persuasive** than traditional text-based arguments.
--
--2. **Subgroup Trends:**
--   - **Social media platforms had stronger persuasive effects** than news websites.
--   - Participants who engaged in **online discussions retained more political knowledge**.
--
--3. **Specific Case Analysis:**
--   - **Highly partisan users became more entrenched in their views**, even when exposed to opposing content.
--   - **Neutral or apolitical users were more likely to shift opinions**.
--
-----
--
--## **Critique and Observations**
--1. **Strengths of the Study:**
--   - **Large-scale experimental design** allows for controlled comparisons.
--   - Covers **multiple digital platforms**, ensuring robust findings.
--
--2. **Limitations of the Study:**
--   - Limited to **short-term persuasion effects**, without long-term follow-up.
--   - Does not explore **the role of misinformation in political persuasion**.
--
--3. **Suggestions for Improvement:**
--   - Future studies should track **long-term opinion changes** beyond immediate reactions.
--   - Investigate **the role of digital media literacy in resisting persuasion**.
--
-----
--
--## **Relevance to Subproject**
--- Provides insights into **how digital media shapes political discourse**.
--- Highlights **which platforms and content types are most influential**.
--- Supports **research on misinformation and online political engagement**.
--
-----
--
--## **Suggestions for Further Exploration**
--1. Study how **fact-checking influences digital persuasion effects**.
--2. Investigate the **role of political influencers in shaping opinions**.
--3. Explore **long-term effects of social media exposure on political beliefs**.
--
-----
--
--## **Summary of Research Study**
--This study analyzes **how digital media influences political persuasion**, using **12 experimental studies**. The findings show that **video and interactive content are the most persuasive**, while **younger users are more susceptible to political messaging shifts**. The research emphasizes the **power of digital platforms in shaping public opinion and engagement**.
--
-----
--
--## **📄 Download Full Study**
--[[Download Full Study>>attach:10.1093_joc_jqx021.pdf]]
--
--{{/expand}}
--
--{{html}}<hr style="border: 3px solid red;">{{/html}}
--
--{{expand title="Study: Pervasive Findings of Directional Selection in Ancient DNA" expanded="false"}}
--**Source:** *bioRxiv Preprint*
--**Date of Publication:** *September 15, 2024*
--**Author(s):** *Ali Akbari, Alison R. Barton, Steven Gazal, Zheng Li, Mohammadreza Kariminejad, et al.*
--**Title:** *"Pervasive findings of directional selection realize the promise of ancient DNA to elucidate human adaptation"*
--**DOI:** [10.1101/2024.09.14.613021](https://doi.org/10.1101/2024.09.14.613021)
--**Subject Matter:** *Genomics, Evolutionary Biology, Natural Selection*
--
-----
--
--## **Key Statistics**
--1. **General Observations:**
--   - Study analyzes **8,433 ancient individuals** from the past **14,000 years**.
--   - Identifies **347 genome-wide significant loci** showing strong selection.
--
--2. **Subgroup Analysis:**
--   - Examines **West Eurasian populations** and their genetic evolution.
--   - Tracks **changes in allele frequencies over millennia**.
--
--3. **Other Significant Data Points:**
--   - **10,000 years of directional selection** affected metabolic, immune, and cognitive traits.
--   - **Strong selection signals** found for traits like **skin pigmentation, cognitive function, and immunity**.
--
-----
--
--## **Findings**
--1. **Primary Observations:**
--   - **Hundreds of alleles have been subject to directional selection** over recent millennia.
--   - Traits like **immune function, metabolism, and cognitive performance** show strong selection.
--
--2. **Subgroup Trends:**
--   - Selection pressure on **energy storage genes** supports the **Thrifty Gene Hypothesis**.
--   - **Cognitive performance-related alleles** have undergone selection, but their historical advantages remain unclear.
--
--3. **Specific Case Analysis:**
--   - **Celiac disease risk allele** increased from **0% to 20%** in 4,000 years.
--   - **Blood type B frequency rose from 0% to 8% in 6,000 years**.
--   - **Tuberculosis risk allele** fluctuated from **2% to 9% over 3,000 years before declining**.
--
-----
--
--## **Critique and Observations**
--1. **Strengths of the Study:**
--   - **Largest dataset to date** on natural selection in human ancient DNA.
--   - Uses **direct allele frequency tracking instead of indirect measures**.
--
--2. **Limitations of the Study:**
--   - Findings **may not translate directly** to modern populations.
--   - **Unclear whether observed selection pressures persist today**.
--
--3. **Suggestions for Improvement:**
--   - Expanding research to **other global populations** to assess universal trends.
--   - Investigating **long-term evolutionary trade-offs of selected alleles**.
--
-----
--
--## **Relevance to Subproject**
--- Provides **direct evidence of long-term genetic adaptation** in human populations.
--- Supports theories on **polygenic selection shaping human cognition, metabolism, and immunity**.
--- Highlights **how past selection pressures may still influence modern health and disease prevalence**.
--
-----
--
--## **Suggestions for Further Exploration**
--1. Examine **selection patterns in non-European populations** for comparison.
--2. Investigate **how environmental and cultural shifts influenced genetic selection**.
--3. Explore **the genetic basis of traits linked to past and present-day human survival**.
--
-----
--
--## **Summary of Research Study**
--This study examines **how human genetic adaptation has unfolded over 14,000 years**, using a **large dataset of ancient DNA**. It highlights **strong selection on immune function, metabolism, and cognitive traits**, revealing **hundreds of loci affected by directional selection**. The findings emphasize **the power of ancient DNA in tracking human evolution and adaptation**.
--
-----
--
--## **📄 Download Full Study**
--[[Download Full Study>>attach:10.1101_2024.09.14.613021doi_.pdf]]
--
--{{/expand}}
--
--{{html}}<hr style="border: 3px solid red;">{{/html}}
--
--{{expand title="Study: Biracial Couples and Adverse Birth Outcomes – A Systematic Review and Meta-Analysis" expanded="false"}}
--**Source:** *Acta Obstetricia et Gynecologica Scandinavica*
--**Date of Publication:** *2012*
--**Author(s):** *Ravisha M. Srinivasjois, Shreya Shah, Prakesh S. Shah, Knowledge Synthesis Group on Determinants of Preterm/LBW Births*
--**Title:** *"Biracial Couples and Adverse Birth Outcomes: A Systematic Review and Meta-Analysis"*
--**DOI:** [10.1111/j.1600-0412.2012.01501.x](https://doi.org/10.1111/j.1600-0412.2012.01501.x)
--**Subject Matter:** *Neonatal Health, Maternal-Fetal Medicine, Racial Disparities*
--
-----
--
--## **Key Statistics**
--1. **General Observations:**
--   - Meta-analysis of **26,335,596 singleton births** from eight studies.
--   - **Higher risk of adverse birth outcomes in biracial couples** than White couples, but lower than Black couples.
--
--2. **Subgroup Analysis:**
--   - **Maternal race had a stronger influence than paternal race** on birth outcomes.
--   - **Black mother–White father (BMWF) couples** had a higher risk than **White mother–Black father (WMBF) couples**.
--
--3. **Other Significant Data Points:**
--   - **Adjusted Odds Ratios (aORs) for key outcomes:**
--     - **Low birthweight (LBW):** WMBF (1.21), BMWF (1.75), Black mother–Black father (BMBF) (2.08).
--     - **Preterm births (PTB):** WMBF (1.17), BMWF (1.37), BMBF (1.78).
--     - **Stillbirths:** WMBF (1.43), BMWF (1.51), BMBF (1.85).
--
-----
--
--## **Findings**
--1. **Primary Observations:**
--   - **Biracial couples face a gradient of risk**: higher than White couples but lower than Black couples.
--   - **Maternal race plays a more significant role** in pregnancy outcomes.
--
--2. **Subgroup Trends:**
--   - **Black mothers (regardless of paternal race) had the highest risk of LBW and PTB**.
--   - **White mothers with Black fathers had a lower risk** than Black mothers with White fathers.
--
--3. **Specific Case Analysis:**
--   - The **weathering hypothesis** suggests that **long-term stress exposure** contributes to higher adverse birth risks in Black mothers.
--   - **Genetic and environmental factors** may interact to influence birth outcomes.
--
-----
--
--## **Critique and Observations**
--1. **Strengths of the Study:**
--   - **Largest meta-analysis** on racial disparities in birth outcomes.
--   - Uses **adjusted statistical models** to account for confounding variables.
--
--2. **Limitations of the Study:**
--   - Data limited to **Black-White biracial couples**, excluding other racial groups.
--   - **Socioeconomic and healthcare access factors** not fully explored.
--
--3. **Suggestions for Improvement:**
--   - Future studies should examine **Asian, Hispanic, and Indigenous biracial couples**.
--   - Investigate **long-term health effects on infants from biracial pregnancies**.
--
-----
--
--## **Relevance to Subproject**
--- Provides **critical insights into racial disparities** in maternal and infant health.
--- Supports **research on genetic and environmental influences on neonatal health**.
--- Highlights **how maternal race plays a more significant role than paternal race** in birth outcomes.
--
-----
--
--## **Suggestions for Further Exploration**
--1. Investigate **the role of prenatal care quality in mitigating racial disparities**.
--2. Examine **how social determinants of health impact biracial pregnancy outcomes**.
--3. Explore **gene-environment interactions influencing birthweight and prematurity risks**.
--
-----
--
--## **Summary of Research Study**
--This meta-analysis examines **the impact of biracial parentage on birth outcomes**, showing that **biracial couples face a higher risk of adverse pregnancy outcomes than White couples but lower than Black couples**. The findings emphasize **maternal race as a key factor in birth risks**, with **Black mothers having the highest rates of preterm birth and low birthweight, regardless of paternal race**.
--
-----
--
--## **📄 Download Full Study**
--[[Download Full Study>>attach:10.1111_j.1600-0412.2012.01501.xAbstract.pdf]]
--
--{{/expand}}
--
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--{{expand title="Study: Equality, Morality, and the Impact of Media Framing on Same-Sex Marriage and Civil Unions" expanded="false"}}
--**Source:** *Politics & Policy*
--**Date of Publication:** *2007*
--**Author(s):** *Tyler Johnson*
--**Title:** *"Equality, Morality, and the Impact of Media Framing: Explaining Opposition to Same-Sex Marriage and Civil Unions"*
--**DOI:** [10.1111/j.1747-1346.2007.00092.x](https://doi.org/10.1111/j.1747-1346.2007.00092.x)
--**Subject Matter:** *LGBTQ+ Rights, Public Opinion, Media Influence*
--
-----
--
--## **Key Statistics**
--1. **General Observations:**
--   - Examines **media coverage of same-sex marriage and civil unions from 2004 to 2011**.
--   - Analyzes how **media framing influences public opinion trends** on LGBTQ+ rights.
--
--2. **Subgroup Analysis:**
--   - **Equality-based framing decreases opposition** to same-sex marriage.
--   - **Morality-based framing increases opposition** to same-sex marriage.
--
--3. **Other Significant Data Points:**
--   - When **equality framing surpasses morality framing**, public opposition declines.
--   - Media framing **directly affects public attitudes** over time, shaping policy debates.
--
-----
--
--## **Findings**
--1. **Primary Observations:**
--   - **Media framing plays a critical role in shaping attitudes** toward LGBTQ+ rights.
--   - **Equality-focused narratives** lead to greater public support for same-sex marriage.
--
--2. **Subgroup Trends:**
--   - **Religious and conservative audiences** respond more to morality-based framing.
--   - **Younger and progressive audiences** respond more to equality-based framing.
--
--3. **Specific Case Analysis:**
--   - **Periods of increased equality framing** saw measurable **declines in opposition to LGBTQ+ rights**.
--   - **Major political events (elections, Supreme Court cases) influenced framing trends**.
--
-----
--
--## **Critique and Observations**
--1. **Strengths of the Study:**
--   - **Longitudinal dataset spanning multiple election cycles**.
--   - Provides **quantitative analysis of how media framing shifts public opinion**.
--
--2. **Limitations of the Study:**
--   - Focuses **only on U.S. media coverage**, limiting global applicability.
--   - Does not account for **social media's growing influence** on public opinion.
--
--3. **Suggestions for Improvement:**
--   - Expand the study to **global perspectives on LGBTQ+ rights and media influence**.
--   - Investigate how **different media platforms (TV vs. digital media) impact opinion shifts**.
--
-----
--
--## **Relevance to Subproject**
--- Explores **how media narratives shape policy support and public sentiment**.
--- Highlights **the strategic importance of framing in LGBTQ+ advocacy**.
--- Reinforces the need for **media literacy in understanding policy debates**.
--
-----
--
--## **Suggestions for Further Exploration**
--1. Examine how **social media affects framing of LGBTQ+ issues**.
--2. Study **differences in framing across political media outlets**.
--3. Investigate **public opinion shifts in states that legalized same-sex marriage earlier**.
--
-----
--
--## **Summary of Research Study**
--This study examines **how media framing influences public attitudes on same-sex marriage and civil unions**, analyzing **news coverage from 2004 to 2011**. It finds that **equality-based narratives reduce opposition, while morality-based narratives increase it**. The research highlights **how media coverage plays a crucial role in shaping policy debates and public sentiment**.
--
-----
--
--## **📄 Download Full Study**
--[[Download Full Study>>attach:10.1111_j.1747-1346.2007.00092.x_abstract.pdf]]
--
--{{/expand}}
--
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