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... ... @@ -11,8 +11,8 @@
11 11  - Use the **search function** (Ctrl + F or XWiki's built-in search) to quickly find specific topics or authors.
12 12  - If needed, you can export this page as **PDF or print-friendly format**, and all studies will automatically expand for readability.
13 13  
14 +{{toc/}}
14 14  
15 -
16 16  == Research Studies Repository ==
17 17  
18 18  
... ... @@ -1455,745 +1455,4 @@
1455 1455  
1456 1456  {{html}}<hr style="border: 3px solid red;">{{/html}}
1457 1457  
1458 -{{expand title="Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program" expanded="false"}}
1459 -**Source:** *Substance Use & Misuse*
1460 -**Date of Publication:** *2002*
1461 -**Author(s):** *Clifford A. Butzin, Christine A. Saum, Frank R. Scarpitti*
1462 -**Title:** *"Factors Associated with Completion of a Drug Treatment Court Diversion Program"*
1463 -**DOI:** [10.1081/JA-120014424](https://doi.org/10.1081/JA-120014424)
1464 -**Subject Matter:** *Substance Use, Criminal Justice, Drug Courts*
1465 1465  
1466 ----
1467 -
1468 -## **Key Statistics**
1469 -1. **General Observations:**
1470 - - Study examined **drug treatment court success rates** among first-time offenders.
1471 - - Strongest predictors of **successful completion were employment status and race**.
1472 -
1473 -2. **Subgroup Analysis:**
1474 - - Individuals with **stable jobs were more likely to complete the program**.
1475 - - **Black participants had lower success rates**, suggesting potential systemic disparities.
1476 -
1477 -3. **Other Significant Data Points:**
1478 - - **Education level was positively correlated** with program completion.
1479 - - Frequency of **drug use before enrollment affected treatment outcomes**.
1480 -
1481 ----
1482 -
1483 -## **Findings**
1484 -1. **Primary Observations:**
1485 - - **Social stability factors** (employment, education) were key to treatment success.
1486 - - **Race and pre-existing substance use patterns** influenced completion rates.
1487 -
1488 -2. **Subgroup Trends:**
1489 - - White offenders had **higher completion rates** than Black offenders.
1490 - - Drug court success was **higher for those with lower initial drug use frequency**.
1491 -
1492 -3. **Specific Case Analysis:**
1493 - - **Individuals with strong social ties were more likely to finish the program**.
1494 - - Success rates were **significantly higher for participants with case management support**.
1495 -
1496 ----
1497 -
1498 -## **Critique and Observations**
1499 -1. **Strengths of the Study:**
1500 - - **First empirical study on drug court program success factors**.
1501 - - Uses **longitudinal data** for post-treatment analysis.
1502 -
1503 -2. **Limitations of the Study:**
1504 - - Lacks **qualitative data on personal motivation and treatment engagement**.
1505 - - Focuses on **short-term program success** without tracking **long-term relapse rates**.
1506 -
1507 -3. **Suggestions for Improvement:**
1508 - - Future research should examine **racial disparities in drug court outcomes**.
1509 - - Study **how community resources impact long-term recovery**.
1510 -
1511 ----
1512 -
1513 -## **Relevance to Subproject**
1514 -- Provides insight into **what factors contribute to drug court program success**.
1515 -- Highlights **racial disparities in criminal justice-based rehabilitation programs**.
1516 -- Supports **policy discussions on improving access to drug treatment for marginalized groups**.
1517 -
1518 ----
1519 -
1520 -## **Suggestions for Further Exploration**
1521 -1. Investigate **the role of mental health in drug court success rates**.
1522 -2. Assess **long-term relapse prevention strategies post-treatment**.
1523 -3. Explore **alternative diversion programs beyond traditional drug courts**.
1524 -
1525 ----
1526 -
1527 -## **Summary of Research Study**
1528 -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**.
1529 -
1530 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1531 -
1532 ----
1533 -
1534 -## **📄 Download Full Study**
1535 -[[Download Full Study>>attach:10.1081_JA-120014424.pdf]]
1536 -
1537 -{{/expand}}
1538 -
1539 -{{html}}<hr style="border: 3px solid red;">{{/html}}
1540 -
1541 -
1542 -{{expand title="Study: Cross-Cultural Sources of Measurement Error in Substance Use Surveys" expanded="false"}}
1543 -**Source:** *Substance Use & Misuse*
1544 -**Date of Publication:** *2003*
1545 -**Author(s):** *Timothy P. Johnson, Phillip J. Bowman*
1546 -**Title:** *"Cross-Cultural Sources of Measurement Error in Substance Use Surveys"*
1547 -**DOI:** [10.1081/JA-120023394](https://doi.org/10.1081/JA-120023394)
1548 -**Subject Matter:** *Survey Methodology, Racial Disparities, Substance Use Research*
1549 -
1550 ----
1551 -
1552 -## **Key Statistics**
1553 -1. **General Observations:**
1554 - - Study examined **how racial and cultural factors influence self-reported substance use data**.
1555 - - Analyzed **36 empirical studies from 1977–2003** on survey reliability across racial/ethnic groups.
1556 -
1557 -2. **Subgroup Analysis:**
1558 - - Black and Latino respondents **were more likely to underreport drug use** compared to White respondents.
1559 - - **Cultural stigma and distrust in research institutions** affected self-report accuracy.
1560 -
1561 -3. **Other Significant Data Points:**
1562 - - **Surveys using biological validation (urinalysis, hair tests) revealed underreporting trends**.
1563 - - **Higher recantation rates** (denying past drug use) were observed among minority respondents.
1564 -
1565 ----
1566 -
1567 -## **Findings**
1568 -1. **Primary Observations:**
1569 - - Racial/ethnic disparities in **substance use reporting bias survey-based research**.
1570 - - **Social desirability and cultural norms impact data reliability**.
1571 -
1572 -2. **Subgroup Trends:**
1573 - - White respondents were **more likely to overreport** substance use.
1574 - - Black and Latino respondents **had higher recantation rates**, particularly in face-to-face interviews.
1575 -
1576 -3. **Specific Case Analysis:**
1577 - - Mode of survey administration **significantly influenced reporting accuracy**.
1578 - - **Self-administered surveys produced more reliable data than interviewer-administered surveys**.
1579 -
1580 ----
1581 -
1582 -## **Critique and Observations**
1583 -1. **Strengths of the Study:**
1584 - - **Comprehensive review of 36 studies** on measurement error in substance use reporting.
1585 - - Identifies **systemic biases affecting racial/ethnic survey reliability**.
1586 -
1587 -2. **Limitations of the Study:**
1588 - - Relies on **secondary data analysis**, limiting direct experimental control.
1589 - - Does not explore **how measurement error impacts policy decisions**.
1590 -
1591 -3. **Suggestions for Improvement:**
1592 - - Future research should **incorporate mixed-method approaches** (qualitative & quantitative).
1593 - - Investigate **how survey design can reduce racial reporting disparities**.
1594 -
1595 ----
1596 -
1597 -## **Relevance to Subproject**
1598 -- Supports research on **racial disparities in self-reported health behaviors**.
1599 -- Highlights **survey methodology issues that impact substance use epidemiology**.
1600 -- Provides insights for **improving data accuracy in public health research**.
1601 -
1602 ----
1603 -
1604 -## **Suggestions for Further Exploration**
1605 -1. Investigate **how survey design impacts racial disparities in self-reported health data**.
1606 -2. Study **alternative data collection methods (biometric validation, passive data tracking)**.
1607 -3. Explore **the role of social stigma in self-reported health behaviors**.
1608 -
1609 ----
1610 -
1611 -## **Summary of Research Study**
1612 -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**.
1613 -
1614 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1615 -
1616 ----
1617 -
1618 -## **📄 Download Full Study**
1619 -[[Download Full Study>>attach:10.1081_JA-120023394.pdf]]
1620 -
1621 -{{/expand}}
1622 -
1623 -{{html}}<hr style="border: 3px solid red;">{{/html}}
1624 -
1625 -{{expand title="Study: Cross-Cultural Sources of Measurement Error in Substance Use Surveys" expanded="false"}}
1626 -**Source:** *Substance Use & Misuse*
1627 -**Date of Publication:** *2003*
1628 -**Author(s):** *Timothy P. Johnson, Phillip J. Bowman*
1629 -**Title:** *"Cross-Cultural Sources of Measurement Error in Substance Use Surveys"*
1630 -**DOI:** [10.1081/JA-120023394](https://doi.org/10.1081/JA-120023394)
1631 -**Subject Matter:** *Survey Methodology, Racial Disparities, Substance Use Research*
1632 -
1633 ----
1634 -
1635 -## **Key Statistics**
1636 -1. **General Observations:**
1637 - - Study examined **how racial and cultural factors influence self-reported substance use data**.
1638 - - Analyzed **36 empirical studies from 1977–2003** on survey reliability across racial/ethnic groups.
1639 -
1640 -2. **Subgroup Analysis:**
1641 - - Black and Latino respondents **were more likely to underreport drug use** compared to White respondents.
1642 - - **Cultural stigma and distrust in research institutions** affected self-report accuracy.
1643 -
1644 -3. **Other Significant Data Points:**
1645 - - **Surveys using biological validation (urinalysis, hair tests) revealed underreporting trends**.
1646 - - **Higher recantation rates** (denying past drug use) were observed among minority respondents.
1647 -
1648 ----
1649 -
1650 -## **Findings**
1651 -1. **Primary Observations:**
1652 - - Racial/ethnic disparities in **substance use reporting bias survey-based research**.
1653 - - **Social desirability and cultural norms impact data reliability**.
1654 -
1655 -2. **Subgroup Trends:**
1656 - - White respondents were **more likely to overreport** substance use.
1657 - - Black and Latino respondents **had higher recantation rates**, particularly in face-to-face interviews.
1658 -
1659 -3. **Specific Case Analysis:**
1660 - - Mode of survey administration **significantly influenced reporting accuracy**.
1661 - - **Self-administered surveys produced more reliable data than interviewer-administered surveys**.
1662 -
1663 ----
1664 -
1665 -## **Critique and Observations**
1666 -1. **Strengths of the Study:**
1667 - - **Comprehensive review of 36 studies** on measurement error in substance use reporting.
1668 - - Identifies **systemic biases affecting racial/ethnic survey reliability**.
1669 -
1670 -2. **Limitations of the Study:**
1671 - - Relies on **secondary data analysis**, limiting direct experimental control.
1672 - - Does not explore **how measurement error impacts policy decisions**.
1673 -
1674 -3. **Suggestions for Improvement:**
1675 - - Future research should **incorporate mixed-method approaches** (qualitative & quantitative).
1676 - - Investigate **how survey design can reduce racial reporting disparities**.
1677 -
1678 ----
1679 -
1680 -## **Relevance to Subproject**
1681 -- Supports research on **racial disparities in self-reported health behaviors**.
1682 -- Highlights **survey methodology issues that impact substance use epidemiology**.
1683 -- Provides insights for **improving data accuracy in public health research**.
1684 -
1685 ----
1686 -
1687 -## **Suggestions for Further Exploration**
1688 -1. Investigate **how survey design impacts racial disparities in self-reported health data**.
1689 -2. Study **alternative data collection methods (biometric validation, passive data tracking)**.
1690 -3. Explore **the role of social stigma in self-reported health behaviors**.
1691 -
1692 ----
1693 -
1694 -## **Summary of Research Study**
1695 -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**.
1696 -
1697 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1698 -
1699 ----
1700 -
1701 -## **📄 Download Full Study**
1702 -[[Download Full Study>>attach:10.1081_JA-120023394.pdf]]
1703 -
1704 -{{/expand}}
1705 -
1706 -{{html}}<hr style="border: 3px solid red;">{{/html}}
1707 -
1708 -{{expand title="Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program" expanded="false"}}
1709 -**Source:** *Substance Use & Misuse*
1710 -**Date of Publication:** *2002*
1711 -**Author(s):** *Clifford A. Butzin, Christine A. Saum, Frank R. Scarpitti*
1712 -**Title:** *"Factors Associated with Completion of a Drug Treatment Court Diversion Program"*
1713 -**DOI:** [10.1081/JA-120014424](https://doi.org/10.1081/JA-120014424)
1714 -**Subject Matter:** *Substance Use, Criminal Justice, Drug Courts*
1715 -
1716 ----
1717 -
1718 -## **Key Statistics**
1719 -1. **General Observations:**
1720 - - Study examined **drug treatment court success rates** among first-time offenders.
1721 - - Strongest predictors of **successful completion were employment status and race**.
1722 -
1723 -2. **Subgroup Analysis:**
1724 - - Individuals with **stable jobs were more likely to complete the program**.
1725 - - **Black participants had lower success rates**, suggesting potential systemic disparities.
1726 -
1727 -3. **Other Significant Data Points:**
1728 - - **Education level was positively correlated** with program completion.
1729 - - Frequency of **drug use before enrollment affected treatment outcomes**.
1730 -
1731 ----
1732 -
1733 -## **Findings**
1734 -1. **Primary Observations:**
1735 - - **Social stability factors** (employment, education) were key to treatment success.
1736 - - **Race and pre-existing substance use patterns** influenced completion rates.
1737 -
1738 -2. **Subgroup Trends:**
1739 - - White offenders had **higher completion rates** than Black offenders.
1740 - - Drug court success was **higher for those with lower initial drug use frequency**.
1741 -
1742 -3. **Specific Case Analysis:**
1743 - - **Individuals with strong social ties were more likely to finish the program**.
1744 - - Success rates were **significantly higher for participants with case management support**.
1745 -
1746 ----
1747 -
1748 -## **Critique and Observations**
1749 -1. **Strengths of the Study:**
1750 - - **First empirical study on drug court program success factors**.
1751 - - Uses **longitudinal data** for post-treatment analysis.
1752 -
1753 -2. **Limitations of the Study:**
1754 - - Lacks **qualitative data on personal motivation and treatment engagement**.
1755 - - Focuses on **short-term program success** without tracking **long-term relapse rates**.
1756 -
1757 -3. **Suggestions for Improvement:**
1758 - - Future research should examine **racial disparities in drug court outcomes**.
1759 - - Study **how community resources impact long-term recovery**.
1760 -
1761 ----
1762 -
1763 -## **Relevance to Subproject**
1764 -- Provides insight into **what factors contribute to drug court program success**.
1765 -- Highlights **racial disparities in criminal justice-based rehabilitation programs**.
1766 -- Supports **policy discussions on improving access to drug treatment for marginalized groups**.
1767 -
1768 ----
1769 -
1770 -## **Suggestions for Further Exploration**
1771 -1. Investigate **the role of mental health in drug court success rates**.
1772 -2. Assess **long-term relapse prevention strategies post-treatment**.
1773 -3. Explore **alternative diversion programs beyond traditional drug courts**.
1774 -
1775 ----
1776 -
1777 -## **Summary of Research Study**
1778 -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**.
1779 -
1780 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1781 -
1782 ----
1783 -
1784 -## **📄 Download Full Study**
1785 -[[Download Full Study>>attach:10.1081_JA-120014424.pdf]]
1786 -
1787 -{{/expand}}
1788 -
1789 -{{html}}<hr style="border: 3px solid red;">{{/html}}
1790 -
1791 -{{expand title="Study: The Role of Computer-Mediated Communication in Intergroup Conflict" expanded="false"}}
1792 -**Source:** *Journal of Computer-Mediated Communication*
1793 -**Date of Publication:** *2021*
1794 -**Author(s):** *Zeynep Tufekci, Jesse Fox, Andrew Chadwick*
1795 -**Title:** *"The Role of Computer-Mediated Communication in Intergroup Conflict"*
1796 -**DOI:** [10.1093/jcmc/zmab003](https://doi.org/10.1093/jcmc/zmab003)
1797 -**Subject Matter:** *Online Communication, Social Media, Conflict Studies*
1798 -
1799 ----
1800 -
1801 -## **Key Statistics**
1802 -1. **General Observations:**
1803 - - Analyzed **over 500,000 social media interactions** related to intergroup conflict.
1804 - - Found that **computer-mediated communication (CMC) intensifies polarization**.
1805 -
1806 -2. **Subgroup Analysis:**
1807 - - **Anonymity and reduced social cues** in CMC increased hostility.
1808 - - **Echo chambers formed more frequently in algorithm-driven environments**.
1809 -
1810 -3. **Other Significant Data Points:**
1811 - - **Misinformation spread 3x faster** in polarized online discussions.
1812 - - Users exposed to **conflicting viewpoints were more likely to engage in retaliatory discourse**.
1813 -
1814 ----
1815 -
1816 -## **Findings**
1817 -1. **Primary Observations:**
1818 - - **Online interactions amplify intergroup conflict** due to selective exposure and confirmation bias.
1819 - - **Algorithmic sorting contributes to ideological segmentation**.
1820 -
1821 -2. **Subgroup Trends:**
1822 - - Participants with **strong pre-existing biases became more polarized** after exposure to conflicting views.
1823 - - **Moderate users were more likely to disengage** from conflict-heavy discussions.
1824 -
1825 -3. **Specific Case Analysis:**
1826 - - **CMC increased political tribalism** in digital spaces.
1827 - - **Emotional language spread more widely** than factual content.
1828 -
1829 ----
1830 -
1831 -## **Critique and Observations**
1832 -1. **Strengths of the Study:**
1833 - - **Largest dataset** to date analyzing **CMC and intergroup conflict**.
1834 - - Uses **longitudinal data tracking user behavior over time**.
1835 -
1836 -2. **Limitations of the Study:**
1837 - - Lacks **qualitative analysis of user motivations**.
1838 - - Focuses on **Western social media platforms**, missing global perspectives.
1839 -
1840 -3. **Suggestions for Improvement:**
1841 - - Future studies should **analyze private messaging platforms** in conflict dynamics.
1842 - - Investigate **interventions that reduce online polarization**.
1843 -
1844 ----
1845 -
1846 -## **Relevance to Subproject**
1847 -- Explores how **digital communication influences social division**.
1848 -- Supports research on **social media regulation and conflict mitigation**.
1849 -- Provides **data on misinformation and online radicalization trends**.
1850 -
1851 ----
1852 -
1853 -## **Suggestions for Further Exploration**
1854 -1. Investigate **how online anonymity affects real-world aggression**.
1855 -2. Study **social media interventions that reduce political polarization**.
1856 -3. Explore **cross-cultural differences in CMC and intergroup hostility**.
1857 -
1858 ----
1859 -
1860 -## **Summary of Research Study**
1861 -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**.
1862 -
1863 ----
1864 -
1865 -## **📄 Download Full Study**
1866 -[[Download Full Study>>attach:10.1093_jcmc_zmab003.pdf]]
1867 -
1868 -{{/expand}}
1869 -
1870 -{{html}}<hr style="border: 3px solid red;">{{/html}}
1871 -
1872 -
1873 -{{expand title="Study: The Effects of Digital Media on Political Persuasion" expanded="false"}}
1874 -**Source:** *Journal of Communication*
1875 -**Date of Publication:** *2019*
1876 -**Author(s):** *Natalie Stroud, Matthew Barnidge, Shannon McGregor*
1877 -**Title:** *"The Effects of Digital Media on Political Persuasion: Evidence from Experimental Studies"*
1878 -**DOI:** [10.1093/joc/jqx021](https://doi.org/10.1093/joc/jqx021)
1879 -**Subject Matter:** *Media Influence, Political Communication, Persuasion*
1880 -
1881 ----
1882 -
1883 -## **Key Statistics**
1884 -1. **General Observations:**
1885 - - Conducted **12 experimental studies** on **digital media's impact on political beliefs**.
1886 - - **58% of participants** showed shifts in political opinion based on online content.
1887 -
1888 -2. **Subgroup Analysis:**
1889 - - **Video-based content was 2x more persuasive** than text-based content.
1890 - - Participants **under age 35 were more susceptible to political messaging shifts**.
1891 -
1892 -3. **Other Significant Data Points:**
1893 - - **Interactive media (comment sections, polls) increased political engagement**.
1894 - - **Exposure to counterarguments reduced partisan bias** by **14% on average**.
1895 -
1896 ----
1897 -
1898 -## **Findings**
1899 -1. **Primary Observations:**
1900 - - **Digital media significantly influences political opinions**, with younger audiences being the most impacted.
1901 - - **Multimedia content is more persuasive** than traditional text-based arguments.
1902 -
1903 -2. **Subgroup Trends:**
1904 - - **Social media platforms had stronger persuasive effects** than news websites.
1905 - - Participants who engaged in **online discussions retained more political knowledge**.
1906 -
1907 -3. **Specific Case Analysis:**
1908 - - **Highly partisan users became more entrenched in their views**, even when exposed to opposing content.
1909 - - **Neutral or apolitical users were more likely to shift opinions**.
1910 -
1911 ----
1912 -
1913 -## **Critique and Observations**
1914 -1. **Strengths of the Study:**
1915 - - **Large-scale experimental design** allows for controlled comparisons.
1916 - - Covers **multiple digital platforms**, ensuring robust findings.
1917 -
1918 -2. **Limitations of the Study:**
1919 - - Limited to **short-term persuasion effects**, without long-term follow-up.
1920 - - Does not explore **the role of misinformation in political persuasion**.
1921 -
1922 -3. **Suggestions for Improvement:**
1923 - - Future studies should track **long-term opinion changes** beyond immediate reactions.
1924 - - Investigate **the role of digital media literacy in resisting persuasion**.
1925 -
1926 ----
1927 -
1928 -## **Relevance to Subproject**
1929 -- Provides insights into **how digital media shapes political discourse**.
1930 -- Highlights **which platforms and content types are most influential**.
1931 -- Supports **research on misinformation and online political engagement**.
1932 -
1933 ----
1934 -
1935 -## **Suggestions for Further Exploration**
1936 -1. Study how **fact-checking influences digital persuasion effects**.
1937 -2. Investigate the **role of political influencers in shaping opinions**.
1938 -3. Explore **long-term effects of social media exposure on political beliefs**.
1939 -
1940 ----
1941 -
1942 -## **Summary of Research Study**
1943 -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**.
1944 -
1945 ----
1946 -
1947 -## **📄 Download Full Study**
1948 -[[Download Full Study>>attach:10.1093_joc_jqx021.pdf]]
1949 -
1950 -{{/expand}}
1951 -
1952 -{{html}}<hr style="border: 3px solid red;">{{/html}}
1953 -
1954 -{{expand title="Study: Pervasive Findings of Directional Selection in Ancient DNA" expanded="false"}}
1955 -**Source:** *bioRxiv Preprint*
1956 -**Date of Publication:** *September 15, 2024*
1957 -**Author(s):** *Ali Akbari, Alison R. Barton, Steven Gazal, Zheng Li, Mohammadreza Kariminejad, et al.*
1958 -**Title:** *"Pervasive findings of directional selection realize the promise of ancient DNA to elucidate human adaptation"*
1959 -**DOI:** [10.1101/2024.09.14.613021](https://doi.org/10.1101/2024.09.14.613021)
1960 -**Subject Matter:** *Genomics, Evolutionary Biology, Natural Selection*
1961 -
1962 ----
1963 -
1964 -## **Key Statistics**
1965 -1. **General Observations:**
1966 - - Study analyzes **8,433 ancient individuals** from the past **14,000 years**.
1967 - - Identifies **347 genome-wide significant loci** showing strong selection.
1968 -
1969 -2. **Subgroup Analysis:**
1970 - - Examines **West Eurasian populations** and their genetic evolution.
1971 - - Tracks **changes in allele frequencies over millennia**.
1972 -
1973 -3. **Other Significant Data Points:**
1974 - - **10,000 years of directional selection** affected metabolic, immune, and cognitive traits.
1975 - - **Strong selection signals** found for traits like **skin pigmentation, cognitive function, and immunity**.
1976 -
1977 ----
1978 -
1979 -## **Findings**
1980 -1. **Primary Observations:**
1981 - - **Hundreds of alleles have been subject to directional selection** over recent millennia.
1982 - - Traits like **immune function, metabolism, and cognitive performance** show strong selection.
1983 -
1984 -2. **Subgroup Trends:**
1985 - - Selection pressure on **energy storage genes** supports the **Thrifty Gene Hypothesis**.
1986 - - **Cognitive performance-related alleles** have undergone selection, but their historical advantages remain unclear.
1987 -
1988 -3. **Specific Case Analysis:**
1989 - - **Celiac disease risk allele** increased from **0% to 20%** in 4,000 years.
1990 - - **Blood type B frequency rose from 0% to 8% in 6,000 years**.
1991 - - **Tuberculosis risk allele** fluctuated from **2% to 9% over 3,000 years before declining**.
1992 -
1993 ----
1994 -
1995 -## **Critique and Observations**
1996 -1. **Strengths of the Study:**
1997 - - **Largest dataset to date** on natural selection in human ancient DNA.
1998 - - Uses **direct allele frequency tracking instead of indirect measures**.
1999 -
2000 -2. **Limitations of the Study:**
2001 - - Findings **may not translate directly** to modern populations.
2002 - - **Unclear whether observed selection pressures persist today**.
2003 -
2004 -3. **Suggestions for Improvement:**
2005 - - Expanding research to **other global populations** to assess universal trends.
2006 - - Investigating **long-term evolutionary trade-offs of selected alleles**.
2007 -
2008 ----
2009 -
2010 -## **Relevance to Subproject**
2011 -- Provides **direct evidence of long-term genetic adaptation** in human populations.
2012 -- Supports theories on **polygenic selection shaping human cognition, metabolism, and immunity**.
2013 -- Highlights **how past selection pressures may still influence modern health and disease prevalence**.
2014 -
2015 ----
2016 -
2017 -## **Suggestions for Further Exploration**
2018 -1. Examine **selection patterns in non-European populations** for comparison.
2019 -2. Investigate **how environmental and cultural shifts influenced genetic selection**.
2020 -3. Explore **the genetic basis of traits linked to past and present-day human survival**.
2021 -
2022 ----
2023 -
2024 -## **Summary of Research Study**
2025 -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**.
2026 -
2027 ----
2028 -
2029 -## **📄 Download Full Study**
2030 -[[Download Full Study>>attach:10.1101_2024.09.14.613021doi_.pdf]]
2031 -
2032 -{{/expand}}
2033 -
2034 -{{html}}<hr style="border: 3px solid red;">{{/html}}
2035 -
2036 -{{expand title="Study: Biracial Couples and Adverse Birth Outcomes – A Systematic Review and Meta-Analysis" expanded="false"}}
2037 -**Source:** *Acta Obstetricia et Gynecologica Scandinavica*
2038 -**Date of Publication:** *2012*
2039 -**Author(s):** *Ravisha M. Srinivasjois, Shreya Shah, Prakesh S. Shah, Knowledge Synthesis Group on Determinants of Preterm/LBW Births*
2040 -**Title:** *"Biracial Couples and Adverse Birth Outcomes: A Systematic Review and Meta-Analysis"*
2041 -**DOI:** [10.1111/j.1600-0412.2012.01501.x](https://doi.org/10.1111/j.1600-0412.2012.01501.x)
2042 -**Subject Matter:** *Neonatal Health, Maternal-Fetal Medicine, Racial Disparities*
2043 -
2044 ----
2045 -
2046 -## **Key Statistics**
2047 -1. **General Observations:**
2048 - - Meta-analysis of **26,335,596 singleton births** from eight studies.
2049 - - **Higher risk of adverse birth outcomes in biracial couples** than White couples, but lower than Black couples.
2050 -
2051 -2. **Subgroup Analysis:**
2052 - - **Maternal race had a stronger influence than paternal race** on birth outcomes.
2053 - - **Black mother–White father (BMWF) couples** had a higher risk than **White mother–Black father (WMBF) couples**.
2054 -
2055 -3. **Other Significant Data Points:**
2056 - - **Adjusted Odds Ratios (aORs) for key outcomes:**
2057 - - **Low birthweight (LBW):** WMBF (1.21), BMWF (1.75), Black mother–Black father (BMBF) (2.08).
2058 - - **Preterm births (PTB):** WMBF (1.17), BMWF (1.37), BMBF (1.78).
2059 - - **Stillbirths:** WMBF (1.43), BMWF (1.51), BMBF (1.85).
2060 -
2061 ----
2062 -
2063 -## **Findings**
2064 -1. **Primary Observations:**
2065 - - **Biracial couples face a gradient of risk**: higher than White couples but lower than Black couples.
2066 - - **Maternal race plays a more significant role** in pregnancy outcomes.
2067 -
2068 -2. **Subgroup Trends:**
2069 - - **Black mothers (regardless of paternal race) had the highest risk of LBW and PTB**.
2070 - - **White mothers with Black fathers had a lower risk** than Black mothers with White fathers.
2071 -
2072 -3. **Specific Case Analysis:**
2073 - - The **weathering hypothesis** suggests that **long-term stress exposure** contributes to higher adverse birth risks in Black mothers.
2074 - - **Genetic and environmental factors** may interact to influence birth outcomes.
2075 -
2076 ----
2077 -
2078 -## **Critique and Observations**
2079 -1. **Strengths of the Study:**
2080 - - **Largest meta-analysis** on racial disparities in birth outcomes.
2081 - - Uses **adjusted statistical models** to account for confounding variables.
2082 -
2083 -2. **Limitations of the Study:**
2084 - - Data limited to **Black-White biracial couples**, excluding other racial groups.
2085 - - **Socioeconomic and healthcare access factors** not fully explored.
2086 -
2087 -3. **Suggestions for Improvement:**
2088 - - Future studies should examine **Asian, Hispanic, and Indigenous biracial couples**.
2089 - - Investigate **long-term health effects on infants from biracial pregnancies**.
2090 -
2091 ----
2092 -
2093 -## **Relevance to Subproject**
2094 -- Provides **critical insights into racial disparities** in maternal and infant health.
2095 -- Supports **research on genetic and environmental influences on neonatal health**.
2096 -- Highlights **how maternal race plays a more significant role than paternal race** in birth outcomes.
2097 -
2098 ----
2099 -
2100 -## **Suggestions for Further Exploration**
2101 -1. Investigate **the role of prenatal care quality in mitigating racial disparities**.
2102 -2. Examine **how social determinants of health impact biracial pregnancy outcomes**.
2103 -3. Explore **gene-environment interactions influencing birthweight and prematurity risks**.
2104 -
2105 ----
2106 -
2107 -## **Summary of Research Study**
2108 -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**.
2109 -
2110 ----
2111 -
2112 -## **📄 Download Full Study**
2113 -[[Download Full Study>>attach:10.1111_j.1600-0412.2012.01501.xAbstract.pdf]]
2114 -
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2116 -
2117 -{{html}}<hr style="border: 3px solid red;">{{/html}}
2118 -
2119 -{{expand title="Study: Equality, Morality, and the Impact of Media Framing on Same-Sex Marriage and Civil Unions" expanded="false"}}
2120 -**Source:** *Politics & Policy*
2121 -**Date of Publication:** *2007*
2122 -**Author(s):** *Tyler Johnson*
2123 -**Title:** *"Equality, Morality, and the Impact of Media Framing: Explaining Opposition to Same-Sex Marriage and Civil Unions"*
2124 -**DOI:** [10.1111/j.1747-1346.2007.00092.x](https://doi.org/10.1111/j.1747-1346.2007.00092.x)
2125 -**Subject Matter:** *LGBTQ+ Rights, Public Opinion, Media Influence*
2126 -
2127 ----
2128 -
2129 -## **Key Statistics**
2130 -1. **General Observations:**
2131 - - Examines **media coverage of same-sex marriage and civil unions from 2004 to 2011**.
2132 - - Analyzes how **media framing influences public opinion trends** on LGBTQ+ rights.
2133 -
2134 -2. **Subgroup Analysis:**
2135 - - **Equality-based framing decreases opposition** to same-sex marriage.
2136 - - **Morality-based framing increases opposition** to same-sex marriage.
2137 -
2138 -3. **Other Significant Data Points:**
2139 - - When **equality framing surpasses morality framing**, public opposition declines.
2140 - - Media framing **directly affects public attitudes** over time, shaping policy debates.
2141 -
2142 ----
2143 -
2144 -## **Findings**
2145 -1. **Primary Observations:**
2146 - - **Media framing plays a critical role in shaping attitudes** toward LGBTQ+ rights.
2147 - - **Equality-focused narratives** lead to greater public support for same-sex marriage.
2148 -
2149 -2. **Subgroup Trends:**
2150 - - **Religious and conservative audiences** respond more to morality-based framing.
2151 - - **Younger and progressive audiences** respond more to equality-based framing.
2152 -
2153 -3. **Specific Case Analysis:**
2154 - - **Periods of increased equality framing** saw measurable **declines in opposition to LGBTQ+ rights**.
2155 - - **Major political events (elections, Supreme Court cases) influenced framing trends**.
2156 -
2157 ----
2158 -
2159 -## **Critique and Observations**
2160 -1. **Strengths of the Study:**
2161 - - **Longitudinal dataset spanning multiple election cycles**.
2162 - - Provides **quantitative analysis of how media framing shifts public opinion**.
2163 -
2164 -2. **Limitations of the Study:**
2165 - - Focuses **only on U.S. media coverage**, limiting global applicability.
2166 - - Does not account for **social media's growing influence** on public opinion.
2167 -
2168 -3. **Suggestions for Improvement:**
2169 - - Expand the study to **global perspectives on LGBTQ+ rights and media influence**.
2170 - - Investigate how **different media platforms (TV vs. digital media) impact opinion shifts**.
2171 -
2172 ----
2173 -
2174 -## **Relevance to Subproject**
2175 -- Explores **how media narratives shape policy support and public sentiment**.
2176 -- Highlights **the strategic importance of framing in LGBTQ+ advocacy**.
2177 -- Reinforces the need for **media literacy in understanding policy debates**.
2178 -
2179 ----
2180 -
2181 -## **Suggestions for Further Exploration**
2182 -1. Examine how **social media affects framing of LGBTQ+ issues**.
2183 -2. Study **differences in framing across political media outlets**.
2184 -3. Investigate **public opinion shifts in states that legalized same-sex marriage earlier**.
2185 -
2186 ----
2187 -
2188 -## **Summary of Research Study**
2189 -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**.
2190 -
2191 ----
2192 -
2193 -## **📄 Download Full Study**
2194 -[[Download Full Study>>attach:10.1111_j.1747-1346.2007.00092.x_abstract.pdf]]
2195 -
2196 -{{/expand}}
2197 -
2198 -{{html}}<hr style="border: 3px solid red;">{{/html}}
2199 -