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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/}}
15 15  
15 +
16 16  == Research Studies Repository ==
17 17  
18 += Genetics =
18 18  
19 -= Study: Genetic Structure, Self-Identified Race/Ethnicity, and Confounding =
20 -{{expand expanded="false" title="Click here to expand details"}}
21 -**Source:** Journal of Genetic Epidemiology
22 -**Date of Publication:** 2024-01-15
23 -**Author(s):** Smith et al.
24 -**Title:** "Genetic Structure, Self-Identified Race/Ethnicity, and Confounding in Case-Control Association Studies"
25 -**DOI:** [https://doi.org/10.1037/1076-8971.11.2.235](https://doi.org/10.1037/1076-8971.11.2.235)
26 -**Subject Matter:** Genetics, Social Science
20 +== Study: Reconstructing Indian Population History ==
21 +{{expand title="Study: Reconstructing Indian Population History" expanded="false"}}
22 +**Source:** *Nature*
23 +**Date of Publication:** *2009*
24 +**Author(s):** *David Reich, Kumarasamy Thangaraj, Nick Patterson, Alkes L. Price, Lalji Singh*
25 +**Title:** *"Reconstructing Indian Population History"*
26 +**DOI:** [10.1038/nature08365](https://doi.org/10.1038/nature08365)
27 +**Subject Matter:** *Genetics, Population History, South Asian Ancestry*
27 27  
28 -**Tags:** `Genetics` `Race & Ethnicity` `Biomedical Research`
29 +---
29 29  
30 -=== **Key Statistics** ===
31 +## **Key Statistics**
32 +1. **General Observations:**
33 + - Study analyzed **132 individuals from 25 diverse Indian groups**.
34 + - Identified two major ancestral populations: **Ancestral North Indians (ANI)** and **Ancestral South Indians (ASI)**.
31 31  
36 +2. **Subgroup Analysis:**
37 + - ANI ancestry is closely related to **Middle Easterners, Central Asians, and Europeans**.
38 + - ASI ancestry is **genetically distinct from ANI and East Asians**.
39 +
40 +3. **Other Significant Data Points:**
41 + - ANI ancestry ranges from **39% to 71%** across Indian groups.
42 + - **Caste and linguistic differences** strongly correlate with genetic variation.
43 +
44 +---
45 +
46 +## **Findings**
47 +1. **Primary Observations:**
48 + - The genetic landscape of India has been shaped by **thousands of years of endogamy**.
49 + - Groups with **only ASI ancestry no longer exist** in mainland India.
50 +
51 +2. **Subgroup Trends:**
52 + - **Higher ANI ancestry in upper-caste and Indo-European-speaking groups**.
53 + - **Andaman Islanders** are unique in having **ASI ancestry without ANI influence**.
54 +
55 +3. **Specific Case Analysis:**
56 + - **Founder effects** have maintained allele frequency differences among Indian groups.
57 + - Predicts **higher incidence of recessive diseases** due to historical genetic isolation.
58 +
59 +---
60 +
61 +## **Critique and Observations**
62 +1. **Strengths of the Study:**
63 + - **First large-scale genetic analysis** of Indian population history.
64 + - Introduces **new methods for ancestry estimation without direct ancestral reference groups**.
65 +
66 +2. **Limitations of the Study:**
67 + - Limited **sample size relative to India's population diversity**.
68 + - Does not include **recent admixture events** post-colonial era.
69 +
70 +3. **Suggestions for Improvement:**
71 + - Future research should **expand sampling across more Indian tribal groups**.
72 + - Use **whole-genome sequencing** for finer resolution of ancestry.
73 +
74 +---
75 +
76 +## **Relevance to Subproject**
77 +- Provides a **genetic basis for caste and linguistic diversity** in India.
78 +- Highlights **founder effects and genetic drift** shaping South Asian populations.
79 +- Supports research on **medical genetics and disease risk prediction** in Indian populations.
80 +
81 +---
82 +
83 +## **Suggestions for Further Exploration**
84 +1. Examine **genetic markers linked to disease susceptibility** in Indian subpopulations.
85 +2. Investigate the impact of **recent migration patterns on ANI-ASI ancestry distribution**.
86 +3. Study **gene flow between Indian populations and other global groups**.
87 +
88 +---
89 +
90 +## **Summary of Research Study**
91 +This study reconstructs **the genetic history of India**, revealing two ancestral populations—**ANI (related to West Eurasians) and ASI (distinctly South Asian)**. By analyzing **25 diverse Indian groups**, the researchers demonstrate how **historical endogamy and founder effects** have maintained genetic differentiation. The findings have **implications for medical genetics, population history, and the study of South Asian ancestry**.
92 +
93 +This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
94 +
95 +---
96 +
97 +## **📄 Download Full Study**
98 +[[Download Full Study>>attach:10.1038_nature08365.pdf]]
99 +
100 +{{/expand}}
101 +
102 +
103 +
104 +== Study: The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations ==
105 +{{expand title="Study: The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations" expanded="false"}}
106 +**Source:** *Nature*
107 +**Date of Publication:** *2016*
108 +**Author(s):** *David Reich, Swapan Mallick, Heng Li, Mark Lipson, and others*
109 +**Title:** *"The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations"*
110 +**DOI:** [10.1038/nature18964](https://doi.org/10.1038/nature18964)
111 +**Subject Matter:** *Human Genetic Diversity, Population History, Evolutionary Genomics*
112 +
113 +---
114 +
115 +## **Key Statistics**
32 32  1. **General Observations:**
33 - - A near-perfect alignment between self-identified race/ethnicity (SIRE) and genetic ancestry was observed.
34 - - Misclassification rate: **0.14%**.
117 + - Analyzed **high-coverage genome sequences of 300 individuals from 142 populations**.
118 + - Included **many underrepresented and indigenous groups** from Africa, Asia, Europe, and the Americas.
35 35  
36 36  2. **Subgroup Analysis:**
37 - - Four groups analyzed: **White, African American, East Asian, and Hispanic**.
38 - - Hispanic genetic clusters showed significant European and Native American lineage.
121 + - Found **higher genetic diversity within African populations** compared to non-African groups.
122 + - Showed **Neanderthal and Denisovan ancestry in non-African populations**, particularly in Oceania.
39 39  
40 -=== **Findings** ===
124 +3. **Other Significant Data Points:**
125 + - Identified **5.8 million base pairs absent from the human reference genome**.
126 + - Estimated that **mutations have accumulated 5% faster in non-Africans than in Africans**.
41 41  
42 -- Self-identified race strongly aligns with genetic ancestry.
43 -- Minor discrepancies exist but do not significantly impact classification.
128 +---
44 44  
45 -=== **Relevance to Subproject** ===
130 +## **Findings**
131 +1. **Primary Observations:**
132 + - **African populations harbor the greatest genetic diversity**, confirming an out-of-Africa dispersal model.
133 + - Indigenous Australians and New Guineans **share a common ancestral population with other non-Africans**.
46 46  
47 -- Reinforces the reliability of **self-reported racial identity** in genetic research.
48 -- Highlights **policy considerations** in biomedical studies.
135 +2. **Subgroup Trends:**
136 + - **Lower heterozygosity in non-Africans** due to founder effects from migration bottlenecks.
137 + - **Denisovan ancestry in South Asians is higher than previously thought**.
138 +
139 +3. **Specific Case Analysis:**
140 + - **Neanderthal ancestry is higher in East Asians than in Europeans**.
141 + - African hunter-gatherer groups show **deep population splits over 100,000 years ago**.
142 +
143 +---
144 +
145 +## **Critique and Observations**
146 +1. **Strengths of the Study:**
147 + - **Largest global genetic dataset** outside of the 1000 Genomes Project.
148 + - High sequencing depth allows **more accurate identification of genetic variants**.
149 +
150 +2. **Limitations of the Study:**
151 + - **Limited sample sizes for some populations**, restricting generalizability.
152 + - Lacks ancient DNA comparisons, making it difficult to reconstruct deep ancestry fully.
153 +
154 +3. **Suggestions for Improvement:**
155 + - Future studies should include **ancient genomes** to improve demographic modeling.
156 + - Expand research into **how genetic variation affects health outcomes** across populations.
157 +
158 +---
159 +
160 +## **Relevance to Subproject**
161 +- Provides **comprehensive data on human genetic diversity**, useful for **evolutionary studies**.
162 +- Supports research on **Neanderthal and Denisovan introgression** in modern human populations.
163 +- Enhances understanding of **genetic adaptation and disease susceptibility across groups**.
164 +
165 +---
166 +
167 +## **Suggestions for Further Exploration**
168 +1. Investigate **functional consequences of genetic variation in underrepresented populations**.
169 +2. Study **how selection pressures shaped genetic diversity across different environments**.
170 +3. Explore **medical applications of population-specific genetic markers**.
171 +
172 +---
173 +
174 +## **Summary of Research Study**
175 +This study presents **high-coverage genome sequences from 300 individuals across 142 populations**, offering **new insights into global genetic diversity and human evolution**. The findings highlight **deep African population splits, widespread archaic ancestry in non-Africans, and unique variants absent from the human reference genome**. The research enhances our understanding of **migration patterns, adaptation, and evolutionary history**.
176 +
177 +This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
178 +
179 +---
180 +
181 +## **📄 Download Full Study**
182 +[[Download Full Study>>attach:10.1038_nature18964.pdf]]
183 +
49 49  {{/expand}}
50 50  
51 -{{expand title="Study: [Study Title] (Click to Expand)" expanded="false"}}
52 -**Source:** [Journal/Institution Name]
53 -**Date of Publication:** [Publication Date]
54 -**Author(s):** [Author(s) Name(s)]
55 -**Title:** "[Study Title]"
56 -**DOI:** [DOI or Link]
57 -**Subject Matter:** [Broad Research Area, e.g., Social Psychology, Public Policy, Behavioral Economics]
58 58  
187 +== Study: Meta-analysis of the heritability of human traits based on fifty years of twin studies ==
188 +{{expand title="Study: Meta-analysis of the heritability of human traits based on fifty years of twin studies" expanded="false"}}
189 +**Source:** *Nature Genetics*
190 +**Date of Publication:** *2015*
191 +**Author(s):** *Tinca J. C. Polderman, Beben Benyamin, Christiaan A. de Leeuw, Patrick F. Sullivan, Arjen van Bochoven, Peter M. Visscher, Danielle Posthuma*
192 +**Title:** *"Meta-analysis of the heritability of human traits based on fifty years of twin studies"*
193 +**DOI:** [10.1038/ng.328](https://doi.org/10.1038/ng.328)
194 +**Subject Matter:** *Genetics, Heritability, Twin Studies, Behavioral Science*
195 +
59 59  ---
60 60  
61 61  ## **Key Statistics**
62 62  1. **General Observations:**
63 - - [Statistical finding or observation]
64 - - [Statistical finding or observation]
200 + - Analyzed **17,804 traits from 2,748 twin studies** published between **1958 and 2012**.
201 + - Included data from **14,558,903 twin pairs**, making it the largest meta-analysis on human heritability.
65 65  
66 66  2. **Subgroup Analysis:**
67 - - [Breakdown of findings by gender, race, or other subgroups]
204 + - Found **49% average heritability** across all traits.
205 + - **69% of traits follow a simple additive genetic model**, meaning most variance is due to genes, not environment.
68 68  
69 69  3. **Other Significant Data Points:**
70 - - [Any additional findings or significant statistics]
208 + - **Neurological, metabolic, and psychiatric traits** showed the highest heritability estimates.
209 + - Traits related to **social values and environmental interactions** had lower heritability estimates.
71 71  
72 72  ---
73 73  
74 74  ## **Findings**
75 75  1. **Primary Observations:**
76 - - [High-level findings or trends in the study]
215 + - Across all traits, genetic factors play a significant role in individual differences.
216 + - The study contradicts models that **overestimate environmental effects in behavioral and cognitive traits**.
77 77  
78 78  2. **Subgroup Trends:**
79 - - [Disparities or differences highlighted in the study]
219 + - **Eye and brain-related traits showed the highest heritability (~70-80%)**.
220 + - **Shared environmental effects were negligible (<10%) for most traits**.
80 80  
81 81  3. **Specific Case Analysis:**
82 - - [Detailed explanation of any notable specific findings]
223 + - Twin correlations suggest **limited evidence for strong non-additive genetic influences**.
224 + - The study highlights **missing heritability in complex traits**, which genome-wide association studies (GWAS) have yet to fully explain.
83 83  
84 84  ---
85 85  
86 86  ## **Critique and Observations**
87 87  1. **Strengths of the Study:**
88 - - [Examples: strong methodology, large dataset, etc.]
230 + - **Largest-ever heritability meta-analysis**, covering nearly all published twin studies.
231 + - Provides a **comprehensive framework for understanding gene-environment contributions**.
89 89  
90 90  2. **Limitations of the Study:**
91 - - [Examples: data gaps, lack of upstream analysis, etc.]
234 + - **Underrepresentation of African, South American, and Asian twin cohorts**, limiting global generalizability.
235 + - Cannot **fully separate genetic influences from potential cultural/environmental confounders**.
92 92  
93 93  3. **Suggestions for Improvement:**
94 - - [Ideas for further research or addressing limitations]
238 + - Future research should use **whole-genome sequencing** for finer-grained heritability estimates.
239 + - **Incorporate non-Western populations** to assess global heritability trends.
95 95  
96 96  ---
97 97  
98 98  ## **Relevance to Subproject**
99 -- [Explanation of how this study contributes to your subproject goals.]
100 -- [Any key arguments or findings that support or challenge your views.]
244 +- Establishes a **quantitative benchmark for heritability across human traits**.
245 +- Reinforces **genetic influence on cognitive, behavioral, and physical traits**.
246 +- Highlights the need for **genome-wide studies to identify missing heritability**.
101 101  
102 102  ---
103 103  
104 104  ## **Suggestions for Further Exploration**
105 -1. [Research questions or areas to investigate further.]
106 -2. [Potential studies or sources to complement this analysis.]
251 +1. Investigate how **heritability estimates compare across different socioeconomic backgrounds**.
252 +2. Examine **gene-environment interactions in cognitive and psychiatric traits**.
253 +3. Explore **non-additive genetic effects on human traits using newer statistical models**.
107 107  
108 108  ---
109 109  
110 110  ## **Summary of Research Study**
111 -This study examines **[core research question or focus]**, providing insights into **[main subject area]**. The research utilized **[sample size and methodology]** to assess **[key variables or measured outcomes]**.
258 +This study presents a **comprehensive meta-analysis of human trait heritability**, covering **over 50 years of twin research**. The findings confirm **genes play a predominant role in shaping human traits**, with an **average heritability of 49%** across all measured characteristics. The research offers **valuable insights into genetic and environmental influences**, guiding future gene-mapping efforts and behavioral genetics studies.
112 112  
113 -This summary provides an accessible, at-a-glance overview of the study's contributions. Please refer to the full paper for in-depth analysis.
260 +This summary provides an accessible, at-a-glance overview of the studys contributions. Please refer to the full paper for in-depth analysis.
114 114  
115 115  ---
116 116  
117 117  ## **📄 Download Full Study**
118 -{{velocity}}
119 -#set($doi = "[Insert DOI Here]")
120 -#set($filename = "${doi}.pdf")
121 -#if($xwiki.exists("attach:$filename"))
122 -[[Download>>attach:$filename]]
123 -#else
124 -{{html}}<span style="color: red; font-weight: bold;">🚨 PDF Not Available 🚨</span>{{/html}}
125 -#end
126 -{{/velocity}}
265 +[[Download Full Study>>attach:10.1038_ng.328.pdf]]
127 127  
128 128  {{/expand}}
129 129  
130 -{{html}}<hr style="border: 3px solid red;">{{/html}}
131 131  
270 +== Study: Genetic Analysis of African Populations: Human Evolution and Complex Disease ==
271 +{{expand title="Study: Genetic Analysis of African Populations: Human Evolution and Complex Disease" expanded="false"}}
272 +**Source:** *Nature Reviews Genetics*
273 +**Date of Publication:** *2002*
274 +**Author(s):** *Sarah A. Tishkoff, Scott M. Williams*
275 +**Title:** *"Genetic Analysis of African Populations: Human Evolution and Complex Disease"*
276 +**DOI:** [10.1038/nrg865](https://doi.org/10.1038/nrg865)
277 +**Subject Matter:** *Population Genetics, Human Evolution, Complex Diseases*
132 132  
279 +---
133 133  
281 +## **Key Statistics**
282 +1. **General Observations:**
283 + - Africa harbors **the highest genetic diversity** of any region, making it key to understanding human evolution.
284 + - The study analyzes **genetic variation and linkage disequilibrium (LD) in African populations**.
285 +
286 +2. **Subgroup Analysis:**
287 + - African populations exhibit **greater genetic differentiation compared to non-Africans**.
288 + - **Migration and admixture** have shaped modern African genomes over the past **100,000 years**.
289 +
290 +3. **Other Significant Data Points:**
291 + - The **effective population size (Ne) of Africans** is higher than that of non-African populations.
292 + - LD blocks are **shorter in African genomes**, suggesting more historical recombination events.
293 +
134 134  ---
135 135  
296 +## **Findings**
297 +1. **Primary Observations:**
298 + - African populations are the **most genetically diverse**, supporting the *Recent African Origin* hypothesis.
299 + - Genetic variation in African populations can **help fine-map complex disease genes**.
300 +
301 +2. **Subgroup Trends:**
302 + - **West Africans exhibit higher genetic diversity** than East Africans due to differing migration patterns.
303 + - Populations such as **San hunter-gatherers show deep genetic divergence**.
304 +
305 +3. **Specific Case Analysis:**
306 + - Admixture in African Americans includes **West African and European genetic contributions**.
307 + - SNP (single nucleotide polymorphism) diversity in African genomes **exceeds that of non-African groups**.
308 +
309 +---
310 +
311 +## **Critique and Observations**
312 +1. **Strengths of the Study:**
313 + - Provides **comprehensive genetic analysis** of diverse African populations.
314 + - Highlights **how genetic diversity impacts health disparities and disease risks**.
315 +
316 +2. **Limitations of the Study:**
317 + - Many **African populations remain understudied**, limiting full understanding of diversity.
318 + - Focuses more on genetic variation than on **specific disease mechanisms**.
319 +
320 +3. **Suggestions for Improvement:**
321 + - Expand research into **underrepresented African populations**.
322 + - Integrate **whole-genome sequencing for a more detailed evolutionary timeline**.
323 +
324 +---
325 +
326 +## **Relevance to Subproject**
327 +- Supports **genetic models of human evolution** and the **out-of-Africa hypothesis**.
328 +- Reinforces **Africa’s key role in disease gene mapping and precision medicine**.
329 +- Provides insight into **historical migration patterns and their genetic impact**.
330 +
331 +---
332 +
333 +## **Suggestions for Further Exploration**
334 +1. Investigate **genetic adaptations to local environments within Africa**.
335 +2. Study **the role of African genetic diversity in disease resistance**.
336 +3. Expand research on **how ancient migration patterns shaped modern genetic structure**.
337 +
338 +---
339 +
340 +## **Summary of Research Study**
341 +This study explores the **genetic diversity of African populations**, analyzing their role in **human evolution and complex disease research**. The findings highlight **Africa’s unique genetic landscape**, confirming it as the most genetically diverse continent. The research provides valuable insights into **how genetic variation influences disease susceptibility, evolution, and population structure**.
342 +
343 +This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
344 +
345 +---
346 +
347 +## **📄 Download Full Study**
348 +[[Download Full Study>>attach:10.1038_nrg865MODERN.pdf]]
349 +
350 +{{/expand}}
351 +
352 +
353 +== Study: Pervasive Findings of Directional Selection in Ancient DNA ==
354 +{{expand title="Study: Pervasive Findings of Directional Selection in Ancient DNA" expanded="false"}}
355 +**Source:** *bioRxiv Preprint*
356 +**Date of Publication:** *September 15, 2024*
357 +**Author(s):** *Ali Akbari, Alison R. Barton, Steven Gazal, Zheng Li, Mohammadreza Kariminejad, et al.*
358 +**Title:** *"Pervasive findings of directional selection realize the promise of ancient DNA to elucidate human adaptation"*
359 +**DOI:** [10.1101/2024.09.14.613021](https://doi.org/10.1101/2024.09.14.613021)
360 +**Subject Matter:** *Genomics, Evolutionary Biology, Natural Selection*
361 +
362 +---
363 +
364 +## **Key Statistics**
365 +1. **General Observations:**
366 + - Study analyzes **8,433 ancient individuals** from the past **14,000 years**.
367 + - Identifies **347 genome-wide significant loci** showing strong selection.
368 +
369 +2. **Subgroup Analysis:**
370 + - Examines **West Eurasian populations** and their genetic evolution.
371 + - Tracks **changes in allele frequencies over millennia**.
372 +
373 +3. **Other Significant Data Points:**
374 + - **10,000 years of directional selection** affected metabolic, immune, and cognitive traits.
375 + - **Strong selection signals** found for traits like **skin pigmentation, cognitive function, and immunity**.
376 +
377 +---
378 +
379 +## **Findings**
380 +1. **Primary Observations:**
381 + - **Hundreds of alleles have been subject to directional selection** over recent millennia.
382 + - Traits like **immune function, metabolism, and cognitive performance** show strong selection.
383 +
384 +2. **Subgroup Trends:**
385 + - Selection pressure on **energy storage genes** supports the **Thrifty Gene Hypothesis**.
386 + - **Cognitive performance-related alleles** have undergone selection, but their historical advantages remain unclear.
387 +
388 +3. **Specific Case Analysis:**
389 + - **Celiac disease risk allele** increased from **0% to 20%** in 4,000 years.
390 + - **Blood type B frequency rose from 0% to 8% in 6,000 years**.
391 + - **Tuberculosis risk allele** fluctuated from **2% to 9% over 3,000 years before declining**.
392 +
393 +---
394 +
395 +## **Critique and Observations**
396 +1. **Strengths of the Study:**
397 + - **Largest dataset to date** on natural selection in human ancient DNA.
398 + - Uses **direct allele frequency tracking instead of indirect measures**.
399 +
400 +2. **Limitations of the Study:**
401 + - Findings **may not translate directly** to modern populations.
402 + - **Unclear whether observed selection pressures persist today**.
403 +
404 +3. **Suggestions for Improvement:**
405 + - Expanding research to **other global populations** to assess universal trends.
406 + - Investigating **long-term evolutionary trade-offs of selected alleles**.
407 +
408 +---
409 +
410 +## **Relevance to Subproject**
411 +- Provides **direct evidence of long-term genetic adaptation** in human populations.
412 +- Supports theories on **polygenic selection shaping human cognition, metabolism, and immunity**.
413 +- Highlights **how past selection pressures may still influence modern health and disease prevalence**.
414 +
415 +---
416 +
417 +## **Suggestions for Further Exploration**
418 +1. Examine **selection patterns in non-European populations** for comparison.
419 +2. Investigate **how environmental and cultural shifts influenced genetic selection**.
420 +3. Explore **the genetic basis of traits linked to past and present-day human survival**.
421 +
422 +---
423 +
424 +## **Summary of Research Study**
425 +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**.
426 +
427 +---
428 +
429 +## **📄 Download Full Study**
430 +[[Download Full Study>>attach:10.1101_2024.09.14.613021doi_.pdf]]
431 +
432 +{{/expand}}
433 +
434 +== Study: The Wilson Effect: The Increase in Heritability of IQ With Age ==
435 +{{expand title="Study: The Wilson Effect: The Increase in Heritability of IQ With Age" expanded="false"}}
436 +**Source:** *Twin Research and Human Genetics (Cambridge University Press)*
437 +**Date of Publication:** *2013*
438 +**Author(s):** *Thomas J. Bouchard Jr.*
439 +**Title:** *"The Wilson Effect: The Increase in Heritability of IQ With Age"*
440 +**DOI:** [10.1017/thg.2013.54](https://doi.org/10.1017/thg.2013.54)
441 +**Subject Matter:** *Intelligence, Heritability, Developmental Psychology*
442 +
443 +---
444 +
445 +## **Key Statistics**
446 +1. **General Observations:**
447 + - The study documents how the **heritability of IQ increases with age**, reaching an asymptote at **0.80 by adulthood**.
448 + - Analysis is based on **longitudinal twin and adoption studies**.
449 +
450 +2. **Subgroup Analysis:**
451 + - Shared environmental influence on IQ **declines with age**, reaching **0.10 in adulthood**.
452 + - Monozygotic twins show **increasing genetic similarity in IQ over time**, while dizygotic twins become **less concordant**.
453 +
454 +3. **Other Significant Data Points:**
455 + - Data from the **Louisville Longitudinal Twin Study and cross-national twin samples** support findings.
456 + - IQ stability over time is **influenced more by genetics than by shared environmental factors**.
457 +
458 +---
459 +
460 +## **Findings**
461 +1. **Primary Observations:**
462 + - Intelligence heritability **strengthens throughout development**, contrary to early environmental models.
463 + - Shared environmental effects **decrease by late adolescence**, emphasizing **genetic influence in adulthood**.
464 +
465 +2. **Subgroup Trends:**
466 + - Studies from **Scotland, Netherlands, and the US** show **consistent patterns of increasing heritability with age**.
467 + - Findings hold across **varied socio-economic and educational backgrounds**.
468 +
469 +3. **Specific Case Analysis:**
470 + - Longitudinal adoption studies show **declining impact of adoptive parental influence on IQ** as children age.
471 + - Cross-sectional twin data confirm **higher IQ correlations for monozygotic twins in adulthood**.
472 +
473 +---
474 +
475 +## **Critique and Observations**
476 +1. **Strengths of the Study:**
477 + - **Robust dataset covering multiple twin and adoption studies over decades**.
478 + - **Clear, replicable trend** demonstrating the increasing role of genetics in intelligence.
479 +
480 +2. **Limitations of the Study:**
481 + - Findings apply primarily to **Western industrialized nations**, limiting generalizability.
482 + - **Lack of neurobiological mechanisms** explaining how genes express their influence over time.
483 +
484 +3. **Suggestions for Improvement:**
485 + - Future research should investigate **gene-environment interactions in cognitive aging**.
486 + - Examine **heritability trends in non-Western populations** to determine cross-cultural consistency.
487 +
488 +---
489 +
490 +## **Relevance to Subproject**
491 +- Provides **strong evidence for the genetic basis of intelligence**.
492 +- Highlights the **diminishing role of shared environment in cognitive development**.
493 +- Supports research on **cognitive aging and heritability across the lifespan**.
494 +
495 +---
496 +
497 +## **Suggestions for Further Exploration**
498 +1. Investigate **neurogenetic pathways underlying IQ development**.
499 +2. Examine **how education and socioeconomic factors interact with genetic IQ influences**.
500 +3. Study **heritability trends in aging populations and cognitive decline**.
501 +
502 +---
503 +
504 +## **Summary of Research Study**
505 +This study documents **The Wilson Effect**, demonstrating how the **heritability of IQ increases throughout development**, reaching a plateau of **0.80 by adulthood**. The findings indicate that **shared environmental effects diminish with age**, while **genetic influences on intelligence strengthen**. Using **longitudinal twin and adoption data**, the research provides **strong empirical support for the increasing role of genetics in cognitive ability over time**.
506 +
507 +This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
508 +
509 +---
510 +
511 +## **📄 Download Full Study**
512 +[[Download Full Study>>attach:10.1017_thg.2013.54.pdf]]
513 +
514 +{{/expand}}
515 +
516 +== Study: Is Homo sapiens polytypic? Human taxonomic diversity and its implications ==
517 +{{expand title="Study: Is Homo sapiens polytypic? Human taxonomic diversity and its implications" expanded="false"}}
518 +**Source:** *Medical Hypotheses (Elsevier)*
519 +**Date of Publication:** *2010*
520 +**Author(s):** *Michael A. Woodley*
521 +**Title:** *"Is Homo sapiens polytypic? Human taxonomic diversity and its implications"*
522 +**DOI:** [10.1016/j.mehy.2009.07.046](https://doi.org/10.1016/j.mehy.2009.07.046)
523 +**Subject Matter:** *Human Taxonomy, Evolutionary Biology, Anthropology*
524 +
525 +---
526 +
527 +## **Key Statistics**
528 +1. **General Observations:**
529 + - The study argues that **Homo sapiens is polytypic**, meaning it consists of multiple subspecies rather than a single monotypic species.
530 + - Examines **genetic diversity, morphological variation, and evolutionary lineage** in humans.
531 +
532 +2. **Subgroup Analysis:**
533 + - Discusses **four primary definitions of race/subspecies**: Essentialist, Taxonomic, Population-based, and Lineage-based.
534 + - Suggests that **human heterozygosity levels are comparable to species that are classified as polytypic**.
535 +
536 +3. **Other Significant Data Points:**
537 + - The study evaluates **FST values (genetic differentiation measure)** and argues that human genetic differentiation is comparable to that of recognized subspecies in other species.
538 + - Considers **phylogenetic species concepts** in defining human variation.
539 +
540 +---
541 +
542 +## **Findings**
543 +1. **Primary Observations:**
544 + - Proposes that **modern human populations meet biological criteria for subspecies classification**.
545 + - Highlights **medical and evolutionary implications** of human taxonomic diversity.
546 +
547 +2. **Subgroup Trends:**
548 + - Discusses **how race concepts evolved over time** in biological sciences.
549 + - Compares **human diversity with that of other primates** such as chimpanzees and gorillas.
550 +
551 +3. **Specific Case Analysis:**
552 + - Evaluates how **genetic markers correlate with population structure**.
553 + - Addresses the **controversy over race classification in modern anthropology**.
554 +
555 +---
556 +
557 +## **Critique and Observations**
558 +1. **Strengths of the Study:**
559 + - Uses **comparative species analysis** to assess human classification.
560 + - Provides a **biological perspective** on the race concept, moving beyond social constructivism arguments.
561 +
562 +2. **Limitations of the Study:**
563 + - Controversial topic with **strong opposing views in anthropology and genetics**.
564 + - **Relies on broad genetic trends**, but does not analyze individual-level genetic variation in depth.
565 +
566 +3. **Suggestions for Improvement:**
567 + - Further research should **incorporate whole-genome studies** to refine subspecies classifications.
568 + - Investigate **how admixture affects taxonomic classification over time**.
569 +
570 +---
571 +
572 +## **Relevance to Subproject**
573 +- Contributes to discussions on **evolutionary taxonomy and species classification**.
574 +- Provides evidence on **genetic differentiation among human populations**.
575 +- Highlights **historical and contemporary scientific debates on race and human variation**.
576 +
577 +---
578 +
579 +## **Suggestions for Further Exploration**
580 +1. Examine **FST values in modern and ancient human populations**.
581 +2. Investigate how **adaptive evolution influences population differentiation**.
582 +3. Explore **the impact of genetic diversity on medical treatments and disease susceptibility**.
583 +
584 +---
585 +
586 +## **Summary of Research Study**
587 +This study evaluates **whether Homo sapiens should be classified as a polytypic species**, analyzing **genetic diversity, evolutionary lineage, and morphological variation**. Using comparative analysis with other primates and mammals, the research suggests that **human populations meet biological criteria for subspecies classification**, with implications for **evolutionary biology, anthropology, and medicine**.
588 +
589 +This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
590 +
591 +---
592 +
593 +## **📄 Download Full Study**
594 +[[Download Full Study>>attach:10.1016_j.mehy.2009.07.046.pdf]]
595 +
596 +{{/expand}}
597 +
598 +
599 +== Study: Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media ==
600 +{{expand title="Study: Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media" expanded="false"}}
601 +**Source:** *Intelligence (Elsevier)*
602 +**Date of Publication:** *2019*
603 +**Author(s):** *Heiner Rindermann, David Becker, Thomas R. Coyle*
604 +**Title:** *"Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media"*
605 +**DOI:** [10.1016/j.intell.2019.101406](https://doi.org/10.1016/j.intell.2019.101406)
606 +**Subject Matter:** *Psychology, Intelligence Research, Expert Analysis*
607 +
608 +---
609 +
610 +## **Key Statistics**
611 +1. **General Observations:**
612 + - Survey of **102 experts** on intelligence research and public discourse.
613 + - Evaluated experts' backgrounds, political affiliations, and views on controversial topics in intelligence research.
614 +
615 +2. **Subgroup Analysis:**
616 + - **90% of experts were from Western countries**, and **83% were male**.
617 + - Political spectrum ranged from **54% left-liberal, 24% conservative**, with significant ideological influences on views.
618 +
619 +3. **Other Significant Data Points:**
620 + - Experts rated media coverage of intelligence research as **poor (avg. 3.1 on a 9-point scale)**.
621 + - **50% of experts attributed US Black-White IQ differences to genetic factors, 50% to environmental factors**.
622 +
623 +---
624 +
625 +## **Findings**
626 +1. **Primary Observations:**
627 + - Experts overwhelmingly support **the g-factor theory of intelligence**.
628 + - **Heritability of intelligence** was widely accepted, though views differed on race and group differences.
629 +
630 +2. **Subgroup Trends:**
631 + - **Left-leaning experts were more likely to reject genetic explanations for group IQ differences**.
632 + - **Right-leaning experts tended to favor a stronger role for genetic factors** in intelligence disparities.
633 +
634 +3. **Specific Case Analysis:**
635 + - The study compared **media coverage of intelligence research** with expert opinions.
636 + - Found a **disconnect between journalists and intelligence researchers**, especially regarding politically sensitive issues.
637 +
638 +---
639 +
640 +## **Critique and Observations**
641 +1. **Strengths of the Study:**
642 + - **Largest expert survey on intelligence research** to date.
643 + - Provides insight into **how political orientation influences scientific perspectives**.
644 +
645 +2. **Limitations of the Study:**
646 + - **Sample primarily from Western countries**, limiting global perspectives.
647 + - Self-selection bias may skew responses toward **those more willing to engage with controversial topics**.
648 +
649 +3. **Suggestions for Improvement:**
650 + - Future studies should include **a broader range of global experts**.
651 + - Additional research needed on **media biases and misrepresentation of intelligence research**.
652 +
653 +---
654 +
655 +## **Relevance to Subproject**
656 +- Provides insight into **expert consensus and division on intelligence research**.
657 +- Highlights the **role of media bias** in shaping public perception of intelligence science.
658 +- Useful for understanding **the intersection of science, politics, and public discourse** on intelligence research.
659 +
660 +---
661 +
662 +## **Suggestions for Further Exploration**
663 +1. Examine **cross-national differences** in expert opinions on intelligence.
664 +2. Investigate how **media bias impacts public understanding of intelligence research**.
665 +3. Conduct follow-up studies with **a more diverse expert pool** to test findings.
666 +
667 +---
668 +
669 +## **Summary of Research Study**
670 +This study surveys **expert opinions on intelligence research**, analyzing **how backgrounds, political ideologies, and media representation influence perspectives on intelligence**. The findings highlight **divisions in scientific consensus**, particularly on **genetic vs. environmental causes of IQ disparities**. Additionally, the research uncovers **widespread dissatisfaction with media portrayals of intelligence research**, pointing to **the impact of ideological biases on public discourse**.
671 +
672 +This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
673 +
674 +---
675 +
676 +## **📄 Download Full Study**
677 +[[Download Full Study>>attach:10.1016_j.intell.2019.101406.pdf]]
678 +
679 +{{/expand}}
680 +
681 +
682 +== Study: A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation ==
683 +{{expand title="Study: A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation" expanded="false"}}
684 +**Source:** *Intelligence (Elsevier)*
685 +**Date of Publication:** *2015*
686 +**Author(s):** *Davide Piffer*
687 +**Title:** *"A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation"*
688 +**DOI:** [10.1016/j.intell.2015.08.008](https://doi.org/10.1016/j.intell.2015.08.008)
689 +**Subject Matter:** *Genetics, Intelligence, GWAS, Population Differences*
690 +
691 +---
692 +
693 +## **Key Statistics**
694 +1. **General Observations:**
695 + - Study analyzed **genome-wide association studies (GWAS) hits** linked to intelligence.
696 + - Found a **strong correlation (r = .91) between polygenic intelligence scores and national IQ levels**.
697 +
698 +2. **Subgroup Analysis:**
699 + - Factor analysis of **9 intelligence-associated alleles** revealed a metagene correlated with **country IQ (r = .86)**.
700 + - **Allele frequencies varied significantly by continent**, aligning with observed population differences in cognitive ability.
701 +
702 +3. **Other Significant Data Points:**
703 + - GWAS intelligence SNPs predicted **IQ levels more strongly than random genetic markers**.
704 + - Genetic differentiation (Fst values) showed that **selection pressure, rather than drift, influenced intelligence-related allele distributions**.
705 +
706 +---
707 +
708 +## **Findings**
709 +1. **Primary Observations:**
710 + - Intelligence-associated SNP frequencies correlate **highly with national IQ levels**.
711 + - Genetic selection for intelligence appears **stronger than selection for height-related genes**.
712 +
713 +2. **Subgroup Trends:**
714 + - **East Asian populations** exhibited the **highest frequencies of intelligence-associated alleles**.
715 + - **African populations** showed lower frequencies compared to European and East Asian populations.
716 +
717 +3. **Specific Case Analysis:**
718 + - Polygenic scores using **intelligence-related alleles significantly outperformed random SNPs** in predicting IQ.
719 + - Selection pressures **may explain differences in global intelligence distribution** beyond genetic drift effects.
720 +
721 +---
722 +
723 +## **Critique and Observations**
724 +1. **Strengths of the Study:**
725 + - **Comprehensive genetic analysis** of intelligence-linked SNPs.
726 + - Uses **multiple statistical methods (factor analysis, Fst analysis) to confirm results**.
727 +
728 +2. **Limitations of the Study:**
729 + - **Correlation does not imply causation**; factors beyond genetics influence intelligence.
730 + - **Limited number of GWAS-identified intelligence alleles**—future studies may identify more.
731 +
732 +3. **Suggestions for Improvement:**
733 + - Larger **cross-population GWAS studies** needed to validate findings.
734 + - Investigate **non-genetic contributors to IQ variance** in addition to genetic factors.
735 +
736 +---
737 +
738 +## **Relevance to Subproject**
739 +- Supports research on **genetic influences on intelligence at a population level**.
740 +- Aligns with broader discussions on **cognitive genetics and natural selection effects**.
741 +- Provides a **quantitative framework for analyzing polygenic selection in intelligence studies**.
742 +
743 +---
744 +
745 +## **Suggestions for Further Exploration**
746 +1. Conduct **expanded GWAS studies** including diverse populations.
747 +2. Investigate **gene-environment interactions influencing intelligence**.
748 +3. Explore **historical selection pressures shaping intelligence-related alleles**.
749 +
750 +---
751 +
752 +## **Summary of Research Study**
753 +This study reviews **genome-wide association study (GWAS) findings on intelligence**, demonstrating a **strong correlation between polygenic intelligence scores and national IQ levels**. The research highlights how **genetic selection may explain population-level cognitive differences beyond genetic drift effects**. Intelligence-linked alleles showed **higher variability across populations than height-related alleles**, suggesting stronger selection pressures.
754 +
755 +This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
756 +
757 +---
758 +
759 +## **📄 Download Full Study**
760 +[[Download Full Study>>attach:10.1016_j.intell.2015.08.008.pdf]]
761 +
762 +{{/expand}}
763 +
764 +== Study: Genetic Structure, Self-Identified Race/Ethnicity, and Confounding ==
765 +{{expand expanded="false" title="Click here to expand details"}}
766 +**Source:** Journal of Genetic Epidemiology
767 +**Date of Publication:** 2024-01-15
768 +**Author(s):** Smith et al.
769 +**Title:** "Genetic Structure, Self-Identified Race/Ethnicity, and Confounding in Case-Control Association Studies"
770 +**DOI:** [https://doi.org/10.1037/1076-8971.11.2.235](https://doi.org/10.1037/1076-8971.11.2.235)
771 +**Subject Matter:** Genetics, Social Science
772 +
773 +**Tags:** `Genetics` `Race & Ethnicity` `Biomedical Research`
774 +
775 +=== **Key Statistics** ===
776 +
777 +1. **General Observations:**
778 + - A near-perfect alignment between self-identified race/ethnicity (SIRE) and genetic ancestry was observed.
779 + - Misclassification rate: **0.14%**.
780 +
781 +2. **Subgroup Analysis:**
782 + - Four groups analyzed: **White, African American, East Asian, and Hispanic**.
783 + - Hispanic genetic clusters showed significant European and Native American lineage.
784 +
785 +=== **Findings** ===
786 +
787 +- Self-identified race strongly aligns with genetic ancestry.
788 +- Minor discrepancies exist but do not significantly impact classification.
789 +
790 +=== **Relevance to Subproject** ===
791 +
792 +- Reinforces the reliability of **self-reported racial identity** in genetic research.
793 +- Highlights **policy considerations** in biomedical studies.
794 +{{/expand}}
795 +
796 +
797 +---
798 +
799 += Dating and Interpersonal Relationships =
800 +
801 +== Study: Trends in Frequency of Sexual Activity and Number of Sexual Partners Among Adults Aged 18 to 44 Years in the US, 2000-2018 ==
136 136  {{expand title="Study: Trends in Frequency of Sexual Activity and Number of Sexual Partners Among Adults Aged 18 to 44 Years in the US, 2000-2018" expanded="false"}}
137 137  **Source:** *JAMA Network Open*
138 138  **Date of Publication:** *2020*
... ... @@ -220,9 +220,91 @@
220 220  
221 221  {{/expand}}
222 222  
223 -{{html}}<hr style="border: 3px solid red;">{{/html}}
224 224  
890 +== Study: Biracial Couples and Adverse Birth Outcomes – A Systematic Review and Meta-Analysis ==
891 +{{expand title="Study: Biracial Couples and Adverse Birth Outcomes – A Systematic Review and Meta-Analysis" expanded="false"}}
892 +**Source:** *Acta Obstetricia et Gynecologica Scandinavica*
893 +**Date of Publication:** *2012*
894 +**Author(s):** *Ravisha M. Srinivasjois, Shreya Shah, Prakesh S. Shah, Knowledge Synthesis Group on Determinants of Preterm/LBW Births*
895 +**Title:** *"Biracial Couples and Adverse Birth Outcomes: A Systematic Review and Meta-Analysis"*
896 +**DOI:** [10.1111/j.1600-0412.2012.01501.x](https://doi.org/10.1111/j.1600-0412.2012.01501.x)
897 +**Subject Matter:** *Neonatal Health, Maternal-Fetal Medicine, Racial Disparities*
225 225  
899 +---
900 +
901 +## **Key Statistics**
902 +1. **General Observations:**
903 + - Meta-analysis of **26,335,596 singleton births** from eight studies.
904 + - **Higher risk of adverse birth outcomes in biracial couples** than White couples, but lower than Black couples.
905 +
906 +2. **Subgroup Analysis:**
907 + - **Maternal race had a stronger influence than paternal race** on birth outcomes.
908 + - **Black mother–White father (BMWF) couples** had a higher risk than **White mother–Black father (WMBF) couples**.
909 +
910 +3. **Other Significant Data Points:**
911 + - **Adjusted Odds Ratios (aORs) for key outcomes:**
912 + - **Low birthweight (LBW):** WMBF (1.21), BMWF (1.75), Black mother–Black father (BMBF) (2.08).
913 + - **Preterm births (PTB):** WMBF (1.17), BMWF (1.37), BMBF (1.78).
914 + - **Stillbirths:** WMBF (1.43), BMWF (1.51), BMBF (1.85).
915 +
916 +---
917 +
918 +## **Findings**
919 +1. **Primary Observations:**
920 + - **Biracial couples face a gradient of risk**: higher than White couples but lower than Black couples.
921 + - **Maternal race plays a more significant role** in pregnancy outcomes.
922 +
923 +2. **Subgroup Trends:**
924 + - **Black mothers (regardless of paternal race) had the highest risk of LBW and PTB**.
925 + - **White mothers with Black fathers had a lower risk** than Black mothers with White fathers.
926 +
927 +3. **Specific Case Analysis:**
928 + - The **weathering hypothesis** suggests that **long-term stress exposure** contributes to higher adverse birth risks in Black mothers.
929 + - **Genetic and environmental factors** may interact to influence birth outcomes.
930 +
931 +---
932 +
933 +## **Critique and Observations**
934 +1. **Strengths of the Study:**
935 + - **Largest meta-analysis** on racial disparities in birth outcomes.
936 + - Uses **adjusted statistical models** to account for confounding variables.
937 +
938 +2. **Limitations of the Study:**
939 + - Data limited to **Black-White biracial couples**, excluding other racial groups.
940 + - **Socioeconomic and healthcare access factors** not fully explored.
941 +
942 +3. **Suggestions for Improvement:**
943 + - Future studies should examine **Asian, Hispanic, and Indigenous biracial couples**.
944 + - Investigate **long-term health effects on infants from biracial pregnancies**.
945 +
946 +---
947 +
948 +## **Relevance to Subproject**
949 +- Provides **critical insights into racial disparities** in maternal and infant health.
950 +- Supports **research on genetic and environmental influences on neonatal health**.
951 +- Highlights **how maternal race plays a more significant role than paternal race** in birth outcomes.
952 +
953 +---
954 +
955 +## **Suggestions for Further Exploration**
956 +1. Investigate **the role of prenatal care quality in mitigating racial disparities**.
957 +2. Examine **how social determinants of health impact biracial pregnancy outcomes**.
958 +3. Explore **gene-environment interactions influencing birthweight and prematurity risks**.
959 +
960 +---
961 +
962 +## **Summary of Research Study**
963 +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**.
964 +
965 +---
966 +
967 +## **📄 Download Full Study**
968 +[[Download Full Study>>attach:10.1111_j.1600-0412.2012.01501.xAbstract.pdf]]
969 +
970 +{{/expand}}
971 +
972 +
973 +== Study: One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness ==
226 226  {{expand title="Study: One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness" expanded="false"}}
227 227  **Source:** *Current Psychology*
228 228  **Date of Publication:** *2024*
... ... @@ -304,145 +304,81 @@
304 304  
305 305  {{/expand}}
306 306  
307 -{{html}}<hr style="border: 3px solid red;">{{/html}}
308 308  
309 -{{expand title="Study: Associations Between Cannabis Use and Mental Health Symptoms in Young Adults" expanded="false"}} Source: Addictive Behaviors
310 -Date of Publication: 2016
311 -Author(s): Andrea Hussong, Christy Capron, Gregory T. Smith, Jennifer L. Maggs
312 -Title: "Associations Between Cannabis Use and Mental Health Symptoms in Young Adults"
313 -DOI: 10.1016/j.addbeh.2016.02.030
314 -Subject Matter: Substance Use, Mental Health, Adolescent Development
1056 += Crime and Substance Abuse =
315 315  
316 -Key Statistics
317 -General Observations:
1058 +== Study: Cross-Cultural Sources of Measurement Error in Substance Use Surveys ==
1059 +{{expand title="Study: Cross-Cultural Sources of Measurement Error in Substance Use Surveys" expanded="false"}}
1060 +**Source:** *Substance Use & Misuse*
1061 +**Date of Publication:** *2003*
1062 +**Author(s):** *Timothy P. Johnson, Phillip J. Bowman*
1063 +**Title:** *"Cross-Cultural Sources of Measurement Error in Substance Use Surveys"*
1064 +**DOI:** [10.1081/JA-120023394](https://doi.org/10.1081/JA-120023394)
1065 +**Subject Matter:** *Survey Methodology, Racial Disparities, Substance Use Research*
318 318  
319 -Study examined cannabis use trends in young adults over time.
320 -Found significant correlations between cannabis use and increased depressive symptoms.
321 -Subgroup Analysis:
322 -
323 -Males exhibited higher rates of cannabis use, but females reported stronger mental health impacts.
324 -Individuals with pre-existing anxiety disorders were more likely to report problematic cannabis use.
325 -Other Significant Data Points:
326 -
327 -Frequent cannabis users showed a 23% higher likelihood of developing anxiety symptoms.
328 -Co-occurring substance use (e.g., alcohol) exacerbated negative psychological effects.
329 -Findings
330 -Primary Observations:
331 -
332 -Cannabis use was linked to higher depressive and anxiety symptoms, particularly in frequent users.
333 -Self-medication patterns emerged among those with pre-existing mental health conditions.
334 -Subgroup Trends:
335 -
336 -Early cannabis initiation (before age 16) was associated with greater mental health risks.
337 -College-aged users reported more impairments in daily functioning due to cannabis use.
338 -Specific Case Analysis:
339 -
340 -Participants with a history of childhood trauma were twice as likely to develop problematic cannabis use.
341 -Co-use of cannabis and alcohol significantly increased impulsivity scores in the study sample.
342 -Critique and Observations
343 -Strengths of the Study:
344 -
345 -Large, longitudinal dataset with a diverse sample of young adults.
346 -Controlled for confounding variables like socioeconomic status and prior substance use.
347 -Limitations of the Study:
348 -
349 -Self-reported cannabis use may introduce bias in reported frequency and effects.
350 -Did not assess specific THC potency levels, which could influence mental health outcomes.
351 -Suggestions for Improvement:
352 -
353 -Future research should investigate dose-dependent effects of cannabis on mental health.
354 -Assess long-term psychological outcomes of early cannabis exposure.
355 -Relevance to Subproject
356 -Supports mental health risk assessment models related to substance use.
357 -Highlights gender differences in substance-related psychological impacts.
358 -Provides insight into self-medication behaviors among young adults.
359 -Suggestions for Further Exploration
360 -Investigate the long-term impact of cannabis use on neurodevelopment.
361 -Examine the role of genetic predisposition in cannabis-related mental health risks.
362 -Assess regional differences in cannabis use trends post-legalization.
363 -Summary of Research Study
364 -This study examines the relationship between cannabis use and mental health symptoms in young adults, focusing on depressive and anxiety-related outcomes. Using a longitudinal dataset, the researchers found higher risks of anxiety and depression in frequent cannabis users, particularly among those with pre-existing mental health conditions or early cannabis initiation.
365 -
366 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
367 -
368 -📄 Download Full Study
369 -[[Download Full Study>>attach:10.1016_j.addbeh.2016.02.030.pdf]]
370 -
371 -{{/expand}}
372 -
373 -{{html}}<hr style="border: 3px solid red;">{{/html}}
374 -
375 -{{expand title="Study: Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time?" expanded="false"}}
376 -**Source:** *Intelligence (Elsevier)*
377 -**Date of Publication:** *2014*
378 -**Author(s):** *Michael A. Woodley, Jan te Nijenhuis, Raegan Murphy*
379 -**Title:** *"Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time?"*
380 -**DOI:** [10.1016/j.intell.2014.05.012](https://doi.org/10.1016/j.intell.2014.05.012)
381 -**Subject Matter:** *Cognitive Decline, Intelligence, Dysgenics*
382 -
383 383  ---
384 384  
385 385  ## **Key Statistics**
386 386  1. **General Observations:**
387 - - The study examines reaction time data from **13 age-matched studies** spanning **1884–2004**.
388 - - Results suggest an estimated **decline of 13.35 IQ points** over this period.
1071 + - Study examined **how racial and cultural factors influence self-reported substance use data**.
1072 + - Analyzed **36 empirical studies from 1977–2003** on survey reliability across racial/ethnic groups.
389 389  
390 390  2. **Subgroup Analysis:**
391 - - The study found **slower reaction times in modern populations** compared to Victorian-era individuals.
392 - - Data from **Western countries (US, UK, Canada, Australia, Finland)** were analyzed.
1075 + - Black and Latino respondents **were more likely to underreport drug use** compared to White respondents.
1076 + - **Cultural stigma and distrust in research institutions** affected self-report accuracy.
393 393  
394 394  3. **Other Significant Data Points:**
395 - - The estimated **dysgenic rate is 1.21 IQ points lost per decade**.
396 - - Meta-regression analysis confirmed a **steady secular trend in slowing reaction time**.
1079 + - **Surveys using biological validation (urinalysis, hair tests) revealed underreporting trends**.
1080 + - **Higher recantation rates** (denying past drug use) were observed among minority respondents.
397 397  
398 398  ---
399 399  
400 400  ## **Findings**
401 401  1. **Primary Observations:**
402 - - Supports the hypothesis of **intelligence decline due to genetic and environmental factors**.
403 - - Reaction time, a **biomarker for cognitive ability**, has slowed significantly over time.
1086 + - Racial/ethnic disparities in **substance use reporting bias survey-based research**.
1087 + - **Social desirability and cultural norms impact data reliability**.
404 404  
405 -2. **Subgroup Trends:**
406 - - A stronger **correlation between slower reaction time and lower general intelligence (g)**.
407 - - Flynn effect (IQ gains) does not contradict this finding, as reaction time is a **biological, not environmental, measure**.
1089 +2. **Subgroup Trends:**
1090 + - White respondents were **more likely to overreport** substance use.
1091 + - Black and Latino respondents **had higher recantation rates**, particularly in face-to-face interviews.
408 408  
409 -3. **Specific Case Analysis:**
410 - - Cross-national comparisons indicate a **global trend in slower reaction times**.
411 - - Factors like **modern neurotoxin exposure** and **reduced selective pressure for intelligence** may contribute.
1093 +3. **Specific Case Analysis:**
1094 + - Mode of survey administration **significantly influenced reporting accuracy**.
1095 + - **Self-administered surveys produced more reliable data than interviewer-administered surveys**.
412 412  
413 413  ---
414 414  
415 415  ## **Critique and Observations**
416 -1. **Strengths of the Study:**
417 - - **Comprehensive meta-analysis** covering over a century of reaction time data.
418 - - **Robust statistical corrections** for measurement variance between historical and modern studies.
1100 +1. **Strengths of the Study:**
1101 + - **Comprehensive review of 36 studies** on measurement error in substance use reporting.
1102 + - Identifies **systemic biases affecting racial/ethnic survey reliability**.
419 419  
420 -2. **Limitations of the Study:**
421 - - Some historical data sources **lack methodological consistency**.
422 - - **Reaction time measurements vary by study**, requiring adjustments for equipment differences.
1104 +2. **Limitations of the Study:**
1105 + - Relies on **secondary data analysis**, limiting direct experimental control.
1106 + - Does not explore **how measurement error impacts policy decisions**.
423 423  
424 -3. **Suggestions for Improvement:**
425 - - Future studies should **replicate results with more modern datasets**.
426 - - Investigate **alternative cognitive biomarkers** for intelligence over time.
1108 +3. **Suggestions for Improvement:**
1109 + - Future research should **incorporate mixed-method approaches** (qualitative & quantitative).
1110 + - Investigate **how survey design can reduce racial reporting disparities**.
427 427  
428 428  ---
429 429  
430 430  ## **Relevance to Subproject**
431 -- Provides evidence for **long-term intelligence trends**, contributing to research on **cognitive evolution**.
432 -- Aligns with broader discussions on **dysgenics, neurophysiology, and cognitive load**.
433 -- Supports the argument that **modern societies may be experiencing intelligence decline**.
1115 +- Supports research on **racial disparities in self-reported health behaviors**.
1116 +- Highlights **survey methodology issues that impact substance use epidemiology**.
1117 +- Provides insights for **improving data accuracy in public health research**.
434 434  
435 435  ---
436 436  
437 437  ## **Suggestions for Further Exploration**
438 -1. Investigate **genetic markers associated with reaction time** and intelligence decline.
439 -2. Examine **regional variations in reaction time trends**.
440 -3. Explore **cognitive resilience factors that counteract the decline**.
1122 +1. Investigate **how survey design impacts racial disparities in self-reported health data**.
1123 +2. Study **alternative data collection methods (biometric validation, passive data tracking)**.
1124 +3. Explore **the role of social stigma in self-reported health behaviors**.
441 441  
442 442  ---
443 443  
444 444  ## **Summary of Research Study**
445 -This study examines **historical reaction time data** as a measure of **cognitive ability and intelligence decline**, analyzing data from **Western populations between 1884 and 2004**. The results suggest a **measurable decline in intelligence, estimated at 13.35 IQ points**, likely due to **dysgenic fertility, neurophysiological factors, and reduced selection pressures**.
1129 +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**.
446 446  
447 447  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
448 448  
... ... @@ -449,83 +449,82 @@
449 449  ---
450 450  
451 451  ## **📄 Download Full Study**
452 -[[Download Full Study>>attach:10.1016_j.intell.2014.05.012.pdf]]
1136 +[[Download Full Study>>attach:10.1081_JA-120023394.pdf]]
453 453  
454 454  {{/expand}}
455 455  
456 -{{html}}<hr style="border: 3px solid red;">{{/html}}
1140 +== Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program ==
1141 +{{expand title="Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program" expanded="false"}}
1142 +**Source:** *Substance Use & Misuse*
1143 +**Date of Publication:** *2002*
1144 +**Author(s):** *Clifford A. Butzin, Christine A. Saum, Frank R. Scarpitti*
1145 +**Title:** *"Factors Associated with Completion of a Drug Treatment Court Diversion Program"*
1146 +**DOI:** [10.1081/JA-120014424](https://doi.org/10.1081/JA-120014424)
1147 +**Subject Matter:** *Substance Use, Criminal Justice, Drug Courts*
457 457  
458 -{{expand title="Study: A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation" expanded="false"}}
459 -**Source:** *Intelligence (Elsevier)*
460 -**Date of Publication:** *2015*
461 -**Author(s):** *Davide Piffer*
462 -**Title:** *"A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation"*
463 -**DOI:** [10.1016/j.intell.2015.08.008](https://doi.org/10.1016/j.intell.2015.08.008)
464 -**Subject Matter:** *Genetics, Intelligence, GWAS, Population Differences*
465 -
466 466  ---
467 467  
468 468  ## **Key Statistics**
469 469  1. **General Observations:**
470 - - Study analyzed **genome-wide association studies (GWAS) hits** linked to intelligence.
471 - - Found a **strong correlation (r = .91) between polygenic intelligence scores and national IQ levels**.
1153 + - Study examined **drug treatment court success rates** among first-time offenders.
1154 + - Strongest predictors of **successful completion were employment status and race**.
472 472  
473 473  2. **Subgroup Analysis:**
474 - - Factor analysis of **9 intelligence-associated alleles** revealed a metagene correlated with **country IQ (r = .86)**.
475 - - **Allele frequencies varied significantly by continent**, aligning with observed population differences in cognitive ability.
1157 + - Individuals with **stable jobs were more likely to complete the program**.
1158 + - **Black participants had lower success rates**, suggesting potential systemic disparities.
476 476  
477 477  3. **Other Significant Data Points:**
478 - - GWAS intelligence SNPs predicted **IQ levels more strongly than random genetic markers**.
479 - - Genetic differentiation (Fst values) showed that **selection pressure, rather than drift, influenced intelligence-related allele distributions**.
1161 + - **Education level was positively correlated** with program completion.
1162 + - Frequency of **drug use before enrollment affected treatment outcomes**.
480 480  
481 481  ---
482 482  
483 483  ## **Findings**
484 484  1. **Primary Observations:**
485 - - Intelligence-associated SNP frequencies correlate **highly with national IQ levels**.
486 - - Genetic selection for intelligence appears **stronger than selection for height-related genes**.
1168 + - **Social stability factors** (employment, education) were key to treatment success.
1169 + - **Race and pre-existing substance use patterns** influenced completion rates.
487 487  
488 488  2. **Subgroup Trends:**
489 - - **East Asian populations** exhibited the **highest frequencies of intelligence-associated alleles**.
490 - - **African populations** showed lower frequencies compared to European and East Asian populations.
1172 + - White offenders had **higher completion rates** than Black offenders.
1173 + - Drug court success was **higher for those with lower initial drug use frequency**.
491 491  
492 492  3. **Specific Case Analysis:**
493 - - Polygenic scores using **intelligence-related alleles significantly outperformed random SNPs** in predicting IQ.
494 - - Selection pressures **may explain differences in global intelligence distribution** beyond genetic drift effects.
1176 + - **Individuals with strong social ties were more likely to finish the program**.
1177 + - Success rates were **significantly higher for participants with case management support**.
495 495  
496 496  ---
497 497  
498 498  ## **Critique and Observations**
499 499  1. **Strengths of the Study:**
500 - - **Comprehensive genetic analysis** of intelligence-linked SNPs.
501 - - Uses **multiple statistical methods (factor analysis, Fst analysis) to confirm results**.
1183 + - **First empirical study on drug court program success factors**.
1184 + - Uses **longitudinal data** for post-treatment analysis.
502 502  
503 503  2. **Limitations of the Study:**
504 - - **Correlation does not imply causation**; factors beyond genetics influence intelligence.
505 - - **Limited number of GWAS-identified intelligence alleles**—future studies may identify more.
1187 + - Lacks **qualitative data on personal motivation and treatment engagement**.
1188 + - Focuses on **short-term program success** without tracking **long-term relapse rates**.
506 506  
507 507  3. **Suggestions for Improvement:**
508 - - Larger **cross-population GWAS studies** needed to validate findings.
509 - - Investigate **non-genetic contributors to IQ variance** in addition to genetic factors.
1191 + - Future research should examine **racial disparities in drug court outcomes**.
1192 + - Study **how community resources impact long-term recovery**.
510 510  
511 511  ---
512 512  
513 513  ## **Relevance to Subproject**
514 -- Supports research on **genetic influences on intelligence at a population level**.
515 -- Aligns with broader discussions on **cognitive genetics and natural selection effects**.
516 -- Provides a **quantitative framework for analyzing polygenic selection in intelligence studies**.
1197 +- Provides insight into **what factors contribute to drug court program success**.
1198 +- Highlights **racial disparities in criminal justice-based rehabilitation programs**.
1199 +- Supports **policy discussions on improving access to drug treatment for marginalized groups**.
517 517  
518 518  ---
519 519  
520 520  ## **Suggestions for Further Exploration**
521 -1. Conduct **expanded GWAS studies** including diverse populations.
522 -2. Investigate **gene-environment interactions influencing intelligence**.
523 -3. Explore **historical selection pressures shaping intelligence-related alleles**.
1204 +1. Investigate **the role of mental health in drug court success rates**.
1205 +2. Assess **long-term relapse prevention strategies post-treatment**.
1206 +3. Explore **alternative diversion programs beyond traditional drug courts**.
524 524  
525 525  ---
526 526  
527 527  ## **Summary of Research Study**
528 -This study reviews **genome-wide association study (GWAS) findings on intelligence**, demonstrating a **strong correlation between polygenic intelligence scores and national IQ levels**. The research highlights how **genetic selection may explain population-level cognitive differences beyond genetic drift effects**. Intelligence-linked alleles showed **higher variability across populations than height-related alleles**, suggesting stronger selection pressures.
1211 +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**.
529 529  
530 530  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
531 531  
... ... @@ -532,83 +532,82 @@
532 532  ---
533 533  
534 534  ## **📄 Download Full Study**
535 -[[Download Full Study>>attach:10.1016_j.intell.2015.08.008.pdf]]
1218 +[[Download Full Study>>attach:10.1081_JA-120014424.pdf]]
536 536  
537 537  {{/expand}}
538 538  
539 -{{html}}<hr style="border: 3px solid red;">{{/html}}
1222 +== Study: Cross-Cultural Sources of Measurement Error in Substance Use Surveys ==
1223 +{{expand title="Study: Cross-Cultural Sources of Measurement Error in Substance Use Surveys" expanded="false"}}
1224 +**Source:** *Substance Use & Misuse*
1225 +**Date of Publication:** *2003*
1226 +**Author(s):** *Timothy P. Johnson, Phillip J. Bowman*
1227 +**Title:** *"Cross-Cultural Sources of Measurement Error in Substance Use Surveys"*
1228 +**DOI:** [10.1081/JA-120023394](https://doi.org/10.1081/JA-120023394)
1229 +**Subject Matter:** *Survey Methodology, Racial Disparities, Substance Use Research*
540 540  
541 -{{expand title="Study: Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media" expanded="false"}}
542 -**Source:** *Intelligence (Elsevier)*
543 -**Date of Publication:** *2019*
544 -**Author(s):** *Heiner Rindermann, David Becker, Thomas R. Coyle*
545 -**Title:** *"Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media"*
546 -**DOI:** [10.1016/j.intell.2019.101406](https://doi.org/10.1016/j.intell.2019.101406)
547 -**Subject Matter:** *Psychology, Intelligence Research, Expert Analysis*
548 -
549 549  ---
550 550  
551 551  ## **Key Statistics**
552 552  1. **General Observations:**
553 - - Survey of **102 experts** on intelligence research and public discourse.
554 - - Evaluated experts' backgrounds, political affiliations, and views on controversial topics in intelligence research.
1235 + - Study examined **how racial and cultural factors influence self-reported substance use data**.
1236 + - Analyzed **36 empirical studies from 1977–2003** on survey reliability across racial/ethnic groups.
555 555  
556 556  2. **Subgroup Analysis:**
557 - - **90% of experts were from Western countries**, and **83% were male**.
558 - - Political spectrum ranged from **54% left-liberal, 24% conservative**, with significant ideological influences on views.
1239 + - Black and Latino respondents **were more likely to underreport drug use** compared to White respondents.
1240 + - **Cultural stigma and distrust in research institutions** affected self-report accuracy.
559 559  
560 560  3. **Other Significant Data Points:**
561 - - Experts rated media coverage of intelligence research as **poor (avg. 3.1 on a 9-point scale)**.
562 - - **50% of experts attributed US Black-White IQ differences to genetic factors, 50% to environmental factors**.
1243 + - **Surveys using biological validation (urinalysis, hair tests) revealed underreporting trends**.
1244 + - **Higher recantation rates** (denying past drug use) were observed among minority respondents.
563 563  
564 564  ---
565 565  
566 566  ## **Findings**
567 567  1. **Primary Observations:**
568 - - Experts overwhelmingly support **the g-factor theory of intelligence**.
569 - - **Heritability of intelligence** was widely accepted, though views differed on race and group differences.
1250 + - Racial/ethnic disparities in **substance use reporting bias survey-based research**.
1251 + - **Social desirability and cultural norms impact data reliability**.
570 570  
571 -2. **Subgroup Trends:**
572 - - **Left-leaning experts were more likely to reject genetic explanations for group IQ differences**.
573 - - **Right-leaning experts tended to favor a stronger role for genetic factors** in intelligence disparities.
1253 +2. **Subgroup Trends:**
1254 + - White respondents were **more likely to overreport** substance use.
1255 + - Black and Latino respondents **had higher recantation rates**, particularly in face-to-face interviews.
574 574  
575 -3. **Specific Case Analysis:**
576 - - The study compared **media coverage of intelligence research** with expert opinions.
577 - - Found a **disconnect between journalists and intelligence researchers**, especially regarding politically sensitive issues.
1257 +3. **Specific Case Analysis:**
1258 + - Mode of survey administration **significantly influenced reporting accuracy**.
1259 + - **Self-administered surveys produced more reliable data than interviewer-administered surveys**.
578 578  
579 579  ---
580 580  
581 581  ## **Critique and Observations**
582 -1. **Strengths of the Study:**
583 - - **Largest expert survey on intelligence research** to date.
584 - - Provides insight into **how political orientation influences scientific perspectives**.
1264 +1. **Strengths of the Study:**
1265 + - **Comprehensive review of 36 studies** on measurement error in substance use reporting.
1266 + - Identifies **systemic biases affecting racial/ethnic survey reliability**.
585 585  
586 -2. **Limitations of the Study:**
587 - - **Sample primarily from Western countries**, limiting global perspectives.
588 - - Self-selection bias may skew responses toward **those more willing to engage with controversial topics**.
1268 +2. **Limitations of the Study:**
1269 + - Relies on **secondary data analysis**, limiting direct experimental control.
1270 + - Does not explore **how measurement error impacts policy decisions**.
589 589  
590 -3. **Suggestions for Improvement:**
591 - - Future studies should include **a broader range of global experts**.
592 - - Additional research needed on **media biases and misrepresentation of intelligence research**.
1272 +3. **Suggestions for Improvement:**
1273 + - Future research should **incorporate mixed-method approaches** (qualitative & quantitative).
1274 + - Investigate **how survey design can reduce racial reporting disparities**.
593 593  
594 594  ---
595 595  
596 596  ## **Relevance to Subproject**
597 -- Provides insight into **expert consensus and division on intelligence research**.
598 -- Highlights the **role of media bias** in shaping public perception of intelligence science.
599 -- Useful for understanding **the intersection of science, politics, and public discourse** on intelligence research.
1279 +- Supports research on **racial disparities in self-reported health behaviors**.
1280 +- Highlights **survey methodology issues that impact substance use epidemiology**.
1281 +- Provides insights for **improving data accuracy in public health research**.
600 600  
601 601  ---
602 602  
603 603  ## **Suggestions for Further Exploration**
604 -1. Examine **cross-national differences** in expert opinions on intelligence.
605 -2. Investigate how **media bias impacts public understanding of intelligence research**.
606 -3. Conduct follow-up studies with **a more diverse expert pool** to test findings.
1286 +1. Investigate **how survey design impacts racial disparities in self-reported health data**.
1287 +2. Study **alternative data collection methods (biometric validation, passive data tracking)**.
1288 +3. Explore **the role of social stigma in self-reported health behaviors**.
607 607  
608 608  ---
609 609  
610 610  ## **Summary of Research Study**
611 -This study surveys **expert opinions on intelligence research**, analyzing **how backgrounds, political ideologies, and media representation influence perspectives on intelligence**. The findings highlight **divisions in scientific consensus**, particularly on **genetic vs. environmental causes of IQ disparities**. Additionally, the research uncovers **widespread dissatisfaction with media portrayals of intelligence research**, pointing to **the impact of ideological biases on public discourse**.
1293 +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**.
612 612  
613 613  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
614 614  
... ... @@ -615,83 +615,83 @@
615 615  ---
616 616  
617 617  ## **📄 Download Full Study**
618 -[[Download Full Study>>attach:10.1016_j.intell.2019.101406.pdf]]
1300 +[[Download Full Study>>attach:10.1081_JA-120023394.pdf]]
619 619  
620 620  {{/expand}}
621 621  
622 -{{html}}<hr style="border: 3px solid red;">{{/html}}
623 623  
624 -{{expand title="Study: Is Homo sapiens polytypic? Human taxonomic diversity and its implications" expanded="false"}}
625 -**Source:** *Medical Hypotheses (Elsevier)*
626 -**Date of Publication:** *2010*
627 -**Author(s):** *Michael A. Woodley*
628 -**Title:** *"Is Homo sapiens polytypic? Human taxonomic diversity and its implications"*
629 -**DOI:** [10.1016/j.mehy.2009.07.046](https://doi.org/10.1016/j.mehy.2009.07.046)
630 -**Subject Matter:** *Human Taxonomy, Evolutionary Biology, Anthropology*
1305 +== Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program ==
1306 +{{expand title="Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program" expanded="false"}}
1307 +**Source:** *Substance Use & Misuse*
1308 +**Date of Publication:** *2002*
1309 +**Author(s):** *Clifford A. Butzin, Christine A. Saum, Frank R. Scarpitti*
1310 +**Title:** *"Factors Associated with Completion of a Drug Treatment Court Diversion Program"*
1311 +**DOI:** [10.1081/JA-120014424](https://doi.org/10.1081/JA-120014424)
1312 +**Subject Matter:** *Substance Use, Criminal Justice, Drug Courts*
631 631  
632 632  ---
633 633  
634 634  ## **Key Statistics**
635 635  1. **General Observations:**
636 - - The study argues that **Homo sapiens is polytypic**, meaning it consists of multiple subspecies rather than a single monotypic species.
637 - - Examines **genetic diversity, morphological variation, and evolutionary lineage** in humans.
1318 + - Study examined **drug treatment court success rates** among first-time offenders.
1319 + - Strongest predictors of **successful completion were employment status and race**.
638 638  
639 639  2. **Subgroup Analysis:**
640 - - Discusses **four primary definitions of race/subspecies**: Essentialist, Taxonomic, Population-based, and Lineage-based.
641 - - Suggests that **human heterozygosity levels are comparable to species that are classified as polytypic**.
1322 + - Individuals with **stable jobs were more likely to complete the program**.
1323 + - **Black participants had lower success rates**, suggesting potential systemic disparities.
642 642  
643 643  3. **Other Significant Data Points:**
644 - - The study evaluates **FST values (genetic differentiation measure)** and argues that human genetic differentiation is comparable to that of recognized subspecies in other species.
645 - - Considers **phylogenetic species concepts** in defining human variation.
1326 + - **Education level was positively correlated** with program completion.
1327 + - Frequency of **drug use before enrollment affected treatment outcomes**.
646 646  
647 647  ---
648 648  
649 649  ## **Findings**
650 650  1. **Primary Observations:**
651 - - Proposes that **modern human populations meet biological criteria for subspecies classification**.
652 - - Highlights **medical and evolutionary implications** of human taxonomic diversity.
1333 + - **Social stability factors** (employment, education) were key to treatment success.
1334 + - **Race and pre-existing substance use patterns** influenced completion rates.
653 653  
654 654  2. **Subgroup Trends:**
655 - - Discusses **how race concepts evolved over time** in biological sciences.
656 - - Compares **human diversity with that of other primates** such as chimpanzees and gorillas.
1337 + - White offenders had **higher completion rates** than Black offenders.
1338 + - Drug court success was **higher for those with lower initial drug use frequency**.
657 657  
658 658  3. **Specific Case Analysis:**
659 - - Evaluates how **genetic markers correlate with population structure**.
660 - - Addresses the **controversy over race classification in modern anthropology**.
1341 + - **Individuals with strong social ties were more likely to finish the program**.
1342 + - Success rates were **significantly higher for participants with case management support**.
661 661  
662 662  ---
663 663  
664 664  ## **Critique and Observations**
665 665  1. **Strengths of the Study:**
666 - - Uses **comparative species analysis** to assess human classification.
667 - - Provides a **biological perspective** on the race concept, moving beyond social constructivism arguments.
1348 + - **First empirical study on drug court program success factors**.
1349 + - Uses **longitudinal data** for post-treatment analysis.
668 668  
669 669  2. **Limitations of the Study:**
670 - - Controversial topic with **strong opposing views in anthropology and genetics**.
671 - - **Relies on broad genetic trends**, but does not analyze individual-level genetic variation in depth.
1352 + - Lacks **qualitative data on personal motivation and treatment engagement**.
1353 + - Focuses on **short-term program success** without tracking **long-term relapse rates**.
672 672  
673 673  3. **Suggestions for Improvement:**
674 - - Further research should **incorporate whole-genome studies** to refine subspecies classifications.
675 - - Investigate **how admixture affects taxonomic classification over time**.
1356 + - Future research should examine **racial disparities in drug court outcomes**.
1357 + - Study **how community resources impact long-term recovery**.
676 676  
677 677  ---
678 678  
679 679  ## **Relevance to Subproject**
680 -- Contributes to discussions on **evolutionary taxonomy and species classification**.
681 -- Provides evidence on **genetic differentiation among human populations**.
682 -- Highlights **historical and contemporary scientific debates on race and human variation**.
1362 +- Provides insight into **what factors contribute to drug court program success**.
1363 +- Highlights **racial disparities in criminal justice-based rehabilitation programs**.
1364 +- Supports **policy discussions on improving access to drug treatment for marginalized groups**.
683 683  
684 684  ---
685 685  
686 686  ## **Suggestions for Further Exploration**
687 -1. Examine **FST values in modern and ancient human populations**.
688 -2. Investigate how **adaptive evolution influences population differentiation**.
689 -3. Explore **the impact of genetic diversity on medical treatments and disease susceptibility**.
1369 +1. Investigate **the role of mental health in drug court success rates**.
1370 +2. Assess **long-term relapse prevention strategies post-treatment**.
1371 +3. Explore **alternative diversion programs beyond traditional drug courts**.
690 690  
691 691  ---
692 692  
693 693  ## **Summary of Research Study**
694 -This study evaluates **whether Homo sapiens should be classified as a polytypic species**, analyzing **genetic diversity, evolutionary lineage, and morphological variation**. Using comparative analysis with other primates and mammals, the research suggests that **human populations meet biological criteria for subspecies classification**, with implications for **evolutionary biology, anthropology, and medicine**.
1376 +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**.
695 695  
696 696  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
697 697  
... ... @@ -698,83 +698,148 @@
698 698  ---
699 699  
700 700  ## **📄 Download Full Study**
701 -[[Download Full Study>>attach:10.1016_j.mehy.2009.07.046.pdf]]
1383 +[[Download Full Study>>attach:10.1081_JA-120014424.pdf]]
702 702  
703 703  {{/expand}}
704 704  
705 -{{html}}<hr style="border: 3px solid red;">{{/html}}
1387 +== Study: Associations Between Cannabis Use and Mental Health Symptoms in Young Adults ==
1388 +{{expand title="Study: Associations Between Cannabis Use and Mental Health Symptoms in Young Adults" expanded="false"}} Source: Addictive Behaviors
1389 +Date of Publication: 2016
1390 +Author(s): Andrea Hussong, Christy Capron, Gregory T. Smith, Jennifer L. Maggs
1391 +Title: "Associations Between Cannabis Use and Mental Health Symptoms in Young Adults"
1392 +DOI: 10.1016/j.addbeh.2016.02.030
1393 +Subject Matter: Substance Use, Mental Health, Adolescent Development
706 706  
707 -{{expand title="Study: The Wilson Effect: The Increase in Heritability of IQ With Age" expanded="false"}}
708 -**Source:** *Twin Research and Human Genetics (Cambridge University Press)*
709 -**Date of Publication:** *2013*
710 -**Author(s):** *Thomas J. Bouchard Jr.*
711 -**Title:** *"The Wilson Effect: The Increase in Heritability of IQ With Age"*
712 -**DOI:** [10.1017/thg.2013.54](https://doi.org/10.1017/thg.2013.54)
713 -**Subject Matter:** *Intelligence, Heritability, Developmental Psychology*
1395 +Key Statistics
1396 +General Observations:
714 714  
1398 +Study examined cannabis use trends in young adults over time.
1399 +Found significant correlations between cannabis use and increased depressive symptoms.
1400 +Subgroup Analysis:
1401 +
1402 +Males exhibited higher rates of cannabis use, but females reported stronger mental health impacts.
1403 +Individuals with pre-existing anxiety disorders were more likely to report problematic cannabis use.
1404 +Other Significant Data Points:
1405 +
1406 +Frequent cannabis users showed a 23% higher likelihood of developing anxiety symptoms.
1407 +Co-occurring substance use (e.g., alcohol) exacerbated negative psychological effects.
1408 +Findings
1409 +Primary Observations:
1410 +
1411 +Cannabis use was linked to higher depressive and anxiety symptoms, particularly in frequent users.
1412 +Self-medication patterns emerged among those with pre-existing mental health conditions.
1413 +Subgroup Trends:
1414 +
1415 +Early cannabis initiation (before age 16) was associated with greater mental health risks.
1416 +College-aged users reported more impairments in daily functioning due to cannabis use.
1417 +Specific Case Analysis:
1418 +
1419 +Participants with a history of childhood trauma were twice as likely to develop problematic cannabis use.
1420 +Co-use of cannabis and alcohol significantly increased impulsivity scores in the study sample.
1421 +Critique and Observations
1422 +Strengths of the Study:
1423 +
1424 +Large, longitudinal dataset with a diverse sample of young adults.
1425 +Controlled for confounding variables like socioeconomic status and prior substance use.
1426 +Limitations of the Study:
1427 +
1428 +Self-reported cannabis use may introduce bias in reported frequency and effects.
1429 +Did not assess specific THC potency levels, which could influence mental health outcomes.
1430 +Suggestions for Improvement:
1431 +
1432 +Future research should investigate dose-dependent effects of cannabis on mental health.
1433 +Assess long-term psychological outcomes of early cannabis exposure.
1434 +Relevance to Subproject
1435 +Supports mental health risk assessment models related to substance use.
1436 +Highlights gender differences in substance-related psychological impacts.
1437 +Provides insight into self-medication behaviors among young adults.
1438 +Suggestions for Further Exploration
1439 +Investigate the long-term impact of cannabis use on neurodevelopment.
1440 +Examine the role of genetic predisposition in cannabis-related mental health risks.
1441 +Assess regional differences in cannabis use trends post-legalization.
1442 +Summary of Research Study
1443 +This study examines the relationship between cannabis use and mental health symptoms in young adults, focusing on depressive and anxiety-related outcomes. Using a longitudinal dataset, the researchers found higher risks of anxiety and depression in frequent cannabis users, particularly among those with pre-existing mental health conditions or early cannabis initiation.
1444 +
1445 +This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1446 +
1447 +📄 Download Full Study
1448 +[[Download Full Study>>attach:10.1016_j.addbeh.2016.02.030.pdf]]
1449 +
1450 +{{/expand}}
1451 +
1452 +
1453 +== Study: Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time? ==
1454 +{{expand title="Study: Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time?" expanded="false"}}
1455 +**Source:** *Intelligence (Elsevier)*
1456 +**Date of Publication:** *2014*
1457 +**Author(s):** *Michael A. Woodley, Jan te Nijenhuis, Raegan Murphy*
1458 +**Title:** *"Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time?"*
1459 +**DOI:** [10.1016/j.intell.2014.05.012](https://doi.org/10.1016/j.intell.2014.05.012)
1460 +**Subject Matter:** *Cognitive Decline, Intelligence, Dysgenics*
1461 +
715 715  ---
716 716  
717 717  ## **Key Statistics**
718 718  1. **General Observations:**
719 - - The study documents how the **heritability of IQ increases with age**, reaching an asymptote at **0.80 by adulthood**.
720 - - Analysis is based on **longitudinal twin and adoption studies**.
1466 + - The study examines reaction time data from **13 age-matched studies** spanning **1884–2004**.
1467 + - Results suggest an estimated **decline of 13.35 IQ points** over this period.
721 721  
722 722  2. **Subgroup Analysis:**
723 - - Shared environmental influence on IQ **declines with age**, reaching **0.10 in adulthood**.
724 - - Monozygotic twins show **increasing genetic similarity in IQ over time**, while dizygotic twins become **less concordant**.
1470 + - The study found **slower reaction times in modern populations** compared to Victorian-era individuals.
1471 + - Data from **Western countries (US, UK, Canada, Australia, Finland)** were analyzed.
725 725  
726 726  3. **Other Significant Data Points:**
727 - - Data from the **Louisville Longitudinal Twin Study and cross-national twin samples** support findings.
728 - - IQ stability over time is **influenced more by genetics than by shared environmental factors**.
1474 + - The estimated **dysgenic rate is 1.21 IQ points lost per decade**.
1475 + - Meta-regression analysis confirmed a **steady secular trend in slowing reaction time**.
729 729  
730 730  ---
731 731  
732 732  ## **Findings**
733 733  1. **Primary Observations:**
734 - - Intelligence heritability **strengthens throughout development**, contrary to early environmental models.
735 - - Shared environmental effects **decrease by late adolescence**, emphasizing **genetic influence in adulthood**.
1481 + - Supports the hypothesis of **intelligence decline due to genetic and environmental factors**.
1482 + - Reaction time, a **biomarker for cognitive ability**, has slowed significantly over time.
736 736  
737 737  2. **Subgroup Trends:**
738 - - Studies from **Scotland, Netherlands, and the US** show **consistent patterns of increasing heritability with age**.
739 - - Findings hold across **varied socio-economic and educational backgrounds**.
1485 + - A stronger **correlation between slower reaction time and lower general intelligence (g)**.
1486 + - Flynn effect (IQ gains) does not contradict this finding, as reaction time is a **biological, not environmental, measure**.
740 740  
741 741  3. **Specific Case Analysis:**
742 - - Longitudinal adoption studies show **declining impact of adoptive parental influence on IQ** as children age.
743 - - Cross-sectional twin data confirm **higher IQ correlations for monozygotic twins in adulthood**.
1489 + - Cross-national comparisons indicate a **global trend in slower reaction times**.
1490 + - Factors like **modern neurotoxin exposure** and **reduced selective pressure for intelligence** may contribute.
744 744  
745 745  ---
746 746  
747 747  ## **Critique and Observations**
748 748  1. **Strengths of the Study:**
749 - - **Robust dataset covering multiple twin and adoption studies over decades**.
750 - - **Clear, replicable trend** demonstrating the increasing role of genetics in intelligence.
1496 + - **Comprehensive meta-analysis** covering over a century of reaction time data.
1497 + - **Robust statistical corrections** for measurement variance between historical and modern studies.
751 751  
752 752  2. **Limitations of the Study:**
753 - - Findings apply primarily to **Western industrialized nations**, limiting generalizability.
754 - - **Lack of neurobiological mechanisms** explaining how genes express their influence over time.
1500 + - Some historical data sources **lack methodological consistency**.
1501 + - **Reaction time measurements vary by study**, requiring adjustments for equipment differences.
755 755  
756 756  3. **Suggestions for Improvement:**
757 - - Future research should investigate **gene-environment interactions in cognitive aging**.
758 - - Examine **heritability trends in non-Western populations** to determine cross-cultural consistency.
1504 + - Future studies should **replicate results with more modern datasets**.
1505 + - Investigate **alternative cognitive biomarkers** for intelligence over time.
759 759  
760 760  ---
761 761  
762 762  ## **Relevance to Subproject**
763 -- Provides **strong evidence for the genetic basis of intelligence**.
764 -- Highlights the **diminishing role of shared environment in cognitive development**.
765 -- Supports research on **cognitive aging and heritability across the lifespan**.
1510 +- Provides evidence for **long-term intelligence trends**, contributing to research on **cognitive evolution**.
1511 +- Aligns with broader discussions on **dysgenics, neurophysiology, and cognitive load**.
1512 +- Supports the argument that **modern societies may be experiencing intelligence decline**.
766 766  
767 767  ---
768 768  
769 769  ## **Suggestions for Further Exploration**
770 -1. Investigate **neurogenetic pathways underlying IQ development**.
771 -2. Examine **how education and socioeconomic factors interact with genetic IQ influences**.
772 -3. Study **heritability trends in aging populations and cognitive decline**.
1517 +1. Investigate **genetic markers associated with reaction time** and intelligence decline.
1518 +2. Examine **regional variations in reaction time trends**.
1519 +3. Explore **cognitive resilience factors that counteract the decline**.
773 773  
774 774  ---
775 775  
776 776  ## **Summary of Research Study**
777 -This study documents **The Wilson Effect**, demonstrating how the **heritability of IQ increases throughout development**, reaching a plateau of **0.80 by adulthood**. The findings indicate that **shared environmental effects diminish with age**, while **genetic influences on intelligence strengthen**. Using **longitudinal twin and adoption data**, the research provides **strong empirical support for the increasing role of genetics in cognitive ability over time**.
1524 +This study examines **historical reaction time data** as a measure of **cognitive ability and intelligence decline**, analyzing data from **Western populations between 1884 and 2004**. The results suggest a **measurable decline in intelligence, estimated at 13.35 IQ points**, likely due to **dysgenic fertility, neurophysiological factors, and reduced selection pressures**.
778 778  
779 779  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
780 780  
... ... @@ -781,12 +781,17 @@
781 781  ---
782 782  
783 783  ## **📄 Download Full Study**
784 -[[Download Full Study>>attach:10.1017_thg.2013.54.pdf]]
1531 +[[Download Full Study>>attach:10.1016_j.intell.2014.05.012.pdf]]
785 785  
786 786  {{/expand}}
787 787  
788 -{{html}}<hr style="border: 3px solid red;">{{/html}}
789 789  
1536 +
1537 +
1538 +
1539 += Whiteness =
1540 +
1541 +== Study: Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports ==
790 790  {{expand title="Study: Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports" expanded="false"}}
791 791  **Source:** *Journal of Diversity in Higher Education*
792 792  **Date of Publication:** *2019*
... ... @@ -868,79 +868,84 @@
868 868  
869 869  {{/expand}}
870 870  
871 -{{html}}<hr style="border: 3px solid red;">{{/html}}
872 872  
873 -{{expand title="Study: Reconstructing Indian Population History" expanded="false"}}
874 -**Source:** *Nature*
875 -**Date of Publication:** *2009*
876 -**Author(s):** *David Reich, Kumarasamy Thangaraj, Nick Patterson, Alkes L. Price, Lalji Singh*
877 -**Title:** *"Reconstructing Indian Population History"*
878 -**DOI:** [10.1038/nature08365](https://doi.org/10.1038/nature08365)
879 -**Subject Matter:** *Genetics, Population History, South Asian Ancestry*
880 880  
1625 +
1626 +
1627 += White Guilt =
1628 +
1629 +== Study: Racial Bias in Pain Assessment and Treatment Recommendations ==
1630 +{{expand title="Study: Racial Bias in Pain Assessment and Treatment Recommendations" expanded="false"}}
1631 +**Source:** *Proceedings of the National Academy of Sciences (PNAS)*
1632 +**Date of Publication:** *2016*
1633 +**Author(s):** *Kelly M. Hoffman, Sophie Trawalter, Jordan R. Axta, M. Norman Oliver*
1634 +**Title:** *"Racial Bias in Pain Assessment and Treatment Recommendations, and False Beliefs About Biological Differences Between Blacks and Whites"*
1635 +**DOI:** [10.1073/pnas.1516047113](https://doi.org/10.1073/pnas.1516047113)
1636 +**Subject Matter:** *Health Disparities, Racial Bias, Medical Treatment*
1637 +
881 881  ---
882 882  
883 883  ## **Key Statistics**
884 884  1. **General Observations:**
885 - - Study analyzed **132 individuals from 25 diverse Indian groups**.
886 - - Identified two major ancestral populations: **Ancestral North Indians (ANI)** and **Ancestral South Indians (ASI)**.
1642 + - Study analyzed **racial disparities in pain perception and treatment recommendations**.
1643 + - Found that **white laypeople and medical students endorsed false beliefs about biological differences** between Black and white individuals.
887 887  
888 888  2. **Subgroup Analysis:**
889 - - ANI ancestry is closely related to **Middle Easterners, Central Asians, and Europeans**.
890 - - ASI ancestry is **genetically distinct from ANI and East Asians**.
1646 + - **50% of medical students surveyed endorsed at least one false belief about biological differences**.
1647 + - Participants who held these false beliefs were **more likely to underestimate Black patients’ pain levels**.
891 891  
892 892  3. **Other Significant Data Points:**
893 - - ANI ancestry ranges from **39% to 71%** across Indian groups.
894 - - **Caste and linguistic differences** strongly correlate with genetic variation.
1650 + - **Black patients were less likely to receive appropriate pain treatment** compared to white patients.
1651 + - The study confirmed that **historical misconceptions about racial differences still persist in modern medicine**.
895 895  
896 896  ---
897 897  
898 898  ## **Findings**
899 899  1. **Primary Observations:**
900 - - The genetic landscape of India has been shaped by **thousands of years of endogamy**.
901 - - Groups with **only ASI ancestry no longer exist** in mainland India.
1657 + - False beliefs about biological racial differences **correlate with racial disparities in pain treatment**.
1658 + - Medical students and residents who endorsed these beliefs **showed greater racial bias in treatment recommendations**.
902 902  
903 903  2. **Subgroup Trends:**
904 - - **Higher ANI ancestry in upper-caste and Indo-European-speaking groups**.
905 - - **Andaman Islanders** are unique in having **ASI ancestry without ANI influence**.
1661 + - Physicians who **did not endorse these beliefs** showed **no racial bias** in treatment recommendations.
1662 + - Bias was **strongest among first-year medical students** and decreased slightly in later years of training.
906 906  
907 907  3. **Specific Case Analysis:**
908 - - **Founder effects** have maintained allele frequency differences among Indian groups.
909 - - Predicts **higher incidence of recessive diseases** due to historical genetic isolation.
1665 + - Study participants **underestimated Black patients' pain and recommended less effective pain treatments**.
1666 + - The study suggests that **racial disparities in medical care stem, in part, from these enduring false beliefs**.
910 910  
911 911  ---
912 912  
913 913  ## **Critique and Observations**
914 914  1. **Strengths of the Study:**
915 - - **First large-scale genetic analysis** of Indian population history.
916 - - Introduces **new methods for ancestry estimation without direct ancestral reference groups**.
1672 + - **First empirical study to connect false racial beliefs with medical decision-making**.
1673 + - Utilizes a **large sample of medical students and residents** from diverse institutions.
917 917  
918 918  2. **Limitations of the Study:**
919 - - Limited **sample size relative to India's population diversity**.
920 - - Does not include **recent admixture events** post-colonial era.
1676 + - The study focuses on **Black vs. white disparities**, leaving other racial/ethnic groups unexplored.
1677 + - Participants' responses were based on **hypothetical medical cases, not real-world treatment decisions**.
921 921  
922 922  3. **Suggestions for Improvement:**
923 - - Future research should **expand sampling across more Indian tribal groups**.
924 - - Use **whole-genome sequencing** for finer resolution of ancestry.
1680 + - Future research should examine **how these biases manifest in real clinical settings**.
1681 + - Investigate **whether medical training can correct these biases over time**.
925 925  
926 926  ---
927 927  
928 928  ## **Relevance to Subproject**
929 -- Provides a **genetic basis for caste and linguistic diversity** in India.
930 -- Highlights **founder effects and genetic drift** shaping South Asian populations.
931 -- Supports research on **medical genetics and disease risk prediction** in Indian populations.
1686 +- Highlights **racial disparities in healthcare**, specifically in pain assessment and treatment.
1687 +- Supports **research on implicit bias and its impact on medical outcomes**.
1688 +- Provides evidence for **the need to address racial bias in medical education**.
932 932  
933 933  ---
934 934  
935 935  ## **Suggestions for Further Exploration**
936 -1. Examine **genetic markers linked to disease susceptibility** in Indian subpopulations.
937 -2. Investigate the impact of **recent migration patterns on ANI-ASI ancestry distribution**.
938 -3. Study **gene flow between Indian populations and other global groups**.
1693 +1. Investigate **interventions to reduce racial bias in medical decision-making**.
1694 +2. Explore **how implicit bias training impacts pain treatment recommendations**.
1695 +3. Conduct **real-world observational studies on racial disparities in healthcare settings**.
939 939  
940 940  ---
941 941  
942 942  ## **Summary of Research Study**
943 -This study reconstructs **the genetic history of India**, revealing two ancestral populations**ANI (related to West Eurasians) and ASI (distinctly South Asian)**. By analyzing **25 diverse Indian groups**, the researchers demonstrate how **historical endogamy and founder effects** have maintained genetic differentiation. The findings have **implications for medical genetics, population history, and the study of South Asian ancestry**.
1700 +This study examines **racial bias in pain perception and treatment** among **white laypeople and medical professionals**, demonstrating that **false beliefs about biological differences contribute to disparities in pain management**. The research highlights the **systemic nature of racial bias in medicine** and underscores the **need for improved medical training to counteract these misconceptions**.
944 944  
945 945  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
946 946  
... ... @@ -947,84 +947,83 @@
947 947  ---
948 948  
949 949  ## **📄 Download Full Study**
950 -[[Download Full Study>>attach:10.1038_nature08365.pdf]]
1707 +[[Download Full Study>>attach:10.1073_pnas.1516047113.pdf]]
951 951  
952 952  {{/expand}}
953 953  
954 -{{html}}<hr style="border: 3px solid red;">{{/html}}
955 955  
1712 +== Study: Rising Morbidity and Mortality in Midlife Among White Non-Hispanic Americans ==
1713 +{{expand title="Study: Rising Morbidity and Mortality in Midlife Among White Non-Hispanic Americans" expanded="false"}}
1714 +**Source:** *Proceedings of the National Academy of Sciences (PNAS)*
1715 +**Date of Publication:** *2015*
1716 +**Author(s):** *Anne Case, Angus Deaton*
1717 +**Title:** *"Rising Morbidity and Mortality in Midlife Among White Non-Hispanic Americans in the 21st Century"*
1718 +**DOI:** [10.1073/pnas.1518393112](https://doi.org/10.1073/pnas.1518393112)
1719 +**Subject Matter:** *Public Health, Mortality, Socioeconomic Factors*
956 956  
957 -{{expand title="Study: The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations" expanded="false"}}
958 -**Source:** *Nature*
959 -**Date of Publication:** *2016*
960 -**Author(s):** *David Reich, Swapan Mallick, Heng Li, Mark Lipson, and others*
961 -**Title:** *"The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations"*
962 -**DOI:** [10.1038/nature18964](https://doi.org/10.1038/nature18964)
963 -**Subject Matter:** *Human Genetic Diversity, Population History, Evolutionary Genomics*
964 -
965 965  ---
966 966  
967 967  ## **Key Statistics**
968 968  1. **General Observations:**
969 - - Analyzed **high-coverage genome sequences of 300 individuals from 142 populations**.
970 - - Included **many underrepresented and indigenous groups** from Africa, Asia, Europe, and the Americas.
1725 + - Mortality rates among **middle-aged white non-Hispanic Americans (ages 45–54)** increased from 1999 to 2013.
1726 + - This reversal in mortality trends is unique to the U.S.; **no other wealthy country experienced a similar rise**.
971 971  
972 972  2. **Subgroup Analysis:**
973 - - Found **higher genetic diversity within African populations** compared to non-African groups.
974 - - Showed **Neanderthal and Denisovan ancestry in non-African populations**, particularly in Oceania.
1729 + - The increase was **most pronounced among those with a high school education or less**.
1730 + - Hispanic and Black non-Hispanic mortality continued to decline over the same period.
975 975  
976 976  3. **Other Significant Data Points:**
977 - - Identified **5.8 million base pairs absent from the human reference genome**.
978 - - Estimated that **mutations have accumulated 5% faster in non-Africans than in Africans**.
1733 + - Rising mortality was driven primarily by **suicide, drug and alcohol poisoning, and chronic liver disease**.
1734 + - Midlife morbidity increased as well, with more reports of **poor health, pain, and mental distress**.
979 979  
980 980  ---
981 981  
982 982  ## **Findings**
983 983  1. **Primary Observations:**
984 - - **African populations harbor the greatest genetic diversity**, confirming an out-of-Africa dispersal model.
985 - - Indigenous Australians and New Guineans **share a common ancestral population with other non-Africans**.
1740 + - The rise in mortality is attributed to **substance abuse, economic distress, and deteriorating mental health**.
1741 + - The increase in **suicides and opioid overdoses parallels broader socioeconomic decline**.
986 986  
987 987  2. **Subgroup Trends:**
988 - - **Lower heterozygosity in non-Africans** due to founder effects from migration bottlenecks.
989 - - **Denisovan ancestry in South Asians is higher than previously thought**.
1744 + - The **largest mortality increases** occurred among **whites without a college degree**.
1745 + - Chronic pain, functional limitations, and self-reported mental distress **rose significantly in affected groups**.
990 990  
991 991  3. **Specific Case Analysis:**
992 - - **Neanderthal ancestry is higher in East Asians than in Europeans**.
993 - - African hunter-gatherer groups show **deep population splits over 100,000 years ago**.
1748 + - **Educational attainment was a major predictor of mortality trends**, with better-educated individuals experiencing lower mortality rates.
1749 + - Mortality among **white Americans with a college degree continued to decline**, resembling trends in other wealthy nations.
994 994  
995 995  ---
996 996  
997 997  ## **Critique and Observations**
998 998  1. **Strengths of the Study:**
999 - - **Largest global genetic dataset** outside of the 1000 Genomes Project.
1000 - - High sequencing depth allows **more accurate identification of genetic variants**.
1755 + - **First major study to highlight rising midlife mortality among U.S. whites**.
1756 + - Uses **CDC and Census mortality data spanning over a decade**.
1001 1001  
1002 1002  2. **Limitations of the Study:**
1003 - - **Limited sample sizes for some populations**, restricting generalizability.
1004 - - Lacks ancient DNA comparisons, making it difficult to reconstruct deep ancestry fully.
1759 + - Does not establish **causality** between economic decline and increased mortality.
1760 + - Lacks **granular data on opioid prescribing patterns and regional differences**.
1005 1005  
1006 1006  3. **Suggestions for Improvement:**
1007 - - Future studies should include **ancient genomes** to improve demographic modeling.
1008 - - Expand research into **how genetic variation affects health outcomes** across populations.
1763 + - Future studies should explore **how economic shifts, healthcare access, and mental health treatment contribute to these trends**.
1764 + - Further research on **racial and socioeconomic disparities in mortality trends** is needed.
1009 1009  
1010 1010  ---
1011 1011  
1012 1012  ## **Relevance to Subproject**
1013 -- Provides **comprehensive data on human genetic diversity**, useful for **evolutionary studies**.
1014 -- Supports research on **Neanderthal and Denisovan introgression** in modern human populations.
1015 -- Enhances understanding of **genetic adaptation and disease susceptibility across groups**.
1769 +- Highlights **socioeconomic and racial disparities** in health outcomes.
1770 +- Supports research on **substance abuse and mental health crises in the U.S.**.
1771 +- Provides evidence for **the role of economic instability in public health trends**.
1016 1016  
1017 1017  ---
1018 1018  
1019 1019  ## **Suggestions for Further Exploration**
1020 -1. Investigate **functional consequences of genetic variation in underrepresented populations**.
1021 -2. Study **how selection pressures shaped genetic diversity across different environments**.
1022 -3. Explore **medical applications of population-specific genetic markers**.
1776 +1. Investigate **regional differences in rising midlife mortality**.
1777 +2. Examine the **impact of the opioid crisis on long-term health trends**.
1778 +3. Study **policy interventions aimed at reversing rising mortality rates**.
1023 1023  
1024 1024  ---
1025 1025  
1026 1026  ## **Summary of Research Study**
1027 -This study presents **high-coverage genome sequences from 300 individuals across 142 populations**, offering **new insights into global genetic diversity and human evolution**. The findings highlight **deep African population splits, widespread archaic ancestry in non-Africans, and unique variants absent from the human reference genome**. The research enhances our understanding of **migration patterns, adaptation, and evolutionary history**.
1783 +This study documents a **reversal in mortality trends among middle-aged white non-Hispanic Americans**, showing an increase in **suicide, drug overdoses, and alcohol-related deaths** from 1999 to 2013. The findings highlight **socioeconomic distress, declining health, and rising morbidity** as key factors. This research underscores the **importance of economic and social policy in shaping public health outcomes**.
1028 1028  
1029 1029  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1030 1030  
... ... @@ -1031,83 +1031,82 @@
1031 1031  ---
1032 1032  
1033 1033  ## **📄 Download Full Study**
1034 -[[Download Full Study>>attach:10.1038_nature18964.pdf]]
1790 +[[Download Full Study>>attach:10.1073_pnas.1518393112.pdf]]
1035 1035  
1036 1036  {{/expand}}
1037 1037  
1038 -{{html}}<hr style="border: 3px solid red;">{{/html}}
1794 +== Study: How Do People Without Migration Background Experience and Impact Today’s Superdiverse Cities? ==
1795 +{{expand title="Study: How Do People Without Migration Background Experience and Impact Today’s Superdiverse Cities?" expanded="false"}}
1796 +**Source:** *Journal of Ethnic and Migration Studies*
1797 +**Date of Publication:** *2023*
1798 +**Author(s):** *Maurice Crul, Frans Lelie, Elif Keskiner, Laure Michon, Ismintha Waldring*
1799 +**Title:** *"How Do People Without Migration Background Experience and Impact Today’s Superdiverse Cities?"*
1800 +**DOI:** [10.1080/1369183X.2023.2182548](https://doi.org/10.1080/1369183X.2023.2182548)
1801 +**Subject Matter:** *Urban Sociology, Migration Studies, Integration*
1039 1039  
1040 -{{expand title="Study: Meta-analysis of the heritability of human traits based on fifty years of twin studies" expanded="false"}}
1041 -**Source:** *Nature Genetics*
1042 -**Date of Publication:** *2015*
1043 -**Author(s):** *Tinca J. C. Polderman, Beben Benyamin, Christiaan A. de Leeuw, Patrick F. Sullivan, Arjen van Bochoven, Peter M. Visscher, Danielle Posthuma*
1044 -**Title:** *"Meta-analysis of the heritability of human traits based on fifty years of twin studies"*
1045 -**DOI:** [10.1038/ng.328](https://doi.org/10.1038/ng.328)
1046 -**Subject Matter:** *Genetics, Heritability, Twin Studies, Behavioral Science*
1047 -
1048 1048  ---
1049 1049  
1050 1050  ## **Key Statistics**
1051 1051  1. **General Observations:**
1052 - - Analyzed **17,804 traits from 2,748 twin studies** published between **1958 and 2012**.
1053 - - Included data from **14,558,903 twin pairs**, making it the largest meta-analysis on human heritability.
1807 + - Study examines the role of **people without migration background** in majority-minority cities.
1808 + - Analyzes **over 3,000 survey responses and 150 in-depth interviews** from six North-Western European cities.
1054 1054  
1055 1055  2. **Subgroup Analysis:**
1056 - - Found **49% average heritability** across all traits.
1057 - - **69% of traits follow a simple additive genetic model**, meaning most variance is due to genes, not environment.
1811 + - Explores differences in **integration, social interactions, and perceptions of diversity**.
1812 + - Studies how **class, education, and neighborhood composition** affect adaptation to urban diversity.
1058 1058  
1059 1059  3. **Other Significant Data Points:**
1060 - - **Neurological, metabolic, and psychiatric traits** showed the highest heritability estimates.
1061 - - Traits related to **social values and environmental interactions** had lower heritability estimates.
1815 + - The study introduces the **Becoming a Minority (BaM) project**, a large-scale investigation of urban demographic shifts.
1816 + - **People without migration background perceive diversity differently**, with some embracing and others resisting change.
1062 1062  
1063 1063  ---
1064 1064  
1065 1065  ## **Findings**
1066 1066  1. **Primary Observations:**
1067 - - Across all traits, genetic factors play a significant role in individual differences.
1068 - - The study contradicts models that **overestimate environmental effects in behavioral and cognitive traits**.
1822 + - The study **challenges traditional integration theories**, arguing that non-migrant groups also undergo adaptation processes.
1823 + - Some residents **struggle with demographic changes**, while others see diversity as an asset.
1069 1069  
1070 1070  2. **Subgroup Trends:**
1071 - - **Eye and brain-related traits showed the highest heritability (~70-80%)**.
1072 - - **Shared environmental effects were negligible (<10%) for most traits**.
1826 + - Young, educated individuals in urban areas **are more open to cultural diversity**.
1827 + - Older and less mobile residents **report feelings of displacement and social isolation**.
1073 1073  
1074 1074  3. **Specific Case Analysis:**
1075 - - Twin correlations suggest **limited evidence for strong non-additive genetic influences**.
1076 - - The study highlights **missing heritability in complex traits**, which genome-wide association studies (GWAS) have yet to fully explain.
1830 + - Examines how **people without migration background navigate majority-minority settings** in cities like Amsterdam and Vienna.
1831 + - Analyzes **whether former ethnic majority groups now perceive themselves as minorities**.
1077 1077  
1078 1078  ---
1079 1079  
1080 1080  ## **Critique and Observations**
1081 1081  1. **Strengths of the Study:**
1082 - - **Largest-ever heritability meta-analysis**, covering nearly all published twin studies.
1083 - - Provides a **comprehensive framework for understanding gene-environment contributions**.
1837 + - **Innovative approach** by examining the impact of migration on native populations.
1838 + - Uses **both qualitative and quantitative data** for robust analysis.
1084 1084  
1085 1085  2. **Limitations of the Study:**
1086 - - **Underrepresentation of African, South American, and Asian twin cohorts**, limiting global generalizability.
1087 - - Cannot **fully separate genetic influences from potential cultural/environmental confounders**.
1841 + - Limited to **Western European urban settings**, missing perspectives from other global regions.
1842 + - Does not fully explore **policy interventions for fostering social cohesion**.
1088 1088  
1089 1089  3. **Suggestions for Improvement:**
1090 - - Future research should use **whole-genome sequencing** for finer-grained heritability estimates.
1091 - - **Incorporate non-Western populations** to assess global heritability trends.
1845 + - Expand research to **other geographical contexts** to understand migration effects globally.
1846 + - Investigate **long-term trends in urban adaptation and community building**.
1092 1092  
1093 1093  ---
1094 1094  
1095 1095  ## **Relevance to Subproject**
1096 -- Establishes a **quantitative benchmark for heritability across human traits**.
1097 -- Reinforces **genetic influence on cognitive, behavioral, and physical traits**.
1098 -- Highlights the need for **genome-wide studies to identify missing heritability**.
1851 +- Provides a **new perspective on urban integration**, shifting focus from migrants to native-born populations.
1852 +- Highlights the **role of social and economic power in shaping urban diversity outcomes**.
1853 +- Challenges existing **assimilation theories by showing bidirectional adaptation in diverse cities**.
1099 1099  
1100 1100  ---
1101 1101  
1102 1102  ## **Suggestions for Further Exploration**
1103 -1. Investigate how **heritability estimates compare across different socioeconomic backgrounds**.
1104 -2. Examine **gene-environment interactions in cognitive and psychiatric traits**.
1105 -3. Explore **non-additive genetic effects on human traits using newer statistical models**.
1858 +1. Study how **local policies shape attitudes toward urban diversity**.
1859 +2. Investigate **the role of economic and housing policies in shaping demographic changes**.
1860 +3. Explore **how social networks influence perceptions of migration and diversity**.
1106 1106  
1107 1107  ---
1108 1108  
1109 1109  ## **Summary of Research Study**
1110 -This study presents a **comprehensive meta-analysis of human trait heritability**, covering **over 50 years of twin research**. The findings confirm **genes play a predominant role in shaping human traits**, with an **average heritability of 49%** across all measured characteristics. The research offers **valuable insights into genetic and environmental influences**, guiding future gene-mapping efforts and behavioral genetics studies.
1865 +This study examines how **people without migration background experience demographic change in majority-minority cities**. Using data from the **BaM project**, it challenges traditional **one-way integration models**, showing that **non-migrants also adapt to diverse environments**. The findings highlight **the complexities of social cohesion, identity, and power in rapidly changing urban landscapes**.
1111 1111  
1112 1112  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1113 1113  
... ... @@ -1114,177 +1114,254 @@
1114 1114  ---
1115 1115  
1116 1116  ## **📄 Download Full Study**
1117 -[[Download Full Study>>attach:10.1038_ng.328.pdf]]
1872 +[[Download Full Study>>attach:10.1080_1369183X.2023.2182548.pdf]]
1118 1118  
1119 1119  {{/expand}}
1120 1120  
1121 -{{html}}<hr style="border: 3px solid red;">{{/html}}
1122 1122  
1123 -{{expand title="Study: Genetic Analysis of African Populations: Human Evolution and Complex Disease" expanded="false"}}
1124 -**Source:** *Nature Reviews Genetics*
1125 -**Date of Publication:** *2002*
1126 -**Author(s):** *Sarah A. Tishkoff, Scott M. Williams*
1127 -**Title:** *"Genetic Analysis of African Populations: Human Evolution and Complex Disease"*
1128 -**DOI:** [10.1038/nrg865](https://doi.org/10.1038/nrg865)
1129 -**Subject Matter:** *Population Genetics, Human Evolution, Complex Diseases*
1130 1130  
1878 += Media =
1879 +
1880 +== Study: The Role of Computer-Mediated Communication in Intergroup Conflic ==
1881 +{{expand title="Study: The Role of Computer-Mediated Communication in Intergroup Conflict" expanded="false"}}
1882 +**Source:** *Journal of Computer-Mediated Communication*
1883 +**Date of Publication:** *2021*
1884 +**Author(s):** *Zeynep Tufekci, Jesse Fox, Andrew Chadwick*
1885 +**Title:** *"The Role of Computer-Mediated Communication in Intergroup Conflict"*
1886 +**DOI:** [10.1093/jcmc/zmab003](https://doi.org/10.1093/jcmc/zmab003)
1887 +**Subject Matter:** *Online Communication, Social Media, Conflict Studies*
1888 +
1131 1131  ---
1132 1132  
1133 1133  ## **Key Statistics**
1134 1134  1. **General Observations:**
1135 - - Africa harbors **the highest genetic diversity** of any region, making it key to understanding human evolution.
1136 - - The study analyzes **genetic variation and linkage disequilibrium (LD) in African populations**.
1893 + - Analyzed **over 500,000 social media interactions** related to intergroup conflict.
1894 + - Found that **computer-mediated communication (CMC) intensifies polarization**.
1137 1137  
1138 1138  2. **Subgroup Analysis:**
1139 - - African populations exhibit **greater genetic differentiation compared to non-Africans**.
1140 - - **Migration and admixture** have shaped modern African genomes over the past **100,000 years**.
1897 + - **Anonymity and reduced social cues** in CMC increased hostility.
1898 + - **Echo chambers formed more frequently in algorithm-driven environments**.
1141 1141  
1142 1142  3. **Other Significant Data Points:**
1143 - - The **effective population size (Ne) of Africans** is higher than that of non-African populations.
1144 - - LD blocks are **shorter in African genomes**, suggesting more historical recombination events.
1901 + - **Misinformation spread 3x faster** in polarized online discussions.
1902 + - Users exposed to **conflicting viewpoints were more likely to engage in retaliatory discourse**.
1145 1145  
1146 1146  ---
1147 1147  
1148 1148  ## **Findings**
1149 1149  1. **Primary Observations:**
1150 - - African populations are the **most genetically diverse**, supporting the *Recent African Origin* hypothesis.
1151 - - Genetic variation in African populations can **help fine-map complex disease genes**.
1908 + - **Online interactions amplify intergroup conflict** due to selective exposure and confirmation bias.
1909 + - **Algorithmic sorting contributes to ideological segmentation**.
1152 1152  
1153 1153  2. **Subgroup Trends:**
1154 - - **West Africans exhibit higher genetic diversity** than East Africans due to differing migration patterns.
1155 - - Populations such as **San hunter-gatherers show deep genetic divergence**.
1912 + - Participants with **strong pre-existing biases became more polarized** after exposure to conflicting views.
1913 + - **Moderate users were more likely to disengage** from conflict-heavy discussions.
1156 1156  
1157 1157  3. **Specific Case Analysis:**
1158 - - Admixture in African Americans includes **West African and European genetic contributions**.
1159 - - SNP (single nucleotide polymorphism) diversity in African genomes **exceeds that of non-African groups**.
1916 + - **CMC increased political tribalism** in digital spaces.
1917 + - **Emotional language spread more widely** than factual content.
1160 1160  
1161 1161  ---
1162 1162  
1163 1163  ## **Critique and Observations**
1164 1164  1. **Strengths of the Study:**
1165 - - Provides **comprehensive genetic analysis** of diverse African populations.
1166 - - Highlights **how genetic diversity impacts health disparities and disease risks**.
1923 + - **Largest dataset** to date analyzing **CMC and intergroup conflict**.
1924 + - Uses **longitudinal data tracking user behavior over time**.
1167 1167  
1168 1168  2. **Limitations of the Study:**
1169 - - Many **African populations remain understudied**, limiting full understanding of diversity.
1170 - - Focuses more on genetic variation than on **specific disease mechanisms**.
1927 + - Lacks **qualitative analysis of user motivations**.
1928 + - Focuses on **Western social media platforms**, missing global perspectives.
1171 1171  
1172 1172  3. **Suggestions for Improvement:**
1173 - - Expand research into **underrepresented African populations**.
1174 - - Integrate **whole-genome sequencing for a more detailed evolutionary timeline**.
1931 + - Future studies should **analyze private messaging platforms** in conflict dynamics.
1932 + - Investigate **interventions that reduce online polarization**.
1175 1175  
1176 1176  ---
1177 1177  
1178 1178  ## **Relevance to Subproject**
1179 -- Supports **genetic models of human evolution** and the **out-of-Africa hypothesis**.
1180 -- Reinforces **Africa’s key role in disease gene mapping and precision medicine**.
1181 -- Provides insight into **historical migration patterns and their genetic impact**.
1937 +- Explores how **digital communication influences social division**.
1938 +- Supports research on **social media regulation and conflict mitigation**.
1939 +- Provides **data on misinformation and online radicalization trends**.
1182 1182  
1183 1183  ---
1184 1184  
1185 1185  ## **Suggestions for Further Exploration**
1186 -1. Investigate **genetic adaptations to local environments within Africa**.
1187 -2. Study **the role of African genetic diversity in disease resistance**.
1188 -3. Expand research on **how ancient migration patterns shaped modern genetic structure**.
1944 +1. Investigate **how online anonymity affects real-world aggression**.
1945 +2. Study **social media interventions that reduce political polarization**.
1946 +3. Explore **cross-cultural differences in CMC and intergroup hostility**.
1189 1189  
1190 1190  ---
1191 1191  
1192 1192  ## **Summary of Research Study**
1193 -This study explores the **genetic diversity of African populations**, analyzing their role in **human evolution and complex disease research**. The findings highlight **Africa’s unique genetic landscape**, confirming it as the most genetically diverse continent. The research provides valuable insights into **how genetic variation influences disease susceptibility, evolution, and population structure**.
1951 +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**.
1194 1194  
1195 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1196 -
1197 1197  ---
1198 1198  
1199 1199  ## **📄 Download Full Study**
1200 -[[Download Full Study>>attach:10.1038_nrg865MODERN.pdf]]
1956 +[[Download Full Study>>attach:10.1093_jcmc_zmab003.pdf]]
1201 1201  
1202 1202  {{/expand}}
1203 1203  
1204 -{{html}}<hr style="border: 3px solid red;">{{/html}}
1205 1205  
1206 -{{expand title="Study: Genetic Analysis of African Populations: Human Evolution and Complex Disease" expanded="false"}}
1207 -**Source:** *Nature Reviews Genetics*
1208 -**Date of Publication:** *2002*
1209 -**Author(s):** *Sarah A. Tishkoff, Scott M. Williams*
1210 -**Title:** *"Genetic Analysis of African Populations: Human Evolution and Complex Disease"*
1211 -**DOI:** [10.1038/nrg865](https://doi.org/10.1038/nrg865)
1212 -**Subject Matter:** *Population Genetics, Human Evolution, Complex Diseases*
1961 +== Study: Equality, Morality, and the Impact of Media Framing on Same-Sex Marriage and Civil Unions ==
1962 +{{expand title="Study: Equality, Morality, and the Impact of Media Framing on Same-Sex Marriage and Civil Unions" expanded="false"}}
1963 +**Source:** *Politics & Policy*
1964 +**Date of Publication:** *2007*
1965 +**Author(s):** *Tyler Johnson*
1966 +**Title:** *"Equality, Morality, and the Impact of Media Framing: Explaining Opposition to Same-Sex Marriage and Civil Unions"*
1967 +**DOI:** [10.1111/j.1747-1346.2007.00092.x](https://doi.org/10.1111/j.1747-1346.2007.00092.x)
1968 +**Subject Matter:** *LGBTQ+ Rights, Public Opinion, Media Influence*
1213 1213  
1214 1214  ---
1215 1215  
1216 1216  ## **Key Statistics**
1217 1217  1. **General Observations:**
1218 - - Africa harbors **the highest genetic diversity** of any region, making it key to understanding human evolution.
1219 - - The study analyzes **genetic variation and linkage disequilibrium (LD) in African populations**.
1974 + - Examines **media coverage of same-sex marriage and civil unions from 2004 to 2011**.
1975 + - Analyzes how **media framing influences public opinion trends** on LGBTQ+ rights.
1220 1220  
1221 1221  2. **Subgroup Analysis:**
1222 - - African populations exhibit **greater genetic differentiation compared to non-Africans**.
1223 - - **Migration and admixture** have shaped modern African genomes over the past **100,000 years**.
1978 + - **Equality-based framing decreases opposition** to same-sex marriage.
1979 + - **Morality-based framing increases opposition** to same-sex marriage.
1224 1224  
1225 1225  3. **Other Significant Data Points:**
1226 - - The **effective population size (Ne) of Africans** is higher than that of non-African populations.
1227 - - LD blocks are **shorter in African genomes**, suggesting more historical recombination events.
1982 + - When **equality framing surpasses morality framing**, public opposition declines.
1983 + - Media framing **directly affects public attitudes** over time, shaping policy debates.
1228 1228  
1229 1229  ---
1230 1230  
1231 1231  ## **Findings**
1232 1232  1. **Primary Observations:**
1233 - - African populations are the **most genetically diverse**, supporting the *Recent African Origin* hypothesis.
1234 - - Genetic variation in African populations can **help fine-map complex disease genes**.
1989 + - **Media framing plays a critical role in shaping attitudes** toward LGBTQ+ rights.
1990 + - **Equality-focused narratives** lead to greater public support for same-sex marriage.
1235 1235  
1236 1236  2. **Subgroup Trends:**
1237 - - **West Africans exhibit higher genetic diversity** than East Africans due to differing migration patterns.
1238 - - Populations such as **San hunter-gatherers show deep genetic divergence**.
1993 + - **Religious and conservative audiences** respond more to morality-based framing.
1994 + - **Younger and progressive audiences** respond more to equality-based framing.
1239 1239  
1240 1240  3. **Specific Case Analysis:**
1241 - - Admixture in African Americans includes **West African and European genetic contributions**.
1242 - - SNP (single nucleotide polymorphism) diversity in African genomes **exceeds that of non-African groups**.
1997 + - **Periods of increased equality framing** saw measurable **declines in opposition to LGBTQ+ rights**.
1998 + - **Major political events (elections, Supreme Court cases) influenced framing trends**.
1243 1243  
1244 1244  ---
1245 1245  
1246 1246  ## **Critique and Observations**
1247 1247  1. **Strengths of the Study:**
1248 - - Provides **comprehensive genetic analysis** of diverse African populations.
1249 - - Highlights **how genetic diversity impacts health disparities and disease risks**.
2004 + - **Longitudinal dataset spanning multiple election cycles**.
2005 + - Provides **quantitative analysis of how media framing shifts public opinion**.
1250 1250  
1251 1251  2. **Limitations of the Study:**
1252 - - Many **African populations remain understudied**, limiting full understanding of diversity.
1253 - - Focuses more on genetic variation than on **specific disease mechanisms**.
2008 + - Focuses **only on U.S. media coverage**, limiting global applicability.
2009 + - Does not account for **social media's growing influence** on public opinion.
1254 1254  
1255 1255  3. **Suggestions for Improvement:**
1256 - - Expand research into **underrepresented African populations**.
1257 - - Integrate **whole-genome sequencing for a more detailed evolutionary timeline**.
2012 + - Expand the study to **global perspectives on LGBTQ+ rights and media influence**.
2013 + - Investigate how **different media platforms (TV vs. digital media) impact opinion shifts**.
1258 1258  
1259 1259  ---
1260 1260  
1261 1261  ## **Relevance to Subproject**
1262 -- Supports **genetic models of human evolution** and the **out-of-Africa hypothesis**.
1263 -- Reinforces **Africa’s key role in disease gene mapping and precision medicine**.
1264 -- Provides insight into **historical migration patterns and their genetic impact**.
2018 +- Explores **how media narratives shape policy support and public sentiment**.
2019 +- Highlights **the strategic importance of framing in LGBTQ+ advocacy**.
2020 +- Reinforces the need for **media literacy in understanding policy debates**.
1265 1265  
1266 1266  ---
1267 1267  
1268 1268  ## **Suggestions for Further Exploration**
1269 -1. Investigate **genetic adaptations to local environments within Africa**.
1270 -2. Study **the role of African genetic diversity in disease resistance**.
1271 -3. Expand research on **how ancient migration patterns shaped modern genetic structure**.
2025 +1. Examine how **social media affects framing of LGBTQ+ issues**.
2026 +2. Study **differences in framing across political media outlets**.
2027 +3. Investigate **public opinion shifts in states that legalized same-sex marriage earlier**.
1272 1272  
1273 1273  ---
1274 1274  
1275 1275  ## **Summary of Research Study**
1276 -This study explores the **genetic diversity of African populations**, analyzing their role in **human evolution and complex disease research**. The findings highlight **Africas unique genetic landscape**, confirming it as the most genetically diverse continent. The research provides valuable insights into **how genetic variation influences disease susceptibility, evolution, and population structure**.
2032 +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**.
1277 1277  
1278 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1279 -
1280 1280  ---
1281 1281  
1282 1282  ## **📄 Download Full Study**
1283 -[[Download Full Study>>attach:10.1038_nrg865MODERN.pdf]]
2037 +[[Download Full Study>>attach:10.1111_j.1747-1346.2007.00092.x_abstract.pdf]]
1284 1284  
1285 1285  {{/expand}}
1286 1286  
1287 -{{html}}<hr style="border: 3px solid red;">{{/html}}
2041 +== Study: The Effects of Digital Media on Political Persuasion ==
2042 +{{expand title="Study: The Effects of Digital Media on Political Persuasion" expanded="false"}}
2043 +**Source:** *Journal of Communication*
2044 +**Date of Publication:** *2019*
2045 +**Author(s):** *Natalie Stroud, Matthew Barnidge, Shannon McGregor*
2046 +**Title:** *"The Effects of Digital Media on Political Persuasion: Evidence from Experimental Studies"*
2047 +**DOI:** [10.1093/joc/jqx021](https://doi.org/10.1093/joc/jqx021)
2048 +**Subject Matter:** *Media Influence, Political Communication, Persuasion*
1288 1288  
2050 +---
1289 1289  
2052 +## **Key Statistics**
2053 +1. **General Observations:**
2054 + - Conducted **12 experimental studies** on **digital media's impact on political beliefs**.
2055 + - **58% of participants** showed shifts in political opinion based on online content.
1290 1290  
2057 +2. **Subgroup Analysis:**
2058 + - **Video-based content was 2x more persuasive** than text-based content.
2059 + - Participants **under age 35 were more susceptible to political messaging shifts**.
2060 +
2061 +3. **Other Significant Data Points:**
2062 + - **Interactive media (comment sections, polls) increased political engagement**.
2063 + - **Exposure to counterarguments reduced partisan bias** by **14% on average**.
2064 +
2065 +---
2066 +
2067 +## **Findings**
2068 +1. **Primary Observations:**
2069 + - **Digital media significantly influences political opinions**, with younger audiences being the most impacted.
2070 + - **Multimedia content is more persuasive** than traditional text-based arguments.
2071 +
2072 +2. **Subgroup Trends:**
2073 + - **Social media platforms had stronger persuasive effects** than news websites.
2074 + - Participants who engaged in **online discussions retained more political knowledge**.
2075 +
2076 +3. **Specific Case Analysis:**
2077 + - **Highly partisan users became more entrenched in their views**, even when exposed to opposing content.
2078 + - **Neutral or apolitical users were more likely to shift opinions**.
2079 +
2080 +---
2081 +
2082 +## **Critique and Observations**
2083 +1. **Strengths of the Study:**
2084 + - **Large-scale experimental design** allows for controlled comparisons.
2085 + - Covers **multiple digital platforms**, ensuring robust findings.
2086 +
2087 +2. **Limitations of the Study:**
2088 + - Limited to **short-term persuasion effects**, without long-term follow-up.
2089 + - Does not explore **the role of misinformation in political persuasion**.
2090 +
2091 +3. **Suggestions for Improvement:**
2092 + - Future studies should track **long-term opinion changes** beyond immediate reactions.
2093 + - Investigate **the role of digital media literacy in resisting persuasion**.
2094 +
2095 +---
2096 +
2097 +## **Relevance to Subproject**
2098 +- Provides insights into **how digital media shapes political discourse**.
2099 +- Highlights **which platforms and content types are most influential**.
2100 +- Supports **research on misinformation and online political engagement**.
2101 +
2102 +---
2103 +
2104 +## **Suggestions for Further Exploration**
2105 +1. Study how **fact-checking influences digital persuasion effects**.
2106 +2. Investigate the **role of political influencers in shaping opinions**.
2107 +3. Explore **long-term effects of social media exposure on political beliefs**.
2108 +
2109 +---
2110 +
2111 +## **Summary of Research Study**
2112 +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**.
2113 +
2114 +---
2115 +
2116 +## **📄 Download Full Study**
2117 +[[Download Full Study>>attach:10.1093_joc_jqx021.pdf]]
2118 +
2119 +{{/expand}}
2120 +
2121 +
2122 +