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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/}}
14 14  
15 -
16 16  == Research Studies Repository ==
17 17  
18 -= Genetics =
19 19  
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*
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
28 28  
28 +**Tags:** `Genetics` `Race & Ethnicity` `Biomedical Research`
29 +
30 +=== **Key Statistics** ===
31 +
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%**.
35 +
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.
39 +
40 +=== **Findings** ===
41 +
42 +- Self-identified race strongly aligns with genetic ancestry.
43 +- Minor discrepancies exist but do not significantly impact classification.
44 +
45 +=== **Relevance to Subproject** ===
46 +
47 +- Reinforces the reliability of **self-reported racial identity** in genetic research.
48 +- Highlights **policy considerations** in biomedical studies.
49 +{{/expand}}
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 +
29 29  ---
30 30  
31 31  ## **Key Statistics**
32 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)**.
63 + - [Statistical finding or observation]
64 + - [Statistical finding or observation]
35 35  
36 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**.
67 + - [Breakdown of findings by gender, race, or other subgroups]
39 39  
40 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.
70 + - [Any additional findings or significant statistics]
43 43  
44 44  ---
45 45  
46 46  ## **Findings**
47 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.
76 + - [High-level findings or trends in the study]
50 50  
51 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**.
79 + - [Disparities or differences highlighted in the study]
54 54  
55 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.
82 + - [Detailed explanation of any notable specific findings]
58 58  
59 59  ---
60 60  
61 61  ## **Critique and Observations**
62 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**.
88 + - [Examples: strong methodology, large dataset, etc.]
65 65  
66 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.
91 + - [Examples: data gaps, lack of upstream analysis, etc.]
69 69  
70 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.
94 + - [Ideas for further research or addressing limitations]
73 73  
74 74  ---
75 75  
76 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.
99 +- [Explanation of how this study contributes to your subproject goals.]
100 +- [Any key arguments or findings that support or challenge your views.]
80 80  
81 81  ---
82 82  
83 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**.
105 +1. [Research questions or areas to investigate further.]
106 +2. [Potential studies or sources to complement this analysis.]
87 87  
88 88  ---
89 89  
90 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**.
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]**.
92 92  
93 -This summary provides an accessible, at-a-glance overview of the studys contributions. Please refer to the full paper for in-depth analysis.
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.
94 94  
95 95  ---
96 96  
97 97  ## **📄 Download Full Study**
98 -[[Download Full Study>>attach:10.1038_nature08365.pdf]]
118 +{{velocity}}
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99 99  
100 100  {{/expand}}
101 101  
130 +{{html}}<hr style="border: 3px solid red;">{{/html}}
102 102  
103 103  
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*
112 112  
113 113  ---
114 114  
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 +**Source:** *JAMA Network Open*
138 +**Date of Publication:** *2020*
139 +**Author(s):** *Ueda P, Mercer CH, Ghaznavi C, Herbenick D.*
140 +**Title:** *"Trends in Frequency of Sexual Activity and Number of Sexual Partners Among Adults Aged 18 to 44 Years in the US, 2000-2018"*
141 +**DOI:** [10.1001/jamanetworkopen.2020.3833](https://doi.org/10.1001/jamanetworkopen.2020.3833)
142 +**Subject Matter:** *Public Health, Sexual Behavior, Demography*
143 +
144 +---
145 +
115 115  ## **Key Statistics**
116 116  1. **General Observations:**
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.
148 + - Study analyzed **General Social Survey (2000-2018)** data.
149 + - Found **declining trends in sexual activity** among young adults.
119 119  
120 120  2. **Subgroup Analysis:**
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.
152 + - Decreases in sexual activity were most prominent among **men aged 18-34**.
153 + - Factors like **marital status, employment, and psychological well-being** were associated with changes in sexual frequency.
123 123  
124 124  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**.
156 + - Frequency of sexual activity decreased by **8-10%** over the studied period.
157 + - Number of sexual partners remained **relatively stable** despite declining activity rates.
127 127  
128 128  ---
129 129  
130 130  ## **Findings**
131 131  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**.
163 + - A significant decline in sexual frequency, especially among **younger men**.
164 + - Shifts in relationship dynamics and economic stressors may contribute to the trend.
134 134  
135 135  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**.
167 + - More pronounced decline among **unmarried individuals**.
168 + - No major change observed for **married adults** over time.
138 138  
139 139  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**.
171 + - **Mental health and employment status** were correlated with decreased activity.
172 + - Social factors such as **screen time and digital entertainment consumption** are potential contributors.
142 142  
143 143  ---
144 144  
145 145  ## **Critique and Observations**
146 146  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**.
178 + - **Large sample size** from a nationally representative dataset.
179 + - **Longitudinal design** enables trend analysis over time.
149 149  
150 150  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.
182 + - Self-reported data may introduce **response bias**.
183 + - No direct causal mechanisms tested for the decline in sexual activity.
153 153  
154 154  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.
186 + - Further studies should incorporate **qualitative data** on behavioral shifts.
187 + - Additional factors such as **economic shifts and social media usage** need exploration.
157 157  
158 158  ---
159 159  
160 160  ## **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**.
192 +- Provides evidence on **changing demographic behaviors** in relation to relationships and social interactions.
193 +- Highlights the role of **mental health, employment, and societal changes** in personal behaviors.
164 164  
165 165  ---
166 166  
167 167  ## **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**.
198 +1. Investigate the **impact of digital media consumption** on relationship dynamics.
199 +2. Examine **regional and cultural differences** in sexual activity trends.
171 171  
172 172  ---
173 173  
174 174  ## **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**.
204 +This study examines **trends in sexual frequency and number of partners among U.S. adults (2000-2018)**, highlighting significant **declines in sexual activity, particularly among young men**. The research utilized **General Social Survey data** to analyze the impact of **sociodemographic factors, employment status, and mental well-being** on sexual behavior.
176 176  
177 -This summary provides an accessible, at-a-glance overview of the studys contributions. Please refer to the full paper for in-depth analysis.
206 +This summary provides an accessible, at-a-glance overview of the study's contributions. Please refer to the full paper for in-depth analysis.
178 178  
179 179  ---
180 180  
181 181  ## **📄 Download Full Study**
182 -[[Download Full Study>>attach:10.1038_nature18964.pdf]]
211 +{{velocity}}
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214 +#if($xwiki.exists("attach:$filename"))
215 +[[Download>>attach:$filename]]
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217 +{{html}}<span style="color: red; font-weight: bold;">🚨 PDF Not Available 🚨</span>{{/html}}
218 +#end
219 +{{/velocity}}
183 183  
184 184  {{/expand}}
185 185  
223 +{{html}}<hr style="border: 3px solid red;">{{/html}}
186 186  
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*
195 195  
226 +{{expand title="Study: One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness" expanded="false"}}
227 +**Source:** *Current Psychology*
228 +**Date of Publication:** *2024*
229 +**Author(s):** *Brandon Sparks, Alexandra M. Zidenberg, Mark E. Olver*
230 +**Title:** *"One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness"*
231 +**DOI:** [10.1007/s12144-023-04275-z](https://doi.org/10.1007/s12144-023-04275-z)
232 +**Subject Matter:** *Psychology, Mental Health, Social Isolation*
233 +
196 196  ---
197 197  
198 198  ## **Key Statistics**
199 199  1. **General Observations:**
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.
238 + - Study analyzed **67 self-identified incels** and **103 non-incel men**.
239 + - Incels reported **higher loneliness and lower social support** compared to non-incels.
202 202  
203 203  2. **Subgroup Analysis:**
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.
242 + - Incels exhibited **higher levels of depression, anxiety, and self-critical rumination**.
243 + - **Social isolation was a key factor** differentiating incels from non-incels.
206 206  
207 207  3. **Other Significant Data Points:**
208 - - **Neurological, metabolic, and psychiatric traits** showed the highest heritability estimates.
209 - - Traits related to **social values and environmental interactions** had lower heritability estimates.
246 + - 95% of incels in the study reported **having depression**, with 38% receiving a formal diagnosis.
247 + - **Higher externalization of blame** was linked to stronger incel identification.
210 210  
211 211  ---
212 212  
213 213  ## **Findings**
214 214  1. **Primary Observations:**
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**.
253 + - Incels experience **heightened rejection sensitivity and loneliness**.
254 + - Lack of social support correlates with **worse mental health outcomes**.
217 217  
218 218  2. **Subgroup Trends:**
219 - - **Eye and brain-related traits showed the highest heritability (~70-80%)**.
220 - - **Shared environmental effects were negligible (<10%) for most traits**.
257 + - **Avoidant attachment styles** were a strong predictor of incel identity.
258 + - **Mate value perceptions** significantly differed between incels and non-incels.
221 221  
222 222  3. **Specific Case Analysis:**
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.
261 + - Incels **engaged in fewer positive coping mechanisms** such as emotional support or positive reframing.
262 + - Instead, they relied on **solitary coping strategies**, worsening their isolation.
225 225  
226 226  ---
227 227  
228 228  ## **Critique and Observations**
229 229  1. **Strengths of the Study:**
230 - - **Largest-ever heritability meta-analysis**, covering nearly all published twin studies.
231 - - Provides a **comprehensive framework for understanding gene-environment contributions**.
268 + - **First quantitative study** on incels’ social isolation and mental health.
269 + - **Robust sample size** and validated psychological measures.
232 232  
233 233  2. **Limitations of the Study:**
234 - - **Underrepresentation of African, South American, and Asian twin cohorts**, limiting global generalizability.
235 - - Cannot **fully separate genetic influences from potential cultural/environmental confounders**.
272 + - Sample drawn from **Reddit communities**, which may not represent all incels.
273 + - **No causal conclusions**—correlations between isolation and inceldom need further research.
236 236  
237 237  3. **Suggestions for Improvement:**
238 - - Future research should use **whole-genome sequencing** for finer-grained heritability estimates.
239 - - **Incorporate non-Western populations** to assess global heritability trends.
276 + - Future studies should **compare incel forum users vs. non-users**.
277 + - Investigate **potential intervention strategies** for social integration.
240 240  
241 241  ---
242 242  
243 243  ## **Relevance to Subproject**
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**.
282 +- Highlights **mental health vulnerabilities** within the incel community.
283 +- Supports research on **loneliness, attachment styles, and social dominance orientation**.
284 +- Examines how **peer rejection influences self-perceived mate value**.
247 247  
248 248  ---
249 249  
250 250  ## **Suggestions for Further Exploration**
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**.
289 +1. Explore how **online community participation** affects incel mental health.
290 +2. Investigate **cognitive biases** influencing self-perceived rejection among incels.
291 +3. Assess **therapeutic interventions** to address incel social isolation.
254 254  
255 255  ---
256 256  
257 257  ## **Summary of Research Study**
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.
296 +This study examines the **psychological characteristics of self-identified incels**, comparing them with non-incel men in terms of **mental health, loneliness, and coping strategies**. The research found **higher depression, anxiety, and avoidant attachment styles among incels**, as well as **greater reliance on solitary coping mechanisms**. It suggests that **lack of social support plays a critical role in exacerbating incel identity and related mental health concerns**.
259 259  
260 260  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
261 261  
... ... @@ -262,83 +262,149 @@
262 262  ---
263 263  
264 264  ## **📄 Download Full Study**
265 -[[Download Full Study>>attach:10.1038_ng.328.pdf]]
303 +[[Download Full Study>>attach:10.1007_s12144-023-04275-z.pdf]]
266 266  
267 267  {{/expand}}
268 268  
307 +{{html}}<hr style="border: 3px solid red;">{{/html}}
269 269  
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*
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
278 278  
316 +Key Statistics
317 +General Observations:
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 +
279 279  ---
280 280  
281 281  ## **Key Statistics**
282 282  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**.
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.
285 285  
286 286  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**.
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.
289 289  
290 290  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.
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**.
293 293  
294 294  ---
295 295  
296 296  ## **Findings**
297 297  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**.
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.
300 300  
301 301  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**.
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**.
304 304  
305 305  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**.
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.
308 308  
309 309  ---
310 310  
311 311  ## **Critique and Observations**
312 312  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**.
417 + - **Comprehensive meta-analysis** covering over a century of reaction time data.
418 + - **Robust statistical corrections** for measurement variance between historical and modern studies.
315 315  
316 316  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**.
421 + - Some historical data sources **lack methodological consistency**.
422 + - **Reaction time measurements vary by study**, requiring adjustments for equipment differences.
319 319  
320 320  3. **Suggestions for Improvement:**
321 - - Expand research into **underrepresented African populations**.
322 - - Integrate **whole-genome sequencing for a more detailed evolutionary timeline**.
425 + - Future studies should **replicate results with more modern datasets**.
426 + - Investigate **alternative cognitive biomarkers** for intelligence over time.
323 323  
324 324  ---
325 325  
326 326  ## **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**.
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**.
330 330  
331 331  ---
332 332  
333 333  ## **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**.
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**.
337 337  
338 338  ---
339 339  
340 340  ## **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**.
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**.
342 342  
343 343  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
344 344  
... ... @@ -345,164 +345,166 @@
345 345  ---
346 346  
347 347  ## **📄 Download Full Study**
348 -[[Download Full Study>>attach:10.1038_nrg865MODERN.pdf]]
452 +[[Download Full Study>>attach:10.1016_j.intell.2014.05.012.pdf]]
349 349  
350 350  {{/expand}}
351 351  
456 +{{html}}<hr style="border: 3px solid red;">{{/html}}
352 352  
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*
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*
361 361  
362 362  ---
363 363  
364 364  ## **Key Statistics**
365 365  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.
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**.
368 368  
369 369  2. **Subgroup Analysis:**
370 - - Examines **West Eurasian populations** and their genetic evolution.
371 - - Tracks **changes in allele frequencies over millennia**.
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.
372 372  
373 373  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**.
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**.
376 376  
377 377  ---
378 378  
379 379  ## **Findings**
380 380  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.
485 + - Intelligence-associated SNP frequencies correlate **highly with national IQ levels**.
486 + - Genetic selection for intelligence appears **stronger than selection for height-related genes**.
383 383  
384 384  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.
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.
387 387  
388 388  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**.
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.
392 392  
393 393  ---
394 394  
395 395  ## **Critique and Observations**
396 396  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**.
500 + - **Comprehensive genetic analysis** of intelligence-linked SNPs.
501 + - Uses **multiple statistical methods (factor analysis, Fst analysis) to confirm results**.
399 399  
400 400  2. **Limitations of the Study:**
401 - - Findings **may not translate directly** to modern populations.
402 - - **Unclear whether observed selection pressures persist today**.
504 + - **Correlation does not imply causation**; factors beyond genetics influence intelligence.
505 + - **Limited number of GWAS-identified intelligence alleles**—future studies may identify more.
403 403  
404 404  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**.
508 + - Larger **cross-population GWAS studies** needed to validate findings.
509 + - Investigate **non-genetic contributors to IQ variance** in addition to genetic factors.
407 407  
408 408  ---
409 409  
410 410  ## **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**.
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**.
414 414  
415 415  ---
416 416  
417 417  ## **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**.
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**.
421 421  
422 422  ---
423 423  
424 424  ## **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**.
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.
426 426  
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 +
427 427  ---
428 428  
429 429  ## **📄 Download Full Study**
430 -[[Download Full Study>>attach:10.1101_2024.09.14.613021doi_.pdf]]
535 +[[Download Full Study>>attach:10.1016_j.intell.2015.08.008.pdf]]
431 431  
432 432  {{/expand}}
433 433  
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*
539 +{{html}}<hr style="border: 3px solid red;">{{/html}}
442 442  
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 +
443 443  ---
444 444  
445 445  ## **Key Statistics**
446 446  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**.
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.
449 449  
450 450  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**.
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.
453 453  
454 454  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**.
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**.
457 457  
458 458  ---
459 459  
460 460  ## **Findings**
461 461  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**.
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.
464 464  
465 465  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**.
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.
468 468  
469 469  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**.
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.
472 472  
473 473  ---
474 474  
475 475  ## **Critique and Observations**
476 476  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.
583 + - **Largest expert survey on intelligence research** to date.
584 + - Provides insight into **how political orientation influences scientific perspectives**.
479 479  
480 480  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.
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**.
483 483  
484 484  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.
591 + - Future studies should include **a broader range of global experts**.
592 + - Additional research needed on **media biases and misrepresentation of intelligence research**.
487 487  
488 488  ---
489 489  
490 490  ## **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**.
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.
494 494  
495 495  ---
496 496  
497 497  ## **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**.
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.
501 501  
502 502  ---
503 503  
504 504  ## **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**.
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**.
506 506  
507 507  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
508 508  
... ... @@ -509,11 +509,12 @@
509 509  ---
510 510  
511 511  ## **📄 Download Full Study**
512 -[[Download Full Study>>attach:10.1017_thg.2013.54.pdf]]
618 +[[Download Full Study>>attach:10.1016_j.intell.2019.101406.pdf]]
513 513  
514 514  {{/expand}}
515 515  
516 -== Study: Is Homo sapiens polytypic? Human taxonomic diversity and its implications ==
622 +{{html}}<hr style="border: 3px solid red;">{{/html}}
623 +
517 517  {{expand title="Study: Is Homo sapiens polytypic? Human taxonomic diversity and its implications" expanded="false"}}
518 518  **Source:** *Medical Hypotheses (Elsevier)*
519 519  **Date of Publication:** *2010*
... ... @@ -595,79 +595,79 @@
595 595  
596 596  {{/expand}}
597 597  
705 +{{html}}<hr style="border: 3px solid red;">{{/html}}
598 598  
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*
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*
607 607  
608 608  ---
609 609  
610 610  ## **Key Statistics**
611 611  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.
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**.
614 614  
615 615  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.
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**.
618 618  
619 619  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**.
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**.
622 622  
623 623  ---
624 624  
625 625  ## **Findings**
626 626  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.
734 + - Intelligence heritability **strengthens throughout development**, contrary to early environmental models.
735 + - Shared environmental effects **decrease by late adolescence**, emphasizing **genetic influence in adulthood**.
629 629  
630 630  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.
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**.
633 633  
634 634  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.
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**.
637 637  
638 638  ---
639 639  
640 640  ## **Critique and Observations**
641 641  1. **Strengths of the Study:**
642 - - **Largest expert survey on intelligence research** to date.
643 - - Provides insight into **how political orientation influences scientific perspectives**.
749 + - **Robust dataset covering multiple twin and adoption studies over decades**.
750 + - **Clear, replicable trend** demonstrating the increasing role of genetics in intelligence.
644 644  
645 645  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**.
753 + - Findings apply primarily to **Western industrialized nations**, limiting generalizability.
754 + - **Lack of neurobiological mechanisms** explaining how genes express their influence over time.
648 648  
649 649  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**.
757 + - Future research should investigate **gene-environment interactions in cognitive aging**.
758 + - Examine **heritability trends in non-Western populations** to determine cross-cultural consistency.
652 652  
653 653  ---
654 654  
655 655  ## **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.
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**.
659 659  
660 660  ---
661 661  
662 662  ## **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.
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**.
666 666  
667 667  ---
668 668  
669 669  ## **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**.
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**.
671 671  
672 672  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
673 673  
... ... @@ -674,83 +674,83 @@
674 674  ---
675 675  
676 676  ## **📄 Download Full Study**
677 -[[Download Full Study>>attach:10.1016_j.intell.2019.101406.pdf]]
784 +[[Download Full Study>>attach:10.1017_thg.2013.54.pdf]]
678 678  
679 679  {{/expand}}
680 680  
788 +{{html}}<hr style="border: 3px solid red;">{{/html}}
681 681  
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*
790 +{{expand title="Study: Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports" expanded="false"}}
791 +**Source:** *Journal of Diversity in Higher Education*
792 +**Date of Publication:** *2019*
793 +**Author(s):** *Kirsten Hextrum*
794 +**Title:** *"Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports"*
795 +**DOI:** [10.1037/dhe0000140](https://doi.org/10.1037/dhe0000140)
796 +**Subject Matter:** *Race and Sports, Higher Education, Institutional Racism*
690 690  
691 691  ---
692 692  
693 693  ## **Key Statistics**
694 694  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**.
802 + - Analyzed **47 college athlete narratives** to explore racial disparities in non-revenue sports.
803 + - Found three interrelated themes: **racial segregation, racial innocence, and racial protection**.
697 697  
698 698  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.
806 + - **Predominantly white sports programs** reinforce racial hierarchies in college athletics.
807 + - **Recruitment policies favor white athletes** from affluent, suburban backgrounds.
701 701  
702 702  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**.
810 + - White athletes are **socialized to remain unaware of racial privilege** in their athletic careers.
811 + - Media and institutional narratives protect white athletes from discussions on race and systemic inequities.
705 705  
706 706  ---
707 707  
708 708  ## **Findings**
709 709  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**.
817 + - Colleges **actively recruit white athletes** from majority-white communities.
818 + - Institutional policies **uphold whiteness** by failing to challenge racial biases in recruitment and team culture.
712 712  
713 713  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.
821 + - **White athletes show limited awareness** of their racial advantage in sports.
822 + - **Black athletes are overrepresented** in revenue-generating sports but underrepresented in non-revenue teams.
716 716  
717 717  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.
825 + - Examines **how sports serve as a mechanism for maintaining racial privilege** in higher education.
826 + - Discusses the **role of athletics in reinforcing systemic segregation and exclusion**.
720 720  
721 721  ---
722 722  
723 723  ## **Critique and Observations**
724 724  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**.
832 + - **Comprehensive qualitative analysis** of race in college sports.
833 + - Examines **institutional conditions** that sustain racial disparities in athletics.
727 727  
728 728  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.
836 + - Focuses primarily on **Division I non-revenue sports**, limiting generalizability to other divisions.
837 + - Lacks extensive **quantitative data on racial demographics** in college athletics.
731 731  
732 732  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.
840 + - Future research should **compare recruitment policies across different sports and divisions**.
841 + - Investigate **how athletic scholarships contribute to racial inequities in higher education**.
735 735  
736 736  ---
737 737  
738 738  ## **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**.
846 +- Provides evidence of **systemic racial biases** in college sports recruitment.
847 +- Highlights **how institutional policies protect whiteness** in non-revenue athletics.
848 +- Supports research on **diversity, equity, and inclusion (DEI) efforts in sports and education**.
742 742  
743 743  ---
744 744  
745 745  ## **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**.
853 +1. Investigate how **racial stereotypes influence college athlete recruitment**.
854 +2. Examine **the role of media in shaping public perceptions of race in sports**.
855 +3. Explore **policy reforms to increase racial diversity in non-revenue sports**.
749 749  
750 750  ---
751 751  
752 752  ## **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.
860 +This study explores how **racial segregation, innocence, and protection** sustain whiteness in college sports. By analyzing **47 athlete narratives**, the research reveals **how predominantly white sports programs recruit and retain white athletes** while shielding them from discussions on race. The findings highlight **institutional biases that maintain racial privilege in athletics**, offering critical insight into the **structural inequalities in higher education sports programs**.
754 754  
755 755  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
756 756  
... ... @@ -757,291 +757,333 @@
757 757  ---
758 758  
759 759  ## **📄 Download Full Study**
760 -[[Download Full Study>>attach:10.1016_j.intell.2015.08.008.pdf]]
867 +[[Download Full Study>>attach:10.1037_dhe0000140.pdf]]
761 761  
762 762  {{/expand}}
763 763  
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
871 +{{html}}<hr style="border: 3px solid red;">{{/html}}
772 772  
773 -**Tags:** `Genetics` `Race & Ethnicity` `Biomedical Research`
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*
774 774  
775 -=== **Key Statistics** ===
881 +---
776 776  
883 +## **Key Statistics**
777 777  1. **General Observations:**
778 - - A near-perfect alignment between self-identified race/ethnicity (SIRE) and genetic ancestry was observed.
779 - - Misclassification rate: **0.14%**.
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)**.
780 780  
781 781  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.
889 + - ANI ancestry is closely related to **Middle Easterners, Central Asians, and Europeans**.
890 + - ASI ancestry is **genetically distinct from ANI and East Asians**.
784 784  
785 -=== **Findings** ===
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.
786 786  
787 -- Self-identified race strongly aligns with genetic ancestry.
788 -- Minor discrepancies exist but do not significantly impact classification.
896 +---
789 789  
790 -=== **Relevance to Subproject** ===
898 +## **Findings**
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.
791 791  
792 -- Reinforces the reliability of **self-reported racial identity** in genetic research.
793 -- Highlights **policy considerations** in biomedical studies.
794 -{{/expand}}
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**.
795 795  
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.
796 796  
797 797  ---
798 798  
799 -= Dating and Interpersonal Relationships =
913 +## **Critique and Observations**
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**.
800 800  
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 ==
802 -{{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"}}
803 -**Source:** *JAMA Network Open*
804 -**Date of Publication:** *2020*
805 -**Author(s):** *Ueda P, Mercer CH, Ghaznavi C, Herbenick D.*
806 -**Title:** *"Trends in Frequency of Sexual Activity and Number of Sexual Partners Among Adults Aged 18 to 44 Years in the US, 2000-2018"*
807 -**DOI:** [10.1001/jamanetworkopen.2020.3833](https://doi.org/10.1001/jamanetworkopen.2020.3833)
808 -**Subject Matter:** *Public Health, Sexual Behavior, Demography*
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.
809 809  
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.
925 +
810 810  ---
811 811  
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.
932 +
933 +---
934 +
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**.
939 +
940 +---
941 +
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**.
944 +
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 +
947 +---
948 +
949 +## **📄 Download Full Study**
950 +[[Download Full Study>>attach:10.1038_nature08365.pdf]]
951 +
952 +{{/expand}}
953 +
954 +{{html}}<hr style="border: 3px solid red;">{{/html}}
955 +
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 +---
966 +
812 812  ## **Key Statistics**
813 813  1. **General Observations:**
814 - - Study analyzed **General Social Survey (2000-2018)** data.
815 - - Found **declining trends in sexual activity** among young adults.
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.
816 816  
817 817  2. **Subgroup Analysis:**
818 - - Decreases in sexual activity were most prominent among **men aged 18-34**.
819 - - Factors like **marital status, employment, and psychological well-being** were associated with changes in sexual frequency.
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.
820 820  
821 821  3. **Other Significant Data Points:**
822 - - Frequency of sexual activity decreased by **8-10%** over the studied period.
823 - - Number of sexual partners remained **relatively stable** despite declining activity rates.
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**.
824 824  
825 825  ---
826 826  
827 827  ## **Findings**
828 828  1. **Primary Observations:**
829 - - A significant decline in sexual frequency, especially among **younger men**.
830 - - Shifts in relationship dynamics and economic stressors may contribute to the trend.
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**.
831 831  
832 832  2. **Subgroup Trends:**
833 - - More pronounced decline among **unmarried individuals**.
834 - - No major change observed for **married adults** over time.
988 + - **Lower heterozygosity in non-Africans** due to founder effects from migration bottlenecks.
989 + - **Denisovan ancestry in South Asians is higher than previously thought**.
835 835  
836 836  3. **Specific Case Analysis:**
837 - - **Mental health and employment status** were correlated with decreased activity.
838 - - Social factors such as **screen time and digital entertainment consumption** are potential contributors.
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**.
839 839  
840 840  ---
841 841  
842 842  ## **Critique and Observations**
843 843  1. **Strengths of the Study:**
844 - - **Large sample size** from a nationally representative dataset.
845 - - **Longitudinal design** enables trend analysis over time.
999 + - **Largest global genetic dataset** outside of the 1000 Genomes Project.
1000 + - High sequencing depth allows **more accurate identification of genetic variants**.
846 846  
847 847  2. **Limitations of the Study:**
848 - - Self-reported data may introduce **response bias**.
849 - - No direct causal mechanisms tested for the decline in sexual activity.
1003 + - **Limited sample sizes for some populations**, restricting generalizability.
1004 + - Lacks ancient DNA comparisons, making it difficult to reconstruct deep ancestry fully.
850 850  
851 851  3. **Suggestions for Improvement:**
852 - - Further studies should incorporate **qualitative data** on behavioral shifts.
853 - - Additional factors such as **economic shifts and social media usage** need exploration.
1007 + - Future studies should include **ancient genomes** to improve demographic modeling.
1008 + - Expand research into **how genetic variation affects health outcomes** across populations.
854 854  
855 855  ---
856 856  
857 857  ## **Relevance to Subproject**
858 -- Provides evidence on **changing demographic behaviors** in relation to relationships and social interactions.
859 -- Highlights the role of **mental health, employment, and societal changes** in personal behaviors.
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**.
860 860  
861 861  ---
862 862  
863 863  ## **Suggestions for Further Exploration**
864 -1. Investigate the **impact of digital media consumption** on relationship dynamics.
865 -2. Examine **regional and cultural differences** in sexual activity trends.
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**.
866 866  
867 867  ---
868 868  
869 869  ## **Summary of Research Study**
870 -This study examines **trends in sexual frequency and number of partners among U.S. adults (2000-2018)**, highlighting significant **declines in sexual activity, particularly among young men**. The research utilized **General Social Survey data** to analyze the impact of **sociodemographic factors, employment status, and mental well-being** on sexual behavior.
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**.
871 871  
872 -This summary provides an accessible, at-a-glance overview of the study's contributions. Please refer to the full paper for in-depth analysis.
1029 +This summary provides an accessible, at-a-glance overview of the studys contributions. Please refer to the full paper for in-depth analysis.
873 873  
874 874  ---
875 875  
876 876  ## **📄 Download Full Study**
877 -{{velocity}}
878 -#set($doi = "10.1001_jamanetworkopen.2020.3833")
879 -#set($filename = "${doi}.pdf")
880 -#if($xwiki.exists("attach:$filename"))
881 -[[Download>>attach:$filename]]
882 -#else
883 -{{html}}<span style="color: red; font-weight: bold;">🚨 PDF Not Available 🚨</span>{{/html}}
884 -#end
885 -{{/velocity}}
1034 +[[Download Full Study>>attach:10.1038_nature18964.pdf]]
886 886  
887 887  {{/expand}}
888 888  
1038 +{{html}}<hr style="border: 3px solid red;">{{/html}}
889 889  
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*
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*
898 898  
899 899  ---
900 900  
901 901  ## **Key Statistics**
902 902  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.
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.
905 905  
906 906  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**.
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.
909 909  
910 910  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).
1060 + - **Neurological, metabolic, and psychiatric traits** showed the highest heritability estimates.
1061 + - Traits related to **social values and environmental interactions** had lower heritability estimates.
915 915  
916 916  ---
917 917  
918 918  ## **Findings**
919 919  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.
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**.
922 922  
923 923  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.
1071 + - **Eye and brain-related traits showed the highest heritability (~70-80%)**.
1072 + - **Shared environmental effects were negligible (<10%) for most traits**.
926 926  
927 927  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.
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.
930 930  
931 931  ---
932 932  
933 933  ## **Critique and Observations**
934 934  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.
1082 + - **Largest-ever heritability meta-analysis**, covering nearly all published twin studies.
1083 + - Provides a **comprehensive framework for understanding gene-environment contributions**.
937 937  
938 938  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.
1086 + - **Underrepresentation of African, South American, and Asian twin cohorts**, limiting global generalizability.
1087 + - Cannot **fully separate genetic influences from potential cultural/environmental confounders**.
941 941  
942 942  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**.
1090 + - Future research should use **whole-genome sequencing** for finer-grained heritability estimates.
1091 + - **Incorporate non-Western populations** to assess global heritability trends.
945 945  
946 946  ---
947 947  
948 948  ## **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.
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**.
952 952  
953 953  ---
954 954  
955 955  ## **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**.
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**.
959 959  
960 960  ---
961 961  
962 962  ## **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**.
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.
964 964  
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 +
965 965  ---
966 966  
967 967  ## **📄 Download Full Study**
968 -[[Download Full Study>>attach:10.1111_j.1600-0412.2012.01501.xAbstract.pdf]]
1117 +[[Download Full Study>>attach:10.1038_ng.328.pdf]]
969 969  
970 970  {{/expand}}
971 971  
1121 +{{html}}<hr style="border: 3px solid red;">{{/html}}
972 972  
973 -== Study: One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness ==
974 -{{expand title="Study: One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness" expanded="false"}}
975 -**Source:** *Current Psychology*
976 -**Date of Publication:** *2024*
977 -**Author(s):** *Brandon Sparks, Alexandra M. Zidenberg, Mark E. Olver*
978 -**Title:** *"One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness"*
979 -**DOI:** [10.1007/s12144-023-04275-z](https://doi.org/10.1007/s12144-023-04275-z)
980 -**Subject Matter:** *Psychology, Mental Health, Social Isolation*
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*
981 981  
982 982  ---
983 983  
984 984  ## **Key Statistics**
985 985  1. **General Observations:**
986 - - Study analyzed **67 self-identified incels** and **103 non-incel men**.
987 - - Incels reported **higher loneliness and lower social support** compared to non-incels.
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**.
988 988  
989 989  2. **Subgroup Analysis:**
990 - - Incels exhibited **higher levels of depression, anxiety, and self-critical rumination**.
991 - - **Social isolation was a key factor** differentiating incels from non-incels.
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**.
992 992  
993 993  3. **Other Significant Data Points:**
994 - - 95% of incels in the study reported **having depression**, with 38% receiving a formal diagnosis.
995 - - **Higher externalization of blame** was linked to stronger incel identification.
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.
996 996  
997 997  ---
998 998  
999 999  ## **Findings**
1000 1000  1. **Primary Observations:**
1001 - - Incels experience **heightened rejection sensitivity and loneliness**.
1002 - - Lack of social support correlates with **worse mental health outcomes**.
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**.
1003 1003  
1004 1004  2. **Subgroup Trends:**
1005 - - **Avoidant attachment styles** were a strong predictor of incel identity.
1006 - - **Mate value perceptions** significantly differed between incels and non-incels.
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**.
1007 1007  
1008 1008  3. **Specific Case Analysis:**
1009 - - Incels **engaged in fewer positive coping mechanisms** such as emotional support or positive reframing.
1010 - - Instead, they relied on **solitary coping strategies**, worsening their isolation.
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**.
1011 1011  
1012 1012  ---
1013 1013  
1014 1014  ## **Critique and Observations**
1015 1015  1. **Strengths of the Study:**
1016 - - **First quantitative study** on incels social isolation and mental health.
1017 - - **Robust sample size** and validated psychological measures.
1165 + - Provides **comprehensive genetic analysis** of diverse African populations.
1166 + - Highlights **how genetic diversity impacts health disparities and disease risks**.
1018 1018  
1019 1019  2. **Limitations of the Study:**
1020 - - Sample drawn from **Reddit communities**, which may not represent all incels.
1021 - - **No causal conclusions**—correlations between isolation and inceldom need further research.
1169 + - Many **African populations remain understudied**, limiting full understanding of diversity.
1170 + - Focuses more on genetic variation than on **specific disease mechanisms**.
1022 1022  
1023 1023  3. **Suggestions for Improvement:**
1024 - - Future studies should **compare incel forum users vs. non-users**.
1025 - - Investigate **potential intervention strategies** for social integration.
1173 + - Expand research into **underrepresented African populations**.
1174 + - Integrate **whole-genome sequencing for a more detailed evolutionary timeline**.
1026 1026  
1027 1027  ---
1028 1028  
1029 1029  ## **Relevance to Subproject**
1030 -- Highlights **mental health vulnerabilities** within the incel community.
1031 -- Supports research on **loneliness, attachment styles, and social dominance orientation**.
1032 -- Examines how **peer rejection influences self-perceived mate value**.
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**.
1033 1033  
1034 1034  ---
1035 1035  
1036 1036  ## **Suggestions for Further Exploration**
1037 -1. Explore how **online community participation** affects incel mental health.
1038 -2. Investigate **cognitive biases** influencing self-perceived rejection among incels.
1039 -3. Assess **therapeutic interventions** to address incel social isolation.
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**.
1040 1040  
1041 1041  ---
1042 1042  
1043 1043  ## **Summary of Research Study**
1044 -This study examines the **psychological characteristics of self-identified incels**, comparing them with non-incel men in terms of **mental health, loneliness, and coping strategies**. The research found **higher depression, anxiety, and avoidant attachment styles among incels**, as well as **greater reliance on solitary coping mechanisms**. It suggests that **lack of social support plays a critical role in exacerbating incel identity and related mental health concerns**.
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**.
1045 1045  
1046 1046  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1047 1047  
... ... @@ -1048,85 +1048,85 @@
1048 1048  ---
1049 1049  
1050 1050  ## **📄 Download Full Study**
1051 -[[Download Full Study>>attach:10.1007_s12144-023-04275-z.pdf]]
1200 +[[Download Full Study>>attach:10.1038_nrg865MODERN.pdf]]
1052 1052  
1053 1053  {{/expand}}
1054 1054  
1204 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1055 1055  
1056 -= Crime and Substance Abuse =
1057 1057  
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*
1066 1066  
1208 +{{expand title="Study: Racial Bias in Pain Assessment and Treatment Recommendations" expanded="false"}}
1209 +**Source:** *Proceedings of the National Academy of Sciences (PNAS)*
1210 +**Date of Publication:** *2016*
1211 +**Author(s):** *Kelly M. Hoffman, Sophie Trawalter, Jordan R. Axta, M. Norman Oliver*
1212 +**Title:** *"Racial Bias in Pain Assessment and Treatment Recommendations, and False Beliefs About Biological Differences Between Blacks and Whites"*
1213 +**DOI:** [10.1073/pnas.1516047113](https://doi.org/10.1073/pnas.1516047113)
1214 +**Subject Matter:** *Health Disparities, Racial Bias, Medical Treatment*
1215 +
1067 1067  ---
1068 1068  
1069 1069  ## **Key Statistics**
1070 1070  1. **General Observations:**
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.
1220 + - Study analyzed **racial disparities in pain perception and treatment recommendations**.
1221 + - Found that **white laypeople and medical students endorsed false beliefs about biological differences** between Black and white individuals.
1073 1073  
1074 1074  2. **Subgroup Analysis:**
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.
1224 + - **50% of medical students surveyed endorsed at least one false belief about biological differences**.
1225 + - Participants who held these false beliefs were **more likely to underestimate Black patients pain levels**.
1077 1077  
1078 1078  3. **Other Significant Data Points:**
1079 - - **Surveys using biological validation (urinalysis, hair tests) revealed underreporting trends**.
1080 - - **Higher recantation rates** (denying past drug use) were observed among minority respondents.
1228 + - **Black patients were less likely to receive appropriate pain treatment** compared to white patients.
1229 + - The study confirmed that **historical misconceptions about racial differences still persist in modern medicine**.
1081 1081  
1082 1082  ---
1083 1083  
1084 1084  ## **Findings**
1085 1085  1. **Primary Observations:**
1086 - - Racial/ethnic disparities in **substance use reporting bias survey-based research**.
1087 - - **Social desirability and cultural norms impact data reliability**.
1235 + - False beliefs about biological racial differences **correlate with racial disparities in pain treatment**.
1236 + - Medical students and residents who endorsed these beliefs **showed greater racial bias in treatment recommendations**.
1088 1088  
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.
1238 +2. **Subgroup Trends:**
1239 + - Physicians who **did not endorse these beliefs** showed **no racial bias** in treatment recommendations.
1240 + - Bias was **strongest among first-year medical students** and decreased slightly in later years of training.
1092 1092  
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**.
1242 +3. **Specific Case Analysis:**
1243 + - Study participants **underestimated Black patients' pain and recommended less effective pain treatments**.
1244 + - The study suggests that **racial disparities in medical care stem, in part, from these enduring false beliefs**.
1096 1096  
1097 1097  ---
1098 1098  
1099 1099  ## **Critique and Observations**
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**.
1249 +1. **Strengths of the Study:**
1250 + - **First empirical study to connect false racial beliefs with medical decision-making**.
1251 + - Utilizes a **large sample of medical students and residents** from diverse institutions.
1103 1103  
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**.
1253 +2. **Limitations of the Study:**
1254 + - The study focuses on **Black vs. white disparities**, leaving other racial/ethnic groups unexplored.
1255 + - Participants' responses were based on **hypothetical medical cases, not real-world treatment decisions**.
1107 1107  
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**.
1257 +3. **Suggestions for Improvement:**
1258 + - Future research should examine **how these biases manifest in real clinical settings**.
1259 + - Investigate **whether medical training can correct these biases over time**.
1111 1111  
1112 1112  ---
1113 1113  
1114 1114  ## **Relevance to Subproject**
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**.
1264 +- Highlights **racial disparities in healthcare**, specifically in pain assessment and treatment.
1265 +- Supports **research on implicit bias and its impact on medical outcomes**.
1266 +- Provides evidence for **the need to address racial bias in medical education**.
1118 1118  
1119 1119  ---
1120 1120  
1121 1121  ## **Suggestions for Further Exploration**
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**.
1271 +1. Investigate **interventions to reduce racial bias in medical decision-making**.
1272 +2. Explore **how implicit bias training impacts pain treatment recommendations**.
1273 +3. Conduct **real-world observational studies on racial disparities in healthcare settings**.
1125 1125  
1126 1126  ---
1127 1127  
1128 1128  ## **Summary of Research Study**
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**.
1278 +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**.
1130 1130  
1131 1131  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1132 1132  
... ... @@ -1133,82 +1133,84 @@
1133 1133  ---
1134 1134  
1135 1135  ## **📄 Download Full Study**
1136 -[[Download Full Study>>attach:10.1081_JA-120023394.pdf]]
1285 +[[Download Full Study>>attach:10.1073_pnas.1516047113.pdf]]
1137 1137  
1138 1138  {{/expand}}
1139 1139  
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*
1289 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1148 1148  
1291 +
1292 +{{expand title="Study: Rising Morbidity and Mortality in Midlife Among White Non-Hispanic Americans" expanded="false"}}
1293 +**Source:** *Proceedings of the National Academy of Sciences (PNAS)*
1294 +**Date of Publication:** *2015*
1295 +**Author(s):** *Anne Case, Angus Deaton*
1296 +**Title:** *"Rising Morbidity and Mortality in Midlife Among White Non-Hispanic Americans in the 21st Century"*
1297 +**DOI:** [10.1073/pnas.1518393112](https://doi.org/10.1073/pnas.1518393112)
1298 +**Subject Matter:** *Public Health, Mortality, Socioeconomic Factors*
1299 +
1149 1149  ---
1150 1150  
1151 1151  ## **Key Statistics**
1152 1152  1. **General Observations:**
1153 - - Study examined **drug treatment court success rates** among first-time offenders.
1154 - - Strongest predictors of **successful completion were employment status and race**.
1304 + - Mortality rates among **middle-aged white non-Hispanic Americans (ages 45–54)** increased from 1999 to 2013.
1305 + - This reversal in mortality trends is unique to the U.S.; **no other wealthy country experienced a similar rise**.
1155 1155  
1156 1156  2. **Subgroup Analysis:**
1157 - - Individuals with **stable jobs were more likely to complete the program**.
1158 - - **Black participants had lower success rates**, suggesting potential systemic disparities.
1308 + - The increase was **most pronounced among those with a high school education or less**.
1309 + - Hispanic and Black non-Hispanic mortality continued to decline over the same period.
1159 1159  
1160 1160  3. **Other Significant Data Points:**
1161 - - **Education level was positively correlated** with program completion.
1162 - - Frequency of **drug use before enrollment affected treatment outcomes**.
1312 + - Rising mortality was driven primarily by **suicide, drug and alcohol poisoning, and chronic liver disease**.
1313 + - Midlife morbidity increased as well, with more reports of **poor health, pain, and mental distress**.
1163 1163  
1164 1164  ---
1165 1165  
1166 1166  ## **Findings**
1167 1167  1. **Primary Observations:**
1168 - - **Social stability factors** (employment, education) were key to treatment success.
1169 - - **Race and pre-existing substance use patterns** influenced completion rates.
1319 + - The rise in mortality is attributed to **substance abuse, economic distress, and deteriorating mental health**.
1320 + - The increase in **suicides and opioid overdoses parallels broader socioeconomic decline**.
1170 1170  
1171 1171  2. **Subgroup Trends:**
1172 - - White offenders had **higher completion rates** than Black offenders.
1173 - - Drug court success was **higher for those with lower initial drug use frequency**.
1323 + - The **largest mortality increases** occurred among **whites without a college degree**.
1324 + - Chronic pain, functional limitations, and self-reported mental distress **rose significantly in affected groups**.
1174 1174  
1175 1175  3. **Specific Case Analysis:**
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**.
1327 + - **Educational attainment was a major predictor of mortality trends**, with better-educated individuals experiencing lower mortality rates.
1328 + - Mortality among **white Americans with a college degree continued to decline**, resembling trends in other wealthy nations.
1178 1178  
1179 1179  ---
1180 1180  
1181 1181  ## **Critique and Observations**
1182 1182  1. **Strengths of the Study:**
1183 - - **First empirical study on drug court program success factors**.
1184 - - Uses **longitudinal data** for post-treatment analysis.
1334 + - **First major study to highlight rising midlife mortality among U.S. whites**.
1335 + - Uses **CDC and Census mortality data spanning over a decade**.
1185 1185  
1186 1186  2. **Limitations of the Study:**
1187 - - Lacks **qualitative data on personal motivation and treatment engagement**.
1188 - - Focuses on **short-term program success** without tracking **long-term relapse rates**.
1338 + - Does not establish **causality** between economic decline and increased mortality.
1339 + - Lacks **granular data on opioid prescribing patterns and regional differences**.
1189 1189  
1190 1190  3. **Suggestions for Improvement:**
1191 - - Future research should examine **racial disparities in drug court outcomes**.
1192 - - Study **how community resources impact long-term recovery**.
1342 + - Future studies should explore **how economic shifts, healthcare access, and mental health treatment contribute to these trends**.
1343 + - Further research on **racial and socioeconomic disparities in mortality trends** is needed.
1193 1193  
1194 1194  ---
1195 1195  
1196 1196  ## **Relevance to Subproject**
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**.
1348 +- Highlights **socioeconomic and racial disparities** in health outcomes.
1349 +- Supports research on **substance abuse and mental health crises in the U.S.**.
1350 +- Provides evidence for **the role of economic instability in public health trends**.
1200 1200  
1201 1201  ---
1202 1202  
1203 1203  ## **Suggestions for Further Exploration**
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**.
1355 +1. Investigate **regional differences in rising midlife mortality**.
1356 +2. Examine the **impact of the opioid crisis on long-term health trends**.
1357 +3. Study **policy interventions aimed at reversing rising mortality rates**.
1207 1207  
1208 1208  ---
1209 1209  
1210 1210  ## **Summary of Research Study**
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**.
1362 +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**.
1212 1212  
1213 1213  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1214 1214  
... ... @@ -1215,82 +1215,83 @@
1215 1215  ---
1216 1216  
1217 1217  ## **📄 Download Full Study**
1218 -[[Download Full Study>>attach:10.1081_JA-120014424.pdf]]
1369 +[[Download Full Study>>attach:10.1073_pnas.1518393112.pdf]]
1219 1219  
1220 1220  {{/expand}}
1221 1221  
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*
1373 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1230 1230  
1375 +{{expand title="Study: How Do People Without Migration Background Experience and Impact Today’s Superdiverse Cities?" expanded="false"}}
1376 +**Source:** *Journal of Ethnic and Migration Studies*
1377 +**Date of Publication:** *2023*
1378 +**Author(s):** *Maurice Crul, Frans Lelie, Elif Keskiner, Laure Michon, Ismintha Waldring*
1379 +**Title:** *"How Do People Without Migration Background Experience and Impact Today’s Superdiverse Cities?"*
1380 +**DOI:** [10.1080/1369183X.2023.2182548](https://doi.org/10.1080/1369183X.2023.2182548)
1381 +**Subject Matter:** *Urban Sociology, Migration Studies, Integration*
1382 +
1231 1231  ---
1232 1232  
1233 1233  ## **Key Statistics**
1234 1234  1. **General Observations:**
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.
1387 + - Study examines the role of **people without migration background** in majority-minority cities.
1388 + - Analyzes **over 3,000 survey responses and 150 in-depth interviews** from six North-Western European cities.
1237 1237  
1238 1238  2. **Subgroup Analysis:**
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.
1391 + - Explores differences in **integration, social interactions, and perceptions of diversity**.
1392 + - Studies how **class, education, and neighborhood composition** affect adaptation to urban diversity.
1241 1241  
1242 1242  3. **Other Significant Data Points:**
1243 - - **Surveys using biological validation (urinalysis, hair tests) revealed underreporting trends**.
1244 - - **Higher recantation rates** (denying past drug use) were observed among minority respondents.
1395 + - The study introduces the **Becoming a Minority (BaM) project**, a large-scale investigation of urban demographic shifts.
1396 + - **People without migration background perceive diversity differently**, with some embracing and others resisting change.
1245 1245  
1246 1246  ---
1247 1247  
1248 1248  ## **Findings**
1249 1249  1. **Primary Observations:**
1250 - - Racial/ethnic disparities in **substance use reporting bias survey-based research**.
1251 - - **Social desirability and cultural norms impact data reliability**.
1402 + - The study **challenges traditional integration theories**, arguing that non-migrant groups also undergo adaptation processes.
1403 + - Some residents **struggle with demographic changes**, while others see diversity as an asset.
1252 1252  
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.
1405 +2. **Subgroup Trends:**
1406 + - Young, educated individuals in urban areas **are more open to cultural diversity**.
1407 + - Older and less mobile residents **report feelings of displacement and social isolation**.
1256 1256  
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**.
1409 +3. **Specific Case Analysis:**
1410 + - Examines how **people without migration background navigate majority-minority settings** in cities like Amsterdam and Vienna.
1411 + - Analyzes **whether former ethnic majority groups now perceive themselves as minorities**.
1260 1260  
1261 1261  ---
1262 1262  
1263 1263  ## **Critique and Observations**
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**.
1416 +1. **Strengths of the Study:**
1417 + - **Innovative approach** by examining the impact of migration on native populations.
1418 + - Uses **both qualitative and quantitative data** for robust analysis.
1267 1267  
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**.
1420 +2. **Limitations of the Study:**
1421 + - Limited to **Western European urban settings**, missing perspectives from other global regions.
1422 + - Does not fully explore **policy interventions for fostering social cohesion**.
1271 1271  
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**.
1424 +3. **Suggestions for Improvement:**
1425 + - Expand research to **other geographical contexts** to understand migration effects globally.
1426 + - Investigate **long-term trends in urban adaptation and community building**.
1275 1275  
1276 1276  ---
1277 1277  
1278 1278  ## **Relevance to Subproject**
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**.
1431 +- Provides a **new perspective on urban integration**, shifting focus from migrants to native-born populations.
1432 +- Highlights the **role of social and economic power in shaping urban diversity outcomes**.
1433 +- Challenges existing **assimilation theories by showing bidirectional adaptation in diverse cities**.
1282 1282  
1283 1283  ---
1284 1284  
1285 1285  ## **Suggestions for Further Exploration**
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**.
1438 +1. Study how **local policies shape attitudes toward urban diversity**.
1439 +2. Investigate **the role of economic and housing policies in shaping demographic changes**.
1440 +3. Explore **how social networks influence perceptions of migration and diversity**.
1289 1289  
1290 1290  ---
1291 1291  
1292 1292  ## **Summary of Research Study**
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**.
1445 +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**.
1294 1294  
1295 1295  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1296 1296  
... ... @@ -1297,12 +1297,12 @@
1297 1297  ---
1298 1298  
1299 1299  ## **📄 Download Full Study**
1300 -[[Download Full Study>>attach:10.1081_JA-120023394.pdf]]
1452 +[[Download Full Study>>attach:10.1080_1369183X.2023.2182548.pdf]]
1301 1301  
1302 1302  {{/expand}}
1303 1303  
1456 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1304 1304  
1305 -== Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program ==
1306 1306  {{expand title="Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program" expanded="false"}}
1307 1307  **Source:** *Substance Use & Misuse*
1308 1308  **Date of Publication:** *2002*
... ... @@ -1384,144 +1384,163 @@
1384 1384  
1385 1385  {{/expand}}
1386 1386  
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
1539 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1394 1394  
1395 -Key Statistics
1396 -General Observations:
1397 1397  
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:
1542 +{{expand title="Study: Cross-Cultural Sources of Measurement Error in Substance Use Surveys" expanded="false"}}
1543 +**Source:** *Substance Use & Misuse*
1544 +**Date of Publication:** *2003*
1545 +**Author(s):** *Timothy P. Johnson, Phillip J. Bowman*
1546 +**Title:** *"Cross-Cultural Sources of Measurement Error in Substance Use Surveys"*
1547 +**DOI:** [10.1081/JA-120023394](https://doi.org/10.1081/JA-120023394)
1548 +**Subject Matter:** *Survey Methodology, Racial Disparities, Substance Use Research*
1401 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:
1550 +---
1405 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:
1552 +## **Key Statistics**
1553 +1. **General Observations:**
1554 + - Study examined **how racial and cultural factors influence self-reported substance use data**.
1555 + - Analyzed **36 empirical studies from 1977–2003** on survey reliability across racial/ethnic groups.
1410 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:
1557 +2. **Subgroup Analysis:**
1558 + - Black and Latino respondents **were more likely to underreport drug use** compared to White respondents.
1559 + - **Cultural stigma and distrust in research institutions** affected self-report accuracy.
1414 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:
1561 +3. **Other Significant Data Points:**
1562 + - **Surveys using biological validation (urinalysis, hair tests) revealed underreporting trends**.
1563 + - **Higher recantation rates** (denying past drug use) were observed among minority respondents.
1418 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:
1565 +---
1423 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:
1567 +## **Findings**
1568 +1. **Primary Observations:**
1569 + - Racial/ethnic disparities in **substance use reporting bias survey-based research**.
1570 + - **Social desirability and cultural norms impact data reliability**.
1427 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:
1572 +2. **Subgroup Trends:**
1573 + - White respondents were **more likely to overreport** substance use.
1574 + - Black and Latino respondents **had higher recantation rates**, particularly in face-to-face interviews.
1431 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.
1576 +3. **Specific Case Analysis:**
1577 + - Mode of survey administration **significantly influenced reporting accuracy**.
1578 + - **Self-administered surveys produced more reliable data than interviewer-administered surveys**.
1444 1444  
1580 +---
1581 +
1582 +## **Critique and Observations**
1583 +1. **Strengths of the Study:**
1584 + - **Comprehensive review of 36 studies** on measurement error in substance use reporting.
1585 + - Identifies **systemic biases affecting racial/ethnic survey reliability**.
1586 +
1587 +2. **Limitations of the Study:**
1588 + - Relies on **secondary data analysis**, limiting direct experimental control.
1589 + - Does not explore **how measurement error impacts policy decisions**.
1590 +
1591 +3. **Suggestions for Improvement:**
1592 + - Future research should **incorporate mixed-method approaches** (qualitative & quantitative).
1593 + - Investigate **how survey design can reduce racial reporting disparities**.
1594 +
1595 +---
1596 +
1597 +## **Relevance to Subproject**
1598 +- Supports research on **racial disparities in self-reported health behaviors**.
1599 +- Highlights **survey methodology issues that impact substance use epidemiology**.
1600 +- Provides insights for **improving data accuracy in public health research**.
1601 +
1602 +---
1603 +
1604 +## **Suggestions for Further Exploration**
1605 +1. Investigate **how survey design impacts racial disparities in self-reported health data**.
1606 +2. Study **alternative data collection methods (biometric validation, passive data tracking)**.
1607 +3. Explore **the role of social stigma in self-reported health behaviors**.
1608 +
1609 +---
1610 +
1611 +## **Summary of Research Study**
1612 +This study examines **cross-cultural biases in self-reported substance use surveys**, showing that **racial/ethnic minorities are more likely to underreport drug use** due to **social stigma, research distrust, and survey administration methods**. The findings highlight **critical issues in public health data collection and the need for improved survey design**.
1613 +
1445 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 1446  
1447 -📄 Download Full Study
1448 -[[Download Full Study>>attach:10.1016_j.addbeh.2016.02.030.pdf]]
1616 +---
1449 1449  
1618 +## **📄 Download Full Study**
1619 +[[Download Full Study>>attach:10.1081_JA-120023394.pdf]]
1620 +
1450 1450  {{/expand}}
1451 1451  
1623 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1452 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*
1625 +{{expand title="Study: Cross-Cultural Sources of Measurement Error in Substance Use Surveys" expanded="false"}}
1626 +**Source:** *Substance Use & Misuse*
1627 +**Date of Publication:** *2003*
1628 +**Author(s):** *Timothy P. Johnson, Phillip J. Bowman*
1629 +**Title:** *"Cross-Cultural Sources of Measurement Error in Substance Use Surveys"*
1630 +**DOI:** [10.1081/JA-120023394](https://doi.org/10.1081/JA-120023394)
1631 +**Subject Matter:** *Survey Methodology, Racial Disparities, Substance Use Research*
1461 1461  
1462 1462  ---
1463 1463  
1464 1464  ## **Key Statistics**
1465 1465  1. **General Observations:**
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.
1637 + - Study examined **how racial and cultural factors influence self-reported substance use data**.
1638 + - Analyzed **36 empirical studies from 1977–2003** on survey reliability across racial/ethnic groups.
1468 1468  
1469 1469  2. **Subgroup Analysis:**
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.
1641 + - Black and Latino respondents **were more likely to underreport drug use** compared to White respondents.
1642 + - **Cultural stigma and distrust in research institutions** affected self-report accuracy.
1472 1472  
1473 1473  3. **Other Significant Data Points:**
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**.
1645 + - **Surveys using biological validation (urinalysis, hair tests) revealed underreporting trends**.
1646 + - **Higher recantation rates** (denying past drug use) were observed among minority respondents.
1476 1476  
1477 1477  ---
1478 1478  
1479 1479  ## **Findings**
1480 1480  1. **Primary Observations:**
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.
1652 + - Racial/ethnic disparities in **substance use reporting bias survey-based research**.
1653 + - **Social desirability and cultural norms impact data reliability**.
1483 1483  
1484 -2. **Subgroup Trends:**
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**.
1655 +2. **Subgroup Trends:**
1656 + - White respondents were **more likely to overreport** substance use.
1657 + - Black and Latino respondents **had higher recantation rates**, particularly in face-to-face interviews.
1487 1487  
1488 -3. **Specific Case Analysis:**
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.
1659 +3. **Specific Case Analysis:**
1660 + - Mode of survey administration **significantly influenced reporting accuracy**.
1661 + - **Self-administered surveys produced more reliable data than interviewer-administered surveys**.
1491 1491  
1492 1492  ---
1493 1493  
1494 1494  ## **Critique and Observations**
1495 -1. **Strengths of the Study:**
1496 - - **Comprehensive meta-analysis** covering over a century of reaction time data.
1497 - - **Robust statistical corrections** for measurement variance between historical and modern studies.
1666 +1. **Strengths of the Study:**
1667 + - **Comprehensive review of 36 studies** on measurement error in substance use reporting.
1668 + - Identifies **systemic biases affecting racial/ethnic survey reliability**.
1498 1498  
1499 -2. **Limitations of the Study:**
1500 - - Some historical data sources **lack methodological consistency**.
1501 - - **Reaction time measurements vary by study**, requiring adjustments for equipment differences.
1670 +2. **Limitations of the Study:**
1671 + - Relies on **secondary data analysis**, limiting direct experimental control.
1672 + - Does not explore **how measurement error impacts policy decisions**.
1502 1502  
1503 -3. **Suggestions for Improvement:**
1504 - - Future studies should **replicate results with more modern datasets**.
1505 - - Investigate **alternative cognitive biomarkers** for intelligence over time.
1674 +3. **Suggestions for Improvement:**
1675 + - Future research should **incorporate mixed-method approaches** (qualitative & quantitative).
1676 + - Investigate **how survey design can reduce racial reporting disparities**.
1506 1506  
1507 1507  ---
1508 1508  
1509 1509  ## **Relevance to Subproject**
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**.
1681 +- Supports research on **racial disparities in self-reported health behaviors**.
1682 +- Highlights **survey methodology issues that impact substance use epidemiology**.
1683 +- Provides insights for **improving data accuracy in public health research**.
1513 1513  
1514 1514  ---
1515 1515  
1516 1516  ## **Suggestions for Further Exploration**
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**.
1688 +1. Investigate **how survey design impacts racial disparities in self-reported health data**.
1689 +2. Study **alternative data collection methods (biometric validation, passive data tracking)**.
1690 +3. Explore **the role of social stigma in self-reported health behaviors**.
1520 1520  
1521 1521  ---
1522 1522  
1523 1523  ## **Summary of Research Study**
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**.
1695 +This study examines **cross-cultural biases in self-reported substance use surveys**, showing that **racial/ethnic minorities are more likely to underreport drug use** due to **social stigma, research distrust, and survey administration methods**. The findings highlight **critical issues in public health data collection and the need for improved survey design**.
1525 1525  
1526 1526  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1527 1527  
... ... @@ -1528,88 +1528,83 @@
1528 1528  ---
1529 1529  
1530 1530  ## **📄 Download Full Study**
1531 -[[Download Full Study>>attach:10.1016_j.intell.2014.05.012.pdf]]
1702 +[[Download Full Study>>attach:10.1081_JA-120023394.pdf]]
1532 1532  
1533 1533  {{/expand}}
1534 1534  
1706 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1535 1535  
1708 +{{expand title="Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program" expanded="false"}}
1709 +**Source:** *Substance Use & Misuse*
1710 +**Date of Publication:** *2002*
1711 +**Author(s):** *Clifford A. Butzin, Christine A. Saum, Frank R. Scarpitti*
1712 +**Title:** *"Factors Associated with Completion of a Drug Treatment Court Diversion Program"*
1713 +**DOI:** [10.1081/JA-120014424](https://doi.org/10.1081/JA-120014424)
1714 +**Subject Matter:** *Substance Use, Criminal Justice, Drug Courts*
1536 1536  
1537 -
1538 -
1539 -= Whiteness =
1540 -
1541 -== Study: Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports ==
1542 -{{expand title="Study: Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports" expanded="false"}}
1543 -**Source:** *Journal of Diversity in Higher Education*
1544 -**Date of Publication:** *2019*
1545 -**Author(s):** *Kirsten Hextrum*
1546 -**Title:** *"Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports"*
1547 -**DOI:** [10.1037/dhe0000140](https://doi.org/10.1037/dhe0000140)
1548 -**Subject Matter:** *Race and Sports, Higher Education, Institutional Racism*
1549 -
1550 1550  ---
1551 1551  
1552 1552  ## **Key Statistics**
1553 1553  1. **General Observations:**
1554 - - Analyzed **47 college athlete narratives** to explore racial disparities in non-revenue sports.
1555 - - Found three interrelated themes: **racial segregation, racial innocence, and racial protection**.
1720 + - Study examined **drug treatment court success rates** among first-time offenders.
1721 + - Strongest predictors of **successful completion were employment status and race**.
1556 1556  
1557 1557  2. **Subgroup Analysis:**
1558 - - **Predominantly white sports programs** reinforce racial hierarchies in college athletics.
1559 - - **Recruitment policies favor white athletes** from affluent, suburban backgrounds.
1724 + - Individuals with **stable jobs were more likely to complete the program**.
1725 + - **Black participants had lower success rates**, suggesting potential systemic disparities.
1560 1560  
1561 1561  3. **Other Significant Data Points:**
1562 - - White athletes are **socialized to remain unaware of racial privilege** in their athletic careers.
1563 - - Media and institutional narratives protect white athletes from discussions on race and systemic inequities.
1728 + - **Education level was positively correlated** with program completion.
1729 + - Frequency of **drug use before enrollment affected treatment outcomes**.
1564 1564  
1565 1565  ---
1566 1566  
1567 1567  ## **Findings**
1568 1568  1. **Primary Observations:**
1569 - - Colleges **actively recruit white athletes** from majority-white communities.
1570 - - Institutional policies **uphold whiteness** by failing to challenge racial biases in recruitment and team culture.
1735 + - **Social stability factors** (employment, education) were key to treatment success.
1736 + - **Race and pre-existing substance use patterns** influenced completion rates.
1571 1571  
1572 1572  2. **Subgroup Trends:**
1573 - - **White athletes show limited awareness** of their racial advantage in sports.
1574 - - **Black athletes are overrepresented** in revenue-generating sports but underrepresented in non-revenue teams.
1739 + - White offenders had **higher completion rates** than Black offenders.
1740 + - Drug court success was **higher for those with lower initial drug use frequency**.
1575 1575  
1576 1576  3. **Specific Case Analysis:**
1577 - - Examines **how sports serve as a mechanism for maintaining racial privilege** in higher education.
1578 - - Discusses the **role of athletics in reinforcing systemic segregation and exclusion**.
1743 + - **Individuals with strong social ties were more likely to finish the program**.
1744 + - Success rates were **significantly higher for participants with case management support**.
1579 1579  
1580 1580  ---
1581 1581  
1582 1582  ## **Critique and Observations**
1583 1583  1. **Strengths of the Study:**
1584 - - **Comprehensive qualitative analysis** of race in college sports.
1585 - - Examines **institutional conditions** that sustain racial disparities in athletics.
1750 + - **First empirical study on drug court program success factors**.
1751 + - Uses **longitudinal data** for post-treatment analysis.
1586 1586  
1587 1587  2. **Limitations of the Study:**
1588 - - Focuses primarily on **Division I non-revenue sports**, limiting generalizability to other divisions.
1589 - - Lacks extensive **quantitative data on racial demographics** in college athletics.
1754 + - Lacks **qualitative data on personal motivation and treatment engagement**.
1755 + - Focuses on **short-term program success** without tracking **long-term relapse rates**.
1590 1590  
1591 1591  3. **Suggestions for Improvement:**
1592 - - Future research should **compare recruitment policies across different sports and divisions**.
1593 - - Investigate **how athletic scholarships contribute to racial inequities in higher education**.
1758 + - Future research should examine **racial disparities in drug court outcomes**.
1759 + - Study **how community resources impact long-term recovery**.
1594 1594  
1595 1595  ---
1596 1596  
1597 1597  ## **Relevance to Subproject**
1598 -- Provides evidence of **systemic racial biases** in college sports recruitment.
1599 -- Highlights **how institutional policies protect whiteness** in non-revenue athletics.
1600 -- Supports research on **diversity, equity, and inclusion (DEI) efforts in sports and education**.
1764 +- Provides insight into **what factors contribute to drug court program success**.
1765 +- Highlights **racial disparities in criminal justice-based rehabilitation programs**.
1766 +- Supports **policy discussions on improving access to drug treatment for marginalized groups**.
1601 1601  
1602 1602  ---
1603 1603  
1604 1604  ## **Suggestions for Further Exploration**
1605 -1. Investigate how **racial stereotypes influence college athlete recruitment**.
1606 -2. Examine **the role of media in shaping public perceptions of race in sports**.
1607 -3. Explore **policy reforms to increase racial diversity in non-revenue sports**.
1771 +1. Investigate **the role of mental health in drug court success rates**.
1772 +2. Assess **long-term relapse prevention strategies post-treatment**.
1773 +3. Explore **alternative diversion programs beyond traditional drug courts**.
1608 1608  
1609 1609  ---
1610 1610  
1611 1611  ## **Summary of Research Study**
1612 -This study explores how **racial segregation, innocence, and protection** sustain whiteness in college sports. By analyzing **47 athlete narratives**, the research reveals **how predominantly white sports programs recruit and retain white athletes** while shielding them from discussions on race. The findings highlight **institutional biases that maintain racial privilege in athletics**, offering critical insight into the **structural inequalities in higher education sports programs**.
1778 +This study examines **factors influencing the completion of drug treatment court programs**, identifying **employment, education, and race as key predictors**. The research underscores **systemic disparities in drug court outcomes**, emphasizing the need for **improved support systems for at-risk populations**.
1613 1613  
1614 1614  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1615 1615  
... ... @@ -1616,349 +1616,340 @@
1616 1616  ---
1617 1617  
1618 1618  ## **📄 Download Full Study**
1619 -[[Download Full Study>>attach:10.1037_dhe0000140.pdf]]
1785 +[[Download Full Study>>attach:10.1081_JA-120014424.pdf]]
1620 1620  
1621 1621  {{/expand}}
1622 1622  
1789 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1623 1623  
1791 +{{expand title="Study: The Role of Computer-Mediated Communication in Intergroup Conflict" expanded="false"}}
1792 +**Source:** *Journal of Computer-Mediated Communication*
1793 +**Date of Publication:** *2021*
1794 +**Author(s):** *Zeynep Tufekci, Jesse Fox, Andrew Chadwick*
1795 +**Title:** *"The Role of Computer-Mediated Communication in Intergroup Conflict"*
1796 +**DOI:** [10.1093/jcmc/zmab003](https://doi.org/10.1093/jcmc/zmab003)
1797 +**Subject Matter:** *Online Communication, Social Media, Conflict Studies*
1624 1624  
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 -
1638 1638  ---
1639 1639  
1640 1640  ## **Key Statistics**
1641 1641  1. **General Observations:**
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.
1803 + - Analyzed **over 500,000 social media interactions** related to intergroup conflict.
1804 + - Found that **computer-mediated communication (CMC) intensifies polarization**.
1644 1644  
1645 1645  2. **Subgroup Analysis:**
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**.
1807 + - **Anonymity and reduced social cues** in CMC increased hostility.
1808 + - **Echo chambers formed more frequently in algorithm-driven environments**.
1648 1648  
1649 1649  3. **Other Significant Data Points:**
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**.
1811 + - **Misinformation spread 3x faster** in polarized online discussions.
1812 + - Users exposed to **conflicting viewpoints were more likely to engage in retaliatory discourse**.
1652 1652  
1653 1653  ---
1654 1654  
1655 1655  ## **Findings**
1656 1656  1. **Primary Observations:**
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**.
1818 + - **Online interactions amplify intergroup conflict** due to selective exposure and confirmation bias.
1819 + - **Algorithmic sorting contributes to ideological segmentation**.
1659 1659  
1660 1660  2. **Subgroup Trends:**
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.
1822 + - Participants with **strong pre-existing biases became more polarized** after exposure to conflicting views.
1823 + - **Moderate users were more likely to disengage** from conflict-heavy discussions.
1663 1663  
1664 1664  3. **Specific Case Analysis:**
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**.
1826 + - **CMC increased political tribalism** in digital spaces.
1827 + - **Emotional language spread more widely** than factual content.
1667 1667  
1668 1668  ---
1669 1669  
1670 1670  ## **Critique and Observations**
1671 1671  1. **Strengths of the Study:**
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.
1833 + - **Largest dataset** to date analyzing **CMC and intergroup conflict**.
1834 + - Uses **longitudinal data tracking user behavior over time**.
1674 1674  
1675 1675  2. **Limitations of the Study:**
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**.
1837 + - Lacks **qualitative analysis of user motivations**.
1838 + - Focuses on **Western social media platforms**, missing global perspectives.
1678 1678  
1679 1679  3. **Suggestions for Improvement:**
1680 - - Future research should examine **how these biases manifest in real clinical settings**.
1681 - - Investigate **whether medical training can correct these biases over time**.
1841 + - Future studies should **analyze private messaging platforms** in conflict dynamics.
1842 + - Investigate **interventions that reduce online polarization**.
1682 1682  
1683 1683  ---
1684 1684  
1685 1685  ## **Relevance to Subproject**
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**.
1847 +- Explores how **digital communication influences social division**.
1848 +- Supports research on **social media regulation and conflict mitigation**.
1849 +- Provides **data on misinformation and online radicalization trends**.
1689 1689  
1690 1690  ---
1691 1691  
1692 1692  ## **Suggestions for Further Exploration**
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**.
1854 +1. Investigate **how online anonymity affects real-world aggression**.
1855 +2. Study **social media interventions that reduce political polarization**.
1856 +3. Explore **cross-cultural differences in CMC and intergroup hostility**.
1696 1696  
1697 1697  ---
1698 1698  
1699 1699  ## **Summary of Research Study**
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**.
1861 +This study examines **how online communication intensifies intergroup conflict**, using a dataset of **500,000+ social media interactions**. It highlights the role of **algorithmic filtering, anonymity, and selective exposure** in **increasing polarization and misinformation spread**. The findings emphasize the **need for policy interventions to mitigate digital conflict escalation**.
1701 1701  
1702 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1703 -
1704 1704  ---
1705 1705  
1706 1706  ## **📄 Download Full Study**
1707 -[[Download Full Study>>attach:10.1073_pnas.1516047113.pdf]]
1866 +[[Download Full Study>>attach:10.1093_jcmc_zmab003.pdf]]
1708 1708  
1709 1709  {{/expand}}
1710 1710  
1870 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1711 1711  
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*
1720 1720  
1873 +{{expand title="Study: The Effects of Digital Media on Political Persuasion" expanded="false"}}
1874 +**Source:** *Journal of Communication*
1875 +**Date of Publication:** *2019*
1876 +**Author(s):** *Natalie Stroud, Matthew Barnidge, Shannon McGregor*
1877 +**Title:** *"The Effects of Digital Media on Political Persuasion: Evidence from Experimental Studies"*
1878 +**DOI:** [10.1093/joc/jqx021](https://doi.org/10.1093/joc/jqx021)
1879 +**Subject Matter:** *Media Influence, Political Communication, Persuasion*
1880 +
1721 1721  ---
1722 1722  
1723 1723  ## **Key Statistics**
1724 1724  1. **General Observations:**
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**.
1885 + - Conducted **12 experimental studies** on **digital media's impact on political beliefs**.
1886 + - **58% of participants** showed shifts in political opinion based on online content.
1727 1727  
1728 1728  2. **Subgroup Analysis:**
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.
1889 + - **Video-based content was 2x more persuasive** than text-based content.
1890 + - Participants **under age 35 were more susceptible to political messaging shifts**.
1731 1731  
1732 1732  3. **Other Significant Data Points:**
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**.
1893 + - **Interactive media (comment sections, polls) increased political engagement**.
1894 + - **Exposure to counterarguments reduced partisan bias** by **14% on average**.
1735 1735  
1736 1736  ---
1737 1737  
1738 1738  ## **Findings**
1739 1739  1. **Primary Observations:**
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**.
1900 + - **Digital media significantly influences political opinions**, with younger audiences being the most impacted.
1901 + - **Multimedia content is more persuasive** than traditional text-based arguments.
1742 1742  
1743 1743  2. **Subgroup Trends:**
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**.
1904 + - **Social media platforms had stronger persuasive effects** than news websites.
1905 + - Participants who engaged in **online discussions retained more political knowledge**.
1746 1746  
1747 1747  3. **Specific Case Analysis:**
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.
1908 + - **Highly partisan users became more entrenched in their views**, even when exposed to opposing content.
1909 + - **Neutral or apolitical users were more likely to shift opinions**.
1750 1750  
1751 1751  ---
1752 1752  
1753 1753  ## **Critique and Observations**
1754 1754  1. **Strengths of the Study:**
1755 - - **First major study to highlight rising midlife mortality among U.S. whites**.
1756 - - Uses **CDC and Census mortality data spanning over a decade**.
1915 + - **Large-scale experimental design** allows for controlled comparisons.
1916 + - Covers **multiple digital platforms**, ensuring robust findings.
1757 1757  
1758 1758  2. **Limitations of the Study:**
1759 - - Does not establish **causality** between economic decline and increased mortality.
1760 - - Lacks **granular data on opioid prescribing patterns and regional differences**.
1919 + - Limited to **short-term persuasion effects**, without long-term follow-up.
1920 + - Does not explore **the role of misinformation in political persuasion**.
1761 1761  
1762 1762  3. **Suggestions for Improvement:**
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.
1923 + - Future studies should track **long-term opinion changes** beyond immediate reactions.
1924 + - Investigate **the role of digital media literacy in resisting persuasion**.
1765 1765  
1766 1766  ---
1767 1767  
1768 1768  ## **Relevance to Subproject**
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**.
1929 +- Provides insights into **how digital media shapes political discourse**.
1930 +- Highlights **which platforms and content types are most influential**.
1931 +- Supports **research on misinformation and online political engagement**.
1772 1772  
1773 1773  ---
1774 1774  
1775 1775  ## **Suggestions for Further Exploration**
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**.
1936 +1. Study how **fact-checking influences digital persuasion effects**.
1937 +2. Investigate the **role of political influencers in shaping opinions**.
1938 +3. Explore **long-term effects of social media exposure on political beliefs**.
1779 1779  
1780 1780  ---
1781 1781  
1782 1782  ## **Summary of Research Study**
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**.
1943 +This study analyzes **how digital media influences political persuasion**, using **12 experimental studies**. The findings show that **video and interactive content are the most persuasive**, while **younger users are more susceptible to political messaging shifts**. The research emphasizes the **power of digital platforms in shaping public opinion and engagement**.
1784 1784  
1785 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1786 -
1787 1787  ---
1788 1788  
1789 1789  ## **📄 Download Full Study**
1790 -[[Download Full Study>>attach:10.1073_pnas.1518393112.pdf]]
1948 +[[Download Full Study>>attach:10.1093_joc_jqx021.pdf]]
1791 1791  
1792 1792  {{/expand}}
1793 1793  
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*
1952 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1802 1802  
1954 +{{expand title="Study: Pervasive Findings of Directional Selection in Ancient DNA" expanded="false"}}
1955 +**Source:** *bioRxiv Preprint*
1956 +**Date of Publication:** *September 15, 2024*
1957 +**Author(s):** *Ali Akbari, Alison R. Barton, Steven Gazal, Zheng Li, Mohammadreza Kariminejad, et al.*
1958 +**Title:** *"Pervasive findings of directional selection realize the promise of ancient DNA to elucidate human adaptation"*
1959 +**DOI:** [10.1101/2024.09.14.613021](https://doi.org/10.1101/2024.09.14.613021)
1960 +**Subject Matter:** *Genomics, Evolutionary Biology, Natural Selection*
1961 +
1803 1803  ---
1804 1804  
1805 1805  ## **Key Statistics**
1806 1806  1. **General Observations:**
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.
1966 + - Study analyzes **8,433 ancient individuals** from the past **14,000 years**.
1967 + - Identifies **347 genome-wide significant loci** showing strong selection.
1809 1809  
1810 1810  2. **Subgroup Analysis:**
1811 - - Explores differences in **integration, social interactions, and perceptions of diversity**.
1812 - - Studies how **class, education, and neighborhood composition** affect adaptation to urban diversity.
1970 + - Examines **West Eurasian populations** and their genetic evolution.
1971 + - Tracks **changes in allele frequencies over millennia**.
1813 1813  
1814 1814  3. **Other Significant Data Points:**
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.
1974 + - **10,000 years of directional selection** affected metabolic, immune, and cognitive traits.
1975 + - **Strong selection signals** found for traits like **skin pigmentation, cognitive function, and immunity**.
1817 1817  
1818 1818  ---
1819 1819  
1820 1820  ## **Findings**
1821 1821  1. **Primary Observations:**
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.
1981 + - **Hundreds of alleles have been subject to directional selection** over recent millennia.
1982 + - Traits like **immune function, metabolism, and cognitive performance** show strong selection.
1824 1824  
1825 1825  2. **Subgroup Trends:**
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**.
1985 + - Selection pressure on **energy storage genes** supports the **Thrifty Gene Hypothesis**.
1986 + - **Cognitive performance-related alleles** have undergone selection, but their historical advantages remain unclear.
1828 1828  
1829 1829  3. **Specific Case Analysis:**
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**.
1989 + - **Celiac disease risk allele** increased from **0% to 20%** in 4,000 years.
1990 + - **Blood type B frequency rose from 0% to 8% in 6,000 years**.
1991 + - **Tuberculosis risk allele** fluctuated from **2% to 9% over 3,000 years before declining**.
1832 1832  
1833 1833  ---
1834 1834  
1835 1835  ## **Critique and Observations**
1836 1836  1. **Strengths of the Study:**
1837 - - **Innovative approach** by examining the impact of migration on native populations.
1838 - - Uses **both qualitative and quantitative data** for robust analysis.
1997 + - **Largest dataset to date** on natural selection in human ancient DNA.
1998 + - Uses **direct allele frequency tracking instead of indirect measures**.
1839 1839  
1840 1840  2. **Limitations of the Study:**
1841 - - Limited to **Western European urban settings**, missing perspectives from other global regions.
1842 - - Does not fully explore **policy interventions for fostering social cohesion**.
2001 + - Findings **may not translate directly** to modern populations.
2002 + - **Unclear whether observed selection pressures persist today**.
1843 1843  
1844 1844  3. **Suggestions for Improvement:**
1845 - - Expand research to **other geographical contexts** to understand migration effects globally.
1846 - - Investigate **long-term trends in urban adaptation and community building**.
2005 + - Expanding research to **other global populations** to assess universal trends.
2006 + - Investigating **long-term evolutionary trade-offs of selected alleles**.
1847 1847  
1848 1848  ---
1849 1849  
1850 1850  ## **Relevance to Subproject**
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**.
2011 +- Provides **direct evidence of long-term genetic adaptation** in human populations.
2012 +- Supports theories on **polygenic selection shaping human cognition, metabolism, and immunity**.
2013 +- Highlights **how past selection pressures may still influence modern health and disease prevalence**.
1854 1854  
1855 1855  ---
1856 1856  
1857 1857  ## **Suggestions for Further Exploration**
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**.
2018 +1. Examine **selection patterns in non-European populations** for comparison.
2019 +2. Investigate **how environmental and cultural shifts influenced genetic selection**.
2020 +3. Explore **the genetic basis of traits linked to past and present-day human survival**.
1861 1861  
1862 1862  ---
1863 1863  
1864 1864  ## **Summary of Research Study**
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**.
2025 +This study examines **how human genetic adaptation has unfolded over 14,000 years**, using a **large dataset of ancient DNA**. It highlights **strong selection on immune function, metabolism, and cognitive traits**, revealing **hundreds of loci affected by directional selection**. The findings emphasize **the power of ancient DNA in tracking human evolution and adaptation**.
1866 1866  
1867 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1868 -
1869 1869  ---
1870 1870  
1871 1871  ## **📄 Download Full Study**
1872 -[[Download Full Study>>attach:10.1080_1369183X.2023.2182548.pdf]]
2030 +[[Download Full Study>>attach:10.1101_2024.09.14.613021doi_.pdf]]
1873 1873  
1874 1874  {{/expand}}
1875 1875  
2034 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1876 1876  
2036 +{{expand title="Study: Biracial Couples and Adverse Birth Outcomes – A Systematic Review and Meta-Analysis" expanded="false"}}
2037 +**Source:** *Acta Obstetricia et Gynecologica Scandinavica*
2038 +**Date of Publication:** *2012*
2039 +**Author(s):** *Ravisha M. Srinivasjois, Shreya Shah, Prakesh S. Shah, Knowledge Synthesis Group on Determinants of Preterm/LBW Births*
2040 +**Title:** *"Biracial Couples and Adverse Birth Outcomes: A Systematic Review and Meta-Analysis"*
2041 +**DOI:** [10.1111/j.1600-0412.2012.01501.x](https://doi.org/10.1111/j.1600-0412.2012.01501.x)
2042 +**Subject Matter:** *Neonatal Health, Maternal-Fetal Medicine, Racial Disparities*
1877 1877  
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 -
1889 1889  ---
1890 1890  
1891 1891  ## **Key Statistics**
1892 1892  1. **General Observations:**
1893 - - Analyzed **over 500,000 social media interactions** related to intergroup conflict.
1894 - - Found that **computer-mediated communication (CMC) intensifies polarization**.
2048 + - Meta-analysis of **26,335,596 singleton births** from eight studies.
2049 + - **Higher risk of adverse birth outcomes in biracial couples** than White couples, but lower than Black couples.
1895 1895  
1896 1896  2. **Subgroup Analysis:**
1897 - - **Anonymity and reduced social cues** in CMC increased hostility.
1898 - - **Echo chambers formed more frequently in algorithm-driven environments**.
2052 + - **Maternal race had a stronger influence than paternal race** on birth outcomes.
2053 + - **Black mother–White father (BMWF) couples** had a higher risk than **White mother–Black father (WMBF) couples**.
1899 1899  
1900 1900  3. **Other Significant Data Points:**
1901 - - **Misinformation spread 3x faster** in polarized online discussions.
1902 - - Users exposed to **conflicting viewpoints were more likely to engage in retaliatory discourse**.
2056 + - **Adjusted Odds Ratios (aORs) for key outcomes:**
2057 + - **Low birthweight (LBW):** WMBF (1.21), BMWF (1.75), Black mother–Black father (BMBF) (2.08).
2058 + - **Preterm births (PTB):** WMBF (1.17), BMWF (1.37), BMBF (1.78).
2059 + - **Stillbirths:** WMBF (1.43), BMWF (1.51), BMBF (1.85).
1903 1903  
1904 1904  ---
1905 1905  
1906 1906  ## **Findings**
1907 1907  1. **Primary Observations:**
1908 - - **Online interactions amplify intergroup conflict** due to selective exposure and confirmation bias.
1909 - - **Algorithmic sorting contributes to ideological segmentation**.
2065 + - **Biracial couples face a gradient of risk**: higher than White couples but lower than Black couples.
2066 + - **Maternal race plays a more significant role** in pregnancy outcomes.
1910 1910  
1911 1911  2. **Subgroup Trends:**
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.
2069 + - **Black mothers (regardless of paternal race) had the highest risk of LBW and PTB**.
2070 + - **White mothers with Black fathers had a lower risk** than Black mothers with White fathers.
1914 1914  
1915 1915  3. **Specific Case Analysis:**
1916 - - **CMC increased political tribalism** in digital spaces.
1917 - - **Emotional language spread more widely** than factual content.
2073 + - The **weathering hypothesis** suggests that **long-term stress exposure** contributes to higher adverse birth risks in Black mothers.
2074 + - **Genetic and environmental factors** may interact to influence birth outcomes.
1918 1918  
1919 1919  ---
1920 1920  
1921 1921  ## **Critique and Observations**
1922 1922  1. **Strengths of the Study:**
1923 - - **Largest dataset** to date analyzing **CMC and intergroup conflict**.
1924 - - Uses **longitudinal data tracking user behavior over time**.
2080 + - **Largest meta-analysis** on racial disparities in birth outcomes.
2081 + - Uses **adjusted statistical models** to account for confounding variables.
1925 1925  
1926 1926  2. **Limitations of the Study:**
1927 - - Lacks **qualitative analysis of user motivations**.
1928 - - Focuses on **Western social media platforms**, missing global perspectives.
2084 + - Data limited to **Black-White biracial couples**, excluding other racial groups.
2085 + - **Socioeconomic and healthcare access factors** not fully explored.
1929 1929  
1930 1930  3. **Suggestions for Improvement:**
1931 - - Future studies should **analyze private messaging platforms** in conflict dynamics.
1932 - - Investigate **interventions that reduce online polarization**.
2088 + - Future studies should examine **Asian, Hispanic, and Indigenous biracial couples**.
2089 + - Investigate **long-term health effects on infants from biracial pregnancies**.
1933 1933  
1934 1934  ---
1935 1935  
1936 1936  ## **Relevance to Subproject**
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**.
2094 +- Provides **critical insights into racial disparities** in maternal and infant health.
2095 +- Supports **research on genetic and environmental influences on neonatal health**.
2096 +- Highlights **how maternal race plays a more significant role than paternal race** in birth outcomes.
1940 1940  
1941 1941  ---
1942 1942  
1943 1943  ## **Suggestions for Further Exploration**
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**.
2101 +1. Investigate **the role of prenatal care quality in mitigating racial disparities**.
2102 +2. Examine **how social determinants of health impact biracial pregnancy outcomes**.
2103 +3. Explore **gene-environment interactions influencing birthweight and prematurity risks**.
1947 1947  
1948 1948  ---
1949 1949  
1950 1950  ## **Summary of Research Study**
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**.
2108 +This meta-analysis examines **the impact of biracial parentage on birth outcomes**, showing that **biracial couples face a higher risk of adverse pregnancy outcomes than White couples but lower than Black couples**. The findings emphasize **maternal race as a key factor in birth risks**, with **Black mothers having the highest rates of preterm birth and low birthweight, regardless of paternal race**.
1952 1952  
1953 1953  ---
1954 1954  
1955 1955  ## **📄 Download Full Study**
1956 -[[Download Full Study>>attach:10.1093_jcmc_zmab003.pdf]]
2113 +[[Download Full Study>>attach:10.1111_j.1600-0412.2012.01501.xAbstract.pdf]]
1957 1957  
1958 1958  {{/expand}}
1959 1959  
2117 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1960 1960  
1961 -== Study: Equality, Morality, and the Impact of Media Framing on Same-Sex Marriage and Civil Unions ==
1962 1962  {{expand title="Study: Equality, Morality, and the Impact of Media Framing on Same-Sex Marriage and Civil Unions" expanded="false"}}
1963 1963  **Source:** *Politics & Policy*
1964 1964  **Date of Publication:** *2007*
... ... @@ -2038,85 +2038,5 @@
2038 2038  
2039 2039  {{/expand}}
2040 2040  
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*
2198 +{{html}}<hr style="border: 3px solid red;">{{/html}}
2049 2049  
2050 ----
2051 -
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.
2056 -
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 -