Raw Story93%

Medical experts argue against Hegseth's testosterone obsession 58%

By María Teresita Armstrong-Matta90%

7/24/2026, 5:50:01 PM

BS Summary: This article contains 17 faulty reasoning types, including Appeal to Authority, Framing Effect, and Confirmation Bias, with Negativity Bias as the most egregious example at 63.9% saturation with 108 hits. Analysis detected 566 faulty-reasoning hits from 169 analyzed words, generating a BS Score of 54.4% and a BS Rank of 58% (9,341 of 21,887 articles). This article is worse (more manipulative) than 57.30% of the article peer group.

Medical experts are warning against Defense Secretary Pete Hegseth's controversial testosterone testing policy for service members. 
Hegseth announced the policy last week, requiring annual testosterone testing for all service members over 30 as part of his "High-T Department of War" initiative. 
The policy faces legal challenges, with a federal judge ordering the Trump administration to explain how it aligns with existing bans on hormone treatment for transgender service members. 
Two medical experts told The Intercept Friday the procedure may reduce fertility in male soldiers. 
Dr. 
Adrian Dobs of Johns Hopkins University School of Medicine explained to The Intercept that testosterone replacement therapy creates dependency and reduces sperm counts in men who take it. 
“Men who take testosterone will have a reduction in their sperm counts,” Dr. 
Dobs said. 
Dr. 
Alvin Matsumoto warned, mandatory screening produces unreliable results since testosterone levels vary based on time of day and meals, potentially leading to unnecessary hormone therapy for otherwise healthy troops. 
Watch the video below. 
Article reasoning-pattern comparisonThis article: 26.0%María Teresita Armstrong-Matta: 9.8%Rawstory: 8.4%Confirmation Bias26.0%This article: 14.8%María Teresita Armstrong-Matta: 3.6%Rawstory: 0.8%Anchoring Bias14.8%This article: 9.5%María Teresita Armstrong-Matta: 4.4%Rawstory: 4.5%Availability Heuristic9.5%This article: 0.0%María Teresita Armstrong-Matta: 0.9%Rawstory: 1.1%Representativeness Heuristic0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.6%Rawstory: 1.0%Hindsight Bias0.0%This article: 0.0%María Teresita Armstrong-Matta: 5.8%Rawstory: 2.2%Overconfidence Bias0.0%This article: 28.4%María Teresita Armstrong-Matta: 15.6%Rawstory: 13.4%Framing Effect28.4%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.4%Loss Aversion0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.3%Rawstory: 0.4%Status Quo Bias0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.1%Sunk Cost Effect0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.6%Rawstory: 0.7%Optimism Bias0.0%This article: 7.7%María Teresita Armstrong-Matta: 2.3%Rawstory: 2.9%Pessimism Bias7.7%This article: 63.9%María Teresita Armstrong-Matta: 20.7%Rawstory: 21.6%Negativity Bias63.9%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 1.2%Self-Serving Bias0.0%This article: 0.0%María Teresita Armstrong-Matta: 7.0%Rawstory: 2.8%Fundamental Attribution Error0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.3%Actor-Observer Bias0.0%This article: 0.0%María Teresita Armstrong-Matta: 1.6%Rawstory: 2.5%In-Group Bias0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.6%Rawstory: 1.6%Out-Group Homogeneity Bias0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.6%Halo Effect0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.7%Rawstory: 0.9%Horn Effect0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.0%Dunning-Kruger Effect0.0%This article: 16.6%María Teresita Armstrong-Matta: 1.1%Rawstory: 1.8%Recency Bias16.6%This article: 4.1%María Teresita Armstrong-Matta: 0.4%Rawstory: 0.7%Primacy Effect4.1%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.1%Blind-Spot Bias0.0%This article: 0.0%María Teresita Armstrong-Matta: 10.2%Rawstory: 6.3%Ad Hominem0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.6%Rawstory: 0.7%Straw Man0.0%This article: 50.3%María Teresita Armstrong-Matta: 3.3%Rawstory: 4.1%Appeal to Authority50.3%This article: 17.2%María Teresita Armstrong-Matta: 3.8%Rawstory: 3.0%False Dilemma17.2%This article: 0.0%María Teresita Armstrong-Matta: 0.3%Rawstory: 1.5%Slippery Slope0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.2%Circular Reasoning0.0%This article: 0.0%María Teresita Armstrong-Matta: 7.7%Rawstory: 12.1%Hasty Generalization0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.6%Rawstory: 0.7%Red Herring0.0%This article: 0.0%María Teresita Armstrong-Matta: 1.2%Rawstory: 0.8%Bandwagon0.0%This article: 18.9%María Teresita Armstrong-Matta: 6.7%Rawstory: 9.2%Appeal to Emotion18.9%This article: 0.0%María Teresita Armstrong-Matta: 2.8%Rawstory: 1.6%Begging the Question0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.8%Rawstory: 3.8%Post Hoc (False Cause)0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.6%Tu Quoque0.0%This article: 16.6%María Teresita Armstrong-Matta: 3.7%Rawstory: 1.7%Burden of Proof16.6%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.1%Appeal to Nature0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.6%Rawstory: 0.5%Composition/Division0.0%This article: 16.6%María Teresita Armstrong-Matta: 1.2%Rawstory: 3.9%Anecdotal16.6%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.3%No True Scotsman0.0%This article: 16.6%María Teresita Armstrong-Matta: 3.1%Rawstory: 2.4%Ambiguity (Equivocation)16.6%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.0%Gambler’s Fallacy0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.1%Middle Ground0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.2%Personal Incredulity0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.1%Special Pleading0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 0.4%Genetic Fallacy0.0%This article: 8.9%María Teresita Armstrong-Matta: 4.2%Rawstory: 5.3%Unattributed Quote8.9%This article: 14.8%María Teresita Armstrong-Matta: 4.6%Rawstory: 4.1%Quote-first Misdirection14.8%This article: 4.1%María Teresita Armstrong-Matta: 9.1%Rawstory: 15.7%Biased Writer Voice4.1%This article: 0.0%María Teresita Armstrong-Matta: 3.3%Rawstory: 3.2%Indoctrination0.0%This article: 0.0%María Teresita Armstrong-Matta: 6.2%Rawstory: 8.0%Politically Left Leaning Bias0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.0%Rawstory: 1.0%Politically Right Leaning Bias0.0%This article: 0.0%María Teresita Armstrong-Matta: 0.5%Rawstory: 0.5%Attempt to Sell a Product or S…0.0%

169 words analyzed.

Speakers

No attributed speakers were identified in this analysis.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.