A New Dentist Told a Man He Had Seven Cavities and His Wife Had Two  a Second Opinion Found He Had None, and Now X Is Sharing Similar Stories 30%

By Sayantan62%

8/6/2026, 5:49:34 AM

BS Summary: This article contains 28 faulty reasoning types, including Anecdotal, Unattributed Quote, and Availability Heuristic, with Appeal to Authority as the most egregious example at 16.7% saturation with 103 hits. Analysis detected 846 faulty-reasoning hits from 616 analyzed words, generating a BS Score of 33.6% and a BS Rank of 30% (20,242 of 28,846 articles). This article is better (less manipulative) than 70.20% of the article peer group.

An X user, @LoganARobison, described his experience with a new dentist after moving to town in a post, who he wrote came “highly recommended.” 
At the first appointment, the dentist told him he had seven cavities and told his wife she had two, despite her never having had a cavity before. 
The couple reluctantly had his wife’s cavities filled before scheduling his own appointment, he wrote. 
However, they grew skeptical once they saw the bill for filling seven cavities, prompting him to request a copy of his X-rays. 
He sent the images to his uncle, a dentist practicing in another state, who told him the X-rays were of such poor quality that they could not confirm a single cavity, let alone seven. 
The couple then canceled the appointment and found a new dentist, who found that he had no cavities at all. 
My wife and I went to a new dentist when we first moved to town. 
He came highly recommended so we didn’t think twice. 
At the first appointment, he told me I had 7 cavities. 
He told my wife she had 2. 
My wife has never had a cavity in her life. 
But we reluctantly got them… 
- Logan Robison (@LoganARobison) August 5, 2026 
Several replies described similar patterns from their own dental history. 
One commenter wrote, “Looking back to when I was a kid, I think my family dentist was doing the same thing. 
I got drilled so many times I lost count. 
My teeth have been F’d ever since then.” 
Others pointed to ownership structure as a warning sign. 
One person wrote, “Same thing happened to me. 
If the office is PE owned or financed by a Private Capital, I move on. 
The family owned practice I go to in Cincinnati takes 9 months to get an appointment because they are the only ones left the community trusts.” 
The X user wrote that the experience left him questioning how widespread undetected billing irregularities might be in dentistry. 
“I’ve learned that now with a dentist and a general contractor. 
Need to triangulate now. 
Online reviews, recommendations, and a 3rd thing… Reddit?”, he wrote in the comments. 
This happened to me recently.. 
Hygienist said "did they talk to you about your 9 cavities?". 
I said "9 cavities!?" 
she said yes and showed me xrays where AI had flagged 9 different places. 
She said lets compare it to your xrays last year, she pulled those up and those had 2… 
- J Lapier (@JustinLapier) August 5, 2026 
Another cautioned against relying on recommendations alone. 
They wrote, “Unfortunately, most people’s recommendation [sic] only means that they subjectively had a pleasant interaction. 
It doesn’t mean the work was of high quality.” 
Another cited a personal connection working in the field. 
They wrote, “I have a very close friend that is a dentist plus 30 years, he said more than half of his procedures, while pertinent and billable, are not absolutely necessary. 
He’s a multimillionaire.” 
The Daily Dot was unable to independently verify the events described in this post, including the specific diagnosis, X-ray quality, or the dentist’s identity. 
The details above reflect the original poster’s account as shared on X. 
Sign up to receive the Daily Dot’s Internet Insider newsletter for urgent news from the frontline of online. 
The post A New Dentist Told a Man He Had Seven Cavities and His Wife Had Two  a Second Opinion Found He Had None, and Now X Is Sharing Similar Stories appeared first on The Daily Dot . 
Article reasoning-pattern comparisonThis article: 5.7%Sayantan: 4.7%dailydot.com: 3.5%Confirmation Bias5.7%This article: 6.5%Sayantan: 1.4%dailydot.com: 0.8%Anchoring Bias6.5%This article: 9.7%Sayantan: 4.5%dailydot.com: 3.5%Availability Heuristic9.7%This article: 1.5%Sayantan: 0.7%dailydot.com: 1.0%Representativeness Heuristic1.5%This article: 0.0%Sayantan: 0.7%dailydot.com: 0.6%Hindsight Bias0.0%This article: 0.0%Sayantan: 2.2%dailydot.com: 1.3%Overconfidence Bias0.0%This article: 2.4%Sayantan: 3.0%dailydot.com: 4.2%Framing Effect2.4%This article: 0.8%Sayantan: 0.7%dailydot.com: 0.5%Loss Aversion0.8%This article: 5.7%Sayantan: 0.1%dailydot.com: 0.5%Status Quo Bias5.7%This article: 2.4%Sayantan: 0.2%dailydot.com: 0.2%Sunk Cost Effect2.4%This article: 0.0%Sayantan: 0.7%dailydot.com: 1.0%Optimism Bias0.0%This article: 2.3%Sayantan: 1.6%dailydot.com: 1.2%Pessimism Bias2.3%This article: 8.8%Sayantan: 7.9%dailydot.com: 7.5%Negativity Bias8.8%This article: 0.0%Sayantan: 0.6%dailydot.com: 0.9%Self-Serving Bias0.0%This article: 0.0%Sayantan: 1.2%dailydot.com: 2.1%Fundamental Attribution Error0.0%This article: 0.0%Sayantan: 0.1%dailydot.com: 0.2%Actor-Observer Bias0.0%This article: 0.0%Sayantan: 1.9%dailydot.com: 1.2%In-Group Bias0.0%This article: 0.0%Sayantan: 1.3%dailydot.com: 1.1%Out-Group Homogeneity Bias0.0%This article: 0.5%Sayantan: 0.4%dailydot.com: 1.8%Halo Effect0.5%This article: 0.0%Sayantan: 0.3%dailydot.com: 0.3%Horn Effect0.0%This article: 0.0%Sayantan: 0.0%dailydot.com: 0.0%Dunning-Kruger Effect0.0%This article: 0.8%Sayantan: 0.5%dailydot.com: 0.6%Recency Bias0.8%This article: 3.9%Sayantan: 0.3%dailydot.com: 0.3%Primacy Effect3.9%This article: 0.0%Sayantan: 0.1%dailydot.com: 0.1%Blind-Spot Bias0.0%This article: 0.0%Sayantan: 1.8%dailydot.com: 1.7%Ad Hominem0.0%This article: 0.0%Sayantan: 0.1%dailydot.com: 0.3%Straw Man0.0%This article: 16.7%Sayantan: 2.6%dailydot.com: 1.6%Appeal to Authority16.7%This article: 2.4%Sayantan: 2.1%dailydot.com: 1.8%False Dilemma2.4%This article: 0.0%Sayantan: 0.4%dailydot.com: 0.6%Slippery Slope0.0%This article: 4.2%Sayantan: 0.1%dailydot.com: 0.1%Circular Reasoning4.2%This article: 8.1%Sayantan: 12.4%dailydot.com: 7.7%Hasty Generalization8.1%This article: 0.0%Sayantan: 0.3%dailydot.com: 0.2%Red Herring0.0%This article: 0.0%Sayantan: 0.8%dailydot.com: 2.1%Bandwagon0.0%This article: 1.9%Sayantan: 4.0%dailydot.com: 5.7%Appeal to Emotion1.9%This article: 1.5%Sayantan: 0.7%dailydot.com: 0.8%Begging the Question1.5%This article: 4.2%Sayantan: 1.2%dailydot.com: 1.2%Post Hoc (False Cause)4.2%This article: 0.0%Sayantan: 0.1%dailydot.com: 0.2%Tu Quoque0.0%This article: 3.1%Sayantan: 2.7%dailydot.com: 1.6%Burden of Proof3.1%This article: 0.0%Sayantan: 0.3%dailydot.com: 0.1%Appeal to Nature0.0%This article: 0.0%Sayantan: 0.2%dailydot.com: 0.2%Composition/Division0.0%This article: 16.7%Sayantan: 11.0%dailydot.com: 6.4%Anecdotal16.7%This article: 0.0%Sayantan: 0.3%dailydot.com: 0.1%No True Scotsman0.0%This article: 7.8%Sayantan: 1.3%dailydot.com: 1.6%Ambiguity (Equivocation)7.8%This article: 0.0%Sayantan: 0.0%dailydot.com: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Sayantan: 0.1%dailydot.com: 0.2%Middle Ground0.0%This article: 0.6%Sayantan: 0.2%dailydot.com: 0.2%Personal Incredulity0.6%This article: 0.0%Sayantan: 0.1%dailydot.com: 0.1%Special Pleading0.0%This article: 0.0%Sayantan: 0.3%dailydot.com: 0.1%Genetic Fallacy0.0%This article: 10.6%Sayantan: 5.5%dailydot.com: 4.3%Unattributed Quote10.6%This article: 0.0%Sayantan: 2.5%dailydot.com: 2.7%Quote-first Misdirection0.0%This article: 4.9%Sayantan: 1.8%dailydot.com: 3.3%Biased Writer Voice4.9%This article: 0.6%Sayantan: 0.4%dailydot.com: 1.4%Indoctrination0.6%This article: 0.0%Sayantan: 0.1%dailydot.com: 0.1%Politically Left Leaning Bias0.0%This article: 0.0%Sayantan: 0.5%dailydot.com: 0.6%Politically Right Leaning Bias0.0%This article: 2.9%Sayantan: 1.0%dailydot.com: 1.6%Attempt to Sell a Product or S…2.9%

616 words analyzed.

Speakers

3speakers6.2%attributed speech578writer words
Selected voice

Daily Dot

0%flagged-word coverage
24 attributed words63% of attributed speech79% writer coverage
0%7.5%15.0%Unattributed Quote-11.2 ptsWriter: 11.2%Daily Dot: 0.0%0.0%Biased Writer Voice-5.2 ptsWriter: 5.2%Daily Dot: 0.0%0.0%Attempt to Sell a Product -3.1 ptsWriter: 3.1%Daily Dot: 0.0%0.0%Indoctrination-0.7 ptsWriter: 0.7%Daily Dot: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

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