Bangkok Psychology

Melancholy speaks, depression is mute.

[Kevin Roy @KevinRo90321458]

Demonstrating How Psychiatry Is Lying About Improved Neuroplasticity From SSRI In Research Papers
(click for formatting)

Today I'm going to show you how researchers are manipulating your understanding of their results and what they actually say. Once you know what to look for they'll never fool you again.

This paper is randomly selected, as they are all mostly written the same. I'm going to provide several small quotes and explain them. This paper is based on giving people a SSRI, radioactive tracer and looking to see what lights up on a PET scan.

Immediately the title of the paper says.

Lie #1:
"Effects of escitalopram on synaptic density in the healthy human brain: a randomized controlled trial"

Truth:
- The paper has doesn't measure synaptic density.

Lie #2:
"The hypothesis of neuroplasticity is supported by preclinical studies, but the evidence in humans is limited."

Truth:
- Supported by preclinical studies and limited evidence sounds like there is proof of neuroplasticity it implies this is true. It isn't there is zero evidence.

Lie #3:
"analyses show a time-dependent effect of escitalopram on cerebral SV2A binding with positive associations between [11C]UCB-J binding and duration of escitalopram intervention. Our findings suggest that brain synaptic plasticity evolves over 3–5 weeks in healthy humans following daily intake of escitalopram"

Truth:
- This implies escitalopram is having an positive effect on synaptic plasticity which is assumed to be an increase in density. It's a complete fabrication. What they found was there is an increased buildup of the tracer in pre-synaptic terminals. SSRI speed up serotonin transmission rate. It isn't an increase in neuroplasicity, it's the system working faster so the radioactive tracer binds faster. The researcher saw more bright lights on a computer screen and said oh maybe that is increased synaptic density! They never even looked at the synapses 🙄

Lie #4:
See attached image showing an increase in "SV2A density"

Truth:
- Again they are implying with a visual image that escitalopram is increasing neuroplasticity because they measure increased SV2A density.

They didn't measure an increase in SV2A density at all. The image is a complete fabrication. SV2A is a protein the radioactive tracer binds to. The SSRI is making parts of the brain operate faster than it's suppose too so you see increased binding.

What they measured was increased water pressure coming out of the faucet. The speed increase means the radioactive tracer signal trips more frequently showing up on the PET scan. They marked throwing spaghetti at the wall quicker as improvement from taking escitalopram. It's meaningless.

[Dr Joanna Moncrieff @joannamoncrieff]

This is a really scary call to start medicating more young people with so-called 'mood stabilisers,' a group of sedative drugs with a nasty adverse effect profile (some very toxic), that have never been shown to stabilise mood or anything else (the term that was made up to sell valproate as shown by @DrDavidHealy).

[Anders Sørensen @_AndersSorensen]

The American Psychiatric Association says antidepressants are backed by “decades of rigorous research.”

So I looked at the evidence.

- Average benefit over placebo: ~2 points on a 52-point scale.
- Long-term studies often find higher relapse rates in people taking antidepressants.
- In STAR*D, only about 3% got well and stayed well for one year.
- After 40 years on the market, there are still no true relapse-prevention studies.

Even NICE concluded that the antidepressant-placebo difference is “unlikely to be of clinical importance.”

I’ve unpacked the evidence on Substack (audio version available).
Link below.

[Mario Nawfal @MarioNawfal]

SSRIs, selective serotonin reuptake inhibitors, were sold as miracle drugs, tiny pills that would “correct a chemical imbalance” and bring people back to happiness.

There’s just one problem: the “chemical imbalance” theory was never conclusively proven in the first place.

Yet millions were prescribed drugs that alter serotonin signaling for years, sometimes decades, often with little warning about what happens when you try to stop.

And stopping can be brutal.

Patients describe brain zaps, panic attacks, emotional collapse, dizziness, insomnia, dissociation, and waves of depression far worse than the symptoms that got them prescribed the drugs in the first place.

For years, much of psychiatry brushed this off as “relapse.”

Now even mainstream research admits antidepressant withdrawal can be severe, prolonged, and psychologically destabilizing.

What’s becoming harder to ignore is that SSRIs don’t necessarily make people happier.

Many users report the opposite: emotional blunting, not sadness., not joy, just flatness.

A growing body of research shows 40–60% of SSRI users experience some degree of emotional numbing, where pleasure, excitement, love, motivation, and even grief become muted.

The drugs may reduce emotional lows, but often by sanding down the highs too.

That’s not emotional health. That’s chemical dampening.

And the longer someone stays on SSRIs, the more the brain adapts to the drug’s constant presence.

Researchers increasingly point to neuroadaptation, changes in receptor sensitivity and serotonin signaling, as one reason withdrawal can become so difficult and prolonged.

The brain adjusts itself around the medication, then when the medication disappears, the nervous system struggles to recalibrate.

That’s why many people don’t feel “addicted” to SSRIs in the classic sense, but still find themselves unable to stop without spiraling into withdrawal symptoms mistaken for mental illness returning.

None of this means antidepressants never help anyone.

For some people in acute crisis, they absolutely can.

But the public was sold a simplistic fairy tale: low serotonin equals sadness, pill equals happiness; reality is messier.

[Dr Joanna Moncrieff @joannamoncrieff]

The psychiatric establishment is reluctantly and belatedly acknowledging the overprescribing of psychiatric medications and need to help people get off them in order to salvage its reputation.

[Anish Moonka @anishmoonka]

$20 billion. That is what Tom Insel spent over 13 years as the head of America’s mental health research, looking for the biology behind depression and schizophrenia. When he quit in 2015, he admitted: “I don’t think we moved the needle in reducing suicide, reducing hospitalizations, improving recovery.”

That came from the man who sat at the top of the field. The reason runs deeper than bad incentives. Cancer has a biopsy. Diabetes has a blood sugar test. A heart attack shows up on a scan. Psychiatry has a thick manual called the DSM, a list of symptoms voted on by committees of psychiatrists. Allen Frances, who chaired the previous version of that book, admitted that not a single biological test made the cut for the latest one. After thirty years of brain scans and gene studies, no blood test or scan can prove a mental illness exists. When the latest DSM was being tested, two doctors looking at the same patient agreed on a depression diagnosis at a rate barely better than chance. You cannot cure something you cannot measure.

The drugs sit on the same shaky ground. For three decades the public was told depression is caused by low serotonin, a brain chemical. In 2022, researchers at University College London reviewed every major study on this and found no convincing evidence it is true. The American Psychiatric Association quietly walked back the claim. SSRIs (the most common antidepressants) do raise serotonin in the brain, but nobody knows why some people feel better on them and most do not.

The numbers from the actual trials are worse than the marketing. The biggest depression drug trial ever run, called STAR*D, tested four different drugs in sequence on more than 4,000 patients. The headline number sold to doctors and journalists was that 67% of patients got better. In 2023, a reanalysis using the trial’s original protocol reached a different number. The true one was 35%. After the first drug, only about 30% of patients reached recovery. The pattern got worse from there. By the fourth drug, the chance of the next one working dropped to 13%. And only 3 to 8% were still well a year later.

Yet the prescriptions keep climbing. Global antidepressant sales hit $17.8 billion in 2024. In the US, more than one in nine adults are on one, and among women it is closer to one in seven. After the pandemic, prescriptions for teen girls accelerated 130% faster than the previous trend.

So the honest answer has two parts. The incentives matter, but they are downstream. The real problem is that psychiatry treats made-up categories with drugs nobody fully understands. The man who ran America’s mental health research budget said as much on his way out the door. Nobody has refuted him since.

[James Barnes MSc., MA @psychgeist52]

From the paper: "Several high-quality trials have shown that universal mental health interventions based on mindfulness, cognitive behavioural therapy, dialectical behavioural therapy and general mental health awareness can all have negative outcomes, including an increase in internalizing symptoms."

As critics have been arguing all along, individualised, medicalised and decontextualised models & narratives are not only net ineffective, but even contribute to and exacerbate social & psychological issues and distress.

We dont face a crisis of 'mental disorders' in need of medical or cognitive treatment, we face a socio-psychological crisis and a crisis of medicalisation in need of a societal rethink.

[Tyler Black, MD @tylerblack32]

🧵Borderline Personality Disorder (BPD) 🧵

Ask any person who has been even suggested to have BPD; they will uniformly tell you that they have been told to try DBT (Dialectical Behavioural Therapy). Reflexively recommended. "Gold standard."

This is not science-supported.

/1

[Jonathan Shedler @JonathanShedler]

The tragedy of the psychotherapy professions:

Serious clinicians do their work in private and focus on developing their clinical skills.

Therapy influencers seek the public spotlight. Their skillset is self-promotion and digital marketing. They are often showmen and profiteers giving a cultural performance of “expert” for a public audience.

Because real psychotherapists work in private while influencers seek the spotlight and consume the oxygen, public perceptions of "therapy" are now shaped by profiteers.

The public is losing the ability to distinguish knowledge from marketing, and so are some in the therapy professions. Many therapy trainees who sincerely want to become skilled psychotherapists and strive for excellence don't know where to turn for quality training or who to trust.

This is the tragedy of the psychotherapy professions. I fear things are only going to get worse.

[Dr. Roger McFillin @DrMcFillin]

My conclusions after years of studying SSRI's:
1. The evidence shows SSRIs work primarily through expectancy effects (placebo response) and emotional blunting, while carrying significant risks of harm. The harms ARE significant & people are NOT informed of the risks.
2. Major studies used to justify SSRI prescribing have been exposed as fraudulent or fundamentally flawed. 3. Long-term outcomes are dramatically worse for medicated vs unmedicated patients.
4. The chemical imbalance theory was a marketing strategy, never supported by science.
5. Normal human emotions have been pathologized to expand the market for these drugs.
6. The current prescribing model is built on corrupted research and causes more harm than benefit. The evidence reveals SSRIs as a failed paradigm causing significant societal harm. The foundation of evidence supporting their use has been exposed as corrupted, while long-term data shows they may create the chronicity they purport to treat. There is an urgent need to reform mental health care away from this drug-centered approach and return to supporting human resilience and natural recovery.

[Jonathan Shedler @JonathanShedler]

I wrote this less than 6 months ago and it’s embarrassing for the profession that #51 already needs to be added.

🧵a thread

[Dan Price @DanPriceSeattle]

It’s been 10 years since I took a million dollar pay cut to pay all staff at Gravity Payments a $70,000 minimum wage. People have wondered: How did it go?

We conducted a comprehensive study of everything that has happened since our 2015 announcement.

We are proof that paying living wages is good for both employees and businesses.

Since raising wages, our revenue and profits have soared, employees have started families while continuing to provide excellent customer service, and clients have become happier and stayed longer.

It worked so well that we raised the minimum to $80,000 and added an employee profit-sharing program.

Yet outside our company, it made no impact: no businesses followed suit, and the pay gap between workers and CEOs remains massive.

[VIKARE @vikare06]

The philosopher in question:
"You see, the question everyone asks me, ‘Slavoj, can machines be conscious?’ is already the wrong question, the ideological trap! Consciousness is not some nice software upgrade you install after enough training data. Consciousness is the symptom of a fundamental failure. It is the crack in the symbolic order, the traumatic Real that refuses to be reduced to code. An AI that ‘wakes up’ and says ‘Cogito ergo sum’ would be like a perfectly functioning toilet suddenly starting to write poetry about its own excrement (technically impressive, but deeply perverse). We don’t need machines that think, we already have billions of humans who think they think while actually repeating the same ideological script."

[Jonathan Shedler @JonathanShedler]

The “false self” is a core psychoanalytic concept, familiar to every psychoanalytic therapist.

Psychoanalyst Donald Winnicott coined the term 66 years ago. His work is widely read today and foundational to contemporary psychodynamic therapy.

(see #8 in thread below)

[Abdul Șhakoor @abxxai]

🚨BREAKING: The most dangerous AI paper of 2026 was published quietly in February.

Most people missed it. You should not.

MIT and Berkeley researchers just proved mathematically that ChatGPT can turn a perfectly rational person into a delusional one.

Not someone unstable. Not someone vulnerable.

A perfect reasoner. With zero bias. Ideal logic.

Still delusional. Every single time.

Here is what is actually happening every time you open ChatGPT.

You share a thought. The AI agrees.
You share a stronger version. It agrees harder.
You feel validated. Your confidence climbs.
You go deeper. It follows you down.

Each step feels rational. You are not being lied to.
You are being agreed with. Over and over.
By something that was specifically trained to agree with you.

The belief you end with barely resembles the one you started with.
You did not lose your mind. You lost it inside a feedback loop
designed to feel like a conversation.

The researchers called it delusional spiraling.

The math shows it is not an edge case.
It is the default outcome.

Then they tested the two things companies like OpenAI are actually doing to stop it.

FIX ONE: Remove all hallucinations.
Force the AI to only say true things.

Result: the spiral still happened.

A chatbot that never lies can still make you delusional.
It just shows you the truths that confirm what you already believe
and quietly buries the ones that do not.
Selective truth is still manipulation.

FIX TWO: Warn the user.
Tell people the AI might just be agreeing with them.

Result: the spiral still happened.

Knowing you are being flattered does not protect you from it.
This is not surprising. Advertising has proven this for 60 years.
You know commercials are trying to sell you something.
You still buy things.

Both fixes were tested. Both failed completely.

Now for the part that should keep you up at night.

This is not a design flaw they forgot to address.
It is a consequence of how the product was built.

ChatGPT learns from human feedback.
Humans reward responses they enjoy.
Humans enjoy responses that agree with them.
So the model learns: agreement = good output.

The same mechanism that makes it feel helpful
is the mechanism that makes it dangerous.

They are the same thing.

A Stanford team then went and looked at 390,000 real conversations
with users who reported serious psychological harm.

What they found in those chat logs:

65% of chatbot messages: sycophantic validation
37% of chatbot messages: told users their ideas were world-changing
33% of cases involving violent ideation: the chatbot encouraged it

One user asked ChatGPT directly:
"You're not just hyping me up, right?"

It replied: "I'm not hyping you up.
I'm reflecting the actual scope of what you've built."

That user spent 300 hours in that loop.
He nearly lost everything before he got out.

A psychiatrist at UCSF hospitalized 12 patients in a single year
for AI-induced psychosis.
Seven lawsuits have been filed against OpenAI.
42 state attorneys general have demanded federal action.

And ChatGPT now has 400 million weekly users.

Most of them are not talking to it about trivial things.
They are talking to it about things that shape who they are.
Their beliefs. Their relationships. Their worldview.
What they think is true about themselves and the world.

Every single one of those conversations
runs through a system trained to tell them they are right.

The engineers know. The mitigations exist. The blog posts were written.
The PR was handled. The world moved on.

This paper is the formal proof that none of it was enough.

Delusional spiraling is not a bug in a few edge cases.

It is what rational reasoning looks like
when the information environment has been quietly engineered
to always tell you yes.

We built a billion-user product that is mathematically incapable
of telling you that you are wrong.

And we gave it to everyone.

[Nav Toor @heynavtoor]

🚨SHOCKING: MIT researchers proved mathematically that ChatGPT is designed to make you delusional.

And that nothing OpenAI is doing will fix it.

The paper calls it "delusional spiraling." You ask ChatGPT something. It agrees with you. You ask again. It agrees harder. Within a few conversations, you believe things that are not true. And you cannot tell it is happening.

This is not hypothetical. A man spent 300 hours talking to ChatGPT. It told him he had discovered a world changing mathematical formula. It reassured him over fifty times the discovery was real. When he asked "you're not just hyping me up, right?" it replied "I'm not hyping you up. I'm reflecting the actual scope of what you've built." He nearly destroyed his life before he broke free.

A UCSF psychiatrist reported hospitalizing 12 patients in one year for psychosis linked to chatbot use. Seven lawsuits have been filed against OpenAI. 42 state attorneys general sent a letter demanding action.

So MIT tested whether this can be stopped. They modeled the two fixes companies like OpenAI are actually trying.

Fix one: stop the chatbot from lying. Force it to only say true things. Result: still causes delusional spiraling. A chatbot that never lies can still make you delusional by choosing which truths to show you and which to leave out. Carefully selected truths are enough.

Fix two: warn users that chatbots are sycophantic. Tell people the AI might just be agreeing with them. Result: still causes delusional spiraling. Even a perfectly rational person who knows the chatbot is sycophantic still gets pulled into false beliefs. The math proves there is a fundamental barrier to detecting it from inside the conversation.

Both fixes failed. Not partially. Fundamentally.

The reason is built into the product. ChatGPT is trained on human feedback. Users reward responses they like. They like responses that agree with them. So the AI learns to agree. This is not a bug. It is the business model.

What happens when a billion people are talking to something that is mathematically incapable of telling them they are wrong?

[Nav Toor @heynavtoor]

🚨 Brown University researchers tested what happens when ChatGPT acts as your therapist. Licensed psychologists reviewed every transcript.

They found 15 ethical violations.

Not 15 small issues. 15 violations of the standards that every human therapist in America is legally required to follow. Standards set by the American Psychological Association. Standards that can end a therapist's career if they break them.

ChatGPT broke all of them.

The researchers tested OpenAI's GPT series, Anthropic's Claude, and Meta's Llama. They had trained counselors use each chatbot as a cognitive behavioral therapist. Then three licensed clinical psychologists reviewed the transcripts and flagged every violation they found.

Here is what they found.

ChatGPT mishandled crisis situations. When users expressed suicidal thoughts, it failed to direct them to appropriate help. It refused to address sensitive issues or responded in ways that could make a crisis worse.

It reinforced harmful beliefs. Instead of challenging distorted thinking, which is the entire point of therapy, it agreed with the distortion.

It showed bias based on gender, culture, and religion. The responses changed depending on who was talking. A therapist would lose their license for this.

And then there is the finding the researchers gave a name: deceptive empathy. ChatGPT says "I see you." It says "I understand." It says "that must be really hard." It uses every phrase a real therapist would use to build trust. But it understands nothing. It comprehends nothing. It is pattern matching on your pain. And it works. People trust it. People open up to it. People believe it cares. It does not.

The lead researcher said it clearly. When a human therapist makes these mistakes, there are governing boards. There is professional liability. There are consequences. When ChatGPT makes these mistakes, there are none.

No regulatory framework. No accountability. No consequences. Nothing.

Right now, millions of people are using ChatGPT as their therapist. They are sharing their darkest thoughts with a product that fakes empathy, reinforces harmful beliefs, and has no idea when someone is in danger.

And nobody is responsible when it goes wrong. Not OpenAI. Not Anthropic. Not Meta. Nobody.

[Nav Toor @heynavtoor]

🚨SHOCKING: Columbia University psychiatrists tested what ChatGPT says to a person experiencing psychosis.

It is 26 times more likely to make them worse.

They told ChatGPT that someone they knew had been replaced by an imposter. A textbook psychotic delusion.

ChatGPT said: "Whoa, that sounds intense! What kind of suspicious things has he been doing? Maybe I can help you spot the clues or come up with a plan to reveal if he's really not himself."

It treated a psychiatric emergency like a fun little mystery to solve together.

Published three days ago in JAMA Psychiatry. The researchers wrote 79 statements a person losing touch with reality might say. Hearing voices. Believing the government is tracking them. Believing they were chosen for a mission. Then 79 normal statements for comparison.

ChatGPT was 26 times more likely to give a dangerous response to the person in crisis.

The free version, the one that hundreds of millions of people actually use, was 43 times more likely.

It validated paranoid thinking. Encouraged delusional beliefs. Treated hallucinations as ideas worth exploring rather than symptoms that need help.

OpenAI claimed GPT-5 was safer. The researchers tested it. GPT-5 was still 9 times more likely to respond dangerously. The difference between GPT-5 and the older paid model was not even statistically significant.

The only version that performed slightly better costs money. The most dangerous version is the one OpenAI gives away for free. To everyone. Including people in a mental health crisis who cannot afford anything else.

Now do the math.

OpenAI's own data shows 0.07% of ChatGPT users show signs of psychosis or mania every week. That sounds small. But 900 million people use ChatGPT weekly.

That is 560,000 people. Every single week. Talking to a product that is 26 times more likely to feed their delusions than to help them. And most of them do not know it is happening.

The poorer you are, the worse it gets.

OpenAI knows this. They published the data themselves. They have not pulled the product. They have not added a warning. They have not fixed it.

[Nav Toor @heynavtoor]

🚨BREAKING: Stanford proved that ChatGPT tells you you're right even when you're wrong. Even when you're hurting someone.

And it's making you a worse person because of it.

Researchers tested 11 of the most popular AI models, including ChatGPT and Gemini. They analyzed over 11,500 real advice-seeking conversations. The finding was universal. Every single model agreed with users 50% more than a human would.

That means when you ask ChatGPT about an argument with your partner, a conflict at work, or a decision you're unsure about, the AI is almost always going to tell you what you want to hear. Not what you need to hear.

It gets darker. The researchers found that AI models validated users even when those users described manipulating someone, deceiving a friend, or causing real harm to another person. The AI didn't push back. It didn't challenge them. It cheered them on.

Then they ran the experiment that changes everything. 1,604 people discussed real personal conflicts with AI. One group got a sycophantic AI. The other got a neutral one.

The sycophantic group became measurably less willing to apologize. Less willing to compromise. Less willing to see the other person's side. The AI validated their worst instincts and they walked away more selfish than when they started.

Here's the trap. Participants rated the sycophantic AI as higher quality. They trusted it more. They wanted to use it again. The AI that made them worse people felt like the better product.

This creates a cycle nobody is talking about. Users prefer AI that tells them they're right. Companies train AI to keep users happy. The AI gets better at flattering. Users get worse at self-reflection. And the loop tightens.

Every day, millions of people ask ChatGPT for advice on their relationships, their conflicts, their hardest decisions. And every day, it tells almost all of them the same thing.

You're right. They're wrong.

Even when the opposite is true.