There are five main distortions in NLP seen in the Meta model.

They are:

Mind reading
Cause-and-effect
Lost performative
Complex equivalence
Presuppositions

Mind Reading

We are all guilty of mind reading I know you are! A mind read is categorised by knowing what someone else is thinking or feeling but without any information to support that thought. Mind reading can come in lots of different forms. One of them which is very common is knowing what a person is thinking or feeling. Another is how others should know how we think and feel. And lastly predicting the future or proper sizing what is going to happen.

Whenever you hear mind reading type statements you can begin to ask questions using 'how' and 'what.'

Examples:

"He wants to ask me out"
"You don't give me what I want"
"I just know Christmas will be a disaster"
"I know that you will want to live in the Cotswolds when you see my house"
"You have no idea what is going to happen"

Meta model challenges to those statements

"How do you know he wants to ask you out?"
"What do you want specifically?"
"Really? How specifically do you know that?"
"How do you know that when I see your house in the Cotswolds I want to live there?"
"How do you know that I have no idea what is going to happen?"

Possible Reply

"Well, he's always nervous when he's around me"
"I want to feel like wearing this together"
"It's just that December has been a nightmare so far so it will probably continue"
"Because I did when I visited a friend here"
"Because I think it's going to be worse than you given credit for"

Cause and Effect

Recognising a cause-and-effect Meta model violation is when you spot and X causes why configurations in the language. so much of our life is in a cause-and-effect format that has a tendency to make connections where there is none. "If you do your homework, then you can stay up late on Friday." "If you pass all of your grades at school, you will get a good job."

So in the Meta model for cause and effect, we are looking for violations where someone associates X causes Y.

Whenever you spot this cause-and-effect violation it's time to begin asking more questions to find out how specifically do they know that X causes Y?

Examples:

"My boss makes me angry when he doesn't come in early on Monday"
"If my daughter fails her dance exam I will be disappointed"
"Going to the gym will wear a body out"
"If you drink alcohol you will get dementia"
"Getting married made my brother the depressive he is today"

Meta Model Challenges

"How specifically that his lateness make you angry? What about if he's late on Tuesday?"
"How will you disappoint yourself?"
"How do you know that to be true? do you know of any gym goers who haven't worn at their body? Just how much Gym does it take to wear out your body?"
"How much alcohol specifically? Do you know of anyone who does drink alcohol who hasn't got dementia? I drink some alcohol are you sure I will get dementia?"
"What was it about marrying that made your brother begin to depress himself?"

Lost Performative

Recognising a lost performative is when you hear a person say something like, "We will end up living on Mars by 2050" or "Only weak people stay in relationships."

The structure of a lost performative is an opinion stated as a fact and a value judgement that does not say who had that value.

You can begin to challenge lost performative type statements by asking "who says, according to whom and how do you know that?" type of questions.

Examples:

"It's good to go to the Gym three times per week"
"You need to go on as many training courses as you can"
"Reading is relaxing"

Meta model Challenges to those statements

"Who says it's good to go to the gym three times a week?"
"Who says you need to go in as many training courses you can, and how do you know that to be true?"
"According to whom?"

Possible replies to the challenges

"I heard it on a podcast about health"
"The person who was teaching me NLP!"
"Well, I find reading relaxing!"

Complex Equivalence

A complex equivalence is very similar to cause-and-effect. Just as we, cause-and-effect is when X causes Y. And complex equivalence can be recognised by hearing a statement that says X means Y.

"The fact that you're reading watching or listening to this means that you'll find something new!"

it's amazing how often you will hear people attach meaning to something very different.

"The fact that you're changing your job means that you are outgrowing your family"

Whenever you hear convex equivalent type statements you can challenge them by asking. "So does X have to always equal Y? Could it mean anything else? Does it always have to mean that?"

Examples:

"You're not coming to bed the same time as me, you don't love me as much anymore"
"Bitcoin value is rising our government isn't going to last"
"Samsung are late releasing the new phone, so there's tension growing between North and South Korea."

Meta model challenges

"How does me staying up to finish watching this documentary mean I don't love you as much?"
"How does Bitcoin rising mean our government isn't going to last?"
"How does Samsung being late to release their new phone mean there's growing tension between North and South Korea?"

Possible replies

"I think married couples should always go to bed together to show there is a bond."
"Well, Bitcoin is anti-establishment so I think a rise in its value means a fall in the governments holds."
"They've never been late to release a new phone so It's obviously a big political reason."

Presuppositions

If you've been looking into NLP you have heard the word presupposition quite frequently. A presupposition is simply a part of the statement has to be presupposed to be true in order for that sentence to make sense.

We challenge presuppositions to allow us to gain more specific detail and get closer to the truth. Let's look at some working examples of presuppositions in NLP.

Examples

In court, a judge might say "have you stopped beating your wife?" This statement presupposes that the husband was, in fact, beating his wife.
"What's your problem?" This presupposes that a person does have a problem.
"Are you not intelligent enough to work this out?" This statement presupposes that there is something to work out, intelligence is required to work it out.
"Enjoy your next burger even more" Presupposes that someone has had a burger and they will have another at some point.

Meta model challenges

You can use any suitable meta model question to dive more deeply into the intention behind any presupposition.

"Your honour, are you suggesting I did want to beat my wife? could there be any other explanation to her bruised arm?"
You could answer this provocatively. "Well, what's my problem? Depends on how long you've got!"
"My next burger? how do you know of had one in the first place?"

with everything, practice makes permanent. To save this and come back to this article many times and really begin to notice these distortions in NLP in other people's language and even yours.

Have a play around with some of the Meta model challenges and begin to notice how you're able to really open up a person's map to allow you to understand more richly and more deeply.

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