What does the experience of near-death feel like?

Near-death experiences are rare but for those who go through them, occurrences can be emotionally loaded. But what kind of mark is left of these unsettling encounters? A new study says it can now deliver an “unbiased” evaluation of the accounts of near-death experiences by the participants.

The word most often used in near-death experiences accounts is' light' according to a new study.
The word most often used in near-death experiences accounts is’ light’ according to a new study.

Near-death experiences (NDEs) are states of altered consciousness which may occur in the sense of a life-threatening incident, such as a heart attack or near drowning.

While it’s unclear how many people have ever had an NDE around the world, they are a rare occurrence.

The International Association for Near-Death Studies — a non-profit organization based in Durham, NC — quotes an estimated 774 NDEs that occur every day in the US.

Though uncommon, such experiences are undoubtedly very potent, and reports describing NDEs range from serene and positive to frightening and dark, though anecdotal evidence suggests that more common are positive descriptions.

A team of researchers from Western University in Ontario, Canada and the University of Liège in Belgium have recently developed a new approach for analyzing NDE accounts, which it argues to be unbiased.

The new method incorporates artificial intelligence technology and text mining — using automated software for text analysis— to create a more accurate picture of what NDEs are for the people who go through it.

A research paper that describes the new method and presents the results appears now in PLOS One.

NDEs ‘experienced as extremely pleasant’

The researchers demonstrate that researchers looking at NDEs used detailed surveys to find out more about the experiences of people, such as the Greyson scale.

Such surveys might include the question, “Have you had a sense of peace and delight?” Or “Have you felt your body separate?” However, the researchers point out, such questions might affect the memory of the events of the participants.

“There is no bias with text mining which runs counter to behavioral studies such as Greyson scaling when individuals are asked specific questions,” says study co-author Andrea Soddu, who is a Western University associate professor.

“Text mining is totally unbiased. It’s completely automatic, and we, as researchers, make no assumptions,” he says.

The researchers interviewed 158 participants who had gone via NDEs for the current study, asking each one to compose a first person narrative to explain their experiences.

The mean length of those definitions, the authors say, was 140 words per sentence.

Soddu and his colleagues then used text mining and artificial intelligence to extract keywords and create visual “maps” of all these terms, demonstrating positive versus negative NDE distribution and frequency.

The experiment showed that words with positive connotations appeared much more in the narratives of the participants, while words with negative connotations appeared within the accounts much less and farther apart.

The top five words most used in NDE narratives by the participants were “light,” which was in 106 of the texts examined, “ah” (in 103 narratives), “see” (in 96 texts), “bone” (in 93 texts), and “feel” (in 82).

Some of the less-used terms were “black,” featuring in 30 theories, and “dead,” appearing in 29. “Fear” appeared in 38 (24 percent) of the participants ‘ submitted NDE narratives.

The authors conclude, in their research paper:

Despite their circumstances of occurrence, NDEs are generally experienced as extremely pleasant and can induce life changing consequences on the experiencers’ set of values and attitudes towards death.”

The researchers plan to collect more NDE accounts and apply their approach to a larger majority of texts in order to get a more comprehensive picture of how they feel.

“When there will be a huge volume of these text narratives in the future, it will be much easier to handle the details, using text mining as opposed to the questionnaire method,” says co-first author Demetrius Ribeiro De Paula, who is completing his Western University doctoral studies.

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