1. Research Objective

1. Identifying Shared Structures in Near-Death ExperiencesThe central aim of this research is to identify recurring structural patterns in near-death experiences (NDEs). Although each experience is deeply personal, people around the world report strikingly similar motifs—such as an indescribable sense of love, a feeling of complete acceptance, or the impression of “coming home.”These recurring descriptions raise a fundamental question:Are these similarities coincidental—or do they reflect systematic patterns in human boundary experiences?To address this question, more than a thousand reports are analyzed using linguistic analysis, statistical methods, contextual evaluation, and narrative modeling.

2. Scope of AnalysisThe analysis combines qualitative insights from interviews with data-driven methods. The focus lies on the following aspects:Frequencies & Linguistic Patterns
• Which terms and motifs occur with statistically significant frequency in NDE narratives?
• At which positions within the narrative do they appear - beginning, transition, or climax?Emotional Trajectories• How do typical emotional arcs unfold—for example: fear → light → peace?
• Which emotions accompany different phases of the near-death experience?Positive vs. Negative Experiences• How do linguistic patterns of “positive” experiences (love, light, safety) differ from those characterized by darkness, isolation, or fear?

3. Patterns & Emerging HypothesesThe identification of patterns enables, for the first time, deeply grounded hypotheses about the nature of NDEs.Example: Some individuals report that during their experience they were able to perceive the emotions or even the pain of other people—often those to whom they themselves had caused suffering in the past.Such descriptions suggest that near-death experiences may not be purely individual events, but rather relational experiences connected to other people.It is conceivable that a form of collective emotional or consciousness-based reference system exists—an idea described across many spiritual traditions, such as• Buddhism (interconnected consciousness),
• Hinduism (Atman–Brahman),
• Christian mystical traditions (unity consciousness), or
• shamanic worldviews (shared experiential realms).Through systematic data-driven analysis, concepts that have long been discussed philosophically or spiritually become empirically accessible for the first time.

4. Why This MattersThe combination of:• statistical pattern recognition
• qualitative content analysis
• contextual evaluation
• and narrative modelingmakes it possible to uncover structures that remain hidden when examining individual reports in isolation.This research bridges objective data analysis with human narratives, opening a new perspective on one of the most profound topics of human existence:
consciousness, identity, and potential shared dimensions of experience.

How Does This Project Differ from Classical NDE Research?Classical studies—such as those by Greyson, van Lommel, or Long - primarily examine whether specific features of near-death experiences occur at all:
light, tunnel perception, out-of-body experiences, life review, and similar elements.
These are typically assessed using questionnaires and clinical data.This project takes a different approach.Instead of focusing solely on predefined features, it analyzes hundreds of richly narrated NDE accounts from YouTube interviews, examining how people describe their experiences—the sequence in which events unfold, the language used, and the emotional turning points within their narratives.By applying modern textual and data-driven methods, this approach reveals patterns, narrative arcs, and linguistic imagery that remain invisible in traditional scales and checklists.
The intention is not to challenge existing research, but to complement it with a narrative and linguistic perspective.

2. Research Framework

Structure of the StudyThe investigation follows a clearly structured research process—from data collection to advanced statistical and semantic analysis.1. Data Collection
More than 1,250 interviews from German- and English-speaking YouTube channels were collected and transcribed.2. Preprocessing
All texts were cleaned, standardized, and segmented according to linguistic criteria (sentences, lemmatization, positional markers).3. Descriptive Analysis
Basic patterns such as word distributions, thematic frequencies, and positional profiles were examined.4. Semantic and Narrative Models
Context analyses, emotional trajectories, clustering techniques, and hypothesis testing reveal deeper narrative structures within the reports.5. Advanced Research (ongoing)
Factor analysis, narrative sequences, semantic pathways, and a custom language model are currently under development.

1. Most Frequent Words & Thematic FieldsThe first analyses reveal clear thematic focal points.
Terms such as light, love, fear, time, tunnel, consciousness, and darkness occur with particularly high frequency and form the basis for subsequent semantic clustering.These distributions make visible:• which concepts appear across a large number of reports• how strongly certain motifs are emotionally charged• which themes recur consistently throughout the experiencesThe Top 20 words provide an initial, clear insight into the linguistic landscape of the reports.Terms such as “life,” “body,” “light,” “love,” “time,” and “God” dominate - reflecting a convergence of physical, spiritual, and emotional dimensions that frequently co-occur in near-death experiences.→ The Top 100 words are sufficient to reveal central patterns and emotional focal points.→ The most frequent terms show highly similar distributions across channels—indicating shared thematic core elements.→ The term “life” in particular occupies a central position and raises further questions regarding its narrative context (e.g., hopeful, affirmative, or contrasted with “death”).

The complete dataset currently comprises more than 4 million words.
The ten most frequent terms alone — “life,” “body,” “human,” “experience,” “good,” “time,” “feeling,” “light,” “love,” and “God” — account for 75,008 occurrences.This concentration already highlights a strong thematic core shared across a wide range of individual near-death experience (NDE) reports.

3. Spearman Rank Correlations: Germany vs. United StatesInitial comparisons reveal notable differences in linguistic structure between German and U.S.-based reports:• certain themes occur significantly more frequently in specific regions• word lengths, sentence positions, and emotional evaluations vary• culturally shaped modes of expression can be statistically identifiedChannels within the same language group show strong internal similarity,
yet German and U.S. reports still share a substantial number of common terms.→ A universal language of near-death experience becomes apparent.→ At the same time, cultural differences are clearly reflected in word choice and emphasis.

4. Context Analysis – What Is ExaminedContext analysis examines which words typically occur before or after a key term.
This allows for the precise identification of:• recurring linguistic patterns• emotional structures• spiritual and bodily motifs• cultural interpretations• narrative transitionsIn contrast to POS analysis, context analysis does not focus on grammatical categories, but on semantic surroundings:What tends to precede a word like “light” or “love”?
What follows it?
Which patterns recur across many narratives?

4. Advanced Analyses
(Ongoing Work)

1. Factor Analysis (in progress)Factor analysis is used to identify latent thematic structures within the reports.
Large volumes of textual data are statistically reduced in order to reveal higher-order experience categories, emotional patterns, and recurring narrative building blocks.A central component of this process is a custom-developed research questionnaire consisting of over 40 questions.
Each question represents a typical NDE motif or narrative element, such as:• out-of-body experiences• tunnel or transition passages• encounters with light• spiritual presence• emotional transformations (e.g., fear → peace)• the moment of returnThe question framework was developed through a hybrid qualitative–quantitative approach:• Direct exchanges with cooperating YouTube channels
provided valuable insights into recurring motifs and observational patterns reported by experiencers.• Systematic qualitative content analysis
including the manual review of hundreds of interviews, enabled the identification of recurring experiential elements across narratives.• Statistical validation of qualitative findings
ensured that each motif included in the catalog is empirically anchored in the data and not based on anecdotal impressions alone.The result is a hybrid, data-driven research instrument that integrates experiential knowledge from the community with robust statistical evidence.

2. Narrative Path ModelsIn addition to statistical analyses, dedicated Narrative Path Models are being developed—algorithms that reconstruct typical story chains within near-death experience narratives.
These models do not focus on isolated words alone, but on the sequence in which experiences are described, revealing deeper structural patterns across reports.What the models reveal• which key terms tend to occur in succession• how emotional turning points unfold• which sequences repeatedly appear (e.g., fear → light → peace → return)• and which variants are rarer but potentially meaningfulThese models will later serve as a foundation for storyline prediction:
how narratives typically develop—and where they diverge.To illustrate the complexity of a full Narrative Path Model, here is an exemplary (complex) example showing only the initial layer Human → Experience:• Exemplary Narrative Model.pdfThe figure represents a highly simplified visual layer of the underlying model and is included solely to improve readability.

3. Custom Language Model (LLM)A custom language model is currently being developed, trained on more than 1,250 NDE transcripts.
The goal is a domain-specific LLM capable of:• detecting typical NDE motifs• understanding narrative transitions• automatically mapping semantic clusters• and later identifying patterns in new reports with minimal manual effortThis model is trained iteratively and is intended to become a core component of the project in the long term—especially as new datasets and narrative path structures are added.

4. Research Database (in development)To organize the continuously growing volume of transcripts, analyses, and statistical outputs, a central research database is currently being built.
It forms the backbone of the project and enables a systematic, reproducible, and scientifically traceable evaluation of hundreds of near-death experience reports.• The database aims to consolidate all components in one structured environment, including:• full transcripts of all NDE reports• metadata (e.g., source, year, language, interview length)• quantitative analysis outputs (POS, frequencies, n-grams, etc.)• narrative and emotional patterns• results from semantic models• context and cluster structures• path sequences derived from Narrative Path ModelsStep by step, this creates a scientific foundation that supports both internal research workflows and future collaboration with external partners.

5. Downloads

Key Results, Methods, and Analyses — Compact OverviewThe brochure summarizes all project steps completed so far:
from data collection and statistical analyses to semantic evaluations and the first identified narrative patterns.It provides a clear and accessible overview of the research design and presents key diagrams, findings, and exemplary excerpts from more than 1,250 near-death experience reports.The brochure is continuously updated as soon as new models, clusters, or hypothesis tests are completed.

Click the download button below to access the brochure.Downloads:Brochure DE: December 2025Brochure EN: December 2025

6. Cooperation / Partnerships

NDE Research is an independent project that is open to collaboration—both with individuals and institutions.Whether through scientific analysis, data exchange, interviews, media contributions, or joint research initiatives:
any form of cooperation can contribute to a deeper and more comprehensive understanding of near-death experiences.Current collaborations (selection):YouTube channels (ongoing data collection & exchange):
• Einblicke ins Jenseits• Empirische JenseitsforschungIf you are interested in joint projects or would like to contribute ideas, I would be pleased to hear from you.

• Email

7. Donations / Support

This project analyzes more than 1,250 near-death experience reports using methods from statistics, semantic analysis, and narrative research.
All results are shared openly — without paywalls or commercial intent.However, the creation of transcripts, data pipelines, diagrams, visualizations, and ongoing analyses
(such as factor models, language-based models, and semantic clustering) requires significant time and computational resources.If you would like to support this independent research project, your contribution helps ensure its continued development and openness.

Contact / Imprint

📨 Contact
If you have questions, ideas, or are interested in collaboration, I would be pleased to hear from you.E-Mail: [email protected]LinkedIn: Tobias OmlandI usually respond within a few days.

🧾 Imprint
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