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Record W4414615667 · doi:10.3390/bs15101333

A Dynamic Approach to Compulsive Fantasy: Constraints and Creativity in “Maladaptive Daydreaming”

2025· review· en· W4414615667 on OpenAlexafffund
Jennifer I. Burrell, E. O. Lawson, Kalina Christoff

Bibliographic record

VenueBehavioral Sciences · 2025
Typereview
Languageen
FieldNeuroscience
TopicMind wandering and attention
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsFantasySalience (neuroscience)CreativityEveryday lifeDynamics (music)The ImaginaryMental model

Abstract

fetched live from OpenAlex

Compulsive fantasy, often called "maladaptive daydreaming," involves frequent engagement with immersive fantasies that can sometimes interfere with everyday life and cause distress. This paper expands on Christoff and colleagues' Dynamic Framework of Thought (DFT) to offer a process-based analysis of compulsive fantasy as it relates to other mental phenomena such as daydreaming and creative thought. Drawing on the existing literature and posts on online forums by self-identified maladaptive daydreamers, we also propose an account of how compulsive fantasy episodes may unfold in terms of the oscillating dynamics of various constraints on thought, and how these dynamics may be related to a perceived struggle with agency. Automatic constraints, including affective salience and mental habits, may bring about a fantasy episode. During a fantasy episode, automatic constraints may be relatively high throughout, whereas deliberate constraints may be intermittently engaged to influence the fantasy. Our analysis supports the use of "compulsive fantasy" as a more accurate designation than "maladaptive daydreaming" for this phenomenon: compulsive fantasies are not daydreams, because they are more constrained in their mental dynamics. We show that fantasy and daydreaming are not inherently harmful but can become so when they are accompanied by relatively strong and sustained automatic constraints on thought.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.974
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.154
GPT teacher head0.418
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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