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Record W4411153064 · doi:10.3390/brainsci15060622

The Rapid Sense of Direction (R-SOD) Scale: A Brief Self-Report Tool to Identify Developmental Topographical Disorientation (DTD)

2025· article· en· W4411153064 on OpenAlexafffund
Tejdeep Jaswal, Ford Burles, Giuseppe Iaria

Bibliographic record

VenueBrain Sciences · 2025
Typearticle
Languageen
FieldEngineering
TopicSpatial Cognition and Navigation
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsScale (ratio)PsychologyCognitive psychologyComputer scienceCartographyGeography

Abstract

fetched live from OpenAlex

Background/Objectives: Developmental Topographical Disorientation (DTD) refers to a condition in which individuals report getting lost in very familiar surroundings, since childhood, with no other cognitive complaints, and no brain injuries or neurological disorders. While the cognitive and neurological mechanisms underlying DTD are being investigated, to date, there is no tool available to the public and health practitioners for identifying this lifelong condition. Methods: Here, we used a decade of data (N = 3794) collected in healthy and DTD individuals to produce a short and reliable measure of self-reported sense of direction that could point to the presence of DTD. Results: We adopted a measure of internal consistency (Cronbach’s alpha) and identified four items of the well-known Santa Barbara Sense of Direction (SBSOD) Scale that retain its original strong internal consistency. These four items remain sensitive to the well-known effects of sex on spatial orientation and, importantly, to the presence of DTD, while maintaining the same pattern of association with a cognitive battery of computerized tasks measuring different spatial abilities. Conclusions: This four-item measure could be of practical use to obtain a rapid assessment of an individual’s self-reported sense of direction and help to identify the presence of DTD in the general population.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.795
Threshold uncertainty score0.233

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.009
GPT teacher head0.289
Teacher spread0.280 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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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