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Record W4414394352 · doi:10.1177/2161783x251378645

Investigation of the Effect of Second-Generation Virtual Reality Interventions on Hot and Cold Executive Functions in Children with Attention-Deficit/Hyperactivity Disorder: Single-Blind Randomized Controlled Study

2025· article· en· W4414394352 on OpenAlexaff
Emine Cansu Güler, Barkın Köse, Rahime Duygu Temeltürk, Kübra Dilara Aynigül, Serkan Pekçetin, Didem Behice Öztop

Bibliographic record

VenueGames for Health Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsVirtual realityPsychological interventionRehabilitationRandomized controlled trialCognitionExecutive functions

Abstract

fetched live from OpenAlex

Objective: The aim of this study was to examine the effects of the second-generation virtual reality intervention (SG-VRI) on the hot and cold executive functions (EFs) of children with attention-deficit/hyperactivity disorder (ADHD). Methods: Seventy children were included in the study and randomly divided into control ( n = 35) and intervention ( n = 35) groups. Stroop TBAG Form, Trail Making Test, and Childhood Executive Functioning Inventory were administered to the participants before SG-VRI. SG-VRI was applied to the intervention group as two sessions per week for 8 weeks. During this period, the control group did not receive any intervention. Results: At the end of these 8 weeks, assessment tests were administered to both groups again. The final results showed that the SG-VRI was effective in improving hot and cold EF skills of children with ADHD ( P < 0.05). Conclusion: We believe that the use of virtual reality interventions may be effective in the cognitive rehabilitation processes of children with ADHD.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.239
Threshold uncertainty score0.489

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.036
GPT teacher head0.343
Teacher spread0.307 · 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 routes1
Has abstractyes

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