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Record W3092262466 · doi:10.2196/18127

Cognitive Training Using Fully Immersive, Enriched Environment Virtual Reality for Patients With Mild Cognitive Impairment and Mild Dementia: Feasibility and Usability Study

2020· article· en· W3092262466 on OpenAlexvenueno aff
Seo Jung Yun, Min‐Gu Kang, Dongseok Yang, Younggeun Choi, Heejae Kim, Byung‐Mo Oh, Han Gil Seo

Bibliographic record

VenueJMIR Serious Games · 2020
Typearticle
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsUsabilityDementiaCognitionVirtual realityMoodCognitive trainingCognitive evaluation theoryCognitive rehabilitation therapyTest (biology)Likert scalePsychologyRehabilitationPhysical medicine and rehabilitationPhysical therapyMedicineClinical psychologyHuman–computer interactionComputer sciencePsychiatryDevelopmental psychologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Cognitive training using virtual reality (VR) may result in motivational and playful training for patients with mild cognitive impairment and mild dementia. Fully immersive VR sets patients free from external interference and thus encourages patients with cognitive impairment to maintain selective attention. The enriched environment, which refers to a rich and stimulating environment, has a positive effect on cognitive function and mood. OBJECTIVE: The aim of this study was to investigate the feasibility and usability of cognitive training using fully immersive VR programs in enriched environments with physiatrists, occupational therapists (OTs), and patients with mild cognitive impairment and mild dementia. METHODS: The VR interface system consisted of a commercialized head-mounted display and a custom-made hand motion tracking module. We developed the virtual harvest and cook programs in enriched environments representing rural scenery. Physiatrists, OTs, and patients with mild cognitive impairment and mild dementia received 30 minutes of VR training to evaluate the feasibility and usability of the test for cognitive training. At the end of the test, the usability and feasibility were assessed by a self-report questionnaire based on a 7-point Likert-type scale. Response time and finger tapping were measured in patients before and after the test. RESULTS: Participants included 10 physiatrists, 6 OTs, and 11 patients with mild cognitive impairment and mild dementia. The mean scores for overall satisfaction with the program were 5.75 (SD 1.00) for rehabilitation specialists and 5.64 (SD 1.43) for patients. The response time of the dominant hand in patients decreased after the single session of cognitive training using VR, but this was not statistically significant (P=.25). There was no significant change in finger tapping in either the right or left hand (P=.48 and P=.42, respectively). None of the participants reported headaches, dizziness, or any other motion sickness after the test. CONCLUSIONS: A fully immersive VR cognitive training program may be feasible and usable in patients with mild cognitive impairment and mild dementia based on the positive satisfaction and willingness to use the program reported by physiatrists, OTs, and patients. Although not statistically significant, decreased response time without a change in finger tapping rate may reflect a temporary increase in attention after the test. Additional clinical trials are needed to investigate the effect on cognitive function, mood, and physical outcomes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.057
GPT teacher head0.307
Teacher spread0.250 · 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 source (direct Gemma or distilled Codex), 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

Citations69
Published2020
Admission routes1
Has abstractyes

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