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Record W4381953431 · doi:10.34263/jsotad.2023.17.1.39

Dual-task Training Applying Cognitive Tasks Based on Virtual Reality: A Systematic Review of a Randomized Controlled Trials on the Older Adults

2023· review· en· W4381953431 on OpenAlexaboutno aff
Yunjeong Eom, Yoo Gyeong Jeong, Junsu Choi, Min‐Ye Jung

Bibliographic record

VenueSociety of Occupational Therapy for the Aged and Dementia · 2023
Typereview
Languageen
FieldMedicine
TopicDiverse Approaches in Healthcare and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCognitionTask (project management)Cognitive trainingRandomized controlled trialPsychological interventionMontreal Cognitive AssessmentIntervention (counseling)Virtual realityMEDLINEPhysical medicine and rehabilitationMedicinePsychologyVirtual Reality Exposure TherapyCognitive impairmentCognitive psychologyComputer scienceHuman–computer interactionPsychiatry

Abstract

fetched live from OpenAlex

목적 : 노인을 대상으로 인지과제를 적용한 가상현실 기반의 이중과제 훈련을 시행한 무작위 대조군 실험 연구들을 체계적으로 정리하여 정보를 전달하고, 임상에서의 기초자료를 마련하고자 한다. 연구방법 : 본 연구는 2013년 1월부터 2022년 12월까지 PUBMED, MEDLINE, EBSCO, RISS 데이터베이스의 문헌들 중 선정기준에 따라 5편의 논문을 최종적으로 선정하여 분석하였다. 연구결과 : 분석된 연구들의 연구대상은 주로 경도인지장애와 인지적 허약을 가진 노인이었다. 연구들에서의 중재는 모두 게임 형식의 과제로 제공되었으며, 대부분 운동과제와 인지과제가 함께 적용되었다. 평가를 위해 가장 많이 사용된 평가도구에는 TMT, MoCA, SCWT가 있었다. 모든 연구에서 중재에 따라 운동 또는 인지기능의 유의한 향상이 나타났다. 결론 : 본 연구를 통해 가상현실을 기반으로 인지과제를 적용한 이중과제 훈련에 대한 중재 제공 방법 및 평가, 그에 따른 효과를 파악할 수 있었다. 최근 활발하게 이루어지고 있는 중재에 대한 근거를 제공하여 연구 및 임상에서의 기초자료가 되고자 한다.

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)0.023
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.062
Threshold uncertainty score0.896

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0230.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0080.004
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 head0.372
GPT teacher head0.468
Teacher spread0.097 · 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 designSystematic review
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
Published2023
Admission routes1
Has abstractyes

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