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Record W2580557900 · doi:10.2196/resprot.6570

Effects of Video Game Training on Behavioral and Electrophysiological Measures of Attention and Memory: Protocol for a Randomized Controlled Trial

2017· article· en· W2580557900 on OpenAlexvenueno aff
Soledad Ballesteros, Julia Mayas, Eloísa Ruiz-Marquez, A. Fernandez Prieto, Pilar Toril, Laura Ponce de León Romero, Marı́a L. de Ceballos, José Manuel Reales Avilés

Bibliographic record

VenueJMIR Research Protocols · 2017
Typearticle
Languageen
FieldPsychology
TopicCognitive Abilities and Testing
Canadian institutionsnot available
Fundersnot available
KeywordsCognitive trainingCognitionPsychologyRandomized controlled trialProtocol (science)NeuroplasticityCognitive psychologyMedicinePhysical medicine and rehabilitationNeuroscienceAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Neuroplasticity-based approaches seem to offer promising ways of maintaining cognitive health in older adults and postponing the onset of cognitive decline symptoms. Although previous research suggests that training can produce transfer effects, this study was designed to overcome some limitations of previous studies by incorporating an active control group and the assessment of training expectations. OBJECTIVE: The main objectives of this study are (1) to evaluate the effects of a randomized computer-based intervention consisting of training older adults with nonaction video games on brain and cognitive functions that decline with age, including attention and spatial working memory, using behavioral measures and electrophysiological recordings (event-related potentials [ERPs]) just after training and after a 6-month no-contact period; (2) to explore whether motivation, engagement, or expectations might account for possible training-related improvements; and (3) to examine whether inflammatory mechanisms assessed with noninvasive measurement of C-reactive protein in saliva impair cognitive training-induced effects. A better understanding of these mechanisms could elucidate pathways that could be targeted in the future by either behavioral or neuropsychological interventions. METHODS: A single-blinded randomized controlled trial with an experimental group and an active control group, pretest, posttest, and 6-month follow-up repeated measures design is used in this study. A total of 75 cognitively healthy older adults were randomly distributed into experimental and active control groups. Participants in the experimental group received 16 1-hour training sessions with cognitive nonaction video games selected from Lumosity, a commercial brain training package. The active control group received the same number of training sessions with The Sims and SimCity, a simulation strategy game. RESULTS: We have recruited participants, have conducted the training protocol and pretest assessments, and are currently conducting posttest evaluations. The study will conclude in the first semester of 2017. Data analysis will take place during 2017. The primary outcome is transfer of benefit from training to attention and working memory functions and the neural mechanisms underlying possible cognitive improvements. CONCLUSIONS: We expect that mental stimulation with video games will improve attention and memory both at the behavioral level and in ERP components promoting brain and mental health and extending independence among elderly people by avoiding the negative personal and economic consequences of long-term care. TRIAL REGISTRATION: Clinicaltrials.gov NCT02796508; https://clinicaltrials.gov/ct2/show/NCT02796508 (archived by WebCite at http://www.webcitation.org/6nFeKeFNB).

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)0.027
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.039
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.025
Meta-epidemiology (narrow)0.0070.003
Meta-epidemiology (broad)0.0130.004
Bibliometrics0.0030.003
Science and technology studies0.0030.003
Scholarly communication0.0030.002
Open science0.0030.002
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0390.007

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 head0.368
GPT teacher head0.574
Teacher spread0.206 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations17
Published2017
Admission routes1
Has abstractyes

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