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Record W4385830577 · doi:10.1089/neur.2023.0009

A Protocol for Remote Cognitive Training Developed for Use in Clinical Populations During the COVID-19 Pandemic

2023· article· en· W4385830577 on OpenAlexafffund
Taylor Snowden, Lisa Ohlhauser, Jamie I. Morrison, Jocelyn Faubert, Jodie R. Gawryluk, Brian R. Christie

Bibliographic record

VenueNeurotrauma Reports · 2023
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of British ColumbiaUniversité de MontréalUniversity of Victoria
FundersCanadian Institutes of Health Research
KeywordsPsychological interventionSession (web analytics)CognitionCoronavirus disease 2019 (COVID-19)MedicineProtocol (science)PandemicPhysical therapyPsychologyNursingPsychiatryComputer science

Abstract

fetched live from OpenAlex

Many traumatic brain injury (TBI) survivors face scheduling and transportation challenges when seeking therapeutic interventions. The COVID-19 pandemic created a shift in the use of at-home spaces for work, play, and research, inspiring the development of online therapeutic options. In the current study, we determined the feasibility of an at-home cognitive training tool (NeuroTrackerX) that uses anaglyph three-dimensional (3D) glasses and three-dimensional multiple object tracking (3D-MOT) software. We recruited 20 adults (10 female; mean age = 68.3 years, standard deviation [SD] = 6.75) as the at-home training group. We assessed cognitive health status for participants using a self-report questionnaire and the Mini-Mental State Examination (MMSE), and all participants were deemed cognitively healthy (MMSE >26). At-home participants loaned the necessary equipment (e.g., 3D glasses, computer equipment) from the research facilities and engaged in 10 training sessions over 5 weeks (two times per week). Participant recruitment, retention, adherence, and experience were used as markers of feasibility. For program validation, 20 participants (10 female; mean age = 63.39 years, SD = 12.22), who had previously completed at least eight sessions of the in-lab 3D-MOT program, were randomly selected as the control group. We assessed individual session scores, overall improvement, and learning rates between groups. Program feasibility is supported by high recruitment and retention, 90% participant adherence, and participants' ease of use of the program. Validation of the program is supported. Groups showed no differences in session scores ( p > 0.05) and percentage improvement ( p > 0.05) despite the differences in screen size and 3D technology. Participants in both groups showed significant improvements in task performance across the training sessions ( p < 0.001). NeuroTrackerX provides a promising at-home option for cognitive training in cognitively healthy adults and may be a promising avenue as an at-home therapeutic for TBI survivors. This abstract was previously published on clinicaltrials.gov and can be found at: https://www.clinicaltrials.gov/ct2/show/NCT05278273

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)0.015
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.078
Threshold uncertainty score0.261

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.015
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.001
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0780.022

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 head0.760
GPT teacher head0.575
Teacher spread0.184 · 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 designNot applicable
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

Citations0
Published2023
Admission routes2
Has abstractyes

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