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Data_Sheet_2_The VITAAL Stepping Exergame Prototype for Older Adults With Major Neurocognitive Disorder: A Usability Study.docx

2021· dataset· en· W6927527214 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2021
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicBotanical Research and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsUsabilityThink aloud protocolThematic analysisNeurocognitiveSystem usability scaleCognition

Abstract

fetched live from OpenAlex

<p>Purpose: This study investigates the usability of a stepping exergame in older adults with major neurocognitive disorder (MNCD) residing in a long-term care facility.</p><p>Materials and Methods: A mixed methods study was conducted. Participants played exergames for 30 min on one try-out session. During the exergames, the think aloud method was used, and field notes were taken by the facilitator. Following the exergames, participants completed the System Usability Scale (SUS) and a semi-structured in-depth interview about usability including their personal experiences. Audio files were transcribed and a thematic content analysis of the think aloud data, field notes and interviews were performed using NVivo 12.</p><p>Results: Twenty-two participants with MNCD were included [mean age = 84.3 ± 5.5 (70–95) years; 81.8% women; Short Physical Performance Battery score = 7.5 ± 3.2 (1–12), Montreal Cognitive Assessment score = 11.9 ± 4.4 (2–19)]. System usability was rated “ok to good” with a mean SUS score of 57.8 (SD = 12.3) with scores ranging from 37.5 to 90.0. Five main themes emerged from the thematic content analysis: (1) perceived user friendliness and acceptability of the exergames; (2) interactional experience; (3) motivational factors; (4) training modalities; and (5) risks. There were no adverse events nor dropouts.</p><p>Conclusion: Participants evaluated the usability of the exergames positively. The results indicate that the stepping exergame is usable in older adults with MNCD.</p>

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.103
Threshold uncertainty score0.897

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.1030.001

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 head0.039
GPT teacher head0.295
Teacher spread0.256 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2021
Admission routes1
Has abstractyes

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