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Record W1969423354 · doi:10.1258/135763304323070751

Feasibility of neuropsychological testing of older adults via videoconference: implications for assessing the capacity for independent living

2004· article· en· W1969423354 on OpenAlexaffabout
Roger Hildebrand, Hau Chow, Catherine Williams, Monty Nelson, Peter Wass

Bibliographic record

VenueJournal of Telemedicine and Telecare · 2004
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsBurman UniversityAlberta Hospital Edmonton
Fundersnot available
KeywordsNeuropsychologyVideoconferencingFluencyPsychologyVerbal fluency testAudiologyTest (biology)Boston Naming TestNeuropsychological assessmentClinical psychologyMedicineCognitionMultimediaPsychiatryComputer science

Abstract

fetched live from OpenAlex

We examined the feasibility of administering neuropsychological tests via videoconference. Twenty-nine participants from central Alberta volunteered for the study. All were 60 years of age or older and were without neurological or psychiatric disturbance. All the participants were tested under two experimental conditions: face to face and via videoconference (at a bandwidth of 336 or 384 kbit/s). Memory and learning, letter fluency, expressive word knowledge, reasoning, verbal attention and visual-spatial processing were examined. Scores for expressive word knowledge were similar in the two test conditions, although larger differences were found in the visual-spatial processing scores. Following the final testing session, participants were given a questionnaire which explored their reactions to the technology. There was no significant difference in the proportions of participants who expressed a preference for each mode of testing. All participants were comfortable with the technology.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.101
Threshold uncertainty score0.303

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
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 science0.0000.000
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 head0.077
GPT teacher head0.398
Teacher spread0.321 · 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 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

Citations85
Published2004
Admission routes2
Has abstractyes

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