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Record W7065121594

A DIGITAL APPLICATION FOR ASSESSMENT OF NEUROCOGNITIVE DISABILITIES

2022· dissertation· en· W7065121594 on OpenAlexaboutno aff

Bibliographic record

VenueRowan Digitals Works (Rowan University) · 2022
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsNeurocognitiveDementiaTask (project management)Context (archaeology)Test (biology)Neuropsychological assessmentNeuropsychology
DOInot available

Abstract

fetched live from OpenAlex

Background: Neuropsychological assessment is designed to identify neurocognitive impairment and has traditionally relied on pen-and-paper tests. The behavior collected from these tests is usually expressed as a total summary score or a score that reflects a restricted number of features that assess errors. There is now interest in coupling traditional paper and pencil tests with digital assessment technology. In this context traditional metrics such as summary scores are still available. However, using digital technology, a host of time-based parameters can now be obtained. These time-based parameters include the total time to complete the task or total time to completion, as well the time necessary to generate all responses within a task or test trial. In addition to a wealth of highly nuance data, audio and video files of patients' behavior can be created. This permits subsequent, downstream data mining to uncover and discover new features and variables of interest. Digital assessment platforms are reliable and inexpensive and can be deployed in virtually any clinical situation such as a comprehensive, outpatient dementia evaluation where detailed assessment is conducted, as well as in a primary medical care setting to screen for neurocognitive difficulty associated with chronic or acute medical illness. Cardiovascular risks such as hypertension, elevated cholesterol, and diabetes are common if not endemic. In addition to increasing the risk for heart attack and stroke, it is now commonly understood that cardiovascular risks also convey risk for dementia such as Alzheimer's disease. Indeed, most insidious onset dementia illness presents with some degree of vascular alteration in the brain. Moreover, chronic cardiovascular is now well known to associate with a variety of neuropsychological disabilities such as executive control. Objectives: The current research presents data on the Philadelphia Pointing Span Test (PPST), a digital test designed to measure executive abilities. The current research tested two predictions. The first prediction is that indices from the PPST measuring auditory span and mental manipulation will be related to other indices that assess executive abilities, providing some evidence for criterion validity of the PPST as an executive measure. The second prediction is to assess the degree digitally administered and scored PPST indices are related to cardiovascular risks. Methods: Fifty-one patients from an outpatient ambulatory medical practice were recruited. All participants were assessed with the PPST and the Montreal Cognitive Assessment (MoCA). Statistical analyses of MoCA test performance resulted in neuropsychological indices measuring executive, language, and memory abilities. The PPST was implemented onto an iPad application capable of tracking accuracy and latency between responses. PPST outcome variables of interest included ANY ORDER and SERIAL Order recall, measures of executive abilities related to auditory span and mental manipulation, respectively; and the latency to generate all responses. Results: Consistent with our first prediction, PPST SERIAL ORDER recall was correlated to the MoCA executive index where reduced MoCA executive performance was seen along with reduced PPST SERIAL ORDER recall. Consistent with our second prediction slower or longer latencies from selected PPST tests items were associated with greater cardiovascular risk. Conclusions: The PPST, a digitally administered and scored test, appears to provide an efficient assessment of executive abilities. The relationship between PPST performance and cardiovascular risk suggests that the PPST may be means to screen for neuropsychological difficulty as related to medical illness in a primary care setting.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.090
Threshold uncertainty score0.300

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0900.038

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 head0.010
GPT teacher head0.258
Teacher spread0.248 · 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 designBench or experimental
Domainnot available
GenreMethods

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
Published2022
Admission routes1
Has abstractyes

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