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Record W3118327096 · doi:10.1016/j.arrct.2021.100102

How Well Does the Brief Interview for Mental Status Identify Risk for Cognition Mediated Functional Impairment in a Community Sample?

2021· article· en· W3118327096 on OpenAlexaboutno aff
Timothy S. Marks, Gordon Muir Giles, Muhammad O. Al‐Heizan, Dorothy Farrar Edwards

Bibliographic record

VenueArchives of Rehabilitation Research and Clinical Translation · 2021
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsnot available
FundersNational Institute on AgingNational Institutes of Health
KeywordsMontreal Cognitive AssessmentActivities of daily livingObservational studyCognitionPsychologyLogistic regressionGerontologyCognitive impairmentClinical psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the adequacy of the Brief Interview for Mental Status (BIMS) compared with other screening tools in identifying individuals with limitations in functional cognition and instrumental activities of daily living (IADL). DESIGN: Cross-sectional observational study. SETTING: Midsized midwestern city. PARTICIPANTS: We assessed a convenience sample of community dwelling individuals (N=197) aged 55 years and older who were living independently. MAIN OUTCOME MEASURES: Participant scores on the BIMS, Mini-Cog, Menu Task, and Montreal Cognitive Assessment (MoCA) were compared with the Performance Assessment of Self-Care Skills Checkbook Balancing and Shopping tasks (PCST), which are known to predict impairment in complex IADLs associated with a diagnosis of mild cognitive impairment. Multiple logistic regression analyses controlling for participant demographics, as well as sensitivity and specificity, were computed for each screening measure using the PCST as the criterion measure. RESULTS: The Mini-Cog, Menu Task, and MoCA identified 25.89%, 32.49%, and 47.21% more individuals, respectively, as impaired than the BIMS. In multiple logistical regression analyses, the BIMS correctly identified 58% of those impaired on the PCST. However, each of the alternate screening measures correctly identified at least 70% of individuals as impaired on the PCST. CONCLUSIONS: In this community sample, the BIMS was insensitive to subtle impairments with the potential to compromise community living, suggesting that the BIMS may be inappropriate for use outside nursing home settings.

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)0.006
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.510
Threshold uncertainty score0.880

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.198
GPT teacher head0.514
Teacher spread0.316 · 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

Citations10
Published2021
Admission routes1
Has abstractyes

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