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Record W2889713576 · doi:10.1111/jgs.15521

Cognition and Incarceration: Cognitive Impairment and Its Associated Outcomes in Older Adults in Jail

2018· article· en· W2889713576 on OpenAlexaboutno aff
Cyrus Ahalt, Irena Stijacic‐Cenzer, Bruce L. Miller, Howard J. Rosen, Deborah E. Barnes, Brie Williams

Bibliographic record

VenueJournal of the American Geriatrics Society · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
FundersNational Institute on AgingNational Palliative Care Research Center
KeywordsMedicinePsychosocialMontreal Cognitive AssessmentGerontologyCognitionSocioeconomic statusCognitive impairmentPopulationPsychiatryEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVES: To determine prevalence of, and outcomes associated with, a positive screen for cognitive impairment in older adults in jail. DESIGN: Combined data from cross-sectional (n=185 participants) and longitudinal (n=125 participants) studies. SETTING: Urban county jail. PARTICIPANTS: Individuals in jail aged 55 and older (N = 310; mean age 59, range 55-80). Inclusion of individuals aged 55 and older is justified because the criminal justice system defines "geriatric prisoners" as those aged 55 and older. MEASUREMENTS: Baseline and follow-up assessments of health, psychosocial factors, and cognitive status (using the Montreal Cognitive Assessment (MoCA)); 6-month acute care use and repeat arrest assessed in those followed longitudinally. RESULTS: Participants were of low socioeconomic status (85% annual income < $15,000) and predominantly nonwhite (75%). Many (70%) scored less than 25 on the MoCA; those with a low MoCA score were more likely to be nonwhite (81% vs 62%, p<.001) and report fair or poor health (54% vs 41%, p=.04). Over 6 months, a MoCA score of less than 25 was associated with multiple emergency department visits (32% vs 13%, p=.02), hospitalization (35% vs 16%, p=.03), and repeat arrests (45% vs 21%, p=.01). CONCLUSIONS: Cognitive impairment is prevalent in older adults in jail and is associated with adverse health and criminal justice outcomes. A geriatric approach to jail-based and transitional health care should be developed to assess and address cognitive impairment. Additional research is needed to better assess cognitive impairment and its consequences in this population. J Am Geriatr Soc 66:2065-2071, 2018.

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)0.000
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 score0.052
Threshold uncertainty score0.384

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.011
GPT teacher head0.299
Teacher spread0.288 · 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

Citations63
Published2018
Admission routes1
Has abstractyes

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