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Record W4390084503 · doi:10.1017/s1355617723006811

10 Subtyping Serial Position Score Profiles to Investigate the Nature of Memory Impairment in Homeless and Precariously Housed Persons

2023· article· en· W4390084503 on OpenAlexaffabout
Katie C Benitah, Kristina M. Gicas, Paul Jones, Anna Petersson, Allen E. Thornton, Tari Buchanan, William G. Honer

Bibliographic record

VenueJournal of the International Neuropsychological Society · 2023
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of British ColumbiaSimon Fraser UniversityYork University
Fundersnot available
KeywordsRecallSerial position effectPsychologyVerbal memoryCognitionMemory testWorking memoryFree recallTest (biology)AudiologyDevelopmental psychologyCognitive psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

Objective: Cognitive dysfunction is prominent in homeless and precariously housed persons, and memory dysfunction is the most pervasive domain. The presence of multimorbid physical and mental illness suggests that several underlying mechanisms of memory impairment may be at play. The serial position phenomenon describes the tendency to best recall the beginning (primacy effect) and last (recency effect) words on a supra-span wordlist. Recency recall engages executive and working-memory systems, whereas primacy recall depends on long-term memory. This study investigates memory dysfunction in a homeless and precariously housed sample by identifying and characterizing unique subtypes of serial position profiles on a test of verbal memory. Participants and Methods: Data were used from a 20-year study of homeless and precariously housed adults recruited from an impoverished neighbourhood in Vancouver, Canada. Participants were sub-grouped according to their serial position profile on the Hopkins Verbal Learning Test-Revised using a latent profile analysis (LPA; n = 411). Paired samples t-tests were conducted to determine differences in percent recall from each word-list region within classes. Linear regression analyses were used to examine between-class differences in mean serial position scores and other cognitive measures (memory, attention, processing speed, cognitive control). Covariates included age, sex, and education. Results: LPA identified two profiles characterized by (1) reduced primacy relative to recency (RP; n = 150); and (2) reduced recency relative to primacy (RR; n = 261). Pairwise comparisons within the RP class showed that recency was better than primacy (p < .001, d = .66) and middle recall (p < .001, d = .52), with no difference between primacy and middle recall (p = .68, d = .04). All pairwise comparisons differed within the RR class (primacy > middle recall: p < .001, d = 1.85; primacy > recency recall: p < .001, d = 1.32; middle > recency recall: p < .05, d = .132). The RP class had worse performance on measures of total immediate (ß = .47, p < .001) and delayed verbal recall (ß = .32, p < .001); processing speed (ß = .20, p < .001); and cognitive control (ß = .22, p < .001). The RR class made more repetition errors (ß = .25, p < .001). Conclusions: These findings support substantial heterogeneity in memory functioning in homeless and precariously housed individuals. The RP profile was characterized by poorer cognitive functioning across several domains, which suggests multiple contributions to memory impairment, including dysfunction of long-term memory circuitry. The RR profile with their higher number of repetition errors, may experience difficulties with self-monitoring in verbal learning. Subsequent studies will explore the neurobiological underpinnings of these subgroups to further characterize profiles and identify targets for cognitive intervention.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.045
GPT teacher head0.375
Teacher spread0.329 · 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 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

Citations0
Published2023
Admission routes2
Has abstractyes

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