MétaCan
Menu
Back to cohort
Record W4404508471 · doi:10.2196/64033

Association of Subjective Cognitive Concerns With Performance on Mobile App–Based Cognitive Assessment in Cognitively Normal Older Adults: Observational Study

2024· article· en· W4404508471 on OpenAlexvenueno aff
Caroline O. Nester, Alyssa N. De Vito, Sarah Prieto, Zachary J. Kunicki, Jennifer Strenger, Karra Harrington, Nelson Roque, Martin J. Sliwinski, Laura A. Rabin, Louisa I. Thompson

Bibliographic record

VenueJMIR Aging · 2024
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersNational Institute on AgingAlzheimer's Association
KeywordsPreprintObservational studyCognitionPsychologyMobile appsMedicineComputer scienceWorld Wide WebPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Subjective cognitive concerns (SCC) may be among the earliest clinical symptoms of dementia. There is growing interest in applying mobile app-based cognitive assessment to remotely screen for cognitive status in preclinical dementia, but the relationship between SCC and relevant mobile assessment metrics is uncertain. OBJECTIVE: We characterized the relationship between SCC and adherence, satisfaction, and performance on mobile-app assessments in cognitively unimpaired older adults. METHODS: Participants (N=122, Mage=69.85, Meducation=16.52, %female=66.7, %White=86.2) completed 8 assessment days using Mobile Monitoring of Cognitive Change (M2C2), an app-based testing platform, with brief daily sessions within morning, afternoon, and evening time windows (24 total testing sessions). M2C2 includes digital working memory, processing speed, and episodic memory tasks. Participants provided feedback about their satisfaction and motivation related to M2C2 upon study completion. SCC was assessed using the Cognitive Function Instrument (CFI). Regression analyses evaluated the association between SCC and adherence, satisfaction, and performance on M2C2, controlling for age, sex, depression, and loneliness. Linear-mixed effects models evaluated whether SCC predicted M2C2 subtest performance over the 8-day testing period, controlling for covariates. RESULTS: SCC was not associated with app satisfaction or protocol motivation, but it was significantly associated with lower rates of protocol adherence (ß=-0.197, p=.037, 95% CI -0.647, -0.021). Higher SCC endorsement significantly predicted worse overall episodic memory performance (ß=-0.200, p = .020, 95% CI -0.020, -0.002), but not working memory or processing speed. There was a main effect of SCC on working memory performance at day 1 (Est=-1.047, SE=0.47, p=0.031) and a significant interaction between SCC and working memory over the 8-day period (Est=0.048, SE=0.02, p=0.031), such that SCC was associated with initially worse, then progressively better working memory performance. CONCLUSIONS: SCCs are associated with worse overall memory performance on mobile-app assessments, patterns of cognitive inefficiency (variable working memory) and mildly diminished adherence across an 8-day assessment period. Findings suggest that mobile app assessments may be sensitive to subtle cognitive changes, with important implications for early detection and treatment for individuals at risk for dementia.

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 score0.026
Threshold uncertainty score0.895

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 integrity0.0000.001
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 head0.028
GPT teacher head0.372
Teacher spread0.344 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJMIR AgingSame topicDementia and Cognitive Impairment ResearchFrench-language works237,207