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Record W4414656052 · doi:10.29400/tjgeri.2025.454

INVESTIGATION OF THE LONG-TERM EFFECTS OF PANDEMIC VACCINES ON PHYSICAL AND COGNITIVE PERFORMANCE AFTER THE PANDEMIC

2025· article· en· W4414656052 on OpenAlexaboutno aff
Rıdvan Yıldız, Onur Seçgin Nişancı

Bibliographic record

VenueThe Turkish Journal of Geriatrics · 2025
Typearticle
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsnot available
Fundersnot available
KeywordsPandemicCognitionEffects of sleep deprivation on cognitive performanceQuality of life (healthcare)Coronavirus disease 2019 (COVID-19)CoronavirusTest (biology)Significant difference

Abstract

fetched live from OpenAlex

Introduction:The present study compared the post-pandemic effects of different vaccines and vaccine combinations administered during the coronavirus disease 2019 pandemic in individuals defined as “young-elderly.” Materials and Method: Participants included 440 volunteers who met the inclusion criteria. They were divided into four groups based on the type of vaccine they had received. During data collection, participants completed a Personal Information Form, the Montreal Cognitive Assessment, the 36- item Short Form Health Survey, and the Alusti Test. The study was conducted between December 15, 2024, and May 29, 2025.Data were analyzed using SPSS version 28.0. Results: The analyses revealed a statistically significant difference between groups in both the Alusti test (assesses physical performance) and the 36-item Short Form Health Survey (assesses quality of life) (p<0.05).This difference was particularly pronounced in the group that received the combination of BioNTech and Sinovac vaccines;it hadlower scores on physical performance and quality of life compared to the other groups. Cognitive performance did not differ significantly between the groups (p>0.05). Conclusion:Therefore,the coronavirus disease vaccines may have varying long-term effects on the individual’s overall health status and quality of life. Keywords: COVID-19; Physical Functional Performance; Cognition; Quality of Life; Vaccines.

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)0.001
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 score0.012
Threshold uncertainty score0.297

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.010
GPT teacher head0.274
Teacher spread0.264 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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