MétaCan
Menu
← Back to cohort
Record W7033677519

The Relationship Between Social Isolation and Cognitive Frailty Among Community-Dwelling Older Adults: The Mediating Role of Depressive Symptoms

2024· article· en· W7033677519 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2024
Typearticle
Languageen
FieldMedicine
TopicRadiomics and Machine Learning in Medical Imaging
Canadian institutionsnot available
Fundersnot available
KeywordsSocial isolationLogistic regressionDepressive symptomsGeriatric Depression ScaleCognitionDementiaDepression (economics)Association (psychology)Clinical Dementia Rating
DOInot available

Abstract

fetched live from OpenAlex

Yamei Bai,* Yuqing Chen,* Meng Tian, Jiaojiao Gao, Yulei Song, Xueqing Zhang, Haiyan Yin, Guihua Xu School of Nursing, Nanjing University of Chinese Medicine, Nanjing, 210023, People’s Republic of China*These authors contributed equally to this workCorrespondence: Guihua Xu, School of Nursing, Nanjing University of Chinese Medicine, No. 138, Xianlin Avenue, Qixia District, Nanjing, Jiangsu Province, 210023, People’s Republic of China, Tel +86-153-6513-2927, Email 7115@njucm.edu.cnPurpose: Social isolation and depression have an impact on cognitive frailty. However, the underlying mechanisms between these variables have not been well defined. This study aims to investigate the mediating role of depressive symptoms in the association between social isolation and cognitive frailty among older adults in China.Methods: From Mar 2023 to Aug 2023, a cross-sectional study was conducted with 496 community-dwelling older adults aged ≥ 60 years in Nanjing, Jiangsu Province, China. Demographic information was collected using the General Information Questionnaire. The Lubben Social Network Scale-6 (LSNS-6), Geriatric Depression Scale 15-item (GDS-15), Montreal Cognitive Assessment (MoCA), Clinical Dementia Rating (CDR), and FRAIL scale were used for the questionnaire survey. Multiple linear regression and binary logistic regression were utilized to explore the associations among social isolation, depressive symptoms, and cognitive frailty, and Bootstrap analysis was used to explore the mediating role of depressive symptoms in social isolation and cognitive frailty.Results: Linear regression results revealed that social isolation was positively associated with depressive symptoms (β = 0.873, p < 0.001). Logistic regression analysis showed that social isolation (OR = 1.769, 95% CI = 1.018~3.075) and depressive symptoms (OR = 1.227, 95% CI = 1.108~1.357) were significantly associated with cognitive frailty. Mediation analysis demonstrated that depressive symptoms significantly mediated the relationship between social isolation and cognitive frailty, with an indirect effect of 0.027 (95% CI = 0.003~0.051), and the mediating effect accounted for 23.6% of the total effect.Conclusion: Social isolation is associated with cognitive frailty in community-dwelling older adults, and depressive symptoms partially mediate the effect between social isolation and cognitive frailty. Active promotion of social integration among older individuals is recommended to enhance their mental health, reduce the incidence of cognitive frailty, and foster active aging.Keywords: cognitive frailty, social isolation, depressive symptoms, older adults

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)0.001
metaresearch head score (Gemma)0.002
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 score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.129
GPT teacher head0.516
Teacher spread0.388 · 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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueDOAJ (DOAJ: Directory of Open Access Journals)→Same topicRadiomics and Machine Learning in Medical Imaging→French-language works237,207→