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Record W4200633464

Prevalence, Influencing Factors, and Cognitive Characteristics of Depressive Symptoms in Elderly Patients with Schizophrenia

2021· article· en· W4200633464 on OpenAlexaboutno aff
Yuan Yao Chen, Wei Li

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2021
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Wellbeing Research
Canadian institutionsnot available
Fundersnot available
KeywordsSchizophrenia (object-oriented programming)Depressive symptomsCognitionClinical psychologyPsychologyPsychiatryDepression (economics)Medicine
DOInot available

Abstract

fetched live from OpenAlex

Yaopian Chen, 1 Wei Li 2, 3 1Department of Sleep Medicine, Wenzhou Seventh People’s Hospital, Wenzhou, People’s Republic of China; 2Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China; 3Alzheimer’s Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, People’s Republic of ChinaCorrespondence: Wei LiDepartment of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People’s Republic of ChinaTel +86 021 64387250Email 822203867@qq.comPurpose: To investigate the prevalence, influencing factors, and cognitive characteristics of depressive symptoms in elderly patients with chronic schizophrenia.Patients and Methods: A total of 241 elderly patients with chronic schizophrenia and 156 healthy controls were enrolled in this study. The Geriatric Depression Scale (GDS) was used to assess depressive symptoms; the Positive and Negative Syndrome Scale was used to assess psychotic symptoms; and both the Mini-Mental State Examination and Montreal Cognitive Assessment were used to assess overall cognitive function, while the Activity of Daily Living Scale was used to assess daily living ability.Results: The prevalence of depressive symptoms was 48.5% (117/241) in elderly patients with chronic schizophrenia, which was substantially higher than that of normal controls (17.3%, 27/156). Using a stepwise binary logistic regression analysis, we found that high education (p=0.006, odds ratio [OR]=1.122, 95% confidence interval [CI]:1.034– 1.218) and hypertension (p=0.019, OR=0.519, 95% CI: 0.300– 0.898) were influencing factors for the comorbidity of depressive symptoms. Compared with individuals without depressive symptoms, individuals with depressive symptoms usually display worse overall cognitive function and more severe impairment of activities of daily living, but fewer psychotic symptoms. Interestingly, the GDS score was negatively correlated with the course of the disease (r=− 0.157, p=0.016), suggesting that patients who had recently been admitted to the hospital were more likely to develop depression.Conclusion: Elderly patients with chronic schizophrenia are often associated with higher levels of depression. Therefore, their overall cognitive function is worse, and their activities of daily living are more seriously impaired. Therefore, these patients should be provided with appropriate psychological comfort, especially those who have recently been admitted to the hospital.Keywords: elderly, chronic schizophrenia, depressive symptoms, hypertension, education

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 score0.004
Threshold uncertainty score0.009

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.139
GPT teacher head0.552
Teacher spread0.413 · 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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