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TRANSTORNOS DE ANSIEDADE EM IDOSOS: UM ESTUDO BIBLIOMÉTRICO ANXIETY DISORDERS IN THE ELDERLY PEOPLE: A BIBLIOMETRIC STUDY

2023· article· pt· W4385211235 on OpenAlexaff
Sandra Regina Sá, Flávio Rebustini

Bibliographic record

VenueArquivos de Ciências da Saúde da UNIPAR · 2023
Typearticle
Languagept
FieldComputer Science
TopicHealthcare during COVID-19 Pandemic
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsAnxietyPsychologyScopusHumanitiesPsychiatryPolitical scienceMEDLINEPhilosophy

Abstract

fetched live from OpenAlex

OBJETIVO: Esboçar o panorama científico sobre os sintomas dos transtornos de ansiedade em idosos. MÉTODOS: Trata-se de um artigo original com abordagem descritiva através de um estudo bibliométrico a partir de dois bancos gerados pela SCOPUS, os dados foram organizados com o Rayyan com a retirada das duplicidades e o VOSviewer foi o software escolhido para realizar as análises bibliométricas. RESULTADOS: Destaca-se que as análises bibliométricas agruparam os termos em clusters, corroborando com os pressupostos teóricos encontrados, com a prevalência de sintomas clínicos e doenças neurológicas associando-se com as intervenções e aspectos sociais, entretanto, os índices também revelam novas linhas de pesquisas. A partir das análises mais minuciosas e individualizadas da bibliometria, podemos inferir que os termos associados aos sintomas dos transtornos de ansiedade e idosos estabelecem baixa correlação, existindo assim, lacunas e fragilidades no campo de pesquisa com este tema. CONCLUSÃO: Este estudo permitiu explorar os sintomas dos transtornos de ansiedade em idosos através do campo literário e científico produzido em 2020, 2021 e 2022 em um cenário mundial com o total de 22.087 documentos, sendo 17.665 artigos e 4.422 revisões. Sugerimos que novos estudos com o objetivo de avançar frente a temática, ressaltando a importância dos estudos longitudinais e/ou multidisciplinares devido à natureza das variáveis.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Other designhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.010
metaresearch head score (Gemma)0.046
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.903
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.046
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0970.147
Science and technology studies0.0020.001
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.331
Teacher spread0.285 · 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

Labeled directly by 2 models reading the full record.

Bibliometrics

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Other design
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 routes1
Has abstractyes

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