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Record W4313415928 · doi:10.24193/cbb.2022.26.13

Global research trends on psychosocial rehabilitation in patients with cardiovascular diseases: A bibliometric analysis using CiteSpace

2022· article· en· W4313415928 on OpenAlexaboutno aff
Kanatt Suryasree, S. Kadhiravan

Bibliographic record

VenueCognition Brain Behavior An Interdisciplinary Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsPsychosocialCitationRehabilitationInstitutionMedicinePopularityGerontologyCitation analysisWeb of scienceScience Citation IndexBibliometricsLibrary scienceFamily medicinePsychologySocial scienceSociologyPhysical therapyPsychiatryPathologyComputer science

Abstract

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Cardiovascular diseases (CVDs) pose a serious threat to global public health due to its high prevalence and mortality. Meanwhile, psychosocial rehabilitation (PSR) has gained popularity due to its beneficial effects on the cardiovascular system. There is substantial evidence that PSR is effective in lessening cardiovascular morbidity and mortality in CVD patients. To learn more about the development of PSR, 3,759 publications about PSR and related research were retrieved from the Web of Science (WoS) Core Collection from 1989 to 2022. Then, these publications were analysed using CiteSpace 6.1.R3 (64-bit) W version software in terms of country and institution-based analysis, author co-citation analysis (ACA), keyword analysis, and document co-citation analysis (DCA). The outcomes were elaborated in four aspects. First, the number of annual publications related to PSR has consistently increased in last three decades. Second, country and institution-based analysis showed that a few developed countries such as the United States, England and Canada, and institutions such as the Harvard University, the University of California, and the University of Toronto were the most active countries and institutions in carrying out PSR-related studies. Third, author co-citation analysis (ACA) revealed that Sherry L. Grace from York University had the highest number of publications (35). Her research majorly focused on optimizing post-acute cardiovascular care and its outcomes that contribute to the field of PSR. Frasure-Smith had the highest burst count of 41.39. His research mainly emphasized on the impact of psychological stress in acute myocardial infarction which is related to CVD. Document co-citation analysis (DCA) revealed that epidemiologic evidence was the predominant cluster in the domain of PSR. Fourth, Keyword based analysis showed that keywords such as coronary heart disease, cardiovascular disease, acute myocardial infarction and major depression made outstanding contribution to the PSR field. In conclusion, this study has provided useful information for gaining knowledge about PSR such as identifying potential contributors for researchers interested in the field of PSR, and discovering research trends in PSR, which can provide guidance for more extensive studies related to PSR in the future.

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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics, Science and technology studies
Consensus categoriesBibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0520.099
Science and technology studies0.0010.000
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 head0.050
GPT teacher head0.452
Teacher spread0.403 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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