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Scopus based bibliometric and scientometric analysis of occupational therapy publications from 2001 to 2020

2022· preprint· en· W4210843327 on OpenAlexaboutno aff
Koushik Sau, Yogendra Nayak

Bibliographic record

VenueF1000Research · 2022
Typepreprint
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsnot available
Fundersnot available
KeywordsScopusBibliometricsOccupational therapyPublishingScientometricsMedicineImpact factorMultidisciplinary approachLibrary scienceMEDLINEFamily medicineSocial sciencePolitical scienceSociologyPsychiatry

Abstract

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<ns7:p> <ns7:bold>Background:</ns7:bold> Occupational therapy (OT) is one of the allied health professions that had its first journals way back in 1920. The main objective of this study was to find out the publication trend in the field of OT research for the period of 2001-2020 using the principles of bibliometrics and scientometrics. </ns7:p> <ns7:p> <ns7:bold>Methods:</ns7:bold> The data was retrieved from Scopus from the past 20-years (2001-2020). VOSviewer software was used to find year-wise publications in OT-specific and non-OT-specific Journals along with top journals, countries, organisations, authors, cited articles, and highly used keywords. </ns7:p> <ns7:p> <ns7:bold>Results:</ns7:bold> There was a steady growth of OT articles from the past 20-years. Scopus indexes 16 OT-specific journals are identified. American Journal of Occupational Therapy, British Journal of Occupational Therapy Journal, Australian Occupational Therapy Journal, Scandinavian Journal of Occupational Therapy and Canadian Journal of Occupational Therapy are the leading publications and citations. Comparison of OT-specific and non-OT journals inferred that the OT-specific papers are three times more published in non-OT journals. There is a trend in publishing multidisciplinary medical journals than OT journals. The US publishes the highest number of articles, followed by the UK, Australia, Canada, and Germany. Though the US alone produced a considerable number of articles (9517), only five organisations are listed in the top-20, compared to Canada (n=6) and Australia (n=5). Australia represents the highest published authors (n=11/20), and Canada represents a highly cited author from the top-cited publications. The “occupational therapy”, “rehabilitation”, “stroke”, “physical therapy,” and “activities of daily living” are the five common keywords used by OT authors. This study lists top-20 journals along with their CiteScore and Journal Impact Factor. </ns7:p> <ns7:p> <ns7:bold>Conclusions:</ns7:bold> This study will help the budding researchers in OT to select a suitable quality journal for publication and, further, helpful for research promotion, researcher incentivising, grant allocations, and policymakers in the OT field. </ns7:p>

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
Observationalhigh
models agreeAgreement 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)0.013
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Insufficient payload (model declined to judge)
Consensus categoriesBibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.262
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.2770.539
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0030.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0280.000

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 head0.524
GPT teacher head0.606
Teacher spread0.082 · 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.

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

Citations6
Published2022
Admission routes1
Has abstractyes

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