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Global publications on Covid-19 and psychology: A scientometric assessment

2022· article· en· W4285243003 on OpenAlexaboutno aff
Sandeep Grover, B. M. Gupta

Bibliographic record

VenueLibrary Herald · 2022
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Social scienceVeterinary medicineLibrary scienceMedicineSociologyVirologyComputer sciencePathologyOutbreak

Abstract

fetched live from OpenAlex

The article evaluates the global output on ‘COVID-19 and Psychology’ using bibliometric methods and indicators. The quantitative and qualitative analysis of all the publications in Scopus database was performed using ‘Covid- 19’ and its synonyms keywords in ‘Keyword’ and ‘Title’ tags. The results obtained were further restricted to the subject Psychology under the subject tag. A total of 8205 global publications were identified on the topic of ‘Covid- 19 and Psychology’ in Scopus database, that were cited 63361 times with an average of 7.72 citations per paper. About one-sixth (17.9%) of these publications received external funding support and registered 11.35 citations per paper. The maximum number of publications emerged from the USA, the U.K. and China (2640, 997 and 757 publications), and publications from Canada (16.68 and 2.16), Australia (15.25 and 1.98), U.K. (13.49 and 1.75) received the highest citation per paper and relative citation index. The organisations that produced the highest number of publications were Sapienza University of Rome, Italy (97 papers), University College London, U.K. (95 papers) and King's College London, U.K (91 papers). The organizations with highest citation impact per paper and relative citation index were: Peking University, China (46.46 and 6.02), University of Michigan, Ann Arbor, USA (41.74 and 5.41) and University of Queensland, Australia (39.48 and 5.11). The authors that produced the highest number of publications were G.J. Asmundson (26 papers), S. Grover (22 papers) and S. Taylor (22 papers). The authors who had the highest citation impact per paper and relative citation index were KM. Douglas (137.6 and 17.82), M.M. Paluszek (68.27 and 8.84) and S.K Kar (63.9 and 8.28). The journals that produced the highest number of publications were Frontiers in Psychology (1028 papers), Asian Journal of Psychiatry (324 papers) and the most impactful journals were Nature Human Behavior (52.18), Lancet Child & Adolescent Health (43.68) and Asian Journal of Psychiatry (19.78). The most studied subfields as reflected in keyword frequency were: Mental Health (1187), Anxiety (1176), Depression (881), Mental Disease (408), Distress Syndrome (217), etc. A significant amount ofliterature has emerged on psychological impact of COVID-19 since the beginning of the pandemic.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.340
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0140.000

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 head0.115
GPT teacher head0.490
Teacher spread0.375 · 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 teacher head, not a consensus.

Study designNot applicable
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
Published2022
Admission routes1
Has abstractyes

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