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Record W4390918012 · doi:10.32388/jwyqie.2

Research Trends in Mindfulness for Adolescents: Based on CiteSpace Visualization Analysis

2024· preprint· en· W4390918012 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueQeios · 2024
Typepreprint
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMindfulnessChinaWeb of sciencePsychologyBibliometricsGeographyPolitical scienceLibrary scienceComputer scienceMEDLINEClinical psychologyArchaeology

Abstract

fetched live from OpenAlex

Mindfulness has been increasingly used to improve the mental health of adolescents. This study focused on evaluating the latest research status of mindfulness for adolescents through CiteSpace and on identifying research hotspots and frontiers. We extracted the English literature of mindfulness for adolescents from the Web of Science (WoS) and the Chinese literature from the China National Knowledge Infrastructure (CNKI) databases, covering the period from 1999 to 2022. A total of 1317 papers were obtained. CiteSpace was used to generate online maps of worldwide cooperation among countries, institutions, and authors. Hotspots and frontiers were systematically summarized. There is a paucity of collaboration among institutions in the Chinese literature compared to the English literature. The research themes of the literatures of the two languages have overlaps and also discrepancies at different times. Future research may focus on the mechanism of mindfulness and appropriate groups for application. Collaboration among authors should be strengthened.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.857
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.000

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 head0.099
GPT teacher head0.474
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