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Record W3098029319 · doi:10.1097/md.0000000000023196

Supportive psychological intervention on psychological disorders in clinical medicine students with English Learning Difficulties

2020· article· en· W3098029319 on OpenAlexaboutno aff
Hongli Wen, Shuling Zhang, Xiaowei Li

Bibliographic record

VenueMedicine · 2020
Typearticle
Languageen
FieldMedicine
TopicMedical Education and Admissions
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCochrane LibraryMEDLINEIntervention (counseling)English languageEvidence-based medicineScale (ratio)Medical educationAlternative medicinePsychiatryPathologyPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: This study aims to examine the effect of supportive psychological intervention (SPI) on psychological disorders (PD) in clinical medicine students (CMS) with English Learning Difficulties (ELD). METHODS: We will perform a comprehensive literature search from the following databases: Cochrane Library, MEDLINE, EMBASE, Allied and Complementary Medicine Database, Chinese Biomedical Literature Database, and China National Knowledge Infrastructure. All databases will be performed from their inception to the present without language limitation by 2 independent reviewers. We will also look for grey literature, such as conference proceedings, dissertations or theses. Newcastle-Ottawa Scale will be used to assess study quality, and RevMan 5.3 software will be applied to carry out statistical analysis. RESULTS: This study will summarize the most recent evidence to assess the effect of SPI on PD in CMS with ELD. CONCLUSION: This study may provide helpful evidence of SPI on PD in CMS with ELD. OSF REGISTRATION NUMBER:: osf.io/tah2s.

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)0.001
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.124
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0100.000

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 head0.089
GPT teacher head0.489
Teacher spread0.400 · 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 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

Citations1
Published2020
Admission routes1
Has abstractyes

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