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Forest plots of the meta-analysis.

2023· other· en· W6942275926 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2023
Typeother
Languageen
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsnot available
Fundersnot available
KeywordsRuminationCohort studyPsycINFOMEDLINECoping (psychology)CohortForest plotDepressive symptoms

Abstract

fetched live from OpenAlex

<div><p>Objective</p><p>This systematic review aims to examine the influencing factors of undergraduates’ depressive symptoms by summarizing the categories and intensity of the factors, to lay a foundation for subsequent research.</p><p>Methods</p><p>Two authors independently searched in Medline (Ovid), Embase (Ovid), Scopu, PsycINFO, PsycARTICLES, the Chinese Scientific Journal Database (VIP Database), China National Knowledge database (CNKI), and the WanFang database for cohort studies related to the influencing factors affecting depressive symptoms among undergraduates published prior to September 12, 2022. Adjusted Newcastle-Ottawa scale (NOS) was used to assess the risk of bias. Meta-analyses of regression coefficient estimates were performed to calculate pooled estimates with R 4.0.3 software.</p><p>Results</p><p>A total of 73 cohort studies were included, involving 46362 participants from 11 countries. Factors affecting depressive symptoms were classified into relational, psychological, predictors of response to trauma, occupational, sociodemographic and lifestyle factors. In Meta-analysis, 4 of 7 influencing factors were revealed to be statistically significant: negative coping (B = 0.98, 95%CI: 0.22–1.74), rumination (B = 0.06, 95%CI: 0.01–0.11), stress (OR = 0.22, 95%CI: 0.16–0.28) and childhood abuse (B = 0.42, 95%CI:0.13–0.71). No significant association was found in positive coping, gender and ethnicity.</p><p>Limitations</p><p>The current studies have the problems of inconsistent use of scales and large heterogeneity of research design, making it difficult to summarize, which is expected to be further improved in future research.</p><p>Conclusion</p><p>This review evidences the importance of several influencing factors of depressive symptoms among undergraduates. We advocate for more high-quality studies with more coherent and appropriate study designs and outcome measurement approaches in this field.</p><p>Trial registration</p><p><b><i>Systematic review registration</i>:</b> PROSPERO registration <a href="https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021267841" target="_blank">CRD42021267841</a>.</p></div>

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.423
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.4260.002

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 head0.120
GPT teacher head0.306
Teacher spread0.186 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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