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Record W4311665288 · doi:10.3390/ijerph192316334

Depressive Symptoms as a Mediator between Excessive Daytime Sleepiness and Suicidal Ideation among Chinese College Students

2022· article· en· W4311665288 on OpenAlexafffund
Yao-Kun Yu, Zhi-Ying Yao, Yan-Xin Wei, Changgui Kou, Bin Yao, Wenjun Sun, Suyun Li, Kenneth Fung, Cun-Xian Jia

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2022
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsToronto Western HospitalUniversity of Toronto
FundersCanadian Institutes of Health ResearchNational Natural Science Foundation of China
KeywordsSuicidal ideationDepressive symptomsIdeationExcessive daytime sleepinessPsychologyClinical psychologyPsychiatryDepression (economics)MedicinePoison controlSuicide preventionSleep disorderInsomniaAnxietyMedical emergency

Abstract

fetched live from OpenAlex

The purpose of this study was to verify the mediating role of depressive symptoms between excessive daytime sleepiness and suicidal ideation in college students. Of the 6944 participants, 2609 (37.6%) were male and 4335 (62.4%) were female. College students with excessive daytime sleepiness (p < 0.001) and those with depressive symptoms (p < 0.001) were more likely to have suicidal ideation. Moreover, both excessive daytime sleepiness (β = 0.14, 95% CI: 1.01−1.32) and depressive symptoms (β = 1.47, 95% CI: 3.80−5.00) were associated with suicidal ideation. The effect size of the mediating role of depressive symptoms in excessive daytime sleepiness to suicidal ideation was 50.41% for the entire sample, 58.33% for males, and 42.98% for females. Depressive symptoms partially mediated the relationship between excessive daytime sleepiness and suicidal ideation. The timely assessment of depressive symptoms in college students with excessive daytime sleepiness, and intervention, may reduce their risk of suicidal ideation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.414
Teacher spread0.373 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations5
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Environmental Research and Public Health→Same topicSuicide and Self-Harm Studies→French-language works237,207→