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Record W2889389337 · doi:10.5539/ass.v14n9p25

Personality Factors, Academic Stress and Socio-economic Status as Factors in Suicide Ideation among Undergraduates of Ebonyi State University

2018· article· en· W2889389337 on OpenAlexvenueno aff
Ronald C.N. Oginyi, Ofoke S. Mbam, Nwonyi Sampson, Ekwo Jude Chukwudi, Martin O. E. Nwoba

Bibliographic record

VenueAsian Social Science · 2018
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSuicidal ideationPersonalityPsychologyClinical psychologyPsychological interventionBig Five personality traitsIdeationRegression analysisSuicide preventionPoison controlSocial psychologyPsychiatryMedicineEnvironmental health

Abstract

fetched live from OpenAlex

The major purpose of this research was to investigate personality factors, academic stress and socio-economic status as factors in suicide ideation among undergraduates. The second purpose was to determine the extent to which personality factors, academic stress and socio-economic status could buffer the negative impacts of suicidal ideation. Cross sectional survey was used for the design of this study and hierarchical multiple regression was adopted for data analysis. Results showed that personality factors, academic stress and socio-economic status jointly and separately predicted suicidal ideation. The research findings implied that interventions strategies to improve social network and assessment of their personality factors may have positive outcome in reducing or preventing suicide ideation among undergraduates.

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)0.001
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.034
GPT teacher head0.328
Teacher spread0.293 · 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

Citations6
Published2018
Admission routes1
Has abstractyes

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