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Record W3004564770 · doi:10.5539/gjhs.v12n3p12

Moderating Effect of Self-Esteem on the Relationship Between Optimism and Life Satisfaction in Final Year University Students

2020· article· en· W3004564770 on OpenAlexvenueno aff
Samson F. Agberotimi, Choja Oduaran

Bibliographic record

VenueGlobal Journal of Health Science · 2020
Typearticle
Languageen
FieldPsychology
TopicOptimism, Hope, and Well-being
Canadian institutionsnot available
Fundersnot available
KeywordsOptimismLife satisfactionSelf-esteemPsychologyScale (ratio)Clinical psychologySocial psychology

Abstract

fetched live from OpenAlex

This study examined the moderating effect of self-esteem on the relationship between optimism and life satisfaction in final year university students. A correlational survey design was utilized. Two hundred and twenty-three university final year students of a Nigerian university consisting of 124 males and 99 females aged 24.67±2.56 participated in the study. Data were collected with a structured self-report questionnaire containing satisfaction with life scale (α = .82), Rosenberg self-esteem scale (α = .86), and life orientation test – revised (α = .79). Data were analyzed with SPSS v.23 at 0.05 significant level. Self-esteem significantly moderated the relationship between optimism and life satisfaction as indicated by a significant increase in proportion of the variance in life satisfaction when the interaction term between optimism and self-esteem was added to the regression model [ΔR2 = .03, ΔF (1, 219) = 7.26, p < .008, b = .188, t(220) = 2.69, p < .01]. It was concluded that the predictive impact of optimism on life satisfaction of university final year students is enhanced by their self-esteem; thus, students should be exposed to environment and program that promotes the development of high self-esteem and optimistic life orientation to enhance their well-being.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.003
Threshold uncertainty score0.194

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.059
GPT teacher head0.366
Teacher spread0.308 · 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.

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

Citations3
Published2020
Admission routes1
Has abstractyes

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