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Record W2999667632 · doi:10.5430/ijhe.v9n2p144

Social Self-Efficacy and its Relationship to Loneliness and Internet Addiction among Hashemite University Students

2020· article· en· W2999667632 on OpenAlexvenueno aff
Ahmad M. Gazo, Ahmad M. Mahasneh, Mohammed H. Abood, Faten A. Muhediat

Bibliographic record

VenueInternational Journal of Higher Education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsnot available
Fundersnot available
KeywordsLonelinessAddictionThe InternetPsychologySelf-efficacyUCLA Loneliness ScaleSocial mediaClinical psychologySocial psychologyPsychiatryWorld Wide Web

Abstract

fetched live from OpenAlex

The present study investigates the relationship between social self-efficacy, loneliness and internet addiction among Hashemite University students. It defines the level of social self-efficacy, and whether there are statistically significant differences by gender, academic specialization and academic level; and defines the levels of loneliness and internet addiction. The purposive sample consisted of (618) students at Hashemite University. The Social Self-efficacy, Loneliness and Internet Addiction Scales were used. The results show that the level of social self-efficacy was medium, with statistically significant differences in the level of social self-efficacy attributed to students by gender in favor of male students, and in the level of social self-efficacy by academic level in favor of second-year students. The level of loneliness was medium, as was the level of internet addiction. There was a negative correlation between social self-efficacy and loneliness and internet addiction, and a positive correlation between loneliness and internet addiction.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.029
GPT teacher head0.361
Teacher spread0.332 · 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

Citations38
Published2020
Admission routes1
Has abstractyes

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