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Record W3015522173 · doi:10.5430/wje.v10n2p50

Cyberbullying among Normal and Attention Deficit Hyperactivity Disorder University Students (A Psychometric-Clinical Study)

2020· article· en· W3015522173 on OpenAlexvenueno aff
Mohamed Mustafa Abdelrazek, Mahmoud Mohamed Eltantawy

Bibliographic record

VenueWorld Journal of Education · 2020
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyAttention deficit hyperactivity disorderClinical psychologyAttention deficitTest (biology)PopulationDevelopmental psychologyMedicine

Abstract

fetched live from OpenAlex

The present study aimed to investigate cyberbullying among normal and attention deficit hyperactivity disorder (ADHD) university students based on some variables. Its population comprised (1312) students at Saudi universities and disability centers and covered a sample of (148) normal and ADHD students encountering cyberbullying. Two clinical case studies were conducted. The study adopted the descriptive and analytical method, as well as the clinical approach. It utilized the cyberbullying scale, interview form, and Thematic Apperception Test. Results revealed the proliferation of some cyberbullying types among normal and ADHD university students. The cultural nature of the community affected the type of cyberbullying. Furthermore, there were differences in cyberbullying between normal and ADHD university students in favor of the ADHD students and between males and females, favoring the males. Such differences were caused by psychological and cultural variables .

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)0.001
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 score0.022
Threshold uncertainty score0.445

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.035
GPT teacher head0.355
Teacher spread0.319 · 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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