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Record W2882977615 · doi:10.5430/wje.v8n4p11

Investigation of Smartphone Addiction Effect on Recreational and Physical Activity and Educational Success

2018· article· en· W2882977615 on OpenAlexvenueno aff
Osman Gümüşgül

Bibliographic record

VenueWorld Journal of Education · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsnot available
Fundersnot available
KeywordsRecreationPsychologyAddictionSmartphone addictionPhysical activitySignificant differenceTest (biology)Scale (ratio)Applied psychologyPhysical therapyMedicinePsychiatry

Abstract

fetched live from OpenAlex

The aim of the study was to investigate smartphone addiction effect on physical activity, recreational sportsparticipation and educational success. In total, 255 students studying at Dumlupinar University and using smartphone(136 male and 119 female) voluntarily participated to the study. Within the scope of this study, SmartphoneAddiction Scale-Short Version (SAS-SV) (Noyan, Darcin, Nurmedov, Yilmaz & Dilbaz, 2015) was applied to theparticipants. To the data gathered from the participants, parametric tests as Independent Sample T-Test and ANOVAwere applied (p<0.05). According to the results there is significant difference between smartphone addiction ofparticipants and gender, age and recreational sports (p<0,05); but there is no significant difference betweensmartphone addiction and academic success and recreational activities practiced (p>0,05). It is considered thatparticipants with higher academic grades may have higher smartphone addiction score because of using smartphonesas teaching tool in classrooms. Participants practicing physical and recreational sports have less smartphoneaddiction score and it can give a clue that smartphones are constraints for physical activities and this may be a reasonand taking precaution subject for a sedentary lifestyle and unhealthy individuals.

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 score0.338
Threshold uncertainty score0.254

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.016
GPT teacher head0.341
Teacher spread0.324 · 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

Citations15
Published2018
Admission routes1
Has abstractyes

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