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Record W4283271707 · doi:10.1080/07448481.2022.2087473

Comparing the prevalence of nomophobia and smartphone addiction among university students pre-COVID-19 and during COVID-19

2022· article· en· W4283271707 on OpenAlexaff
Wuyou Sui, Anna Sui, Joseph Munn, Jennifer D. Irwin

Bibliographic record

VenueJournal of American College Health · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsWestern University
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Smartphone addictionAddictionMedicineClinical psychology2019-20 coronavirus outbreakPsychologyPsychiatryPathology

Abstract

fetched live from OpenAlex

Background This study aimed to: (a) explore differences in the prevalence of nomophobia and smartphone addiction (SA) from pre- to during COVID-19; (b) identify students’ self-reported changes in smartphone reliance and screen time during COVID-19; and (c) examine whether self-perceived changes in smartphone usage predicted nomophobia and SA scores.Methods Scores on the Nomophobia Questionnaire and Smartphone Addiction Scale between two surveys administered at two timepoints were compared: Sample 1 (September 2019–January 2020; N = 878) and Sample 2 (May-June 2020; N = 258).Results No significant differences were found between samples on nomophobia or SA. Nearly all of Sample 2 reported using some type of app more, using their smartphone a little more, and about the same perceived smartphone reliance during COVID-19. Increased screen time, smartphone reliance, and social media significantly predicted nomophobia and SA.Conclusion COVID-19 does not appear to have exacerbated the prevalence of nomophobia or SA.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
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 head0.021
GPT teacher head0.333
Teacher spread0.312 · 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.

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

Citations7
Published2022
Admission routes1
Has abstractyes

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