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Record W2587164166 · doi:10.1089/cyber.2016.0194

Associations Between Internet Attachment, Cyber Victimization, and Internalizing Symptoms Among Adolescents

2017· article· en· W2587164166 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCyberpsychology Behavior and Social Networking · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsAnxietyThe InternetPsychologyVulnerability (computing)Depression (economics)Mental healthClinical psychologyAttachment theoryPsychiatryComputer securityWorld Wide Web

Abstract

fetched live from OpenAlex

With increasing frequency of Internet use among adolescents, there are growing concerns about their risk for becoming attached to these forms of communication and increased vulnerability for negative online experiences, including cyber victimization. The effect of these experiences on adolescent mental health is not well understood. In this study, we examine how Internet attachment is related to anxiety and depression and assess the mediating effect of cyber victimization on these associations. Participants included 1,151 middle school students (51.4 percent males) aged 10 to 16 (M = 12.7, SD = 0.93). Structural equation models show that greater Internet attachment was associated with more cyber victimization and greater symptoms of anxiety and depression. Cyber victimization mediated the associations between Internet attachment and anxiety and between Internet attachment and depression. Implications for online awareness efforts are discussed.

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.

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 categoriesMeta-epidemiology (narrow), Science 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 score0.068
Threshold uncertainty score1.000

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 studies0.0040.002
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.039
GPT teacher head0.368
Teacher spread0.329 · 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