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Record W3123754015

The Impact of Social Networking Sites Use on Health-Related Outcomes Among UK Adolescents

2020· article· en· W3123754015 on OpenAlexaff
Alexander Serenko, Ofir Turel, Hafsa Siddiqui

Bibliographic record

VenueJournal of the Association for Information Systems · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsLakehead UniversityOntario Tech University
Fundersnot available
KeywordsSleep hygieneSocial mediaUnhealthy foodCohortPsychologyHealthy eatingDuration (music)HygienePerspective (graphical)Sleep (system call)Environmental healthMedia useGerontologyMedicineObesitySocial psychologyPsychiatryPhysical activityPhysical therapy
DOInot available

Abstract

fetched live from OpenAlex

This study explores the impact of social networking site (SNS) use on health outcomes in adolescents. By using data from the 2015-16 sweep of the Millennium Cohort Study, SNS use and its effects on sleep duration, healthy eating (fruits/vegetables intake, eating breakfast), and self-rated health was evaluated in 11,884 adolescents (13-17 year-old). SNS use was found to be negatively associated with general health through decreased sleep duration and reduced healthy eating. Females have a higher risk of being negatively affected by the extent of their SNS use, compared to males. IS developers and SNS providers should allow easier tracking and monitoring of the use of their systems, as well as offer time management features, as unchecked use can lead to adverse health outcomes. Policymakers should consider public health interventions to address balancing SNS use with healthy behaviors, and shifting school start times to allow adolescents to have later wake times.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.034
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.323
Teacher spread0.291 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2020
Admission routes1
Has abstractyes

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Same venueJournal of the Association for Information SystemsSame topicImpact of Technology on AdolescentsFrench-language works237,207