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Record W3195063874 · doi:10.1111/jora.12658

Social Disconnection During COVID‐19: The Role of Attachment, Fear of Missing Out, and Smartphone Use

2021· article· en· W3195063874 on OpenAlexafffundabout
Natasha Parent, Kyle Dadgar, Bowen Xiao, Cassandra L. Hesse, Jennifer D. Shapka

Bibliographic record

VenueJournal of Research on Adolescence · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsDisconnectionFeelingPsychologyThematic analysisCoronavirus disease 2019 (COVID-19)PandemicSocial psychologySocial isolationSocial media2019-20 coronavirus outbreakProtective factorDevelopmental psychologyQualitative researchPsychotherapistSociologyMedicine

Abstract

fetched live from OpenAlex

This mixed-methods study explored adolescents' (n = 682) feelings of social connection in the time of the COVID-19 pandemic and examined potential risk (fear of missing out, problematic smartphone use) and protective (parent/peer attachment, smartphone use) factors to social disconnection. Data were collected from two schools in Canada using an online survey with questionnaires and open-ended questions. Three themes regarding adolescents' feelings of social connection during the pandemic were identified through thematic content analysis: (1) feeling socially connected, (2) feeling socially disconnected, and (3) feeling socially indifferent. Moreover, regression analysis identified secure peer attachments as a protective factor against social disconnection in the time of the COVID-19 pandemic, while fear of missing out was identified as an independent risk factor.

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)0.005
metaresearch head score (Gemma)0.009
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 score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.107
GPT teacher head0.456
Teacher spread0.349 · 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

Citations57
Published2021
Admission routes3
Has abstractyes

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