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Record W4379472890 · doi:10.3389/fpsyt.2023.1029082

COVID-19-related anxiety and the role of social media among Canadian youth

2023· article· en· W4379472890 on OpenAlexafffundabout
Soyeon Kim, Kimberly D. Belfry, Jennifer Crawford, Arlene G. MacDougall, Nathan J. Kolla

Bibliographic record

VenueFrontiers in Psychiatry · 2023
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsUniversity of TorontoOntario Tech UniversityMcMaster UniversityCentre for Addiction and Mental HealthWestern UniversityWaypoint Centre for Mental Health Care
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsAnxietyScreen timeCoronavirus disease 2019 (COVID-19)PsychologyLogistic regressionDemographySocial anxietyClinical psychologyMedicinePsychiatryDiseasePhysical activitySociologyInternal medicinePhysical therapy

Abstract

fetched live from OpenAlex

Background Current literature indicates that safety measures, including lockdowns during the COVID-19 pandemic, severely disrupted our lifestyle, marked by increased screen time. The increased screen time is mostly associated with exacerbated physical and mental wellbeing. However, the studies that examine the relationship between specific types of screen time and COVID-19-related anxiety among youth are limited. Methods We examined the usage of passive watching, social media, video games, and educational screen time and COVID-19-related anxiety at the 5-time points (Early-Spring 2021, Late-Spring 2021, Fall 2021, Winter 2022, and Spring 2022) among youth in Southern Ontario, Canada (N = 117, mean age = 16.82, male = 22%, non-White = 21%) and investigated the role of 4 types of screen time in COVID-19 related anxiety. COVID-related anxiety was measured using the Coronavirus Anxiety Scale (CAS). Descriptive statistics examined the binary relationships between demographic factors, screen time, and COVID-related anxiety. Also, partially adjusted and fully adjusted binary logistic regression analyses were conducted to examine the association between the types of screen time and COVID-19-related anxiety. Results During the late Spring of 2021, when the provincial safety restrictions were most stringent, screen time was the highest among the 5 data collection time points. Further, adolescents experienced the highest COVID-19-related anxiety during this period. On the other hand, young adults experienced the highest COVID-19-related anxiety during Spring 2022. In a partially adjusted model (accounting for other types of screen time), engaging in 1–5 h per day on social media increased the likelihood of experiencing COVID-19-related anxiety compared to those who spend less than 1 h per day (OR = 3.50, 95%CI = 1.14–10.72, p < 0.05). Other types of screen time was not significantly associated with COVID-19-related anxiety. In a fully adjusted model (accounting for age, sex and ethnicity besides four types on screen time), 1–5 h per day of social media remained significantly associated with COVID-19-related anxiety (OR = 4.08, 95%CI = 1.22–13.62, p < 0.05). Conclusion Our findings suggest that COVID-19-related anxiety is associated with youth engagement in social media during the COVID-19 pandemic. Clinicians, parents, and educators should work collaboratively to provide developmentally appropriate approaches to reduce the negative social media impact on COVID-19-related anxiety and promote/foster resiliency in our community during the recovery period.

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)0.003
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 score0.247

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.006
Science and technology studies0.0060.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.015
GPT teacher head0.305
Teacher spread0.290 · 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

Citations4
Published2023
Admission routes3
Has abstractyes

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