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Record W4307631979 · doi:10.3390/ijerph192113969

Age and Gender Perspectives on Social Media and Technology Practices during the COVID-19 Pandemic

2022· article· en· W4307631979 on OpenAlexaffabout
Mary Chidiac, Christopher Ross, Hannah R. Marston, Shannon Freeman

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsLonelinessPandemicSocial mediaCoronavirus disease 2019 (COVID-19)PsychologyDemographicsScale (ratio)UCLA Loneliness ScaleMobile technologySocial distanceGerontologyDemographyMedicineMobile deviceSocial psychologySociologyGeographyPolitical science

Abstract

fetched live from OpenAlex

Few studies have examined social media and technology use during the COVID-19 pandemic in Canada. Therefore, the main research question and objective of this study was to examine similarities and differences in the influences of mobile technology and social media use on Canadians among different age groups and across gender during the COVID-19 pandemic. From June through October 2021, 204 persons completed a 72-item online survey. Survey questions encompassed COVID-19 pandemic experiences and technology use. Standardized measures including the Psychological Wellbeing measure, eHeals, and the UCLA V3 Loneliness scale were collected to examine the psychological influences of the COVID-19 pandemic. Findings showed that males under 50 years were most likely to self-isolate compared to the other demographic results of the study. Males reported using technology less than females but were more likely to report using technology to share information regarding COVID-19. Respondents under 50 years were also more likely to use smartphones/mobile phones as their most used mobile technology device, whereas respondents over 50 were more split between smartphones/mobile phones and computers/tablets as their most used device. Males scored higher on the UCLA loneliness scale and lower on the Psychological Wellbeing sub-scores compared to females. Further research should explore additional demographics in relation to broader aspects of digital skills across different age groups.

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)0.004
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.322
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.198
GPT teacher head0.482
Teacher spread0.285 · 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

Citations33
Published2022
Admission routes2
Has abstractyes

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