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Record W4404024861 · doi:10.22215/cujs.v3i1.4838

Reflections on Limiting Social Media Use and Mental Health

2024· article· en· W4404024861 on OpenAlexaff
Abby Wilson

Bibliographic record

VenueCarleton undergraduate journal of science. · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsCarleton University
Fundersnot available
KeywordsLimitingMental healthSocial mediaPsychologySociologyComputer sciencePsychiatryWorld Wide WebEngineering

Abstract

fetched live from OpenAlex

The relationship between social media use and mental health has been well documented. A study by Bradley et al. (2023) examined whether reducing social media use to 30 minutes per day would improve mental health, but found no significant improvements, partly due to participants’ lack of adherence to study instructions. The current study examines qualitative responses to an open-ended reflection question from participants of this previous study. Most participants struggled to limit their social media use, largely because of benefits social media use provided and perceived consequences of not using social media. Many participants wanted to limit their social media use, despite most failing to do so during the study. Participants who did limit their social media use experienced improved mental health when limiting. Additionally, many participants had negative opinions about social media use, such as increasing social comparison, though positive and mixed opinions were also reported. This study suggests social media use limiting interventions may not be viable, and that different types of social media use must also be considered. Additionally, research viewing social media use as only having negative impacts is inaccurate; this study demonstrates that there is a continuum of effects it may have.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.273
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0010.001
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 head0.080
GPT teacher head0.400
Teacher spread0.320 · 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 designTheoretical or conceptual
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
Published2024
Admission routes1
Has abstractyes

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