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Record W4311680955 · doi:10.22215/etd/2022-15233

Towards a Better Understanding of the Neurobiological Basis of Problematic Social Media use in Young Adults

2022· dissertation· en· W4311680955 on OpenAlexaff
Holly Shannon

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsCarleton University
Fundersnot available
KeywordsAddictionPsychologySocial mediaStriatumAssociation (psychology)Cognitive psychologyDevelopmental psychologyNeurosciencePsychotherapistPolitical science

Abstract

fetched live from OpenAlex

Problematic social media use is a maladaptive and detrimental pattern of addictive behaviours towards social media. Although problematic social media use has been based upon framework characterizing behavioural addiction, it is currently not part of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Morphological abnormalities of the striatum have been found in behavioural addictions, however the neurobiological basis of problematic social media use has yet to be investigated. The present study aimed to investigate striatal volume and shape in association with problematic social media use and frequency of social media use. Higher levels of problematic social media use and increased frequency of use were not significantly related to the volume of the striatum. However, when examining the shape of the striatum, surface area deformations were significantly associated with higher problematic social media use. We call for continued research to further validate problematic social media use as a behavioural addiction.

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)0.001
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.055
GPT teacher head0.315
Teacher spread0.259 · 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
Published2022
Admission routes1
Has abstractyes

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