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Social media as an incubator of personality and behavioral psychopathology: Symptom and disorder authenticity or psychosomatic social contagion?

2022· letter· en· W4312204614 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueComprehensive Psychiatry · 2022
Typeletter
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsUniversity of CalgaryWestern UniversityCentre for Addiction and Mental HealthUniversity of Toronto
Fundersnot available
KeywordsPhenomenonPsychologyPsychopathologyPersonalityEmpirical researchSocial mediaNosologyMental healthPsychiatryClinical psychologySocial psychology

Abstract

fetched live from OpenAlex

There has been an increasing recognition among both medical and psychological professionals, as well as the public media, of a concerning trend for child and adolescent users of audiovisual-based, algorithmic social media platforms (e.g., TikTok) to present with or claim functional psychiatric impairment that is inconsistent with or distinct from classic psychiatric nosology. In this short communication, we provide a detailed historical overview of this transdiagnostic phenomenon and suggest a conceptual model to organize thinking and research examining it. We then discuss the implications of our suggested model for accurate assessment, diagnosis, and medical-psychiatric treatment. We believe there is an urgent need for focused empirical research investigation into this concerning phenomenon that is related to the broader research and discourse examining social media influences on mental health.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.692
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.064
GPT teacher head0.407
Teacher spread0.343 · 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