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Record W244103393 · doi:10.1089/cyber.2014.0407

Do It Yourself: Examination of Self-Injury First Aid Tips on YouTube

2015· article· en· W244103393 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

VenueCyberpsychology Behavior and Social Networking · 2015
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsOutreachContext (archaeology)The InternetPsychologyHuman factors and ergonomicsPoison controlSuicide preventionInjury preventionApplied psychologyMedicineComputer scienceMedical emergencyWorld Wide Web

Abstract

fetched live from OpenAlex

Individuals who engage in nonsuicidal self-injury (NSSI) may prefer the Internet as a medium to communicate about NSSI experiences and obtain NSSI information. Recent research suggests that NSSI first aid information is shared. Yet, no research has examined the context in which this information occurs. This study examined the nature and scope of NSSI first aid tips on YouTube using a content analysis to examine 40 NSSI first aid videos. Findings indicated that videos were viewed 157,571 total times; they were typically favorably viewed. Most had a neutral purpose and neither encouraged nor discouraged NSSI. Messages encouraging NSSI help seeking were scant. Similarly, medical help seeking was not commonly encouraged, with several videos providing "safe" NSSI instructions. Overall, videos with NSSI first aid information may contribute to NSSI reinforcement and the belief that professional and medical help may not be needed for NSSI. Findings have implications for research, clinical work, and e-outreach, which are discussed.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.386
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.087
GPT teacher head0.362
Teacher spread0.274 · 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