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Record W2173035384 · doi:10.1002/jclp.22242

A Double-Edged Sword: A Review of Benefits and Risks of Online Nonsuicidal Self-Injury Activities

2015· review· en· W2173035384 on OpenAlex
Stephen P. Lewis, Yukari Seko

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

VenueJournal of Clinical Psychology · 2015
Typereview
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsThematic analysisPsychologyContext (archaeology)Poison controlHuman factors and ergonomicsSuicide preventionInjury preventionSocial isolationOccupational safety and healthClinical psychologyApplied psychologyQualitative researchPsychotherapistMedicineMedical emergency

Abstract

fetched live from OpenAlex

OBJECTIVE: This review aimed to synthesize current evidence on the perceived benefits and risks of online activity pertinent to nonsuicidal self-injury (NSSI). METHOD: A systematic literature search was conducted to identify peer-reviewed articles, which yielded a total of 27 articles published between 2005 and 2015. Following this, a thematic analysis was employed to identify perceived benefits and risks of online NSSI activity. RESULTS: Our thematic analysis identified 4 potential benefits (mitigation of social isolation, recovery encouragement, emotional self-disclosure, curbing NSSI urges) and 3 potential risks (NSSI reinforcement, triggering NSSI urges, stigmatization of NSSI) associated with online NSSI activities. CONCLUSION: Given the double-edged effect of online NSSI activities, clinicians may benefit from incorporating clients' online NSSI activity in the context of NSSI assessment and treatment. Future research ought to directly examine the link between online NSSI activity and NSSI behavior to better understand the nature of these benefits and risks.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.931
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0100.002
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
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 head0.537
GPT teacher head0.614
Teacher spread0.077 · 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