Googling Self-injury
Bibliographic record
Abstract
IMPORTANCE: Nonsuicidal self-injury (NSSI), the deliberate destruction of one's body tissue without suicidal intent, is a significant issue for many youth. Research suggests that adolescents and emerging adults prefer the Internet as a means to retrieve NSSI resources and that important others (eg, caregivers) may also seek this information online. To our knowledge, no research to date has examined the quality of health information regarding NSSI on the Internet. OBJECTIVES: To examine the scope and nature of web searches for NSSI websites and to evaluate the quality of health-information websites found via these online searches. DESIGN, SETTING, AND PARTICIPANTS: Ninety-two NSSI-related search terms were identified using the Google AdWords Keywords program. The first page of Google search results for each term was content-analyzed for website type and health-information websites were further coded for credibility, NSSI myth propagation, and quality of health information. MAIN OUTCOMES AND MEASURES: Frequency of NSSI web searches and indices of health information quality. RESULTS: Nonsuicidal self-injury-related search terms were sought more than 42 million times in the past year and health-information websites were the most common website type found (21.5%). Of these, a health and/or academic institution endorsed only 9.6%. At least one NSSI myth was propagated per website, including statements that NSSI indicates a mental disorder (49.3%), a history of abuse (40%), or the notion that primarily women self-injure (37%). The mean quality of health information score on these websites was 3.49 (SD = 1.40) of 7. CONCLUSIONS AND RELEVANCE: Nonsuicidal self-injury-related search terms are frequently sought out worldwide and are likely to yield noncredible and low-quality information that may propagate common NSSI myths. These data suggest health professionals need to be aware of what information is online and should refer young patients and their families to reliable online resources to enhance NSSI literacy. Efforts to facilitate people's access to credible NSSI resources via the Internet are also needed.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.121 | 0.026 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".