Internet Addiction and Its Relationship With Suicidal Behaviors
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.
Bibliographic record
Abstract
OBJECTIVE: To perform a systematic review and meta-analysis of observational studies that investigated the putative association between internet addiction and suicidality. DATA SOURCES: Major electronic databases (PubMed, Embase, ClinicalKey, Cochrane Library, ProQuest, Science Direct, and ClinicalTrials.gov) were searched using the following keywords (internet addiction OR internet gaming disorder OR internet use disorder OR pathological internet use OR compulsive internet use OR problematic internet use) AND (suicide OR depression) to identify observational studies from inception to October 31, 2017. STUDY SELECTION: We included 23 cross-sectional studies (n = 270,596) and 2 prospective studies (n = 1,180) that investigated the relationship between suicide and internet addiction. DATA EXTRACTION: We extracted the rates of suicidal ideation, planning, and attempts in individuals with internet addiction and controls. RESULTS: The individuals with internet addiction had significantly higher rates of suicidal ideation (odds ratio [OR] = 2.952), planning (OR = 3.172), and attempts (OR = 2.811) and higher severity of suicidal ideation (Hedges g = 0.723). When restricted to adjusted ORs for demographic data and depression, the odds of suicidal ideation and attempts were still significantly higher in the individuals with internet addiction (ideation: pooled adjusted OR = 1.490; attempts: pooled adjusted OR = 1.559). In subgroup analysis, there was a significantly higher prevalence rate of suicidal ideation in children (age less than 18 years) than in adults (OR = 3.771 and OR = 1.955, respectively). CONCLUSIONS: This meta-analysis provides evidence that internet addiction is associated with increased suicidality even after adjusting for potential confounding variables including depression. However, the evidence was derived mostly from cross-sectional studies. Future prospective studies are necessary to confirm these findings.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it