A Systematic Review of the Prospective Relationship Between Bullying Victimization and Pain
Bibliographic record
Abstract
OBJECTIVE: This systematic review synthesized evidence about the relationship between childhood bullying victimization and chronic pain, with a focus on the temporal nature of the relationship and moderating factors, such as the type and intensity of victimization. METHOD: We included prospective cohort studies that examined the relationship between childhood bullying victimization and pain measured at least three months later. We conducted electronic searches of Medline, EMBASE, PsycINFO, and CINAHL up to June 30, 2019. Standard methodological procedures consistent with Cochrane reviews of prognosis studies were used (PROSPERO record ID 133146). RESULTS: We included four longitudinal studies (6275 participants) in this review. The mean age of participants at baseline ranged from 10 to 14 years and the follow-up periods ranged from 6 months to 12 years. Two of the four studies were judged as having high risk of bias. Meta-analysis of results from four studies revealed increased risk of pain among victimized compared to non-victimized youth (adjusted OR [95% CI] = 1.45 [1.06-1.97], but the effect size was small and not clinically important. Only one study examined the inverse association (ie, from pain to victimization), and there was not enough evidence to conduct a meaningful analysis of the proposed moderators. CONCLUSIONS: Study findings were limited by few prospective studies. Meta-analytic findings suggested that victimization may incur some risk for later pain, although the evidence was judged to be very low quality. High-quality studies that measure and report the nuances of bullying victimization are needed to test the proposed moderator models.
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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 | 0.017 | 0.080 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.010 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".