How cyberbullying victimization relates to suicide risk: Evidence of feature-based heterogeneity from double machine learning.

Liu X, Liao Y, Feng F, Tu Y, Kang X, Ren Z, Liu M

DOI: 10.1017/s0033291726106229
Published: 2026 Nov 3
Container: Psychological medicine
Publisher: Not recorded
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1017/s0033291726106229,
  title = {How cyberbullying victimization relates to suicide risk: Evidence of feature-based heterogeneity from double machine learning.},
  author = {Liu X and Liao Y and Feng F and Tu Y and Kang X and Ren Z and Liu M},
  year = {2026},
  journal = {Psychological medicine},
  doi = {10.1017/s0033291726106229},
  url = {https://doi.org/10.1017/s0033291726106229}
}

RIS

TY  - JOUR
TI  - How cyberbullying victimization relates to suicide risk: Evidence of feature-based heterogeneity from double machine learning.
AU  - Liu X
AU  - Liao Y
AU  - Feng F
AU  - Tu Y
AU  - Kang X
AU  - Ren Z
AU  - Liu M
PY  - 2026
JO  - Psychological medicine
DO  - 10.1017/s0033291726106229
UR  - https://doi.org/10.1017/s0033291726106229
ER  -

APA

X, L., Y, L., F, F., Y, T., X, K., Z, R., & M, L. (2026). How cyberbullying victimization relates to suicide risk: Evidence of feature-based heterogeneity from double machine learning.. Psychological medicine. https://doi.org/10.1017/s0033291726106229

Source records

pubmed · retrieved 2026-11-10T13:17:10.597Z