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Rates and predictors of suicidal ideation during the first year after traumatic brain injury

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  • Mackelprang, J.L.
  • Bombardier, C.H.
  • Fann, J.R.
  • Temkin, N.R.
  • Barber, J.K.
  • Dikmen, S.S.

Abstract

Objectives. We examined rates of suicidal ideation (SI) after traumatic brain injury (TBI) and investigated whether demographic characteristics, preinjury psychiatric history, or injury-related factors predicted SI during the first year after injury. Methods. We followed a cohort of 559 adult patients who were admitted to Harborview Medical Center in Seattle, Washington, with a complicated mild to severe TBI between June 2001 and March 2005. Participants completed structured telephone interviews during months 1 through 6, 8, 10, and 12 after injury. We assessed SI using item 9 of the Patient Health Questionnaire (PHQ-9). Results. Twenty-five percent of the sample reported SI during 1 or more assessment points. The strongest predictor of SI was the first PHQ-8 score (i.e., PHQ-9 with item 9 excluded) after injury. Other significant multivariate predictors included a history of a prior suicide attempt, a history of bipolar disorder, and having less than a high school education. Conclusions. Rates of SI among individuals who have sustained a TBI exceed those found among the general population. Increased knowledge of risk factors for SI may assist health care providers in identifying patients who may be vulnerable to SI after TBI.

Suggested Citation

  • Mackelprang, J.L. & Bombardier, C.H. & Fann, J.R. & Temkin, N.R. & Barber, J.K. & Dikmen, S.S., 2014. "Rates and predictors of suicidal ideation during the first year after traumatic brain injury," American Journal of Public Health, American Public Health Association, vol. 104(7), pages 100-107.
  • Handle: RePEc:aph:ajpbhl:10.2105/ajph.2013.301794_1
    DOI: 10.2105/AJPH.2013.301794
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    Cited by:

    1. Yu-Tang Shen & Kylie Radford & Gail Daylight & Robert Cumming & Tony G. A. Broe & Brian Draper, 2018. "Depression, Suicidal Behaviour, and Mental Disorders in Older Aboriginal Australians," IJERPH, MDPI, vol. 15(3), pages 1-14, March.
    2. Sunhae Kim & Hye-Kyung Lee & Kounseok Lee, 2021. "Which PHQ-9 Items Can Effectively Screen for Suicide? Machine Learning Approaches," IJERPH, MDPI, vol. 18(7), pages 1-10, March.

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