Association of Childhood Maltreatment With Suicide Behaviors Among Young People

Angelakis, Ioannis; Austin, John; Gooding, Patricia

doi:10.1001/jamanetworkopen.2020.12563

Cited by 160 publications

(90 citation statements)

References 130 publications

(580 reference statements)

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“…20 STB prediction was not in uenced by childhood trauma or perceived parental support, which are usually strongly associated with STB in young adults. 21,22 These results are in line with previous studies. 20,23 This nding highlights that association doesn't necessarily means prediction, 11 and that proximal risk factors of STB may be better than distal one for predicting one-year STB.…”

Section: Discussionsupporting

confidence: 93%

Predicting suicidal thoughts and behaviors among college students: a machine learning approach

Macalli

Navarro

Orri

et al. 2021

Preprint

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Suicidal thoughts and behaviors are prevalent among college students. Yet little is known about screening tools to identify students at higher risk. We aimed to develop a risk algorithm to identify the main predictors of suicidal thoughts and behaviors among college students within one-year of baseline assessment. We used data collected in 2013–2019 from the French i-Share cohort, a longitudinal population-based study including 5066 volunteer students. To predict suicidal thoughts and behaviours at follow-up, we used random forests models with 70 potential predictors measured at baseline, including sociodemographic and familial characteristics, mental health and substance use. Model performance was measured using the area under the receiver operating curve (AUC), sensitivity, and positive predictive value. At follow-up, 17.4% of girls and 16.8% of boys reported suicidal thoughts and behaviors. The models achieved good predictive performance: AUC, 0.8; sensitivity, 79% for girls, 81% for boys; and positive predictive value, 40% for girls and 36% for boys. Among the 70 potential predictors, four showed the highest predictive power: 12-month suicidal thoughts, trait anxiety, depression symptoms, and self-esteem. We identified a parsimonious set of mental health indicators that accurately predicted one-year suicidal thoughts and behaviors in a community sample of college students.

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Section: Discussionsupporting

confidence: 93%

Predicting suicidal thoughts and behaviors among college students: a machine learning approach

Macalli

Navarro

Orri

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…STB prediction was not influenced by childhood trauma or perceived parental support, which are usually strongly associated with STB in young adults 35 , 36 . These results are in line with previous studies 34 , 37 .…”

Section: Discussionmentioning

confidence: 79%

A machine learning approach for predicting suicidal thoughts and behaviours among college students

Macalli

Navarro

Orri

et al. 2021

Sci Rep

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Suicidal thoughts and behaviours are prevalent among college students. Yet little is known about screening tools to identify students at higher risk. We aimed to develop a risk algorithm to identify the main predictors of suicidal thoughts and behaviours among college students within one-year of baseline assessment. We used data collected in 2013–2019 from the French i-Share cohort, a longitudinal population-based study including 5066 volunteer students. To predict suicidal thoughts and behaviours at follow-up, we used random forests models with 70 potential predictors measured at baseline, including sociodemographic and familial characteristics, mental health and substance use. Model performance was measured using the area under the receiver operating curve (AUC), sensitivity, and positive predictive value. At follow-up, 17.4% of girls and 16.8% of boys reported suicidal thoughts and behaviours. The models achieved good predictive performance: AUC, 0.8; sensitivity, 79% for girls, 81% for boys; and positive predictive value, 40% for girls and 36% for boys. Among the 70 potential predictors, four showed the highest predictive power: 12-month suicidal thoughts, trait anxiety, depression symptoms, and self-esteem. We identified a parsimonious set of mental health indicators that accurately predicted one-year suicidal thoughts and behaviours in a community sample of college students.

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“…Previous studies have reported association between abuse and suicidal behaviours in individuals with or without depression [15][16][17][18]. Meta-analyses of adults and young people report that sexual abuse and physical abuse are associated with two-to three-fold increased risk for suicide attempts [19,20]. There are fewer studies of associations between sexual/physical abuse and other depressive symptoms.…”

Section: Introductionmentioning

confidence: 99%

Sexual and physical abuse and depressive symptoms in the UK Biobank

2021

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Background The association between sexual and physical abuse and subsequent depression is well-established, but the associations with specific depressive symptoms and sex differences remain relatively understudied. We investigated the associations of sexual and physical abuse with depressive symptoms in men and women in a large population cohort. Methods Observational study based on 151,396 UK Biobank participants. Exposures included self-reported experiences of childhood physical abuse and sexual abuse. Mid-life outcomes included current depressive symptoms score, individual depressive symptoms, and lifetime depression. We used logistic regression to test associations of childhood sexual/physical abuse with depressive outcomes. Results Recalled childhood sexual and physical abuse were both associated with current depressive symptoms score in adults. Results for individual symptoms-based analyses suggest that sexual and physical abuse are associated with all depressive symptoms, particularly suicidal behaviours. The associations between lifetime depression and sexual/physical abuse were not fully explained by current depressive symptoms score, indicating that these findings may not be fully attributable to recall bias. There was no indication of differential risk for specific depressive symptoms among men and women. Conclusions Sexual and physical abuse are robust risk factors for depression/depressive symptoms regardless of sex. Higher risk of suicidal behaviours associated with childhood sexual/physical abuse are of particular concern. Longitudinal research into sex-specific associations for individual depressive symptoms is required.

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Association of Childhood Maltreatment With Suicide Behaviors Among Young People

Abstract: This systematic review and meta-analysis assesses the association between experiences of childhood maltreatment and suicide behaviors in children and young adults.

Cited by 160 publications

References 130 publications

Predicting suicidal thoughts and behaviors among college students: a machine learning approach

Predicting suicidal thoughts and behaviors among college students: a machine learning approach

A machine learning approach for predicting suicidal thoughts and behaviours among college students

Sexual and physical abuse and depressive symptoms in the UK Biobank

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