Perceived parental support in childhood and adolescence as a tool for mental health screening in students: A longitudinal study in the i-Share cohort

Macalli, Mélissa; Côté, Sylvana M.; Tzourio, Christophe

doi:10.1016/j.jad.2020.02.009

Cited by 36 publications

(36 citation statements)

References 49 publications

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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

Self Cite

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: 78%

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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“…Studies have shown that parental support and a positive familial relationship in childhood have positive long-term effects on adult mental health and provide a crucial foundation for social interactions [ 33 , 34 ]. Thus, parental maltreatment in childhood increases the likelihood that a child will be victimized by peers, due to the child’s impaired emotional regulation skills [ 35 ].…”

Section: Discussionmentioning

confidence: 99%

Contributions of childhood peer victimization and/or maltreatment to young adult anxiety, depression, and suicidality: a cross-sectional study

et al. 2021

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Background Childhood maltreatment and peer victimization are major risk factors for depression and suicidal behavior. Furthermore, childhood maltreatment increases the risk of peer victimization. Our objective was to distinguish between the contributions of parental maltreatment and peer victimization to the development of mental health problems in young adulthood. Specifically, we tested whether peer victimization alone or in combination with parental maltreatment before 18 years old was associated with anxiety, depression, and suicidal thoughts and behaviors at age 21 years. Methods We analyzed data collected from questionnaires administered in the i-Share (Internet-based Students’ Health ResearchEnterprise) study in France from February 2013 to September 2019 (N = 2271 participants). We performed multinomial and binary logistic regression analyses to assess the single and combined contributions of childhood peer victimization and parental maltreatment to anxiety, depression, and suicidality in adulthood. Results Nearly one third of students (28.8%) reported at least one mental health problem; 29.8% reported peer victimization alone; 7.5% reported parental maltreatment alone; and 10.3% reported both parental maltreatment and victimization. In multivariate models, compared to participants that did not experience maltreatment or peer victimization, those that experienced peer victimization alone were more likely to report anxiety (adjusted odds ratio [aOR]: 1.90; 95% CI: 1.50–2.40), depression (aOR: 1.95; 95% CI: 1.46–2.60), or suicidal ideation, without (aOR: 1.62; 95% CI: 1.26–2.09) or with a suicide attempt (aOR: 2.70; 95% CI: 1.51–4.85). Similar associations were observed for participants that experienced maltreatment alone. Participants that experienced both maltreatment and peer victimization were at increased risk of depression (aOR: 2.63; 95% CI: 1.79–3.86) and suicidal ideation, with (aOR: 9.19; 95% CI: 4.98–16.92) and without a suicide attempt (aOR: 2.64; 95% CI: 1.86–3.76). Conclusions Separate and combined exposures to parental maltreatment and peer victimization in childhood or adolescence were associated with increased risks of anxiety, depression, and suicidal behaviors. Peer victimization appeared to play a specific role in mental health disorders that were not otherwise explained by polyvictimization. Currently, peer victimization is a frequent, but avoidable type of child abuse; therefore, these findings have implications for policies for preventing and dealing with peer victimization.

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Perceived parental support in childhood and adolescence as a tool for mental health screening in students: A longitudinal study in the i-Share cohort

Cited by 36 publications

References 49 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

Contributions of childhood peer victimization and/or maltreatment to young adult anxiety, depression, and suicidality: a cross-sectional study

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