Journal Articles

Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915

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    The associations of childhood adversities and mental disorders with suicidal thoughts and behaviors - Results from the World Mental Health International College Student Initiative
    (Elsevier B V, 2025-08-01) Mortier P; Yang X; Altwaijri YA; Holdcraft JA; Lee S; Sampson NA; Albor Y; Alhadi AN; Alonso J; Al-Saud NK; Andersson C; Atwoli L; Auerbach RP; Muaka CA; Báez-Mansur PM; Ballester L; Bantjes J; Baumeister H; Bendtsen M; Benjet C; Berman AH; Bruffaerts R; Carrasco P; Chan SCN; Cohut I; Covarrubias Díaz Couder MA; Crockett MA; Cuijpers P; David OA; Dong D; Ebert DD; Gaete J; Felez-Nobrega M; García Forero C; Gili M; Gutiérrez-García RA; Haro JM; Hasking P; Hunt X; Husky MM; Jaguga F; Jansen L; Langer ÁI; Liu Y; Mac-Ginty S; Martínez V; Mason A; Mathai M; McLafferty M; Miranda-Mendizabal A; Murray EK; Musyoka CM; O'Neill SM; Papasteri CC; Piqueras JA; Popescu CA; Rapsey C; Robinson K; Rodriguez-Jimenez T; Scarf D; Siu O-L; Stein DJ; Struijs SY; Tomoiaga CT; Valdés-García KP; Vereecke S; Vigo DV; Wang AY; Wong SYS; Kessler RC; World Mental Health International College Student collaborators
    Objective: To investigate the associations of demographic variables, childhood adversities (CAs), and mental disorders (MDx) with onset, transition, and persistence of suicidal thoughts and behaviors (STB) among first-year university students. Method: Poisson regression models within a discrete-time survival framework were constructed using web-based self-report survey data from 72,288 incoming university students across 18 countries (response rate=20.9%; median age=19 years, 57.9% female, 1.4% transgender, 21.0% non-heterosexual). These models examined the associations of four demographic variables, five CAs, and eight MDx with STB outcomes. Results: Lifetime prevalence of suicidal ideation, plans, and attempts was 47.0%, 26.0%, and 9.6%, respectively; 12-month estimates were 30.6%, 14.0%, and 2.3%. In unadjusted analyses, associations were strongest between lifetime onset of suicidal ideation and CAs (RR range 4.4–7.0), particularly parental psychopathology (relative risk [RR]=7.0 [95% CI 6.5–7.7]), followed by MDx (RR range 1.3–3.0). Of the demographic subgroups, transgender students had highest risk of STB (lifetime ideation onset RR=2.4 [2.3–2.6]; ideation-to-attempt transition RR=1.5 [1.3–1.8]). In fully adjusted models, strongest predictors of lifetime ideation onset were emotional abuse (RR=2.1 [1.9–2.2]), major depressive disorder (RR=2.0 [1.9–2.1]), and bipolar disorder (RR=1.8 [1.6–2.0]). Ideation-to-attempt transition remained most strongly associated with panic disorder (RR=1.5 [1.3–1.7]), bipolar disorder (RR=1.4 [1.2–1.7]), and sexual abuse (RR=1.4 [1.2–1.7]). Most predictors were significantly but weakly associated with persistence of ideation and plan, while only physical abuse remained associated with repeated suicide attempts (RR=1.3 [1.0–1.8]). Conclusion: CAs and MDx are strong predictors of both onset of and transition within the STB spectrum, underscoring the importance of implementing early-life prevention interventions.
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    Development and evaluation of a predictive algorithm and telehealth intervention to reduce suicidal behavior among university students.
    (Cambridge University Press, 2024-04-01) Hasking PA; Robinson K; McEvoy P; Melvin G; Bruffaerts R; Boyes ME; Auerbach RP; Hendrie D; Nock MK; Preece DA; Rees C; Kessler RC
    BACKGROUND: Suicidal behaviors are prevalent among college students; however, students remain reluctant to seek support. We developed a predictive algorithm to identify students at risk of suicidal behavior and used telehealth to reduce subsequent risk. METHODS: Data come from several waves of a prospective cohort study (2016-2022) of college students (n = 5454). All first-year students were invited to participate as volunteers. (Response rates range: 16.00-19.93%). A stepped-care approach was implemented: (i) all students received a comprehensive list of services; (ii) those reporting past 12-month suicidal ideation were directed to a safety planning application; (iii) those identified as high risk of suicidal behavior by the algorithm or reporting 12-month suicide attempt were contacted via telephone within 24-h of survey completion. Intervention focused on support/safety-planning, and referral to services for this high-risk group. RESULTS: 5454 students ranging in age from 17-36 (s.d. = 5.346) participated; 65% female. The algorithm identified 77% of students reporting subsequent suicidal behavior in the top 15% of predicted probabilities (Sensitivity = 26.26 [95% CI 17.93-36.07]; Specificity = 97.46 [95% CI 96.21-98.38], PPV = 53.06 [95% CI 40.16-65.56]; AUC range: 0.895 [95% CIs 0.872-0.917] to 0.966 [95% CIs 0.939-0.994]). High-risk students in the Intervention Cohort showed a 41.7% reduction in probability of suicidal behavior at 12-month follow-up compared to high-risk students in the Control Cohort. CONCLUSIONS: Predictive risk algorithms embedded into universal screening, coupled with telehealth intervention, offer significant potential as a suicide prevention approach for students.