Browsing by Author "Hasking PA"

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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.
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    Who are we missing? Self-selection bias in nonsuicidal self-injury research.
    (John Wiley and Sons, Inc., 2023-10) Robinson K; Dayer KF; Mirichlis S; Hasking PA; Wilson MS
    BACKGROUND: Despite the threat of self-selection bias to the generalizability of research findings, remarkably little is known about who chooses to take part in non-suicidal self-injury (NSSI) research specifically. We aimed to establish the extent of willingness to take part in NSSI research within a commonly sampled population before assessing whether individual differences in demographic characteristics, NSSI lived experience, and participation experiences were associated with willingness to take part in future NSSI research. METHODS: New Zealand university students (nā€‰=ā€‰3098) completed self-report measures of their NSSI, psychological distress, emotional dysregulation, experience of their participation in the current study, and willingness to participate in future NSSI research. RESULTS: Most participants (78.2%) indicated that they were willing to take part in future NSSI research. Men, older participants, people with NSSI lived experience, and those with more frequent past-year NSSI were more likely to be willing to take part in future NSSI research. Participants who reported a more positive subjective experience of the current study also indicated greater willingness. CONCLUSIONS: Findings demonstrate systematic differences in who is willing to take part in NSSI research. Future research should implement methodological and statistical approaches to mitigate the impact of self-selection bias on NSSI research.