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Non-suicidal self-injury (NSSI) is associated with mental disorders, yet work regarding the direction of this association is inconsistent. We examined the prevalence, comorbidity, time–order associations with mental disorders, and sex differences in sporadic and repetitive NSSI among emerging adults.
Methods
We used survey data from n = 72,288 first-year college students as part of the World Mental Health-International College Student Survey Initiative (WMH-ICS) to explore time–order associations between onset of NSSI and mental disorders, based on retrospective age-of-onset reports using discrete-time survival models. We distinguished between sporadic (1–5 lifetime episodes) and repetitive (≥6 lifetime episodes) NSSI in relation to DSM-5 mood, anxiety, and externalizing disorders.
Results
We estimated a lifetime NSSI rate of 24.5%, with approximately half reporting sporadic NSSI and half repetitive NSSI. The time–order associations between onset of NSSI and mental disorders were bidirectional, but mental disorders were stronger predictors of the onset of NSSI (median RR = 1.94) than vice versa (median RR = 1.58). These associations were stronger among individuals engaging in repetitive rather than sporadic NSSI. While associations between NSSI and mental disorders generally did not differ by sex, repetitive NSSI was a stronger predictor for the onset of subsequent substance use disorders among females compared to males. Most mental disorders marginally increased the risk for persistent repetitive NSSI (median RR = 1.23).
Conclusions
Our findings offer unique insights into the temporal order between NSSI and mental disorders. Further work exploring the mechanism underlying these associations will pave the way for early identification and intervention of both NSSI and mental disorders.
Although it is clear that i-frame approaches cannot stand alone, the impact of s-frame changes can plateau. Combinations of these approaches may best reflect what we know about behavior and how to support behavioral change. Interactions between i-frame and s-frame thinking are explored here using two examples: alcohol consumption and meat consumption.
Brief interventions can be efficacious in changing alcohol consumption and increasingly take advantage of the internet to reach high-risk populations such as students.
Aims
To evaluate the effectiveness of a brief online intervention, controlling for the possible effects of the research process.
Method
A three-arm parallel groups design was used to explore the magnitude of the feedback and assessment component effects. The three groups were: alcohol assessment and feedback (group 1); alcohol assessment only without feedback (group 2); and no contact, and thus neither assessment nor feedback (group 3). Outcomes were evaluated after 3 months via an invitation to participate in a brief cross-sectional lifestyle survey. The study was undertaken in two universities randomising the email addresses of all 14910 students (the AMADEUS-1 study, trial registration: ISRCTN28328154).
Results
Overall, 52% (n = 7809) of students completed follow-up, with small differences in attrition between the three groups. For each of the two primary outcomes, there was one statistically significant difference between groups, with group 1 having 3.7% fewer risky drinkers at follow-up than group 3 (P = 0.006) and group 2 scoring 0.16 points lower than group 3 on the three alcohol consumption questions from the Alcohol Use Disorders Identification Test (AUDIT-C) (P = 0.039).
Conclusions
This study provides some evidence of population-level benefit attained through intervening with individual students.
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