Elsevier

Journal of Psychiatric Research

Volume 95, December 2017, Pages 253-259
Journal of Psychiatric Research

Suicidal ideation and behavior in institutions of higher learning: A latent class analysis

https://doi.org/10.1016/j.jpsychires.2017.09.003Get rights and content

Abstract

Suicide is the second leading cause of death among undergraduate students, with an annual rate of 7.5 per 100,000. Suicidal behavior (SB) is complex and heterogeneous, which might be explained by there being multiple etiologies of SB. Data-driven identification of distinct at-risk subgroups among undergraduates would bolster this argument. We conducted a latent class analysis (LCA) on survey data from a large convenience sample of undergraduates to identify subgroups, and validated the resulting latent class model on a sample of graduate students. Data were collected through the Interactive Screening Program deployed by the American Foundation for Suicide Prevention. LCA identified 6 subgroups from the undergraduate sample (N = 5654). In the group with the most students reporting current suicidal thoughts (N = 623, 66% suicidal), 22.5% reported a prior suicide attempt, and 97.6% endorsed moderately severe or worse depressive symptoms. Notably, LCA identified a second at-risk group (N = 662, 27% suicidal), in which only 1.5% of respondents noted moderately severe or worse depressive symptoms. When graduate students (N = 1138) were classified using the model, a similar frequency distribution of groups was found. Finding multiple replicable groups at-risk for suicidal behavior, each with a distinct prevalence of risk factors, including a group of students who would not be classified as high risk with depression-based screening, is consistent with previous studies that identified multiple potential etiologies of SB.

Introduction

Suicide is the second leading cause of death for college students, with an estimated overall annual suicide rate of 7.5 per 100,000 (Drum et al., 2009, Silverman et al., 1997). The highest suicide rates are among students over age 25 and those enrolled in graduate school (Silverman et al., 1997). Factors associated with increased risk for suicidal behavior among young people include history of suicide attempt, depression, and substance use (D'Eramo et al., 2004, Dvorak et al., 2013, Esposito-Smythers and Spirito, 2004, Fowler et al., 1986, Garlow, 2002, Gonzalez, 2012, Nemeroff et al., 2001). Other risk factors include adverse life events, contact with legal authorities, family history of mental illness, family history of suicide, and history of sexual abuse (Agerbo et al., 2002, Cooper et al., 2002, Gray et al., 2002, Juon and Ensminger, 1997).

Mood, anxiety, and substance use disorders commonly emerge during late adolescence and early adulthood (Kessler et al., 2005). Among college students, the difficulties of age-related transitions are further exacerbated by social, academic, and professional stressors (Ross et al., 1999). A 2015 survey found that one in three college students reported “feeling so depressed that it was difficult to function,” and one in 10 said they had “seriously considered attempting suicide” in the last 12 months (American College Health Association, 2015). Alarmingly, results from a screening project at one university found that only 14.5% of moderately severe or severely depressed students were receiving mental health treatment (Garlow et al., 2008).

The American Foundation for Suicide Prevention (AFSP) developed the Interactive Screening Program (ISP) to support institutions of higher learning in engaging at-risk students in mental healthcare. Implemented by each school's counseling center, the ISP provides screening, personalized feedback, and recommendations for next steps entirely online. The program offers students concerned about stigma and confidentially—common barriers to accessing services—an anonymous way to obtain information and support (Haas et al., 2008).

Latent class analysis (LCA), related to cluster analysis, can be used to discover groups of similar cases in multivariate categorical data. In the suicide risk literature, LCA has been used to identify precipitants for suicidal thoughts among adolescents of various ethnic and racial backgrounds (De Luca et al., 2014, Stoep et al., 2009); to predict suicidal behavior (Thompson et al., 2009); to recognize patterns in known risk factors for suicide among suicide decedents (Judd et al., 2012, Kim et al., 2003, Logan et al., 2011); to identify psychiatric disorder subtypes that might be more strongly associated with suicidal thoughts or behaviors (Li et al., 2014, Pan et al., 2014); and to explore interactions among suicide risk factors (Pena et al., 2012).

We used LCA to identify subgroups of at-risk students using data collected via the ISP. Since suicidal behavior is complex and heterogeneous, there are likely multiple subtypes of suicidal behavior, and risk factors can differ across subtypes (Conner et al., 2007, Dombrovski et al., 2013, Mann et al., 2009). Data-driven identification of distinct at-risk groups in this sample would further bolster this argument. Characterization of these groups might propel a deeper understanding of suicidal behavior subtypes and their respective etiologies.

Section snippets

Data collection and measures

The ISP was implemented at a diverse set of United States institutions of higher learning over a 12-year period (2002–2014). The 45 schools varied in size (ranging from approximately 900 to 65,000 students), were from all major geographic regions, varied by urban or rural location, and educational environment. Each institution selected which students to invite to the ISP. Emails were sent from designated officials in batches at each school to the selected students’ school email addresses. The

Results

The median age was 20 for undergraduate and 26 for graduate students. Respondents identifying as women comprised the majority of both samples. The prevalence of moderately severe or severe depression was 23.7% in undergraduate and 15.0% in graduate students; 14.3% and 10.0% endorsed recent thoughts of suicide, with 7.1% and 4.9% indicating they had made at least one prior suicide attempt, respectively. Accounting for age and clustering by school, there were no statistically significant

Discussion

In this study, we identified subgroups of at-risk undergraduate and graduate students using LCA. The prevalence of depression and thoughts of suicide in the undergraduate sample was similar to a previous AFSP screening survey deployed at a single institution, though a smaller percentage in this sample reported a previous suicide attempt (Garlow et al., 2008). Other studies have found similar rates of thoughts of suicide but lower rates of depression (Mackenzie et al., 2011). One large national

Funding

This work is funded by the American Foundation for Suicide Prevention and the National Institute of Mental Health (P50 MH090964, R01MH109326).

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