Suicide is one of only three leading causes of death in the United States that continues to increase (Stone et al., 2018). In 2016, World Health Organization statistics estimated that nearly 45,000 suicides (123 suicides per day) occurred in the U.S. among people aged 18 and older. Among the U.S. military, suicide rates of active duty service members now surpass rates within the general population (U.S. Department of Veterans Affairs, 2016). In addition, from 1999 to 2015 deaths by suicide increased among all racial/ethnic groups, both sexes, and all age groups of those under the age of 75 (Stone et al., 2018). Despite a slew of new initiatives that have been recently implemented by various government and non-government agencies to prevent deaths by suicide, suicide in the U.S. remains a national public health concern.
Trauma is a well-documented risk factor for suicidal thoughts and behaviors (LeBouthillier, McMillan, Thibodeau, & Asmundson, 2015). A diagnosis of posttraumatic stress disorder (PTSD) is one of the strongest predictors of both recent and lifetime suicide attempts, with a comorbid diagnosis of depression and PTSD further amplifying the risk for suicide (Bryan, 2016). Research also indicates that individuals diagnosed with PTSD who, at some point, experience suicidal ideation (SI) have an increased likelihood of transitioning to a suicide attempt compared to those who are diagnosed with other psychiatric disorders (Nock et al., 2009). Therefore, providers who treat clients with a trauma history and/or those diagnosed with PTSD are urged to continually monitor and assess for SI using well-validated assessment measures.
PTSD often includes somatic problems that motivate patients to seek treatment in either primary care or emergency department (ED) settings (Greene, Neria, & Gross, 2016; Onoye et al., 2013). Given this, one place that mental health clinicians may be able to successfully identify and intervene for those most at risk for suicide is in EDs. From 2001 to 2016, rates of ED visits for nonfatal self-harm, a primary risk factor for suicide, increased by 42% (Stone et al., 2018). In addition, it was estimated that as many as one in ten individuals who died by suicide had been seen in an ED during the prior two months (Bowers et al., 2018). This observation highlights EDs as a crucial setting for suicide assessment and prevention. As ED psychiatric services are frequently required to assess a high number of patients and provide a clinical opinion about their future risk for suicide, the need for reliable and valid suicide assessment protocols is critical.
Risk Factors Associated with Suicide Assessment Instruments
Identifying standardized instruments that can reliably and validly assess suicidal behavior has been a focus of research for decades (Cochrane-Brink, Lofchy, & Sakinofsky, 2000; Cull & Gill, 1988; Jobes & Drozd, 2004; Russ, Kashdan, Pollack, & Bajmakovic-Kacila, 1999; Yufit & Lester, 2005). A recent systematic review suggests that researchers developing these instruments have typically focused on identifying and validating risk factors and sets of suicidal predictors in order to assess a person’s risk of suicide (Runeson et al., 2017). These risk factors have been reported to cluster into two domains: socio-demographic factors and clinical factors (Bisconer & Gross, 2007; Large et al., 2011). Some of these factors include: a history of deliberate self-harm, hopelessness, male gender, substance use, unemployment, feelings of guilt or inadequacy, social isolation, depressed mood, a family history of suicide, and a diagnosis of bipolar disorder or schizophrenia (Cull & Gill, 1988; Large et al., 2011; Links & Hoffman, 2005; Ruiz, 2001; Russ et al., 1999; Stack & Wasserman, 2005).
Researchers have identified clients seen in inpatient settings as a subpopulation that presents with slightly different risk factors for suicide compared to those who are seen in outpatient clinical settings (Large et al., 2011). A history of a suicide attempts was the strongest predictor of death by suicide among inpatients. Moderate predictors include depressed mood, a family history of suicide, being prescribed an antidepressant medication, a diagnosis of schizophrenia, and feelings of hopelessness, worthlessness, inadequacy, or guilt (Large et al., 2011). Interestingly, weak predictors for in-patient suicide included a higher number of previous psychiatric admissions and a suicide attempt at the time of admission (Large et al., 2011). Additionally, this meta-analysis identified no demographic factor as significantly associated with inpatient suicide (Large et al., 2011). Moreover, physical illness, co-morbid substance abuse, the presence of hallucinations, delusional beliefs, or treatment with antipsychotic medication were also not significantly associated with suicide for patients receiving inpatient care (Large et al., 2011).
These research findings underscore the difficulty of relying on a singular assessment tool to detect all of the varied risk factors when determining suicide risk. Although, these research findings suggest that specific socio-demographic factors and clinical factors contribute to an individual’s risk for suicide, setting also influences an individual’s potential risk. It is clear that each of these factors must be thoroughly considered when designing, selecting, and utilizing an assessment tool that will help a clinician predict an individual’s risk of suicide.
Selection of an Assessment Instrument
Ideally, each high-risk patient seen in a hospital setting should be assessed with a clinical interview in addition to a measure that can reliably and validly detect factors that may place them at an increased risk for suicide. Overall, current research is clear that assessment instruments should never be a substitute for a clinical interview, as interviews can address multiple areas of a patient’s life that may be contributing to their increased risk for suicide (Links & Hoffman, 2005; Podlogar et al., 2016; Stone et al., 2018). Assessments should be used to augment a clinical interview and the results should be used to inform the clinician’s decision to hospitalize or discharge the patient. Some of the most widely accepted instruments used to detect risk of suicide include the Beck Anxiety Inventory (BAI; Beck & Steer, 1993a), the Suicide Probability Scale (SPS; Cull & Gill, 1988), the Adult Suicidal Ideation Questionnaire (ASIQ; Reynolds, 1991), the Patient Health Questionnaire (PHQ-9; Kroenke, Spitzer, & Williams, 2001), the Beck Scale for Suicide Ideation (BSS; Beck & Steer, 1993c), the Beck Hopelessness Scale (BHS; Beck & Steer, 1993b), and the Beck Depression Inventory II (BDI-II; Beck, Steer, & Brown, 1996).
Research at a psychiatric hospital evaluated the ability of the SPS, ASIQ, BSS, BHS, BDI-II, and the BAI to distinguish between patients who were admitted for suicidal behavior and patients admitted for other reasons (Bisconer & Gross, 2007). Results indicated that the BAI, BHS, and BSS, while face valid for suicidal behaviors, did not perform as well as the SPS, ASIQ, and BDI-II. Additionally, while the SPS and ASIQ were specifically designed to assess suicide behaviors, results suggested that the BDI-II was the overall best predictor of suicide risk compared to the SPS and ASIQ (Bisconer & Gross, 2007).
In addition, Baryshnikov et al. (2018) used the BDI, BHS, and the BAI to identify which scale best detected risk for suicide by inpatients in context with the patient’s personality characteristics as measured by the BIG-5 Inventory (McCrae & John, 1992). Results of their study revealed that suicidal inpatients with high levels of neuroticism and extroversion were best identified using the BHS (Baryshnikov et al., 2018), Moreover, having a low level of perceived social support increased the predictive validity of the BHS with these patients, helping to explain both state and trait variations of hopelessness as it relates to risk for suicide (Baryshnikov et al., 2018). These results suggest that an individual’s personality traits also influence the usefulness of a suicide risk assessment measure.
The PTSD and Suicide Screener (PSS; Briere, 2013) is a less known, 14-item self-report measure that is designed to quickly screen for PTSD and suicide risk. This screener contains two scales: the PTSD Risk (PR) and the Suicide Risk (SR). The SR contains four items that assess for suicide risk. The PSS is effective as a quick indication that a patient may be experiencing SI. However, its limitations include the nuanced ways that SI is experienced among individuals, which may not be fully captured in fourteen questions.
Results of these studies highlight a major limitation of existing assessment measures; relying on single-construct measures such as PTSD, depression, hopelessness, historical factors, or level of overt suicidal intent to determine an individual’s risk of suicide (Hawes, Yaseen, Briggs, & Galynker, 2017). It is evident that single-construct assessment measures are not able to adequately capture all of the nuanced ways that setting, sociodemographic, cultural, and personality characteristics influence a person’s risk for suicide. This may also help to explain why, to date, there is no singular assessment instrument that demonstrates predictive validity for death by suicide (Runeson et al., 2017). An additional limitation of using a single construct assessment measures is missing data. Research shows that when participants skip suicide risk screening items it does not occur completely at random (Podlogar et al., 2016). Selective nondisclosure by inpatients can be intentional and is likely to predict a subpopulation of respondents who have some level of elevated risk, based on the information they do not endorse (Podlogar et al., 2016). Missing data could lead a psychologist to mistakenly discharge an inpatient if they do not identify and address the specific items that the patient skipped.
In general, these limitations highlight the need for hospitals to use suicide risk protocols that encompass multiple assessment instruments in order to capture all of the unique factors that could contribute to a patient’s increased risk for suicide.
Future Directions for Risk of Suicide Assessment Instruments
To address the lack of multi-factor assessment instruments, recent suicide risk assessments have turned to a multi-informant approach for assessing a patient’s risk for suicide. The Modular Assessment of Risk for Imminent Suicide (MARIS) was developed to assess a patient’s short-term suicide risk following hospital discharge (Hawes et al., 2017). This assessment instrument combines both the patient’s self-report and the clinician’s evaluation of the patient’s risk for suicide into one singular score (Hawes et al., 2017). Interestingly, the patients’ self-report does not contain items overtly referring to their suicidal history, ideation, or intent but the clinician’s portion of the assessment does (Hawes et al., 2017). It is the combination of these two scores that define an inpatient’s short-term risk for suicide (Hawes et al., 2017). Results of Hawes et al. (2017) suggests that the MARIS demonstrated adequate predictive validity for detecting high-risk psychiatric inpatients who will engage in suicidal behavior during the four to eight weeks following hospital discharge. This research identified the use of multi-informant approaches as a promising area for future directions within the field of suicide risk assessment instruments.
As clinicians, our ethical principles dictate that we do our best when assessing patients who express SI and intent (APA, 2013; Bongar, 1991). Assessment instruments that measure risk of suicide include the BAI, SPS, ASIQ, PHQ-9, BSS, BHS, BDI-II, and the PSS. Overall, results indicate that using single factor assessment measures are problematic due to the varied and nuanced ways that patients’ characteristics influence a variety of risk factors that increase their risk for suicide. Recent advances in suicide risk assessment measures have demonstrated predictive validity for multi-informant approaches, making these a prominent area of future research. These types of approaches are aligned with APA guidelines that outline the usefulness of both a clinical interview and an assessment battery to adequately evaluate a patient’s risk for suicide. While death by suicide remains a national public health concern in the U.S., EDs have a unique opportunity to identify and intervene for those most at risk, in part through the creation of valid and reliable assessment measures.
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Amanda Wallick graduated from the University of Nevada, Las Vegas in 2016, with a Bachelor’s in Psychology and a Minor in Marriage and Family Therapy. In 2017, she began the Clinical Psychology Ph.D. program at Palo Alto University (PAU), where she recently completed the Trauma Area of Emphasis. Amanda has first-authored a book chapter on resiliency and mental health and a previous Division 56 newsletter contribution looking at the importance of trauma core competencies in graduate programs. She also served as PAU’s secretary for the Association of Traumatic Stress Studies student group for the 2018-2019 academic year and was recently elected as APA Campus Ambassador for PAU. Her research interests include trauma/PTSD, severe mental illness, and personality. She is a student affiliate of APA Division 56, the Association for Psychological Science (APS), as well as the International Society for Traumatic Stress Studies (ISTSS).
Lisa M. Brown, Ph.D., ABPP is a tenured Professor, Director of the Trauma Program, Director of the Risk and Resilience Research Lab at Palo Alto University, and faculty advisor for the Association of Traumatic Stress Studies. Her clinical and research focus is on trauma and resilience, global mental health, aging, and vulnerable populations. As a researcher, she is actively involved in developing and evaluating mental health programs used nationally and internationally, drafting recommendations aimed at protecting individuals and communities during catastrophic events, facilitating participation of key stakeholders, and improving access to resources and services. Dr. Brown is a Fellow of the American Psychological Association and the recipient of two Fulbright Specialist awards with the University of the West Indies, Mona, Jamaica (2014) and with Massey University, Palmerston North, New Zealand (2015).