Depression, PTSD, and Suicidal Ideation Among Active Duty Veterans ...

Psychological Services 2011, Vol. 8, No. 2, 94 –103

© 2011 American Psychological Association 1541-1559/11/$12.00 DOI: 10.1037/a0023451

Depression, PTSD, and Suicidal Ideation Among Active Duty Veterans in an Integrated Primary Care Clinic Craig J. Bryan

Kent A. Corso

University of Texas Health Science Center at San Antonio

NCR Behavioral Health, LLC, Washington, DC

Active duty veterans increasingly access primary care for needed mental health services, but the relationship among depression, PTSD, and suicidal ideation in this subpopulation remains unclear. The relationship is explored in 120 active duty members treated in a military integrated primary care behavioral health service. Logistic regression analyses resulted in a significant relationship between PTSD and suicidal ideation, but this relationship was fully explained by depression symptoms. The interaction between depression and PTSD symptoms was likewise unrelated to suicidal ideation, and it did not improve overall model fit, suggesting that depression independently explained increased risk for suicidal ideation in the current sample. The authors discuss the differences between suicidal ideation and suicidal behaviors, and how depression and PTSD symptoms might differentially relate to each. Keywords: suicidal ideation, military, primary care, assessment

lihood that active duty members will seek treatment for mental health symptoms such as PTSD and depression. Assuming that these obstacles can be surmounted, effective treatment protocols remain rigorous and time consuming, lasting as long as 12 weeks, with weekly 60 –90 min sessions (e.g., Foa et al., 2005; Resick, Nishith, Weaver, Astin, & Feurer, 2002). Given increased operational demands required of service members, the frequency and intensity of traditional treatment protocols can serve as a further barrier to mental health care access. Similar to the civilian world, patients in the military have more frequent and feasible contact with medical providers in primary care clinics versus specialty mental health settings. Recent reports of psychiatric prevalence rates (i.e., meeting criteria for at least one mental health disorder) for OIF/OEF veterans seen in primary care were determined to be as high as 25% (Seal, Bertenthal, Miner, Sen, & Marmar, 2007). PTSD and depression symptoms, in particular, are significant health problems contributing to poorer general health and somatic symptoms including headaches, chest pain, dizziness, fainting, and digestive problems (Hoge, Terhakopian, Castro, Messer, & Engel, 2007). It is therefore not surprising that veterans with PTSD visit primary care medical providers more frequently and miss twice as many days of

Symptoms of posttraumatic stress disorder (PTSD) among U.S. military veterans deployed during Operation Iraqi Freedom (OIF) and Operation Enduring Freedom (OEF) have been reported at rates as high as 17% (Hoge et al., 2004). Unfortunately, only 10% of male and 26% of female active duty personnel reporting mental health symptoms following a deployment will actually pursue treatment (Visco, 2009) for a number of reasons, including avoidant coping strategies; instability in living arrangements due to mission demands and frequent redeployments; and fears that seeking mental health treatment will negatively impact one’s career. These obstacles, which are especially salient among military personnel as compared to civilian populations, decrease the like-

This article was published Online First April 11, 2011. Craig J. Bryan, Department of Psychiatry, University of Texas Health Science Center at San Antonio; Kent A. Corso, NCR Behavioral Health, LLC, Washington, DC. The views expressed in this article are solely those of the authors and do not necessarily represent an endorsement by, or the views of, the U.S. Government, the Department of Defense, or the Department of the Air Force. Correspondence concerning this article should be addressed to Craig J. Bryan, Assistant Professor/Research, Department of Psychiatry, University of Texas Health Science Center at San Antonio, 7550 IH-10 West, Suite 1325, San Antonio, TX 78229. E-mail: [email protected] 94

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work compared to veterans without PTSD (Hoge et al., 2007). These health problems and functional impairment worsen with comorbid depression (Campbell et al., 2007), as does the risk for suicide (Oquendo et al., 2003). In response to the rapid expansion of primary care medical clinics as a primary default source of mental health care (and often times the only source of mental health care) for service members, an increasing number of specially trained mental health providers have been integrated into Department of Defense (DoD) and Veterans Affairs (VA) primary care clinics to work alongside primary care providers in order to improve detection, diagnosis, and treatment of psychological health issues. For example, the United States Air Force (USAF) has aggressively expanded its behavioral health consultant model (cf. Robinson & Reiter, 2007) of integrated primary care in the past few years. The VA has expanded several models of integrated care, including the collocated/collaborative care model, in which traditional mental health treatment is provided within the primary care clinic; the care management model, in which a nurse provides follow-up (typically via phone) to reinforce adherence to the primary care physician’s treatment plan; and the Behavioral Health Laboratory (BHL) model, in which structured mental health assessments and treatment monitoring are provided (Zeiss & Karlin, 2008). Yet another model of integrated care implemented by the U.S. Army is the RESPECTMil program, which emphasizes psychotropic medication management for depression and PTSD (Oxman, 2008). This integration has proven effective for the general patient population (Bryan, Morrow, & Appolonio, 2009) and has also demonstrated preliminary effectiveness for deployment-related health problems (Corso et al., 2009). Depression is a well-established risk factor for the full spectrum of suicidality (Harris & Barraclough, 1997; Henriksson et al., 1993), but the link between PTSD and suicidality is less clear. Marshall et al. (2008) found a positive association between number of PTSD symptoms and suicidal ideation, even when controlling for the presence of other psychiatric disorders. Likewise, Wilcox, Storr, and Breslau (2009) found that PTSD was independently associated with increased risk for suicide attempts in the presence of other psychiatric disorders.

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The demonstrated association between suicidal ideation and nightmares, a common symptom of PTSD, above and beyond the effects of insomnia and depression (Bernert, Joiner, Cukrowicz, Schmidt, & Krakow, 2005; Cukrowicz et al., 2006), further points to a possible pathway linking PTSD with suicidality. Other research suggests that it is the cooccurrence of PTSD with other psychiatric conditions, notably depression, that contributes to suicidality but not PTSD by itself. Comorbid PTSD and depression, for example, is associated with greater prevalence of suicidal ideation (Campbell et al., 2007) and suicide attempts (Oquendo et al., 2003). Though co-occurrence or interaction effects were not explicitly tested by Marshall et al. (2008), results of their study could potentially point to the importance of interaction effects. Specifically, these authors reported that as the number of PTSD symptoms increased, so did the rate of comorbid major depressive disorder. Yet another line of research suggests that the relationship between PTSD and suicidality is mediated by depression (Leiner, Comptom, Houry, & Kaslow, 2008). Similarly, a number of studies have failed to support the incremental predictive utility of PTSD above and beyond the presence of depression (Fordwood, Asarnow, Huizar, & Reise, 2007; Holtzheimer, Rousso, Zatzick, Bundy, & Roy-Byrne, 2005; Zlotnick, Mattia, & Zimmerman, 2001). Despite the mixed results of these studies, it seems that the association between suicidality and PTSD symptoms is related, at least in part, to co-occurring depression. Critically, none of these studies investigated the relationships among depression, PTSD, and suicidality in active duty military personnel. Given the increased utilization of primary care medical services by military personnel and rising concerns about the psychiatric sequelae arising from combat experiences, identifying the clinical variables that are most strongly related to suicidality among veterans presenting to primary care is critical for prevention and treatment efforts. The primary aim of this study was therefore to conduct a retrospective analysis of clinical data obtained from active duty patients in an integrated primary care clinic to test the association among PTSD symptoms, depression symptoms, and the endorsement of suicidal ideation. Although suicidality includes a number of

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measurable dimensions (e.g., frequency, intensity, and duration of suicidal ideation; severity of intent), the current study measured suicidal ideation using an endorsed/denied approach that mirrors typical screening and assessment procedures in primary care clinics (Bryan, Corso, Neal-Walden, & Rudd, 2009; Bryan & Rudd, 2010). Method Participants and Procedures Participants included 120 active duty service members referred by their primary care provider (PCP) to a behavioral health consultation (BHC) service integrated into a large family medicine clinic at an Air Force base in the southwestern United States over the course of 15 months. During the same time period, the BHC service met with a total of 1,067 patients. The sample was predominantly men (66.7%) who were an average of 31.07 ⫾ 9.25 years of age. Racial breakdown was as follows: 50.0% Caucasian, 21.7% African American, 22.5% Hispanic/Latino, 2.5% Asian, and 2.5% Other. Rank was largely junior-enlisted (27.7% E1-E4) and middle-enlisted (53.0% E5-E6), although the sample included a fair number of seniorenlisted (5.9% E7-E9) and officers (0.8% warrant officer, 5.0% O1-O3, and 4.1% O4-O5). Participants were referred to the BHC service by their PCPs when psychosocial health issues related to deployment were identified during routine primary care medical appointments or upon review of a completed Post Deployment Health Reassessment (PDHRA), a health screening offered between 90 and 180 days postdeployment. Upon check-in for each BHC appointment, members were given paper-and-pencil symptom checklists (described in the Measures section) to complete in the waiting room prior to the appointment. Scores from these checklists were reviewed by the clinician as a part of routine care to guide clinical decision making, and they were stored in an electronic database for outcomes tracking and epidemiological reporting. Paper-and-pencil surveys were stored in the secured BHC service administrative office located in the primary care clinic. Upon IRB approval for exempt research, the electronic database was deidentified and analyzed.

Measures PTSD symptoms. PTSD symptoms were measured by the PTSD Checklist-Military Version (PCL-M; Weathers, Litz, Herman, Huska, & Keane, 1993), which is a 17-item self-report inventory that assesses the severity of each DSM–IV-defined PTSD symptom. The PCL-M is widely used in the DoD and the VA, and it has excellent reliability and validity, but has a range of proposed cutoff scores that vary according to setting (Blanchard, Jones-Alexander, Buckley, & Forneris, 1996; Bliese et al., 2008; Weathers et al., 1993). In primary care settings, several psychometric studies (including two of utilizing military samples) have identified a cutoff of 34 as the optimal score for maximizing efficiency for a PTSD diagnosis (Bliese et al., 2008; Lang et al., 2003; Sherman et al., 2005; Walker et al., 2002). This cutoff score is lower than the more widely recognized cutoff of 50, but as noted by Bliese et al. (2008), different cutoff scores need to be applied to different samples. A high specificity score of 50 may be a reasonable cutoff value for a treatment-seeking population in a mental health setting or in an anonymous population-based epidemiological survey, but is too high a cutoff value when screening in primary care or a postdeployment setting. (p. 279)

Patients were directed to think about their most stressful deployment experience while responding to the PCL-M in order to ensure responses were directly related to deploymentrelated traumas. PCL-M score was not used as the sole diagnostic determinant for clinical practice but, rather, was used as a measure of symptom severity. Depression symptoms. Depression symptoms were measured by the 5-item Depression subscale of the Behavioral Health Measure-20 (BHM), which is a brief self-report questionnaire that uses a five-point Likert scale to assess mental health symptoms and functioning (Kopta & Lowry, 2002). The BHM can be used to distinguish four levels of mental health functioning (Normal, Mild, Moderate, Severe) based on the clinical significance criteria recommended by Jacobson and Truax (1991). As such, the BHM is designed to detect clinically meaningful changes in mental health functioning. Total scale scores have internal consistency coefficients ranging from .89 to .90, with testretest reliability being .80 (Kopta & Lowry,


2002). The scale correlates highly (rs ⬎ .61) with other symptom measures, such as the Outcomes Questionnaire-45 (Lambert et al., 1996) and the Symptom Checklist-90-R (Derogatis, 1994), and can significantly differentiate between clinical and nonclinical samples. The Depression subscale consists of items that ask about the frequency of low energy and motivation, not liking oneself, difficulty concentrating, sadness, and hopelessness during the preceding 2 weeks. Internal consistency for the Depression subscale was ␣ ⫽ .845, which is consistent with unpublished data from three separate primary care clinical samples demonstrating internal consistencies ranging from .834 to .857 (Blount et al., 2010). In terms of construct validity, the BHM’s Depression subscale correlates highly with validated measures of depression (rs ⬎ .51) and happiness (r ⫽ ⫺.46) in the expected directions among military clinical and nonclinical samples (Blount et al., 2010). The Depression scale is constructed such that higher scores indicate better health (i.e., lower levels of depression), with a recommended clinical cutoff of 2.84 (CelestHealth, 2008). To aid in interpretation of results for the purposes of the current study, this scale was therefore reverse-keyed such that higher scores indicated greater levels of depression; this transformation shifts the clinical cutoff score to 1.16 (i.e., scores at or above this level are in the clinical range). Suicidal ideation. Suicidal ideation was measured using Item 10 of the BHM, which asks patients to rate the frequency of “thoughts of ending your life . . . within the last week” on a scale ranging from 0 (“almost always”) to 4 (“never”). Unpublished data indicate that the BHM’s Item 10 correlates highly with the 4-item Suicidal Behaviors Questionnaire— Revised’s (SBQ-R; Osman et al., 2001) item about suicidal ideation in the past year (“How often have you thought about killing yourself in the past year?”; r ⫽ .61, p ⬍ .001), the SBQ-R’s self-reported likelihood of attempting suicide (“How likely is it that you will attempt suicide someday?”; r ⫽ .65, p ⬍ .001), and the SBQ-R’s total score (r ⫽ .71, p ⬍ .001). The BHM item 10 also correlates very highly (r ⫽ .99, p ⬍ .001) with the PHQ-9’s suicide-risk screening item, which asks respondents to indicate the frequency of “thoughts that you would be better off dead, or of hurting yourself” during

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the preceding 2 weeks. Responses on the BHM Item 10 were dichotomized to indicate the presence of suicidal ideation. Results Prior to statistical analysis, a number of transformations were made to the data. First, race was collapsed into a dichotomous variable (Caucasian and non-Caucasian) due to low count in certain racial categories (i.e., Asian and Other). We repeated analyses with race entered both as a dichotomized variable and in its original, nonaggregated form, with no changes in results, suggesting that dichotomization was not adversely affecting outcomes. Means, standard deviations, and intercorrelations for all variables are presented in Table 1 to better describe the sample. Symptom scores for both PCL-M (M ⫽ 37.47, SD ⫽ 12.79) and Depression (M ⫽ 1.32, SD ⫽ .85) were elevated, as would be expected in a clinical setting among patients presenting for deployment-related problems. Depression and PCL-M scores were correlated with each other in the expected direction, consistent with research demonstrating their high co-occurrence. In terms of depression, 47.0% scored within the normal range, 29.8% scored in the mild range, 9.1% scored in the moderate range, and 14.0% fell in the severe range. In terms of PCL-M scores, 61.3% scored above the primary care recommended cutoff of 34 for primary care. Only 6.7% of the sample reported suicidal ideation, which was correlated with both PCL-M and Depression scores. Next, a logistic regression equation predicting presence or absence of suicidal ideation was constructed (see Table 2). Continuous variables were first centered to reduce collinearity. We first entered PCL-M score along with the three covariates (gender, race, age), resulting in a ⫺2 log likelihood (⫺2LL) value of 52.848; the ⫺2LL statistic is a measure of overall model fit. In this first step, only PTSD symptoms were significantly associated with suicidal ideation (B ⫽ .064, SE ⫽ .031, p ⫽ .038, OR ⫽ 1.066 [1.004 –1.133]), with each one-point increase in PCL-M score being associated with a 1.6% increase in the likelihood of endorsing suicidal ideation, which is equivalent to a 15.6% increase in the likelihood of endorsing suicidal ideation for each 10-point increase in PCL-M score, the generally accepted criterion for a clin-

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Table 1 Means, Standard Deviations, and Intercorrelations for All Variables Variable

1

2

3

4

5

6

1. SI 2. Gender 3. Race 4. Age 5. PCL-M 6. Depression M SD Range

— ⫺.043 ⫺.063 .039 .189ⴱ .352ⴱⴱ 0.07 0.25 —

— ⫺.050 ⫺.104 ⫺.117 .124 0.33 — —

— ⫺.124 .141ⴱ .080 0.50 — —

— .130 .221ⴱ 31.07 8.34 19–54

— .550ⴱⴱ 37.47 12.79 17–76

— 1.32 0.85 0–3.80

Note. SI ⫽ suicidal ideation; PCL-M ⫽ PTSD Checklist-Military Version. Gender is coded female ⫽ 1 and male ⫽ 0, such that the mean reflects the percentage of the sample that is female. Race is coded Caucasian ⫽ 1 and non-Caucasian ⫽ 0, such that the mean reflects the percentage of the sample that is Caucasian. The Depression scale is reverse keyed such that higher scores indicate greater levels of depression.

ratio of this magnitude means that a patient with a mean depression score (i.e., M ⫽ 1.32) has a 50% likelihood of endorsing suicidal ideation, but a patient with a depression score of 2.32 has an approximately 87% likelihood of endorsing suicidal ideation, whereas a patient with a depression score of .32 has an approximately 17% likelihood of endorsing suicidal ideation. PCL-M scores were not, however, significantly associated with suicidal ideation (B ⫽ ⫺.006, SE ⫽ .043, p ⫽ .882, OR ⫽ .994 [.914 –1.080]) when Depression was included in the equation, suggesting a possible mediation effect. The mediation hypothesis is traditionally represented in a triangular diagram (see Figure 1), which depicts a direct causal path from independent variable (i.e., PCL-M score) through the mediator (i.e., Depression score) to the outcome (i.e., suicidal ideation), in which regression analyses

ically meaningful change in PCL-M total score. In other words, a patient with a PCL-M score of 38 (i.e., rounded up from the sample mean of 37.5) has an approximately 50% chance of endorsing suicidal ideation, and a patient with a PCL-M score of 48 has an approximately 65.6% chance of endorsing suicidal ideation, whereas a patient with a PCL-M score of 28 has an approximately 34.4% chance of endorsing suicidal ideation. In the second step, Depression score was added to the equation, resulting in a significantly improved model fit, as indicated by a significant reduction in ⫺2LL from 52.848 to 41.708 (⌬(⫺2LL) ⫽ 11.14; ␹2(5) ⫽ 11.07, p ⫽ .049). In this step, depression significantly increased the likelihood of suicidal ideation with large effect (B ⫽ 1.909, SE ⫽ .648, p ⫽ .003, OR ⫽ 6.743 [1.893–24.015]). An odds

Table 2 Stepwise Logistic Regression Model Predicting Suicidal Ideation 95% CI Step

⫺2LL

Variable

B

SE

Wald

df

p

OR

Lower

Upper

1

52.848

2

41.708

3

41.610

Gender (Female) Race (Caucasian) Age PCL-M PCL-M Depression PCL-M Depression Depression ⫻ PCL-M

.143 ⫺.936 ⫺.002 .064 ⫺.006 1.909 ⫺.016 1.864 .010

.873 .811 .046 .031 .043 .648 .053 .670 .034

.027 1.334 .003 4.301 .022 8.673 .091 7.744 .095

1 1 1 1 1 1 1 1 1

.870 .248 .958 .038 .882 .003 .764 .005 .758

1.153 .392 .998 1.066 .994 6.743 .984 6.451 1.011

.208 .080 .912 1.004 .914 1.893 .888 1.735 .945

6.388 1.921 1.091 1.133 1.080 24.015 1.091 23.980 1.080

Note. SE ⫽ standard error; OR ⫽ odds ratio; CI ⫽ confidence interval; PCL-M ⫽ PTSD Checklist-Military Version; ⫺2LL ⫽ ⫺2 log likelihood.


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Mediator (Depression)

a = .363

Independent Variable (PTSD)

b = 1.909 c = .064 c’ = -.006

Dependent Variable (Suicidal Ideaon)

Covariates (Gender, age, race)

Figure 1. The mediation hypothesis is typically represented in a triangular diagram that depicts a direct causal path from the independent variable to the dependent variable (c), and an indirect path from the independent variable through the mediator (a) to the dependent variable (b). The effect of the covariates on both the independent and dependent variables are also displayed. In the current study, the independent variable is PCL-M score, the dependent variable is suicidal ideation, and the mediator is Depression score. If the mediation hypothesis is supported, the direct effect of the independent variable on the dependent variable (c⬘) will be significantly reduced relative to the total effect (c) in the presence of the multiplicative path through the mediator (a ⴱ b).

are used to estimate causal paths. To test the mediation hypothesis, the bootstrapped test of indirect effects recommended by contemporary mediation experts (e.g., Preacher & Hayes, 2008) was utilized. The indirect effect of PCL-M on suicidal ideation through Depression (i.e., a * b) resulted in a value of .069. The bootstrapped value, based on 1,000 resamples, suggested only minimal bias (bootstrapped coefficient ⫽ .085, SE ⫽ .056, bias ⫽ .019). The bias corrected and accelerated 95% confidence interval for the indirect effect was .010 –.177, confirming that the indirect effect was statistically significant and suggesting that the association of PCL-M with suicidal ideation was fully explained by depression. In the third and final step, the interaction of PTSD and depression symptoms was added to the equation in order to test the moderation hypothesis to better understand which patients endorse suicidal ideation. By including the interaction term, we sought to determine if association between depression and suicidal ideation was augmented or suppressed by PTSD symptom severity. The resulting model did not significantly change overall data fit (⌬(⫺2LL) ⫽ .098, ␹2(6) ⫽ .145, p ⫽ .999), with depression being the sole variable significantly associated with suicidal ideation (B ⫽ 1.864, SE ⫽ .670, p ⫽ .005, OR ⫽ 6.451 [1.735–23.980]). This pattern of results sug-

gests that PTSD did not serve as a moderator of depression’s effect on the endorsement of suicidal ideation, and the second model utilizing only the main effects of depression and PTSD symptoms was adequate for describing the data. Discussion The relationship among PTSD, depression, and suicidality is complex, as evidenced by the mixed results reported in prior studies. Importantly, no studies, to date, have considered the relationship between these factors among active duty military personnel presenting with deployment-related problems to integrated primary care behavioral health services—a rapidly expanding setting for active duty veterans to seek mental health care. The purpose of the current study was therefore to preliminarily investigate the nature of the association between these important clinical variables in a primary care setting. Results of our analyses indicated that although PTSD symptoms demonstrated a small association with suicidal ideation, this association did not remain statistically significant when depression symptoms were simultaneously considered, suggesting that the relationship between PTSD and suicidal ideation that existed in the current sample was explained by depression. The interaction of depression and PTSD

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was also nonsignificant and did not substantially alter results, suggesting that PTSD symptoms neither augmented nor suppressed the magnitude of the association between depression and suicidal ideation. These findings suggests that, among the active duty military personnel presenting to our integrated primary care behavioral health service for deploymentrelated health concerns, the presence of suicidal ideation was primarily associated with depression symptoms. The present study converges with previous studies failing to find a direct relationship between PTSD and suicidality when factoring in depression (Fordwood et al., 2007; Holtzheimer et al., 2005; Zlotnick et al., 2001) but diverges from other studies demonstrating a significant main effect of PTSD even in the presence of depression (Clum & Weaver, 1997; Lewis, 2005; Marshall et al., 2008). The absence of an interaction effect of depression and PTSD symptoms similarly diverges from prior studies suggesting that the combined presence of depression and PTSD heightens the risk for suicidal ideation (Campbell et al., 2007; Oquendo et al., 2003). One potential explanation for these findings is the methods used to measure PTSD and depression. For example, many studies utilized dichotomized PTSD and/or depression predictors in their analyses (e.g., Campbell et al., 2007; Marshall et al., 2008; Oquendo et al., 2003; Wilcox et al., 2009), which can result in lost information. The current study, in contrast, utilized continuous variables to predict suicidal ideation. The benefit of using continuous variables arises from the fact that symptoms such as depression and PTSD do not manifest clinically in a dichotomous (i.e., present/absent) manner; rather, they manifest on a spectrum of severity. Indeed, a post hoc analysis of our data supported this possibility: dichotomizing the PCL-M and Depression scales according to the recommended cutoff scores resulted in a nonsignificant main effect of PTSD in Step 1 (demonstrating a loss of information), although the pattern of results in Step 2 did not change, with depression maintaining a significant effect in Step 2.1 Another potential explanation for our results within the context of the greater body of mixed outcomes is the tendency to lump the full range of suicide-related and self-injurious phenomena (e.g., desire for death, suicidal ideation, suicide

plans, suicide attempts) under the umbrella of “suicidality,” when these constructs might actually represent distinct, though related, constructs. Van Orden et al. (2010) have argued, for example, that suicidal ideation emerges from heightened desire for suicide, which is more strongly associated with depressive symptoms, whereas traumatic experiences contribute to the capability for suicide, which simultaneously lowers an individual’s fear of death and elevates his or her pain tolerance. Consistent with this conceptualization of suicide risk, depression would be expected to be significantly associated with suicidal ideation, whereas PTSD would be expected to be associated with suicidal intent. The combination of PTSD and depression would result in the merging of suicidal desire with suicidal capability, the outcome of which would be more severe suicidal behaviors. Given that the outcome variable in the current study was suicidal ideation, we might expect the main effect of depression— but not PTSD or the interaction of depression and PTSD—to be more strongly associated with suicidal ideation, consistent with Van Orden et al. (2010). Additional research is needed to test the possibility that depression and PTSD are related to different dimensions of suicidality. An important limitation of our study is our restricted outcome variable, which measured only the presence/absence of suicidal ideation based on an item keyed to measure the frequency of suicidal ideation, not the level of suicidal intent or severity of suicidal ideation. This is a critical distinction given that suicide attempts are strongly predicted by the presence of suicidal intent, behavioral preparation, and greater intensity of suicidal ideation (which is very closely associated with intent), and less robustly predicted by frequency of suicidal ideation (Joiner, Rudd, & Rajab, 1997). Future research should include measures of suicidal intent and behavioral preparation to further understand their relationship with depression and PTSD. However, because suicidal ideation is a necessary (thought not sufficient) condition for severe suicidal behaviors, our study provides critical information for better understanding the full range of suicidality among military person1 These data were not presented in this article but are available from the first author upon request.


nel. Future replications of this study should therefore measure those dimensions of suicidality that more strongly predict suicidal behavior (i.e., intent, behavioral preparation, intensity of ideation). The study is additionally limited to only a small number of those service members voluntarily accessing integrated mental health services for deployment-related concerns. Given the well-documented problem of mental health stigma (Hoge et al., 2004), which reduces service members’ likelihood of accessing services and reporting mental health symptoms, generalizability of results to service members who turn down such services is therefore limited. Similarly, the extent to which these findings apply to the broader spectrum of veterans across all branches of service, especially those who do not access mental health services for depression, PTSD, and/or suicidal thinking, is unknown. Replication of these preliminary findings with larger samples is therefore warranted. Our results nonetheless provide some important preliminary data related to an issue that is of particular concern to mental health providers working in integrated primary care clinics. On a pragmatic level, although suicidal ideation and desire certainly do not manifest in a dichotomized present/absent scheme, but rather exist on a spectrum of intensity, clinical practice standards related to the management of suicidal risk often operate on such a present/absent scheme. Specifically, positive screens are typically associated with higher intensity response than negative screens for suicide risk. Results of our study indicate that the endorsement of suicidal ideation among active duty patients presenting to one particular primary care clinic for deployment-related health concerns was more robustly related to symptoms of depression than PTSD. In the context of primary care, it is expected that providers will quickly and accurately identify and treat problems within a very short amount of time, which does not allow for the lengthy history taking that is more characteristic of tertiary care models. Therefore, current results are most applicable for practitioners working within primary care delivery models. When working with service members who are endorsing suicidal ideation within the context of deployment-related PTSD symptoms, clinicians should be alert to co-occurring depression for immediate clinical intervention, since targeting depression could have a more direct impact on

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reducing suicide risk than targeting PTSD symptoms. Additional research in integrated primary care settings is required to further elucidate these preliminary findings. References Bernert, R. A., Joiner, T. E., Cukrowicz, K. C., Schmidt, N. B., & Krakow, B. (2005). Suicidality and sleep disturbances, Sleep, 28, 1135–1141. Blanchard, E. B., Jones-Alexander, J., Buckley, T. C., & Forneris, C. A. (1996). Psychometric properties of the PTSD Checklist (PCL). Behavior Research and Therapy, 34, 669 – 673. Bliese, P. D., Wright, K. M., Adler, A. B., Cabrera, O., Castro, C. A., & Hoge, C. W. (2008). Validating the primary care posttraumatic stress disorder screen and the posttraumatic stress disorder checklist with soldiers returning from combat. Journal of Consulting and Clinical Psychology, 70, 272– 281. Blount, T. H., Bryan, C. J., Kanzler, K. E., Morrow, C. E., Corso, K. A., & Corso, M. L. (2010). Psychometric properties of the BHM-20 in military samples. Poster presented at the annual meeting of the Association for Behavioral and Cognitive Therapies, San Francisco, CA. Bryan, C. J., Corso, K. A., Neal-Walden, T. A., & Rudd, M. D. (2009). Managing suicide risk in primary care: Practice recommendations for behavioral health consultants. Professional Psychology: Research and Practice, 40, 148 –155. Bryan, C. J., Morrow, C. E., & Appolonio, K. K. (2009). Impact of behavioral health consultant interventions on patient symptoms and functioning in an integrated family medicine clinic. Journal of Clinical Psychology, 65, 281–293. Bryan, C. J., & Rudd, M. D. (2010). Managing suicide risk in primary care. New York, NY: Springer. Campbell, D. G., Felker, B. L., Liu, C., Yano, E. M., Kirchner, J. E., Chan, D., . . . Chaney, E. F. (2007). Prevalence of depression-PTSD comorbidity: Implications for clinical practice guidelines and primary care-based interventions. Journal of General Internal Medicine, 22, 711–718. CelestHealth Solutions. (2008). Clinical Report Manual College Counseling Version. Newburgh, IN: CelestHealth Solutions. Clum, G. A., & Weaver, T. L. (1997). Diagnostic morbidity and its relationship to severity of ideation for a nonpsychiatric sample of chronic and severe suicide ideators. Journal of Psychopathology and Behavioral Assessment, 19, 191–206. Corso, K. A., Bryan, C. J., Morrow, C. E., Appolonio, K. K., Dodendorf, D. M., & Baker, M. T. (2009). Managing posttraumatic stress disorder

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