Screening for post-traumatic stress disorder in female Veteran’s Affairs patients: validation of the PTSD checklist

General Hospital Psychiatry 24 (2002) 367–374

Psychiatry and primary care Recent epidemiologic studies have found that most patients with mental illness are seen exclusively in primary care medicine. These patients often present with medically unexplained somatic symptoms and utilize at least twice as many health care visits as controls. There has been an exponential growth in studies in this interface between primary care and psychiatry in the last 10 years. This special section, edited by Wayne J. Katon, M.D., will publish informative research articles that address primary care-psychiatric issues.

Screening for post-traumatic stress disorder in female Veteran’s Affairs patients: validation of the PTSD checklist Dorcas J. Dobie, M.D.a,e,*, Daniel R. Kivlahan, Ph.D.a,b,e, Charles Maynard, Ph.D.d,g, Kristen R. Bush, M.P.H.b, Miles McFall, Ph.D.a,e, Amee J. Epler, B.A.c, Katharine A. Bradley, M.D., M.P.H.c,f,g b

a Mental Illness Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle, WA, USA Center of Excellence in Substance Abuse Treatment and Education, VA Puget Sound Health Care System, Seattle, WA 98108, USA c Health Services Research & Development, VA Puget Sound Health Care System, Seattle, WA 98108, USA d Epidemiologic Research and Information Center, VA Puget Sound Health Care System, Seattle, WA 98108, USA e Departments of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA 98195, USA f Department of Medicine, University of Washington, Seattle, WA 98195, USA g School of Public Health, University of Washington, Seattle, WA 98195, USA

Abstract We evaluated the screening validity of a self-report measure for post traumatic stress disorder (PTSD), the PTSD Checklist (PCL), in female Veterans Affairs (VA) patients. All women seen for care at the VA Puget Sound Health Care system from October 1996 –January 1999 (n⫽2,545) were invited to participate in a research interview. Participants (n⫽282) completed the 17-item PCL, followed by a gold standard diagnostic interview for PTSD, the Clinician Administered PTSD Scale (CAPS). Thirty-six percent of the participants (n⫽100) met CAPS diagnostic criteria for current PTSD. Receiver Operating Characteristic (ROC) analysis was used to evaluate the screening performance of the PCL. The area under the ROC curve was 0.86 (95% CI 0.82– 0.90). A PCL score of 38 optimized the performance of the PCL as a screening test (sensitivity 0.79, specificity 0.79). The PCL performed well as a screening measure for the detection of PTSD in female VA patients. © 2002 Elsevier Science Inc. All rights reserved. Keywords: Stress disorders; Post-traumatic; Women; Veterans; Psychiatric status rating scales; Quality of life

1. Introduction Posttraumatic stress disorder (PTSD), is defined in DSMIV as an anxiety disorder that develops in response to severe traumatic life stress [1]. The symptoms of PTSD fall into three domains: re-experiencing symptoms, numbing and avoidance symptoms, and hyper-arousal symptoms. Studies have consistently demonstrated that the probability of de* Corresponding author. Tel.: ⫹1-206-277-3317; fax: ⫹1-206-7642572. E-mail address: [email protected] (DJ. Dobie) The views expressed in this article are those of the authors and do not necessarily represent the views of the Department of Veteran’s Affairs, the University of Washington, the Robert Wood Johnson Foundation, or NIAAA.

veloping PTSD following a traumatic exposure is higher for women than for men, and that certain types of trauma (rape, combat and other forms of assaultive violence) are more likely than others to result in PTSD [2– 4]. Furthermore, PTSD is associated with poor health, low functional status and higher health care utilization [5–11]. With recognition of the negative impact of PTSD on overall health, emphasis on screening for PTSD outside of specialty mental health settings has grown [12–14]. In 1973, women made up about 2–3% of the total armed forces. In 1998, women comprised 14% of active duty forces and 20% of new military recruits [15,16]. The proportion of the veteran population that is female is projected to increase from 4.9% in 1998 to 10% by the year 2010 [16]. The Veterans Health Administration (VHA) manages the

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largest integrated health care system in the United States [17]. As the number of female veterans rises, the number of women seeking care at VA facilities has increased dramatically. In 1995, women accounted for 1.6 million VA ambulatory care visits, an increase of 40% over 1991 [15]. Despite the closing of many VA hospital beds, the number of female inpatient admissions increased by 11% during that same period. This shift in demographics has necessitated the rapid development of primary and specialty care for women in VA settings. Unfortunately, there is relatively little information about their health care needs. Available data suggest that female veterans are a highly trauma-exposed group, and hence may be particularly vulnerable to the development of PTSD. Most studies have focused on traumatic experiences that occurred during military duty. A national cross-sectional telephone survey of 537 female veterans reported that 48% percent experienced assaultive violence while in the military, including rape (30% of assaults), physical assault (35% of assaults), or both (10% of assaults) [18]. Similarly, a mailed survey of 3,632 women seen for care at VA outpatient facilities concluded that 23% had been sexually assaulted in the military [19,20]. As tactical military roles for female soldiers have expanded, women veterans are increasingly likely to be traumatized from dangerous duty in war zone and peace keeping operations [21]. In addition to traumatic military experiences, many veteran women suffered premilitary stressors, such as sexual and physical abuse, that may predispose them to the development of PTSD. In the previously described telephone survey of veteran women, 47% reported sexual abuse during childhood or rape prior to entering the military, and 35% endorsed childhood physical abuse [18]. In a small sample of female Desert Storm veterans, 60% endorsed precombat physical or sexual abuse compared with 27% of the male veterans [22]. A survey of lifetime trauma among a sequential sample of 500 women seen at a VA women’s primary care clinic found that 20% had been raped, 27% were victims of domestic violence, and 19% reported early life sexual trauma [23]. Methodological differences make these rates of trauma exposure somewhat difficult to compare to samples of nonveteran women. Nonetheless, female veteran patients appear to report higher rates of exposure to assaultive violence than women surveyed in other clinical and community settings [3,24 –27]. Although female VA patients appear to be at high risk for PTSD, efficient screening instruments for PTSD have not been validated in this population. The primary goal of this study was to evaluate the PTSD Checklist (PCL), a 17-item self-report measure that assesses past-month symptoms of PTSD [28]. Our aims were to determine if the PCL was an effective screening test in women seen for care at one large VA medical center, and to determine the optimal PCL cut-point to screen for PTSD among female veteran patients. Determining this cut-point would be useful in the development of clinical screening programs for PTSD.

2. Methods 2.1. Subjects and setting Eligible participants were all women who received care at the VA Puget Sound Health Care System (VA PSHCS) between October 1, 1996 and January 1, 1999. Women were excluded if they no longer resided in Washington State or if they had previously indicated that they were not willing to participate in women’s health research (n⫽47). All eligible women (n⫽2545) received a mailed information sheet stating that they may be invited by phone to participate in a face-to-face research interview concerning women’s “health habits, drug and alcohol use, pain and mental health.” Women who did not wish to be contacted indicated this by returning the mailed information sheet (n⫽189). Women were then randomly selected to receive telephone recruitment calls (n⫽1,794). Recruitment calls were staggered in waves over a nine-month period to allow for prompt scheduling. Recruitment calls and interviews were conducted between January and September 2001, when funding for the project ceased. Administrative data from the VA National Patient Care Database were used for the analysis of selection bias among interview participants and eligible nonparticipants. The University of Washington Institutional Review Board approved the study. The PTSD interviews were conducted as part of a larger VA funded study of Veteran Women’s Alcohol Problems. The interviews took place at either the Seattle or the American Lake Divisions of the VA Puget Sound Health Care System (VA PSHCS). Prior to the interview, patients completed several self-administered measures. These included the PCL and the veteran’s version of Medical Outcomes Study SF-36 V to assess health related quality of life [29, 30]. Following completion of these measures, a trained research associate administered the Alcohol Use Disorder and Associated Disabilities Interview Schedule (AUDADIS); a validated structured lay interview to diagnose substance use disorders [31]. After the AUDADIS was completed, a clinician performed the Clinician-Administered PTSD Scale (CAPS) interview [32,33]. Clinician interviewers were blind to all self-report and AUDADIS results and had no information about the participants prior to interview. Informed consent was obtained prior to each interview. Participants received $35.00 upon completion of the interview. 2.2. Measures 2.2.1. PTSD Checklist (PCL) The PTSD checklist is a 17-item self-administered questionnaire that assesses the full domain of DSM-IV PTSD symptoms. It inquires about the three symptom clusters of PTSD: five re-experiencing symptoms, seven numbing/ avoidance symptoms, and five hyper-arousal symptoms (DSM-IV criteria B, C and D, respectively) [28]. We used

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the civilian version of the measure, which asks respondents to rate past-month symptoms of PTSD referent to “a past stressful experience” on a 1–5 Likert scale. The sum of all responses generates a total score that ranges from 17– 85. In this study, a PCL was considered complete only if patients completed at least 16 of the total 17 items. In the 15 participants who skipped one item, the score for the missing item was imputed using the average value of the remaining items within the symptom cluster. The PCL was initially developed and validated in samples of Vietnam and Persian Gulf Veterans [28]. It has also been used successfully to measure PTSD symptoms in mixed gender populations of civilian trauma patients [34], in survivors of cancer [13,35], and in parents of pediatric cancer patients [36]. The score providing the optimal screening cut-point has ranged from 35 to 50 among these studies, depending on the clinical sample and the particular criterion measure of PTSD used as a “gold standard” comparison test. 2.2.2. Clinician Administered PTSD Scale (CAPS) The CAPS is a structured interview developed by the National Center for PTSD to diagnose current and lifetime PTSD as defined in DSM-IV [33]. The CAPS provides a structured assessment of the 17 PTSD symptoms (DSM-IV criteria B-D) measured by the PCL, assigning each symptom a score of 0 – 4 for past month frequency (never to almost always) and 0 – 4 for intensity (none to resulting in extreme functional impairment). The score on these two domains are summed for each item to create an overall severity score for each symptom (range 0 – 8). The CAPS interview also standardizes the assessment of trauma exposure (DSM-IV criterion A), symptom duration (criterion E), and functional impairment (criterion F). Since its introduction in 1990, the CAPS’ psychometric properties and its utility in research and clinical settings have been extensively documented [37]. We used the diagnostic version of the CAPS interview to assess past-month diagnosis of PTSD. Trauma exposure was assessed by first reviewing lifetime trauma history based on an interview checklist administered at the beginning of the CAPS interview. If a subject reported exposure to more than three traumatic experiences, we asked her to select the three traumatic experiences that she felt had affected her the most. We then reviewed these experiences in more detail to determine which, if any, met full DSM-IV criterion A for significant trauma exposure. If the trauma(s) met criterion A, the remainder of the interview was conducted to evaluate the subject’s current (past-month) PTSD symptoms as related to the qualifying traumatic event(s). Many different rules for scoring the CAPS have been proposed. We scored the CAPS based on the “rule of 4” [38, 39]. The sum of the frequency and intensity scores for each symptom needed to be ⱖ4 for a symptom to be positive. The diagnosis of past-month PTSD required that all DSM-IV diagnostic criteria be satisfied, including trauma

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exposure, distribution of positive symptoms, functional disability, and symptom duration of at least one month. The “rule of 4” scoring sets a fairly sensitive threshold for PTSD [38]. Nonetheless, this threshold has been shown to be specific enough to selectively identify individuals with PTSD who also endorse functional impairment [39]. The CAPS primary interviewers were comprised of two MSW psychiatric social workers, one psychiatric research RN, and one psychiatrist (DD), all of whom had experience in treating women with PTSD. The interviewers were trained by the director of the VA PSHCS PTSD program, who has developed national training programs for CAPS interviewing (MM). Training consisted of reviewing didactic oral and written materials and of independently rating four live or videotaped CAPS interviews. Inter-rater reliability was further established by asking each of the primary interviewers to audiotape four research interviews, which were then independently rated by the other interviewers. The interview team also met twice monthly to discuss issues related to administering the CAPS. Due to circumstances unrelated to the study, the two MSW staff were replaced by two doctoral level clinical psychologists during the last 2 months of interviewing. These interviewers underwent the above training. Inter-rater agreement among the interviewers on the CAPS categorical diagnosis of PTSD was 94.8%. 2.3. Analyses To evaluate interview recruitment bias, demographic characteristics obtained from the VA administrative database were compared between CAPS interview participants and all other eligible participants using Student’s t tests or ␹2 statistics as appropriate. The number and type of lifetime traumatic events endorsed by study participants with and without a CAPS diagnosis of PTSD were compared using Student’s t test or the ␹2 statistics as appropriate. Sensitivity, specificity, and positive and negative likelihood ratios were calculated for the PCL using the CAPS diagnosis of PTSD as a gold standard. A receiver operating characteristic (ROC) curve was plotted [sensitivity vs. (1-specificity)] for the PCL compared to a CAPS diagnosis of PTSD. The area under the ROC curve (AUROC) and 95% confidence intervals (95% CI) were calculated to provide additional information about the performance of the PCL relative to the CAPS. All analyses were performed using SPSS 10.0.7 [40]. Receiver operating characteristic (ROC) methods have been used in clinical settings to determine the score on a continuous screening measure that will optimally predict a dichotomous outcome (e.g., having or not having a particular illness.) The ROC curve plots sensitivity vs. (1-specificity) [41]. For most clinically useful tests, the ROC curve has an initial steep section in which sensitivity increases while the false positive rate (1-specificity) changes only minimally. This is followed by a bend in the curve, and then a flattened section where the false positive rate increases

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Table 1 Characteristics of study participants (n ⫽ 282) Mean (s.d.) Age (years) Race White Black Other Marital Status Married/Domestic partner Divorced Widowed Never married Education High school Some college Associate Arts or technical school degree College grad Grad school CAPS diagnosis of PTSD Health-related Quality of Life (SF-36 V) Physical functioning Role-physical Bodily pain General health Vitality Social functioning Role-emotional Mental health

48 (13.7) N (%) 210 (74.5%) 26 (9.2%) 42 (14.9%) N (%) 112 (39.7) 105 (37.2) 23 (8.2) 40 (14.2) N (%) 27 (35.2) 93 (33) 70 (24.8) 47 (16.7) 43 (15.2) 100 (35.5) Mean (s.d.) 60.0 (28.8) 59.7 (32.0) 47.2 (25.0) 53.5 (25.4) 40.6 (24.9) 58.7 (31.5) 67.0 (31.5) 60.5 (23.7)

rapidly with little improvement in sensitivity. The cut-point score that maximizes the detection of true positives and true negatives is the score that results in the sensitivity/(1-specificity) value found at the upper left corner of the curve. Calculation of the area under the ROC curve can be used to compare different diagnostic tests used to screen for the same condition. Potential values for the area under the ROC curve range from .5 (a useless test represented by a diagonal line) to 1.0. 3. Results 3.1. Characteristics of participants Two hundred eighty-two women (11% of eligible pool of participants and 16% of those randomly selected for telephone recruitment) completed both the PCL and the CAPS interview. Demographic characteristics of the participants are presented in Table 1. Table 1 also reports health-related quality of life scores in the sample. Participants (n⫽282) were slightly older (48 years s.d. 14 vs. 46 years s.d 15, P⫽0.03) and more often divorced (32% vs. 26%, P⫽0.09) than eligible nonparticipants (n⫽2,263). There were no significant differences in race between participants and eligible nonparticipants. One hundred (36%) of the participants had a CAPS diagnosis of PTSD. The number of lifetime traumatic events endorsed during the CAPS interview and the frequencies of various types of traumatic events are presented in Table 2. Women with

PTSD reported significantly more lifetime trauma exposure and were more likely to have experienced interpersonal assaultive violence (sexual or physical assault in childhood or adulthood). Among women with a CAPs diagnosis of PTSD, 99% reported exposure to assaultive violence and 51% reported rape or sexual assault in the military. Notably, 24% of all the study participants (with or without PTSD) reported a history of rape or sexual assault in the military. 3.2. Performance of the PCL The mean score on the PCL for the entire interview group was 37.6⫾18.3 s.d. with a median value of 31.0. Women with PTSD had a mean score on the PCL of 52.9⫾17.7 s.d.; those without PTSD had a mean score of 29.2⫾12.3 s.d. Fig. 1 depicts the ROC curve for the PCL compared with diagnoses of PTSD based on the CAPS. The area under the ROC curve⫽0.86 (95% C.I. ⫽ 0.82– 0.90). A cut-point of 38 on the PCL was associated with a specificity of .79 and a sensitivity of .79 (Table 3). Using this screening cut-point of 38, 41.5% (117) of the CAPS interview participants would screen positive for PTSD. Thus, the proposed screening cut-point overestimates the CAPS-defined prevalence of PTSD in our sample by about 6%, acceptably accurate for a screening measure. The sensitivity, specificity, and positive and negative likelihood ratios of the PCL using other screening cut-points that have been recommended in the literature are also presented in Table 3. The likelihood ratio is a constant that can be used to calculate the probability that a patient has a condition based on a positive or negative screening test result. The computational formula for using likelihood ratios to calculate post-test probability of disease is shown in the legend for Table 3. Using this formula, if we were to estimate the baseline pretest probability of PTSD in our sample to be 36% (based on 36% of the women interviewed having a CAPS diagnosis of PTSD), the probability that a particular individual would have PTSD if she scored 38 or more on the screening PCL rises to 68%. The likelihood ratio can be similarly used to calculate post-test probabilities of disease for other populations that may have a different estimated pretest prevalence of PTSD.

4. Discussion The PCL performed well as a screening measure for the detection of CAPS-diagnosed PTSD in female VA patients participating in this study. A PCL cut-point score of 38 optimized specificity and sensitivity of the test and so appeared to be the best screening cut-point in this population. A secondary finding was that the female VA patients recruited for this study reported high rates of lifetime trauma exposure and had a high prevalence of past-month PTSD based on the CAPS interview. The women with PTSD were more likely to endorse a history of physical or sexual as-

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Table 2 Lifetime trauma exposure in study participants

Number of traumatic events (mean ⫾ s.d.) Type of traumatic event Adult sexual trauma Rape Other sexual assault Military rape or sexual assault Childhood trauma Rape Sexual molestation Physical abuse Serious neglect Assault trauma Threatened with weapon, held captive, or kidnapped Serious physical attack/assault Domestic violence Other military trauma Combat Exposure to death/serious injury as medical provider Military duty-related trauma (not in direct combat) Traumatic loss Shock because of the sudden death of someone close Early loss of child (miscarriage/stillbirth) Other trauma Life-threatening accident Witnessed death or serious injury of another person Natural disaster (flood, fire, earthquake, etc) Hospitalized for serious life-threatening illness Any lifetime assaultive violence (rape, sexual assault, physical assault, or combat)

PTSD negative participants N ⫽ 182

PTSD positive participants N ⫽ 100

P-Value

3.85 ⫾ 2.32 N (%)

6.19 ⫾ 2.51 N (%)

0.000*

35 (19.2) 14 (7.7) 17 (9.3)

50 (50.0) 19 (19.0) 51 (51.0)

0.000* 0.005 0.000*

16 (8.8) 42 (23.1) 50 (27.5) 24 (13.2)

27 (27.0) 51 (51.0) 51 (51.0) 28 (28.0)

0.000* 0.000* 0.000* 0.002*

52 (28.6) 62 (34.1) 42 (23.1)

60 (60.0) 66 (66.0) 40 (40.0)

0.000* 0.000* 0.003*

11 (6.0) 17 (9.3) 20 (11.0)

8 (8.0) 9 (9.0) 11 (11.0)

0.531 0.925 0.998

84 (46.2) 12 (6.6)

56 (56.0) 8 (8.0)

0.114 0.660

48 (26.4) 71 (39.0) 78 (42.9) 43 (23.6) 127 (69.8)

38 (38.0) 51 (51.0) 44 (44.0) 23 (23.0) 99 (99.0)

0.042 0.052 0.853 0.905 0.000*

* P-values are significant at alpha ⱕ 0.003 (Bonferroni adjustment for multiple (N ⫽ 20) comparisons).

sault. This is consistent with previous studies demonstrating that PTSD is most likely to be associated with rape and other forms of interpersonal assaultive violence [2– 4]. The PCL cut-point of 38 identified in this study is lower than described in Vietnam combat veterans and in civilians recently exposed to trauma. In male Vietnam combat veterans, the optimal cut-point for screening for PTSD with the PCL is 50 (sensitivity 0.82, specificity 0.84) [28]. In a civilian sample of recently traumatized men and women, the optimal screening threshold was reported to be 44[34]. Recommended cut-points for oncology patients and their families have ranged from to 35 to 50 or greater [13,36]. A recent study of PTSD screening in an HMO sample of women recommended a screening threshold of 30[42]. The performance of the PCL in our sample at these thresholds is presented in Table 3 for comparison purposes. The differences found between the optimal PCL cutpoints in the present study and others is not surprising. The optimal PCL cut-point is expected to vary somewhat with the clinical context, as recommended cut-points are designed to maximize diagnostic accuracy and utility in a specific population. These differences likely reflect several differences in patient characteristics and in study design. Participants in our study were not restricted to recently traumatized individuals or to those seeking mental health

treatment. Thus, compared with veterans in a PTSD clinic, they may have underreported symptoms on the PCL due to social desirability bias. Underreporting of symptoms is observed in other self-report instruments that inquire about sensitive mental health conditions [43– 45]. Supporting this possibility in our study, the false negative rate on the PCL was 15% (sensitivity of 85%) even at a low cut-point of 30 (Table 3). Another explanation for the lower cut-point may be that women in our study, while meeting diagnostic criteria for PTSD, were less severely ill than those in studies that selected for recent trauma or who were selected from a PTSD clinic. Consistent with this explanation are the lower mean PCL scores in our sample (mean⫽37.6) compared with those reported by Blanchard et al. (mean⫽45.8) [34]. The differences in optimal cut-point may also reflect the use of a different criterion standard. Several of the other validation studies of the PCL used the PTSD module of the SCID interview [46] rather than the CAPS to diagnose PTSD. The CAPS may be a more reliable measure of PTSD than the SCID [37]. Despite these differences, our cut-point of 38 is comparable to that reported in a recent abstract by Spiro et al. [47], who found that a cut-point of 42 optimized performance of the PCL in a similarly unselected sample of male VA ambulatory care patients. The choice of the optimal cut-point for a diagnostic test

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Fig. 1. Receiver Operating Characteristic Curve (sensitivity vs. (1-specificity)) for PCL score vs. CAPS diagnosis of PTSD.

hinges on the consequence of a positive or negative result. If the anticipated consequence of positive PCL test is not onerous (e.g., the patient’s provider would inquire further into psychiatric symptoms, a likely scenario if the PCL were used in waiting room screening), then a case can be made for using a lower (more sensitive) PCL screening cut-point. Conversely, a more specific cut-point may have greater utility in certain research applications, where diagnostic accuracy may be more essential. To assist providers with the interpretation of PCL scores in female VA patients in other settings, we have presented the likelihood ratios, which have advantages over positive or negative predictive value in determining the clinical implications of a positive or negative diagnostic screening test [48]. A likelihood ratio can be used to estimate the post-test prevalence of a condition following a screening test while taking into account

pretest prevalences that may vary in different clinical settings. It is thus more useful in comparing a screening test across populations than reporting the predictive value of a negative or positive test. The prevalence rate of past-month PTSD in our study, as diagnosed by the CAPS interview, was 36%. This high prevalence can be explained in part by selection bias. PTSD is associated with higher health care utilization [10]. Women who volunteered to appear for an interview at the medical center are likely to be higher utilizers of care and hence to have a higher prevalence of PTSD. Furthermore, we did not attempt to exclude women who were being currently followed for VA mental health care. Indeed, interview recruitment materials did indicate that mental health issues would be addressed. Nonetheless, data from other sources suggest that PTSD is commonly encountered in both men and women treated in VA settings. A past month PTSD screening prevalence of 21% was reported in male VA patients seen in an ambulatory care clinic [49]. Similarly, using a conventional combat veteran-derived PCL cut-point of 50, we recently reported that 21% of 1,259 female VA patients at the VAPSHCS (representing 65% of those surveyed) screened positive for PTSD on a 1998 mailed survey [50]. Since female gender is a risk factor for the development of PTSD, a higher screening prevalence of PTSD among female than male veteran patients would not be an unexpected observation. Indeed, a reanalysis of the 1998 survey data, using this new threshold score of 38, results in a past-month PTSD screening prevalence of 32% in the 1998 survey sample. The PCL screening prevalence rate of PTSD of 41.5% among participants in the CAPS interview sample is higher than the 32% screening prevalence noted in our reanalysis of data from the broader 1998 survey sample, again consistent with some interview sample bias. This study was conducted at one VA Health Care System with a group of predominantly Caucasian female VA patients who volunteered for a research interview that con-

Table 3 Performance of PCL in study participants PCL score

Sensitivity

Specificity

Positive likelihood ratio* (95% confidence interval)

Negative likelihood ratio* (95% confidence interval)

ⱖ30 ⱖ38 ⱖ44 ⱖ50 ⱖ60

85% 79% 68% 58% 41%

64% 79% 86% 92% 97%

2.38 (1.93–2.94) 3.78 (2.80–5.11) 4.69 (3.20–6.87) 7.54 (4.44–12.81) 12.44 (5.47–28.27)

0.23 (0.14–0.38) 0.26 (0.18–0.39) 0.38 (0.29–0.51) 0.45 (0.36–0.58) 0.61 (0.52–0.72)

* Computational formula using likelihood ratio to estimate post-test prevalence of PTSD based on pre-test estimate of prevalence of PTSD in a sample: R post ⫽

LR ⫻ Rpre (LR ⫻ Rpre) ⫹ (1 ⫺ R pre)

where LR ⫽ likelihood ratio, Rpre ⫽ estimated pre-test prevalence in a sample, Rpost ⫽ post-test prevalence Positive likelihood ratio is used to estimate prevalence of PTSD if the PCL test is positive; negative likelihoodratio is used to estimate the prevalence of PTSD if the PCL is negative.

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cerned sensitive issues. Although response bias analyses indicated that participants were demographically representative of our local female VA patient population, the findings cannot be generalized to women in general, or to all female veterans. This study is cross-sectional and relies on patients’ retrospective reporting of traumatic events. We cannot prospectively assess the temporal relationship between trauma exposure and PTSD symptoms. Conducting the CAPS interview following the AUDADIS interview may also have affected our results. Participants may have been more willing to discuss their psychiatric symptoms during the clinical CAPS interview following the elicitation of symptoms of affective disorders during the AUDADIS. Despite these limitations, the rates of military sexual assault and domestic violence observed in this study are comparable to screening rates reported in other studies of female VA patients [18 –20,23,51]. Furthermore, the health related quality of life scores reported in this sample are extremely similar to those reported in women in other VA medical centers nationwide [52]. Hence, we expect that our observations will be applicable to female patients in other VA facilities. Given the prevalence of trauma exposure, and the negative effects of PTSD on health and health-related quality of life in veteran women [7,11,53], there is a compelling rationale for screening for PTSD among female VA patients. These findings suggest that the PCL appears to perform well as a screening measure in this population. It also appears to be acceptable to large numbers of women when included in mailed survey instruments [49,50]. However, some data suggests that the PCL may perform better for the overall detection of PTSD than it does for the assessment of individual PTSD symptoms. Furthermore, the longitudinal validity of the PCL in measuring change in individual PTSD symptoms in response to specific treatment needs to be definitively established [54]. PTSD is only one of several mental disorders vying for assessment in primary care settings. Future research should be aimed at identifying valid screening measures for PTSD that are briefer than the PCL for use in primary care settings. Several briefer screens for PTSD have been proposed and others are under active development [55–57]. Nonetheless, the availability of a validated instrument to screen for PTSD in women served in VA settings is a first step in recognizing and designing interventions to treat this common and disabling condition.

Acknowledgments The authors acknowledge the invaluable assistance of Kirsten Rhode, R.N., Denise Pritzl MSW, Nancy Heller MSW, Tracy Simpson PhD, and Kristy Straits-Troster PhD. Supported by grants from the VA Epidemiologic Research and Information Center (EPC 97-010); VA Health Services Research and Development (GEN 97-022); and by the

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VISN 20 Mental Illness Research, Education, and Clinical Center. Dr Bradley is supported by the Robert Wood Johnson Foundation as a Generalist Physician Faculty Scholar and by the National Institute of Alcohol Abuse and Alcoholism (NIAAA #K23AA00313).

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