J Behav Med DOI 10.1007/s10865-015-9628-3

Chronic pain and comorbid mental health conditions: independent associations of posttraumatic stress disorder and depression with pain, disability, and quality of life Samantha D. Outcalt1,2,3,9 • Kurt Kroenke1,3,4 • Erin E. Krebs5,6 • Neale R. Chumbler7 Jingwei Wu8 • Zhangsheng Yu8 • Matthew J. Bair1,3,4

•

Received: September 24, 2014 / Accepted: March 9, 2015 Ó Springer Science+Business Media New York (outside the USA) 2015

Abstract Both posttraumatic stress disorder (PTSD) and depression are highly comorbid with chronic pain and have deleterious effects on pain and treatment outcomes, but the nature of the relationships among chronic pain, PTSD, and depression has not been fully elucidated. This study examined 250 Veterans Affairs primary care patients with moderate to severe chronic musculoskeletal pain who participated in a randomized controlled pain treatment trial. Baseline data were analyzed to examine the independent associations of PTSD and major depression with multiple domains of pain, psychological status, quality of life, and

disability. PTSD was strongly associated with these variables and in multivariate models, PTSD and major depression each had strong independent associations with these domains. PTSD demonstrated similar relationships as major depression with psychological, quality of life, and disability outcomes and significant but somewhat smaller associations with pain. Because PTSD and major depression have independent negative associations with pain, psychological status, quality of life, and disability, it is important for clinicians to recognize and treat both mental disorders in patients with chronic pain.

Trial registration: clinicaltrials.gov Identifier: NCT00926588.

Keywords Chronic pain
PTSD
Depression
Veterans
Quality of life
Disability

& Samantha D. Outcalt [email protected] 1

Department of Veterans Affairs, Veterans Health Administration, Health Services Research and Development Service CIN 13-416, Center for Health Information and Communication, Indianapolis, IN, USA

2

Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA

3

Regenstrief Institute, Inc., Indianapolis, IN, USA

4

Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA

5

Center for Chronic Disease Outcomes Research, Minneapolis VA Health Care System, Minneapolis, MN, USA

6

Department of Medicine, University of Minnesota Medical School, Minneapolis, MN, USA

7

Department of Health Policy and Management, College of Public Health, University of Georgia, Athens, GA, USA

8

Department of Biostatistics, Indiana University School of Medicine, Indianapolis, IN, USA

9

Roudebush VA Medical Center, 1481 W. 10th St. (11H), Indianapolis, IN 46202, USA

Introduction The high co-prevalence of mental health conditions with chronic pain has been documented extensively (Bair et al., 2003; Banks & Kerns, 1996; Bosco et al., 2013; Haythornthwaite et al., 1991; Otis et al., 2003) and multiple studies have demonstrated that emotional distress contributes to more intense pain, greater pain-related disability, and poorer response to chronic pain treatment (Sherman et al., 2000). A large body of literature examines chronic pain and depression co-occurrence (Bair et al., 2003). Although comparatively fewer studies have examined the overlap of PTSD and chronic pain, recent attention has focused on the unique features of this comorbidity. For example, chronic pain and PTSD are characterized by parallel clinical characteristics, such as behavioral avoidance, heightened physiological arousal, and certain maladaptive thought patterns (Beck & Clapp, 2011; Bosco et al., 2013; Otis et al., 2003, 2009). Multiple theories

123

J Behav Med

(Asmundson et al., 2002; Otis et al., 2006; Sharp & Harvey, 2001) have been proposed to explain how chronic pain and PTSD may develop from the same risk factors and/or serve to exacerbate and maintain one another over time. Studies examining PTSD and chronic pain find considerable overlap of PTSD with depression (Alschuler & Otis, 2012; Jakupcak et al., 2006; Outcalt et al., 2014). A recent study of US Veterans (Runnals et al., 2013) found that PTSD predicted more pain complaints independent of depression, but noted considerably higher rates of pain complaints among those with both PTSD and depression. This raises the question of whether the impact of PTSD on chronic pain is predominantly explained by the strong and reciprocal relationship between chronic pain and depression (Kroenke et al., 2011). Some researchers have approached this issue by controlling for depression when examining the relationship between PTSD and pain and have concluded that PTSD remains influential even after accounting for depression (Outcalt et al., 2014). Other investigators have argued that statistically controlling for depression omits an essential affective component of PTSD (Alschuler & Otis, 2012) and have chosen not to include depression as a covariate in their pain-PTSD models. A third approach has to been to test depression as a potential mediator of the effect of PTSD on chronic pain. Morasco et al. (2013) found that depression partially mediated the relationship between PTSD and pain interference, but not pain severity. However, in a separate study, the associations between PTSD and both pain interference and severity were partially mediated by depression symptoms and pain coping strategies (Kelsall et al., 2014). Irwin et al. (2014) examined depression, anxiety, and alcohol use as potential mediators of the pain-PTSD relationship and found support for mediation by depression and anxiety symptoms. In another test of mediation, Poundja et al. (2006) found that PTSD did not predict pain when depression was included as a mediator and that the relationship between PTSD and pain was almost entirely (89.5 % of the variance) explained by depression. Similarly, Jakupcak et al. (2006) found that depression might serve as a proxy risk variable, leading the authors to conclude that the relationship between PTSD and somatic complaints such as pain is explained by depression (and anxiety sensitivity) rather than by PTSD itself. Finally, others have suggested that PTSD directly impacts depression severity which then contributes to pain intensity and disability (Roth et al., 2008). Consensus is lacking with regard to the nature of the relationships between PTSD, depression, and chronic pain. Understanding how these conditions interrelate is essential for designing effective treatments and ensuring high quality care to those who suffer from them. This study examined the independent associations of each disorder, PTSD

123

and depression, because we sought to understand the impact of PTSD on the chronic pain experience, recognized the common comorbidity of PTSD and depression, and wished to elucidate how these two mental health conditions may each contribute to chronic pain. We hypothesized that Veterans with chronic pain and PTSD would report greater pain, more psychological impairment, worse quality of life, and greater disability than those without PTSD. Additionally, we postulated that both PTSD and depression would have independent adverse associations with these various domains.

Methods Participants and procedure This is a secondary analysis of the Stepped Care to Optimize Pain care Effectiveness (SCOPE) study, a 12-month randomized controlled effectiveness trial testing whether a collaborative care intervention for primary care patients with chronic musculoskeletal pain is superior to usual primary care in reducing pain severity and disability. Study design and sample characteristics of the SCOPE trial have been described in detail elsewhere (Kroenke et al., 2013). Briefly, Veterans with chronic pain were recruited from five primary care clinics at a large Midwestern Veterans Affairs (VA) Medical Center. Physicians working in these clinics were informed of the study in detail and were asked for permission to contact their patients for possible participation in the study. Potential patients of participating physicians were identified through the Computerized Patient Record System (the VA’s electronic medical record). A list of potential patients was created using two criteria: (1) An ICD musculoskeletal pain diagnosis (715, 719, 721, 722, 723, 724, 726, 729.0, 729.1, 729.3, 729.5, 738.4, 738.5); and (2) a primary care visit within the past 12 months. A letter briefly describing SCOPE was mailed to patients on this list who could either contact the study coordinator or return a form indicating their interest in the study or a desire to opt out of further contact. Letters were mailed to 940 patients of whom 311 were contacted by phone (most of these had returned a study form expressing their potential interest in the study). Ten of the patients contacted by phone did not complete an eligibility interview, 29 were ineligible, 22 were eligible but not interested in the trial, and 250 were eligible, consented to participate, and were enrolled. To be eligible, a patient had to have pain that was (a) musculoskeletal, including both regional (joints, limbs, back, neck) and more generalized pain (fibromyalgia or chronic widespread pain); (b) at least moderate to severe, defined by a Brief Pain Inventory (BPI; Cleeland & Ryan,

J Behav Med

1994) intensity score C 5; and (c) persistent (i.e., C3 months) despite trying at least one analgesic medication prior to the trial. Patients were excluded if they had a pending pain-related disability claim, dementia, schizophrenia, bipolar disorder, illicit drug use, active suicidality or an anticipated life expectancy of \12 months. The SCOPE study was approved by the Indiana University Institutional Review Board and the VA Research Review Committee.

the SF-36 Mental Health and Mental Component Summary scales (Ware et al., 1996), the 7-item Generalized Anxiety Disorder (GAD-7) questionnaire (Spitzer et al., 2006), the 4-item Perceived Stress Scale (Cohen et al., 1983), and the 3-item Sense of Coherence Scale (Lundberg & Nystrom, 1995). Health-related quality of life and disability measures

The primary pain measure for this analysis was the Brief Pain Inventory (BPI; Cleeland & Ryan, 1994) total score, which is the mean of pain severity and pain interference items. This self-report questionnaire rates the severity of pain on four items (current, worst, least and average pain in past week) on a scale of 0–10 where 0 indicates no pain and 10 refers to the worst pain imaginable. Seven domains of pain-related functional interference (mood, physical activity, work, social activity, relations with others, sleep and enjoyment of life) are rated with one item each on a scale of 0–10 where 0 designates no interference and 10 indicates complete interference. The BPI total score is a composite of pain severity and interference that has demonstrated sensitivity to change and has been argued as preferable to separate scale scores for its simplicity in assessment and data analysis (Krebs et al., 2010). Secondary pain outcomes included the SF-36 Bodily Pain Scale (McHorney et al., 1993), the PROMIS Pain Profile and the PROMIS Pain Impact Scale (Cella et al., 2010), the Arthritis Self-Efficacy Scale (Lorig et al., 1989), and the Coping Strategies Questionnaire Pain-Catastrophizing Scale (Robinson et al., 1997).

Multiple domains of quality of life were assessed, including social functioning, vitality, and general health perceptions by the SF-36 (Ware & Sherbourne, 1992), overall physical health with the SF-12 Physical Component Summary scale, somatization by the 15-item Patient Health Questionnaire (PHQ) somatic symptom scale (Kroenke et al., 2002), and fatigue and sleep by PROMIS instruments (Cella et al., 2010). Disability was measured by a percentage of work effectiveness, number of general health disability days, and number of pain-specific disability days (Kroenke et al., 2007; Wang et al., 2011). Work effectiveness was assessed with the question: ‘‘On days that you worked during the past 4 weeks, how effective were you in your job on average? On a scale of 0–100, where 0 % means that you were not at all effective and 100 % means that you were completely effective, how effective would you say you have been on your job?’’ General health and pain-specific disability days were assessed with two questions: (a) ‘‘During the past 4 weeks, how many days did you cut down on the things you usually do for one-half day or more because of your physical health or emotional problems?’’ (b) ‘‘How many of these days that you cut down on your activities were because of pain?’’ Thus, a disability day was not linked to work but defined more broadly as one in which the patient had to reduce usual activity by 50 % or more due to physical or emotional health in general or due to pain specifically.

Psychological measures

Statistical analysis

Posttraumatic stress disorder (PTSD) was measured by a two-step procedure: (1) a 4-item screening instrument, the Primary Care PTSD Screen (PC-PTSD; Prins et al., 2004) and, if triggered positive by endorsement of two items on the PC-PTSD, (2) the 17-item Posttraumatic Stress Disorder Checklist (PCL; Blanchard et al., 1996). We categorized participants into the PTSD group if they had a PCL score of at least 41, which has been shown to represent clinically significant posttraumatic stress (Blanchard et al., 1996). The diagnostic algorithm of the Patient Health Questionnaire (PHQ-9; Kroenke et al., 2001) was used to classify patients as having probable major depressive disorder or not. Secondary psychological measures included

Demographic and clinical differences between the PTSD and no PTSD groups (PC-PTSD screen negative or PCL \41) were compared using Chi square tests for categorical variables and two sample independent t tests for continuous variables. Likewise, differences between the two groups on pain, psychological, quality of life, and disability outcomes were tested using Chi square tests and two sample independent t tests. Effect sizes for associations of PTSD with each of these variables were calculated as the mean difference between the PTSD and no PTSD groups divided by the pooled standard deviation. Effect sizes of 0.2, 0.5, and 0.8 are considered small, moderate, and large clinical differences, respectively (Kazis et al., 1989). The independent

Measures Pain measures

123

J Behav Med

associations of PTSD and major depression with pain, psychological, and quality of life were examined in multiple linear regression models that included PTSD and major depression as the primary independent variables and adjusted for the covariates of age, sex, race (white; other), medical comorbidity, and sociodemographic disadvantage index. Medical comorbidity (scored 0–9) was assessed using a checklist of nine common medical conditions shown to predict hospitalization and mortality (Perkins et al., 2004). The sociodemographic index (scored 0–3) assigns one point each for low education (high school or less), unemployment, and low income reported as ‘‘just enough or not enough to make ends meet’’ (Chumbler et al., 2013). From these multivariable models, the beta coefficients for PTSD and major depression represented the independent effect of each disorder on the absolute value of the scale score, that is, the adjusted mean difference between individuals with and without the psychological disorder. Adjusted effect sizes for PTSD and major depression were calculated as the adjusted mean difference divided by the root mean standard error from the model. Disability days were analyzed using a Poisson regression model and by a logistic regression model when dichotomized into high/low disability groups and adjusted for the same set of covariates. Since all participants completed the baseline interview, and all questions were interviewer-administered, there was not a problem of missing data. All analyses were performed using SAS 9.3 (Cary, NC).

Results Patient characteristics The sample included 250 participants with a mean age of 55.1 years (range 28–65); 83 % (n = 207) were men; 77 % were White (n = 192), 19 % Black (n = 48), and 4 % other race (n = 10). Nearly three quarters (74 %, n = 185) had completed at least some college, the same number of participants (74 %, n = 185) were married, most were employed (64 %, n = 160) or retired (20 %, n = 51), and nearly all (90 %, n = 225) reported that they were either comfortable with their current income or had enough to make ends meet. Forty-three participants (17 %) met our criteria for PTSD and 60 (24 %) for depression. Approximately one-third of participants (34 %, n = 84) were prescribed opioid medications at baseline. Nearly every patient (92 %, n = 231) reported more than one site of pain and pain had lasted for more than 10 years for over half the sample (52 %, n = 131). Of the 250 patients in the study sample, 43 (17.2 %) met the PTSD criteria. As shown in Table 1, patients with and without PTSD were similar in terms of most sociodemo-

123

graphic characteristics. The exceptions were that patients without PTSD were more likely to be white (78.7 vs. 67.4 %) and much less likely to meet criteria for major depression (15.9 vs. 62.8 %). Association of PTSD with pain, psychological, quality of life, and disability domains PTSD was strongly associated with nearly all pain, psychological, health-related quality of life, and disability domains (see Table 2). Moreover, the magnitude of the adverse association between PTSD and most domains was large (effect size of 0.80 or greater) except for the few domains where the effect size was moderate (0.50–0.61; general health and disability days) or small (0.20–0.49; pain severity, physical component summary, and work effectiveness). Incidentally, it is unknown how ‘‘work’’ effectiveness was interpreted by participants who were not employed at the time of assessment; however, 247/250 respondents answered this question and 64 % of our sample self-reported that they were employed, 15.6 % that they were unemployed, and 20.4 % retired. Notably, PTSD was associated with a near doubling of the number of healthrelated disability days (14.6 vs. 7.9) over the past month and a large effect size (i.e., exceeding 1.0) for most pain and psychological domains. Independent associations of PTSD and major depression The majority of the sample had neither PTSD nor major depression (69.6 %, n = 174), while 13.2 % (n = 33) had PTSD only, 6.4 % (n = 16) had major depression only, and 10.8 % (n = 27) had both. As shown in Table 3, PTSD and major depression have independent and, for many domains, similarly sized negative associations with pain, psychological status, health-related quality of life, and disability domains in adjusted models that included both PTSD and depression. The adjusted mean differences (which are the beta coefficients for PTSD and major depression derived from the multivariable models) show the effect that the two mental disorders have on the absolute scale scores. For example, the presence of PTSD increases, on average, the BPI pain interference score by an average of 1.2 points (after controlling for major depression and other covariates), while the presence of major depression increases the BPI pain interference score by an average of 1.7 points. These absolute scores represent, in turn, adjusted effect sizes of 0.61 for PTSD and 0.91 for major depression, respectively. Also, as expected, PTSD and major depression had their strongest associations with the mental component summary score (adjusted effect sizes of 1.32 and 1.41, respectively)

J Behav Med Table 1 Comparison of chronic pain patients with and without posttraumatic stress disorder (PTSD) Variable

No PTSDa (n = 207)

Age in years [mean (SD)]

PTSDb (n = 43)

P value

55.6 (8.3)

.72

55.1 (8.5)

Male [n (%)]

170 (82.1)

37 (86.0)

.54

White [n (%)]

163 (78.7)

29 (67.4)

.001

Education [ high school [n (%)]

153 (73.9)

32 (74.4)

.41

Employed [n (%)]

177 (85.5)

34 (79.1)

.16

Income adequate by self-report [n (%)]

187 (90.3)

38 (88.4)

.70

53 (25.6)

10 (23.3)

Current smoker [n (%)] Comorbid medical diseases [mean (SD)]

2.0 (1.4)

.70

2.3 (1.3)

.21

Major depression [n (%)]

33 (15.9)

27 (62.8)

\.0001

AUDIT-C alcohol use score C4 [n (%)]

50 (24.2)

12 (27.9)

.60

N (%) with no PTSD or Maj Dep, PTSD only, Maj Dep only, and both was 174 (69.6 %), 33 (13.2 %), 16 (6.4 %), and 27 (10.8 %) No PTSD group defined by negative screen on PC-PTSD or PCL \41

a

b

PTSD group defined by positive screen on PC-PTSD and PCL C41

Table 2 Association of PTSD with pain, psychological, quality of life, and disability domains Variablea

No PTSD (n = 207)

PTSD (n = 43)

P value

Effect sizeb

Pain measures BPI total [0–10]

5.0 (1.8)

6.4 (1.6)

\.0001

0.78

BPI interference [0–10]

4.9 (2.1)

7.0 (1.9)

\.0001

0.94

BPI severity [0–10]

5.0 (1.7)

5.8 (1.6)

.005

0.47

ASES pain self-efficacy [1–10]

6.6 (2.0)

4.8 (2.3)

\.0001

0.83

CSQ pain catastrophizing [0–60]

9.6 (7.3)

19.0 (8.9)

\.0001

1.13

4.4 (4.3)

13.2 (5.6)

\.0001

1.57

Psychological measures GAD-7 anxiety [0–21] SF-36 mental health [0–100]

75.5 (17.9)

43.6 (19.5)

\.0001

1.47

SF-12 mental component [norm = 50]

51.3 (10.0)

33.6 (11.8)

\.0001

1.44

PHQ-9 depression [0–27]

7.7 (5.4)

15.9 (5.5)

\.0001

1.31

Perceived stress [0–16]

4.2 (3.4)

8.5 (4.2)

\.0001

1.11

Sense of coherence [0–6]

1.1 (1.2)

2.7 (1.7)

\.0001

1.10

SF-36 social functioning [0–100]

72.3 (24.3)

40.1 (24.8)

\.0001

1.18

PHQ-14 somatization [0–28] PROMIS fatigue [4–20]

9.6 (4.4) 11.7 (4.2)

13.9 (3.7) 15.8 (3.0)

\.0001 \.0001

0.95 0.95

PROMIS sleep [4–20]

12.1 (4.1)

15.8 (3.6)

\.0001

0.86

SF-36 vitality [0–100]

43.9 (21.9)

24.4 (18.7)

\.0001

0.86

Quality of life measures

SF-36 general health [0–100]

54.5 (28.0)

35.5 (28.9)

\.0001

0.66

SF-12 physical component [norm = 50]

36.0 (9.4)

32.7 (7.2)

.028

0.36

Disability days, health-relatedc [0–28]

7.9 (7.9)

14.6 (9.4)

.0002

0.61

Pain-specific disability daysc [0–28]

7.1 (7.8)

12.4 (9.3)

.0004

0.59

Percent work effectiveness [0–100]

74.0 (22.6)

62.3 (25.4)

.003

0.50

Disability measures

a

Numbers in brackets are minimum–maximum scale score. Bolded number is the worst score

b

Effect size = between-group difference divided the pooled SD for the entire sample. Effect sizes of 0.2, 0.5, and 0.8 represent small, moderate, and large differences c

P values and effect sizes for disability days are computed with two-sample t test using log-transformed values due to skewness

123

J Behav Med Table 3 Independent associations of PTSD and major depression with selected symptom and health-related quality of life domains in multivariable linear regression models Variable

Adjusted mean differencea

Adjusted effect size

P value

PTSD

PTSD

Major Dep

PTSD

Major Dep

Major Dep

BPI pain total score

0.75

1.20

0.47

0.75

.01

\.0001

BPI pain interference

1.15

1.72

0.61

0.91

.001

\.0001

BPI pain severity

0.34

0.69

0.21

0.42

.27

.016

-0.78

-1.92

0.43

1.07

.022

\.0001

CSQ pain catastrophizing

5.17

7.84

0.80

1.21

\.0001

\.0001

SF-12 Mental Component

-11.50

-12.34

1.32

1.41

\.0001

\.0001

SF-36 social functioning PHQ-14 somatization

-20.34 2.60

-24.64 3.24

0.94 0.73

1.14 0.92

\.0001 .0001

\.0001 \.0001

SF-36 vitality

-12.59

-13.84

0.68

0.75

.0003

\.0001

-9.32

-12.00

0.39

0.50

.039

.004

PROMIS fatigue

2.62

3.04

0.73

0.85

.0001

\.0001

PROMIS sleep

2.42

2.86

0.65

0.77

.0006

\.0001

ASES pain self-efficacy

SF-36 general health

Log risk ratio Disability days

b

0.41

Risk ratio 0.42

1.51

P value 1.52

\.0001

\.0001

Multivariable models included PTSD and major depression as the primary independent (predictor) variables and adjusted for the covariates of age, sex, race, sociodemographic disadvantage index, medical comorbidity a PTSD and major depression were associated with worse scores on all domains, with the signs for adjusted mean differences being positive for domains where a higher score is worse and negative where a lower score is worse b

For disability days, Poisson modeling was used since these are count data. All other models use GLM. Risk ratio represents the increased number of disability days attributable to PTSD or major depression

followed by social functioning (adjusted effect sizes of 0.94 and 1.14, respectively). Adjusted effect sizes and the concomitant P values showed independent associations of PTSD and major depression with all domains except pain severity. The magnitude of effect for many domains was substantial. For example, PTSD and major depression were each associated with more than 20 point decreases in SF-36 social functioning and SF mental component scores, a 9.3 point decrement in general health, and a 13.8 point decrease in vitality.

major depression, compared to only 23 % of patients without depression (P \ .0001). Logistic regression modeling, adjusting for age, sex, medical comorbidity, and socioeconomic disadvantage index showed that the adjusted odd ratios (95 % CI) for high disability were 3.6 (1.6–7.9) for PTSD and 3.0 (1.5–6.1) for major depression. Thus, PTSD is as strong as major depression in predicting high disability among chronic pain patients.

Discussion Associations of PTSD and major depression with disability days The independent associations of PTSD and major depression with number of disability days are equivalent as demonstrated by their identical risk ratios of 1.51 and 1.52 (see Table 3). This means that PTSD and major depression each increase the number of disability days by more than 50 %. Both disorders were strong predictors of high disability, which we defined as reducing activity by 50 % or more because of physical or emotional health for at least two of the past four weeks. High disability was reported by 65 % of PTSD patients, as compared to only 25 % of nonPTSD patients (P \ .0001), and by 62 % of patients with

123

To our knowledge, this is the first study to examine both PTSD and depression in the same statistical model to determine independent contributions of each on chronic pain and related variables; it has several important findings. First, PTSD is strongly associated with multiple domains of pain, psychological status, quality of life, and disability. Second, these associations remain robust even after controlling for the presence of major depression. Third, the magnitude of association with pain, psychological, and disability domains is similar for PTSD and depression. Fourth, both PTSD and major depression are strongly associated with disability, with the presence of PTSD or major depression each increasing the number of health-

J Behav Med

related disability days by more than 50 % and each disorder tripling the likelihood of high disability, even after controlling for one another. Taken together, these results suggest that PTSD has an independent influence on painrelated variables and that depression neither confounds nor explains the relationship between PTSD and chronic pain. We did not aim to parcel out depression from the effect of PTSD but instead treated both depression and PTSD as two independent variables and found that each contributed its own substantial relationship. Our findings are consistent with studies demonstrating that PTSD and depression have independent (but additive) effects on suicidal thoughts and behavior (Cougle et al., 2009), uniquely predict different HIV indicators and adherence behaviors (Boarts et al., 2006), and differentially impact the burden of physical illness and use of mental health services (Possemato et al., 2010). Likewise, an analysis of motor vehicle accident survivors concluded that although PTSD and depression are correlated and highly co-prevalent, they have independent effects (Blanchard et al., 1998). Collectively, these papers demonstrate unique contributions of PTSD and depression in multiple realms of mental health and health psychology. Our study adds to this literature by showing their independent effects on the experience of chronic pain. Our results suggest independent effects of each mental health condition, which may differ from the mediating influence of comorbid depression on the relationship between PTSD and chronic pain found in other studies (Jakupcak et al., 2006; Morasco et al., 2013; Poundja et al., 2006; Roth et al., 2008). A strict mediational model would assume that, in addition to PTSD predicting pain severity or pain interference, PTSD also causes or predicts depression. PTSD and depression are highly coprevalent as confirmed by a recent meta-analysis that yielded a 52 % rate of comorbid major depressive disorder among those with current PTSD (Rytwinski et al., 2013). However, it is not yet clear whether one predicts the other. Indeed, a bidirectional relationship is plausible, where some patients might have lived with depression prior to a traumatic incident and were thus at greater risk of developing PTSD and others may have developed depression in response to a traumatic event either concurrently or after the development of PTSD. It is also possible that an inherited vulnerability or another variable predisposes an individual to developing both PTSD and depression. Our study has several limitations. First, cross-sectional analysis demonstrates strong associations of PTSD and major depression with multiple outcomes but does not allow for conclusions about causation or directionality of effects. Second, this was a largely male sample of Veterans, so findings may not generalize to non-Veteran populations. Additionally, based on previous reports of mental health screening of Veterans with chronic pain

where women screened positive more frequently than men for depression and less frequently for PTSD (Haskell et al., 2010), our findings may not generalize to samples with greater gender diversity or those with all women. Third, we did not use a gold standard structured diagnostic interview to identify PTSD; however, we used well-validated cutoffs on established measures. Fourth, since this study used the DSM-IV-TR criteria for PTSD, the estimate of depression’s relative contribution may be inflated by affective elements of PTSD. Future research in this area would benefit from the use of DSM-5 PTSD criteria, which better account for negative affect and cognitions. Despite these limitations, this paper contributes to the literature with a comprehensive evaluation of the biopsychosocial aspects of chronic pain, including pain interference, cognitions such as pain self-efficacy and catastrophizing, quality of life factors, and pain-related disability. The clinical implications of this research include the importance of assessing both PTSD and depression among patients with chronic pain; VA primary care clinics routinely screen for symptoms of both disorders and patients may benefit from the adoption of this policy in non-VA primary care settings as well. When positive screens are identified for PTSD, depression, or both conditions, it is important for primary care providers to ensure that behavioral health care is incorporated into the patient’s overall treatment plan. Also, since PTSD and major depression have strong and independent adverse effects, it is likely that some patients with chronic pain who are suffering from both mental disorders require more intensive therapy. Longitudinal studies are warranted to further untangle the complicated relationships of PTSD, depression, and chronic pain. Meanwhile, simple measures to screen for both conditions are available and should be used to identify a subset of chronic pain patients at risk of worse pain, more impairment, and greater disability. Acknowledgments This work was supported by a Department of Veterans Affairs Health Services Research and Development (VA HSR&D) Merit Review award to Dr. Kroenke (IIR 07-119) and Career Development Award to Dr. Krebs (CDA 07-215). The sponsor had no role in study design; in the collection, analysis and interpretation of data; in the writing of the report; or in the decision to submit the article for publication. The views expressed in this article are those of the authors and do not necessarily represent the views of the Department of Veterans Affairs. Conflict of interest Samantha D. Outcalt, Kurt Kroenke, Erin E. Krebs, Neale R. Chumbler, Jingwei Wu, Zhangsheng Yu, and Matthew J. Bair declare that they have no conflict of interest. Human and animal rights and informed consent All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000 (5). Informed consent was obtained from all patients for being in-

123

J Behav Med cluded in the study. Additional informed consent was obtained from all patients for which identifying information is included in this article.

References Alschuler, K. N., & Otis, J. D. (2012). Coping strategies and beliefs about pain in Veterans with comorbid chronic pain and significant levels of posttraumatic stress disorder symptoms. European Journal of Pain, 16, 312–319. Asmundson, G. J. G., Coons, M. J., Taylor, S., & Katz, J. (2002). PTSD and the experience of pain: Research and clinical implications of shared vulnerability and mutual maintenance models. Canadian Journal of Psychiatry, 47, 930–937. Bair, M. J., Robinson, R. L., Katon, W., & Kroenke, K. (2003). Depression and pain comorbidity. Archives of Internal Medicine, 163, 2433–2445. Banks, S. M., & Kerns, R. D. (1996). Explaining high rates of depression in chronic pain: A diathesis-stress framework. Psychological Bulletin, 119, 95–110. Beck, J. G., & Clapp, J. D. (2011). A different kind of comorbidity: Understanding posttraumatic stress disorder and chronic pain. Psychological Trauma: Theory, Research, Practice, and Policy, 3, 101–108. Blanchard, E. B., Buckley, T. C., Hickling, E. J., & Taylor, A. E. (1998). Posttraumatic stress disorder and comorbid major depression: Is the correlation an illusion? Journal of Anxiety Disorders, 12, 21–37. Blanchard, E. B., Jones-Alexander, J., Buckley, T. C., & Forneris, C. A. (1996). Psychometric properties of the PTSD Checklist (PCL). Behaviour Research and Therapy, 34, 669–673. Boarts, J. M., Sledjeski, E. M., Bogart, L. M., & Delahanty, D. L. (2006). The differential impact of PTSD and depression on HIV disease markers and adherence to HAART in people living with HIV. AIDS Behavior, 10, 253–261. Bosco, M. A., Gallinati, J. L., & Clark, M. E. (2013). Conceptualizing and treating comorbid chronic pain and PTSD. Pain Research and Treatment, 2013, 174728. Cella, D., Riley, W., Stone, A., Rothrock, N., Reeve, B., Yount, S., et al. (2010). The Patient-Reported Outcomes Measurement Information System (PROMIS) developed and tested its first wave of adult self-reported health outcome item banks: 2005–2008. Journal of Clinical Epidemiology, 63, 1179–1194. Chumbler, N. R., Kroenke, K., Outcalt, S. D., Bair, M. J., Krebs, E. E., Wu, J., & Yu, Z. (2013). Association between sense of coherence and health-related quality of life among primary care patients with chronic musculoskeletal pain. Health Quality of Life Outcomes, 11, 216. Cleeland, C. S., & Ryan, K. M. (1994). Pain assessment: Global use of the brief pain inventory. Annals of the Academy of Medicine, Singapore, 23, 129–138. Cohen, S., Kamarck, T., & Mermelstein, R. (1983). A global measure of perceived stress. Journal of Health and Social Behavior, 24, 385–396. Cougle, J. R., Resnick, H., & Kilpatrick, D. G. (2009). PTSD, depression, and their comorbidity in relation to suicidality: Crosssectional and prospective analyses of a national probability sample of women. Depression and Anxiety, 26, 1151–1157. Haskell, S. G., Gordon, K. S., Mattocks, K., Duggal, M., Erdos, J., Justice, A., & Brandt, C. A. (2010). Gender differences in rates of depression, PTSD, pain, obesity, and military sexual trauma among Connecticut war Veterans of Iraq and Afghanistan. Journal of Women’s Health, 19, 267–271. Haythornthwaite, J. A., Sieber, W. J., & Kerns, R. D. (1991). Depression and the chronic pain experience. Pain, 46, 177–184.

123

Irwin, K. C., Konnert, C., Wong, M., & O’Neill, T. A. (2014). PTSD symptoms and pain in Canadian military Veterans: The mediating roles of anxiety, depression, and alcohol use. Journal of Traumatic Stress, 27, 175–181. Jakupcak, M., Osborne, T., Michael, S., Cook, J., Albrizio, P., & McFall, M. (2006). Anxiety sensitivity and depression: Mechanisms for understanding somatic complaints in Veterans with posttraumatic stress disorder. Journal of Traumatic Stress, 19, 471–479. Kazis, L. E., Anderson, J. J., & Meenan, R. F. (1989). Effect sizes for interpreting changes in health status. Medical Care, 27, S178– S189. Kelsall, H. K., McKenzie, D. P., Forbes, A. B., Roberts, M. H., Urquhart, D. M., & Sim, M. R. (2014). Pain-related musculoskeletal disorders, psychological comorbidity, and the relationship with physical and mental well-being in Gulf War Veterans. Pain, 155, 685–692. Krebs, E. E., Bair, M. J., Damush, T. M., Tu, W., Wu, J., & Kroenke, K. (2010). Comparative responsiveness of pain outcome measures among primary care patients with musculoskeletal pain. Medical Care, 48, 1007–1014. Kroenke, K., Bair, M. J., Damush, T. M., Hoke, S., Nicholas, G., Kempf, C., et al. (2007). Stepped care for affective disorders and musculoskeletal pain (SCAMP) study: Design and practical implications of an intervention for comorbid pain and depression. General Hospital Psychiatry, 29, 506–517. Kroenke, K., Krebs, E., Wu, J., Bair, M. J., Damush, T., Chumbler, N., et al. (2013). Stepped Care to Optimize Pain care Effectiveness (SCOPE) trial study design and sample characteristics. Contemporary Clinical Trials, 34, 270–281. Kroenke, K., Spitzer, R. L., & Williams, J. B. (2001). The PHQ-9: Validity of a brief depression severity measure. Journal of General Internal Medicine, 16, 606–613. Kroenke, K., Spitzer, R. L., & Williams, J. B. (2002). The PHQ-15: Validity of a new measure for evaluating the severity of somatic symptoms. Psychosomatic Medicine, 64, 258–266. Kroenke, K., Wu, J., Bair, M. J., Krebs, E. E., Damush, T. M., & Tu, W. (2011). Reciprocal relationship between pain and depression: A 12-month longitudinal analysis in primary care. Journal of Pain, 12, 964–973. Lorig, K., Chastain, R. L., Ung, E., Shoor, S., & Holman, H. R. (1989). Development and evaluation of a scale to measure perceived self-efficacy in people with arthritis. Arthritis and Rheumatology, 32, 37–44. Lundberg, O., & Nystrom, M. (1995). A simplified way of measuring sense of coherence: Experiences from a population survey in Sweden. European Journal of Public Health, 5, 56–69. McHorney, C. A., Ware, J. E., & Raczek, A. E. (1993). The MOS 36-item short-form health survey (SF-36): II. Psychometric and clinical tests of validity in measuring physical and mental health constructs. Medical Care, 31, 247–263. Morasco, B. J., Lovejoy, T. I., Lu, M., Turk, D. C., Lewis, L., & Dobscha, S. K. (2013). The relationship between PTSD and chronic pain: Mediating role of coping strategies and depression. Pain, 154, 609–616. Otis, J. D., Keane, T. M., & Kerns, R. D. (2003). An examination of the relationship between chronic pain and post-traumatic stress disorder. Journal of Rehabilitation Research and Development, 40, 397–406. Otis, J. D., Keane, T. M., Kerns, R. D., Monson, C., & Scioli, E. (2009). The development of an integrated treatment for Veterans with comorbid chronic pain and posttraumatic stress disorder. Pain Medicine, 10, 1300–1311. Otis, J. D., Pincus, D. B., & Keane, T. M. (2006). Comorbid chronic pain and posttraumatic stress disorder across the lifespan: A review of theoretical models. In G. Young, A. W. Kane, & K.

J Behav Med Nicholson (Eds.), Psychological knowledge in court: PTSD, pain, and TBI (pp. 242–268). New York: Springer. Outcalt, S. D., Ang, D. C., Wu, J., Sargent, C., Yu, Z., & Bair, M. J. (2014). Pain experience of Iraq and Afghanistan Veterans with comorbid chronic pain and posttraumatic stress. Journal of Rehabilitation Research and Development, 51, 559–570. Perkins, A. J., Kroenke, K., Unutzer, J., Katon, W., Williams, J. W., Hope, C., & Callahan, C. M. (2004). Common comorbidity scales were similar in their ability to predict health care costs and mortality. Journal of Clinical Epidemiology, 57, 1040–1048. Possemato, K., Wade, M., Andersen, J., & Ouimette, P. (2010). The impact of PTSD, depression, and substance abuse on disease burden and health care utilization among OEF/OIF Veterans. Psychological Trauma, 2(3), 218–223. Poundja, J., Fikretoglu, D., & Brunet, A. (2006). The co-occurrence of posttraumatic stress disorder symptoms and pain: Is depression a mediator? Journal of Traumatic Stress, 19, 747–751. Prins, A., Ouimette, P., Kimerling, R., Cameron, R. P., Hugelshofer, D. S., Shaw-Hegwer, J., et al. (2004). The primary care PTSD screen (PC-PTSD): Development and operating characteristics. Primary Care Psychiatry, 9, 9–14. Robinson, M. E., Riley, J. L, I. I. I., Myers, C. D., Sadler, I. J., Kvaal, S. A., Geisser, M. E., & Keefe, F. J. (1997). The Coping Strategies Questionnaire: A large sample, item level factor analysis. Clinical Journal of Pain, 13, 43–49. Roth, R. S., Geisser, M. E., & Bates, R. (2008). The relation of posttraumatic stress symptoms to depression and pain in patients with accident-related chronic pain. Journal of Pain, 9, 588–596.

Runnals, J. J., Van Voorhees, E., Robbins, A. T., Brancu, M., StraitsTroster, K., Beckham, J. C., & Calhoun, P. S. (2013). Selfreported pain complaints among Afghanistan/Iraq era men and women Veterans with comorbid posttraumatic stress disorder and major depressive disorder. Pain Medicine, 14, 1529–1533. Rytwinski, N. K., Scur, M. D., Feeny, N. C., & Youngstrom, E. A. (2013). The co-occurrence of major depressive disorder among individuals with posttraumatic stress disorder: A meta-analysis. Journal of Traumatic Stress, 26, 299–309. Sharp, T. J., & Harvey, A. G. (2001). Chronic pain and posttraumatic stress disorder: Mutual maintenance. Clinical Psychology Review, 21, 857–877. Sherman, J. J., Turk, D. C., & Okifuji, A. (2000). Prevalence and impact of posttraumatic stress disorder-like symptoms on patients with fibromyalgia syndrome. Clinical Journal of Pain, 16, 127–134. Spitzer, R. L., Kroenke, K., Williams, J. B., & Lo¨we, B. (2006). A brief measure for assessing generalized anxiety disorder: The GAD-7. Archives of Internal Medicine, 166, 1092–1097. Wang, H. L., Kroenke, K., Wu, J., Tu, W., Theobald, D., & Rawl, S. M. (2011). Cancer-related pain and disability: A longitudinal study. Journal of Pain and Symptom Management, 42, 813–821. Ware, J. E., Kosinski, M., & Keller, S. D. (1996). A 12-item shortform health survey: Construction of scales and preliminary tests of reliability and validity. Medical Care, 34, 220–233. Ware, J. E., & Sherbourne, C. D. (1992). The MOS-36 item shortform health survey (SF-36): I. Conceptual framework and item selection. Medical Care, 30, 473–483.

123