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International Journal of Methods in Psychiatric Research logoLink to International Journal of Methods in Psychiatric Research
. 2011 Nov 4;20(4):e69–e82. doi: 10.1002/mpr.353

Assessing anxious features in depressed outpatients

Shawn M McClintock 1,2,✉, Mustafa M Husain 1, Ira H Bernstein 3, Stephen R Wisniewski 4, Madhukar H Trivedi 1, David Morris 1, Jonathan Alpert 5, Diane Warden 1, James F Luther 4, Susan G Kornstein 6, Melanie M Biggs 1,7, Maurizio Fava 5, A John Rush 8
PMCID: PMC3708141  NIHMSID: NIHMS473680  PMID: 22057975

Abstract

Both the 17‐item Hamilton Rating Scale for Depression (HRSD17) and 30‐item Inventory of Depressive Symptomatology – Clinician‐rated (IDS‐C30) contain a subscale that assesses anxious symptoms. We used classical test theory and item response theory methods to assess and compare the psychometric properties of the two anxiety subscales (HRSDANX and IDS‐CANX) in a large sample (N = 3453) of outpatients with non‐psychotic major depressive disorder in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study. Approximately 48% of evaluable participants had at least one concurrent anxiety disorder by the self‐report Psychiatric Diagnostic Screening Questionnaire (PDSQ). The HRSDANX and IDS‐CANX were highly correlated (r = 0.75) and both had moderate internal consistency given their limited number of items (HRSDANX Cronbach's alpha = 0.48; IDS‐CANX Cronbach's alpha = 0.58). The optimal threshold for ascribing the presence/absence of anxious features was found at a total score of eight or nine for the HRSDANX and seven or eight for the IDS‐CANX. It would seem beneficial to delete item 17 (loss of insight) from the HRSDANX as it negatively correlated with the scale's total score. Both the HRSDANX and IDS‐CANX subscales have acceptable psychometric properties and can be used to identify anxious features for clinical or research purposes. Copyright © 2011 John Wiley & Sons, Ltd.

Keywords: depression, anxiety, rating scales, STAR*D, measurement‐based care

Introduction

Major depressive disorder (MDD) has a lifetime prevalence rate of 15% to 20% and is a significant cause of disability worldwide (Murray and Lopez, 1996; McKenna et al., 2005; Moussavi et al., 2007). Individuals with MDD often have anxiety and sympathetic nervous system arousal, which characterizes anxious symptom features. Although depression with anxious features is not codified in the DSM‐IV‐TR (American Psychiatric Association, 2000), it has been defined in the literature as either MDD with high levels of anxiety symptoms, or the concurrent (not lifetime) presence of depression and anxiety (Fava et al., 2004).

Anxiety disorders are frequently comorbid with MDD. Studies have found comorbid anxiety (lifetime) in 60% to 65% of individuals with MDD in a community sample (Kessler et al., 1996) and comorbid anxiety disorder in 59.2% of individuals with MDD based on DSM‐IV criteria (Kessler et al., 2003). In clinical trial populations, prevalence rates of concurrent (not lifetime) anxious features of approximately 40% to 60% have been documented. Thus, roughly half of all patients who have MDD experience anxious symptoms and consequently suffer from increased levels of impairment (Fava et al., 2004; Lydiard and Brawman‐Mintzer, 1998).

While no standard measure exists for systematically identifying depressed outpatients with “anxious features” (Bramley et al., 1988), the six‐item anxiety/somatization factor within the 17‐item Hamilton Rating Scale for Depression (HRSD17) (Hamilton, 1960, 1967; Cleary and Guy, 1977) has been used to assess anxiety as it contains items that measure psychic and somatic anxiety symptoms (Fava et al., 2008). However, no studies to date have assessed the psychometric properties of this anxiety/somatization factor (HRSDANX) in depressed patients with and without anxious features (Bagby et al., 2004). The 30‐item Inventory of Depressive Symptomatology – Clinician‐rated (IDS‐C30) (Rush et al., 1986, 1996) also assesses anxious features through the inclusion of items that assess anxious mood, somatic complaints, and sympathetic arousal. Again, no psychometric studies have yet assessed the anxiety subscale (IDS‐CANX).

The current study assessed the psychometric performance of both the HRSDANX and the IDS‐CANX in depressed outpatients enrolled in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study. We hypothesized that both scales would have satisfactory psychometric properties.

Materials and methods

Study overview

The STAR*D study aimed to define prospectively the comparative effectiveness of several antidepressant treatments in individuals with non‐psychotic MDD who have an unsatisfactory clinical outcome to an initial and, if necessary, subsequent treatment(s) (Fava et al., 2003; Rush et al., 2004).

Fourteen Regional Centers oversaw the STAR*D study, which was conducted at 18 primary and 23 psychiatric care settings. The STAR*D protocol was developed in accordance with the principles of the Declaration of Helsinki and was approved and monitored by the study's National Coordinating Center (University of Texas Southwestern Medical Center, Dallas, TX), Data Coordinating Center (University of Pittsburgh Epidemiology Data Center, Pittsburgh, PA), the institutional review boards at each Clinical Site and Regional Center, and the Data Safety and Monitoring Board of the National Institute of Mental Health (NIMH; Bethesda, MD). Prior to enrollment, all potential risks, benefits, and adverse events associated with STAR*D participation were explained and a written informed consent was obtained from each participant.

Study population

STAR*D enrolled 4041 outpatients from across the United States, 18 to 75 years of age, who were diagnosed with non‐psychotic MDD (based on the Mini‐International Neuropsychiatric Interview (Sheehan et al., 1998) and had a baseline HRSD17 score ≥ 14 (moderate severity). Patients were excluded if they had schizophrenia, schizoaffective disorder, bipolar disorder, anorexia nervosa, a current primary diagnosis of bulimia nervosa or obsessive‐compulsive disorder, psychiatric disorders or substance abuse that required immediate hospitalization, general medical conditions or concomitant medications that contraindicated the use of protocol treatments in the first two treatment steps, were using a targeted psychotherapy for depression, or had a well‐documented history of non‐response or intolerance (in the current major depressive episode) to one or more of the protocol treatments in the first two treatment steps. The study also excluded patients who were breastfeeding, pregnant, or trying to become pregnant.

Assessment measures

Sociodemographic and clinical data were collected at the screening/baseline visit. Participants completed the self‐report Psychiatric Diagnostic Screening Questionnaire (PDSQ) (Zimmerman and Mattia, 1999) to identify the following concurrent anxiety disorders: Generalized Anxiety Disorder, Panic Disorder, Post‐Traumatic Stress Disorder, Social Phobia, Obsessive‐Compulsive Disorder, and Agoraphobia (Zimmerman and Mattia, 1999, 2001; Castel et al., 2007; Gibbons et al., 2009). The presence of each disorder was determined based on the specific PDSQ subscales (each PDSQ subscale has an 89% sensitivity and 97% negative predictive value), which have been found to be valid for assessing DSM Axis‐I categories (Gibbons et al., 2009; Rush et al., 2005). Within 72 hours of the screening/baseline visit, trained Research Outcome Assessors (ROAs), who were masked to treatment and to the results of the PDSQ, conducted telephone interviews to complete the HRSD17 and the IDS‐C30. A study by Rush et al. (2006a) found the telephone interview format of the HRSD17 and the IDS‐C30 to be reliable and valid.

Defining anxious features

For this report, we defined the presence of anxious features as a minimum of one anxiety diagnosis based on the PDSQ (Zimmerman and Mattia, 1999). The HRSDANX was based on the analyses of Cleary and Guy (1977), while the IDS‐CANX was based on prior analyses (Gullion and Rush, 1998; Bernstein et al., 2006) and expert consensus.

Statistical analysis

Data for these analyzes were obtained by the ROA at baseline and at exit from the first treatment trial with one antidepressant medication (citalopram) (Rush et al., 2006b). Only those participants (N = 3453) who were not on any antidepressant medications at baseline were included in the analyses. Summary statistics were used to describe the sociodemographic and clinical characteristics of the sample. Means and standard deviations are presented for continuous variables; percentages are presented for discrete variables. The association between sociodemographic and clinical characteristics and the number of anxiety comorbidities was estimated using a Poisson regression model that was adjusted for dispersion. Results were interpreted based on standard guidelines for acceptable psychometric properties (Nunnally and Bernstein, 1994). A p‐value of < 0.05 indicated a significant association.

To identify a possible threshold on the HRSDANX and IDS‐CANX subscales for the identification of anxious features, sensitivity and specificity were calculated when comparing each subscale total to the presence of anxiety (yes/no). Receiver operating characteristic (ROC) curves were generated from the sensitivity and specificity estimates.

Similar to other investigations (Bernstein et al., 2007, 2009), data were analyzed using both classical test theory (CTT) (Nunnally and Bernstein, 1994) and modern test theory (item response theory, IRT) (Embretson and Reise, 2000). CTT's key outputs are the item means, which define level of response, and item/total correlations (r it), which define the strength of relation between the item and the scale, plus the scale mean, scale standard deviation and a measure of internal consistency reliability, usually Cronbach's alpha. CTT assumes the dimension to be assessed (anxiety in the present case) is the sum of the item scores, whereas IRT views the dimension as a latent variable to be inferred. The two are complementary. Although CTT rests upon more familiar constructs so that its results are generally rather easily understood, IRT allows the sensitivity of the test in making discriminations at various levels of the latent variable, focusing on the reliabilities instead of treating it as a constant (the internal consistency, i.e. coefficient alpha) and focusing on the scores as is done in CTT. This analysis involves the test information function (TIF). The Samejima graded response model (Samejima, 1997) was employed for IRT analysis. IRT was also used to equate scores on the two tests being considered (Lord, 1980; Orlando et al., 2000).

IRT models can use a wide array of response formats (e.g. binary, multiple choice), but the Samejima model specifically assumes a graded response format. Thus, for the purpose of these analyses, we chose the Samejima model as it was designed for tests that employ an ordered series of responses, such as the 0–3 scale of the IDS‐C30. It is assumed that the probability of a participant choosing the higher of two response categories is a logistic (S‐shaped) function of the latent trait (symbolized “Θ”), which for this study represents depression. In this analysis, there are three possible categorizations (0 versus 1, 2, or 3 – normal versus pathological; 0 or 1 versus 2 or 3 – normal and mildly pathological versus moderately or severely pathological; and 0, 1, or 2 versus 3 – normal, mildly pathological, and moderately pathological versus severely pathological). The three categorizations are assumed to produce a common slope but different locations along the anxiety axis. Collectively, these categorizations form category response functions. The slope that is common to the three functions is designated “a”. The three locations along the depression axis are designated “b 1”, “b 2”, and “b 3” (“bi” collectively). A steeper slope indicates a more discriminating item. The higher the values of b, the less likely the more pathological category is chosen, yielding four parameter estimations per item. In view of the six HRSDANX items and five IDS‐CANX items, the item analysis generates 24 parameter estimates for the former measure and 20 for the latter. These a and bi parameters are of central interest when groups are being compared to investigate what is known as differential item functioning. However, they are of lesser interest in this one‐group design, so they have been omitted. They can be obtained upon request from the first author. The computation of TIF is described in Nunnally and Bernstein (1994) and Embretson and Reise (2000).

The Samejima model does assume that the items define a unidimensional scale. Scale dimensionality was inferred by parallel analysis (Horn, 1965; Humphreys and Ilgen, 1969; Humphreys and Montanelli, 1975; Montanelli and Humphreys, 1976). This involves generating matrices of random normal deviates with the same number of variables and observations as the obtained data. The random data are then factored. In the present case, 50 such random matrices were generated, and the results averaged. The dimensionality of the obtained data is the number of eigenvalues greater than in the randomly generated factors. Specifically, a series of variables is unidimensional if the first eigenvalue it generates is larger than the first eigenvalue of the randomly‐generated data but the reverse is true of the second eigenvalue.

Statistical software packages used included SAS (Version 9.1.3, SAS Institute, Cary, NC) for CTT and factor analyses, and MULTILOG (Version 7, Scientific Software International, Lincolnwood, Il) for IRT analyses.

Results

Sociodemographic and clinical characteristics

In our study sample (N = 3453), most participants were female and the racial composition was comparable to the US population (US Census Bureau, 2000) (Table 1). Although statistically significant associations were found in sociodemographic and clinical characteristics, many were not clinically meaningful (Tables 1 and 2). Of clinical relevance, participants with anxiety comorbidities had higher rates of unemployment, correspondingly lower monthly household incomes, greater depression severity on both clinician‐rated and self‐report measures, and were more likely to have attempted suicide.

Table 1.

Sociodemographic and clinical characteristics of participants by number of anxiety‐related disorders

Number of anxiety related disordersa Analyses
Measure All (N = 3453) 0 (N = 1799) 1 (N = 852) 2 (N = 415) 3 (N = 203) 4 (N = 117) 5 (N = 67)
n % n % n % n % n % n % n % β SE χ 2 df p
Male gender 1291 37.4 718 39.9 324 38.0 136 32.8 59 29.1 34 29.1 20 29.9 −0.0977 0.0259 14.2 1 0.0002
Race 24.8 2 <0.0001
White 2622 76.0 1414 78.7 645 75.8 301 72.7 143 70.4 79 67.5 40 59.7
Black 586 17.0 259 14.4 151 17.7 75 18.1 51 25.1 28 23.9 22 32.8 0.1595 0.0316 25.5 1 <0.0001
Other 241 7.0 124 6.9 55 6.5 38 9.2 9 4.4 10 8.5 5 7.5 0.0475 0.0486 0.95 1 0.3285
Hispanic ethnicity 426 12.3 186 10.3 103 12.1 68 16.4 38 18.7 22 18.8 9 13.4 0.1398 0.0357 15.3 1 <0.0001
Employment status 42.8 2 <0.0001
Employed 2001 58.0 1095 60.9 518 60.9 219 52.8 97 47.8 44 37.6 28 41.8
Unemployed 1250 36.2 591 32.9 285 33.5 173 41.7 97 47.8 66 56.4 38 56.7 0.1651 0.0257 41.2 1 <0.0001
Retired 200 5.8 113 6.3 47 5.5 23 5.5 9 4.4 7 6.0 1 1.5 −0.0091 0.0558 0.03 1 0.8707
Medical insurance 47.2 2 <0.0001
Any private 1762 52.6 997 57.1 435 52.6 187 47.1 82 41.2 35 30.7 26 41.3
Public only 447 13.4 190 10.9 106 12.8 66 16.6 44 22.1 32 28.1 9 14.3 0.2344 0.0365 41.2 1 <0.0001
None 1138 34.0 560 32.1 286 34.6 144 36.3 73 36.7 47 41.2 28 44.4 0.1249 0.0277 20.3 1 <0.0001
Marital status 3.9 3 0.2761
Never married 1036 30.0 525 29.2 278 32.7 131 31.6 55 27.1 31 26.5 16 23.9 0.0091 0.0298
Married/cohabiting 1448 41.9 781 43.4 348 40.9 158 38.1 88 43.3 47 40.2 26 38.8
Divorced/separated 870 25.2 444 24.7 200 23.5 114 27.5 53 26.1 37 31.6 22 32.8 0.0578 0.0309
Widowed 98 2.8 49 2.7 25 2.9 12 2.9 7 3.4 2 1.7 3 4.5 0.0465 0.0749
Age at first episode <18 1280 37.4 603 33.8 340 40.3 185 44.9 76 38.0 50 43.9 26 40.0 0.0827 0.0254 10.6 1 0.0011
At least one prior episode 2373 74.0 1221 72.3 594 75.4 284 74.7 146 79.8 80 75.5 48 80.0 0.0625 0.0298 4.4 1 0.0362
Ever attempted suicide 574 16.6 248 13.8 144 16.9 88 21.2 43 21.3 34 29.3 17 25.4 0.1633 0.0315 26.9 1 <0.0001
Family history of depression 1887 55.1 974 54.6 464 54.9 232 56.3 117 57.9 63 54.3 37 56.1 0.0160 0.0250 0.41 1 0.5226
Months since index onset ≥24 853 24.9 410 23.0 191 22.7 138 33.6 56 28.0 37 31.6 21 31.8 0.1003 0.0280 12.8 1 0.0003
Psychiatric care 2115 61.3 1086 60.4 536 62.9 262 63.1 129 63.5 61 52.1 41 61.2 0.0006 0.0254 <0.01 1 0.9820
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a

Assessed by the Psychiatric Diagnostic Screening Questionnaire.

Table 2.

Sociodemographic and clinical characteristics of participants by number of anxiety‐related disorders

Number of anxiety related disordersa Analyses
All (N = 3453) 0 (N = 1799) 1 (N = 852) 2 (N = 415) 3 (N = 203) 4 (N = 117) 5 (N = 67)
M SD M SD M SD M SD M SD M SD M SD β SE χ b df p
Age 40.3 13.2 41.7 13.6 38.8 12.7 38.3 12.9 39.5 12.4 39.4 12.0 40.4 11.5 −0.0035 0.0009 13.5 1 0.0002
Education (years) 13.5 3.2 14.0 3.3 13.4 3.1 12.9 3.3 12.3 3.0 11.7 2.6 12.5 2.4 −0.0362 0.0038 93.1 1 <0.0001
Monthly household incomeb 2440 3191 2768 3735 2346 2569 2117 2582 1587 1788 1371 1744 1342 1323 −0.0322 0.0049 42.6 1 <0.0001
Age at first episode 25.3 14.3 27.0 15.0 24.2 13.5 22.6 13.2 22.7 12.3 22.6 12.5 21.6 12.4 −0.0056 0.0009 38.6 1 <0.0001
Years since first episode 15.1 13.1 14.7 13.5 14.6 12.4 15.6 12.8 17.0 12.9 16.9 12.7 18.8 12.8 0.0029 0.0009 9.4 1 0.0021
N Episodes 5.4 9.2 4.9 8.6 5.8 9.8 5.6 9.2 6.7 10.6 5.7 10.3 8.4 11.7 0.0038 0.0013 8.3 1 0.0040
Months since index onset 24.2 51.6 21.2 45.3 23.5 53.7 32.3 60.5 21.8 32.8 42.3 82.7 42.0 80.4 0.0009 0.0002 20.4 1 <0.0001
N Moderate to severe GMCsc 1.0 1.3 1.0 1.3 1.0 1.2 1.0 1.3 1.2 1.4 s1.5 1.5 1.6 1.3 0.0481 0.0093 26.6 1 <0.0001
HRSD17 19.9 6.5 17.9 6.1 20.3 6.0 22.5 5.9 23.4 6.0 26.8 5.5 28.2 4.1 0.0386 0.0019 410 1 <0.0001
IDS‐C30 35.5 11.5 31.7 10.6 36.5 10.4 40.4 10.4 42.7 10.2 47.8 10.1 50.8 7.1 0.0233 0.0011 467 1 <0.0001
QIDS‐SR16 15.4 4.3 14.1 4.1 15.8 4.0 17.4 3.6 17.9 3.9 19.0 3.6 19.8 3.6 0.0561 0.0030 361 1 <0.0001
Q‐LES‐Q 41.8 15.2 45.6 14.2 40.6 14.2 37.5 14.8 32.5 14.7 30.9 16.7 27.4 15.6 −0.0131 0.0008 246 1 <0.0001
SF12 Mental 26.5 8.6 27.7 9.0 25.5 8.1 24.4 7.6 25.1 7.1 26.8 9.1 23.4 7.4 −0.0092 0.0015 36.8 1 <0.0001
SF12 Physical 49.8 11.8 51.5 11.6 50.0 11.4 48.1 11.4 44.4 11.7 41.7 12.0 40.0 10.4 −0.0118 0.0010 127 1 <0.0001
WSAS 23.4 9.3 21.0 9.1 24.3 8.9 26.4 8.2 29.2 7.7 29.5 8.5 30.9 7.8 0.0219 0.0014 235 1 <0.0001
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Note: GMC, general medical comorbidity; HRSD17, 17‐item Hamilton Rating Scale for Depression; IDS‐C30, 30‐item Inventory of Depressive Symptomatology – Clinician‐rated; QIDS‐SR16, 16‐item Quick Inventory of Depressive Symptomatology – Self‐rated; Q‐LES‐Q, Quality of Life and Enjoyment Satisfaction Questionnaire; SF12, 12‐item short‐form health survey; WSAS, Work and Social Adjustment Scale.

a

Assessed by the Psychiatric Diagnostic Screening Questionnaire.

b

Beta based on units of $1000.

c

Assessed by the Cumulative Illness Rating Scale.

CTT analysis

Given their brevity, both the HRSDANX (Cronbach's alpha = 0.48) and the IDS‐CANX (Cronbach's alpha = 0.58) demonstrated modest internal consistency (Table 3). The HRSD17 and the IDS‐C30 were highly correlated (r = 0.89). The HRSDANX and the IDS‐CANX were also highly correlated (r = 0.75), indicating that they tend to measure the same general construct. One negative feature of the HRSDANX was that the correlation between item 17 (loss of insight) and the total score was essentially zero at both baseline and exit (rs = −0.07 and −0.15, respectively), suggesting it is irrelevant to the scale. Disattenuation (correction for unreliability) suggested that virtually all of the systematic variance in each respective test is shared with the other.

Table 3.

Comparison of HRSDANX and IDS‐CANX

Baseline Exit Changea Analyses
# Item M SD r it M SD r it M SD t df p ES
HRSDANX α = 0.48 α = 0.65
10 Anxiety, psychic 1.64 0.98 0.23 0.89 0.98 0.50 0.74 0.98 26.6 4924 <0.0001 0.76
11 Anxiety, somatic 1.60 0.90 0.39 1.27 0.97 0.49 0.33 0.94 12.5 4894 <0.0001 0.36
12 Somatic symptoms, gastrointestinal 0.67 0.83 0.18 0.31 0.63 0.36 0.36 0.74 17.3 4577 <0.0001 0.49
13 Somatic symptoms, general 1.41 0.74 0.31 0.85 0.84 0.52 0.56 0.79 24.9 4845 <0.0001 0.71
15 Hypochondriasis 0.69 0.87 0.30 0.49 0.76 0.43 0.20 0.82 8.4 4844 <0.0001 0.24
17 Insight 0.03 0.20 –0.07 0.06 0.31 –0.15 –0.03 0.26 3.5 4274 0.0004 0.10
Total 6.03 2.52 3.86 2.84 2.17 2.69 28.4 4853 <0.0001 0.81
IDS‐CANX α = 0.58 α = 0.68
7 Mood (anxious) 1.37 0.88 0.36 0.75 0.86 0.49 0.62 0.87 25.1 4924 <0.0001 0.72
25 Somatic complaints 1.31 1.00 0.28 0.94 1.01 0.43 0.36 1.01 12.7 4924 <0.0001 0.36
26 Sympathetic arousal 0.91 0.80 0.45 0.72 0.78 0.49 0.19 0.79 8.6 4924 <0.0001 0.25
27 Panic 0.62 0.94 0.37 0.30 0.71 0.44 0.33 0.83 13.7 4598 <0.0001 0.39
28 Gastrointestinal 0.63 0.87 0.24 0.54 0.84 0.36 0.09 0.85 3.6 4924 0.0003 0.10
Total 4.85 2.75 3.25 2.81 1.60 2.78 20.2 4924 <0.0001 0.57
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Note: HRSDANX, Hamilton Rating Scale for Depression anxiety subscale; IDS‐CANX, Inventory of Depressive Symptomatology –Clinician‐rated anxiety subscale; r it, item‐total correlation coefficient.

a

Change from baseline (entry into STAR*D Level 1) to exit (end of STAR*D Level 1).

The values of item‐total correlation (r it), and thus the overall coefficients alpha, increased from baseline to exit for both subscales (Table 3), which is expected given the greater variation among individual items at exit. At baseline, somatic anxiety, somatic symptoms‐general and hypochondriasis all contributed to the HRSDANX scale total, and were joined by psychic anxiety at exit. In fact, the baseline and exit values of r it have a very high correlation of 0.96. The most discriminating IDS‐CANX item at baseline was sympathetic arousal, followed by the nearly equal contribution of panic/phobic symptoms and anxious mood. At exit, the five items were closer to equal, with anxious mood and sympathetic arousal being the two most discriminating items. In general, the correlation between baseline and exit values of r it for the two subscales was relatively similar.

Table 3 shows the change in each item's mean score from baseline to exit (effect sizes), effect sizes in terms of Cohen's d = mean change/SD, the corresponding values of t testing the null hypothesis that the mean change was zero, and the total HRSDANX and IDS‐CANX scale scores. Overall, the two scales were similar in effect size (HRSDANX = 0.81 versus IDS‐CANX = 0.57) and the largest effect size was seen in psychic anxiety and general somatic symptoms on the HRSDANX and anxious mood on the IDS‐CANX.

All correlations of the HRSDANX and the IDS‐CANX with the anxiety dimensions of the PDSQ were significant (p < 0.0001) (Table 4). Although the correlations between the IDS‐CANX and PDSQ anxiety dimensions were slightly higher than those between HRSDANX and PDSQ, these differences were modest.

Table 4.

Correlations between the PDSQ anxiety subscales, HRSDANX and IDS‐CANX a (N = 3453)

PDSQ anxiety subscale HRSDANX IDS‐CANX
Post traumatic stress 0.31 0.41
Panic 0.34 0.42
Agorophobia 0.42 0.51
Social phobia 0.25 0.31
Generalized anxiety 0.16 0.24
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Note: HRSDANX, Hamilton Rating Scale for Depression Anxiety/Somatization Factor; IDS‐CANX, Inventory of Depressive Symptomatology Anxiety Factor; PDSQ, Psychiatric Diagnostic Screening Questionnaire.

a

All correlations were significant at p < 0.0001.

Sensitivity and specificity

Approximately 48% of participants had at least one PDSQ‐defined anxiety disorder. ROC curve analyses were estimated for the PDSQ anxiety diagnoses in each subscale (Figure 1) to examine the sensitivity and specificity estimates. The area under the ROC curve (AUC) for the HRSDANX was 0.656 for 1–5 PDSQ anxiety diagnoses, 0.702 for 2–5 PDSQ anxiety diagnoses, 0.740 for 3–5 PDSQ anxiety diagnoses, and 0.809 for 4–5 PDSQ anxiety diagnoses. For the IDS‐CANX, the AUC was 0.701 for 1–5 PDSQ anxiety diagnoses, 0.758 for 2–5 PDSQ anxiety diagnoses, 0.808 for 3–5 PDSQ anxiety diagnoses, and 0.849 for 4–5 PDSQ anxiety diagnoses. The AUC was greatest when all five anxiety diagnoses of the PDSQ were examined in relation to the HRSDANX (AUC = 0.833) and IDS‐CANX (AUC = 0.860) range of cut‐off scores. The greater area under the curve that is above the line of discrimination, the more valid is the classification system. Sensitivity and specificity in distinguishing depressed participants with and without at least one concurrent anxiety disorder were maximized with a cut‐off score of eight or nine for the HRSDANX, and seven or eight for the IDS‐CANX.

Figure 1.

Figure 1

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ROC curve for the HRSDANX and IDS‐CANX factors: (a) HRSDANX ROC curve; (b) IDS‐CANX ROC curve.

Factor analyses

The obtained first and second eigenvalues were 1.80 and 0.99 for the baseline HRSDANX, 2.37 and 0.97 for the exit HRSDANX, 1.99 and 1.018 for the baseline IDS‐CANX and 2.25 and 0.95 for the exit IDS‐CANX. The corresponding simulated eigenvalues were 1.05 and 1.05, 1.06 and 1.03, 1.05 and 1.021, and 1.06 and 1.01. Thus, the obtained first eigenvalue exceeded the simulated first eigenvalue, but the reverse was true for the second eigenvalue. This means that the two measures were unidimensional at both baseline and exit, fulfilling the requirements of the IRT analysis.

IRT analyses

The HRSDANX was better able to resolve differences in anxiety up to Θ of about 1.0 (Figure 2), which represents the bottom 84% of the sample (in reference to level of anxiety) since the scale for Θ is the normal distribution. Beyond this point, the IDS‐CANX was the more sensitive to anxious features. Thus, the HRSDANX was more sensitive to anxious features in participants with low depression severity, whereas the IDS‐CANX was more sensitive to anxious features in participants with moderate to high depression severity.

Figure 2.

Figure 2

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Test information function for the HRSDANX and the IDS‐CANX.

Test equating

Test equating involves associating total test scores on each test with values of the dimension under investigation, commonly denoted “Θ”. Total scores on each test that have similar values of Θ derived from the same sample are considered matched. Table 5 contains the matching scores on the HRSDANX and the IDS‐CANX with their estimated values of Θ.

Table 5.

Equated scores on the HRSDANX and IDS‐CANX a

HRSDANX IDS‐CANX
Raw score Θ Raw score Θ
0 −1.40 0 −1.20
1 −0.84 1 −0.63
2 −0.48 2 —
3 −0.17 3 −0.27
4 0.11 4 0.01
5 0.36 5 0.29
6 0.60 6 0.54
7 0.84 7 0.78
8 1.10 8 1.00
9 1.30 9 1.20
10 1.50 10 1.50
11 1.80 11 1.70
12 2.00 12 1.90
13 2.30 13 2.10
14 2.50 14 2.40
15 2.70 15 2.70
16 2.90 — —
17 3.30 — —
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Note: HRSDANX, Hamilton Rating Scale for Depression Anxiety/Somatization Factor (N = 2697); IDS‐CANX, Inventory of Depressive Symptomatology Anxiety Factor (N = 2698).

a

Test equating involves associating raw scores on each test with values of the dimension under investigation denoted Θ, which in this case are anxious symptom features. The total range for the HRSDANX is 0–18 and the total range for the IDS‐CANX is 0–15.

Discussion

Both the HRSDANX and IDS‐CANX subscales were found to have adequate psychometric properties and were moderately sensitive indicators of anxious features in depressed outpatients. IDS‐CANX demonstrated a moderate level of internal consistency. The lack of redundancy in the IDS‐CANX items suggests that all are valuable. The high correlation between the subscales supported their concurrent validity, and both showed discriminant ability in identifying patients with anxious features. Factor analytic methods indicated that both scales were unidimensional. The IDS‐CANX had greater sensitivity to anxious features in patients with moderate to severe depression, while the HRSDANX had greater sensitivity to anxious features in patients with mild depression severity.

CTT and IRT analyses indicated that HRSDANX item 17 (loss of insight) may be problematic. Its removal improved the measure's Cronbach's alpha coefficient (increased to 0.54), suggesting greater internal consistency among the remaining five items (removal of any of these items lowered alpha between 0.37 and 0.49). Item 17 has been found to have variable internal reliability and poor inter‐rater reliability (Bagby et al., 2004). Other investigations of factors on the HRSD17 have also reported mixed results (Fleck et al., 1995; Pancheri et al., 2002). Recent research (Pancheri et al., 2002) suggests that the HRSD17 contains two independent anxiety factors: somatic anxiety (including somatic anxiety, hypochondriasis, somatic energy, appetite, and insomnia symptoms) and psychic anxiety (including psychic anxiety, psychomotor agitation, insight, and guilt). This dispute, however, does not bear upon what we found to be a unidimensional structure of the six anxiety items.

The IDS‐C30 has been well validated as a comprehensive measure of depression severity (Rush et al., 1996; Trivedi et al., 2004) with demonstrated significant strengths (e.g. excellent psychometric properties, structured gradient metric, sensitivity to change, and availability of self‐report). Bernstein et al. (2006) found that the IDS‐C30 had two dimensions, a depressive dimension that consists mainly of core depressive items, and a second dimension containing somatic and anxiety items (e.g. somatic complaints, sympathetic arousal, gastrointestinal complaints). Our investigation confirms that certain items contribute to a somatic/anxiety domain.

The threshold total score by which to identify anxious features with either subscale depends on the desired ratio between sensitivity (i.e. correctly identifying depressed patients with anxious features) and specificity (i.e. correctly identifying depressed patients without anxious features). Ideally, the threshold should maximize both sensitivity and specificity (Loong, 2003). Based on this paradigm, the thresholds that maximized sensitivity and specificity in this study (based on 69 participants with five or more anxiety disorders) were 8–9 for the HRSDANX and 7–8 for the IDS‐CANX. The cut‐off score previously recommended for the HRSDANX (Cleary and Guy, 1977) and used in clinical trials was seven (Fava et al., 2004, 2008), which the present study indicates would result in high sensitivity (94.2) but moderate specificity (55.5). This could result in some over‐identification of patients with anxious features.

Differences between the HRSDANX and IDS‐CANX

The HRSDANX and the IDS‐CANX are unitary measures of anxious features, but these subscales differ in terms of item content (i.e. face validity) and rating metric. The face validity of these scales is different based on their respective item content. Both measure physical and psychic anxious symptoms, but the HRSDANX includes items related to appetite, energy, and insight, all core depressive features in the DSM‐IV‐TR (American Psychiatric Association, 2000). Also, Gullion and Rush (1998) reported HRSD17 item 13 (somatic symptoms: general) loaded on the “hedonic capacity” factor, and item 17 (loss of insight) was excluded from their analyses as it was endorsed by less than 25% of the participant sample and could have obscured factor construction. Other studies have also suggested that item 17 does not contribute to the HRSD17 (Bech, 1981; Bech et al., 1981). The present study further suggests that item 17 was poor in discriminating between the presence and absence of anxious features. Thus, the HRSDANX may have poor face validity, as only two of the six items are related to anxiety. The IDS‐CANX items, however, are representative of symptoms included in DSM‐IV‐TR anxiety spectrum disorders. These items are germane to anxiety, somatic and phobic symptoms, and demonstrate good discriminatory ability (e.g. the removal of any one item from the subscale did not result in a significant change in the Cronbach's alpha, which indicates its relative importance in the IDS‐CANX).

The HRSD17 and the HRSDANX weigh items disproportionately by assigning greater weight to psychic anxiety, somatic anxiety and hypochondriacal symptoms. This could be problematic as there is no theoretical or empirical basis for the HRSDANX item metric‐rating assignments. In contrast, the IDS‐CANX assigns equal weight to all items with the rationale that all contribute equally to the total score.

Utility of the HRSDANX and IDS‐CANX

Both the HRSDANX and the IDS‐CANX would be useful for systematically monitoring anxious features in clinical practice and research studies. Depressed patients with comorbid anxiety may have increased levels of clinical impairment and functional impairment (Fava et al., 2004), and may be less likely to achieve remission with antidepressant medications than depressed patients without anxiety (Fava et al., 2008, 1997). Thus, the monitoring and treatment of anxiety symptoms can enhance clinical practice by optimizing antidepressant therapy and overall clinical outcome (Zimmerman and McGlinchey, 2008). Further, the monitoring of anxiety symptoms is warranted for research studies to address their effects on therapeutic outcome. Use of the HRSDANX and IDS‐CANX by clinicians or trained interviewers is feasible (Duffy et al., 2008) and may enhance time management and office‐visit efficiency because they are subscales of the HRSD17 and the IDS‐C30, respectively, and thus enable depression and anxiety symptoms to be monitored with a single instrument. Both of these psychometrically sound instruments can play a vital role for psychiatric practitioners and researchers with the advent of measurement‐based care (Trivedi and Daly, 2007; Rush et al., 2009). Indeed, recommendations from international studies suggest that many clinicians and clinical practices could maximize efficiency and increase quality of care through the use of depression and anxiety rating instruments (Gibody et al., 2002; Pancheri et al., 2002; Laugharne 2009; Zimmerman et al., 2010).

Limitations

The study sample comprised patients who did and did not remit with citalopram, which could introduce a treatment bias as alternative therapeutic interventions (e.g. psychotherapy) may have resulted in different change scores on the HRSDANX and the IDS‐CANX. However, these measures will be useful in assessing anxious features in depressed patients regardless of treatment intervention. This study used the self‐report PDSQ to diagnose anxiety disorders, an instrument designed to compliment, not replace, clinical interview strategies (e.g. SCID‐I [First et al., 1997]) for diagnoses (Zimmerman and Chelminski, 2006). It may be possible that the sensitivity and specificity of the HRSD17 and IDS‐C30 anxiety subscales could be different if they were validated by the SCID‐I. However, the STAR*D trial benefited from the moderate to strong sensitivity and negative predictive value of the PDSQ anxiety disorder subscales (Rush et al., 2005; Zimmerman and Chelminski, 2006). Further, the PDSQ has been shown to be a valid instrument for assessing DSM diagnostic categories (Gibbons et al., 2009). Nonetheless, a structured clinical interview such as the SCID‐I would be helpful in future validation studies. A second limitation was not comparing either subscale to pure anxiety rating measures such as the State Trait Anxiety Inventory (Spielberger, 2005) or the Hamilton Rating Scale for Anxiety (HRSA) (Hamilton, 1959), which would have improved the reliability and validity of the psychometric analyses. However, we did compare the HRSDANX and IDS‐CANX to the PDSQ anxiety dimensions and found convergent validity for both subscales. Although not a limitation of the present study, both subscales had modest alpha levels, which were likely related to the small number of items (Nunnally and Bernstein, 1994) that constitute the respective scales. In future investigations, these subscales may benefit from the addition of newer items that measure anxiety spectrum symptoms. One approach to optimize the item content would be to combine these psychometric data with the clinimetric method (Bech, 2004; Emmelkamp, 2004). Clinimetrics principally focuses on the sensitivity of the rating scale to discriminate between cohorts and has been used to evaluate and develop other depression and anxiety rating scales (Sirri et al., 2008; Bech, 2009). Lastly, the high correlation between the HRSDANX and the IDS‐CANX could have been due to their administration by the same trained ROA.

Conclusion

Both the HRSDANX and the IDS‐CANX have adequate psychometric properties and reliably identify anxious features in depressed patients. Thus, both may be useful for clinical and research work by systematically monitoring both depressive symptoms and anxious features in order to optimize therapeutic outcome. Given the validity and utility of self‐report measures of depression and anxiety (Prusoff et al., 1972; Fava et al., 1986), future research to evaluate the anxiety subscale of the patient self‐report version of the IDS is warranted. Further, future studies should examine the HRSDANX and the IDS‐CANX for sensitivity to change with antidepressant therapies as well as their predictive validity. In future studies, the utility of the HRSDANX to identify anxious features may benefit from the removal of item 17 (loss of insight).

Declaration of interest statement

Dr Alpert has served as in the advisor/consultative relationship role with Eli Lilly & Company, Pamlab LLC, and Pharmavite LLC. Dr Biggs has served as a consultant for Bristol‐Meyers Squibb, Eli Lilly, GlaoxSmithKline, Merck, and Pfizer. Dr Fava has provided scientific consultation to or served on the Advisory Boards for Aspect Medical Systems, Astra‐Zeneca, Bayer AG, Biovail Pharmaceuticals, Inc., BrainCells, Inc. Bristol‐Myers Squibb Company, Cephalon, Compellis, Cypress Pharmaceuticals, Dov Pharmaceuticals, Eli Lilly & Company, EPIX Pharmaceuticals, Fabre‐Kramer Pharmaceuticals, Inc., Forest Pharmaceuticals Inc., GlaxoSmithKline, Grunenthal GmBH, Janssen Pharmaceutica, Jazz Pharmaceuticals, J & J Pharmaceuticals, Knoll Pharmaceutical Company, Lundbeck, MedAvante, Inc., Neuronetics, Novartis, Nutrition 21, Organon Inc., PamLab, LLC, Pfizer Inc, PharmaStar, Pharmavite, Roche, Sanofi/Synthelabo, Sepracor, Solvay Pharmaceuticals, Inc., Somaxon, Somerset Pharmaceuticals, Wyeth‐Ayerst Laboratories. He has been on speaker bureaus for Astra‐Zeneca, Boehringer‐Ingelheim, Bristol‐Myers Squibb Company, Cephalon, Eli Lilly & Company, Forest Pharmaceuticals Inc., GlaxoSmithKline, Novartis, Organon Inc., Pfizer Inc, PharmaStar, Wyeth‐Ayerst Laboratories. He has received research/grant support from Abbott Laboratories, Alkermes, Aspect Medical Systems, Astra‐Zeneca, Bristol‐Myers Squibb Company, Cephalon, Eli Lilly & Company, Forest Pharmaceuticals Inc., GlaxoSmithKline, J & J Pharmaceuticals, Lichtwer Pharma GmbH, Lorex Pharmaceuticals, Novartis, Organon Inc., PamLab, LLC, Pfizer Inc, Pharmavite, Roche, Sanofi/Synthelabo, Solvay Pharmaceuticals, Inc., Wyeth‐Ayerst Laboratories. He has equity holdings in Compellis, MedAvante. Dr Husain has served on Advisory Boards for AstraZeneka, VersusMed, Avinar, Boston Scientific, MEASURE, Bristol‐Meyer‐Squibb, and Clinical Advisors and on speakers bureaus for Cyberonics, Inc., Avinar, Inc., Cerebrio, Inc., AstraZeneka, Bristol‐Meyers‐ Squibb, Optima/Forrest Pharmaceuticals, Glaxo‐Smith‐Kline, Forrest Pharmaceuticals, and Janssen. Dr Kornstein has served on Advisory Boards/recieved honoraria from Pfizer, Inc., Wyeth, Inc., Lilly, Inc., Bristol‐Myers Squibb Company, Warner‐Chilcott, Inc., Biovail Laboratories, Berlex Laboratories, Forest Laboratories, Neurocrine, and Sepracor, Inc. She has received book royalties from Guilford Press. Dr Morris has been a consultant for Pfizer. Dr Rush has provided scientific consultation to or served on Advisory Boards for Advanced Neuromodulation Systems, Inc.; Best Practice Project Management, Inc.; Bristol‐Myers Squibb Company; Cyberonics, Inc.; Forest Pharmaceuticals, Inc.; Gerson Lehman Group; GlaxoSmithKline; Jazz Pharmaceuticals; Eli Lilly & Company; Merck & Co., Inc.; Neuronetics; Ono Pharmaceutical; Organon USA Inc.; Personality Disorder Research Corp.; Pfizer Inc.; The Urban Institute; and Wyeth‐Ayerst Laboratories Inc. He has received royalties from Guilford Press and Healthcare Technology Systems and research/grant support from the Robert Wood Johnson Foundation, the National Institute of Mental Health, and the Stanley Foundation; has been on speaker bureaus for Cyberonics, Inc., Forest Pharmaceuticals Inc., GlaxoSmithKline, and Eli Lilly & Company; and owns stock in Pfizer Inc. Dr Trivedi has received research support from Bristol‐Myers Squibb Company; Cephalon, Inc.; Corcept Therapeutics, Inc.; Cyberonics, Inc.; Eli Lilly & Company; Forest Pharmaceuticals; GlaxoSmithKline; Janssen Pharmaceutica; Merck; National Institute of Mental Health; National Alliance for Research in Schizophrenia and Depression; Novartis; Pfizer Inc.; Pharmacia & Upjohn; Predix Pharmaceuticals; Solvay Pharmaceuticals, Inc.; and Wyeth‐Ayerst Laboratories. He has served on Advisory Boards for or provided consultation to Abbott Laboratories, Inc.; Akzo (Organon Pharmaceuticals Inc.); Bayer; Bristol‐Myers Squibb Company; Cephalon, Inc.; Cyberonics, Inc.; Forest Pharmaceuticals; GlaxoSmithKline; Janssen Pharmaceutica Products, LP; Johnson & Johnson PRD; Eli Lilly & Company; Meade Johnson; Parke‐Davis Pharmaceuticals, Inc.; Pfizer, Inc.; Pharmacia & Upjohn; Sepracor; Solvay Pharmaceuticals, Inc.; and Wyeth‐Ayerst Laboratories and has been on speaker's bureaus for Akzo (Organon Pharmaceuticals Inc.); Bristol‐Myers Squibb Company; Cephalon, Inc.; Cyberonics, Inc.; Forest Pharmaceuticals; Janssen Pharmaceutica Products, LP; Eli Lilly & Company; Pharmacia & Upjohn; Solvay Pharmaceuticals, Inc.; and Wyeth‐Ayerst Laboratories. Dr. Warden currently owns stock in Pfizer and previously owned stock in Bristol Myers Squibb. Dr Wisniewski has served as a consultant for Cyberonics Inc. (2005‐2005) and ImaRx Therapeutics, Inc. (2006). The remaining authors report no competing interests.

Acknowledgments

This project was funded by the National Institute of Mental Health (NIMH) under contract N01MH90003 to the University of Texas Southwestern Medical Center at Dallas (A.J. Rush, principal investigator). The NIMH had no further role in the study design; in the collection, analysis and interpretation of the data; in the writing of the report; or in the decision to submit the paper for publication. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government. Also, we thank Bristol‐Myers Squibb, Forest Laboratories, GlaxoSmithKline, King Pharmaceuticals, Organon, Pfizer, and Wyeth for providing medications at no cost for this trial. Trial Registration: clinicaltrials.gov Identifier: NCT00021528

The authors would like to acknowledge Dr Anna Brandon at University of Texas Southwestern Medical Center and Ms Sara Mlynarchek at the University of Pittsburgh Graduate School of Public Health for input into this manuscript. The authors would like to acknowledge the editorial support of Mr Jon Kilner, MS, MA (Pittsburgh, PA).

Dr McClintock has received research support from the National Institutes of Health (NIH) and the National Alliance for Research on Schizophrenia and Depression (NARSAD). Dr Alpert has received research support from Abbott Laboratories, Alkermes, Lichtwer Pharma GmbH, Lorex Pharmaceuticals; Aspect Medical Systems, Astra‐Zeneca, Bristol‐Myers Squibb Company, Cephalon, Cyberonics, Eli Lilly & Company, Forest Pharmaceuticals Inc., GlaxoSmithkline, J & J Pharmaceuticals, Novartis, Organon Inc., PamLab, LLC, Pfizer Inc, Pharmavite, Roche, Sanofi/Synthelabo, Solvay Pharmaceuticals, Inc., and Wyeth‐Ayerst Laboratories. He has received speakers' honoraria from Eli Lilly & Company, Janssen, Organon. Dr Husain has received research support from the National Institute of Mental Health, Stanley Medical Research Institute, Cyberonics, Inc., Neuronetics, Inc., Magstim, and Advanced Neuromodulation Systems. Dr Kornstein has received research support from the Department of Health and Human Services, National Institute of Mental Health, Pfizer, Inc., Bristol‐Myers Squibb Company, Lilly, Inc., Forest Laboratories, Inc., GlaxoSmithKline, Inc., Mitsubishi‐Tokyo, Merck, Inc., Biovail Laboratories, Inc., Wyeth, Inc., Berlex Laboratories, Novartis Pharmaceuticals, Inc., Sepracor, Inc., Boehringer‐Ingelheim, Sanofi‐Synthelabo, and Astra‐Zeneca.

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