Anxiety and depressive symptom identification using the Duke Health Profile

0895-4356/96/$15.00 SSDl 0895-4356(95)00037-5

J Clin Epidemiol Vol. 49, No. 1, pp. 85-93, 1996 Copyright 0 1996 Elsevier Science Inc.

ELSEVIER

Anxiety and Depressive Symptom Identification Using the Duke Health Profile George R. Parkerson, Jr., * W. Eugene Broadhead and Chiu-Kit J. Tse DEPARTMENT DUKE

UNIVERSITY

OF

COMMUNITY

MEDICAL

CENTER,

AND

FAMILY

DURHAM,

MEDICINE, NORTH

CAROLINA

ABSTRACT. Duke Health

Profile (DUKE) subscales were compared for their ability to identify anxiety and depressive symptoms as measured by the State Anxiety Inventory (SAI) and the Center for Epidemiologic Studies Depression Scale (CES-D) in 413 primary care patients. The seven-item Duke Anxiety-Depression Scale (DUKE-AD) was the best symptom identifier, with sensitivities and specificities greater than 70% for scores predicted five clinical outcomes high scores on both the SAI and CES-D. Also, baseline DUKE-AD during an 18-month follow-up period, with receiver operating characteristic (ROC) curve areas ranging from 57.1 to 58.7%. Patients shown by DUKE-AD scores to be at high risk (~30, scale O-100) for symptoms of anxiety and/or depression were more often women, less well-educated, not working, and with lower socioeconomic status. Their severity of illness was higher than that of low-risk patients. Although the providers did not know which patients were at high risk, they made a clinical diagnosis of anxiety or depression more often in high&k patients. J CLIN EPIDEMIOL 49;1:85-93, 1996.

KEY WORDS. Anxiety status, primary

disorders,

depressive

disorders,

mental

health

measures, screening

measures,

health

care

Anxiety and depression are broad, overlapping, and variously defined terms used by clinicians to describe patients with a wide range of dysfunctional mental health. Both conditions are among the 15 most frequent health problems identified by primary care providers, but are underdiagnosed when compared with case detection based on psychiatric interviews [l-4]. Standardized definitions and diagnostic criteria for anxiety and depression are a major component of the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) [5, 61. Efforts have been made to define more clearly the condition known as “mixed anxiety-depression” [7-91, because DSM criteria for anxiety and depression continue to overlap with regard to sleep disturbance, fatigue, difficulty with concentration, and impairment of social functioning W. From the perspective of the primary care physician, the first order of business is to be sure not to overlook in a busy practice those patients who may have, or be at high risk for, either anxiety or depression. Recognition of high-risk patients depends on the physician’s awareness of the specific symptoms which are most likely to indicate underlying anxiety or depression. The physician must know which questions to ask patients about their symptoms, either during the interview or by questionnaire. Also important in the primary care setting is the selection of the shortest possible set of questions, given time restrictions in high-volume practices. A few key questions can be answered even during a brief patient encounter in the office or by telephone. A number of patient questionnaires have been developed to screen for anxiety [lO,ll], depression [12-151, or both 116-201. Also, instruments that measure functional health and health-related quality of life usually include subscales which assess mental health [21-251. Of these, only the Duke Health Profile (DUKE) h as subscales specific for anxiety

‘Address correspondence to: George R. Parkerson, Jr., M.D., M.P.H., P.O. Box 3886, Duke University Medical Center, Durham, North Carolina 27710. (Received in revised form 30 November 1994).

and depression [25]. For primary care providers these multidimensional global measures may be more useful than those that are entirely condition specific, because the global measures include items that identify physical and social dysfunction, which may be as important to the patient as mental health dysfunction. The present study compares the DUKE functional health measure with the State Anxiety Inventory (SAI) [l l] and the Center for Epidemiologic Studies Depression Scale (CES-D) [14] to determine which subset of DUKE items is the best for identifying symptoms of anxiety and depression in a primary care patient population.

METHODS Study

Design

and Study

Population

The study site was the Caswell Family Medical Center, a rural community health clinic in Caswell County, North Carolina. At the time of the study most primary care ambulatory services were available. Of the 3000 patients in the clinic population approximately half were women, and half were African-American. A research assistant recruited patients at the time of their regular clinic visits during the 8-month period ending in April 1991. The selection process ensured a minimum of 30 patients in each of 12 categories stratified by gender, race, and 3 age groups (18-33, 34-49, and SO-65 years). Those consenting participants who demonstrated literacy sufficient for completion of a brief demographic questionnaire then completed a 129-item set of health-related questions while in the clinic. During the same clinic visit the health care provider completed a severity of illness measure and a quality of life measure on each study patient. Further data were collected during an 18-month follow-up period after the initial visit to measure five outcomes: (1) follow-up status (one or more follow-up visits), (2) frequent follow-up (more than six follow-up visits), (3) referrals and/or hospitalizations (one or more referrals or hospitalizations), (4) high follow-up severity of illness (upper tertile severity of illness scores), and (5) high follow-up cost of

Parkerson

86 health care in the clinic (upper tertile total charges). Data for follow-up visits, referrals, hospitalizations, and follow-up severity of illness were obtained by medical record audit performed by one of the authors (G.R.P.). Cost data were obtained from records of all charges generated in the Caswell Family Medical Center at baseline and during the 18-month follow-up period. Full charges before discounts were used in the analyses. Sociodemographic data included age, gender, race (AfricanAmerican vs. white), educational level (
Questionnaires Previously validated questionnaire instruments were selected to measure a variety of the dimensions of health-related quality of life and functional health (physical, mental, social, anxiety, depression, selfesteem), as well as demographics, severity of illness, and social determinants of health (social support and stress, financial stress). The rationale was to attempt to quantitate and analyze the relationships among as many known important health-related factors as possible. The 129-item patient-report questionnaire packet included the following: a 17-item set for sociodemographic factors, the one-item QLUniscale of Spitzer (271, the 17-item Duke Health Profile (DUKE) [25], the 20-item State Anxiety Inventory (SAI) of Spielberger (111, the 20-item Center for Epidemiologic Studies Depression Scale (CES-D) [14], the lo-item Rosenberg Self-Esteem Scale [28], the 24item Duke Social Support and Stress Scale (DUSOCS) [29], the 8item Duke-UNC Functional Social Support Questionnaire (DUFSS) [30], and the 12.item finance and business strains subscale of the Family Inventory of Life Events (FILE) [31]. The QL-Uniscale of Spitzer is a one-item measure of quality of life, defined in terms of physical and mental independence, ability to do most things enjoyed, and having a positive attitude [27]. An analog scale is used to determine scores of 0 to 100 from lowest to highest quality of life. The DUKE is a 17-item generic patient-report questionnaire instrument with 10 scales for measuring functional health status and healthrelated quality of life during a l-week period of time (25,32,33]. Five of the scales have items independent of the other scales (physical health, mental health, social health, perceived health, and disability) and five are subscales (anxiety, depression, self-esteem, pain, and general health) that contain items from the independent scales. Ten of the 17 items were used on the various scales tested in this study as measures of mental health. There are three response options for each DUKE question, and scoring for the analyses in this report was performed on a scale of O-100, from lowest to highest mental health . _ dystunction. The SAI is a 20-item self-report questionnaire developed by Spielberger to measure state anxiety, or feelings of apprehension, tension, nervousness, and worry at the time at which the questionnaire is completed [ll]. Each item has four response options, and possible scores range from 20 for lowest anxiety to 80 for highest anxiety. The CES-D is a 20-item self-report questionnaire developed by the Center for Epidemiologic Studies of the National Institute of Mental Health to measure depressive symptomatology during a l-week time period [ 141. There are four response options for each item, and possible scores range from 0 to 60, from lowest to highest depressive symptomatology. A CES-D score 216 has been shown to be indicative of

et al.

depression [14,34-361 and a score of 227 has been shown to indicate a higher level of depression [35,36]. The Rosenberg Self-Esteem Scale is a lo-item self-report questionnaire that measures personal self-esteem in terms of liking and/or approving of the self [28]. Each item has four response options, and possible scores range from 10 for lowest to 40 for highest self-esteem when giving equal weight to each item. For the present study, scores were transformed to a scale of O-100 from lowest to highest selfesteem. The DUSOCS is a 24-item questionnaire that measures family support and stress and nonfamily support and stress [29,37]. Item response options vary from 1 to 4, and scores range from 0 to 100 from lowest to highest support or stress. The DUFSS measures confidant support with five items and affective support with three items [30]. There are five response options for each question, and scores range from 5 to 25 for confidant support and 3 to 15 for affective support. For this study, scores were transformed to a scale of O-100, from lowest to highest support. The FILE component used in the present study is the 12-item subscale, which measures finance and business strains (311. There are two response options for each question, and differential weights are given to the items for scoring. For the present study, scores were transformed to a scale of O-100 from lowest to highest financial strain. Providers and the medical record auditor rated severity of illness using the Duke Severity of Illness (DUSOI) Checklist [38,39]. The DUSOI Checklist requires listing all health problems and rating each problem for severity by using four severity parameters (symptom level, complication level, prognosis, and treatability) on a five-point scale. Scores are generated on a scale of 0- 100 from lowest to highest severity for each health problem separately, overall for all problems combined, and for comorbidity associated with any given problem. In the present report only the overall DUSOI Checklist scores were used in the analyses. Providers also completed a modified QL-Uniscale on each patient at the time of the index visit to indicate what they perceived as the quality of life of the patient.

Criterion Indicators for Anxiety and Depression To determine the cross-sectional predictive effect of DUKE scales for symptoms of anxiety and/or depression, cutoff scores on the SAI and CES-D were selected as criterion indicators. For anxiety the criterion score of SAI 246 was selected because it was the cutoff score for the upper tertile in this study population. Also, previous studies had found SAI mean scores of 35.7 ? 10.4 SD for normal working adults, compared with 42.4 + 13.8 SD for general medical patients and 49.0 * 11.6 SD for psychiatric patients with a diagnosis of anxiety reaction [ll]. The 70th percentile for general medical patients was ~48, and for patients with a clinical diagnosis of anxiety it was 253 [l I]. For depression the criterion of CES-D 216 was chosen because previous studies had identified this cutoff score as predictive of depression as measured by psychiatric interview [14,34-361. Also, this score corresponded very closely to the cutoff score of CES-D ~18 for the upper tertile in the present study population.

Statistical Analyses Spearman rank-order correlation coefficients were used scores from different questionnaires. The Student t-test test for differences in mean scores of continuous variables. (Y was used to determine the reliability of questionnaires internal consistency [40].

to compare was used to Cronbach’s in terms of

Anxiety

and Depressive

Symptoms

by DUKE

Cross-sectional predictive accuracy of questionnaire scores for identifying symptoms of anxiety and depression was tested by measuring the area under receiver operating characteristic (ROC) curves derived by plotting sensitivity against (1 - specificity) at multiple score cutoff points [41]. Also, for each cutoff point, the sensitivity, specificity, positive predictive value, negative predictive value, and likelihood ratios [sensitivity divided by (1 - specificity)] were calculated. Logistic regressions were used to calculate odds ratios for the prediction of anxiety and depression by the combination of questionnaire scores and sociodemographic factors.

RESULTS study Pogutation Of the 561 adult patients who were asked to enter the study, 534 (95.2%) consented, and 413 (73.60/)D were included in the analyses. The 121 patients were excluded because 50 could not complete the questionnaires, 42 had excessive omissions, 28 were too sick, and one had a missing medical record. The mean age of the study group was 40.4 (* 13.1 SD) years; 58.6% were women; 47.2% were African-Americans and 52.8% whites; 32.4% were below the high school graduate level; 22.8% were not working at jobs or keeping house; 43.3% were not married; and 13.7% were living alone. Their mean Green SES score was 55.4 + 8.5 SD on a scale of 26 to 85 from lowest to highest SES. Patients had a large number and variety of health problems at the baseline visit (a total of 798 problems, or 1.9 per patient). Details of health problem prevalence and comorbidity have been reported previously [38,39].

87 -0.44, respectively (p ~0.0001 for all correlations described in this paragraph). Reliability of the questionnaires was supported by Cronbach a values of 0.70 for the 10 mental health items of the DUKE, 0.90 for the SAI, 0.88 for the CES-D, and 0.83 for the Rosenberg Self-Esteem Scale.

Sociodemographic

Risk Factors for Anxiety

As shown in Table 1, the prevalence of high anxiety symptoms (SAI 246) was 35.1% and of high depression symptoms (CES-D ~16) was 43.3%. Younger age, female gender, education less than high school graduation, being single, not working, and lower socioeconomic status (SES) were statistically significant risk factors for anxiety. These same factors plus African-American race and living alone placed patients at risk for depression. Other analyses by gender and race showed that white females were more at risk for both anxiety (40.7%) and depression (50.4%) than white males (25.0% for anxiety and 23.7% for depression). African-American males were more at risk for depression (48.5%) than white males (23.7%), but there was no difference for anxiety. There were no statistically significant differences between African-American and white women or between female and male African-Americans for either anxiety or depression.

TABLE 1. So&demographic pression symptoms in primary

risk factors for anxiety care patients Anxiety”

Sociodemographic N

faCt0I-S

Comparison of Mental

Health

Measures

For comparison of the questionnaires in this report all mental health items were classified into six conceptual constructs: negative affect, positive affect, cognition, personal self-esteem, social self-esteem, and somatic symptoms. The CES-D has at least 1 of its 20 items in all constructs; the DUKE has at least 1 of its 10 mental health items in all except the positive affect construct; the SAI has at least 1 item in 4 constructs, but none that can be classified as social self-esteem or somatic symptoms; and the Rosenberg Self-Esteem Scale has all 10 of its items in the personal self-esteem construct. Scores were correlated for each of the mental health constructs. For correlations of the DUKE with the SAI and CES-D, the strongest correlations were between the negative affect construct scores (0.60 with the SAI, and 0.63 with the CES-D), indicating convergent validity between identical constructs on different instruments. Also, these correlations were higher than all of those for the nonidentical constructs, indicating discriminant validity. High correlations also were shown for somatic symptom scores of the DUKE and CES-D (0.53), indicating both convergent and discriminant validity. Correlations were not as strong for cognition, personal self-esteem, and social selfesteem, and there was less discriminatory effect when compared with scores of nonidentical constructs. Moderately strong correlations were found between the total mental health score of the DUKE and the total SAI (0.67) and the total CES-D (0.65), indicating the overall concurrent validity of the three instruments as indicators of anxiety and/or depression. Also, there were strong correlations between the six-item DUKE anxiety scale and the total SAI (0.62), between the five-item DUKE depression scale and the total CES-D (0.65), and between the total SAI and the CES-D scores (0.70). The personal self-esteem constructs of the DUKE, SAI, and CES-D correlated with the Rosenberg Self-Esteem score at coefficients of - 0.5 1, - 0.46, and

and Depression

Entire group Age Younger (539.5 yr) Older (>39.5 yr) Gender Female Male Race African-American White Education Low (54.4 Green score)

and de-

Depressionb %

N

%

385

35.1

386

43.3

197 188

41.1’ 28.7

193 193

49.2’ 37.3

224 161

39.3’ 29.2

225 161

49.8d 34.2

180 205

36.7 (NS) 33.7

178 208

48.9’ 38.5

120 263

49.2’ 28.5

119 267

57.1’ 37.1

168 217

40.5‘ 30.9

172 214

53.5’ 35.0

54 328

40.7 (NS) 34.2

53 330

58.5’ 40.6

76 304

46.1’ 31.9

75 308

54.7’ 40.3

174 178

43.1’ 23.0

177 177

53.7’ 32.2

‘Anxiety = SAI 246 (scale = 20-80). SAI, State Anxiety Inventory of Spielberger. bDepression = CES-D ~16 (scale = O-60). CES-D, Center for Epidemiologic Studies Depression Scale. ‘p 5 0.05. dp 5 0.01. ‘p 5 0.001.

iMeasured by the Green SES score. Abbreviation: NS, Not significant.

Parkerson

Identifying Sympms with the DUKE

of Anxiety

and Depression

The 10 DUKE items that measure mental health dysfunction were used as a scale to identify symptoms of anxiety and depression as Also, the six indicated by high SAI and CES-D scores, respectively. items on the DUKE anxiety scale and the five items on the DUKE depression scale were used to identify those symptoms. A new DUKE Anxiety-Depression scale (DUKE-AD) was formulated using seven items that had been used on one or both of the DUKE anxiety and/ or depression scales. Conceptually, the selection of DUKE-AD items was an attempt to balance the number of items among the conceptual constructs of mental health, while at the same time neither adding new items nor changing the wording of old items. This required the removal of 3 of the 5 self-esteem items from the total set of 10 mental health items. As shown in Fig. 1, the resulting DUKE-AD has two negative affect, two somatic symptom, two self-esteem (one personal and one social), and one cognition item. Reliability as measured by Cronbach’s a was 0.70 for the DUKE mental health dysfunction scale, 0.56 for the DUKE anxiety scale, 0.61 for the DUKE depression scale, and 0.69 for the DUKE-AD. Scoring of the DUKE-AD is done by summing the item response scores (O-2) to obtain the cotal raw score on a scale of O-14. The

Duke Anxiety-Depression CopyrIght

raw score can be used, or it can be multiplied by 7.143 to obtain a final score on the scale of O-100, fr om 1owest to highest anxiety and/ or depression. Psychometric support for selection of the seven DUKE-AD items was demonstrated by comparing the DUKE-AD with the DUKE mental health dysfunction, anxiety, and depression scales as to their predictive effects for SAI 246 and CES-D ~16 scores in the study population. As shown in Table 2, patients who were classified as having high levels of anxiety or depression symptoms by the SAI and CES-D criterion measures had statistically significantly different mean scores on all four DUKE mental health scales. For example, the mean DUKE-AD score for patients with depressive symptoms (CES-D ~16) was 44.5 2 18.5 SD, compared with 21.7 2 14.4 SD for patients without depressive symptoms (CES-D < 16). Also shown in Table 2 are the odds ratios (ORs) for anxiety and depression calculated from logistic regressions that included DUKE-AD scores and eight sociodemographic factors (age, gender, race, education, marital status, living arrangement, work status, and socioeconomic status). The ORs confirmed the cross-sectional predictive effect of the four DUKE scales (ORs ranging from 1.070 for anxiety symptoms by the DUKE depression scale to 1.096 for anxiety symptoms by the DUKE mental health dysfunction scale). For example, in Table 2, the OR of 1.092 for DUKE-AD scores for predicting

Scale (DUKE-AD)

l 1094 by lha Department of Community Duke Unlver~lly MedIcal Csnler, Durham,

and Family Medlshm. NC, USA.

JNSTRUCTfONS: Here are a number of questlons about your health and feelings. Please read each question carefully and check (4 your best answer. You should answer the questions In your own way. There are no liaht or wrona answers. Yes, describes me exactly

1. Iglveuptooeaslly ...................... 2. I have difficulty concentrating .............. 3. I am comfortable belng around people .......

Somewhat describes me 2

-

-

2

-

-

0

-

No, doesn’t describe me et all

1

0

1

0

1

2

-

DlJRlNG THE PAST WEEK How much trouble have you had wifh: None

4. Sleeping ............................ 6. Getting tlred easily .................... 6. Feellng depressed or sad ............... 7. Nervousness .........................

~ -

0 0 0 0

-

Some -

1

A Lot 2

1 1 1

-

HOW TO SCORE I. 2.

Add the scores next to each of the blanks you checked. If your total score is 5 or greater, then your symptoms excessive.

of anxiety

and/or

depression

may be

(For exact scoring, multiply the total score by 7.143 to obtain the DUKE-AD score on a scale of 0 for lowest to 100 for highest symptom level.)

FIGURE

et al.

1. The Duke Anxiety-Depression

Scale (DUKE-AD).

Anxiety

and Depressive

Symptoms

TABLE 2. Duke Health care patients

Profile

89

by DUKE

(DUKE)

mental health scores as indicators

of symptoms

of anxiety

and depression

in primary

DUKE score: Mean (SD)’ Depressiond

Anxiety’ No. items

DUKE mental health scale

10

Mental health dysfunction Anxiety

6

Depression

5

Anxiety-depression (DUKE-AD)

7

(N %O)

Yes (N = 135)

(N%9)

Odds ratiob

(N=

Anxiety’ (N= 385)

Yes 167)

22.0

43.6'

21.4

40.5'

(13.0) 26.4 (15.7) 24.2 (16.6) 23.2 (14.5)

(17.3) 47.9’ (19.3) 47.9’ (20.7) 47.2’ (19.4)

(13.5) 25.4 (16.1) 22.4 (16.2) 21.7 (14.4)

(17.0) 45.3’ (18.8) 45.8’ (19.6) 44.5’ (18.5)

Depressiond (N = 386)

1.096'

1.086'

1.072’

1.071’

1.070’

1.078’

1.087’

1.092’

OHigh scores indicate poor health (scale, o-100). bOdds ratio (OR) calculated by logistic regression equations including the mental health score combmed with the sociodemographic anxiety or depression. The OR indicates that n units of increase in the health score would increase the chance of anxiety or depression ‘Anxiety = SAI ~46 (scale, 20-80). SAI, State Anxiety Inventory of Spielberger. dDepression = CES-D ~16 (scale, O-60). CES-D, Center for Epidemiologic Studies Depression Scale. ‘p 5 0.0001.

factors as predictors by OR” times.

of

depressive symptoms indicates that a patient with a DUKE-AD score 10 points higher than that of another patient would be 2.4 times more likely to have a ~16 CES-D score than the other patient (OR” = 1.092” = 2.4). Other analyses not shown in Table 2 indicated that the overall cross-sectional predictive accuracy was high in terms of RGC curve areas. For example, the ROC area for the DUKE-AD was 82.0% for symptoms of both anxiety and depression. Cross-sectional predictive indicators for anxiety and depressive symptoms using DUKE scores as predictors are shown in Table 3. Score cutoff points are shown that optimized both sensitivity and specificity. The highest sensitivity and specificity for symptoms of both anxiety and depression were produced using a cutoff score of >30 (scale, O-100) for the new DUKE-AD scale (sensitivity = 78.7% and specificity = 74.6% for anxiety; sensitivity = 73.9% and specificity = 78.2% for depression). A higher sensitivity of 82.4% was shown by the mental health dysfunction scale for anxiety symptoms, but the specificity was lower at 67.0%. Table 3 also shows that the DUKE-AD positive predictive value of 62.5% for anxiety symptoms was higher than the values for predicting

anxiety symptoms by the other scales, and that the DUKE-AD positive predictive value of 72.6% for depressive symptoms was higher than all but the 72.7% for predicting depressive symptoms by the DUKE depression scale. Likewise, the DUKE-AD negative predictive values were higher than all except those for the mental health dysfunction scale. Other analyses not shown in Table 3 indicated statistically sig nificant likelihood ratios ranging from 2.4 to 3.4. For example, the likelihood ratio of the DUKE-AD f or anxiety symptoms was 3.1 (95% confidence interval = 2.4-3.9) and for depressive symptoms was 3.4 (95% confidence interval = 2.6-4.5).

TABLE 3. Predictive indicators for Duke Health Profile (DUKE) depression in primary care patients (N = 386)

mental health scores as indicators

DUKE

mental health scales

Mental

health

dysfunction

Predicted outcomes

cutoff point=

10

Anxietyb Depression’ Anxietyh Depression’ Anxietyb Depression’ Anxietyb Depression‘

>30.0 >30.0 >40.0 B40.0 >30.0 >30.0 >30.0 >30.0

6

Depression

5

“Cutoff point and specificity bAnxiety = ‘Depression

(DUKE-AD)

7

of Health-Related

Outcomes

The DUKE-AD was compared with the SAI and the CES-D for predicting outcomes during the 18 months following the initial clinic visit. As shown in Table 4, baseline SAI scores predicted none of the outcomes, CES-D scores predicted follow-up frequency and referral and/or hospitalization, while DUKE-AD scores predicted all five of the outcomes. For example, the baseline mean DUKE-AD score was

No. items

Anxiety

Anxiety-depression

Prediction

Sensitivity W) 82.4 78.1 73.8 68.1 72.7 69.1 78.7 73.9

of symptoms Positive predictive value (%)

Specificity W) 67.0 70.3 75.7 78.0 75.6 79.8 74.6 78.2

= DUKE score values at which low and high groups were separated for calculation of predictor indicators. were selected for Table 3. High scores for all measures indicate poor health on a scale of 0- 100. SAI ~46 (scale, 20-80). SAI, State Anxiety Inventory of Spielberger. = CES-D 2 16 (scale, O-60). CES-D, Center for Epidemiologic Studies Depression Scale.

of anxiety

57.5 66.9 62.0 70.8 61.6 72.7 62.5 72.6 Cutoff

points

that optimized

and

Negative predictive value (%) 87.5 80.7 84.4 75.8 83.7 76.9 86.7 79.3 sensitivity

90 TABLE during

Parkerson 4. Anxiety and depression 1 &month follow-up F&w-up

scores

status

as predictors

of health-related

FoRmup frequency

Odds d0’ 1-6 Viiits >6Visits Ratio= 0 Visits None 21 Wit (NE 106) (N= 307) (N= 413) (N= 222) (N= 85) (N= 307) (N= 234) (N:‘73)

SAI SEOL+ CESD scorese DUKE-AD

scor&

40.1 (10.7)

40.0 (11.0)

I.003

14.1 (9.7) 27.6 (18.1)

16.3 (10.9) 33.3' (20.3)

1.021

39.5 (11.0)

1.014'

15.4 (10.6) 31.4 (19.3)

41.4 (11.2) 18.6' (11.6) 38.2' (22.1)

1.015

39.4 (11.1)

1.027' l.Ol4f

for

Referral and/or hmpitalization

odds

Predictor (h&m visit)

outcomes

15.3 (10.3) 31.3 (18.7)

42.1 (10.6) 19.5" (12.3) 39.01 (23.6)

ambulatory

primary

FoRow.up severity*

1.023 1.037x 1.016'

adult

patients

FoUow.upchargesb odds

Odds

(N%;)7)

care

(Gi’&) 39.3 (10.9) 15.5 (10.7) 30.9 (18.7)

(N’z’i3)

(Nyb7)

41.5

I.018

odd8 (A%&) 39.6 (10.9) 15.4 (10.7) 30.8 (19.7)

(11.3)

1.023

17.7 (11.2) 37.7, (22.5)

et al.

1.016'

(i’%3)

(N?07)

40.9 (11.3) 17.9 (11.2) 38.I’

I.010

1.022 1.016'

(10.8)

aMean follow-up aud~toraponed Duke Severity of Illness Checklist (DUSOI) score. Scale = O-100 from lowest to highest severity. The cutoff point of ~37.5 separates pattents in the upper tertde from those in the middle and lower teniles. bMean follow-up total charges ior offue health care. The cutoff point of ~$268 separates patwnts m the upper tertile t?om those tn the middle and lower ternles. ‘odds mu” from separate IOQLSOC rewxsion analyses for each baseline vanable as a “redictor of each “utcome vanable after controlling for the effects of age, gender, and race. Here, the odds rat,” (OR) i&ates that n units of tncreax tn SAL CES-D, OI DUKE~AD scores would mcrease the chance of the outcome by OR” urna. %AI, State Anxiety Inventory. Scale = 20-80 from lowest to highest anxiety. ‘CES-D, Cenrer for Epldemlologic St&s Ceprewon Scale. Scale = O-60 f ram lowest I” highest deprewion. ‘p 5 0.05. gp 5 0.01. hDUKE-AD = Duke AnxwyDeprewon Scale. Scale = O-100 fr “m I“west to lughest anxiety and/or deprwon

39.0 ? 23.6 SD for the 73 patients who had at least one referral and/ or hospitalization, compared with 31.3 +- 18.7 SD for the 234 patients who had no referrals or hospitalizations (p I 0.05). Using the same example, the odds ratio (OR) of 1.016 indicates that a patient with a DUKE-AD score 25 points higher than another patient would be 1.5 times more likely to be referred or hospitalized (OR” = 1.01625 = 1.5). Other analyses showed ROC areas for predictive accuracy of baseline DUKE-AD scores to be 58.7% for follow-up, 57.1% for high follow-up frequency, 57.1% for referral and/or hospitalization, 57.5% for high follow-up severity, and 58.6% for high follow-up charges.

Characteristics

of Patients

with High DUKE-AD

Scores

A subset of the study population was identified as a high-risk group for symptoms of anxiety and/or depression, using the DUKE-AD score of >30 as the cutoff point, because sensitivity and specificity were optimum at this cutoff value, as shown in Table 3. This group of 174 (44.8%) high-risk patients was compared with the 214 (55.2%) patients having DUKE-AD scores 530. The high-risk group included more females than the low-risk group (63.8 vs. 53.3%; p = 0.04), more with lower educational level (44.3 vs. 20.7% who did not graduate from high school; p = O.OOO), more who were not working (25.0 vs. 14.6%; p = O.Ol), and more with low (~54.4) Green SES scores (59.9 vs. 42.6%; p = 0.001). There were no statistically significant differences between the two groups for age, race, marital status, or living arrangement. Anxiety and depression levels as measured by the SAI and CES-D were higher for the DUKE-AD high-risk group than for the low-risk group (mean SAI score = 47.5 k 9.1 SD vs. 34.3 f 8.7 SD, p = 0.0000; mean CES-D score = 23.1 * 10.7 SD vs. 10.1 * 6.5 SD, p = 0.0001). Also, as shown in Table 5, there were statistically significant differences between the high-risk and low-risk groups in all of the quality of life, severity of illness, social support, and social stress mean scores, with the exception only of the provider-report of patient quality of life. High-risk patients had lower quality of life scores than the low-risk patients (e.g., 63.4 vs. 82.8 patient-report Spitzer QLIndex scores), higher severity of illness scores (e.g., 46.7 vs. 39.4 provider-report DUSOI), lower social support scores (e.g., 47.4 vs. 56.7 DUSOCS family support), and higher social stress scores (e.g., 17.7 vs. 10.9 DUSOCS family stress).

TABLE 5. Quality of life, severity social stress scores by level of Duke AD) scores

of illness, social support, and Anxiety-Depression (DUKEAnxiety-depression level (DUKE-AD score)’

Measures (scale O-100) Quality of life Patient-report (Spitzer)d Provider-report (Spitzer)d Self-esteem (Rosenberg) f Perceived health (DUKE)g Severity of illness Provider-reported (DUSOI)h Auditor-reported (DUSOI)h Pain (DUKE)g Disability (DUKE)8 Social support Affective support (DUFSS)’ Confidant support (DUFSS)’ Family support (DUSOCS)k Nonfamily support (DUSGCS)k Social stress Financial strain (FILE)” Family stress (DUSCCS) k Nonfamily stress (DUSCXZS)k

Low (530)6 (mean + SD)

High (>30)c

(mean f SD)

82.8 69.4 83.2 78.3

+ 2 2 t

18.3 19.8 12.5 28.4

63.4 65.9 72.8 61.0

-+ 2 ? 2

28.3’ 22.2 (NS) 12.3’ 35.4’

39.4 35.3 41.9 14.8

2 2 r ”

17.1 16.2 32.8 27.6

46.7 42.1 58.3 26.7

k k f t

19.3’ 17.7’ 31.8’ 33.9’

84.3 82.1 56.7 51.3

e 2 2 2

15.6 15.1 24.7 24.9

75.5 71.4 47.4 44.4

2 2 2 2

20.6’ 19.6’ 24.6’ 24.1’

10.9 ? 12.5 16.0 k 17.7 11.3 t 16.9

“Duke Anxiety-Depression Scale (scale, o-100). *N = 214. ‘N = 174. dSpitzer’s Uniscale. ‘p 5 0.0001. fRosenberg’s Self-Esteem Scale. aDuke Health Profile. hDuke Severity of Illness Checklist. ‘p 5 0.001. JDuke-UNC Functional Social Support Questionnaire. kDuke Social Support and Stress Scale. ‘p 5 0.01. “Family Inventory of Life Events. “p ZZ 0.05. Abbreviation: NS, Not statistically significant.

17.7 * 17.4’ 25.3 2 19.4’ 15.4 f 16.4”

Anxiety

and Depressive

Symptoms

by DUKE

At the baseline visit, although the providers did not know which patients had high-risk DUKE-AD scores, they made a clinical diagnosis of anxiety or depression in the high-risk group more often than in the low-risk group (9.8% in the DUKE-AD high-risk group vs. 1.9% in the DUKE-AD low-risk group for anxiety, and 2.9 vs. 1.4% for depression; p = 0.003). These diagnostic rates compare with a rate of 6.7% for anxiety in patients with SAI scores ~46 vs. 4.0% with ~46 (p = 0.58), and a diagnosis rate of 1.8% for depression in patients with CES-D scores ~16 vs. 2.7% with <16 (p = 0.09). There was very little difference between the DUKE-AD high-risk and low-risk groups for the prevalence of clinical diagnoses of mental and social health problems other than anxiety and depression (16.1% prevalence for high-risk patients, and 14.0% for low-risk patients). The most frequent other mental and social problems in the high-risk group were tobacco abuse (10.3%), sexual problems (2.3%), schizophrenia (1.7%), alcohol abuse (1.7%) and family problems (1.1%); and in the low-risk group, tobacco abuse (8.4%), alcohol abuse (2.8%), sexual problems (0.9%), and situational stress (0.9%). During the 18-month follow-up period, additional study patients were diagnosed as having mental or social health problems, with the result that the overall 18-month prevalence for the entire group of 388 patients was 14.4% in the DUKE-AD high-risk group vs. 3.7% in the low-risk group for anxiety, 2.9 vs. 1.9% for depression, 1.1 vs. 0.0% for combined anxiety and depression, and 24.1 vs. 20.6% for other types of mental or social health problems. The combined provider-identified prevalence for high- and low-risk patients was 8.5% for anxiety, 2.3% for depression, 0.5% for both anxiety and depression, and 22.2% for other types of mental or social problems. Although the mean number of all health problems at baseline was higher for high-risk than for low-risk patients (2.1 ? 1.1 SD vs. 1.7 ? 1.0 SD; p = 0.003), and the mean overall DUSOI severity of illness was higher for high-risk patients (46.7 ? 19.3 SD vs. 39.4 + 17.1 SD; p = O.OOOl), the presence of comorbid health problems other than anxiety, depression, or other mental and social problems differed very little between the high-risk and low-risk groups. The five most frequent nonpsychosocial health problems in both groups were hypertension (28.7% in high-risk vs. 26.2% in low-risk patients), lipid disorder (9.8 vs. 6.1%), diabetes type II (7.5 vs. 7.9%), acute bronchitis (7.5 vs. 7.9%), and obesity (5.7 vs. 7.9%). None of these prevalence differences were statistically significant. Although as shown in Table 4, baseline DUKE-AD scores predicted all five outcomes when the full range of DUKE-AD scores was used in the calculations, other analyses showed that patients in the high-risk group (at the cutoff score of ~30) had only one outcome in which they were significantly different from the low-risk group. High-risk patients were more likely to have at least one return visit than low-risk patients (81.0 vs. 67.8%; p = 0.003). Patients with CES-D scores ~16 were more likely to have frequent follow-up visits (more than six) than those with scores ~16 (32.8 vs. 22.2%; p = 0.04) and to have at least one referral or hospitalization (29.8 vs. 17.7%; p = 0.02). Patients with SAI scores 246 compared with those with <46 had no statistically significant differences in any of the five outcomes.

DISCUSSION This study has demonstrated in one rural primary care practice that the 7-item DUKE-AD subscale of the 170item DUKE questionnaire measured conceptual constructs of anxiety and depression that are similar to those on 2 longer, more extensively validated anxiety and depression scales: the 20-item SAI and the 20-item CES-D. At scores >30 (scale = O-100), the very brief DUKE-AD identified patients

91 with high scores for both of these established instruments at sensitivities and specificities greater than 70%. For quick assessment of symptoms of anxiety and depression, DUKE-AD raw scores can be added easily and used as cutoff points for determination of high risk (e.g., a raw score of ~5 is equivalent to a score of >30 on the O-100 scale). Since neither the SAI nor the CES-D includes all the DSM-IV diagnostic criteria for anxiety and/or depression [6], they are not instruments for establishing clinical diagnoses. However, they are credible standards for testing questionnaires such as the DUKE-AD when the goal is not to establish a definitive diagnosis, but rather to identify patients who have high levels of anxiety and/or depression symptoms. For symptom identification the DUKE-AD may be preferable to the SAI and the CES-D in the primary care setting because of its brevity and simplicity. Also, the DUKE-AD can be administered as part of the entire 17-item DUKE, which contains scales for physical health, social health, perceived health, pain, and disability. These scales have been shown in another report to predict follow-up severity of illness, utilization, and cost [42]. Conceptually, the DUKE-AD contains four items that are closely related to the DSM-IV criteria for both anxiety and depression (sleep disturbance, fatigue, difficulty with concentration, and impairment of social functioning). In comparison with other combinations of DUKE items, the 7-item DUKE-AD has a more even balance of negative affect, cognition, self-esteem, and somatic symptoms than the subset of all 10 DUKE mental health dysfunction items. The DUKE-AD contains somatic symptoms, none of which are included on the fiveitem DUKE mental health scale, and unlike the six-item DUKE anxiety scale and the five-item DUKE depression scale the DUKE-AD does not attempt to distinguish anxiety from depression. Psychometrically, in cross-sectional prediction of high levels of anxiety and depressive symptoms the DUKE-AD performed as well or better than the other DUKE mental scales. Further support for clinical validity of the DUKE-AD was the ability of its scores at the baseline clinic visit to predict clinical outcomes during 18-month follow-up. While the predictive effects were very modest in strength (i.e., ROC areas ranging from 57.1 to 58.7%) they were statistically significant for all of the five outcomes measured. In contrast, the SAI predicted none of the outcomes, and the CES-D predicted only two outcomes. While the three mental health instruments identified a large proportion of high-risk patients in the study population (35.1% for anxiety by the SAL 43.3% for depression by the CES-D, and 44.8% for anxiety and/or depressive symptoms by the DUKE-AD), the providers made clinical diagnoses of anxiety or depression in relatively few patients. A diagnosis of anxiety was made for 6.7% of SAI high-risk patients and for 9.8% of DUKE-AD high-risk patients, and a diagnosis of depression was made for 1.8% of CES-D high-risk patients and for 2.9% of DUKE-AD high-risk patients. Comparable data for the prevalence and provider detection rates for patients with high SAI scores were not found in the literature. However, for depression the 43.3% prevalence of CES-D 216 is similar to the 35% found by Coulehan et al. [36] and the 47% by Schulberg et al. [35] in general medical clinics. A lower rate of 21.0% was found by Hankin and Locke in a health maintenance organization [43]. With regard to the rate of clinical diagnoses by providers of depression in high-risk patients, providers in the Hankin and Locke study determined that 14.7% of patients with 2 16 CES-D scores were depressed. However, the detection rate was based on provider responses to a questionnaire that asked them specifically about depressive symptoms, rather than on unsolicited diagnoses recorded in the medical record [43]. Coulehan et al. abstracted diagnostic information from the medi-

92 cal record only for patients with a Diagnostic Interview Schedule (DIS) diagnosis of major depressive disorder and for a 20% sample of nondepressed patients. Using this method, they found that 44% of the DIS depressed patients and 1.0% of the nondepressed patients had been diagnosed by their providers [36]. Schulberg et al. found that 4.1% of all primary care study patients were diagnosed by their providers as having depression, but the distribution by high or low CES-D scores was not reported [35]. Regardless of similarities or differences between anxiety and depression as to their definitions and diagnostic criteria, and regardless of whether or not the level of patient symptoms justifies a clinical diagnosis, it is very clear from the present analyses that the primary care patients in this study who had DUKE-AD scores >30 were very different from those with scores 530. High-risk patients were more likely to be women, less well educated, not working, and with lower socioeconomic status. Their self-reported quality of life and social support were lower, and their social stress, pain, and disability were higher than that of low-risk patients. Their provider- and auditor-reported severity of illness were higher than that of the low-risk group. All of these characteristics indicate that the high-risk patients might need special help from their health care providers, and that identification of symptoms of anxiety and depression with a brief instrument such as the DUKE-AD could be beneficial for patients. The outcome data indicated for this particular high-risk group that, while they were more likely to be seen for at least one follow-up visit than the low-risk group, their follow-up was no different from that of the low-risk group in terms of frequency of visits, referrals, or hospitalizations. The unanswered question is whether they would have been seen more often and received more attention from their providers if at their baseline clinic visit they had been identified as high-risk patients by use of the DUKE-AD questionnaire. might have made a differOne indicator that use of the DUKE-AD ence in patient care was the finding in this study that the provider assessment of patient quality of life was no different between high-risk and low-risk patients, whereas the high-risk patients themselves rated their own quality of life much lower than did the low-risk patients. This discrepancy between provider and patient perceptions may reveal a low level of provider awareness of psychosocial problems suffered by their patients. If the providers had asked their patients the seven brief DUKE-AD questions either face-to-face or by questionnaire, their perception of patient well-being might have been quite different. Further studies are needed to test the effectiveness of the DUKE-AD as a screener for anxiety and depression as diagnosed by DSM criteria. Also, studies are needed to examine the clinical usefulness of the DUKE-AD and the other DUKE scales, particularly as to how they might improve the recognition of dysfunctional conditions such as anxiety and depression by primary care providers and enhance the overall quality of care for their patients. Compktion of the DUSOI Checklists at thetime of patient visits was perfomed by W. E. Broadhead, M.D., Ph.D., James W. R. Harding III, M.D., M.P.H., Janet Jezsik, P.A. SC., Todd Shapky-Q umn, M.D., and Bret C. Williams, M.D., M.P.H. Funding was provided by Glaxo, Inc. (Research Triangle Park, NC) and the Department of Community and Family Medicine, Duke University Medical Center. The authors ave indebted to Allen Frances, M.D., fm his review of the initial manuscript.

References 1. Katon W. The epidemiology of depression in medical care. lntl J Psych Med 1987; 17(l): 93-112. 2. Von Korff M, Shapiro S, Burke ID, et al. Anxiety and depression in a primary care clinic. Arch Gen Psychiatry 1987; 44: 152-156. 3. Schulberg HC, Bums BJ. Mental disorders in primary care: Epidemiologic,

Parkerson

4.

5. 6.

7. 8.

9. 10. Il. 12. 13. 14. 15.

et al.

diagnostic, and treatment research directions. Gen Hosp Psychiatry 1988; 10: 79-87. Eisenberg L. Treating deprewon and anxiety m primary care. Closing the gap between knowledge and practice. N Engl J Med 1992; 326(16): 1080-1084. Frances AJ, Widiger TA, Pincus HA. The development of DSM-IV. Arch Gen Psychiatry 1989; 46: 373-375. American Psychiatric Association. Diagnostic and Statistical Manual of Psychiatric Press, WashMental Disorders, 4th Ed., DSM-IV. A m&can ington, D.C., 1994. Katon W, Roy-Bryne PP. Mixed anxiety and depression. J Abn Psycho1 1991; lOO(3): 337-345. Zinbarg RE, Barlow DH. Mixed anxiety-depression: A new diagnostic category? In: Chronic Anxiety: Generalized Anxiety Disorder and Mixed Anxiety-Depression (Rapee RM, Barlow DH, eds.). Guiiford, New York, 1991. Zinbarg RE, Barlow DH, Liebowitz M, et al. The DSM-IV field trial for mixed anxiety depression. Am J Psychiatry 1994; 151: 1153-1162. Zung WWK. A rating instrument for anxiety disorders. Psychosomatics 1971; 12: 371-379. Spielberger CD. Manual for the State-Trait Anxiety Inventory (Form Y). Consulting Psychologists Press, Palo Alto, California, 1983. Beck AT, Ward CH, Mendelson M, et al. An inventory for measuring depression. Arch Gen Psychiatry 1961; 4: 561-571. Zung WWK. A self-rating depression scale. Arch Gen Psychiatry 1965; 12: 63-70. Radloff LS. The CES-D Scale: A self-report depression scale for research in the general population. Appl Psycho1 Meas 1977; l(3): 385-401. Bumam MA, Wells KB, Leake B, Landsverk J. Development of a brief screening instrument for detecting depressive disorders. Med Care 1988;

26(8): 775-789. 16. Goldberg D, Hillier VC. A scaled version of the General Health Questionnaire. Psycho1 Med 1979; 9: 139-145. 17. Velt CT, Ware JE Jr. The structure of psychological distress and well-being m general populations. J Consult Clin Psycho1 1983; 51: 730-742. 18. Berwick DM, Murphy JM, Goldman PA, et al. Performance of a five-item mental health screening test. Med Care 1991; 29(2): 169-176. 19. Broadhead WE, Leon AC, Weissman MM, et al. Validation of the SDDS-PC Screen for multiple mental disorders in primary care. Arch Fam Med 1995; 4: 211-219. 20. Spitzer RL, Williams JBW, Kroenke K, et al. The PRIME-MD 1000 Study. Presented at the Seventh Annual NIMH International Research Conference on Mental Health Problems in the General Health Sector, Washington, D.C., 1993. 21. Bergner M, Bobbitt RA, Carter WB, Gilson B. The Sickness Impact Profile: Development and final revision of a health status measure. Med Care 1981; 19: 787-805. 22. Parkerson CR Jr, Gehlbach SH, Wagner EH, et al. The Duke-UNC Health Profile: An adult health status instrument for primary care. Med Care 1981; 19(8): 806-828. 23. Stewart AL, Hays RD, Ware JE Jr. The MOS Short-Form General Health Survey: Reliability and validity in a patient population. Med Care 1988;

26(7): 724-735. 24. Ware JE Jr, Snow KK, Kosinski

25.

26. 27.

28. 29.

30.

31.

M, Gandela B. SF-36 Health Survey: Manual and Interpretation Guide. The Health Institute, New England Medical Center, Boston, Massachusetts, 1993. Parkerson GR Jr, Broadhead WE, Tse C-KJ. The Duke Health Profile, a 17-item measure of health and dysfunction. Med Care 1990; 28: 1056-1072. Green LW. Manual for scoring socioeconomic status for research on health behavior. Public Health Rep 1970; 85: 815-827. Spitzer WO, Dobson AJ, Hall J, et al. Measuring the quahty of life of cancer patients, a concise QL-Index for use by physicians. J Chron Dis 1981; 34: 585-597. Rosenberg M. Society and the Adolescent Self-Image. Prmceton Umverwy Press, Princeton, New Jersey, 1965. Parkerson GR Jr, Broadhead WE, Tse C-KJ. Validation of the Duke Social Support and Stress Scale using the Duke Health Profile. Fam Med 1991; -?31 _ _357-360. _ . .. Broadhead WE, Gehlbach SH, deGruy FV, et al. The Duke-UNC Functional Social Support Questionnaire: Measurement of social support in family medicine patients. Med Care 1988; 26: 709-723. McCubbin HI, Patterson JM, Wilson L. Family Inventory of Life Events and Changes (FILE) Form A. Famdy Social Science, St. Paul, Minnesota,

1980.

Anxiety

and Depressive

Symptoms

by DUKE

32. Parkerson GR Jr, Broadhead WE, Tse C-KJ. Development of the U-Item Duke Health Profile. Fam Pratt 1991; 8: 396-401. 33. Parkerson GR Jr, Connis RT, Broadhead WE, et al. Disease-specific versus generic measuremenf of health-related quality of life in insulin-dependent diabetic patients. Med Care 1993; 3 l(7): 629-639. 34. Weissman MM, Scholmskas D, Pottenger M, et al. Assessing depressive symptoms in five psychiatric populations: A validation study. Am J Epidemiol 1977; 106(3): 203-214. 35. Schulberg HC, Saul M, McClelland M, et al. Assessing depression in primary medical and psychiatric pracrices. Arch Gen Psychiatry 1985; 42: 1164-1170. 36. Coulehan JL, Schulberg HC, Block MR, er al. Medical comorbidity of major depressive disorder in a primary medical practice. Arch Intern Med 1990; 150: 2363-2367. 37. Parkerson GR Jr, Michener JL, Wu LR, et al. Associations among family support, family stress, and personal functional health status. J Clin Epidemiol 1989; 42: 217-229.

93 38. Parkerson GR Jr, Broadhead WE, Tse C-KJ. The Duke Severity of Illness Checklist (DUSOI) for measurement of severity and comorbidity. J Clin Epidemiol 1993; 46: 379-393. 39. Parkerson GR Jr, Broadhead WE, Tse C-KJ. Quality of life and functional health of primary care patients. Clin Epidemiol 1992; 45(11): 1303-1313. 40. Cronbach LJ. Coefficient alpha and the internal structure of tests. Psychometrika 1951; 16: 297-334. 41. Hanley JA, McNeil BL. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 1982; 143: 29-36. 42. Parkerson GR Jr, Broadhead WE, Tse C-K]. Health status and severity of illness as predictors of outcomes in primary care. Med Care 1995; 33: 53-66. 43. Hankin JR, Locke BZ. Extent of depressive sympromatology among patients seeking care in a prepaid group practice. Psycho1 Med 1983; 13: 121-129.