The functioning and well-being of patients with unrecognized anxiety disorders and major depressive disorder

Journal of Affective Disorders 43 (1997) 105–119

Research report

The functioning and well-being of patients with unrecognized anxiety disorders and major depressive disorder a, a,1 a a,2 Warren H. Schonfeld *, Carol J. Verboncoeur , Sheila K. Fifer , Ruth C. Lipschutz , Deborah P. Lubeck a , b , Don P. Buesching c , 3 a

Technology Assessment Group, 490 Second Street, Suite 201, San Francisco, CA 94107, USA b Department of Medicine, Stanford University, Palo Alto, CA, USA c The Upjohn Company, Kalamazoo, MI, USA Received 25 March 1996; revised 12 June 1996; accepted 7 October 1996

Abstract This study examines the degree to which untreated anxiety disorders and major depressive disorder, occurring either singly or in combination, reduce functioning and well-being among primary care patients. Adult patients were screened using the SCL-52 to identify those with clinically significant anxiety symptoms. They also completed the Rand Short-Form (SF-36) to measure self-reported patient functioning and well-being. Patients with untreated disorders were identified using the Q-DIS-III-R to diagnose six DIS-anxiety disorders (generalized anxiety disorder, post-traumatic stress disorder (PTSD), simple phobia, social phobia, panic / agoraphobia, obsessive / compulsive disorder) and major depression. Of 319 patients identified, 137 (43%) had a single disorder and 182 (57%) had multiple disorders. Regression models estimated the relative effects of these disorders on health status (SF-36) by comparing patients with the disorders to patients screened as being not-anxious. Estimates of these effects were consistent with available national norms. The estimated effect of each single disorder on all subscales for physical, social and emotional functioning was negative, often as much as a 20–30 point reduction on this 100-point scale. Major depression had the greatest negative impact, followed by PTSD and panic / agoraphobia. For patients with multiple disorders, the presence of major depression was associated with the greatest reduction in functioning status. The impact of untreated anxiety disorders and major depressive disorder on functioning was comparable to, or greater than, the effects of medical conditions such as low back pain, arthritis, diabetes and heart disease.  1997 Elsevier Science B.V. Keywords: Anxiety; Depression; Functioning; Well-being

*Corresponding author. Tel.: 1 1 415 4958966; Fax: 1 1 415 4958969. 1 Present address: Community Healthy Activities Model Program for Seniors, University of California, San Francisco, CA, USA. 2 Present address: Prevention Sciences Group, University of California, San Francisco, CA, USA. 3 Present address: Eli Lilly and Company, Indianapolis, IN, USA. 0165-0327 / 97 / $17.00  1997 Elsevier Science B.V. All rights reserved PII S0165-0327( 96 )01416-4

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1. Introduction Anxiety disorders are among the earliest reported [1] and most common mental health disorders [2]. They were described as early as the 4th century B.C. in the writings of Hippocrates [3]. According to the 1980–1984 Epidemiologic Catchment Area (ECA) study, anxiety disorders have a one-month prevalence rate in the USA of 7.3% [2]. They are chronic conditions [4] that may persist for several years [4,5], just like depression and substance abuse disorders with which they often coexist [5]. Approximately 5% of the population of the USA, or 12 million people, seek treatment for anxiety every year [5], with a substantial cost to the health care system [6]. The majority of patients seeking treatment present to their primary care physician [7,8]. Studies have shown that primary care physicians see more patients with anxiety or depression than patients with diabetes or asthma [9]. Most studies that have examined primary care patients and disability related to mental disorders have focused on depression [10–12]. This research shows depression associated with reduced functioning and well-being equal to, or worse than, such chronic conditions as diabetes and arthritis [12]. Two other studies using ECA data [2] evaluated the impact of panic disorder on functioning and wellbeing [13,14] and found it associated with consequences similar to, or greater than, major depression. Other kinds of anxiety disorders have not been adequately evaluated in this quantitative fashion, although qualitative comparisons of anxiety and depression have been reported [15]. Research documenting the relationship between either anxiety or depression disorders and functioning and well-being has dealt primarily with diagnosed disorders. However, several studies suggest that less than half of the primary care patients having emotional problems may be recognized or treated for them [16–18]. Fifer et al. [19] reported elevated but unrecognized and untreated symptoms of anxiety in 10% of a primary care patient study group. These patients with untreated anxiety reported significantly worse functioning than ‘‘not anxious’’ comparison patients. The current study extends the work of Fifer et al. [19] by estimating the effects of specific disorders

for the subset of patients with symptoms of sufficient number and severity to be classified as a disorder. Its purpose is to quantify the degree to which previously unrecognized and untreated anxiety disorders and / or major depressive disorder, occurring either singly or concurrently, are associated with reduced functioning and well-being. Functioning and well-being were assessed for several groups of patients; those with anxiety disorders and / or major depression compared to those without these disorders; those with a specific type of disorder; and those with a single anxiety disorder or major depression compared to those with multiple disorders. This comprehensive evaluation of functioning and well-being adds to what is currently known about diagnosed disorders by (1) characterizing the effects of specific anxiety disorders and major depression on functioning status, as well as by (2) highlighting the need for treatment among patients suffering from these disorders but previously not diagnosed or treated.

2. Methods

2.1. Study population and site The study was conducted in 1990 and 1991 at a mixed-model health maintenance organization (HMO) located in a region of central Colorado that includes urban (Denver), suburban and rural communities. All 285 primary care physicians under contract to the HMO were invited to participate. The 75 who accepted, for a 26% participation rate, were not different from the declining physicians in terms of training, age, sex or practice size. Practices ranged in size from sole practitioners to group practices of 12. At the time of the study, the HMO served patients with a broad range of economic and educational levels and an average adult age of 40. Approximately 20% of enrollees were members of racial minority groups. The study population was selected from the 10,190 adult primary care patients presenting between November 1990 and April 1991, to the clinics of the 75 participating family and internal medicine physicians. Waiting room staff briefly explained the study to these patients. Those who completed a statement of informed consent were offered a screen-

W.H. Schonfeld et al. / Journal of Affective Disorders 43 (1997) 105 – 119

ing questionnaire and cash honorarium. For patients accepting this waiting room screen, all those between the ages of 21 and 65 who had been enrolled in the HMO for a minimum of six months and who did not have dual health insurance benefits were eligible to continue in the study; 6307 completed the screening process described below. Additional details about the screening procedures and HMO are provided by Fifer et al. [19].

2.2. Procedures Screening and diagnosis of previously unrecognized and untreated anxiety disorders and major depression, as well as the assessment of functioning and well-being, were done in three steps using an initial screening questionnaire, medical record review and face-to-face baseline interview [19]. The entire process took an average of approximately five weeks.

2.2.1. Screening questionnaire While in the waiting room, patients completed a self-administered questionnaire consisting of three components: (a) A five-scale, 52-item symptom checklist for anxiety and depression symptoms (SCL-52) from the longer, validated Symptom Check List 90Revised (SCL-90-R) [20,21]. The five scales, taken in their entirety from the SCL-90-R, measure symptoms of general, phobic, somatic and obsessive / compulsive anxiety, as well as depression. Four additional scales and seven general items from the SCL-90-R were not included in the baseline assessment as they were judged irrelevant to the screening process. (b) A validated, generic measure of functioning and well-being, the Short-Form Health Survey (SF-36) [22]. This widely used instrument, derived from the Medical Outcomes Study, is a comprehensive survey of health-related functioning and well-being that measures eight concepts: Physical functioning, social functioning, role / occupational physical limitation, role / emotional problems, mental health, energy, pain and general health perceptions [23–25]. Each concept is measured on a scale from 0 to 100, with 100

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representing the highest level of functioning and well-being. (c) Questions about diagnosis and treatment developed specifically for this study in order to determine self-reported history of previous treatment. These questions elicited information about treatment for ‘‘worry and stress’’ and were phrased generally to cover the various definitions of anxiety and depression. Respondents who scored high for anxiety on one or more of the four anxiety symptom scales of the SCL-52 and who reported receiving no treatment for an emotional condition during the prior six months, either in the HMO or outside, were eligible for the next phase of the study. The anxiety cut-off point was selected based on pretest data from the study sites, and normative SCL-90-R data [20] for nonmental health patients, indicating that patients with scores $ 61 on any anxiety subscale were above the 86th percentile for anxiety. The screening cut-off point was set at 63, two points higher than the final cut-off point of 61 used during the subsequent baseline interviews, in anticipation that many patients’ scores would decrease at the second administration due to regression to the mean. A total of 4242 patients who scored below the cut-off points on the screening questionnaire were labeled ‘‘not anxious’’ and served as a comparison group with no anxiety disorders.

2.2.2. Medical records reviews The medical records of eligible patients passing the cut were abstracted by a nurse practitioner and a mental health therapist, under the supervision of two general internists, for any notation suggesting recognition or treatment of an emotional condition, diagnosis, counseling, drug therapy or any other form of treatment. Patients whose clinical records (in agreement with their self-report) showed no such notations and no indication of a prescription for a psychotropic drug, and who had no record of any referral to, or care from, the HMO’s mental health provider during the previous six months, were considered to be ‘‘unrecognized and untreated.’’ These patients were invited to undergo a baseline interview. Patients who self-reported no treatment but whose medical records indicated some form of mental

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health treatment were not included in the remainder of the study.

2.2.3. Baseline interviews The baseline interviews took place approximately five weeks after the waiting room screen in order to permit patients having temporary or transitional anxiety to return to their normal status. Patients were asked to complete a longer version of the same self-administered questionnaire that was given at screening and to respond to a structured diagnostic evaluation. The baseline interviews were composed of the following measures: (1) Symptoms: the SCL90-R (the original, longer form of the 52-item symptom checklist used as a screen); (2) Functioning and Well-being: the SF-36 (repeated from the waiting room screen); (3) Physical Comorbidities: a check-list of comorbid conditions developed from pretest data [19] and (4) Diagnostic Evaluation: the quick version, without probes, of the National Institute of Mental Health’s Diagnostic Interview Schedule (Q-DIS-III-R) [26,27]. The Q-DIS-III-R for eight anxiety disorders, major depression, alcohol use and drug use was administered by trained lay interviewers hired for this study to conduct the QDIS-III-R interviews. A total of 637 untreated patients met or exceeded the final cut-off point of 61 on at least one of the four SCL-90-R anxiety subscales. They were considered likely to have clinically significant symptoms of anxiety, which deserved treatment [19]. The Q-DISIII-R was then administered to this group of patients with previously unrecognized and untreated anxiety symptoms. The 319 patients who met the Q-DIS-IIIR diagnostic criteria for one or more of seven disorders [generalized anxiety disorder (GAD), posttraumatic stress disorder (PTSD), simple phobia, social phobia, panic / agoraphobia, obsessive / compulsive disorder (OCD) and major depression] comprised the study sample. 2.3. Statistical methodology In order to estimate the effects of the anxiety disorders and major depressive disorder on functioning and well-being, a series of regression analyses compared patients with disorders to the not-

anxious patients who served as the comparison group. For each scale of the SF-36, a multiple regression model was used to estimate the effects of each disorder on the SF-36 score predicted by the model, as well as the effects of age, gender, the occurrence of multiple disorders, and interactions between these variables. Variables were coded to make the estimated value of each regression intercept correspond to the predicted SF-36 score for a portion of the comparison group of patients. This portion of the comparison group, termed the reference group, was defined to consist of not-anxious female patients aged 25–34. Although any other age–sex group could have been used, this choice facilitated ease of interpretation. By comparison to the reference group, the regression model could predict scores for any other group of patients with differing demographic characteristics and for patients with disorders. This was accomplished by adding the appropriate effects estimated for the characteristics of the group that differed from those of the reference group. For example, to estimate any SF-36 score for a group of male patients aged 25–34 with no disorders, the effect due to gender should be added to the predicted value for the reference group since this effect represents the predicted difference in score between male and female patients. Likewise, to estimate a score for older male patients with no disorders, the appropriate age effect should also be added. Since the age effect corresponds to the estimated difference in scores between patients in successive 10-year age groups, the age effect should be added to make estimates for patients aged 35–44, twice the age effect should be added for patients aged 45–54, and three times the age effect should be added for patients aged 55–64. For each disorder, the model provides an estimate of how much the presence of the disorder affected each predicted SF-36 score. These estimates were made both for single disorders and for multiple disorders by including separate terms in the model for the presence of each disorder, the occurrence of multiple disorders, and the additional interactive effect of each disorder if occurring as part of a multiple disorder. This approach made it possible to estimate the effects of any disorder occurring either singly or as part of a multiple disorder. As a way of testing the validity of the model, the

W.H. Schonfeld et al. / Journal of Affective Disorders 43 (1997) 105 – 119

predicted scores which it estimated were compared to national norms [28] for different age–sex groups and for people with depression. In addition, efforts were made to assess the impact of physical comorbidities on these estimates. Since the number of physical comorbidities was known for all 637 patients who met the cut-off point for anxiety symptoms, a secondary series of regression analyses was performed comparing the 319 patients with disorders against the remaining 318 anxious patients without these disorders, to determine how the presence of physical comorbidities might reduce or enhance the effects attributed to disorders.

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Table 1 Age and gender distribution of not-anxious patients and patients with disorders

Gender Male Female

Not anxious patients (n 5 4242)

Patients with disorders (n 5 335 a)

Number

%

Number

%

1428 2813

34 66

135 200

40 60

35 34 19 12

127 108 74 26

38 32 22 8

b

Age group (years)c 21–34 1477 35–44 1413 45–54 805 55–64 503 a

Includes 16 patients with only alcohol or drug abuse diagnoses. Gender was not recorded for one patient in the not-anxious group. c Age was not recorded for 44 patients in the not-anxious group. b

3. Results Out of all 10,190 presenting patients, 7914 accepted the waiting room screen, and 6307 who completed the screening process were eligible for the study. A survey of those not accepting the screen did not identify any meaningful difference between them and the eligible study participants [19]. A total of 4242 not-anxious patients and 2065 patients exceeding the cut-off point of 63 for anxiety were identified through the initial screening questionnaire. Of the 2065 patients with anxiety symptoms, only 1148 reported receiving no treatment for an emotional condition. At the time of the baseline interviews, 913 of these patients were still enrolled in the HMO, available for the study, and untreated. Only 637 remained above the cut-off point of 61 for anxiety symptoms on the SCL-90-R. A total of 335 previously untreated patients were classified as having disorders. Their distribution by age and gender is compared in Table 1 with the not-anxious patients. Of the 335, 16 were identified with only alcohol or drug abuse diagnoses according to the DIS, and no further analyses are reported for this small group. The remaining 319 patients with anxiety disorders and / or major depressive disorder represented 5.1% of the 6307 eligible patients who were screened. They were similar to other adult primary care patients in this HMO and other managed care plans in terms of age (average age of approximately 40), sex (60% female), marital status (approximately 3 / 4 married), and number of medical comorbidities (average of 1.2) [19].

Out of the 319 patients with the seven disorders examined in this study, 137 had a single disorder and 182 had multiple disorders. The distribution of disorders is shown in Table 2. Major depression occurred most frequently, both as a single disorder and as one of multiple disorders. The effects of specific disorders and demographic characteristics on functioning and well-being are shown in Tables 3, 4 and 5. Table 3 shows the predicted value of each SF-36 score for the reference group of females aged 25–34 with no disorders, as well as the effects due to gender and age. The gender and age effects are almost all statistically significant. The positive effects due to gender indicate that males have higher predicted SF-36 scores than females, ranging from 2.3 to 7.9 points higher, depending on the scale. The 10-year age effects are generally smaller and vary in sign from one SF-36 scale to another. There were no significant interactions between age and gender.

3.1. Effects of single disorders on predicted SF-36 scores Table 4 shows the effects of five single disorders on the predicted SF-36 scores; simple phobia was omitted because it occurred only with other disorders, and OCD was omitted because it occurred as a single disorder for only one patient. The estimated

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Table 2 Distribution of disorders by type Name of Disorder

GAD PTSD Simple phobia Social phobia Panic / agoraphobia OCD Major depression

No. of patients with single disorder (n 5 137)

No. of patients with the disorder as part of a multiple disorder (n 5 182)

Total no. of patients with the disorder (n 5 319)

Number

%

Number

%

Number

%

14 25 0 23 20 1 54

10 18 0 17 15 1 39

41 85 94 66 80 22 104

23 47 52 36 44 12 57

55 110 94 89 100 23 158

17 34 29 28 31 7 50

Table 3 Estimates of SF-36 scores and effects provided by regression analysis of 4577 patients Group / effect

SF-36 functioning levels a Physical functioning

Females aged 25–34 with no disorders Effect for gender (males) Effect for age (10 years) a b c

91.9 2.3 c 2 3.4 c

Social functioning 83.6 4.9 c 1.1 c

Role physical 82.5 5.6 c 2 1.4 b

Role emotional

Mental health

Vitality

84.0

75.6

59.9

4.8 c 1.6 c

3.4 c 0.4

7.9 c 1.2 c

Bodily pain

General health

77.8

77.5

2.3 b 2 1.8 c

2.3 c 2 0.4

All scores are on a scale of 0 to 100, with 100 representing the highest level of functioning and well-being. p , 0.05 for test of hypothesis that effect is 0. p , 0.005 for test of hypothesis that effect is 0.

effect of each of the five disorders on every predicted SF-36 score was negative, and the magnitude of the effects were generally statistically significant. By examining these effects, we can determine which singly occurring disorders have the greatest impact on the various SF-36 scores. Major depression had the most impact on predicted SF-36 scores on five of the eight SF-36 scales; the effects due to major depression were the most negative of any disorder, with score reductions that were typically about 25 points below the predicted scores for the reference group with no disorders. PTSD and panic / agoraphobia also had significant negative effects that were frequently larger than those due to GAD or social phobia. PTSD had significant negative effects across all functioning scales and was estimated to have the second most negative burden on five of the eight SF-36 scales. Social phobia had the least negative effects on four

of the eight SF-36 scales, with effects that were not statistically significant in three cases. The two SF-36 scales most affected by the presence of a single disorder were role-emotional and role-physical. Both PTSD and major depression reduced the role-emotional score by more than 40 points below the predicted scores for the reference group with no disorders. GAD and social phobia reduced the predicted score by more than 20 points. The predicted role-physical score was reduced by more than 20 points by panic / agoraphobia, PTSD, major depression and GAD. Single disorder effects on the other SF-36 scales were typically in the range of 10 to 20 points, except that major depression, as previously noted, had greater effects. In addition to providing an indication of the relative impact of different single disorders on functioning and well-being, these estimated effects in Table 4 can also be used to predict SF-36 scores for

c

b

a

2

2

2 13.9 c 2 7.9 b 2 15.0 c 2 14.2 c 2 9.4 c

91.9

Physical functioning

Social phobia 2 11.4 b Depression 2 4.1 b

2 12.6 b 2 18.1 c 2 5.0 2 10.5 b 2 23.3 c

83.6

Social functioning

SF-36 functioning levels a

Depression 2 11.0 b 2

2 21.1 b 2 29.2 c 2 8.0 2 29.7 c 2 26.9 c

82.5

Role physical

Social phobia 8.1 b Panic /Agora-8.5 c Depression 5.4 b

2

2 28.2 c 2 42.0 c 2 22.0 c 2 14.7 2 46.6 c

84.0

Role emotional

GAD 2 8.5 b Social Phobia 3.3 b

2 2.9 2 9.2 c 2 10.2 c 2 16.0 c 2 27.0 c

75.6

Mental health

All scores are on a scale of 0 to 100, with 100 representing the highest level of functioning and well-being. p , 0.05 for test of hypothesis that effect is 0. p , 0.005 for test of hypothesis that effect is 0.

Interaction effects Disorders with significant interactions with GENDER Disorders with significant interactions with AGE

Effects GAD PTSD Social phobia Panic / agoraphobia Major depression

Reference Group Females aged 25–34 with no disorders

Group / effect

Table 4 Estimates of reference group scores and effects of single disorders on SF-36 scores (n 5 4577)

Depression 2 7.0 b Panic /Agora 2 4.1 b

2 15.8 b 2 23.1 c 2 16.8 c 2 14.8 c 2 24.4 c

59.9

Vitality

2

2

2 12.7 2 13.3 c 2 7.9 2 20.1 c 2 16.2 c

77.8

Bodily pain

Depression 2 5.9 b Panic /Agora 2 6.2 c Depression 3.1 b

2 16.1 c 2 18.8 c 2 12.9 c 2 14.4 c 2 22.6 c

77.5

General health

W.H. Schonfeld et al. / Journal of Affective Disorders 43 (1997) 105 – 119 111

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Table 5 Estimates of reference group scores and effects of each disorder, when part of a multiple disorder, on SF-36 scores (n 5 4577) Group / effect

SF-36 functioning levels a Physical functioning

Reference group Females aged 25–34 with no disorders Females aged 25–34 with multiple disorders Effects GAD PTSD Simple phobia Social phobia Panic / agoraphobia OCD Major depression a b c

Social functioning

Role physical

Role emotional

Mental health

Vitality

Bodily pain

General health

91.9

83.6

82.5

84.0

75.6

59.9

77.8

77.5

87.3

76.0

67.3

66.9

65.3

45.0

67.2

64.4

2 6.5 b 2 7.4 b 2 3.4 2 0.8 2 0.2 3.0 2 5.4 b

2 5.8 2 5.0 2 6.4 b 1.4 1.9 2 6.5 2 9.0 b

2 1.0 2 7.8 2 9.3 9.7 b 2 0.5 3.7 2 3.7

2 7.9b 2 0.8 2 2.6 2 2.5 3.5 , 0.1 2 5.8 b

1.4 2 2.9 2 4.1 2 1.7 2.3 2 5.8 2 4.2

0.3 2 5.7 b 0.1 2 0.5 3.3 2 3.2 2 8.0 b

1.2 2 9.1 2 6.1 2 13.5 b 8.3 15.6 2 27.8 c

2 2.4 2 1.4 2 1.7 2 2.9 0.9 2 2.8 2 13.3 c

All scores are on a scale of 0 to 100, with 100 representing the highest level of functioning and well-being. p , 0.05 for test of hypothesis that effect is 0. p , 0.005 for test of hypothesis that effect is 0.

specific groups of untreated patients with single disorders. For example, the predicted physical-functioning score for females aged 25–34 with major depression is 82.5, obtained by adding the effect for major depression (i.e., 2 9.4) to the reference group score (i.e., 91.9). Up to this point, the results have focused on the additive effects of single disorders, as well as effects due to age and gender. However, some disorders showed a significant interaction with either age or gender, as shown at the bottom of Table 4. For three different SF-36 scales, i.e., role-physical, energy and general health, there was a significant negative interaction between gender and the presence of major depression; thus, men with major depression had a further decrement in these scores compared to women with major depression. This decrement would result in lower predicted role-physical and general health scores for males with major depression than for females with major depression, reversing in these cases the general observation made previously about males having higher predicted SF36 scores than females. On the energy scale, predicted scores for both males and females with major depression are similar. Panic / agoraphobia also had significant negative interactions on three scales, i.e., role-emotional, energy and general health. These

interactions with age show that older patients with panic / agoraphobia had significant decrements in these aspects of functioning and well-being beyond the overall effects of age shown in Table 3.

3.2. Effects of multiple disorders on predicted SF36 scores The impact of a specific disorder that occurs as part of a multiple disorder may be different than when it occurs as a single disorder. Therefore, to estimate SF-36 scores for patients with two or more disorders, it is not appropriate to add their separate single disorder effects to the predicted scores for the reference group. Instead, as discussed below, the regression model provided estimates of the effects due to each disorder when it occurred as one of multiple disorders. In addition to calculating these specific multiple disorder effects, the regression model was designed to estimate the overall effect of having multiple disorders on each predicted SF-36 score. This nonspecific ‘‘multiple-disorder’’ effect can be interpreted as the average impact of having more than one disorder, without considering the specific effect of the particular combination of disorders involved. When this multiple-disorder effect is taken into

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account, it reduces the predicted scores. For example, the second row in Table 5 shows the lower predicted SF-36 scores for females aged 25–34 with multiple disorders, compared to the predicted scores on the first row for the reference group with no disorders, before taking into account how the specific disorders present further affect the scores. Table 5 also shows the additional, and usually smaller, effects of each specific disorder, when part of a multiple disorder, beyond the overall multipledisorder effect. Disorders with a specific multiple disorder effect that is negative reduce functioning and well-being even more than average; disorders with a positive effect, less than average. Thus, the effect estimates in Table 5 show the relative disabling effects of specific disorders when part of a multiple disorder. The comparison between the first two rows suggests that the two SF-36 scales most affected by having a multiple disorder are role-emotional and role-physical, as was the case for single disorders. While this is true in general, particular combinations of multiple disorders may impact predicted SF-36 scores somewhat differently than the overall multiple-disorder effect. In order to estimate specific SF-36 scores for a patient with more than one disorder, the effects from Table 5 due to each specific disorder composing a multiple disorder must be added to the predicted value for patients with multiple disorders that is shown in the second row of Table 5. For example, the predicted physical-functioning score for females aged 25–34 with both major depression and GAD, but no other disorders, is 75.4 ( 5 87.3 1 [25.4] 1 [26.5]). Of course, if the patient is not a

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female aged 25–34, then the appropriate gender and age effects from Table 3 must be added as well.

3.3. Comparison with national norms It is useful to compare the predictions generated by the regression model with national norms, available from a study of a representative sample (n 5 2,467) of the U.S. population [28]. This gives some indication of how well the model estimates both the overall level and patterns of SF-36 scores across various age–sex groups and the eight SF-36 scales. Table 6 shows both the norms and predictions for females and males aged 25–34. Since the norms for age–sex groups are based on a representative sample of the U.S. population, whereas the predictions are for primary care patients with no disorders or elevated symptoms of anxiety, an exact match between the two sets of scores should not be expected. Even so, it is clear that the predictions are quite close to the norms. They show very similar patterns of differences between males and females of the same age (i.e., males have scores typically between 2 and 6 points higher than females). Furthermore, the differences between predicted scores and norms for a given SF-36 scale are much less than the differences between the eight scales (e.g., for females aged 25–34, the largest difference between predictions and norms is 4.2 points, on the role-physical scale, whereas the scores on different scales range from about 60 to 90). Another comparison between model predictions and national norms is shown in Fig. 1 for females aged 35–44. There are eight pairs of bars, one pair

Table 6 Comparison of predicted SF-36 scores with norms a Group

SF-36 scale scores Physical functioning

Social functioning

Role physical

Role emotional

Mental health

Vitality

Bodily pain

General health

Females 25 – 34 Norms Predictions

89.1 91.9

84.1 83.6

86.7 82.5

82.3 84.0

72.5 75.6

58.0 59.9

79.6 77.8

74.8 77.5

Males 25 – 34 Norms Predictions

94.9 94.2

85.7 88.5

91.9 88.1

82.2 88.8

74.1 79.0

64.7 67.8

83.1 80.1

79.4 79.8

a

Norms from SF-36 Health Survey Manual and Interpretation Guide [28].

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Fig. 1. Comparison of predicted SF-36 scores with norms for females aged 35–44 and patients with major depression.

for each of the eight SF-36 scales. The left bar in each pair shows the norms and the right bar shows predictions. As in Table 6, the female norms represented by the total height of each left-hand bar are derived from the sample of U.S. females, and the predictions represented by the total height of each right-hand bar are for female primary care patients without disorders. The norms for a group of 502 patients with major depression or dysthymia [28] are shown by the black portion of the left bar in each pair. These norms are compared with predictions for patients with major depression, shown by the black portion of the right bar in each pair. Since the mean age of the 502 patients was 41.6, and 75.8% were female, the predictions were made using the regression model for females aged 35–44 with major depression as a single disorder. Once again, there is close agreement between the predictions and the norms for patients

with depression on most SF-36 scales, both in overall magnitude and patterns. Even the largest difference, about 10 points on the role-physical scale, is much smaller than the amount of score reduction in the group with major depression (i.e., compared to females aged 35–44 without major depression) or the differences between scales.

3.4. Effects of physical comorbidities From the regression analyses comparing the 319 patients with disorders against the 318 patients with anxiety symptoms but no disorders, we estimated a set of disorder effects similar to those reported in Tables 4 and 5 for the main series of analyses. In addition, we also controlled for physical comorbidities in these secondary analyses, a refinement not possible in the main analysis with the comparison group because comorbidity information was not

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collected for not-anxious patients. We were able to discern the extent to which physical comorbidities affected the estimates of disorder effects in these additional secondary analyses. Of the 13 statistically significant (i.e., p , 0.05) estimates of disorder effects (not shown) obtained when the regression analysis was performed on the 637 patients without controlling for the number of physical comorbidities, 10 remained statistically significant when controlled in this manner. The three estimated disorder effects that lost significance when controlled were the effect of social phobia on the role-physical scale and the effects of PTSD on the social scale and the general health scale. Both estimated effects for PTSD still maintained borderline significance (i.e., p , 0.10). Controlling for physical comorbidities reduced the estimated negative effect of PTSD on the social scale from 2 5.3 to 2 4.8, and on the general health scale from 2 5.4 to 2 3.9. No other significant effects, which ranged from 2 7.3 to 2 26.1, were changed by more than 0.2.

4. Discussion The purpose of this study was to evaluate the functioning and well-being of patients with anxiety disorders and major depressive disorder in a primary care setting. Patients with these previously undiagnosed disorders reported significantly compromised health status compared to similar patients without these disorders. The reduction in health status associated with anxiety disorders and major depression was comparable in magnitude to that reported for chronic physical illnesses [12], with the precise degree of health burden depending upon the specific disorder. A wide range of patients’ emotional and physical functioning capabilities were negatively affected, some considerably more than others. Furthermore, there is evidence that the effects of anxiety disorders and major depression are significant, even when controlled for the presence of physical comorbidities.

4.1. Effects of single disorders on health status While all disorders were estimated to have a negative effect on health, some were associated with substantially worse health status than others. We

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were able to observe the impact of five specific single disorders: GAD, PTSD, social phobia, panic / agoraphobia and major depression. Of these, major depression, PTSD and panic / agoraphobia had noticeably greater negative effects on the eight SF-36 scales than the other disorders, ranging from 7.9 to 46.6 points below the scores for the reference group with no disorders, compared with reductions from 2.9 to 28.2 points for GAD and social phobia. The severity of these disorders can be assessed by comparing their predicted effects to the impact of chronic physical problems. For example, the occurrence of low back pain is associated with a reduction of 9.1 points on the physical functioning scale used in the Medical Outcomes Study questionnaire [12]. The negative effects on physical functioning in this study were comparable for major depression (i.e., 2 9.4), worse for panic / agoraphobia (i.e., 2 14.2) and somewhat less for PTSD (i.e., 2 7.9). However, even the effects of PTSD were worse than the impact of arthritis (27.5) and diabetes (26.6) [12]. As important as observing the specific impact and variations associated with different disorders is noting that all disorders had a substantial effect on a majority of the eight SF-36 scales measuring aspects of functioning and well-being. Most of the effects were both statistically and clinically significant. For example, the negative effect of social phobia on the general health perceptions scale was 13 points, about the same as associated with diabetes and congestive heart failure [12]. Although major depression appears to have the greatest negative effect of any single disorder in this study, we cannot be confident in concluding that this effect was due solely to major depression. Due to our sampling design, all patients receiving a diagnosis of major depression also were symptomatic for anxiety, and we were unable to control for the effects of these comorbid anxiety symptoms. Although patients meeting the diagnostic criteria for anxiety disorders also obviously reported anxiety symptoms, these symptoms were likely to be related to the anxiety disorders for which they were diagnosed and probably did not represent an additional health burden for these patients. However, about 70% of those with anxiety disorders only were estimated to have additional symptoms of depression exceeding the cut-off point of 61 on the SCL-90-R depression subscale [19], so that the negative health effects exhibited by

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these patients may not have been due solely to their anxiety disorder. This caveat mirrors the situation for patients with major depression only.

Similarly, although major depression is more prevalent among women [29], in some areas of functioning and well-being, it may impact men more.

4.2. Effects of disorders in a multiple disorder condition

4.4. Functioning capabilities affected by disorders

Our findings also confirm the health burden of multiple disorders. Major depression generally showed the most negative effects of any disorder occurring as part of a multiple disorder. By contrast, panic / agoraphobia, when in a multiple disorder, showed the least additional negative effects, none of which were significant. This is surprising in light of previous research [13,14] suggesting that panic is one of the more severe anxiety disorders, perhaps on a par with major depression. OCD, which is also considered to be very functionally debilitating, likewise had no statistically significant effects. However, it had the greatest negative impact on patients’ reports of bodily pain out of any disorder studied here within a multiple disorder condition, and the greatest negative impact next to depression on social functioning. Interestingly, OCD was reported as having a comparative positive effect in four domains. Whether these positive effects were the result of patients’ reliance upon their OCD behavior as a means of coping with their co-existing disorders, or an anomaly of the small OCD sample size (n 5 23), is not known.

The health burden associated with these disorders was widely distributed across the eight SF-36 scales. The role-emotional scale, a measure of emotional capabilities to carry out daily responsibilities, showed the greatest negative effects from disorders, whether occurring singly or in a multiple disorder condition. Surprisingly, the scale next most affected was role-physical, which measures physical capabilities to carry out daily responsibilities. Substantial negative effects were also seen in social functioning capabilities, energy and vitality, perceived bodily pain, and in patients’ general perceptions of their overall health status. Therefore, not only measures most sensitive to mental health, but also those scales sensitive to physical health, demonstrated a health burden associated with undiagnosed disorders. This impact on physical health, as measured by the SF-36, was also noted for major depression in the Medical Outcomes Study [12]. The fact that undiagnosed patients report reductions in physical as well as emotional health status may help to explain their tendencies to be high users of primary health care services [30].

4.5. Predictive ability and limitations of the model 4.3. Effects of age and gender For the most part, men had somewhat higher functional status and well-being than women with the same disorder. There was, however, no one simple pattern describing the impact of age on health status. Increased age was generally associated with higher scores on the SF-36 scales for emotional and social functioning and lower scores for physical functioning. In addition, certain disorders affected people differently depending on age and gender. For example, panic / agoraphobia produced larger decrements in some functional areas for older individuals. Although other data show that panic / agoraphobia is more prevalent among younger aged cohorts [29], the current analyses suggest that when it occurs in older people it may have a greater negative impact.

It should be noted that even though the effects of disorders on SF-36 scores achieved statistically significant levels, and thus clearly affected the predicted scores, the model is limited in its ability to predict functioning and well-being. There are undoubtedly other factors that affect SF-36 scores. Since the only additional variables examined in the current analysis were patients’ age and gender, it is likely that there are relevant factors that have been omitted. One such factor is a count of physical comorbidities, which was not collected for all patients because it was not relevant to the larger prospective study of which the current analysis is only a part. Without data on physical comorbidities for the comparison group, we could not control for this

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variable in the main analysis. However, the secondary analysis for the 637 patients with symptoms of anxiety suggests that anxiety disorders and major depressive disorder significantly affect most SF-36 scores even when controlling for physical comorbidities. The estimates of the disorder effects in this secondary analysis do not change substantially when physical comorbidities are included in the model. These results are supported by other research findings [12,31–33]. In general, the effects of mental health disorders are similar to, or larger than, those of chronic medical conditions and are only reduced slightly when controlled for physical comorbidities [31,32]. The fact that the regression model predictions agree so well with national norms for different age– sex groups and for patients with depression lends validity to the model. Of course, there is no way of knowing if the predicted effects for anxiety disorders agree with national norms because such norms do not exist in the literature. This is, of course, one reason why the current research was undertaken, i.e., to quantify the effects of other disorders, in addition to major depression. We can say, however, that the effects for age, sex and major depression, as estimated by the model, are consistent with data from national norms. Since all patients studied here were seeking primary care at a HMO, the extent to which the precise estimates resulting from this study can be generalized to people not seeking care or using other kinds of care is unknown. Also, the analysis does not include patients with previously recognized and / or treated disorders, and thus conclusions cannot be reached for such patients. It is possible that recognition and treatment would mitigate the negative consequences of disorders reported here. It is also possible that patients previously recognized and / or treated have lower levels of functioning and wellbeing than the patients in this study, these lower levels being partly responsible for recognition and / or treatment. A recent study [34] of patients beginning antidepressant treatment at a HMO offers some relevant data. A written communication in September 1996, from Gregory Simon, M.D., shows baseline scores for depressed patients on most SF-36 scales to be similar to those estimated by the model for patients with unrecognized and untreated depres-

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sion, although the scores on some scales for newly treated patients were lower than those predicted by the model. Thus, patients with unrecognized depression may have many areas of impaired functioning and well-being comparable to patients beginning treatment. Since a complete analysis of previously recognized and / or treated disorders has not been undertaken, full exploration of these possibilities must remain the subject of speculation and future study. The present study does, however, confirm and extend results of previous studies reporting high rates of mental disorders and associated disabilities in primary care patients [30], problems of under-recognition and under-treatment of mental problems [35], extent of disability and dysfunction [12,36], and overlap between anxiety disorders and major depression [37]. It clearly shows that patients with unrecognized and untreated anxiety disorders have broad and deep reductions in their level of functioning and well-being, which are comparable to those associated with many chronic medical conditions. Moreover, the unrecognized mental disorders are prevalent, occurring in more than 5% of eligible primary care patients initially screened in this study. It is possible that specific aids to assist primary care physicians in recognizing these patients might lead to increased treatment rates and improvement in patient functioning and well-being. This hypothesis is the subject of further research with this patient and physician population [38].

Acknowledgments The authors thank Ms. Lee Ann Prebil and Ms. Megeen Egan at Technology Assessment Group for their assistance with compiling information on national norms and preparing this manuscript for publication. We also appreciate the support of the Upjohn Company for funding the writing of this manuscript and the original research upon which it is based.

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