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JAIDS Journal of Acquired Immune Deficiency Syndromes:
Clinical Science

Validation of a Brief Screening Instrument for Substance Abuse and Mental Illness in HIV-Positive Patients

Pence, Brian Wells MPH*; Gaynes, Bradley N MD†; Whetten, Kathryn PhD§∥¶; Eron, Joseph J Jr MD‡; Ryder, Robert W MD*‡; Miller, William C MD, PhD*‡

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Author Information

From the Department of *Epidemiology, School of Public Health, and †Department of Psychiatry and ‡Division of Infectious Diseases, Department of Medicine, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC; Departments of §Public Policy and ∥Community and Family Medicine and ¶Health Inequalities Program, Duke University, Durham, NC.

Received for publication April 11, 2005; accepted July 1, 2005.

Supported in part by a 2003 developmental grant from the University of North Carolina at Chapel Hill Center for AIDS Research (CFAR), an NIH-funded program (P30 AI50410); funds from the US Department of Health and Human Services, Health Resources and Services Administration, HIV/AIDS Bureau, Office of Science and Epidemiology; funds from the US Department of Health and Human Services, Health Resources and Services Administration, Substance Abuse and Mental Health Service Administration, Center for Mental Health Services (Grant #93-230) and Center for Substance Abuse Treatment; and funds from the National Institutes of Health's (NIH) National Institute of Mental Health (NIMH), National Institute on Drug Abuse (NIDA), and National Institute on Alcohol Abuse and Alcoholism (NIAAA). The content of this publication does not necessarily reflect the views or policies of SAMHSA, HRSA, NIH or the US Department of Health and Human Services. Brian Wells Pence is a Howard Hughes Medical Institute Pre-doctoral Fellow. Dr. Gaynes was supported in part by an NIMH K23 Career Development Award (MH01951-03).

Reprints: Bradley N. Gaynes, Department of Psychiatry, CB# 7160, University of North Carolina, School of Medicine, Chapel Hill, NC 27599-7160 (e-mail:

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Background: Substance abuse (SA) and mental illness (MI) commonly co-occur with HIV infection in the United States and have important implications for clinical management of HIV/AIDS. Yet SA/MI often go untreated due in part to a lack of practical, validated screening tools.

Setting: HIV clinic in academic medical center.

Methods: The 16-item SA/MI Symptoms Screener (SAMISS) targets SA/MI in HIV-positive patients. Consecutive consenting HIV-positive patients completed the SAMISS and then a reference standard diagnostic tool, SCID, the Structured Clinical Interview for DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition).

Results: Twenty percent of participants (29/148) had an SA diagnosis and 41% (59/143) had an MI diagnosis in the past year on the SCID; 48% (68/143) had 1 or both. Thirty-seven percent (55/148) screened positive for SA and 69% (99/143) screened positive for MI on the SAMISS. The SAMISS had 86% (95% CI: 68%-96%) sensitivity and 75% (66%-82%) specificity for SA and 95% (86%-99%) sensitivity and 49% (38%-60%) specificity for MI. Patients with SA were likely to show up as false positives for MI and vice versa.

Conclusion: The SAMISS functioned well as a first-line screening tool for SA/MI in this HIV clinic population. It missed few cases and was easily incorporated into a busy clinical setting. Persons screening positive require a more rigorous confirmatory psychiatric evaluation.

Many people living with HIV/AIDS also suffer from substance abuse (SA) and mental illness (MI), with potential serious consequences for their quality of life and the clinical course of their HIV infection.1,2 The HIV Cost and Services Utilization Study (HCSUS), a survey of a nationally representative sample of HIV-positive patients receiving care in the United States, found that 48% reported significant symptoms of depression, dysthymia, generalized anxiety disorder, or panic disorder and 33% merited a diagnosis of 1 of those 4 disorders within the preceding year.1,3 Thirty-eight percent of respondents had used illicit drugs in the past year, 13% were classified as drug dependent, and 19% reported heavy alcohol use in the past 4 weeks. These rates significantly exceed estimates for the general US population.4,5 Comparably elevated current or recent rates of depression, other mood and anxiety disorders, and SA have been reported in numerous clinical6-10 and community-based11-19 HIV-positive populations, including in samples of women,8,20 homosexual men,11-13,17-19 US military personnel,7,16 injection drug users,9,10 and mixed populations.6,14,15

Identifying and treating SA/MI promptly in HIV clinical settings is clearly important. SA and MI, and particularly depression, are associated with worse adherence to antiretroviral medications, the current cornerstone of managing HIV infection.21-26 Much discussion has focused on the need to promote antiretroviral adherence in clinical settings because of the key role of adherence in preventing the development of drug-resistant virus and slowing the progression of HIV infection.26-34 In addition, evidence suggests that SA and MI may directly influence immune function and HIV disease progression independent of their effect on adherence.35-39 Finally, HIV-positive patients with SA/MI are more likely to engage in unsafe needle-sharing and sexual behaviors that put others at risk for HIV infection.40-44 Both SA and MI can be effectively addressed through well-tested psychotherapeutic and pharmacologic interventions.45-54 The appropriate treatment of depression, the most common MI, is associated with improved antiretroviral adherence.55

Several screening instruments have been used to identify SA/MI in HIV-positive and general clinical populations.1,8,9,12,13,56 We identified only 2 MI screening instruments and no SA instruments with published reports of validation studies in HIV-positive populations. A positive screen on any one of the depression, dysthymia, anxiety, and panic modules of the University of Michigan Composite International Diagnostic Interview-Short Form (UM-CIDI-SF) used by HCSUS had 80% sensitivity and 77% specificity compared with any diagnosis in the 4 categories.56 In an inner-city HIV clinic, a combination of the General Health Questionnaire and the Beck Depression Inventory identified cases of mood and anxiety disorders with 81% sensitivity and 61% specificity.9 The Center for Epidemiologic Studies-Depression scale, used in several large cohort studies of HIV-positive individuals,8,12,13 has 88% sensitivity and 73% specificity in the general population for identifying major depression but has not been validated in HIV-positive individuals.57,58 Limitations of these instruments for clinical practice include length (55 items for the mental health modules of the UM-CIDI-SF; 51 items for the General Health Questionnaire and the Beck Depression Inventory), a focus solely on depressive symptoms (Center for Epidemiologic Studies-Depression scale), and inclusion of symptoms that may signify HIV disease progression rather than MI (eg, fatigue, anorexia, weight loss, and poor concentration).

We conducted a validation study of the Substance Abuse and Mental Illness Symptoms Screener (SAMISS) in an HIV-positive patient population. The SAMISS is a 16-item screening instrument designed to identify SA/MI in HIV-positive patients.59,60

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Study Population

The study population comprised all new patients, or patients never previously screened with the SAMISS, seen at the infectious diseases clinic of the University of North Carolina at Chapel Hill Hospital (UNC-ID) between August 26, 2003, and June 23, 2004, who were HIV positive, at least 18 years old, English speaking, and mentally competent to provide informed consent as assessed by their UNC-ID medical provider.

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The SAMISS comprises 16 questions regarding drug and alcohol use and symptoms of MI (see Appendix).59,60 A panel of experts in psychiatric measurement and diagnosis developed the SAMISS in 1999 as a means of rapidly identifying patients with probable SA/MI in busy HIV clinical settings. The SAMISS was designed to address the need for a screening instrument that assesses both SA and MI, can be administered in ≤10 minutes, and avoids symptoms of HIV disease progression that could be mistaken for signs of MI.

The SAMISS SA module measures frequency and intensity of alcohol use with a 3-question subscale of the Alcohol Use Disorders Identification Test.61,62 Two questions assess abuse of prescription and nonprescription drugs in the past year. The SA module concludes with the Two-Item Conjoint Screener, 2 questions designed to assess dependence on or uncontrolled use of either alcohol or drugs in the past year.63

The SAMISS MI assessment module comprises 8 questions from the CIDI querying key symptoms of manic and depressive episodes, generalized anxiety disorder, panic disorder, post-traumatic stress disorder (PTSD), and adjustment disorder.64 An additional question inquires about use of antidepressant medication in the past year. The question on adjustment disorder references the preceding 3 months, whereas all others reference the past year.

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A tool called the SCID or Structured Clinical Interview for DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition) served as the reference standard to evaluate the performance of the SAMISS in this study. The SCID is a reliable, valid, and widely used interview tool, which may be administered by paraprofessionals, for establishing psychiatric diagnoses in a consistent manner for research purposes.65-67 The SCID has comparable test characteristics when administered in person or over the telephone.68-71

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Study Procedures

Clinic staff reviewed scheduled appointments each morning to identify eligible patients. Two licensed clinical social workers, 2 research assistants, and a co-author (B.W.P.) screened eligible patients with the SAMISS. All personnel were trained to administer the SAMISS in a consistent manner, reading questions as written and not probing for additional information until after completing the SAMISS. Once screened, eligible patients were invited to participate in the validation study. Some eligible patients were not screened or invited to participate because no study staff person was available at the time of their appointment. Interested patients gave informed consent. The Biomedical Institutional Review Board of the University of North Carolina at Chapel Hill approved this study.

A trained research interviewer blinded to the results of the SAMISS then administered the SCID to each participant. Patients completed the interview either in person or by telephone. Interviews occurred the same day as the SAMISS or as soon as possible thereafter (median: 6 days; range: 0-29; 127/148 SCIDs completed within 2 weeks). The interviewer assigned final diagnoses after the interview in consultation with a psychiatrist (B.N.G.). Diagnoses were assigned as being present or absent within the past year. Only diagnoses included in the substance use, mood, and anxiety sections of the SCID were considered, specifically abuse of or dependence on alcohol, sedatives, hypnotics, anxiolytics, stimulants, opioids, “crack”/cocaine, and hallucinogens; major depressive, dysthymic, bipolar I and II, adjustment, obsessive-compulsive, panic, and generalized anxiety disorders; PTSD; bereavement; mood disorder due to a general medical condition or substance abuse; agoraphobia without history of panic disorder; social and specific phobias; and mood, depressive, bipolar, and anxiety disorders not otherwise specified.

During the interview, participants also provided information on sociodemographic characteristics, whether they had been diagnosed with or treated for any of a list of chronic medical conditions in the past 3 years,72-74 and whether they had experienced each of a list of HIV-related symptoms in the past 6 months.1

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The definition of a positive screen for a probable substance use disorder consisted of any of the following: a total score of ≥5 on questions 1-3; a response of “Weekly” or “Daily or almost daily” to question 4 or 5; or any response other than “Never” to questions 6 or 7. The definition of a positive screen for a probable mood or anxiety disorder consisted of an affirmative response to any of questions 8-16 (see Appendix).59,60

Test characteristics (sensitivity, specificity, and positive and negative likelihood ratios [LR+, LR−])75 of the SAMISS SA module were calculated relative to any alcohol or substance use diagnosis on the SCID. Test characteristics of the MI module were calculated relative to any mood or anxiety disorder diagnosis on the SCID. Test characteristics of a positive screen on either module were compared with any SA/MI SCID diagnosis. All CIs were calculated with exact methods. Sensitivity and specificity were compared using Fisher exact test across strata of selected covariates deemed of interest a priori. Positive and negative predictive values (PPV, NPV) were calculated for this population and for a range of hypothetical prevalences of substance use and mood and anxiety disorders.

A cumulative score on the SAMISS MI module representing the number of endorsed symptoms (range: 0-9) was compared with the reference standard of any mood or anxiety disorder diagnosis on the SCID using a receiver operating characteristic curve.76

Methods described by Begg and Greenes77,78 and Rothman and Greenland79 were used in sensitivity analyses to assess the potential bias in estimated test characteristics introduced by refusal to participate and loss to follow-up and misclassification of mental health status by the SCID, respectively.

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Recruitment and Retention

A total of 185 patients consented to participate, representing 82% of all patients invited to participate and 65% of all eligible patients who kept appointments during the recruitment period. Although written records were not kept of reasons for nonparticipation, study staff report that the most common reasons were expressed lack of interest in the study or anticipated difficulty in scheduling the follow-up interview. Lack of available study personnel constituted the only reason eligible patients were not invited to participate.

SCIDs were successfully completed within 30 days with 148 of the 185 participants (80.0%). Twenty SCIDs (13.5%) were conducted in person and 128 (86.5%) by phone. Of the 37 participants who did not complete the SCID, 32 were not successfully recontacted within 30 days after enrollment and 5 refused to complete the SCID when recontacted, citing lack of either time or interest.

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Sample Characteristics

The 148 participants with complete follow-up were primarily 30-50 years old (range: 20-65 years) (Table 1). Approximately one-third of the participants were female. Approximately three-quarters were African American, with the remainder primarily white. Thirty-six percent were on public health insurance and 28% were uninsured. The distribution of age, race, sex, and health insurance status did not differ significantly between participants who completed the SCID and those lost to follow-up. Participants were similar to the clinic patient population in sex (P = 0.92) and insurance status (P = 0.66) but were younger on average (mean age 40.4 years vs. 42.5, P = 0.01) and more likely to be African American (72% vs. 59%, P < 0.01) (data not shown).

Table 1
Table 1
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SA/MI Prevalence

Of the 148 participants with complete follow-up, 29 (19.6%) received at least 1 diagnosis of a substance abuse or dependence disorder in the past year on the SCID (Table 2). All SA diagnoses were of either crack/cocaine (13.5%) or alcohol (10.9%) abuse or dependence, with 4.8% abusing or dependent on both substances.

Table 2
Table 2
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For 5 participants in the first weeks of data collection, incomplete information about dates of symptoms did not allow a determination of whether a mood or anxiety disorder diagnosis had been active within the past year. Of the 143 participants with completed SCIDs and complete date information, 59 (41.3%) received at least 1 diagnosis of a mood or anxiety disorder in the past year on the SCID, with the most common diagnoses being major depressive disorder (15.8%), depressive disorder not otherwise specified (9.5%), and PTSD (6.1%).

Half of participants had either an SA or a mood/anxiety disorder in the past year. Eighteen participants (12.6%) had both conditions. Most commonly, a mood disorder or PTSD co-occurred with alcohol or crack/cocaine abuse or dependence.

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SAMISS Test Characteristics

Of the 148 participants with complete follow-up, 55 (37.2%) screened positive on the SAMISS SA module (Table 1). The 37 participants who did not complete the SCID were no more likely to have screened positive for SA than participants who did complete the SCID (43.2%, P = 0.57, Fisher exact test).

Compared with the SCID, the SA module of the SAMISS had 86% sensitivity (95% CI: 68%-96%) and 75% specificity (66%-82%) (Table 3). The LR+ and LR− were 3.4 and 0.18, respectively. In this population, with a prevalence of substance use disorders of 20%, the PPV and NPV were 46% (32%-59%) and 96% (89%-99%), respectively (Fig. 1). The module was less specific for those with a mood or anxiety disorder than those without (61% vs. 83%, P = 0.05), and there was a nonsignificant trend toward lower sensitivity for women than for men (67% vs. 95%, P = 0.08) (Table 4).

Table 3
Table 3
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Table 4
Table 4
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Figure 1
Figure 1
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Of the 143 participants with completed SCIDs and complete date information, 99 (69.2%) screened positive on the SAMISS MI module (Table 1). The 42 participants who did not complete the SCID or with incomplete date information were no more likely to have screened positive for a mood or anxiety disorder than participants who did complete the SCID (69.1%, P = 1.00, Fisher exact test).

Compared with the SCID, the MI module of the SAMISS had 95% sensitivity (86%-99%) and 49% specificity (38%-60%) (Table 3). The LR+ and LR− were 1.9 and 0.10, respectively. In this population, with a prevalence of mood and anxiety disorders of 41%, the PPV and NPV were 57% (46%-67%) and 93% (81%-99%), respectively (Fig. 2). The sensitivity did not vary significantly by any measured characteristic of the study population (Table 4). The specificity decreased as the number of HIV-related symptoms increased (0%-24% of symptoms endorsed: specificity = 63%; 25%-49%: 41%; 50%-100%: 25%; P = 0.02). There was a nonsignificant trend toward lower specificity for those with a substance use disorder than those without (22% vs. 52%, P = 0.16).

Figure 2
Figure 2
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Seventy-six percent of participants with SCIDs and 81% of participants without SCIDs screened positive on 1 or both modules (P = 0.54, Fisher exact test) (Table 1). A positive screen on either module had 97% sensitivity (90%-100%) and 44% specificity (33%-56%) compared with any SA/MI SCID diagnosis, with LR+ and LR− of 1.7 and 0.067, respectively (Table 3). In this population, the PPV and NPV were 61% (51%-70%) and 94% (81%-99%), respectively.

Using a score of the number of symptoms endorsed in the MI module (range: 0-9), a higher specificity and lower sensitivity can be achieved by choosing a cutpoint >1 (Fig. 3). For example, a definition for a positive screen that requires endorsing at least 2 symptoms has 88% sensitivity (95% CI: 77%-95%) and 67% specificity (56%-77%).

Figure 3
Figure 3
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Sensitivity Analyses

The participants with complete follow-up represent only a subset of the targeted study population of consecutive eligible patients for 3 reasons: some eligible patients were never contacted by study personnel due to logistical constraints, some contacted patients declined to participate, and some participants did not complete the SCID after enrolling. Clinic logistical constraints should be uncorrelated with individual patients' SA/MI status and should not introduce selection bias. Both participation and study completion could plausibly be associated with SA/MI status. In fact, among participants, completion of the SCID was negatively and weakly correlated with reported SA but uncorrelated with symptoms of MI on the SAMISS (Table 1). Adjustment for the loss to follow-up of participants who did not complete the SCID leaves the estimates of sensitivity and specificity virtually unchanged for both modules of the SAMISS (Table 5). Furthermore, the estimates of sensitivity and specificity are relatively insensitive to a wide range of assumptions about the proportion of nonparticipants who would have screened positive.

Table 5
Table 5
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Misclassification of true mental health status by the SCID was unlikely to have introduced important bias (Table 5). Even substantially reduced sensitivity for patients screening negative on the SAMISS, as might occur if some patients underreported symptoms on both the SAMISS and SCID due to concerns about stigmatization or admission of illegal behaviors, would have only marginally affected results (last 2 rows of Table 5). Our results are most sensitive to the choice of SCID specificity: anything less than perfect specificity would suggest that this report has underestimated the true sensitivity of the SAMISS. In fact, our data were not consistent with a specificity of <96% for the SCID because of the very low prevalence of diagnoses in the SAMISS-negative group.

In analyses restricted to participants who completed the SCID within 2 weeks of being screened, no result changed significantly (all estimates of test characteristics changed by <2 percentage points). Test characteristics did not differ significantly according to whether the interview was conducted by phone or in person.

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The SAMISS is a brief screening instrument designed to identify SA/MI in HIV-positive patients. In this study, the SAMISS demonstrated high sensitivity and moderate specificity for both SA and MI. Due to its brevity, the SAMISS can be feasibly integrated into routine care in busy clinical settings. The instrument's high sensitivity makes it an effective universal, first-line screening instrument. Because of its moderate specificity, patients who screen positive will require a more rigorous psychiatric evaluation to confirm the presence of a diagnosis.

In clinical practice, the PPV and NPV of the SAMISS vary depending on the prevalence of SA and MI in the population being screened.80 Our patient population had a prevalence of substance use disorders (20%) and mood and anxiety disorders (41%) comparable to reports from HIV-positive patients nationally.1 In populations with comparable or lower prevalences, the SAMISS will have an NPV close to 100% but a PPV ≤50% for both SA and MI (Figs. 1 and 2), emphasizing the need for further evaluation for persons screening positive.

For the MI module, a lower sensitivity and higher specificity can be achieved by requiring the patient to endorse at least 2 symptoms to screen positive. A decision about the optimal test characteristics should be based on the relative costs of false-positive and false-negative results. In many clinical settings, a false-positive result will cost staff resources to conduct a more in-depth evaluation. A false-negative finding will cause a case of SA or MI not to be identified and treated, which may have mental and physical health consequences for the individual and long-term financial costs to the health care system. A formal cost-effectiveness analysis, although beyond the scope of this paper, could assist administrators and policy makers in balancing these competing considerations.

The sample in this study was recruited at the infectious diseases clinic of an academic medical center in the southeastern United States whose patient population is primarily poor, from minority racial/ethnic groups, and on public health insurance or uninsured. A substantial proportion is female, and heterosexual intercourse represents an important mode of transmission. Nationally, HIV and AIDS are increasingly becoming concentrated among women of reproductive age, racial and ethnic minorities, and the poor.81-83 Heterosexual contact now accounts for about one-third of new HIV/AIDS cases in the United States.82 These dynamics are particularly evident in the Southeast, which has some of the highest rates of HIV infection and HIV/AIDS prevalence in the country.82-84

The SAMISS may perform differently in other populations. Specifically, we found that the SAMISS MI module was less specific the more HIV-related symptoms the respondent endorsed, consistent with the reported performance of the UM-CIDI-SF in HIV-positive patients.56 This could reflect greater subthreshold psychologic distress associated with increasing physical HIV-related illness, or it could indicate that physical symptoms can masquerade as endorsement of psychologic distress even in an instrument that avoids symptoms specifically overlapping with HIV disease progression. We also found a nonsignificant trend for the SA module on the SAMISS to have lower sensitivity for women than for men. The explanation for this finding is unclear but may reflect more distrust on the part of female patients and less willingness to disclose stigmatizing behaviors during brief interactions with clinic personnel. Finally, patients with SA but no MI were likely to screen in as false positives on the MI module, and the reverse was also true for patients with MI but no SA, underscoring the overlap between common indicators of SA and MI. In particular, question 8 in the MI module queries symptoms of mania, which could also indicate substance withdrawal. The inclusion of this question in the definition of a positive SA screen improved the SA module's sensitivity to 93%, as the question detected 2 of 4 original false negatives, but caused the specificity to fall to 62% with the addition of 15 new false positives.

The SCID, used here as the reference standard, is an imperfect measure of psychiatric disease. However, the SCID has been widely used for the validation of numerous other psychiatric measurement scales, including the latest version of the CIDI,85 and for the assignment of psychiatric diagnoses in multiple populations with other coexisting serious medical illnesses.86,87 The test-retest reliability of the SCID for the most common substance use, mood, and anxiety diagnoses ranges from 0.60-0.80 (kappa statistic).67 The SCID may perform differently in disadvantaged populations such as HIV-positive patients than in the general population, but we could identify no published validity or reliability evaluations of the relevant SCID modules in such populations. In this study, all SCIDs were conducted by the same interviewer and all diagnoses were assigned in consultation with the same psychiatrist to ensure consistency in diagnoses. Our sensitivity analyses support the assertion that misclassification of mental health status by the SCID is unlikely to have introduced substantial bias into our results, whether or not it is correlated with misclassification by the SAMISS.

The elapsed time between the administration of the SAMISS and the SCID may have affected the comparability of the symptoms of mental illness and substance use assessed by the 2 measures. Both the SAMISS questions and the SCID diagnoses reference the year preceding the interview. Most SCIDs were completed within 2 weeks of the SAMISS but some took place up to a month after the SAMISS. The results of these analyses were substantively unchanged when the sample was restricted to the 127 participants (86% of the total) whose SCIDs were completed within 2 weeks after the SAMISS. Also, most SCIDs were conducted over the phone, but some were conducted in person. In our sample, no result differed significantly between interviews conducted in person and by phone.

We excluded a small number of patients from this study who were not mentally competent to provide informed consent as assessed by their medical provider. This group is likely to have been at higher risk for needing psychiatric management. Because exclusion was based on provider's judgment, the providers were likely already aware of the mental health needs of these patients. Although the screening instrument may have performed differently in this subgroup, the number of excluded patients was small relative to the size of the study, and in clinical practice a screening instrument would likely not be used with this group.

We chose to assess only mood, anxiety, and substance use disorders, excluding in particular psychotic and personality disorders. We selected the disorders on which we focused due to their high prevalence both in the general population4 and in HIV-positive patients3,6,9,17,88 and their established links to suboptimal medication adherence.21-26 The SAMISS is unlikely to be effective in identifying psychotic or personality disorders.

The UNC-ID provides an example of successful integration of routine SA/MI screening in HIV clinical practice. All patients routinely complete the SAMISS, which generally takes <10 minutes, at their initial or second visit and yearly thereafter. A social worker, research assistant, or other available staff person administers the SAMISS. The patient's provider reviews the responses. Patients who screen positive for SA or MI receive further consultation with their provider, evaluation by a social worker, and enrollment in a clinic-based SA treatment program or referral to other SA/MI services as appropriate.

Overall, the SAMISS demonstrated high sensitivity and moderate specificity as a screening tool for the identification of SA/MI in this HIV-positive patient population. The SAMISS missed few cases in a sample with prevalences of substance use and mood and anxiety disorders comparable to those reported for HIV-positive patients nationally. False-positive results were not uncommon, indicating that in clinical practice the SAMISS should be followed by a more rigorous psychiatric evaluation for patients who screen positive. The brevity of the SAMISS makes it practical for routine use in busy clinical settings.

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The authors gratefully acknowledge the contributions of E. Byrd Quinlivan, MD, Amy Heine, FNP, Sonia Napravnik, PhD, and the UNC-ID clinic staff to the completion of this research.

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1. Bing EG, Burnam MA, Longshore D, et al. Psychiatric disorders and drug use among human immunodeficiency virus-infected adults in the United States. Arch Gen Psychiatry. 2001;58:721-728.

2. Sherbourne CD, Hays RD, Fleishman JA, et al. Impact of psychiatric conditions on health-related quality of life in persons with HIV infection. Am J Psychiatry. 2000;157:248-254.

3. Orlando M, Burnam MA, Beckman R, et al. Re-estimating the prevalence of psychiatric disorders in a nationally representative sample of persons receiving care for HIV: results from the HIV Cost and Services Utilization Study. Int J Methods Psychiatr Res. 2002;11:75-82.

4. Kessler RC, McGonagle KA, Zhao S, et al. Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States: results from the National Comorbidity Survey. Arch Gen Psychiatry. 1994;51:8-19.

5. Regier DA, Boyd JH, Burke JD Jr, et al. One-month prevalence of mental disorders in the United States: based on five Epidemiologic Catchment Area sites. Arch Gen Psychiatry. 1988;45:977-986.

6. Chuang HT, Jason GW, Pajurkova EM, et al. Psychiatric morbidity in patients with HIV infection. Can J Psychiatry. 1992;37:109-115.

7. Kilbourne AM, Justice AC, Rabeneck L, et al. General medical and psychiatric comorbidity among HIV-infected veterans in the post-HAART era. J Clin Epidemiol. 2001;54(Suppl 1):S22-S28.

8. Ickovics JR, Hamburger ME, Vlahov D, et al. Mortality, CD4 cell count decline, and depressive symptoms among HIV-seropositive women: longitudinal analysis from the HIV Epidemiology Research Study. JAMA. 2001;285:1466-1474.

9. Lyketsos CG, Hanson A, Fishman M, et al. Screening for psychiatric morbidity in a medical outpatient clinic for HIV infection: the need for a psychiatric presence. Int J Psychiatry Med. 1994;24:103-113.

10. Lyketsos CG, Hutton H, Fishman M, et al. Psychiatric morbidity on entry to an HIV primary care clinic. AIDS. 1996;10:1033-1039.

11. Atkinson JH Jr, Grant I, Kennedy CJ, et al. Prevalence of psychiatric disorders among men infected with human immunodeficiency virus: a controlled study. Arch Gen Psychiatry. 1988;45:859-864.

12. Burack JH, Barrett DC, Stall RD, et al. Depressive symptoms and CD4 lymphocyte decline among HIV-infected men. JAMA. 1993;270:2568-2573.

13. Lyketsos CG, Hoover DR, Guccione M, et al. Depressive symptoms as predictors of medical outcomes in HIV infection. Multicenter AIDS Cohort Study. JAMA. 1993;270:2563-2567.

14. Gala C, Pergami A, Catalan J, et al. The psychosocial impact of HIV infection in gay men, drug users and heterosexuals: controlled investigation. Br J Psychiatry. 1993;163:651-659.

15. Maj M, Janssen R, Starace F, et al. WHO Neuropsychiatric AIDS study, cross-sectional phase I: study design and psychiatric findings. Arch Gen Psychiatry. 1994;51:39-49.

16. Brown GR, Rundell JR, McManis SE, et al. Prevalence of psychiatric disorders in early stages of HIV infection. Psychosom Med. 1992;54:588-601.

17. Perkins DO, Stern RA, Golden RN, et al. Mood disorders in HIV infection: prevalence and risk factors in a nonepicenter of the AIDS epidemic. Am J Psychiatry. 1994;151:233-236.

18. Rosenberger PH, Bornstein RA, Nasrallah HA, et al. Psychopathology in human immunodeficiency virus infection: lifetime and current assessment. Compr Psychiatry. 1993;34:150-158.

19. Williams JB, Rabkin JG, Remien RH, et al. Multidisciplinary baseline assessment of homosexual men with and without human immunodeficiency virus infection: II: standardized clinical assessment of current and lifetime psychopathology. Arch Gen Psychiatry. 1991;48:124-130.

20. Kaplan MS, Marks G, Mertens SB. Distress and coping among women with HIV infection: preliminary findings from a multiethnic sample. Am J Orthopsychiatry. 1997;67:80-91.

21. Ferrando SJ, Wall TL, Batki SL, et al. Psychiatric morbidity, illicit drug use and adherence to zidovudine (AZT) among injection drug users with HIV disease. Am J Drug Alcohol Abuse. 1996;22:475-487.

22. Gordillo V, del Amo J, Soriano V, et al. Sociodemographic and psychological variables influencing adherence to antiretroviral therapy. AIDS. 1999;13:1763-1769.

23. Paterson DL, Swindells S, Mohr J, et al. Adherence to protease inhibitor therapy and outcomes in patients with HIV infection. Ann Intern Med. 2000;133:21-30.

24. Singh N, Squier C, Sivek C, et al. Determinants of compliance with antiretroviral therapy in patients with human immunodeficiency virus: prospective assessment with implications for enhancing compliance. AIDS Care. 1996;8:261-269.

25. Sternhell PS, Corr MJ. Psychiatric morbidity and adherence to antiretroviral medication in patients with HIV/AIDS. Aust NZJ Psychiatry. 2002;36:528-533.

26. Laurence J, ed. Medication Adherence in HIV/AIDS. Larchmont, NY: Mary Ann Liebert; 2004.

27. Bangsberg DR, Hecht FM, Charlebois ED, et al. Adherence to protease inhibitors, HIV-1 viral load, and development of drug resistance in an indigent population. AIDS. 2000;14:357-366.

28. Harman JJ, Amico KR, Johnson BT. Standard of care: promoting antiretroviral adherence in clinical care. AIDS Care. 2005;17:237-251.

29. Bangsberg DR, Perry S, Charlebois ED, et al. Non-adherence to highly active antiretroviral therapy predicts progression to AIDS. AIDS. 2001;15:1181-1183.

30. Garcia de Olalla P, Knobel H, Carmona A, et al. Impact of adherence and highly active antiretroviral therapy on survival in HIV-infected patients. J Acquir Immune Defic Syndr. 2002;30:105-110.

31. Gifford AL, Bormann JE, Shively MJ, et al. Predictors of self-reported adherence and plasma HIV concentrations in patients on multidrug antiretroviral regimens. J Acquir Immune Defic Syndr. 2000;23:386-395.

32. Haubrich RH, Little SJ, Currier JS, et al. The value of patient-reported adherence to antiretroviral therapy in predicting virologic and immunologic response. California Collaborative Treatment Group. AIDS. 1999;13:1099-1107.

33. Hogg RS, Heath K, Bangsberg D, et al. Intermittent use of triple-combination therapy is predictive of mortality at baseline and after 1 year of follow-up. AIDS. 2002;16:1051-1058.

34. Wood E, Montaner JS, Chan K, et al. Socioeconomic status, access to triple therapy, and survival from HIV-disease since 1996. AIDS. 2002;16:2065-2072.

35. Bouhnik AD, Preau M, Vincent E, et al. Depression and clinical progression in HIV-infected drug users treated with highly active antiretroviral therapy. Antivir Ther. 2005;10:53-61.

36. Bagasra O, Pomerantz RJ. Human immunodeficiency virus type 1 replication in peripheral blood mononuclear cells in the presence of cocaine. J Infect Dis. 1993;168:1157-1164.

37. Leserman J. The effects of stressful life events, coping, and cortisol on HIV infection. CNS Spectr. 2003;8:25-30.

38. Peterson PK, Gekker G, Chao CC, et al. Cocaine potentiates HIV-1 replication in human peripheral blood mononuclear cell cocultures: involvement of transforming growth factor-beta. J Immunol. 1991;146:81-84.

39. Peterson PK, Sharp BM, Gekker G, et al. Morphine promotes the growth of HIV-1 in human peripheral blood mononuclear cell cocultures. AIDS. 1990;4:869-873.

40. Avants SK, Warburton LA, Hawkins KA, et al. Continuation of high-risk behavior by HIV-positive drug users: treatment implications. J Subst Abuse Treat. 2000;19:15-22.

41. Brook DW, Brook JS, Richter L, et al. Needle sharing: a longitudinal study of female injection drug users. Am J Drug Alcohol Abuse. 2000;26:263-281.

42. Kelly JA, Murphy DA, Bahr GR, et al. Factors associated with severity of depression and high-risk sexual behavior among persons diagnosed with human immunodeficiency virus (HIV) infection. Health Psychol. 1993;12:215-219.

43. Moore J, Schuman P, Schoenbaum E, et al. Severe adverse life events and depressive symptoms among women with, or at risk for, HIV infection in four cities in the United States of America. AIDS. 1999;13:2459-2468.

44. Stall RD, Paul JP, Barrett DC, et al. An outcome evaluation to measure changes in sexual risk-taking among gay men undergoing substance use disorder treatment. J Stud Alcohol. 1999;60:837-845.

45. Cruess DG, Evans DL, Repetto MJ, et al. Prevalence, diagnosis, and pharmacological treatment of mood disorders in HIV disease. Biol Psychiatry. 2003;54:307-316.

46. Fleming MF, Wilk A, Kruger J, et al. Hospital-based alcohol and drug specialty consultation service: does it work? South Med J. 1995;88:275-282.

47. Guydish J, Temoshok L, Dilley J, et al. Evaluation of a hospital based substance abuse intervention and referral service for HIV affected patients. Gen Hosp Psychiatry. 1990;12:1-7.

48. Hoffmann NG, Miller NS. Perspectives of effective treatment for alcohol and drug disorders. Psychiatr Clin North Am. 1993;16:127-140.

49. Lyketsos CG, Fishman M, Hutton H, et al. The effectiveness of psychiatric treatment for HIV-infected patients. Psychosomatics. 1997;38:423-432.

50. Markowitz JC, Kocsis JH, Fishman B, et al. Treatment of depressive symptoms in human immunodeficiency virus-positive patients. Arch Gen Psychiatry. 1998;55:452-457.

51. Markowitz JC, Rabkin JG, Perry SW. Treating depression in HIV-positive patients. AIDS. 1994;8:403-412.

52. Nagy PD, ed. Intensive Outpatient Treatment for Alcohol and Other Drug Use. Treatment Improvement Protocol (TIP) Series. Rockville, MD: US Department of Health and Human Services; 1994.

53. Saitz R. Clinical practice: unhealthy alcohol use. N Engl J Med. 2005;352:596-607.

54. Schulberg HC, Katon W, Simon GE, et al. Treating major depression in primary care practice: an update of the Agency for Health Care Policy and Research Practice Guidelines. Arch Gen Psychiatry. 1998;55:1121-1127.

55. Yun LW, Maravi M, Kobayashi JS, et al. Antidepressant treatment improves adherence to antiretroviral therapy among depressed HIV-infected patients. J Acquir Immune Defic Syndr. 2005;38:432-438.

56. Orlando M, Burnam MA, Sherbourne CD, et al. Brief screening of psychiatric disorders among a national sample of HIV-positive adults: concordance between the Composite International Diagnostic Interview (CIDI) and the CIDI Short Form (CIDI-SF). Int J Methods Psychiatr Res. 2001;10:97-107.

57. Breslau N. Depressive symptoms, major depression, and generalized anxiety: a comparison of self-reports on CES-D and results from diagnostic interviews. Psychiatry Res. 1985;15:219-229.

58. Klerman GL. Depressive disorders: further evidence for increased medical morbidity and impairment of social functioning. Arch Gen Psychiatry. 1989;46:856-858.

59. Whetten K, Reif SS, Napravnik S, et al. Substance abuse and symptoms of mental illness among HIV-positive persons in the Southeast. South Med J. 2005;98:9-14.

60. Whetten K, Reif S, Swartz M, et al. A brief mental health and substance abuse screener for persons with HIV. AIDS Patient Care STDS. 2005;19:89-99.

61. Bohn MJ, Babor TF, Kranzler HR. The Alcohol Use Disorders Identification Test (AUDIT): validation of a screening instrument for use in medical settings. J Stud Alcohol. 1995;56:423-432.

62. Saunders JB, Aasland OG, Babor TF, et al. Development of the Alcohol Use Disorders Identification Test (AUDIT): WHO Collaborative Project on Early Detection of Persons with Harmful Alcohol Consumption-II. Addiction. 1993;88:791-804.

63. Brown RL, Leonard T, Saunders LA, et al. A two-item screening test for alcohol and other drug problems. J Fam Pract. 1997;44:151-160.

64. Robins LN, Wing J, Wittchen HU, et al. The Composite International Diagnostic Interview: an epidemiologic instrument suitable for use in conjunction with different diagnostic systems and in different cultures. Arch Gen Psychiatry. 1988;45:1069-1077.

65. First MH, Spitzer RL, Gibbon M, et al. Structured Clinical Interview for DSM-IV Axis I Disorders-Research Version, Patient Edition (SCID-I/P). New York: Biometrics Research, New York State Psychiatric Institute; 1990.

66. Spitzer RL, Williams JB, Gibbon M, et al. The structured clinical interview for DSM-III-R (SCID): I: history, rationale, and description. Arch Gen Psychiatry. 1992;49:624-629.

67. Williams JB, Gibbon M, First MB, et al. The structured clinical interview for DSM-III-R (SCID): II: multisite test-retest reliability. Arch Gen Psychiatry. 1992;49:630-636.

68. Aneshensel CS, Frerichs RR, Clark VA, et al. Telephone versus in-person surveys of community health status. Am J Public Health. 1982;72:1017-1021.

69. Aneshensel CS, Frerichs RR, Clark VA, et al. Measuring depression in the community: a comparison of telephone and personal interviews. Public Opin Q. 1982;46:110-121.

70. Simon GE, Revicki D, VonKorff M. Telephone assessment of depression severity. J Psychiatr Res. 1993;27:247-252.

71. Wells KB, Burnam MA, Leake B, et al. Agreement between face-to-face and telephone-administered versions of the depression section of the NIMH Diagnostic Interview Schedule. J Psychiatr Res. 1988;22:207-220.

72. Linn BS, Linn MW, Gurel L. Cumulative illness rating scale. J Am Geriatr Soc. 1968;16:622-626.

73. Miller MD, Paradis CF, Houck PR, et al. Rating chronic medical illness burden in geropsychiatric practice and research: application of the Cumulative Illness Rating Scale. Psychiatry Res. 1992;41:237-248.

74. Rochon PA, Katz JN, Morrow LA, et al. Comorbid illness is associated with survival and length of hospital stay in patients with chronic disability: a prospective comparison of three comorbidity indices. Med Care. 1996;34:1093-1101.

75. Fletcher RH, Fletcher SW, Wagner EH. Clinical Epidemiology: The Essentials, 3rd ed. Baltimore: Williams & Wilkins; 1996.

76. DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988;44:837-845.

77. Begg CB, Greenes RA. Assessment of diagnostic tests when disease verification is subject to selection bias. Biometrics. 1983;39:207-215.

78. Greenes RA, Begg CB. Assessment of diagnostic technologies: methodology for unbiased estimation from samples of selectively verified patients. Invest Radiol. 1985;20:751-756.

79. Rothman KJ, Greenland S. Modern Epidemiology, 2nd ed. Philadelphia: Lippincott Williams & Wilkins; 1998.

80. Kraemer HC. Evaluating Medical Tests. Thousand Oaks, CA: Sage Publications; 1992.

81. Karon JM, Fleming PL, Steketee RW, et al. HIV in the United States at the turn of the century: an epidemic in transition. Am J Public Health. 2001;91:1060-1068.

82. Centers for Disease Control and Prevention (CDC). HIV/AIDS Surveillance Report, 2003, vol. 15. Atlanta: US Department of Health and Human Services, CDC; 2004.

83. Whetten-Goldstein K, Nguyen TQ.“You're the First One I've Told”: New Faces of HIV in the South. New Brunswick, NJ: Rutgers University Press; 2002.

84. Whetten-Goldstein K, Nguyen TQ, Heald AE. Characteristics of individuals infected with the human immunodeficiency virus and provider interaction in the predominantly rural Southeast. South Med J. 2001;94:212-222.

85. Kessler RC, Abelson J, Demler O, et al. Clinical calibration of DSM-IV diagnoses in the World Mental Health (WMH) version of the World Health Organization (WHO) Composite International Diagnostic Interview (WMHCIDI). Int J Methods Psychiatr Res. 2004;13:122-139.

86. Atesci FC, Baltalarli B, Oguzhanoglu NK, et al. Psychiatric morbidity among cancer patients and awareness of illness. Support Care Cancer. 2004;12:161-167.

87. Polliack ML, Barak Y, Achiron A. Late-onset multiple sclerosis. J Am Geriatr Soc. 2001;49:168-171.

88. McDaniel JS, Fowlie E, Summerville MB, et al. An assessment of rates of psychiatric morbidity and functioning in HIV disease. Gen Hosp Psychiatry. 1995;17:346-352.

Back to Top | Article Outline
The Substance Abuse and Mental Illness Symptoms Screener (SAMISS)

Substance Abuse:

Respondent screens positive if sum of responses to questions 1-3 is ≥5, response to question 4 or 5 is ≥3, or response to question 6 or 7 is ≥1.

1. How often do you have a drink containing alcohol?

(0) Never (1) Monthly or less (2) 2-4 times/mo (3) 2-3 times/wk (4) ≥4 times/wk

2. How many drinks do you have on a typical day when you are drinking?

(0) None (1) 1 or 2 (2) 3 or 4 (3) 5 or 6 (4) 7-9 (5) ≥10

3. How often do you have ≥4 drinks on 1 occasion?

(0) Never (1) Less than monthly (2) Monthly (3) Weekly (4) Daily or almost daily

4. In the past year, how often did you use nonprescription drugs to get high or to change the way you feel?

(0) Never (1) Less than monthly (2) Monthly (3) Weekly (4) Daily or almost daily

5. In the past year, how often did you use drugs prescribed to you or to someone else to get high or change the way you feel?

(0) Never (1) Less than monthly (2) Monthly (3) Weekly (4) Daily or almost daily

6. In the past year, how often did you drink or use drugs more than you meant to?

(0) Never (1) Less than monthly (2) Monthly (3) Weekly (4) Daily or almost daily

7. How often did you feel you wanted or needed to cut down on your drinking or drug use in the past year, and were not able to?

(0) Never (1) Less than monthly (2) Monthly (3) Weekly (4) Daily or almost daily

Mental Illness:

Respondent screens positive if response to any question is “Yes.”

8. In the past year, when not high or intoxicated, did you ever feel extremely energetic or irritable and more talkative than usual?

9. In the past year, were you ever on medication or antidepressants for depression or nerve problems?

10. In the past year, was there ever a time when you felt sad, blue, or depressed for ≥2 weeks in a row?

11. In the past year, was there ever a time lasting ≥2 weeks when you lost interest in most things like hobbies, work, or activities that usually give you pleasure?

12. In the past year, did you ever have a period lasting ≥1 month when most of the time you felt worried and anxious?

13. In the past year, did you have a spell or an attack when all of a sudden you felt frightened, anxious, or very uneasy when most people would not be afraid or anxious?

14. In the past year, did you ever have a spell or an attack when for no reason your heart suddenly started to race, you felt faint, or you couldn't catch your breath? (If respondent volunteers, “Only when having a heart attack or due to physical causes,” mark “No.”)

15. During your lifetime, as a child or adult, have you experienced or witnessed traumatic event(s) that involved harm to yourself or to others? (If yes: In the past year, have you been troubled by flashbacks, nightmares, or thoughts of the trauma?)

16. In the past 3 months, have you experienced any event(s) or received information that was so upsetting it affected how you cope with everyday life? Cited Here...

Cited By:

This article has been cited 2 time(s).

Current Opinion in Psychiatry
Responding to the threat of HIV among persons with mental illness and substance abuse
Parry, CD; Blank, MB; Pithey, AL
Current Opinion in Psychiatry, 20(3): 235-241.
PDF (120) | CrossRef
JAIDS Journal of Acquired Immune Deficiency Syndromes
Psychiatric Illness and Virologic Response in Patients Initiating Highly Active Antiretroviral Therapy
Pence, B; Miller, WC; Gaynes, BN; Eron, JJ
JAIDS Journal of Acquired Immune Deficiency Syndromes, 44(2): 159-166.
PDF (208) | CrossRef
Back to Top | Article Outline

HIV/AIDS; mental illness; depression; substance abuse; screening instruments

© 2005 Lippincott Williams & Wilkins, Inc.


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