Skip to main content

Abstract

Researchers continue to find racial-ethnic disparities in treatment receipt and outcomes. In this VA study of a collaborative program to treat depression in primary care, treatment responses of veterans from minority groups were markedly higher than those of white veterans.

Abstract

Objective:

The authors examined racial differences in response rates to an intervention involving collaborative care and usual care among 360 veterans treated for depression at Department of Veterans Affairs community-based primary care clinics.

Methods:

Individuals who screened positive for depression were assigned randomly to usual care (N=200) or to a collaborative care intervention (N=160) that provided phone contact when necessary with a registered nurse and clinical pharmacist to address issues related to compliance with medication and side effect management as well as supervision by a psychiatrist through video chats with the collaborative care team. Data about patients' characteristics, treatment history, and response to treatment were collected by telephone at baseline and after six months.

Results:

Seventy-five percent (N=272) of the veterans were Caucasian, and 25% (N=88) belonged to a minority group, including 18% (N=64) who were African American, 3% (N=11) who were Native American, and 3.6% (N=13) who were of other minority groups. There were no significant differences between response rates between the Caucasian and minority group to usual care (18% and 8%, respectively), but the minority group had a higher response rate (42%) than Caucasians (19%) to the intervention (χ2=8.2, df=1, p=.004). Regression analysis indicated that the interaction of minority group status by intervention significantly predicted response (odds ratio [OR]=6.2, 95% confidence interval [CI]=1.6–24.5, p=.009), even after adjustment for other factors associated with minority status (OR=6.0, 95% CI=1.5–24.3, p=.01).

Conclusions:

Racial disparities in depression care may be ameliorated through collaborative care programs. (Psychiatric Services 62:1282–1288, 2011)
There are long-standing disparities in treatment seeking for mental disorders among minority groups (111). Recent data suggest that the proportion of depressed adults who seek treatment is significantly lower among African Americans (53%) than among Caucasians (67%) (11). Likewise, in a study of individuals with depression, Alegráa and others (12) found that only 41% of African Americans and 36% of Hispanics sought treatment compared with 60% of Caucasians. Additionally, a majority of persons from minority groups who seek help for depression in the United States are seen in primary care settings (13,14), where their care is often inadequately managed (15,16).
Several barriers may contribute to existing disparities. Stigmatization continues to be one of the primary barriers facing minority populations who need depression care (1720). Other barriers include mistrust of health care providers (21), negative beliefs and attitudes about treatments, and spiritual beliefs, all of which may explain why individuals from minority groups tend to delay treatment (2226). In addition, many people who belong to minority groups have limited financial resources and poor access to affordable care (27). Travel barriers also represent substantial challenges to accessing depression care among individuals from minority groups (2830). African Americans who suffer from depression are also more likely to be underdiagnosed (31) and experience poorer physician-patient communication than Caucasians (14,3235).
In addition to having low rates of treatment seeking, African Americans are less likely than Caucasians to receive guideline-concordant depression care in primary care settings (14,3235). Both Chermack and others (35) and Tiwari and others (36) found that relative to Caucasian veterans, African-American veterans were less likely to receive guideline-concordant depression care at Department of Veterans Affairs (VA) primary care clinics, despite facing relatively few financial barriers. Furthermore, African Americans are less likely to receive or adhere to pharmacotherapy (37,38), perhaps because the acceptability of antidepressants is lower among individuals from racial minority groups (3941).
As a result, individuals from minority groups are also at risk for poorer clinical outcomes. The Sequenced Treatment Alternatives to Relieve Depression (STAR*D) clinical trial found that African Americans were twice as likely as Caucasians to experience worsening symptoms of depression during treatment with citalopram because of premature discontinuation of treatment, more taxing side effects, fewer clinic visits, and less acceptance of medications (42). Likewise, results from the Partners in Care study indicated that the proportion of individuals with probable depression after receiving usual-care treatment for depression for six months in a primary care setting was higher among African Americans (56%) and Hispanics (64%) than among Caucasians (41%) (43).
Efforts to improve the quality of depression care for minority populations have largely focused on collaborative care approaches. The Institute of Medicine's report on health disparities theorized that care management, by way of effective provider-patient communication and patient follow-up, should contribute to better health outcomes for minority groups (44). With respect to collaborative care for depression, promising results have been reported. Miranda and others (43) found that at the six-month follow-up, patients from minority groups in the Partners in Care study who received collaborative care had lower rates of probable depression compared with their counterparts who received usual care (24% and 56% for African-Americans and 47% and 64% for Hispanics, respectively). Miranda and others (42) also reported that patients from minority groups who received guideline-concordant, high-quality care demonstrated lower rates of probable depression at the six-month follow-up, compared with those who did not (21% and 71%, respectively).
Even with evidence that individuals from minority groups can make clinical gains when given high-quality depression care, few studies have examined potential factors contributing to these patients' improved responses to collaborative care interventions. This study evaluated racial-ethnic differences in clinical outcomes following a telemedicine-based collaborative care intervention among veterans from minority groups treated at VA community-based outpatient clinics in rural areas.
We tested several hypotheses. First, individuals from minority groups will have a worse treatment response to usual care than Caucasians. Second, individuals from minority groups will have a better treatment response to collaborative care than Caucasians. Third, minority group status will moderate the intervention's effect on treatment response, as will other characteristics of the veterans, such as having prior or current depression treatment, whether they perceived barriers to treatment, and attitudes toward antidepressant acceptability. Fourth, when the other characteristics are included as covariates, minority group status will no longer moderate the intervention effect. Our study extends the findings of Miranda and others (42,43) by evaluating a set of variable interaction terms to examine why members of racial-ethnic minority groups may respond at better rates than Caucasians to collaborative care to improve the quality of depression interventions.

Methods

Study setting and enrollment procedures

The Telemedicine Enhanced Antidepressant Management (TEAM) study was a randomized trial of telemedicine-based collaborative care tailored for small rural primary care practices, which demonstrated effectiveness (45,46). The study was conducted in seven community-based outpatient clinics that are satellite facilities of VA medical centers.
Administrative data were used to identify 24,882 patients due for annual depression screening, and 74% (N=18,306) were screened by phone by using the nine-item depression scale of the Patient Health Questionnaire (PHQ-9) (47). A total of 1,260 (7%) individuals screened positive for depression as defined by a PHQ-9 score ≥12. Exclusion criteria included having a diagnosis of schizophrenia; having current suicidal ideation; being recently bereaved; being pregnant; having a court-appointed guardian; having substance dependence, bipolar disorder, or cognitive impairment; or having a history of receiving or currently receiving specialty mental health treatment.
A total of 471 met the criteria and were eligible for baseline assessment, and 430 agreed to participate and were administered the baseline interview for baseline screening. Of the 430 patients who scheduled appointments, 395 (92%) attended the appointment and provided written consent. We enrolled 395 patients between April 2003 and September 2004. Patients were randomized to usual care (N=218) and to collaborative care (N=177). Data were collected via telephone interview. Follow-up telephone interviews were completed for 360 (91%) of the study participants at six months. The 35 patients who did not complete the six-month follow-up were not significantly different from those who completed the follow-up with respect to any baseline demographic or clinical characteristics.

TEAM intervention

Depression screening results were entered into the electronic health record for both intervention (N=177) and usual care (N=218) patients. Patients assigned randomly to the intervention received a stepped-care model of depression treatment for up to 12 months. Treatment intensity was increased for patients who did not to respond to lower levels of care by involving a greater number of intervention personnel with increasing mental health expertise.
The intervention involved on-site primary care providers located at the community-based outpatient clinics and an off-site depression care team, including nurses who managed the care of depressed patients (nurse care managers), clinical pharmacists, and psychiatrists, located at the parent VA medical center. The off-site intervention team focused on optimizing pharmacotherapy. A registered nurse serving as care manager used a scripted uniform protocol during telephone calls to patients to address specific treatment barriers, reasons for adherence problems (such as concern about addiction), and strategies for managing side effects. A pharmacist called patients who had not responded to treatment to discuss the patient's medication history and provide management of side effects. Psychiatrists supervised the off-site team and provided consultations via interactive video (for example, Skype).

Data collection

At baseline, information about demographic characteristics (age, sex, race, income, education, and employment) was collected, and depression history (such as family history of depression, age of depression onset, and past and current depression treatment) were measured with the Depression Outcomes Module (48,49). Psychiatric comorbidity was measured with the Mini-International Neuropsychiatric Interview (MINI) (50,51). Social support was measured by using the Duke Social Support and Stress Scale (52,53). Acceptability of antidepressant treatment was measured by using an item developed for the Partners in Care study (54). The Depression Health Beliefs Inventory was used to measure perceptions about depression treatment, including barriers to, perceived need for, and effectiveness of treatment (55).
Health status was measured by using the physical health component score (PCS) and mental health component score (MCS) of the 12-Item Short Form Health Survey (SF-12v2) (56). Depression severity was measured at baseline and six months with the Hopkins Symptom Checklist (SCL-20) (57,58). Treatment response was measured dichotomously as a 50% improvement in depression severity between baseline and six-month follow-up.

Statistical analyses

Explanatory variables with missing values were imputed using the MI and MIANALYZE procedures in SAS, 9.2, which uses multiple imputation methods. Sampling and attrition weights were calculated from administrative and baseline data, respectively, to adjust for the potential bias associated with nonparticipation, loss to follow-up, or both.
To test the hypotheses that individuals in the racial minority group, relative to Caucasians, would have a poorer response to usual care and a better response to collaborative care, we conducted bivariate analysis after stratifying the sample according to intervention group and to determine differences in baseline sample characteristics between racial groups.
If both hypotheses were supported, it would suggest that the intervention was more effective for the racial minority group than for Caucasians. Accordingly, we hypothesized that minority group status would moderate the intervention's effect on response. We further hypothesized that prior depression treatment, current depression treatment, a perception of barriers to treatment (“perceived barriers”), and a belief that antidepressants are acceptable would moderate the effect of the intervention on treatment response and that minority group status would no longer be a significant predictor of treatment response after controlling for these variables. Because prior depression treatment (59), current depression treatment (60), perceived barriers (61,62), and a belief that antidepressants are acceptable (63) have been empirically associated with positive treatment response and were all correlated with minority group status at baseline, we considered them as potential moderators.
We tested a two-stage logistic regression model evaluating the possible moderation of minority group status and other potential moderators on treatment response. The moderation hypotheses were tested by using the analyses methods specified by Kraemer and colleagues (64), in which a moderator is defined as a baseline or prerandomization characteristic that can be shown to have an interactive effect with treatment on the outcome. Kraemer and Blasey (65) also suggested that all measured variables be centered. However, for this study, we chose not to center minority group status and intervention status because we did not want to estimate the overall effect of the interaction across both the minority and the Caucasian groups. Rather, we wanted to estimate the specific treatment effects separately for the minority group and Caucasians.
The first stage of the model included intervention status and minority group status as predictors of treatment response as main effects. An intervention by minority group status interaction term was also included in the model to evaluate whether minority group status was a significant moderator of the intervention effect on response. We controlled for case mix variables that were found to be significant at the p≤.2 level in bivariate analyses. They included age, male gender, married status, income <$20,000, prior or current depression treatment, perceived barriers, and attitudes about whether antidepressants are acceptable forms of treatment.
The second stage of the model included analysis of the interactions of prior depression treatment, current depression treatment, perceived barriers, and views about acceptability of antidepressants and intervention group in the regression model predicting response. We expected that if these variables were significant moderators of the intervention effect on treatment response, minority group status would no longer be considered a significant moderator.
The study was approved by the Research and Development Committees of the Central Arkansas Veterans Healthcare System in Little Rock, the Overton Brooks VA Medical Center in Shreveport, Louisiana, and the G. V. (Sonny) Montgomery VA Medical Center in Jackson, Mississippi, and their affiliated institutional review boards at the University of Arkansas Medical Sciences and the University of Louisiana Health Sciences Center at Shreveport.

Results

Of the 360 patients, 272 (75%) were Caucasian and 88 (25%) were from a minority group, including 64 (18%) African Americans, 11 (3%) Native Americans, and 13 (3.6%) individuals from other groups. As shown in Table 1, those in the Caucasian group were more likely than those in the minority group to be male (94% and 87%, respectively; χ2=4.9, df=1, p=.03) and to be married (66% and 49%, respectively; χ2=8.1, df=1, p=.01). They were also more likely to report that antidepressants are an acceptable treatment (mean±SD ratings of 1.8±.8 and 2.2±.9, respectively; p=.001) and more likely to have had prior depression treatment (70% and 57%, respectively; χ2=4.9, df=1, p=.03) or current depression treatment (45% and 30%, respectively; χ2=6.3, df=1, p=.01). No other variables were found to be statistically different across the two groups.
Figure 1 shows response rates among minority and Caucasian patients to usual care and the intervention. Chi square analyses revealed no significant differences in the response rates among individuals of the minority racial group (8%) and among Caucasians (18%) in the usual care group, a finding that did not support our hypothesis that individuals of minority race would have worse outcomes associated with usual care. However, individuals in the minority group had a significantly higher rate of response than Caucasians to the intervention (42% and 19%, respectively; χ2=8.2, df=1, p=.004), a finding that supported our second hypothesis.
The first stage of the regression analysis is reported in Table 2. Model 1 revealed that neither the intervention nor minority group status predicted treatment response as main effects, an indication that the intervention was not effective for Caucasians. However, the interaction of minority group status and intervention significantly predicted treatment response (odds ratio [OR]=6.18, p=.009), an indication that the intervention was effective for the minority group. Therefore, we found support for our hypothesis that minority group status would moderate the intervention's effect on treatment response.
The second stage of the regression analysis, as shown in Table 2, model 2, revealed no correlation between response to the intervention and any of the other potential moderators, including prior depression treatment, current depression treatment, perceived barriers, and a belief in the acceptability of antidepressants as treatment. Therefore, we did not find support for the hypothesis that factors correlated with minority group status would also moderate the intervention effect and that minority group status would no longer moderate the intervention effect when those factors were included as covariates. Instead, we found that minority group status remained a significant moderator of the intervention's effect on treatment response (OR=6.02, p≤.01).

Discussion

Although our findings are preliminary, the data supported our hypothesis that the minority group would respond better than Caucasians to the collaborative care intervention, as was demonstrated by Miranda and others (42) in the Partners in Care study. Our findings and the earlier study found that minority group status moderated the treatment effect of collaborative care, such that individuals in the minority group were significantly more likely than Caucasians to respond to the intervention. However, it is important to note that most of the gains made by minority groups in the Partners in Care intervention were largely attributed to the component related to quality improvement in psychotherapy, not medication (66). Collectively, these findings suggest that individuals from racial minority groups can make remarkable clinical gains in primary care settings offering collaborative care.
Contrary to our hypothesis, there was no significant difference between the groups in response to usual care, even though small differences in the groups' response rates consistent with those reported in the literature were found (42,66). Because of the relatively small number of minority participants in the usual care group and the low response rates for both groups, there was insufficient statistical power to detect small between-group differences.
We also evaluated other potential treatment moderators that correlated with or otherwise related to minority group status, including prior depression treatment, current depression treatment, perceived barriers, and a belief in antidepressants' acceptability. Contrary to our hypothesis, none of these factors significantly moderated the effectiveness of the intervention, and minority group status remained a significant moderator of the intervention's effect on response. We were surprised to find that none of these other moderators were significant, even though three of them—all but perceived barriers—were significantly correlated with minority group status. Failure to detect significant findings may be due to the fact that the measures we used to assess these constructs were imprecise. For example, our assessment of antidepressant acceptability included one question about treatment preferences, and we did not evaluate other factors that have been found to contribute to an unaccepting attitude toward medication among minority groups, such as tolerance of side effects (39,40,42).
Further, our measures of prior and current treatment were dichotomous and may not have captured the extent to which patients of minority race or ethnic group were engaged in or were adherent to treatment in the past. Last, it is possible that unmeasured constructs associated with race and ethnicity may also explain why minority group status was a significant treatment moderator.
Our main finding that the collaborative care intervention had a greater effect among the minority group than among Caucasians may be explained by prior experiences with antidepressant treatment. A majority of patients in our sample had received prior depression treatment or were receiving depression treatment at baseline. Yet they remained symptomatic enough to meet study eligibility criteria (PHQ-9≥12). Receipt of prior or current depression treatment varied significantly by racial group, but neither prior nor current depression treatment moderated the intervention effect. Therefore, racial differences in the receipt of any prior depression treatment alone cannot explain our findings.
However, we suggest that racial difference in the quality of prior depression treatment may explain our findings. Previous research clearly indicates that veterans in minority groups are less likely to receive adequate depression care (35,36). We speculate that the prior care afforded patients in minority groups in our study may also have been inadequate; once they were enrolled in an intervention that provided high-quality depression care, they responded. On the other hand, the response rates among Caucasian patients to usual care may have reflected true treatment resistance, given that they were nearly identical to the group's response rate to the intervention.
If true, the improvement in quality of pharmacotherapy treatment resulting from the collaborative care intervention would be expected to improve outcomes for minority groups but not for Caucasians. Patients with treatment-resistant depression will likely need supplemental specialty treatments, such as evidence-based psychotherapies, to achieve remission of symptoms. We must also note that many of the 475 patients who were excluded at stage 1 were already in treatment and disproportionately included Caucasians, which might have affected the differential positive outcome for minority patients.
We also speculate that specific aspects of the intervention may have contributed to the success of the intervention in the minority group. As shown in the STAR*D studies, proper prescribing addresses only some of the barriers to receiving adequate care, whereas collaborative care models may address more multifaceted barriers faced by minority groups and lead to a reduction of depression symptoms. More study should be given to specific elements of collaborative care, such as education, activation, and side-effect monitoring, that may improve depression outcomes for minority groups.
Limitations of our study include the possibility that our results cannot be generalized to other populations, such as nonveterans or female veterans. However, in contrast to other depression studies, which include mostly women (14,3235), our study of mostly men confirms that interventions to improve quality of depression treatment may be as effective in closing racial gaps among men as they are among women.
Also, combining African Americans and members of other minorities into one group because of inadequate sample sizes may have oversimplified our findings.

Conclusions

Overall, our findings indicate that racial-ethnic disparities in depression care may be addressed successfully by implementing collaborative care programs in primary care settings and lend support for the use of these programs in an array of populations and health care systems. Most notably, we replicated findings of Partners in Care with a different population and in a different setting. We hope that our findings will promote research into other potential factors that may explain the enhanced treatment responses we found among veterans from minority populations.

Acknowledgments and disclosures

This research was supported by grant VA IIR 00-078-3 to Dr. Fortney and grant VA NPI-01-006-1 to Jeffrey Pyne, M.D., of the VA Health Services Research and Development Center for Mental Health and Outcomes Research and the VA South Central Mental Illness Research Education and Clinical Center.
The authors report no competing interests

References

1.
Mental Health: Culture, Race, and Ethnicity: A Supplement to “Mental Health: A Report of the Surgeon General.” Rockville, Md, US Department of Health and Human Services, National Institute of Mental Health, 2001
2.
Neighbors HW: The help-seeking behavior of black Americans: a summary of findings from the National Survey of Black Americans. Journal of the National Medical Association 80:1009–1012, 1988
3.
Wang PS, Lane M, Olfson M, et al.: Twelve-month use of mental health services in the United States: results from the National Comorbidity Survey Replication. Archives of General Psychiatry 62:629–640, 2005
4.
Breslau J, Aguilar-Gaxiola S, Kendler KS, et al.: Specifying race-ethnic differences in risk for psychiatric disorder in a USA national sample. Psychological Medicine 36:57–68, 2006
5.
Wells KB, Klap R, Koike A, et al.: Ethnic disparities in unmet need for alcoholism, drug abuse, and mental health care. American Journal of Psychiatry 158:2027–2032, 2001
6.
Neighbors HW, Caldwell C, Williams DR, et al.: Race, ethnicity, and the use of services for mental disorders: results from the national survey of American life. Archives of General Psychiatry 64:485–494, 2007
7.
Williams DR, Gonzalez HM, Neighbors HW, et al.: Prevalence and distribution of major depressive disorder in African Americans, Caribbean blacks, and non-Hispanic whites: results from the National Survey of American Life. Archives of General Psychiatry 64:305–315, 2007
8.
Kessler RC, Berglund P, Demler O, et al.: The epidemiology of major depressive disorder: results from the National Comorbidity Survey Replication (NCS-R). JAMA 289:3095–3105, 2003
9.
Kessler RC, McGonagle KA, Zhao S, et al.: Lifetime and 12-month prevalence of DSM-III-R disorders in the United States. Archives of General Psychiatry 51:8–19, 1994
10.
Ojeda VD, McGuire TG: Gender and racial/ethnic differences in use of outpatient mental health and substance use services by depressed adults. Psychiatric Quarterly 77:211–222, 2006
11.
National Healthcare Disparities Report. Rockville, Md, US Department of Health and Human Services, Agency for Healthcare Research and Quality, 2009
12.
Alegría M, Chatterji P, Wells K, et al.: Disparity in depression treatment among racial and ethnic minority populations in the United States. Psychiatric Services 59:1264–1272, 2008
13.
Cooper LA, Gonzales JJ, Gallo JJ, et al.: The acceptability of treatment for depression among African-American, Hispanic, and white primary care patients. Medical Care 41:479–489, 2003
14.
Miranda J, Cooper LA: Disparities in care for depression among primary care patients. Journal of General Internal Medicine 19:120–126, 2004
15.
Das AK, Olfson M, McCurtis HL, et al.: Depression in African Americans: breaking barriers to detection and treatment. Journal of Family Practice 55:30–39, 2006
16.
Gallo JJ, Bogner HR, Morales KH, et al.: Patient ethnicity and the identification and active management of depression in late life. Archives of Internal Medicine 165:1962–1968, 2005
17.
Cruz M, Pincus HA, Harman JS, et al.: Barriers to care-seeking for depressed African Americans. International Journal of Psychiatry in Medicine 38:71–80, 2008
18.
Rusch LC, Kanter JW, Manos RC, et al.: Depression stigma in a predominantly low income African American sample with elevated depressive symptoms. Journal of Nervous and Mental Disease 196:919–922, 2008
19.
Corrigan P: On Stigma of Mental Illness: Practical Strategies for Research and Social Change. Washington, DC, American Psychological Association, 2005
20.
Anglin DM, Link BG, Phelan JC: Racial differences in stigmatizing attitudes toward people with mental illness. Psychiatric Services 57:857–862, 2001
21.
Whaley A: Cultural mistrust and mental health services for African Americans: a review and meta-analysis. Counseling Psychologist 29:513–531, 2001
22.
Cooper-Patrick L, Powe NR, Jenckes MW, et al.: Identification of patient attitudes and preferences regarding treatment of depression. Journal of General Internal Medicine 12:431–438, 1997
23.
Snowden LR: African American service use for mental health problems. Journal of Community Psychology 27:303–313, 1999
24.
Diala CC, Muntaner C, Walrath C, et al.: Racial/ethnic differences in attitudes toward seeking professional mental health services. American Journal of Public Health 91:805–807, 2001
25.
Cooper LA, Brown C, Vu HT, et al.: How important is intrinsic spirituality in depression care? A comparison of white and African-American primary care patients. Journal of General Internal Medicine 16:634–638, 2001
26.
Wells KB, Miranda J, Bauer MS, et al.: Overcoming barriers to reducing the burden of affective disorders. Biological Psychiatry 52:655–675, 2002
27.
Kemppainen JK, Taylor J, Jackson LA, et al.: Incidence, sources, and self-management of depression in persons attending a rural health clinic in southeastern North Carolina. Journal of Community Health Nursing 26:1–13, 2009
28.
Rost K, Fortney J, Fischer E, et al.: Use, quality, and outcomes of care for mental health: the rural perspective. Medical Care Research and Review 59:231–265, 2002; discussion, 59: 266–271, 2002
29.
Fortney J, Rost K, Zhang M, et al.: The impact of geographic accessibility on the intensity and quality of depression treatment. Medical Care 37:884–893, 1999
30.
Coyne JC, Marcus SC: Health disparities in care for depression possibly obscured by the clinical significance criterion. American Journal of Psychiatry 163:1577–1579, 2006
31.
Kristofco RE, Stewart AJ, Vega W: Perspectives on disparities in depression care. Journal of Continuing Education in the Health Professions 27:S18–S25, 2007
32.
Young AS, Klap R, Sherbourne CD, et al.: The quality of care for depressive and anxiety disorders in the United States. Archives of General Psychiatry 58:55–61, 2001
33.
Blazer DG, Hybels CF, Simonsick EM, et al.: Marked differences in antidepressant use by race in an elderly community sample: 1986–1996. American Journal of Psychiatry 157:1089–1094, 2000
34.
Thompson C, Kinmonth AL, Stevens L, et al.: Effects of a clinical-practice guideline and practice-based education on detection and outcome of depression in primary care: Hampshire Depression Project randomised controlled trial. Lancet 355:185–191, 2000
35.
Chermack ST, Zivin K, Valenstein M, et al.: The prevalence and predictors of mental health treatment services in a national sample of depressed veterans. Medical Care 46:813–820, 2008
36.
Tiwari A, Rajan M, Miller D, et al.: Guideline-consistent antidepressant treatment patterns among veterans with diabetes and major depressive disorder. Psychiatric Services 59:1139–1147, 2008
37.
Strothers HS, Rust G, Minor P, et al.: Disparities in antidepressant treatment in Medicaid elderly diagnosed with depression. Journal of the American Geriatrics Society 53:456–461, 2005
38.
Givens JL, Katz IR, Bellamy S, et al.: Stigma and the acceptability of depression treatments among African Americans and whites. Journal of General Internal Medicine 22:1292–1297, 2007
39.
Cooper LA, Gonzales JJ, Gallo JJ, et al.: The acceptability of treatment for depression among African-American, Hispanic, and white primary care patients. Medical Care 41:479–489, 2003
40.
Dwight-Johnson M, Sherbourne CD, Liao D, et al.: Treatment preferences among depressed primary care patients. Journal of General Internal Medicine 15:527–534, 2000
41.
Friedman ES, Wisniewski SR, Gilmer W, et al.: Sociodemographic, clinical, and treatment characteristics associated with worsened depression during treatment with citalopram: results of the NIMH STAR*D trial. Depression and Anxiety 26:612–621, 2009
42.
Miranda J, Duan N, Sherbourne C, et al.: Improving care for minorities: can quality improvement interventions improve care and outcomes for depressed minorities? Results of a randomized, controlled trial. Health Services Research 38:613–630, 2003
43.
Miranda J, Schoenbaum M, Sherbourne C, et al.: Effects of primary care depression treatment on minority patients' clinical status and employment. Archives of General Psychiatry 61:827–834, 2004
44.
Smedley BP, Stith AY, Nelson AR: Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care. Washington, DC, National Academies Press, 2003
45.
Fortney JC, Pyne JM, Edlund MJ, et al.: Design and implementation of the telemedicine-enhanced antidepressant management study. General Hospital Psychiatry 28:18–26, 2006
46.
Kroenke K, Spitzer R: A new depression diagnostic and severity measure. Psychiatric Annals 32:509–515, 2002
47.
Smith G, Burnam A, Burns B, et al.: Depression outcomes module (DOM); in Handbook of Psychiatric Measures. Edited by, Rush AJ. Arlington, Va, American Psychiatric Association, 2002
48.
Rost K, Williams C, Wherry J, et al.: The process and outcomes of care for major depression in rural family practice settings. Journal of Rural Health 11:114–121, 1995
49.
Lecrubier Y, Sheehan D, Weiller E, et al.: The Mini-International Neuropsychiatric Interview (MINI). A short diagnostic structured interview: reliability and validity according to the CIDI. European Psychiatry 12:224–231, 2007
50.
Sheehan D, Lecrubier Y, Sheehan KH, et al.: The validity of the Mini-International Neuropsychiatric Interview (MINI) according to the SCID-P and its reliability. European Psychiatry 12:232–241, 1997
51.
Parkerson GR, Michener JL, Wu LR, et al.: Associations among family support, family stress, and personal functional health status. Journal of Clinical Epidemiology 42:217–229, 1989
52.
Parkerson GR, Broadhead WE, Tse CK: Quality of life and functional health of primary care patients. Journal of Clinical Epidemiology 45:1303–1313, 1992
53.
Wells KB, Sherbourne C, Schoenbaum M, et al.: Impact of disseminating quality improvement programs for depression in managed primary care: a randomized controlled trial. JAMA 283:212–220, 2000
54.
Edlund M, Fortney JC, Reaves CM, et al.: Beliefs about depression and depression treatment among depressed veterans. Medical Care 46:581–589, 2008
55.
Jones D, Kazis L, Lee A, et al.: Health status assessments using the veterans SF-12 and SF-36: methods for evaluating outcomes in the Veterans Health Administration. Journal of Ambulatory Care Management 24:68–86, 1997
56.
Kazis L, Skinner K, Rogers W, et al.: Health Status of Veterans: Physical and Mental Component Summary Scores (SF-12V): 1997 National Survey of Ambulatory Care Patients. Washington, DC, United States Department of Veterans Affairs, Office of Performance and Quality, 1997
57.
Derogatis LR, Lipman RS, Rickels K, et al.: The Hopkins Symptom Checklist (HSCL): a measure of primary symptom dimensions. Modern Problems of Pharmacopsychiatry 7:79–110, 1974
58.
Rubenstein LV, Rayburn NR, Keeler EB, et al.: Predicting outcomes of primary care patients with major depression: development of a depression prognosis index. Psychiatric Services 58:1049–1056, 2007
59.
Simon GE, Von Korff M, Ludman EJ, et al.: Cost-effectiveness of a program to prevent depression relapse in primary care. Medical Care 40:941–950, 2002
60.
Meredith LS, Stein BD, Paddock SM, et al.: Perceived barriers to treatment for adolescent depression. Medical Care 47:677–685, 2009
61.
Wells KB, Tang L, Miranda J, et al.: The effects of quality improvement for depression in primary care at nine years: results from a randomized, controlled group-level trial. Health Services Research 43:1952–1974, 2008
62.
Unutzer J, Katon W, Williams JW, et al.: Improving primary care for depression in late life: the design of a multicenter randomized trial. Medical Care 39:785–799, 2001
63.
Pyne JM, Rost KM, Farahati F, et al.: One size fits some: the impact of patient treatment attitudes on the cost-effectiveness of a depression primary-care intervention. Psychological Medicine 35:839–854, 2005
64.
Kraemer HC, Stice E, Kazdin A, et al.: How do risk factors work together? Mediators, moderators, and independent, overlapping, and proxy risk factors. American Journal of Psychiatry 158:848–856, 2001
65.
Kraemer HC, Blasey CM: Centering in regression analyses: a strategy to prevent errors in statistical inference. International Journal of Methods in Psychiatric Research 13:141–151, 2004
66.
Wells K, Sherbourne C, Schoenbaum M, et al.: Five-year impact of quality improvement for depression: results of a group-level randomized controlled trial. Archives of General Psychiatry 61:378–386, 2004

Figures and Tables

Figure 1 Response rates among veterans enrolled in usual care or a collaborative care intervention for depression, by minority status
Table 1 Characteristics of Caucasian veterans and veterans from minority racial-ethnic groups receiving care for depression
Table 2 Regression analysis of variables predicting response to treatment among veterans (N=360) enrolled in a collaborative care program for depression

Information & Authors

Information

Published In

Go to Psychiatric Services
Go to Psychiatric Services
Psychiatric Services
Pages: 1282 - 1288
PubMed: 22211206

History

Published in print: November 2011
Published online: 13 January 2015

Authors

Details

Teri D. Davis, Ph.D. [email protected]
Dr. Davis is affiliated with the South Central Mental Illness Research, Education, and Clinical Center, and Dr. Deen and Dr. Fortney are with Health Services Research and Development, Central Arkansas Veterans Healthcare System, 2200 Fort Roots Dr., North Little Rock, AR 72204 (e-mail: [email protected]).
Dr. Davis, Dr. Deen, and Dr. Fortney are also with the Department of Health Services Research, University of Arkansas for Medical Sciences (UAMS), Little Rock.
Tisha Deen, Ph.D. [email protected]
Dr. Davis is affiliated with the South Central Mental Illness Research, Education, and Clinical Center, and Dr. Deen and Dr. Fortney are with Health Services Research and Development, Central Arkansas Veterans Healthcare System, 2200 Fort Roots Dr., North Little Rock, AR 72204 (e-mail: [email protected]).
Dr. Davis, Dr. Deen, and Dr. Fortney are also with the Department of Health Services Research, University of Arkansas for Medical Sciences (UAMS), Little Rock.
Keneshia Bryant-Bedell, Ph.D.
Dr. Bryant-Bedell is with the College of Nursing, and Ms. Tate is with the College of Medicine, UAMS.
Vera Tate, B.A.
Dr. Bryant-Bedell is with the College of Nursing, and Ms. Tate is with the College of Medicine, UAMS.
John Fortney, Ph.D. [email protected]
Dr. Davis is affiliated with the South Central Mental Illness Research, Education, and Clinical Center, and Dr. Deen and Dr. Fortney are with Health Services Research and Development, Central Arkansas Veterans Healthcare System, 2200 Fort Roots Dr., North Little Rock, AR 72204 (e-mail: [email protected]).
Dr. Davis, Dr. Deen, and Dr. Fortney are also with the Department of Health Services Research, University of Arkansas for Medical Sciences (UAMS), Little Rock.

Metrics & Citations

Metrics

Citations

Export Citations

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

For more information or tips please see 'Downloading to a citation manager' in the Help menu.

Format
Citation style
Style
Copy to clipboard

View Options

View options

PDF/EPUB

View PDF/EPUB

Login options

Already a subscriber? Access your subscription through your login credentials or your institution for full access to this article.

Personal login Institutional Login Open Athens login
Purchase Options

Purchase this article to access the full text.

PPV Articles - Psychiatric Services

PPV Articles - Psychiatric Services

Not a subscriber?

Subscribe Now / Learn More

PsychiatryOnline subscription options offer access to the DSM-5-TR® library, books, journals, CME, and patient resources. This all-in-one virtual library provides psychiatrists and mental health professionals with key resources for diagnosis, treatment, research, and professional development.

Need more help? PsychiatryOnline Customer Service may be reached by emailing [email protected] or by calling 800-368-5777 (in the U.S.) or 703-907-7322 (outside the U.S.).

Media

Figures

Other

Tables

Share

Share

Share article link

Share