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Published Online:https://doi.org/10.1176/appi.ps.201400295

Abstract

Objective:

This study aimed to determine whether a self-management support service was more effective than treatment as usual in reducing depressive symptoms and major depressive episodes and increasing personal recovery among individuals with chronic or recurrent depressive symptoms.

Methods:

The study was a randomized controlled trial of a self-management support service consisting of depression self-management training, recovery coaching, and care coordination. The 18-month intervention included regular telephone or in-person contacts with a care manager and a structured group program co-led by a professional therapist and a trained peer specialist. Intervention (N=150) and control (N=152) participants ages ≥18 with chronic or recurrent depressive symptoms were recruited from five clinics in Seattle, Washington. Outcome measures included the Hopkins Symptom Checklist depression scale, the Recovery Assessment Scale, the Patient-Rated Global Improvement scale, and the percentage of participants with a major depressive episode. Interviewers were masked to treatment condition.

Results:

Repeated-measures estimates of the long-term effect of the intervention versus usual care (average of the six-, 12-, and 18-month outcomes adjusted for age, gender, and site) indicated that intervention participants had less severe symptoms (p=.002) and higher recovery scores (p=.03), were less likely to be depressed (odds ratio [OR]=.52, p=.001), and were more likely to be much improved (OR=1.96, p=.001).

Conclusions:

These findings support providing regular outreach care management and a self-care group offering a combined behavioral and recovery-oriented approach for people with chronic or recurrent depressive symptoms.

The personal and societal burden of depression weighs most heavily on persons with chronic or recurrent illness. Up to 30% of patients with depression have a chronic course with protracted episodes or incomplete remission between episodes (19). Community surveys estimate that at any given time, at least 3% of the population experiences chronic depression (6,1012). Persistent depression is associated with high utilization of general medical services (11,13), poor general health, and greater impairment in psychosocial and work functioning (4,1417). Chronic depression is one of the strongest risk factors for suicide attempts and hospitalization (18). Among primary care patients treated for depression, 15% have persistent depression, but they account for 35% of health care expenditures and 45% of lost work productivity due to the illness (19).

Efforts to improve the effectiveness of community depression care have primarily focused on initial treatment. Various collaborative care or care management programs have attempted to bridge the gap between efficacy and effectiveness by increasing the proportion of people who receive evidence-based care when they begin depression treatment. Such programs have been repeatedly proven to improve quality of treatment, satisfaction with care, and clinical outcomes (20,21). Key ingredients of these programs have included persistent outreach to promote engagement, systematic measurement of outcomes, application of evidence-based treatment algorithms, and support for self-management of depression (including both psychoeducation and structured psychotherapy) (2224).

A similar effort is needed to improve the effectiveness of care for chronic depression (25). Efficacy of specific treatments for chronic depression, both pharmacotherapy and psychotherapy, is well established (2633), but the actual reach of those treatments is limited. Extending successful collaborative care or care management models to chronic depression must address two challenges. First, chronic depressive symptoms can lead to hopelessness regarding the effectiveness of treatment and the possibility of recovery. Care programs for people living with chronic symptoms must emphasize the possibility of recovery while acknowledging disappointing experiences with treatment (3436). Second, pathways to chronic depression are highly varied in terms of life experience and treatment history (9,37). Effective care programs must improve the quality of treatment while accommodating this diversity.

This study compared the effectiveness of a self-management support service and treatment as usual in reducing depressive symptoms and major depressive episodes and increasing personal recovery among individuals with chronic or recurrent depressive symptoms. This effectiveness trial enrolled a heterogeneous sample of patients with chronic depressive symptoms. The intervention consisted of a flexible program that included outreach care management to improve engagement with mental health services and pharmacotherapy and a self-management skills group program incorporating wellness and recovery elements. We hypothesized that the intervention program would produce greater long-term symptom improvement and perceived recovery compared with usual depression care.

Methods

Participants and Recruitment

Between January 2010 and October 2011, participants were recruited from four primary care clinics of Group Health (GH) Cooperative and from the Swedish Family Medicine Residency Clinic at Cherry Hill. Both GH and Swedish are nonprofit health care organizations in the Seattle, Washington, area. GH clinics provide coverage and care to approximately 600,000 Washington residents; the Cherry Hill clinic provides primary care to an economically disadvantaged population numbering about 20,000 per year.

Potential participants were identified through population-based screening and provider referral. Electronic medical records data from the GH and Cherry Hill clinics were used to identify potentially eligible patients. Identified patients were at least 18 years old, had at least two visits for depression associated with antidepressant treatment in the past year, had no diagnosis of bipolar or psychotic disorder in the past two years, and were not currently participating in other depression-related studies. Providers at participating GH clinics and Cherry Hill were also notified about the study, and patients at both organizations were allowed to self-refer to the study. Brochures and flyers were designed to help providers at Cherry Hill inform other potentially eligible patients (missed by electronic identification) about the study and how to self-refer.

Study staff at each site mailed invitation letters to potentially eligible patients that included a $2 bill as a “preincentive” and an option to decline further contact. Staff followed up with a phone call to assess interest in participation. GH study staff were responsible for conducting eligibility assessment by phone with all patients expressing interest in participation. Staff at Cherry Hill asked interested patients for verbal permission to release their contact information to the GH study staff.

Eligibility and Baseline Assessments

Inclusion criteria were assessed by telephone screening. Eligibility requirements included significant residual symptoms (score of ≥10 on the Patient Health Questionnaire–9 [PHQ-9]) (38,39), history of recurrent major depression (three or more episodes in the past five years) or dysthymia, and willingness to attend groups. Exclusion criteria included history of mania or hypomania, cognitive impairment, metastatic cancer, chronic renal failure, or having a plan to move out of state in the next 18 months. Co-occurring alcohol or drug use, personality, or anxiety disorders were not exclusion criteria.

Following telephone screening, participants were asked to complete an in-person baseline assessment. Research study staff obtained written informed consent, and participants received $20 for time and travel.

At baseline, trained interviewers assessed current depression with the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I) (40) and the 20-item Hopkins Symptom Checklist (SCL-20) for depression (41). The Recovery Assessment Scale (RAS) was included to assess participants’ perceptions of recovery and included five subscales (personal confidence and hope, willingness to ask for help, goal and success orientation, reliance on others, and no domination by symptoms) (42). Co-occurring anxiety disorders were assessed with the Psychiatric Diagnostic Screening Questionnaire (PDSQ) (43), and borderline personality disorder was assessed by using the self-report screener from the Structured Clinical Interview for DSM-IV Axis II Personality Disorders (SCID-II) (44). Cutoff scores for the SCID-II and PDSQ were selected to maximize specificity. Bipolar spectrum disorder was assessed with the Mood Disorder Questionnaire (45). We included additional questions regarding use of depression services (including inpatient and outpatient mental health specialty services, medical visits addressing depression, and antidepressant medication).

Randomization

Following the baseline interview, participants were randomly assigned to the intervention or usual care by using electronically generated randomization tables. Randomization was stratified by site and blocked in randomly allocated block sizes ranging from 4 to 12 through the use of a scheme that was designed by the study statistician and incorporated into the tracking database; interviewers were blinded to treatment group. Participants assigned to the intervention group were notified by a study care manager. Participants assigned to usual care were notified by mail.

Participants assigned to either group were free to use any primary care or mental health specialty services normally available at GH or Cherry Hill or available elsewhere.

Intervention

The 18-month intervention included regular telephone or in-person contacts with a care manager and a structured group program. The meetings were co-led by a care manager and a trained peer specialist. After random assignment, participants who were assigned to the intervention were invited to attend an engagement session modeled on the work of Grote and colleagues (46) and Zuckoff and colleagues (47). During the engagement sessions, the care manager and peer specialist followed an outline and a suggested script that employed evocative and motivational strategies to increase initial engagement in all aspects of the intervention program (46,47). As part of the group program, participants met weekly for ten weeks, twice a month for two months, and then once a month for maintenance of progress.

Over the course of the study, four clinicians with varied professional training functioned as care managers, including a social worker, a marriage and family therapist, a health educator, and a psychologist. All had extensive experience working with patients with depression. Three individuals with personal experience of depression served as paid peer specialists. Each specialist completed a five-day training and certification program from the Depression and Bipolar Support Alliance. Peer specialists held drop-in office hours and made group reminder calls, in addition to cofacilitating groups. During these contacts, peer specialists engaged in conversations focused on goals and strategies to facilitate recovery. Peer specialists referred all clinical concerns to the care manager, treating providers, or supervisory team.

The tracking database supported systematic tracking of patient contacts, assessment of depressive symptoms (PHQ-9), documentation of self-care and recovery goals, and participation in the group program. The care manager contacted patients at specified intervals no longer than a month apart during the first 12 months, after which the intervals between contacts varied according to symptoms, treatment adherence, and patient engagement with treatment providers. During each contact, care managers helped participants identify, plan, and troubleshoot actions to meet personal self-management goals.

Care managers also sent quarterly reports to treating providers via e-mail (for GH providers) or by fax (for Swedish providers). Reports included information about patients’ current depressive symptoms (PHQ-9), participation in the group program, and self-care and recovery goals. The care manager also provided care coordination and facilitated follow-up care. All intervention staff received weekly supervision by the study psychologist and psychiatrist. These weekly sessions were used to discuss patients with moderate or more severe depressive symptoms or who were overdue for contact or to respond to concerns by care managers about a particular patient.

The manualized self-management group program was adapted from the cognitive-behavioral therapy program used in our pilot study (48) and supplemented with recovery-oriented content (49,50). [The content of weekly classes is summarized in an online supplement to this article.] The peer specialist acted as both a cofacilitator and a participant role model for the groups.

Blinded Outcome Assessments

Interviewers blinded to treatment assignment contacted participants by telephone for outcome assessments at three, six, 12, and 18 months after randomization. Participants were paid $20 for completion of each interim assessment and $30 for completion of the final assessment (regardless of treatment assignment or level of participation in treatment). Each assessment included the SCL-20 (41); the current depression module of the SCID-I (40); the RAS (42); the Patient-Rated Global Improvement (PGI) (51), a 7-point rating of treatment effectiveness from a patient’s perspective; and questions about mental health care utilization and antidepressant use since the previous assessment.

Protection of Human Subjects

All participants provided documented oral consent for participation in telephone screening and written informed consent prior to study enrollment. Study procedures and materials were approved by both the GH and Swedish Medical Center institutional review boards. Study safety was monitored by a Data Safety Monitoring Board, which met every six to 12 months to review reports on recruitment, data collection, patient safety, and outcomes.

Data Analysis

We compared the intervention and control groups at baseline by using t tests for continuous variables and chi square tests for binary or categorical variables.

Our primary outcome measure was the mean score on the SCL-20. Secondary outcome measures included percentage of participants with major depression on the basis of SCID-I diagnosis, percentage of participants with a PGI rating of “much improved” or better, and mean score on the RAS. The primary analysis assessed the long-term effect of the intervention by comparing the average of the six-, 12- and 18-month outcomes for each group. We estimated this effect by using repeated-measures methods, including random-effects mixed models for continuous or ordinal outcomes (such as the SCL-20), and generalized estimating equations (GEE) for binary outcomes. GEE models used an independent working correlation with empirical standard errors. We also compared the groups on rate of improvement over the first six months by using random-effects mixed models and GEEs and at each time point (cross-sectional analysis) by using t tests and chi square tests. All analyses were completed with and without adjustment for site, age, gender, and baseline value of the outcome variable (except for the model for initial rate of change).

Analyses classified participants according to initial treatment assignment without regard to their degree of participation in the intervention (intent-to-treat approach.) The study had 80% power to detect an 11.3% difference on the SCL-20. All analyses used SAS 9.1.

Results

Recruitment

Between January 2010 and September 2011, a total of 2,166 potentially eligible patients were identified either by review of computerized records or by referral by treating providers. Of those invited for screening, 1,150 completed screening interviews; 302 patients were eligible to participate, completed baseline interviews, and were randomly assigned to the intervention (N=150) or to a usual care control group (N=152). [A flowchart documenting participation in the intervention is available in an online supplement to this article.] Enrollment continued until we reached our enrollment goal of 300, chosen on the basis of power analyses.

Of the 150 patients assigned to the intervention, 138 (92%), 137 (91%), 135 (90%), and 134 (89%) completed the three-, six-, 12-, and 18-month follow-up interviews, respectively. Of the 152 patients assigned to usual care, 145 (95%), 140 (92%), 138 (91%, and 140 (92%) completed the three-, six-, 12-, and 18-month follow-up interviews, respectively. There were no significant differences between the treatment groups in follow-up rates overall or at any time point.

Characteristics of Participants

As shown in Table 1, the modal participant was a middle-aged female with moderate symptoms of depression. Those assigned to the intervention group were more often female, but treatment groups were similar in all other baseline characteristics.

TABLE 1. Baseline characteristics of participants in depression self-management support services and a control group

Control (N=152)Intervention (N=150)
CharacteristicN%N%p
Age (M±SD)50.9±13.148.7±14.7.16
 18–4442285335
 45–6492617349.12
 ≥6518122416
Female936111275.01
College graduate or some college1338812885.58
Caucasian1117311275.99
Married57385436.85
Employed80537248.42
Major depression1097210570.74
Panic disorder9675.63
General anxiety disorder29192919.96
Borderline personality disorder85568758.71
SCL-20 (mean±SD score)a1.93±.631.91±.53.67
Recovery Assessment Scale (mean±SD score)b3.45±.453.48±.41.58

aSCL-20, Hopkins Symptom Checklist for depression. Possible scores range from 0 to 4, with higher scores indicating more severe depression.

bPossible scores range from 0 to 4, with higher scores indicating greater perceived recovery.

TABLE 1. Baseline characteristics of participants in depression self-management support services and a control group

Enlarge table

Participation in the Intervention

Of the 150 participants randomly assigned to the intervention, 148 (99%) had at least one care manager contact, 133 (89%) had four or more care manager contacts, and 127 (85%) remained engaged (received some care management contacts) during the last six months of their enrollment. A total of 124 (83%) participants attended at least one group session, 71 (47%) completed seven or more weekly group sessions, and 54 (35%) attended some group sessions in the last six months of their enrollment. Study participants attended 10±11 group sessions, including approximately 6±4 weekly sessions and 4±5 maintenance sessions. Thirteen groups were initiated during the course of the study. All sessions were audiotaped; a sampling of sessions (N=7) were independently rated for fidelity, and all were rated excellent.

Primary Outcomes

To determine if the intervention was efficacious, we examined the long-term effects on four outcomes (selected a priori): the SCL-20, the RAS, percentage with major depression (according to the SCID-I), and percentage who reported being greatly improved (PGI). The intervention had significant long-term effects—defined as the average of the six-, 12-, and 18-month follow-ups—on all four outcomes in repeated-measures analyses, with or without adjustment for age, gender, site, and baseline value of the outcome variable (adjusted p<.002, except for the RAS and the SCL-20 [p=.03]) (Table 2).

TABLE 2. Follow-up outcomes among participants in depression self-management support services and a control groupa

OutcomeControl (N=152)Intervention (N=150)Unadjusted analysisAdjusted analysis
MSDMSDDifference in meanspDifference in meansp
SCL-20b
 Baseline1.93.631.91.53–.02.69nana
 Month 31.55.681.47.63–.08.27–.07.27
 Month 61.48.691.32.67–.16.055–.18.015
 Month 121.41.711.27.69–.14.11–.16.03
 Month 181.35.751.07.68–.28.001–.29<.001
 Averagec1.421.22–.20.003–.19.003
Recovery Assessment Scaled
 Baseline3.45.453.48.41.03.56nana
 Month 33.59.433.67.45.08.11.057.12
 Month 63.67.453.76.41.09.11.07.07
 Month 123.69.503.79.48.10.10.11.02
 Month 183.75.513.92.43.17.003.13.01
 Averagec3.693.82.13.01.11.03
N%N%ORpAORp
Major depressione
 Baseline1097210570.92.74nana
 Month 372504029.41<.001.37<.001
 Month 653384130.69.16.67.14
 Month 1254393526.55.02.49.01
 Month 1845322821.56.04.52.03
 Averagec3626.55.003.52.001
Much improvedf
 Month 3261840291.89.031.86.03
 Month 6292153392.42.0012.39.002
 Month 12413050371.40.201.47.15
 Month 18443167502.18.0021.95.001
 Averagec27421.92<.0011.96.001

aThe groups were compared at each follow-up by using t tests for means and chi square tests for binary or ordinal variables in unadjusted models and by using least-squares regression for means and logistic regression for binary or ordinal variables in adjusted models. Adjusted models controlled for site, age, gender, and the baseline value of the outcome. For comparisons based on the combined 6-, 12-, and 18-month follow-ups, all p values are from random-effects mixed models, which account for correlation caused by repeated measures. Data were available for 145, 140, 138, and 140 control participants and 138, 137, 135, and 134 intervention participants at months 3, 6, 12, and 18, respectively.

bSCL-20, Hopkins Symptom Checklist for depression. Possible scores range from 0 to 4, with higher scores indicating more severe depression.

cAverage of the outcomes at 6-, 12-, and 18-month follow-ups

dPossible scores range from 0 to 4, with higher scores indicating higher level of perceived recovery.

eDetermined by the Structured Clinical Interview for DSM-IV Axis I Disorders

fDetermined by the Patient-Rated Global Improvement scale

TABLE 2. Follow-up outcomes among participants in depression self-management support services and a control groupa

Enlarge table

We also examined whether the intervention affected the rate of improvement over the first six months of the trial (“initial improvement”). The intervention resulted in faster rates of initial improvement on the SCL-20 and the RAS (adjusted p=.003 for the SCL and .013 for the RAS). Initial improvement for the control and intervention groups did not differ significantly for either the percentage with major depression or the percentage who reported being greatly improved.

We tested whether the effect of the intervention on the SCL depended on receipt of specialty mental health care at baseline. We found no evidence of such an interaction (data not shown).

Use of Antidepressants and Mental Health Services

Rates of self-reported utilization of nonstudy services for depression and antidepressant medication are shown in Table 3. Of GH participants for whom complete computerized pharmacy records were available, five of 122 in the intervention group and six of 128 in usual care initiated antidepressant treatment between baseline and three months (pharmacy records were not available at the Cherry Hill site). Intervention participants were more likely than members of the control group to be taking antidepressant medication at six, 12, and 18 months. Participants in the intervention group had significantly more nonstudy-related visits for depression at six months, but otherwise the rates of mental health visits between the two groups were comparable.

TABLE 3. Antidepressant use and mental health visits during follow-up among participants in depression self-management support services and a control group

Control (N=152)Intervention (N=150)
OutcomeN with dataN%N with dataN%ORapb
Use of antidepressantsc
 Month 314412486138127921.87.11
 Month 614011582137125912.22.03
 Month 1213811382134121901.98.05
 Month 1814010877134117872.00.03
Percentage of doses taken (M±SD)c,d
 Month 312490%±23%12793%±19%3%.28
 Month 611592%±21%12594%±18%2%.36
 Month 1211391%±19%12192%±19%1%.82
 Month 1810789%±23%11790%±22%1%.94
Any mental health visits
 Baseline15210670150109731.16.49
 Month 3152905915099661.35.22
 Month 6152734815098652.01.003
 Month 12152916015097651.24.33
 Month 18152966415099671.14.6
Mental health visits per year (M±SD)e
 Baseline10621.5±24.510918.6±18.8–14%.35
 Month 39023.0±26.69922.1±28.1–4%.81
 Month 67327.0±27.69822.8±24.8–15%.31
 Month 129122.0±32.89718.7±21.8–15%.42
 Month 189620.9±29.89918.7±30.6–11%.61

aReference group for ORs is the control group. Data for doses taken are reported as the difference in the percentages; data for mental health visits per year are reported as percentage difference in the two rates.

bComparisons of antidepressant use and any mental health visits used chi square tests; other comparisons used t tests.

cNot collected at baseline

dAmong participants who reported use of an antidepressant

eAmong participants who reported at least 1 visit

TABLE 3. Antidepressant use and mental health visits during follow-up among participants in depression self-management support services and a control group

Enlarge table

Discussion

The intervention offered outreach care management and a self-management skills group program that included contributions and perspectives of both mental health professionals and peer support specialists. Results of the study showed broad support for this intervention across the domains of depressive symptoms and episodes, patient-rated global improvement, and recovery. An explicit goal of the intervention was to integrate the perspectives of the chronic care model and the recovery model in a single program. The chronic care model proposes a reorganization of the health care system to manage chronic or recurring illnesses more effectively (22,23). A unique contribution of this model is the focus on outreach to and engagement of people who are not already receiving services. The recovery model focuses on delivery of peer support to improve patients’ enjoyment of life by promoting a sense of well-being, hope, and optimism (52).

Our results suggest that these models can be successfully integrated, but in doing so, we cannot disentangle the effects of different intervention components. As in all multicomponent interventions, it is impossible to isolate the components that helped each individual. However, given the heterogeneity of chronic depression, a flexible program with patient-driven selection of components may meet the needs of the greatest number of people with chronic depression.

The terms self-management and recovery describe complementary, ongoing processes in which a person is the central determinant of his or her health and well-being (53). The intervention aimed to simultaneously diminish symptoms of depression and promote the separate dimension of well-being and life satisfaction. It achieved positive outcomes across both of these domains, similar to results among individuals with serious mental illness (50). Peer providers serve as important coping role models for both of these processes. Including peers as leaders in group programs emphasizes the strengths and experiential knowledge of persons with depression and demonstrates that strengths and internal resources are highly valued. Peer-led groups assist with destigmatization for those whose social identities have been put at risk by their illness. The social support and connectivity of groups enable members to better withstand crisis and alienation (54).

Not surprisingly, improvement of symptoms in both the intervention and the usual care groups was not as great as the improvement seen in trials focused on acute-phase treatment (20,21). Compared with participants in programs focused on acute or new episodes of depression, the participants in our study were likely to have tried treatments before, both pharmacological and psychotherapeutic (although not necessarily at adequate doses or duration). However, in this study, the effects at 18 months were larger compared with the effects that are usually observed in trials of other organized care programs, indicating that the effects of the intervention persisted to an unusual degree.

Strengths of the study included a large sample size, broad eligibility criteria, and recruitment from a variety of practice settings. We measured several outcomes of interest to patients and clinicians and found consistent positive results. Contributions of this study include a focus on persons with chronic depressive symptoms, collaboration between consumers and professionals in the design and delivery of the intervention, and an expansion of measurement-based care to include not only depressive symptoms but also recovery-oriented outcomes.

Delivery of a group program combining elements of traditional CBT for depression with recovery-oriented content was not without its challenges. Others hoping to deliver similar programs must expect ongoing negotiation about how to bridge differences in orientation and culture between two approaches that have not always been historically aligned.

There were several limitations to this study. We used treatment records to identify potential participants and thus did not recruit persons who had longstanding symptoms of depression but had no prior diagnosis. Participants came from two urban clinical systems and were well educated, limiting generalizability. Recruitment from the two sites was lopsided, and the lower number of participants from the clinic serving more disadvantaged patients precludes subgroup comparisons by site. Automated utilization data were available only for GH patients, so we used self-report for the whole sample. Nevertheless, we believe this limitation was offset by including two clinical systems and a more diverse population.

Conclusions

A systematic program of care management and group self-management support is a worthy addition to outpatient care for patients with chronic depressive symptoms. By combining elements of the chronic care model and the recovery model in a single program, the program successfully integrated the management strengths of the chronic care model with the sense of optimism and well-being provided by a care management approach.

The authors are with the Group Health Research Institute, Group Health Cooperative, Seattle, Washington (e-mail: ).

These data were presented at the National Institute of Mental Health Conference on Mental Health Services Research, Bethesda, Maryland, April 23–25, 2014.

The study was supported by grant MH065530 from the National Institute of Mental Health and was registered at clinical trials.gov (NCT01139060).

The authors report no financial relationships with commercial interests.

References

1 Keller MB, Klerman GL, Lavori PW, et al.: Long-term outcome of episodes of major depression: clinical and public health significance. JAMA 252:788–792, 1984Crossref, MedlineGoogle Scholar

2 Angst J: Fortnightly review: a regular review of the long-term follow-up of depression. BMJ 315:1143–1146, 1997Crossref, MedlineGoogle Scholar

3 Judd LL, Akiskal HS, Paulus MP: The role and clinical significance of subsyndromal depressive symptoms (SSD) in unipolar major depressive disorder. Journal of Affective Disorders 45:5–17, 1997Crossref, MedlineGoogle Scholar

4 Simon GE, Heiligenstein J, Revicki D, et al.: Long-term outcomes of initial antidepressant drug choice in a “real world” randomized trial. Archives of Family Medicine 8:319–325, 1999Crossref, MedlineGoogle Scholar

5 Simon GE, Von Korff M, Rutter CM, et al.: Treatment process and outcomes for managed care patients receiving new antidepressant prescriptions from psychiatrists and primary care physicians. Archives of General Psychiatry 58:395–401, 2001Crossref, MedlineGoogle Scholar

6 Murphy JA, Byrne GJ: Prevalence and correlates of the proposed DSM-5 diagnosis of chronic depressive disorder. Journal of Affective Disorders 139:172–180, 2012Crossref, MedlineGoogle Scholar

7 Rubio JM, Markowitz JC, Alegria A, et al.: Epidemiology of chronic and nonchronic major depressive disorder: results from the National Epidemiologic Survey on Alcohol and Related Conditions. Depression and Anxiety 28:622–631, 2011Crossref, MedlineGoogle Scholar

8 Hardeveld F, Spijker J, De Graaf R, et al.: Prevalence and predictors of recurrence of major depressive disorder in the adult population. Acta Psychiatrica Scandinavica 122:184–191, 2010Crossref, MedlineGoogle Scholar

9 Torpey DC, Klein DN: Chronic depression: update on classification and treatment. Current Psychiatry Reports 10:458–464, 2008Crossref, MedlineGoogle Scholar

10 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. Archives of General Psychiatry 51:8–19, 1994Crossref, MedlineGoogle Scholar

11 Weissman MM, Leaf PJ, Bruce ML, et al.: The epidemiology of dysthymia in five communities: rates, risks, comorbidity, and treatment. American Journal of Psychiatry 145:815–819, 1988LinkGoogle Scholar

12 Blanco C, Okuda M, Markowitz JC, et al.: The epidemiology of chronic major depressive disorder and dysthymic disorder: results from the National Epidemiologic Survey on Alcohol and Related Conditions. Journal of Clinical Psychiatry 71:1645–1656, 2010Crossref, MedlineGoogle Scholar

13 Howland RH: Chronic depression. Hospital and Community Psychiatry 44:633–639, 1993AbstractGoogle Scholar

14 Wells KB, Burnam MA, Rogers W, et al.: The course of depression in adult outpatients: results from the Medical Outcomes Study. Archives of General Psychiatry 49:788–794, 1992Crossref, MedlineGoogle Scholar

15 Hays RD, Wells KB, Sherbourne CD, et al.: Functioning and well-being outcomes of patients with depression compared with chronic general medical illnesses. Archives of General Psychiatry 52:11–19, 1995Crossref, MedlineGoogle Scholar

16 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, 2003Crossref, MedlineGoogle Scholar

17 Gopinath S, Katon WJ, Russo JE, et al.: Clinical factors associated with relapse in primary care patients with chronic or recurrent depression. Journal of Affective Disorders 101:57–63, 2007Crossref, MedlineGoogle Scholar

18 Klein DN, Norden KA, Ferro T, et al.: Thirty-month naturalistic follow-up study of early-onset dysthymic disorder: course, diagnostic stability, and prediction of outcome. Journal of Abnormal Psychology 107:338–348, 1998Crossref, MedlineGoogle Scholar

19 Simon GE, Revicki D, Heiligenstein J, et al.: Recovery from depression, work productivity, and health care costs among primary care patients. General Hospital Psychiatry 22:153–162, 2000Crossref, MedlineGoogle Scholar

20 Bower P, Gilbody S, Richards D, et al.: Collaborative care for depression in primary care: making sense of a complex intervention: systematic review and meta-regression. British Journal of Psychiatry 189:484–493, 2006Crossref, MedlineGoogle Scholar

21 Archer J, Bower P, Gilbody S, et al.: Collaborative care for depression and anxiety problems. Cochrane Database of Systematic Reviews 10:CD006525, 2012MedlineGoogle Scholar

22 Wagner EH, Austin BT, Von Korff M: Organizing care for patients with chronic illness. Milbank Quarterly 74:511–544, 1996Crossref, MedlineGoogle Scholar

23 Von Korff M, Gruman J, Schaefer J, et al.: Collaborative management of chronic illness. Annals of Internal Medicine 127:1097–1102, 1997Crossref, MedlineGoogle Scholar

24 Katon W, Unützer J, Wells K, et al.: Collaborative depression care: history, evolution and ways to enhance dissemination and sustainability. General Hospital Psychiatry 32:456–464, 2010Crossref, MedlineGoogle Scholar

25 Murray G, Michalak EE, Axler A, et al.: Relief of chronic or resistant depression (Re-ChORD): a pragmatic, randomized, open-treatment trial of an integrative program intervention for chronic depression. Journal of Affective Disorders 123:243–248, 2010Crossref, MedlineGoogle Scholar

26 Keller MB, Kocsis JH, Thase ME, et al.: Maintenance phase efficacy of sertraline for chronic depression: a randomized controlled trial. JAMA 280:1665–1672, 1998Crossref, MedlineGoogle Scholar

27 Keller MB, McCullough JP, Klein DN, et al.: A comparison of nefazodone, the cognitive behavioral-analysis system of psychotherapy, and their combination for the treatment of chronic depression. New England Journal of Medicine 342:1462–1470, 2000Crossref, MedlineGoogle Scholar

28 Teasdale JD, Segal ZV, Williams JM, et al.: Prevention of relapse/recurrence in major depression by mindfulness-based cognitive therapy. Journal of Consulting and Clinical Psychology 68:615–623, 2000Crossref, MedlineGoogle Scholar

29 Jarrett RB, Kraft D, Doyle J, et al.: Preventing recurrent depression using cognitive therapy with and without a continuation phase: a randomized clinical trial. Archives of General Psychiatry 58:381–388, 2001Crossref, MedlineGoogle Scholar

30 Arnow BA, Constantino MJ: Effectiveness of psychotherapy and combination treatment for chronic depression. Journal of Clinical Psychology 59:893–905, 2003Crossref, MedlineGoogle Scholar

31 Klein DN, Santiago NJ, Vivian D, et al.: Cognitive-behavioral analysis system of psychotherapy as a maintenance treatment for chronic depression. Journal of Consulting and Clinical Psychology 72:681–688, 2004Crossref, MedlineGoogle Scholar

32 Schramm E, Schneider D, Zobel I, et al.: Efficacy of interpersonal psychotherapy plus pharmacotherapy in chronically depressed inpatients. Journal of Affective Disorders 109:65–73, 2008Crossref, MedlineGoogle Scholar

33 Cuijpers P, van Straten A, Schuurmans J, et al.: Psychotherapy for chronic major depression and dysthymia: a meta-analysis. Clinical Psychology Review 30:51–62, 2010Crossref, MedlineGoogle Scholar

34 Jacobson N, Greenley D: What is recovery? A conceptual model and explication. Psychiatric Services 52:482–485, 2001LinkGoogle Scholar

35 Green CA, Perrin NA, Leo MC, et al.: Recovery from serious mental illness: trajectories, characteristics, and the role of mental health care. Psychiatric Services 64:1203–1210, 2013LinkGoogle Scholar

36 Mueser KT, Meyer PS, Penn DL, et al.: The Illness Management and Recovery program: rationale, development, and preliminary findings. Schizophrenia Bulletin 32(suppl 1):S32–S43, 2006Crossref, MedlineGoogle Scholar

37 Gilmer WS, Trivedi MH, Rush AJ, et al.: Factors associated with chronic depressive episodes: a preliminary report from the STAR-D project. Acta Psychiatrica Scandinavica 112:425–433, 2005Crossref, MedlineGoogle Scholar

38 Kroenke K, Spitzer RL, Williams JB: The PHQ-9: validity of a brief depression severity measure. Journal of General Internal Medicine 16:606–613, 2001Crossref, MedlineGoogle Scholar

39 Spitzer RL, Kroenke K, Williams JB: Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study. Primary Care Evaluation of Mental Disorders. Patient Health Questionnaire. JAMA 282:1737–1744, 1999Crossref, MedlineGoogle Scholar

40 First M, Spitzer R, Gibbon J, et al.: Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I) Clinical Version. Washington, DC, American Psychiatric Press, 1997Google Scholar

41 Derogatis L, Rickels K, Uhlenhuth E, et al: The Hopkins Symptom Checklist: a measure of primary symptom dimensions; in Psychological Measurements in Psychopharmacology: Problems in Pharmacopsychiatry. Edited by Pichot P. Basel, Switzerland, Kargerman, 1974Google Scholar

42 Corrigan PW, Salzer M, Ralph RO, et al.: Examining the factor structure of the Recovery Assessment Scale. Schizophrenia Bulletin 30:1035–1041, 2004Crossref, MedlineGoogle Scholar

43 Zimmerman M, Mattia JI: The Psychiatric Diagnostic Screening Questionnaire: development, reliability and validity. Comprehensive Psychiatry 42:175–189, 2001Crossref, MedlineGoogle Scholar

44 First M, Gibbon M, Spitzer R, et al.: User's Guide for the Structured Clinical Interview for DSM-IV Axis II Personality Disorders: SCID-II. Washington, DC, American Psychiatric Press, 1997Google Scholar

45 Hirschfeld RM, Williams JB, Spitzer RL, et al.: Development and validation of a screening instrument for bipolar spectrum disorder: the Mood Disorder Questionnaire. American Journal of Psychiatry 157:1873–1875, 2000LinkGoogle Scholar

46 Grote NK, Zuckoff A, Swartz H, et al.: Engaging women who are depressed and economically disadvantaged in mental health treatment. Social Work 52:295–308, 2007Crossref, MedlineGoogle Scholar

47 Zuckoff A, Swartz HA, Grote NK: Motivational interviewing as a prelude to psychotherapy of depression; in Motivational Interviewing in the Treatment of Psychological Problems. Edited by Arkowitz H, Westra HA, Miller WR, et al. New York, Guilford, 2008Google Scholar

48 Ludman EJ, Simon GE, Grothaus LC, et al.: A pilot study of telephone care management and structured disease self-management groups for chronic depression. Psychiatric Services 58:1065–1072, 2007LinkGoogle Scholar

49 Cook JA, Copeland ME, Jonikas JA, et al.: Results of a randomized controlled trial of mental illness self-management using Wellness Recovery Action Planning. Schizophrenia Bulletin 38:881–891, 2012Crossref, MedlineGoogle Scholar

50 Cook JA, Copeland ME, Floyd CB, et al.: A randomized controlled trial of effects of Wellness Recovery Action Planning on depression, anxiety, and recovery. Psychiatric Services 63:541–547, 2012LinkGoogle Scholar

51 Guy W: ECDEU Assessment Manual for Psychopharmacology. Rockville, Md, US Department of Health, Education and Welfare, Alcohol, Drug Abuse and Mental Health Administration, 1976Google Scholar

52 Mueser KT, Corrigan PW, Hilton DW, et al.: Illness Management and Recovery: a review of the research. Psychiatric Services 53:1272–1284, 2002LinkGoogle Scholar

53 Sterling EW, von Esenwein SA, Tucker S, et al.: Integrating wellness, recovery, and self-management for mental health consumers. Community Mental Health Journal 46:130–138, 2010Crossref, MedlineGoogle Scholar

54 Riessman F, Banks EC: A marriage of opposites: self-help and the health care system. American Psychologist 56:173–174, 2001Crossref, MedlineGoogle Scholar