Context
An understudied crucial step in the help-seeking process is making prompt initial contact with a treatment provider after first onset of a mental disorder.
Objective
To provide data on patterns and predictors of failure and delay in making initial treatment contact after first onset of a mental disorder in the United States from the recently completed National Comorbidity Survey Replication.
Design and Setting
Nationally representative face-to-face household survey carried out between February 2001 and April 2003.
Participants
A total of 9282 respondents aged 18 years and older.
Main Outcome Measures
Lifetime DSM-IV disorders were assessed with the World Mental Health (WMH) Survey Initiative version of the World Health Organization Composite International Diagnostic Interview (WMH-CIDI), a fully structured interview designed to be administered by trained lay interviewers. Information about age of first professional treatment contact for each lifetime DSM-IV/WMH-CIDI disorder assessed in the survey was collected and compared with age at onset of the disorder to study typical duration of delay.
Results
Cumulative lifetime probability curves show that the vast majority of people with lifetime disorders eventually make treatment contact, although more so for mood (88.1%-94.2%) disorders than for anxiety (27.3%-95.3%), impulse control (33.9%-51.8%), or substance (52.7%-76.9%) disorders. Delay among those who eventually make treatment contact ranges from 6 to 8 years for mood disorders and 9 to 23 years for anxiety disorders. Failure to make initial treatment contact and delay among those who eventually make treatment contact are both associated with early age of onset, being in an older cohort, and a number of socio-demographic characteristics (male, married, poorly educated, racial/ethnic minority).
Conclusions
Failure to make prompt initial treatment contact is a pervasive aspect of unmet need for mental health care in the United States. Interventions to speed initial treatment contact are likely to reduce the burdens and hazards of untreated mental disorder.
Research consistently shows that a high proportion of people with prevalent mental disorders in the United States are untreated despite their disorders causing substantial distress and impairment, and despite effective treatments being available.1-5 It is of considerable public health importance to uncover modifiable reasons for this lack of treatment. Successful treatment requires people suffering from the disorder to take a sequence of steps in the help-seeking process.6,7 A critical early step is establishing initial contact with a health care provider following first onset of the disorder. Relatively little is known about patterns and correlates of this early phase of the help-seeking process because most mental health services research focuses on recent treatment of current episodes rather than initial treatment of incident cases.8-14 The few studies that have examined the latter consistently document 2 important facts15-21: that despite low current treatment of prevalent cases, the vast majority of lifetime cases eventually make treatment contact; and that it typically takes quite a number of years after first onset of the disorder for initial treatment contact to occur. The baseline National Comorbidity Survey (NCS), for example, estimated that approximately 80% of all people in the United States with a mental disorder eventually seek treatment, but that the median delay between first onset of the disorder and first treatment contact is nearly a decade.18-21 Studies of delay in initial treatment contact in other developed countries have found similar results.19,20
In the decade since the baseline NCS was carried out, important changes have occurred in the following categories: public attitudes and awareness of mental disorders, clinical diagnostic procedures, the availability of psychotropic medications and evidence-based psychotherapies, and the organization and financing of mental health care.22-41 Unfortunately, the current extent and timing of initial treatment seeking is unknown. The current report addresses this issue by analyzing data from the recently completed National Comorbidity Survey Replication (NCS-R).42 We began by constructing cumulative lifetime probability of treatment contact curves to estimate the current lifetime probability of treatment contact for mental disorders and the typical duration of delay. We then examined socio-demographic predictors of failure and delay in making initial treatment contact. Because recent changes in awareness and management have not occurred uniformly across disorders, with mood disorders in particular receiving considerable attention,25 we examined the extent and predictors of failure and delay separately for each of the core disorders assessed in the NCS-R.
As described in more detail elsewhere,43,44 the NCS-R is a nationally representative, multistage clustered area probability sample of English-speaking respondents aged 18 years and older in the noninstitutionalized civilian population of the 48 coterminous states. Fieldwork was carried out by the professional survey interview field staff of the Institute for Social Research at the University of Michigan, Ann Arbor, between February 2001 and April 2003. A total of 9282 face-to-face interviews were completed. All respondents were administered a part I diagnostic interview of core diagnoses. A subsample of 5692 part I respondents, consisting of all those who met lifetime criteria for a core disorder plus a probability subsample of other respondents, were also administered a part II interview that assessed correlates and disorders of secondary focus. The response rate was 70.9%. Interviewers explained the study and obtained verbal informed consent prior to beginning all interviews. The NCS-R recruitment, consent, and field procedures were approved by the Human Subjects Committees of both Harvard Medical School, Boston, and the University of Michigan.
Diagnoses of DSM-IV disorders were made using the World Health Organization’s World Mental Health Survey Initiative version of the Composite International Diagnostic Interview (WMH-CIDI),44,45 a fully structured lay-administered diagnostic interview that generates diagnoses according to the definitions and criteria of both the ICD-1046 and DSM-IV47 diagnostic systems. Criteria for DSM-IV disorders are used in the current report. The disorders considered in this report include (1) mood disorders, including major depressive episode (MDE), dysthymia (DYS), and bipolar disorder (BPD) I and II studied together for increased statistical power; (2) anxiety disorders, including panic disorder (PD), agoraphobia without panic (AG), specific phobia (SP), social phobia (SoP), generalized anxiety disorder (GAD), posttraumatic stress disorder (PTSD), and separation anxiety disorder (SAD); (3) substance disorders, including alcohol abuse (AA), alcohol dependence (AD), drug abuse (DA), and drug dependence (DD); and (4) impulse control disorders, including intermittent explosive disorder (IED), oppositional defiant disorder (ODD), and attention-deficit/ hyperactivity disorder (ADHD). Lifetime prevalence and age of onset were assessed separately for each disorder.44 It is noteworthy that obsessive-compulsive disorder (OCD) and conduct disorder (CD) were also assessed in the NCS-R and are included in separate reports in substantive analyses, but are not included in the current report because the sample of cases was too small for powerful analysis of OCD. This was because OCD was a secondary disorder assessed in only a fraction of the part II subsample and because age of first treatment seeking was not assessed for CD. All diagnoses are considered with organic exclusions and without diagnostic hierarchy rules. As described by Kessler et al,44 a blind clinical reappraisal study using the Structured Clinical Interview for DSM-IV (SCID)48 showed generally good concordance between DSM-IV diagnoses based on the WMH-CIDI and the SCID for anxiety, mood, and substance disorders. The WMH-CIDI diagnoses of impulse control disorders have not been validated.
Near the end of each WMH-CIDI diagnostic section, respondents were asked whether they ever in their life talked to a medical doctor or other professional about the disorder under investigation. In asking this question, the interviewer clarified that the term “other professional” was meant to apply broadly to include psychologists, counselors, spiritual advisors, herbalists, acupuncturists, and any other healing professionals. Respondents who reported ever talking to any of these professionals about the disorder in question were then asked how old they were the first time they did so. The response to this question was used to define age of first treatment contact.
Predictor variables include age at onset of the focal disorder (coded into the categories 0-12, 13-19, 20-29, and 30 or more years of age), cohort (defined by age at interview in the categories 18-29, 30-44, 45-59, 60 or more years), sex, race/ethnicity (non-Hispanic white, non-Hispanic black, Hispanic, and other), education (categorized as either current students or nonstudents with 0-11, 12, 13-15, or 16 or more years of education), and marital status (categorized as either currently married/cohabitating, previously married, or never married). The last 2 of these predictors vary within a given individual over time. Information was obtained in the NCS-R on timing of marital histories (ie, ages at marriage and marital dissolution), allowing marital status to be coded for each year of each respondent’s life. Information on years of education was also coded as a time-varying predictor by assuming an orderly educational history for each respondent in which 8 years of education corresponds to being a student up to age 14 years and other lengths of education are associated with ages consistent with this benchmark (eg, 12 years of education is assumed to correspond to being a student up to age 18 years).
The data were weighted to adjust for differential probabilities of selection of respondents within households and differential nonresponse as well as to adjust for residual differences between the sample and the United States population on the cross-classification of sociodemographic variables. An additional weight zwas used in the part II sample to adjust for differences in probability of selection into that sample. These procedures are described in more detail by Kessler et al.43 As most disorders considered here were assessed in part I, cumulative probability of lifetime treatment contact curves were estimated using part I data and weights whenever possible. Part II data and weights were used for disorders that were assessed in part II (PTSD, ODD, CD, and ADHD). Survival analysis was used to make estimated projections of cumulative lifetime probability of treatment contact from year of onset. The actuarial method,49 implemented in the Statistical Analysis System version 8.2 (SAS Institute, Cary, NC),50 was used rather than the more familiar Kaplan-Meier method51 of generating survival curves because the former has an advantage over the latter in estimating onsets within a year. Separate curves were generated for each disorder. The typical duration of delay in initial treatment contact was defined as the median number of years from disorder onset to first treatment contact among cases that eventually made treatment contact based on these curves. Time to initial treatment contact in the subset of respondents with BPD was defined as the duration of time from the initial onset of a manic or hypomanic episode to first treatment of a manic or hypomanic episode. Treatment for MDE in the course of BPD was not considered because the current analyses only focused on treatment seeking for specific syndromes and not for comorbid conditions. Discrete-time survival analysis52 with person-year as the unit of analysis was used to examine correlates of treatment contact separately for each disorder. Predictors included both time-invariant predictors (age at onset of the disorder, cohort, sex, race/ethnicity) as well as several time-varying predictors (number of years since first onset of the disorder, education, marital status). Each model was estimated twice for a given disorder: once among all respondents with a history of the disorder to study the predictors of ever making a treatment contact; and then a second time among the subsample who eventually made a treatment contact to study the predictors of delay in initial contact. The Taylor series linearization method53 implemented in the SUDAAN software system54 was used to adjust for the effects of the weighting and clustering of the NCS-R data on significance tests. Multivariate significance tests in the discrete-time survival analyses were made with χ2 tests using Taylor series design-based coefficient variance-covariance matrices. Statistical significance was consistently evaluated using 0.05 level, 2-sided tests.
Cumulative lifetime probabilities of treatment contact
Survival curves were used to make projections of the proportion of cases who will eventually make treatment contact for each disorder assessed in the NCS-R. These proportions are estimated to be 88.1% for MDE, 90.2% for BPD, and 94.2% for DYS (Figure 1), with no statistically significant differences in the survival curves of the individual disorders in this class (χ22 = 0.7; P = .72). Projected proportions are much more variable for anxiety disorders (Figure 2) and are 27.3% for SAD, 50.1% for SoP, 50.1% for SP, 65.3% for PTSD, 66.5% for AG, 86.1% for GAD, and 95.3% for PD, with statistically significant differences in the survival curves of the individual disorders in this class (χ25 = 242.4; P<.001). Projected proportions for impulse control disorders (Figure 3) are 33.9% for ODD, 50.4% for IED, and 51.8% for ADHD, with significant differences in the survival curves of the individual disorders in this class (χ22 = 6.0; P = .05). Projected proportions for substance disorders (Figure 4) are 52.7% for AA, 57.0% for DA, 69.8% for AD, and 76.9% for DD, with significant differences in the survival curves of the individual disorders in this class (χ23 = 44.8; P<.001).
Duration of delays in initial treatment contact
The survival curves were also used to estimate the proportion of cases that made treatment contact in the year of first onset of the disorder and the median delay among people who eventually made treatment contact after the year of first onset (Table 1). The proportion of cases that made treatment contact in the year of disorder onset ranges from highs of 37.4% to 41.6% for the mood disorders to lows of 1.0% to 3.4% for SP, SoP, and SAD. Median years of delay also differ greatly across disorders, from lows of 6 to 8 years for mood disorders to highs of 20 to 23 years for SP and SAD.
Predictors of failure and delay in initial treatment contact
Predictors of failure to ever make a treatment contact among respondents with a given lifetime disorder (Tables 2-4) are very similar to predictors of duration of delay among respondents who eventually made treatment contact. The most consistent predictors of failure to make a treatment contact are cohort and age at onset. Cohort is significantly related to lifetime treatment contact in 14 of 17 comparisons (0.05 level, 2-sided tests), with the dominant pattern being for treatment contact to increase in more recent cohorts. This pattern is even stronger (17 of 17 comparisons) in predicting delay in treatment contact among eventual patients. Age of onset is significantly related to treatment contact in 15 of 17 comparisons, the exceptions being 2 childhood-onset disorders (SAD, ADHD), with a consistent pattern of increasing treatment contact with increasing age at onset. A very similar pattern (17 of 17 significant comparisons) is found in predicting delay in treatment among eventual patients.
Sociodemographic predictors are less consistent. Women have significantly higher odds of treatment contact than men for 4 of the 17 outcomes (MDE, DYS, BPD, SoP), while men never had higher odds than women for any outcome. Sex differences are even weaker (1 of 17 comparisons significant) in predicting delays. Race/ethnic differences are significant in 8 of 17 comparisons, with non-Hispanic whites always having higher odds of treatment than 1 or more minority groups. This pattern is weaker in predicting delays (5 of 17 comparisons significant), even though there are some cases in which minorities have significantly shorter delays than non-Hispanic whites. Education is significant in 8 of 17 comparisons, but the pattern of the association varies considerably across outcomes. The most consistent element in the pattern is that students generally have higher odds of treatment than people who have completed their education. This is quite different from the pattern with respect to delays among eventual cases (10 of 17 comparisons significant), where college graduates generally have the shortest delays. Finally, marital status is significantin 5 of 17 comparisons, with never married respondents consistently more likely and previously married people sometimes more likely than married people to make treatment contact. A similar pattern (7 of 17 comparisons significant) exists in predicting delays among people who eventually make treatment contacts.
The results reported here should be interpreted in light of 5 potential limitations. Perhaps the most concerning is the possibility of recall failure of lifetime events. If respondents who did not seek treatment were more likely either to forget or to normalize symptoms than respondents who received treatment, leading to a false-negative report of lifetime disorder, the prevalence of disorder would be underestimated and the probability of eventual treatment contact would be underestimated. We have no way of evaluating this possibility, although it is noteworthy that in such a case the estimate of the raw number of people with a disorder who had significant delays in initial treatment contact would be conservative.
A second possibility is that despite accurate reports of disorders and treatment contacts occurring, dating was inaccurate. As discussed in more detail by Kessler and Ustun,45 special efforts were made in the NCS-R to help respondents recall age at onset and age at initial treatment contact by asking questions that focused memory search and bounded recall uncertainty.55 Although it is unclear how remaining dating errors would affect results, telescoping (recalling past experiences as having occurred more recently than they actually did occur) is the most likely type of error, which would lead to downward bias in estimates of delays.56
Third, the NCS-R questions about initial treatment contact provide no information about whether treatment was actually obtained or, if so, about the nature, intensity, or adequacy of these treatments. We also did not distinguish between contacts made in health care vs non–health care sectors, as we have done in previous analyses of the original NCS.21 As a result, the findings presented here should be interpreted as upper bounds on the proportions of these cases that received treatment and lower bounds on the typical durations of delays until treatment was received. Furthermore, some meaningful proportion of treated cases received treatment that did not meet minimal standards for treatment adequacy.5 Even though we have no way of pinpointing the specific cases that received inadequate treatment at the point of initial treatment contact, we know that the proportions of cases projected to make eventual treatment contact are greater than the proportions that obtain adequate treatment.
Fourth, predictors of failure and delay in initial contact were necessarily limited to ones that could be retrospectively dated. In the socioeconomic domain, for example, we considered the effects of educational attainment but not of income, as we had no information about each respondent’s income in each year of his or her life. In addition, we limited predictors to variables for which a priori hypotheses have been raised.18-21 Although categories of some predictors (eg, ages at interview and disorder onset, education) were kept broad so as to contain sufficient cases, we still may have lacked the statistical power to identify important differences (eg, between racial and ethnic minority groups). Furthermore, it is important to recognize that even though our outcomes were failures and delays in initial treatment contacts, the estimated effects of the predictors represent amalgamated effects on a number of steps in the help-seeking process that lead up to making an initial treatment contact, such as becoming aware of the disorder, perceiving need for treatment, and accessing care.
Finally, we cannot conclude with certainty how patterns and predictors of failure and delay have changed over the past decade because the current report on the NCS-R differs from earlier analyses of the original NCS18,19,21 in terms of disorders, covariates, and outcomes examined. Even subtle differences between analyses (eg, use of diagnostic hierarchy rules) could have important effects. Exploring temporal trends between the NCS and NCS-R remains an important area for future research.
With these limitations in mind, our results document 2 types of unmet need for mental health treatment in the United States. First, a large number of people never make treatment contacts for the DSM-IV/WMH-CIDI disorders evaluated in the NCS-R. This is especially true for substance and impulse control disorders, where nearly half of all lifetime cases failed to make any treatment contact. Consistent with the finding regarding substance disorders, previous research has shown that people with substance disorders often do not perceive a need for treatment, actively resist treatment, and do not seek treatment until their disorders have become highly debilitating.9,57,58 The low proportion of cases that ever seek treatment for impulse control disorders could reflect the perceptions, both on the part of the people with the disorders and of society at large, that their problems are less relevant to the mental health care system than to other systems (eg, social services, education, criminal justice). Although impulse control disorders can be highly distressing to others, they are often associated with more externalization and less internal dysphoria for cases, resulting in less motivation for afflicted individuals to seek treatment. The facts that these disorders have only recently become recognized as DSM disorders and that treatments are only beginning to emerge are other likely contributing factors to the low rate of treatment of impulse control disorders.47,59,60
The second source of unmet need for mental health care documented in the NCS-R concerns pervasive delays in initial treatment contact. The typical delays documented here persist for years or even decades for some disorders. This has not been a focus of previous research, as mental health services research has traditionally focused on treatment of current episodes for established cases.8-14 This focus led naturally to a concern with lack of treatment rather than with treatment delay. The NCS-R findings suggest that this focus needs to be expanded, as eventual treatment is the typical state of affairs for most of the disorders considered here, while delay in initial treatment seeking is pervasive.
Substantial inter-disorder variation was found both in the probability of eventually making treatment contacts and in typical durations of delay. The pattern of this variation is quite consistent with the pattern found in previous studies of initial treatment contact.18-21 The finding of initial treatment contact being higher and delays shorter for mood disorders than other classes of disorders may be because of the fact that mood disorders have been targeted by educational campaigns, primary care quality improvement programs, and treatment advances.25,26,28,31,61 The prominent and dysphoric somatic symptoms often found in conjunction with panic disorder may account for the finding that treatment contact is more common and occurs more quickly for panic disorder than other types of anxiety disorder.62,63 Greater failure and delays for some anxiety disorders such as phobias and SAD could be because of their generally early age at onset, fewer associated impairments, and even fear of providers or treatments involving social interactions (eg, talking therapies, group settings, waiting rooms).9,12,64
Shorter delays and higher proportions of cases with eventual treatment contact in more recent cohorts provide grounds for optimism, as they provide some evidence that patterns of help-seeking have improved in the recent past. This secular change could be, in part, because of recent programs that destigmatize and increase awareness of mental illness, screening and outreach initiatives, the introduction and direct-to-consumer promotion of new treatments, and expansion of some insurance programs,22-41 although a more fine-grained mapping of time series information would be needed to document effects of specific initiatives. Drug dependence is a notable exception to the general pattern of increased treatment in recent cohorts. There are both longer delays and fewer initial contacts in younger cohorts than older ones. Whether this is the result of methodological (eg, failure to capture contacts with self-help groups which now play increasingly important roles in the treatment of substance disorders) or substantive processes is unclear, although one might expect methodological factors to have effects that emerged more consistently across the full range of conditions. To the extent that the pattern is substantive, it might be because of changes in funding of drug treatment programs, changes in public attitudes toward drug dependence, or a combination of those factors.65-67 Given the importance of timely drug treatment, more detailed investigation is warranted.
We found that early-onset disorders are consistently associated with longer delays and a lower overall probability of initial treatment contact. The same pattern has consistently been found in previous studies of delays in initial treatment contact.18-21 Minors may be less likely to receive timely treatment because they need the help of parents or other adults and recognition is often low among these adults unless symptoms are extreme.68,69 In addition, child- and adolescent-onset mental disorders might be associated with normalization of symptoms or the development of coping strategies (eg, social withdrawal in social phobias) that interfere with help-seeking during adulthood. The paucity of available or accessible child mental health services may also be an important factor.
Men have been shown in earlier research to be slower than women at translating nonspecific feelings of distress into conscious recognition that they have emotional problems, perhaps explaining the NCS-R finding that males sometimes have longer delays and lower rates of treatment contact than women.70,71 The longer delays and lower odds of ever making treatment contacts found among minorities compared with non-Hispanic whites are broadly consistent with findings in earlier studies that minorities often receive suboptimal mental health care,2,3,12 but we are not aware of any previous research that explicitly examined race/ethnic differences in initial treatment contact. Negative attitudes toward treatment on the part of minorities could play an important part in accounting for these results.72 However, the fact that the race/ethnic differences in delays and eventual treatment vary substantially across outcomes suggests that more than broad attitudinal factors are likely to be involved. Greater knowledge and financial resources to pay for treatments could help explain the positive associations between education and initial help-seeking for many mental disorders; on the other hand, greater help-seeking for substance disorders by those less educated could reflect their greater acceptance and lower financial barriers to addiction services, many of which are self-help groups.73 Difficulties forming or maintaining relationships and lack of social support from a partner may be strong impetuses for those not married to rapidly seek mental health treatments.6,12
It is important to consider whether the delays and failures to make initial treatment contacts truly pose a public health problem. An alternative view is that they may only characterize less severe, short-lived, or nondebilitating mental disorders.74 However, research in the baseline NCS data showed that many people with even severe and impairing disorders reported substantial delays in initial treatment contact.21 Long periods of untreated illness may also be harmful to those with less severe disorders. Preclinical studies suggest that neural “kindling” can cause untreated psychiatric disorders to become more frequent, severe, spontaneous, and treatment refractory.75 In addition, epidemiological studies suggest that school failure, teenage child-bearing, unstable employment, early marriage, marital violence, and marital instability are associated with early-onset untreated mental disorders.76-79 Recent randomized clinical trials have shown that treatment can prevent suicidality.80 Furthermore, most people with 1 disorder progress to develop comorbid disorders and such comorbidity is associated with an even more persistent and severe clinical course.81,82 However, it should be kept in mind that not all studies have found a relationship between the duration of untreated mental illness and long-term outcomes.83 Definitively answering whether reducing treatment delays would prevent such negative outcomes requires long-term trials of aggressive outreach and treatment of new cases. Such trials are just beginning to be carried out.84-86
Despite the absence of definitive data from such long-term outreach treatment trials, the findings reported here suggest that more effort is needed to increase prompt initial treatment contacts among people with incident episodes of mental disorders. Additional large-scale public education programs (eg, the NIMH Depression, Awareness, Recognition, and Treatment program) and expanded use of National Screening Days continue to hold great promise for hastening detection and treatment.23,31,68 School-based screening programs using brief self-report and/or informant scales may be needed to detect early-onset mental disorders.87,88 Demand management and other outreach strategies could also help reduce critical delays and failures in initial help-seeking once mental disorders are identified.89,90 Training non–health care professionals to recognize individuals with mental disorders and make timely referrals for health care should also be explored.30,91,92 A range of interventions may ultimately be needed to alleviate the burdens and hazards from untreated mental disorders.
Correspondence: Philip S. Wang, MD, DrPH, 180 Longwood Ave, Boston, MA 02115 (wang@hcp.med.harvard.edu).
Submitted for Publication: June 9, 2004; final revision received October 15, 2004; accepted November 9, 2004.
Funding/Support: The National Comorbidity Survey Replication is supported by the National Institute of Mental Health (U01-MH60220), Rockville, Md; with supplemental support from the National Institute of Drug Abuse, the Substance Abuse and Mental Health Services Administration, Rockville, Md; the Robert Wood Johnson Foundation (grant 044708), Princeton, NJ; and the John W. Alden Trust, Boston, Mass.
Disclaimer: The views and opinions expressed in this report are those of the authors and should not be construed to represent the views of any of the sponsoring organizations, agencies, or the US government.
Additional Information: Collaborating investigators include Dr Kessler, principal investigator; Kathleen Merikangas, co-principal investigator, National Institute of Mental Health, Bethesda, Md; Dr Olfson; Dr Pincus; Dr Wang; Doreen Koretz, Harvard University, Cambridge, Mass; James Anthony, Michigan State University, East Lansing; William Eaton, Johns Hopkins University, Baltimore, Md; Meyer Glantz, National Institute on Drug Abuse, Baltimore, Md; Jane McLeod, Indiana University, Bloomington; Greg Simon and Michael Von Korff, Group Health Cooperative, Seattle, Wash; Kenneth Wells, University of California, Los Angeles; Elaine Wethington, Cornell University, Ithaca, NY; and Hans-Ulrich Wittchen, Institute of Psychology, Technical University, Dresden and Max Planck Institute of Psychiatry, Munich, Germany.
Acknowledgment: We thank Jerry Garcia, Sara Belopavlovich, Eric Bourke and Todd Strauss for assistance with manuscript preparation. A complete list of NCS publications and the full text of all NCS-R instruments can be found at www.hcp.med.harvard.edu/ncs. Send correspondence to ncs@hcp.med.harvard.edu. The NCS-R is carried out in conjunction with the WMH Survey Initiative. We thank the staff of the WMH Data Collection and Data Analysis Coordination Centres for assistance with instrumentation, fieldwork, and consultation on data analysis.
1.Regier
DANarrow
WERae
DSManderscheid
RWLocke
BZGoodwin
FK The de facto US mental and addictive disorders service system: epidemiologic catchment area prospective 1-year prevalence rates of disorders and services.
Arch Gen Psychiatry 1993;5085- 94
PubMedGoogle ScholarCrossref 2.Wang
PSBerglund
PKessler
RC Recent care of common mental disorders in the United States: prevalence and conformance with evidence-based recommendations.
J Gen Intern Med 2000;15284- 292
PubMedGoogle ScholarCrossref 3.Wang
PSDemler
OKessler
RC Adequacy of treatment for serious mental illness in the United States.
Am J Public Health 2002;9292- 98
PubMedGoogle ScholarCrossref 4.Kessler
RCBerglund
PDemler
OJin
RKoretz
DMerikangas
KRRush
AJWalters
EEWang
PS The epidemiology of major depressive disorder: results from the National Comorbidity Survey Replication (NCS-R).
JAMA 2003;2893095- 3105
PubMedGoogle ScholarCrossref 5.Wang
PSLane
MOlfson
MPincus
HAWells
KBKessler
RC Twelve-month use of mental health services in the United States: results from the National Comorbidity Survey Replication.
Arch Gen Psychiatry 2005;62629- 640
Google ScholarCrossref 6.Gallo
JJMarino
SFord
DAnthony
JC Filters on the pathway to mental health care, II: sociodemographic factors.
Psychol Med 1995;251149- 1160
PubMedGoogle ScholarCrossref 7.Rogler
LHCortes
DE Help-seeking pathways: a unifying concept in mental health care.
Am J Psychiatry 1993;150554- 561
PubMedGoogle Scholar 8.Joseph
AEBoeckh
JL Locational variation in mental health care utilization dependent upon diagnosis: a Canadian example.
Soc Sci Med 1981;15395- 440
PubMedGoogle Scholar 9.Leaf
PJLivingston
MMTischler
GLWeissman
MMHolzer
CEMyers
JK Contact with health professionals for the treatment of psychiatric and emotional problems.
Med Care 1985;231322- 1337
PubMedGoogle ScholarCrossref 10.Leaf
PJBruce
MLTischler
GL The differential effect of attitudes on use of mental health services.
Soc Psychiatry 1986;21187- 192
PubMedGoogle ScholarCrossref 11.Temkin-Greener
HClark
KT Ethnicity, gender, and utilization of mental health services in a Medicaid population.
Soc Sci Med 1988;26989- 996
PubMedGoogle ScholarCrossref 12.Leaf
PJBruce
MLTischler
GLFreeman
DHWeissman
MMMyers
JK Factors affecting the utilization of specialty and general medical mental health services.
Med Care 1988;269- 26
PubMedGoogle ScholarCrossref 13.Hu
TWSnowden
LRJerrell
JMNguyen
TD Ethnic populations in public mental health: services choice and level of use.
Am J Public Health 1991;811429- 1434
PubMedGoogle ScholarCrossref 14.Padgett
DKPatrick
CBurns
BJSchlesinger
HJ Ethnicity and use of outpatient mental health services in a national insured population.
Am J Public Health 1994;84222- 226
PubMedGoogle ScholarCrossref 15.Johnstone
ECCrow
TJJohnson
ALMacMillan
JF The Northwick Park study of first episodes of schizophrenia, I: presentation of the illness and problems relating to admission.
Br J Psychiatry 1986;148115- 120
PubMedGoogle ScholarCrossref 16.Loebel
ADLieberman
JAAlvir
JMJMayerhoff
DIGeisler
SHSzymanski
SR Duration of psychosis and outcome in first-episode schizophrenia.
Am J Psychiatry 1992;1491183- 1188
PubMedGoogle Scholar 17.Lincoln
CVMcGorry
P Who cares? Pathways to psychiatric care for young people experiencing a first episode of psychosis.
Psychiatr Serv 1995;461166- 1171
PubMedGoogle Scholar 18.Kessler
RCOlfson
MBerglund
PA Patterns and predictors of treatment contact after first onset of psychiatric disorders.
Am J Psychiatry 1998;15562- 69
PubMedGoogle Scholar 19.Olfson
MKessler
RCBerglund
PALin
E Psychiatric disorder onset and first treatment contact in the United States and Ontario.
Am J Psychiatry 1998;1551415- 1422
PubMedGoogle Scholar 20.Christiana
JMGilman
SEGuardino
MKessler
RCMickelson
KMorselli
PLOlfson
M Duration between onset and time of obtaining initial treatment among people with anxiety and mood disorders: an international survey of members of mental health patient advocate groups.
Psychol Med 2000;30693- 703
PubMedGoogle ScholarCrossref 21.Wang
PSBerglund
PAOlfson
MKessler
RC Delays in initial treatment contact after first onset of a mental disorder.
Health Serv Res 2004;39393- 415
PubMedGoogle ScholarCrossref 23.Regier
DAHirschfeld
RMGoodwin
FKBurke
JD
JrLazar
JBJudd
LL The NIMH Depression, Awareness, Recognition, and Treatment Program: structure, aim, and scientific basis.
Am J Psychiatry 1988;1451351- 1357
PubMedGoogle Scholar 25.Hirschfeld
RMKeller
MBPanico
SArons
BSBarlow
DDavidoff
FEndicott
JFroom
JGoldstein
MGorman
JMMarek
RGMaurer
TAMeyer
RPhillips
KRoss
JSchwenk
TLSharfstein
SSThase
MEWyatt
RJ The national depressive and manic-depressive association consensus statement on the undertreatment of depression.
JAMA 1997;277333- 340
PubMedGoogle ScholarCrossref 26.Olfson
MMarcus
SCDruss
BElinson
LTanielian
TPincus
HA National trends in the outpatient treatment of depression.
JAMA 2002;287203- 209
PubMedGoogle ScholarCrossref 27.Leucht
SPitschel-Walz
GAbraham
DKissling
W Efficacy and extrapyramidal side effects of the new antipsychotics olanzapine, quetiapine, risperidone, and sertindole compared to conventional antipsychotics and placebo: a meta-analysis of randomized controlled trials.
Schizophr Res 1999;3551- 68
PubMedGoogle ScholarCrossref 28.Schatzberg
AFedNemeroff
CBed Textbook of Psychopharmacology. Washington, DC American Psychiatric Publishing2004;
29.Rosenthal
MBBerndt
ERDonohue
JMFrank
RGEpstein
AM Promotion of prescription drugs to consumers.
N Engl J Med 2002;346498- 505
PubMedGoogle ScholarCrossref 30.Kessler
RCSoukup
JDavis
RBFoster
DFWilkey
SAVan Rompay
MMEisenberg
DM The use of complementary and alternative therapies to treat anxiety and depression in the United States.
Am J Psychiatry 2001;158289- 294
PubMedGoogle ScholarCrossref 31.Jacobs
DG National depression screening day: educating the public, reaching those in need of treatment and broadening professional understanding.
Harv Rev Psychiatry 1995;3156- 159
PubMedGoogle ScholarCrossref 32.Spitzer
RLKroenke
KWilliams
JBWThe Patient Health Questionnaire Study Group, Validation and utility of a self-report version of the PRIME-MD: the PHQ primary care study.
JAMA 1999;2821737- 1744
PubMedGoogle ScholarCrossref 33.Kessler
RCWang
PS Screening measures for behavioral health assessment. Hyner
GPeterson
KTravis
JDewey
JFoerster
JFramer
Eeds.
SPM Handbook of Health Assessment Tools. Pittsburgh, Pa Society for Prospective Medicine1999;33- 40
Google Scholar 34.Weissman
EPettigrew
KSotsky
SRegier
DA The cost of access to mental health services in managed care.
Psychiatr Serv 2000;51664- 666
PubMedGoogle ScholarCrossref 35.Sturm
R Tracking changes in behavioral health services: how have carve-outs changed care?
J Behav Health Serv Res 1999;26360- 371
PubMedGoogle ScholarCrossref 37.Williams
JW
JrRost
KDietrich
AJCiotti
MCZyzanski
SJCornell
J Primary care physicians' approach to depressive disorders: effects of physician specialty and practice structure.
Arch Fam Med 1999;858- 67
PubMedGoogle ScholarCrossref 38.Ridgely
MSGoldman
HH Mental health insurance. Rochefort
DAed.
Handbook on Mental Health Policy in the United States. Westport, Conn Greenwood Press1989;341- 361
Google Scholar 40.Kessler
RCBerglund
PABruce
MLKoch
JRLaska
EMLeaf
PJManderscheid
RWRosenheck
RAWalters
EEWang
PS The prevalence and correlates of untreated serious mental illness.
Health Serv Res 2001;36987- 1007
PubMedGoogle Scholar 41.Bender
E Better access to geriatric mental health care goal of new house bill.
Psychiatr News 2002;372- 5
Google Scholar 42.Kessler
RCMerikangas
KR The National Comorbidity Survey Replication (NCS-R): background and aims.
Int J Methods Psychiatr Res 2004;1360- 68
PubMedGoogle ScholarCrossref 43.Kessler
RCBerglund
PChiu
W-TDemler
OHeeringa
SHiripi
EJin
RPennell
B-EWalters
EEZaslavsky
AZheng
H The US National Comorbidity Survey Replication (NCS-R): design and field procedures.
Int J Methods Psychiatr Res 2004;1369- 92
PubMedGoogle ScholarCrossref 44.Kessler
RCBerglund
PDemler
OJin
RWalters
EE Lifetime prevalence and age-of-onset distributions of
DSM-IV disorders in the National Comorbidity Survey Replication.
Arch Gen Psychiatry 2005;62593- 602
Google ScholarCrossref 45.Kessler
RCUstun
TB The World Mental Health (WMH) survey initiative version of the World Health Organization (WHO) Composite International Diagnostic Interview (CIDI).
Int J Methods Psychiatr Res 2004;1393- 121
PubMedGoogle ScholarCrossref 46.World Health Organization, International Classification of Diseases (ICD-10). Geneva, Switzerland World Health Organization1991;
47.American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders, (DSM-IV). 4th ed. Washington, DC American Psychiatric Association1994;
48.First
MBSpitzer
RLWilliams
JBW Structured Clinical Interview for DSM-IV (SCID-I). New York, NY American Psychiatric Association1995;
49.Halli
SSRao
KVHalli
SS Advanced Techniques of Population Analysis. New York, NY Kluwer Academic Publishers1992;
50.SAS Institute, SAS/STAT Software: Changes and Enhancements, Release 8.2. Cary, NC SAS Publishing2001;
51.Kaplan
ELMeier
P Nonparametric estimation from incomplete observations.
J Am Stat Assoc 1958;53457- 481
Google ScholarCrossref 52.Efron
B Logistic regression, survival analysis, and the Kaplan-Meier curve.
J Am Stat Assoc 1988;83414- 425
Google ScholarCrossref 53.Wolter
KM Introduction to Variance Estimation. New York, NY Springer-Verlag1985;
54. SUDAAN [computer program]. Version 8.0.1. Research Triangle Park, NC Research Triangle Institute2002;
55.Kessler
RCWittchen
HUAbelson
JMZhao
S Methodological issues in assessing psychiatric disorder with self-reports. Stone
AATurrkan
JSBachrach
CAJobe
JBKurtzman
HSCain
VSeds.
The Science of Self-Report: Implications for Research and Practice. Mahwah, NJ Lawrence Erlbaum Associates2000;229- 255
Google Scholar 56.Pickles
APickering
KSimonoff
ESilberg
JMeyer
JMaes
H Genetic “clocks” and “soft” events: a twin model for pubertal development and other recalled sequences of developmental milestones, transitions, or ages at onset.
Behav Genet 1998;28243- 253
PubMedGoogle ScholarCrossref 57.Mojtabai
ROlfson
MMechanic
D Perceived need and help-seeking in adults with mood, anxiety, or substance use disorders.
Arch Gen Psychiatry 2002;5977- 84
PubMedGoogle ScholarCrossref 58.Kaskutas
LAWeisner
CCaetano
R Predictors of help seeking among a longitudinal sample of the general population 1984-1992.
J Stud Alcohol 1997;58155- 161
PubMedGoogle Scholar 61.Pincus
HAHough
LHoutsinger
JKRollman
BLFrank
RG Emerging models of depression care: multi-level ('6 P') strategies.
Int J Methods Psychiatr Res 2003;1254- 63
PubMedGoogle ScholarCrossref 62.Katerndahl
DARealini
JP Where do panic attack sufferers seek care?
J Fam Pract 1995;40237- 243
PubMedGoogle Scholar 64.Solomon
PGordon
B Outpatient compliance of psychiatric emergency room patients by presenting problems.
Psychiatr Q 1988;59271- 283
PubMedGoogle ScholarCrossref 65.Cartwright
WSSolano
PL The economics of public health: financing drug abuse treatment services.
Health Policy 2003;66247- 260
PubMedGoogle ScholarCrossref 66.Garland
AFAarons
GABrown
SAWood
PAHough
RL Diagnostic profiles associated with use of mental health and substance abuse services among high-risk youths.
Psychiatr Serv 2003;54562- 564
PubMedGoogle Scholar 67.Green-Hennessy
S Factors associated with receipt of behavioral health services among persons with substance dependence.
Psychiatr Serv 2002;531592- 1598
PubMedGoogle ScholarCrossref 68.Morrissey-Kane
EPrinz
RJ Engagement in child and adolescent treatment: the role of parental cognitions and attributions.
Clin Child Fam Psychol Rev 1999;2183- 198
PubMedGoogle ScholarCrossref 69.Janicke
DMFinney
JWRiley
AW Children's health care use: a prospective investigation of factors related to care-seeking.
Med Care 2001;39990- 1001
PubMedGoogle ScholarCrossref 70.Williams
JBSpitzer
RLLinzer
MKroenke
KHahn
SRdeGruy
FVLazev
A Gender differences in depression in primary care.
Am J Obstet Gynecol 1995;173654- 659
PubMedGoogle ScholarCrossref 71.Kessler
RCBrown
RLBroman
CL Sex differences in psychiatric help-seeking: evidence from four large-scale surveys.
J Health Soc Behav 1981;2249- 64
PubMedGoogle ScholarCrossref 72.Sellwood
WTarrier
N Demographic factors associated with extreme non-compliance in schizophrenia.
Soc Psychiatry Psychiatr Epidemiol 1994;29172- 177
PubMedGoogle Scholar 73.Wells
KBManning
WGDuan
NNewhouse
JPWare
JE
Jr Sociodemographic factors and the use of outpatient mental health services.
Med Care 1986;2475- 85
PubMedGoogle ScholarCrossref 74.Narrow
WERae
DSRobins
LNRegier
DA Revised prevalence estimates of mental disorders in the United States: using a clinical significance criterion to reconcile 2 surveys' estimates.
Arch Gen Psychiatry 2002;59115- 123
PubMedGoogle ScholarCrossref 75.Post
RMWeiss
SR Sensitization and kindling phenomena in mood, anxiety, and obsessive-compulsive disorders: the role of serotonergic mechanisms in illness progression.
Biol Psychiatry 1998;44193- 206
PubMedGoogle ScholarCrossref 76.Forthofer
MSKessler
RCStory
ALGotlib
IH The effects of psychiatric disorders on the probability and timing of first marriage.
J Health Soc Behav 1996;37121- 132
PubMedGoogle ScholarCrossref 77.Kessler
RCFoster
CLSaunders
WBStang
PE Social consequences of psychiatric disorders, I: educational attainment.
Am J Psychiatry 1995;1521026- 1032
PubMedGoogle Scholar 78.Kessler
RCBerglund
PAFoster
CLSaunders
WBStang
PEWalters
EE Social consequences of psychiatric disorders, II: teenage parenthood.
Am J Psychiatry 1997;1541405- 1411
PubMedGoogle Scholar 79.Kessler
RCWalters
EEForthofer
MS The social consequences of psychiatric disorders, III: probability of marital stability.
Am J Psychiatry 1998;1551092- 1096
PubMedGoogle Scholar 80.Meltzer
HYAlphs
LGreen
AIAltamura
ACAnand
RBertoldi
ABourgeois
MChouinard
GIslam
MZKane
JKrishnan
RLindenmayer
JPPotkin
S Clozapine treatment for suicidality in schizophrenia: International Suicide Prevention Trial (InterSePT).
Arch Gen Psychiatry 2003;6082- 91
PubMedGoogle ScholarCrossref 81.Kessler
RC The prevalence of psychiatric comorbidity. Wetzler
SSanderson
WCeds.
Treatment Strategies for Patients with Psychiatric Comorbidity. New York, NY John Wiley & Sons1997;
Google Scholar 83.Norman
RMMalla
AK Duration of untreated psychosis: a critical examination of the concept and its importance.
Psychol Med 2001;31381- 400
PubMedGoogle ScholarCrossref 84.MTA Cooperative Group, A 14-month randomized clinical trial of treatment strategies for attention-deficit/hyperactivity disorder, the MTA Cooperative Group: multimodal treatment study of children with ADHD.
Arch Gen Psychiatry 1999;561073- 1086
PubMedGoogle ScholarCrossref 85.Dierker
LCAlbano
AMClarke
GNHeimberg
RGKendall
PCMerikangas
KRLewinsohn
PMOfford
DRKessler
RKupfer
DJ Screening for anxiety and depression in early adolescence.
J Am Acad Child Adolesc Psychiatry 2001;40929- 936
PubMedGoogle ScholarCrossref 87.Connors
CK The Connors Rating Scales: use in clinical assessment, treatment planning and research. Maruish
Med.
Use of Psychological Testing for Treatment Planning and Outcome Assessment. Hillsdale, NJ Lawrence Erlbaum Associates1994;550- 578
Google Scholar 89.Carleton
RABazzarre
TDrake
JDunn
AFisher
EB
JrGrundy
SMHayman
LHill
MNMaibach
EWProchaska
JSchmid
TSmith
SC
JrSusser
MWWorden
JW Report of the Expert Panel on Awareness and Behavior Change to the Board of Directors, American Heart Association.
Circulation 1996;931768- 1772
PubMedGoogle ScholarCrossref 90.Velicer
WFHughes
SLFava
JLProchaska
JODiClemente
CC An empirical typology of subjects within stage of change.
Addict Behav 1995;20299- 320
PubMedGoogle ScholarCrossref 91.Wang
PSBerglund
PAKessler
RC Patterns and correlates of contacting clergy for mental disorders in the United States.
Health Serv Res 2003;38647- 673
PubMedGoogle ScholarCrossref 92.Weaver
AJ Has there been a failure to prepare and support parish-based clergy in their role as frontline community mental health workers: a review.
J Pastoral Care 1995;49129- 147
PubMedGoogle Scholar