Introduction
A substantial proportion of adults with common mental disorders fail to receive any treatment (Kessler et al. Reference Kessler, Demler, Frank, Olfson, Pincus, Walters, Wang, Wells and Zaslavsky2005c; President's New Freedom Commission on Mental Health, 2005; Wang et al. Reference Wang, Berglund, Olfson, Pincus, Wells and Kessler2005a, b, 2007 a; Sareen et al. Reference Sareen, Jagdeo, Cox, Clara, ten Have, Belik, de Graaf and Stein2007), even when these conditions are quite severe and disabling (Kessler et al. Reference Kessler, Berglund, Bruce, Koch, Laska, Leaf, Manderscheid, Rosenheck, Walters and Wang2001). Furthermore, many who do receive treatment drop out before completing treatment (Edlund et al. Reference Edlund, Unutzer and Curran2006; Wang, Reference Wang2007). Because individuals with psychiatric disorders would often benefit from a full course of treatment, the gap between the prevalence and treatment of disorders contributes to unmet need for care. An important step in reducing unmet need for mental health care involves understanding the reasons why individuals with mental disorders either do not seek treatment or drop out of care.
Several factors are thought to impede appropriate mental health care seeking, including lack of perceived need for treatment (Mojtabai et al. Reference Mojtabai, Olfson and Mechanic2002; Edlund et al. Reference Edlund, Unutzer and Curran2006; Sareen et al. Reference Sareen, Jagdeo, Cox, Clara, ten Have, Belik, de Graaf and Stein2007), stigma (van Voorhees et al. Reference van Voorhees, Fogel, Houston, Cooper, Wang and Ford2005, Reference van Voorhees, Fogel, Houston, Cooper, Wang and Ford2006; Wrigley et al. Reference Wrigley, Jackson, Judd and Komiti2005; Wynaden et al. Reference Wynaden, Chapman, Orb, McGowan, Zeeman and Yeak2005), pessimism regarding the effectiveness of treatments (Bayer & Peay, Reference Bayer and Peay1997), lack of access due to financial barriers (Mojtabai, Reference Mojtabai2005) and other structural barriers, such as inconvenience or inability to obtain an appointment (Sareen et al. Reference Sareen, Jagdeo, Cox, Clara, ten Have, Belik, de Graaf and Stein2007). The contribution of these factors, however, may vary across populations, health care settings (Sareen et al. Reference Sareen, Jagdeo, Cox, Clara, ten Have, Belik, de Graaf and Stein2007) and possibly over time (Mojtabai, Reference Mojtabai2005). In one recently published study, for example, low-income respondents from the US as compared with those from Ontario or the Netherlands were significantly more likely to report a financial barrier to mental health treatment (Sareen et al. Reference Sareen, Jagdeo, Cox, Clara, ten Have, Belik, de Graaf and Stein2007). Nevertheless, in all three settings, attitudinal/evaluative barriers were more commonly reported obstacles than financial factors (Sareen et al. Reference Sareen, Jagdeo, Cox, Clara, ten Have, Belik, de Graaf and Stein2007).
Within the United States, financial barriers to mental health treatment seeking may have grown over the past decade (Mojtabai, Reference Mojtabai2005). During this period, however, public attitudes towards mental health treatment seeking became more favorable (Mojtabai, Reference Mojtabai2007). These trends, coupled with a marked increase in the use of mental health care (Olfson et al. Reference Olfson, Marcus, Druss, Elinson, Tanielian and Pincus2002; Kessler et al. Reference Kessler, Demler, Frank, Olfson, Pincus, Walters, Wang, Wells and Zaslavsky2005c) call for a re-evaluation of reasons for not seeking treatment in the US. A better understanding of these barriers may inform the design of clinical services and public health campaigns aimed at improving access to mental health care.
In the present study, we use data from the National Comorbidity Survey Replication (NCS-R), a representative survey of the US population in the early 2000s, to examine barriers to initiation or continuation of treatment among individuals who meet criteria for a mental disorder. More specifically, we examine the role of perceived need as well as structural and attitudinal/evaluative barriers in treatment seeking and in dropping out of treatment among those who have already started treatment. We also examine and compare the role of these factors at different levels of clinical severity. Finally, we use multivariate models to examine associations between sociodemographic characteristics and severity of illness on the one hand and barriers to mental health treatment seeking, on the other.
Methods
Sample
The NCS-R is a nationally representative household survey of respondents aged ⩾18 years in the contiguous United States (Kessler et al. Reference Kessler, Berglund, Chiu, Demler, Heeringa, Hiripi, Jin, Pennell, Walters, Zaslavsky and Zheng2004, Reference Kessler, Berglund, Demler, Jin, Merikangas and Walters2005a). Face-to-face interviews were carried out with 9282 respondents between 5 February 2001 and 7 April 2003. Part I included a core diagnostic assessment and a service use questionnaire administered to all respondents. Part II (n=5962) assessed risk factors, correlates and additional disorders and was administered to all Part I respondents with lifetime disorders plus a probability subsample of other respondents. Because a number of disorders considered in rating severity level were asked only in Part II, the present analyses are limited to the Part II sample. This sample was appropriately weighted to adjust for the under-sampling of Part I respondents without any disorder. The overall response rate was 70.9%. NCS-R recruitment, consent and field procedures were approved by the Human Subjects Committees of Harvard Medical School and the University of Michigan.
Reasons for not using services or not continuing to use them
Respondents who reported no use of mental health services were asked whether there was a time in the past 12 months that they felt that they might have needed to see a professional for problems with their emotions, nerves or mental health. Those who answered affirmatively were then asked whether or not they endorsed each of a series of reason statements, about why they did not see a professional, from a list that included reasons involving low perceived need, structural barriers (e.g. lack of financial means, available treatments, personnel or transportation or the presence of other inconveniences) and attitudinal/evaluative barriers (e.g. the presence of stigma, low perceived efficacy of treatments or the desire to handle the problem on their own). These reason statements are based on similar statements used in the baseline NCS and earlier studies as well as on focus group interviews about barriers to seeking treatment carried out to expand these earlier lists. Respondents who reported that there was never a time in the past 12 months when they felt they might need help were not asked about reasons and were coded as having ‘low perceived need’ (Appendix A, available online).
Respondents who reported having seen a provider within the mental health specialty, general medical, human service or complementary–alternative medical sectors for help with emotional problems in the past 12 months were asked whether the treatment had stopped and, if so, whether they ‘quit before the [provider] wanted [them] to stop’. Those who answered affirmatively to both questions were then asked to endorse reasons for dropping out of treatment from a list of potential reason statements similar to the list of reasons for not seeking treatment (Appendix B, online). Only respondents who had stopped or quit all ongoing treatments were rated as having dropped out and asked questions about the reasons for dropping out of treatment. Those who continued treatment with providers in one sector while stopping treatment with any providers in other sectors were not rated as having dropped out of treatment. The 160 respondents who reported taking psychotropic medications for their emotional problems at any time in the past year, but reported no contacts with a treatment provided over that time period, were not counted as having received mental health treatment in the past 12 months even though some of them were presumably in long-term treatment and others made their last visit shortly before the beginning of the 12-month recall period (e.g. 13 months ago) and continued taking medications into the early part of that recall period. As we did not ask questions about treatment beyond the 12-month recall period, we had no way of classifying the treatment of these 160 respondents, leading us to delete them from the analysis.
Diagnostic assessment
DSM-IV diagnoses were based on version 3.0 of the Composite International Diagnostic Interview (CIDI) (Kessler & Üstün, Reference Kessler and Üstün2004), a fully structured lay interview that generates diagnoses according to International Classification of Diseases, 10th Revision (WHO, 1992) and DSM-IV (APA, 1994) criteria. The analyses were restricted to respondents with at least one 12-month CIDI/DSM-IV disorder. The 12-month disorders included anxiety disorders (panic disorder, generalized anxiety disorder, agoraphobia without panic disorder, specific phobia, social phobia, post-traumatic stress disorder, obsessive–compulsive disorder, separation anxiety disorder), mood disorders (major depressive disorder, dysthymic disorder, bipolar disorder I or II), impulse control disorders (oppositional defiant disorder, conduct disorder, attention deficit/hyperactivity disorder, intermittent explosive disorder) and substance use disorders (alcohol and drug abuse and dependence). The disorders assessed in Part 2 include the four childhood disorders (separation anxiety disorder, oppositional defiant disorder, conduct disorder and attention deficit/hyperactivity disorder), post-traumatic stress disorder, obsessive–compulsive disorder and the substance use disorders. As described elsewhere (Kessler et al. Reference Kessler, Berglund, Demler, Jin, Merikangas and Walters2005a), blind clinical re-interviews using the Structured Clinical Interview for DSM-IV (SCID) (First et al. Reference First, Spitzer, Gibbon and Williams2002) with a probability subsample of NCS-R respondents found generally good concordance between WMH-CIDI diagnoses and SCID diagnoses. The above disorders were the only ones assessed in the survey. Exclusion of other disorders of clinical interest (e.g. non-affective psychosis, dementia, personality disorders) is a limitation.
Level of severity
The 12-month cases were classified as serious if they had any of the following: a 12-month suicide attempt with serious lethality intent; work disability or substantial limitation due to a mental or substance disorder; positive screen results for non-affective psychosis; bipolar I or II disorder; substance dependence with serious role impairment, as defined by scores in the ‘severe’ or ‘very severe’ range on disorder-specific versions of the Sheehan Disability Scale (Leon et al. Reference Leon, Olfson, Portera, Farber and Sheehan1997); an impulse control disorder with repeated serious violence; or any disorder that resulted in ⩾30 days out of role in the last year. Cases not defined as serious were defined as moderate if they had any of the following: suicide gesture, plan or ideation; substance dependence without serious role impairment; at least moderate work limitation due to a mental or substance disorder; or any disorder with at least ‘moderate’ role impairment in two or more domains of the Sheehan Disability Scale. All other cases were classified as mild. As reported elsewhere (Kessler et al. Reference Kessler, Chiu, Demler, Merikangas and Walters2005b), mean number of days in the past 12 months that respondents were completely unable to carry out their normal daily activities because of mental or substance use problems was 88.3 among respondents classified as having a serious condition, 4.7 among those classified as having a moderate condition and 1.9 among those classified as having a mild condition (F 2,5689=17.7, p<0.001).
Sociodemographic predictor variables
Sociodemographic variables included age (18–34, 35–49, 50–64, ⩾65 years), sex, race–ethnicity (non-Hispanic white, Hispanic, non-Hispanic black, other), years of education (0–11, 12, 13–15, ⩾16), family income in relation to the federal poverty level (Proctor & Dalaker, Reference Proctor and Dalaker2001) [low (⩽1.5 times the poverty line), low average (>1.5–3.0 times the poverty line), high average (>3.0–6.0 times the poverty line), high (⩾6.0 times the poverty line)] and marital status (married/cohabitating, separated/widowed/divorced, never married).
Analysis methods
The NCS-R data were weighted to adjust for differences in selection probabilities, differential non-response and residual differences between the sample and the US population on sociodemographic variables. An additional weight was used in the Part 2 sample to adjust for the over-sampling of Part 1 respondents (Kessler et al. Reference Kessler, Berglund, Chiu, Demler, Heeringa, Hiripi, Jin, Pennell, Walters, Zaslavsky and Zheng2004). All descriptive statistics are based on these weighted data. Analyses of reasons for not initiating treatment or continuing treatment were conducted in three stages. First, reasons were examined and compared in the total group of respondents with any 12-month disorder as well as separately in subgroups defined by severity. Second, analyses of reasons other than those involving lack of need were repeated among respondents who reported perceived need for treatment. Third, multivariate logistic regression models were used to examine variation in reasons for not seeking treatment associated with sociodemographic characteristics and severity of illness. Three main effect models were estimated, one for each of the three broad categories of reasons (low perceived need, any structural barrier, any attitudinal/evaluative barrier). These multivariate analyses were then repeated with the addition of interaction terms between severity and each sociodemographic characteristic to examine whether the association of each sociodemographic factor with each type of barrier was uniform regardless of level of severity. Logistic regression coefficients and their standard errors were exponentiated and reported as odds ratios (OR) and 95% confidence intervals (CI).
Standard errors were calculated using the Taylor series method implemented in the SUDAAN software package (Research Triangle Institute, Reference Petrou, Murray, Cooper and Davidson2002) to adjust for clustering and weighting of data. Multivariate significance tests were conducted using Wald χ2 tests based on coefficient variance–covariance matrices adjusted for design effects using the Taylor series method. Statistical significance was evaluated using two-sided design-based tests and the p<0.05 level of significance. Only when multivariate significance tests were significant did we interpret the significance of individual coefficients. This decision rule was used to guard against the possibility of false positive coefficients in an analysis that made a large number of individual tests. It is important to note, however, that although use of omnibus tests reduces the chance of false positive findings, the only definitive protection against this problem is replication in independent datasets.
Results
Reasons for not seeking treatment
Somewhat more than half (55.2%) of the 1350 Part II NCS-R respondents who met criteria for at least one 12-month DSM-IV/CIDI disorder but did not use any 12-month services reported that they might have needed to see a professional for mental health problems. This perception of need was significantly associated with severity of psychopathology (χ32=52.0, p<0.001), with 74.1% of non-users who had a severe disorder reporting perceived need compared with 60.7% of those who had a moderately severe disorder and 43.0% of those who had a mild disorder. Low perceived need was the most commonly reported barrier to treatment across levels of severity (Table 1). Over and above the effects of global measures of disorder severity, generalized anxiety disorder was the only individual disorder that predicted perceived need significantly, with an OR of 1.8 (95% CI 1.1–2.9, p=0.020). Among respondents who recognized a need for treatment, in comparison, the desire to handle the problem on one's own was the most commonly reported reason for not seeking treatment (72.6%), while attitudinal/evaluative barriers were much more commonly reported (97.4%) than structural barriers (22.2%). Reported reasons for not seeking treatment varied significantly across severity levels, with low perceived need more commonly reported by respondents with mild than moderate or severe disorders compared with structural and most attitudinal/evaluative barriers being reported by a higher proportion of respondents with perceived need who had severe or moderate than mild conditions.
Table 1. Reported reasons for not seeking treatment by level of severity of disorder among respondents with 12-month DSM-IV disorders who did not seek treatment at any time in the past 12 months
* Significant at the 0.05 level, two-sided test.
The joint effects of sociodemographic variables and severity were significant as a set in predicting both low perceived need (χ172=159.9, p<0.001) and structural barriers among respondents with perceived need (χ172=53.6, p<0.001) but not attitudinal/evaluative barriers among respondents with perceived need (χ172=9.9, p=0.54). (Table 2) The failure to find significant predictors of attitudinal/evaluative barriers presumably reflects the fact that virtually every respondent with perceived need reported at least one such barrier (97.4%; detailed results for this model can be found in Appendix C, online). Age (⩾65 compared with 18–64 years), sex (males compared with females), education (0–11 v. ⩾16 years) and severity (mild versus moderate-severe) were significant predictors of low perceived need. Age (18–49 v. ⩾50 years) and severity (severe versus mild-moderate) were significant predictors of structural barriers.
Table 2. Sociodemographic and severity predictors of reported reasons for not seeking treatment among respondents with 12-month DSM-IV disorders who did not seek treatment at any time in the past 12 monthsFootnote a
OR, Odds ratio; CI, confidence interval.
a Based on multivariate logistic regression models controlling for number of 12-month mood, anxiety, substance, and externalizing disorders. A comparable model to predict attitudinal/evaluative barriers found no significant predictors. Results are available on request.
b The reference category was collapsed due to the small number of respondents in the cells.
* Significant at the 0.05 level, two-sided test.
We also evaluated interactions between each sociodemographic variable and severity in predicting perceived need and structural barriers. The 30 interactions (15 sociodemographic variables×two severity variables) were significant as a set in each of the two equations (χ302=74.1, p<0.001 predicting perceived need and χ302=163.0, p<0.001 predicting structural barriers), although none of the more specific interactions between individual sociodemographics and severity was significant in predicting perceived need. Two of these specific interactions were significant, however, in predicting structural barriers. These involved race–ethnicity (χ32=25.7, p<0.001) and marital status (χ22=9.5, p=0.023). (Detailed results are available in Appendix D, online.) In the case of race–ethnicity, the elevated OR of structural barriers among Hispanics compared with Non-Hispanic whites was found to be confined to mild-moderate cases. In the case of marital status, married/cohabiting respondents were found to have a significantly elevated OR of structural barriers compared with the never married among mild cases but not moderate-severe cases.
Reasons for dropping out of treatment
A total of 851 respondents with 12-month disorders reported receiving treatment at some time in the past 12 months, of whom a weighted 10.6% (n=78 actual respondents) reported dropping out of treatment in all service sectors where they received treatment. Wanting to handle the problem on one's own was the most commonly reported reason for dropping out of treatment (42.2%), followed by perceived improvement in mental health (31.2%) (Table 3). Although disorder severity was not significantly related to any of the reported reasons for drop-out (χ22=0.5–5.6, p=0.06–0.78), respondents with severe disorders reported a significantly higher mean number of reasons (2.3) than those with moderately severe (2.0) or mild (1.3) disorders (F 2,848=7.1, p=0.002). In multivariate analyses (data not shown but available in Appendix E, online), a standardized continuous measure of income was the only significant sociodemographic predictor of reporting attitudinal/evaluative barriers. This association was negative (OR 0.2, 95% CI 0.1–0.7; χ12=7.5, p=0.006) and persisted when the sample was limited to respondents who perceived a need for continued treatment (OR 0.1, 95% CI 0.0–0.4, χ12=8.6, p=0.003).
Table 3. Reported reasons for dropping out of treatment by level of severity of disorder among respondents with 12-month DSM-IV disorders dropped out of treatment in the past 12 months
Conclusion
This study had several noteworthy limitations. First, results are subject to recall bias because disorders, treatments and reasons were all assessed retrospectively over a 12-month recall period with self-report. It is noteworthy in this regard that self-reports of service use tend to underestimate service use reported in administrative records (Jobe et al. Reference Jobe, White, Kelley, Mingay, Sanchez and Loftus1990; Clark et al. Reference Clark, Ricketts and McHugo1996; Kashner et al. Reference Kashner, Suppes, Rush and Altshuler1999; Ritter et al. Reference Ritter, Stewart, Kaymaz, Sobel, Block and Lorig2001; Petrou et al. Reference Petrou, Murray, Cooper and Davidson2002), although the underestimation of more recent service use tends to be modest (Clark et al. Reference Clark, Ricketts and McHugo1996; Petrou et al. Reference Petrou, Murray, Cooper and Davidson2002). Second, the list of reasons for not seeking treatment and drop-out was limited to those reported most commonly in past research and elicited in qualitative interviews carried out to expand these earlier lists. Some individuals may have had other reasons for not initiating treatment or dropping out that were not included in our lists. In addition, some reason statements were ambiguous or double-barreled (e.g. ‘The problem went away by itself, and I did not really need help’) and were aggregated into rational categories in ways that could be debated. Furthermore, the reliability of self-reports of reasons for not seeking treatment has not been assessed. Third, with regard to reasons involving severity and change in severity (problem was not severe; problem went away), the analysis was limited by not having information on duration, which was almost certainly related to these reports and would be expected to be a strong predictor of seeking treatment.
Another weakness is that the analysis of treatment drop-out had low power due to the small number of respondents defined as having dropped out of treatment. This may have been due to the stringent definition of drop-out that we used, which classified respondents as having dropped out only if they dropped out of treatment from all sectors in which they obtained treatment. A total of 81 respondents with a 12-month DSM-IV disorder dropped out of one or more types of treatments but stayed in some other type of treatment. We did not classify these respondents as having dropped out, based on the fact that some number of them were presumably referred to a new treatment provider by their original provider or switched rather than dropped out of treatment. These 81 respondents did not differ significantly with regard to severity from those who stayed in the same type of treatment, but both groups were more severe than those who we defined as having dropped out. Given that this group is relatively large, it would be useful for future research to evaluate reasons for switching treatments among respondents of this type.
A final noteworthy limitation is that respondents who reported 12-month service use in one of the disorder-specific diagnostic sections but not in the general service section were not included in the analysis. There were 149 such individuals. These respondents were inconsistent in their reports, making it difficult to know how to classify them. Had we been aware of this inconsistency at the time of designing the interview, we could have included these cases by placing the general services section later in the interview and including respondents who reported disorder-specific treatment. It would be fairly easy to correct this problem in future surveys. Similar inconsistencies between reports of service use when assessed globally versus separately after assessing each condition have been reported in other surveys (Duan et al. Reference Duan, Alegria, Canino, McGuire and Takeuchi2007).
In the context of these limitations, the data provide a broad overview of perceived barriers to initiation and continuation of mental health treatments in the United States. Three patterns are especially noteworthy. First, low perceived need for treatment was a common reason for not seeking treatment, with attitudinal/evaluative reasons much more common than structural barriers among people with perceived need. This pattern is consistent with previous findings from the US and other settings in the 1990s (Sareen et al. Reference Sareen, Jagdeo, Cox, Clara, ten Have, Belik, de Graaf and Stein2007) and suggests that low perceived need has remained a key barrier to seeking treatment for mental disorders.
Second, reasons for not seeking treatment varied significantly across levels of illness severity, with respondents who had more severe disorders being significantly less likely to report low perceived need as a barrier and significantly more likely to report structural and attitudinal/evaluative barriers than people with less severe disorders. These findings are consistent with findings from past research on the association of severity of illness with barriers to seeking treatment for mental disorders (Wang et al. Reference Wang, Gruber, Powers, Schoenbaum, Speier, Wells and Kessler2007b; Drapalski et al. Reference Drapalski, Milford, Goldberg, Brown and Dixon2008). The disjunction between perceived need and our measure of severity highlights the fact that personal evaluations of perceived need do not fully capture objectively measured need. Notably, over one-quarter of respondents with severe psychopathology did not perceive a need for treatment and one in four of those who did perceive a need reported that they thought that the problem was not severe or that it would get better on its own. Furthermore, two-thirds of respondents with severe disorders who perceived a need for treatment and did not seek treatment, and more than one-half of respondents who dropped out, reported a wish to handle their problems on their own as a reason for not seeking treatment or dropping out. These results are consistent with an extensive clinical literature documenting a significant association between illness insight and treatment acceptance/adherence among patients with serious mental illness (Buckley et al. Reference Buckley, Wirshing, Bhushan, Pierre, Resnick and Wirshing2007). Results such as these point to the importance of efforts to educate the public at large as well as patients about indicators of serious psychopathology and appropriate treatment options (Paykel et al. Reference Paykel, Tylee, Wright, Priest, Rix and Hart1997; Hickie, Reference Hickie2004; Jorm et al. Reference Jorm, Christensen and Griffiths2005, Reference Jorm, Christensen and Griffiths2006; Highet et al. Reference Highet, Luscombe, Davenport, Burns and Hickie2006).
Third, over one-third of respondents who dropped out of treatment cited an attitudinal/evaluative barrier, such as stigma, negative experience with providers or perceived ineffectiveness of treatment, that show low perceived treatment quality leads to treatment drop-out. It is sadly ironic that among those who dropped out of treatment, patients with severe psychopathology were more likely than those with less severe disorders (albeit at a statistically insignificant level) to report attitudinal/evaluative obstacles to treatment, as those with the most severe conditions are likely to be in greatest need for treatment and potentially stand to benefit most from care. This finding points to the need to improve quality of mental health services for adults with severe mental disorders in the United States to better address the individual needs and preferences of this patient group (Adams & Drake, Reference Adams and Drake2006).
It is also noteworthy that the reasons for not seeking treatment differed by respondent sociodemographic characteristics. Most notably, young and middle-aged adults were less likely than older adults to report a lack of perceived need for treatment but more likely to report structural and attitudinal/evaluative barriers to treatment seeking after they perceived a need. The effect of age may partly be explained by differences in access to care and life-style. Respondents aged ⩾65 years typically are covered by a Medicare financed health plan and are more likely than younger people to be retired. Thus, they may be less likely than their younger peers to experience financial and time barriers to seeking treatment. Furthermore, younger people tend to have a less positive attitude toward mental health treatment seeking, although this pattern has been changing in recent years (Mojtabai, Reference Mojtabai2007).
Females compared with males and respondents with low compared with high education were less likely to report lack of perceived need as a reason for not seeking treatment. While past research generally supports an association between female sex and greater perceived need for mental health treatment (Meadows et al. Reference Meadows, Burgess, Bobevski, Fossey, Harvey and Liaw2002; Sareen et al. Reference Sareen, Belik, Stein and Asmundson2010), the association with education is puzzling and may suggest that formal education by itself does not significantly promote recognition of mental health care needs. The finding that married/cohabiting respondents had an elevated OR of reporting structural barriers, but only among mild cases, might reflect the fact that married people have more family responsibilities than single people, which place demands on their time and financial resources, thereby creating barriers to seeking treatment that are only overcome when disorders become relatively serious. The finding that high income was associated with low odds of dropping out of treatment for attitudinal/evaluative reasons is consistent with earlier reports that high income is associated with positive attitudes toward mental health treatment (Mojtabai, Reference Mojtabai2007). This might be due to a higher quality of services accessible to individuals from higher income groups or more attitudes related to more general perceptions of medical care.
The results reported here reinforce other evidence that low rates of seeking treatment for common mental disorders remains a major public health problem in the United States (Gonzalez et al. Reference Gonzalez, Vega, Williams, Tarraf, West and Neighbors2010). The President's New Freedom Commission on Mental Health (2005) recommended a campaign to improve treatment seeking by reducing the stigma associated with mental disorders and their treatments. The 2008 Mental Health Parity legislation has also sought to reduce financial barriers to accessing such treatments. The results of the current study show, consistent with these recommendations, that both attitudinal/evaluative and structural barriers are significant impediments to treatment seeking in the US. However, we also found that low perceived need is an even more important barrier. This might well reflect the fact that most of the mental disorders considered here are extreme variants on normal patterns of emotion, cognition and behavior that are difficult for many people to see as distinct from the normal patterns. Our results suggest that new public education initiatives are needed to increase recognition of mental illness in conjunction with the efforts currently underway to reduce stigma and financial barriers.
Note
Supplementary material accompanies this paper, available at: www.hcp.med.harvard.edu/ncs/publications.php.
Acknowledgments
The NCS-R is supported by the National Institute of Mental Health (NIMH; U01-MH60220) with supplemental support from the National Institute on Drug Abuse (NIDA), the Substance Abuse and Mental Health Services Administration (SAMHSA), the Robert Wood Johnson Foundation (RWJF; Grant 044780) and the John W. Alden Trust. Collaborating NCS-R investigators include R. C. Kessler (principal investigator, Harvard Medical School), K. Merikangas (co-principal investigator, NIMH), J. Anthony (Michigan State University), W. Eaton (The Johns Hopkins University), M. Glantz (NIDA), D. Koretz (Harvard University), J. McLeod (Indiana University), M. Olfson (New York State Psychiatric Institute, College of Physicians and Surgeons of Columbia University), H. Pincus (University of Pittsburgh), G. Simon (Group Health Cooperative), M. von Korff (Group Health Cooperative), P. S. Wang (NIMH), K. Wells (UCLA), E. Wethington (Cornell University) and H.-U. Wittchen (Max Planck Institute of Psychiatry; Technical University of Dresden). 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 US Government. A complete list of NCS publications and the full text of all NCS-R instruments can be found at http://www.hcp.med.harvard.edu/ncs (send correspondence to ncs@hcp.med.harvard.edu).
The NCS-R is carried out in conjunction with the World Health Organization World Mental Health (WMH) Survey Initiative. We thank the staff of the WMH Data Collection and Data Analysis Coordination Centers for assistance with instrumentation, fieldwork and consultation on data analysis. These activities were supported by the National Institute of Mental Health (R01 MH070884), the John D. and Catherine T. MacArthur Foundation, the Pfizer Foundation, the US Public Health Service (R13-MH066849, R01-MH069864, and R01 DA016558), the Fogarty International Center (FIRCA R03-TW006481), the Pan American Health Organization, Eli Lilly and Company, Ortho-McNeil Pharmaceutical, Inc., GlaxoSmithKline, and Bristol-Myers Squibb. A complete list of WMH publications can be found at http://www.hcp.med.harvard.edu/wmh/
Declaration of Interest
During the past 3 years, Dr Olfson has received research funding from Eli Lilly & Company, Ortho-McNeil Pharmaceuticals, Bristol–Myers Squibb and AstraZeneca Pharmaceuticals. He has also served as a consultant for Eli Lilly & Company, Pfizer, Janssen and AstraZeneca Pharmaceuticals. Dr Druss has worked as a consultant for Pfizer, Inc. Dr Kessler has been a consultant for AstraZeneca, Analysis Group, Bristol–Myers Squibb, Cerner-Galt Associates, Eli Lilly & Company, GlaxoSmithKline Inc., HealthCore Inc., Health Dialog, Integrated Benefits Institute, John Snow Inc., Kaiser Permanente, Matria Inc., Mensante, Merck & Co, Inc., Ortho-McNeil Janssen Scientific Affairs, Pfizer Inc., Primary Care Network, Research Triangle Institute, Sanofi-Aventis Groupe, Shire US Inc., SRA International, Inc., Takeda Global Research & Development, Transcept Pharmaceuticals Inc. and Wyeth-Ayerst; has served on advisory boards for Appliance Computing II, Eli Lilly & Company, Mindsite, Ortho-McNeil Janssen Scientific Affairs and Wyeth-Ayerst; and has had research support for his epidemiological studies from Analysis Group Inc., Bristol–Myers Squibb, Eli Lilly & Company, EPI-Q, GlaxoSmithKline, Johnson & Johnson Pharmaceuticals, Ortho-McNeil Janssen Scientific Affairs., Pfizer Inc., Sanofi-Aventis Groupe and Shire US, Inc.
Dr Pincus has provided details regarding the source of support for research and any consulting arrangements or sources of support for the past 3 years that may represent a potential conflict interest.
I am currently employed by (all not for profit): Columbia University, New York-Presbyterian Hospital, RAND Corporation, University of Pittsburgh/UPMC (Employer to 6/2006).
My research has been funded by the following organizations (all not for profit): National Institute of Mental Health, National Institute of Child Health and Human Development, National Institute on Drug Abuse, Substance Abuse and Mental Health Services Administration/Center for Substance Abuse Treatment/Center for Mental Health Services, Veterans Administration, The Robert Wood Johnson Foundation, The John A. Hartford Foundation, Raymond John Wean Foundation, The Heinz Endowments, Atlantic Philanthropies, National Institute for Research Resources, MacArthur Foundation, UPMC Health Plan, The Highmark Foundation, Staunton Farm Foundation, FISA Foundation, The Eden Hall Foundation, Centers for Medicare and Medicaid Services, AHRQ, World Health Organization.
Any commercial or financial involvements within the past 3 years that might present an appearance of a conflict of interest (e.g. institutional or corporate affiliations, paid consultancies, stock ownership or other equity interests, patent ownership, royalties, funds for travel and interests in patents, instruments, and technologies) are as follows:
In the past 3 years, I have been a consultant for: University of Washington, University of New Mexico, SUNY Stony Brook, Community Care Behavioral Health Organization/UPMC Health Plan, Magellan Health Care, Urban Institute, Value Options (travel only).
I have received royalties for publications (none of which involved specific products) from: American Psychiatric Press, Current Opinion in Psychiatry/Lippincott, William and Wilkins.
I have received payments for speaking (none of which involve specific products) from: Bimark Medical Education, Comprehensive NeuroScience, Inc., Medical Information Technologies, Cardinal Health Inc., Health Partners, American Medical Association.
