Psychiatric Rehabilitation Journal 2015, Vol. 38, No. 4, 293–299
© 2015 American Psychological Association 1095-158X/15/$12.00 http://dx.doi.org/10.1037/prj0000113
Sociodemographic Disparities Associated With Perceived Causes of Unmet Need for Mental Health Care Sirry M. Alang
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University of Minnesota School of Public Health Objective: Mental disorders are among the leading causes of disability in the United States. In 2011, over 10 million adults felt that even though they needed treatment for mental health problems, they received insufficient or no mental health care and reported unmet need. This article assesses associations between sociodemographic characteristics and perceived causes of unmet needs for mental health care. Method: A sample of 2,564 adults with unmet mental health need was obtained from the National Survey on Drug Use and Health. Outcome variables were 5 main reasons for unmet need: cost, stigma, minimization, low perceived treatment effectiveness, and structural barriers. Each cause of unmet need was regressed on sociodemographic, health, and service use characteristics. Women had higher odds of cost-related reasons for unmet need than men. Odds of stigma and structural barriers were greater among Blacks than Whites, and among rural than metropolitan residents. Compared with the uninsured, insured persons were less likely to report cost barriers. However, insured persons had higher odds of stigma and minimization of mental disorders. Conclusions and Implications for Practice: Insurance alone is unlikely to resolve the problem of unmet need. Understanding the social epidemiology of perceived unmet need will help identify populations at risk of not receiving mental health care or insufficient care. Focusing on specific programs and services that are designed to address the causes of perceived unmet need in particular populations is important. Future research should explore how intersecting social statuses affect the likelihood of perceived unmet need. Keywords: unmet need, mental health disparities, access to mental health care, perceived need for mental health care
White, Blacks and Hispanics are less likely to have access to mental health care and more likely to report delayed or insufficient care (Alegría et al., 2008; Wells, Klap, Koike, & Sherbourne, 2001). Studies also find high probabilities of reporting unmet need among uninsured persons, poor working age adults, persons with chronic conditions, individuals with poor physical health, and among persons with mental health and substance use problems (Mojtabai, 2009; Mojtabai et al., 2011; Roll, Kennedy, Tran, & Howell, 2013; Wang et al., 2005). Although evidence points to cost and stigma as the most common reasons for unmet mental health needs (Corrigan, 2004; Mojtabai, 2005; Mojtabai et al., 2011), research has yet to assess whether cost, stigma, and other causes of unmet need vary sociodemographically. Passage of the Patient Protection and Affordable Care Act (ACA) is expected to reduce cost/affordability barriers to mental health care in states that expand Medicaid, through the inclusion of mental and behavioral treatment in the essential health benefits (EHB) for health exchanges, and by expanding mental health parity. Even after the implementation of the ACA, residual cost barriers are likely to exist. This is true for states that opt out of Medicaid expansion, undocumented immigrants who already encounter access barriers to health care, and persons unable to afford the cost of premiums in the exchanges, and who fall in the cracks between Medicaid and employer-sponsored health insurance (Jacobs, 2013; Nardin et al., 2013; Sommers, 2013). Other more comprehensive behavioral health services that might reduce perceived need but that have limited financing under provisions in the ACA include supportive employment and housing (Goldman &
Mental disorders are among the leading causes of disability in the United States, and 1 in 17 adults has a severe debilitating mental illness in any given year (Kessler, Chiu, Demler, Merikangas, & Walters, 2005). According to the Substance Abuse and Mental Health Services Administration (SAMHSA), over 10 million adults age 18 or older in the general U.S. population felt that even though they needed treatment for their mental health problems, they received insufficient or no mental health care—reporting unmet mental health needs in 2011. This article explores reasons for unmet need and examines whether there are sociodemographic disparities in reported causes of unmet need for professional mental health services. Identifying how causes of unmet need vary across populations will inform policies that address disparities in access to and utilization of mental health services, ultimately reducing rates of untreated mental illness. Although advances in treatment have the potential to improve the ability of persons with even the most severe mental illnesses to manage their symptoms such that they can lead productive lives, sociodemographic disparities and health status differences in unmet need for mental health services persist. For example, data from national surveys in the United States suggest that those who are
This article was published Online First February 9, 2015. Correspondence concerning this article should be addressed to Sirry M. Alang, Division of Health Policy and Management, University of Minnesota School of Public Health, 420 Delaware Street SE, Minneapolis, MN 55455. E-mail: [email protected] 293
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Karakus, 2014; Hogan, Drake, & Goldman, 2014). Regardless of the ACA, challenges that result from lack of evidence around organization and delivery of pharmaceutical versus more psychosocial treatment services (Mechanic, 2014), and the lack of infrastructure for care delivery can increase barriers to mental health care within certain populations (Croft & Parish, 2013; Cummings, Wen, & Druss, 2013). In addition to the residual cost-related reason for unmet need as well infrastructural and organizational barriers to the delivery of mental health services, other significant causes of unmet need for mental health care exist. The main objective of this article is to examine whether there are sociodemographic disparities in reasons for perceived unmet need for mental health care among U.S. adults. It assesses whether race/ethnic, sex, age, income, education, and regional disparities exist in each of five general reasons for not receiving needed mental health services. These reasons are identified by SAMHSA as: cost/affordability, stigma, minimization of symptoms or low perceived need, low perceived effectiveness of treatment, and structural barriers (SAMHSA, 2013). Pinpointing group differences in the likelihood of reporting specific causes of unmet need will facilitate efforts to monitor and address untreated mental illness. It will also increase our current understanding of disparities in unmet need, and inform policies to reduce the burden of untreated and undertreated mental illness across different sociodemographic groups.
Method Data Cross-sectional data came from the 2011 sample of the National Survey on Drug Use and Health (NSDUH). Public-use data were obtained from the Interuniversity Consortium for Political and Social Research (ICPSR). Annually, the NSDUH collects data on the civilian, noninstitutionalized population of the United States, age 12 or older, using a multilevel stratified hierarchical sampling procedure. The response rate for the 2011 survey was 74·4%, with a sample of 70,109 persons representing the U.S. population age 12 or older. Because of the focus on adults, persons aged 12–17 (23,510) were dropped from the sample. The final analytic sample (N ⫽ 2,564) was limited to adults 18 or older who also reported unmet need for mental health services. To establish unmet need, adult respondents were asked whether at any time in the past 12 months, they perceived a need for mental health treatment or counseling but did not receive these services.
Measures The five dependent variables are: cost, stigma, minimization, low perceived treatment effectiveness, and structural barriers. All dependent variables are binary measures (1/0) indicating whether or not the reason was cited by the respondent. In the NSDUH, respondents who perceived need for mental health treatment or counseling but did not receive services were further asked to specify reasons for not receiving mental health services. SAMHSA has grouped reported reasons into five main categories (SAMHSA, 2013). (a) Cost indicates that respondents selected at least one of the following as reasons for unmet need: could not afford costs, health insurance does not cover any mental health treatment/
counseling, and health insurance does not pay enough for mental health treatment/counseling. (b) Stigma indicates that respondents selected at least one of the following reasons: might cause neighbors/community to have a negative opinion, might have negative effect on job, did not want others to find out, concerned about confidentiality, and concerned about being committed/having to take medications. (c) Minimization indicates that respondents either did not feel the need for treatment at the time or thought they could handle the problem without treatment. (d) Low perceived treatment effectiveness indicates that respondents did not receive treatment because they did not think services would help. (e) Structural barriers indicate that respondents cited at least one of the following reasons for unmet need: no transportation/inconvenient, did not know where to go for services, and did not have time. Independent variables include race (non-Hispanic White, nonHispanic Black, Hispanic, and all others), age (18 –25, 26 –34, 35, and older), sex, marital status (married, all others), education (less than High School, completed High School, some college, college degree or higher), region (large metro, small metro, or nonmetro), income (less than 100% of Federal Poverty Level (FPL), 100 to 199% of FPL, 200% or greater than FPL), and employment status (employed, unemployed/not in labor force). Several categorizations for age and income had already been created in the public-use data. Other categories were selected and created based on cell sizes. The small number of Asians, American Indians/Alaskan Natives (AIAN), and persons who reported multiple races led to the combination of these race groups into a single category of “others.” Marital status was collapsed into married versus all other categories because the association between being married and mental health has been more extensively documented compared with other marital statuses (Simon, 2014). It is important to see how being married may be associated with specific reasons for perceived unmet need. Where possible and theoretically justifiable, variability in measures were preserved to avoid loss of information. Based on existing literature (Meadows et al., 2002; Roll et al., 2013), a number of health status and health services factors that might affect the dependent or main independent variables were included as covariates. These variables are: overall health status (fair/poor, good/very good/excellent), substance abuse or dependence (0/1), psychological distress (K6) scores (0 –24), and World Health Organization Disability Assessment Schedule (WHODAS 2.0) (0 –24). Higher K6 and WHODAS scores indicate greater distress and disability, respectively (Kessler et al., 2003; Rehm et al., 1999). A nominal measure of health insurance was also included (uninsured, public, or private). Public insurance indicates federal health plans such as Medicaid, Medicare, and ChampVA, and private insurance consists of self-purchased or employersponsored plans.
Analyses The associations between sociodemographic variables and causes of unmet need were examined using multivariate logistic regressions. Each cause of unmet need was regressed separately on sociodemographic, health and service use characteristics of adults who reported unmet need for mental health services. Multivariate regressions adjust for effects mediated by other variables in the model. Adjusting for factors that may affect the outcome is essen-
CAUSES OF UNMET NEED FOR MENTAL HEALTH CARE
tial for identifying structurally patterned differences or disparities. The significance level was set at ⬍0.05. Sampling weights, clustering, and stratification variables were used to adjust for differential probability of selection and to ensure correct approximation of estimates. All Analyses were performed using Stata 12.
Results
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Sample Characteristics Characteristics of adults with unmet mental health needs are presented in Table 1. More females than males, and a greater proportion of persons in small or large metropolitan areas com-
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pared with rural areas reported perceived unmet need. Almost one-quarter of persons with unmet need rated their physical health as fair or poor, and another quarter met criteria for alcohol or drug abuse or dependence. About half of the sample received at least some professional mental health within the past year, and ⬃30% received alternative forms of mental health care such as care from an herbalist, a spiritual leader, or participating in peer support groups. About 26% of persons with unmet need were uninsured. As shown, more than one-half of the sample reported cost or affordability as reasons for unmet need. Odds ratios (OR) from multivariate logistic regressions assessing disparities in causes of perceived unmet need are presented in Table 2.
Cost/Affordability Table 1 Reasons for Unmet Need and Characteristics of Adults Who Reported Unmet need for mental health care in the 2011 sample of the NSDUH (N ⫽ 2,564)
Reasons for unmet needa Cost/insurance Perceived stigma Minimization Low perceived effectiveness of treatment Structural barriers Sociodemographic characteristics Non-Hispanic White Non-Hispanic Black Hispanic All others (Asian, AIAN, or multiple race) 18–25 years old 26–34 35 and older Female Married Less than high school Completed high school Some college College degree and higher Large metro Small metro Nonmetro 100% of FPL 100%–199% of FPL 200% ⫹ FPL Employed Health status Poor/fair health Substance abuse or dependence Mean K6 scores (SE) Mean WHODAS (SE) Health services utilization Professional care in the past 12 months Alternative care in the past 12 months Health insurance Uninsured Public Private
% Weighted
N (unweighted)
51.19 23.3 24.94 8.51 29.16
1,225 751 709 261 820
73.10 9.50 10.57 6.83 23.19 23.78 53.07 67.19 36.50 15.08 25.88 31.97 27.07 48.28 35.55 16.17 25.05 23.67 51.28 57.49
1,785 252 297 230 1,496 422 646 1,792 650 402 735 859 568 1,047 1,022 495 767 670 1,127 1,552
24.36 26.57 12.33 10.76
480 778 (0.01) 2564 (0.12) 2564
55.17 29.89
1,285 634
26.52 21.22 52.26
664 567 1,333
Note. NSDUH ⫽ National Survey on Drug Use and Health; AIAN ⫽ American Indians/Alaskan Natives; FPL ⫽ Federal Poverty Level; WHODAS ⫽ World Health Organization Disability Assessment Schedule. a Respondents could list more than one reason.
The “all others” race/ethnic category consisting of Asians, AIANs, and persons who reported multiple or other races were less likely than Whites to report cost-related barriers to mental health care (OR ⫽ 0.33, 95% CI [0.21, 0.69]). Compared with males, females had greater odds of having unmet need because of cost (OR ⫽ 1.55, 95% CI [1.14, 2.42]). Respondents who attended some college had higher odds of listing cost as a reason for unmet need compared with their counterparts with no high school education (OR ⫽ 1.87, 95% CI [1.15, 2.30]). Employment was associated with higher odds of costs barriers (OR ⫽ 1.51, 95% CI [1.19, 2.08]). Other factors associated with greater odds of cost barriers were high disability scores and use of alternative mental health care. As expected, health insurance was associated with lower odds of indicating cost as a reason for unmet need.
Stigma Compared with non-Hispanic Whites, both Blacks and Hispanics had significantly greater odds of reporting stigma as a reason for perceived unmet need for mental health care (OR ⫽ 1.45, 95% CI [1.10, 3.01] and OR ⫽ 1.71, 95% CI [1.30, 2.90] for Blacks and Hispanics, respectively). Persons 26 years and older had lower odds of experiencing stigma-related unmet need than younger adults between 18 and 25 years old. Women were also less likely to report stigma compared with men (OR ⫽ 0.56, 95% CI [0.40, 0.87]), and persons who live in rural areas had significantly greater odds of perceiving stigma barriers compared with their counterparts in large metropolitan areas (OR ⫽ 1.63, 95% CI [1.06, 2.10]). Additional factors associated with stigma were elevated distress scores and health insurance.
Minimization Persons 35 and older had significantly lower odds (OR ⫽ 0.68, 95% CI [.026, 0.97]) of thinking that they can handle mental health problems by themselves, compared with their younger counterparts between 18 and 25 years old. Married persons were more likely than never married, divorced/separated, or widowed persons to minimize need for treatment (OR ⫽ 1.53, 95% CI [1.09, 2.01]). Compared with persons with family income of less than 100% FPL, respondents whose household incomes are between 100% and 199% FPL had lower odds of minimization (OR ⫽ 0.55, 95% CI [0.26, 0.89]). Elevated distress scores were associated with lower odds of minimization while having public or private insurance was associated with greater odds of minimization.
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Table 2 Logistic Regressions of Reasons for Unmet Need on Sociodemographic, Health Status, and Health Services Variables
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Cost/affordability
Race (ref: White) Black Hispanic All others Age (18–25) 26–34 35 and older Female Married Education (no high school) Completed high school Some college College degree or higher Region (large metro) Small metro Nonmetro Poverty (⬍100% FPL) 100–199% FPL 200% ⫹ FPL Employed Poor/fair health Substance problem K6 scores (x ) WHODAS (x ) Professional care Alternative care Insurance (uninsured) Public Private
Stigma
Minimization
OR
95% CI
OR
95% CI
OR
95% CI
0.88 0.67 0.33ⴱⴱ
[0.61, 1.75] [0.53, 1.04] [0.21, 0.69]
1.45ⴱ 1.71ⴱⴱ 1.11
[1.10, 3.01] [1.30, 2.90] [0.91, 1.41]
0.71 0.90 1.11
[0.58, 1.13] [0.79, 1.24] [0.96, 1.31]
1.01 1.32 1.55ⴱⴱ 0.75
[0.71, 0.41] [0.95, 1.84] [1.14, 2.12] [0.44, 0.96]
0.55ⴱⴱ 0.50ⴱⴱⴱ 0.56ⴱⴱⴱ 1.02
[0.33, 0.81] [0.35, 0.71] [0.40, 0.87] [0.71, 1.34]
0.85 0.68ⴱ 1.28 1.53ⴱ
1.43 1.87ⴱⴱ 1.20
[0.93, 2.26] [1.15, 2.30] [0.83, 2.34]
1.06 1.27 1.25
[0.65, 1.71] [0.76, 2.09] [0.71, 2.17]
1.01 1.30
[0.73, 1.38] [0.94, 2.03]
1.33 1.63ⴱ
1.41 0.98 1.51ⴱ 1.51 0.93 0.97 1.15ⴱⴱⴱ 0.80 1.23ⴱ
[1.09, 2.11] [0.66, 1.43] [1.19, 2.08] [0.94, 1.96] [0.71, 1.32] [0.94, 1.01] [1.07, 1.19] [0.58, 1.07] [1.02, 1.70]
0.12ⴱⴱⴱ 0.13ⴱⴱⴱ
[0.07, 0.18] [0.08, 0.19]
Low perceived effectiveness OR
Structural barriers
95% CI
OR
95% CI
0.84 0.69 1.10
[0.62, 1.09] [0.48, 1.01] [0.88, 1.23]
1.55ⴱⴱ 1.13 1.70
[1.10, 2.08] [0.57, 1.49] [0.87, 2.50]
[0.37, 1.86] [0.26, 0.97] [0.89, 1.90] [1.09, 2.01]
0.81 0.59ⴱ 0.91 0.58ⴱ
[0.44, 1.45] [0.26, 0.96] [0.56, 1.46] [0.35, 0.98]
0.96 0.65ⴱⴱ 1.21 1.29
[0.68, 1.36] [0.47, 0.90] [0.88, 1.66] [0.91, 1.81]
1.21 0.92 1.22
[0.72, 1.99] [0.55, 1.51] [0.70, 2.12]
4.34ⴱⴱⴱ 3.55ⴱⴱⴱ 3.86ⴱⴱⴱ
[2.14, 6.82] [1.98, 5.10] [1.96, 6.24]
0.82ⴱⴱ 0.42ⴱⴱ 0.40ⴱⴱ
[0.64, 0.98] [0.32, 0.89] [0.21, 0.56]
0.93, 1.89] [1.06, 2.10]
1.01 1.16
[0.72, 1.41] [0.76, 1.74]
1.26 1.36
[0.76, 202] [0.79, 2.32]
1.32ⴱ 0.91
[1.05, 1.80] [0.59, 1.29]
0.76 0.90 1.03 0.91 1.09 1.19ⴱⴱ 1.01 0.93 0.88
[0.50, 1.14] [0.59, 1.34] [0.74, 1.42] [0.59, 1.39] [0.77, 1.51] [1.04, 1.11] [0.98, 1.10] [0.68, 1.26] [0.62, 1.25]
0.55ⴱⴱ 0.78 0.87 0.70 0.91 0.90ⴱⴱ 0.98 0.78 0.98
[0.26, 0.89] [0.53, 1.13] [0.63, 1.19] [0.47, 1.02] [0.64, 1.28] [0.75, 0.98] [0.95, 1.01] [0.56, 1.08] [0.68, 1.38]
0.96 1.35 0.92 0.73 0.57ⴱⴱ 1.17ⴱⴱ 1.01 0.73 1.24
[0.49, 1.81] [0.80, 2.24] [0.53, 1.57] [0.38, 1.38] [0.35, 0.90] [1.02, 1.31] [0.97, 1.05] [0.47, 1.12] [0.74, 2.04]
1.20 1.01 1.25 0.85 0.94 1.00 1.13ⴱⴱ 0.96 0.98
[0.80, 1.78] [0.68, 1.50] [0.90, 1.71] [0.57, 1.24] [0.68, 1.28] [0.97, 1.03] [1.01, 1.09] [0.70, 1.29] [0.70, 1.37]
2.16ⴱⴱ 2.63ⴱⴱⴱ
[1.29, 3.43] [1.76, 4.20]
1.57ⴱ 2.57ⴱⴱⴱ
[1.10, 2.49] [1.67, 2.94]
1.28 1.43
[0.62, 2.61] [0.77, 2.63]
1.32ⴱ 1.15
[1.23, 2.19] [0.98, 1.96]
Note. CI ⫽ confidence level; FPL ⫽ Federal Poverty Level; WHODAS ⫽ World Health Organization Disability Assessment Schedule. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01. ⴱⴱⴱ p ⬍ .001.
Low Perceived Effectiveness Compared with adults younger than 26, persons 35 and older had significantly lower odds (OR ⫽ 0.59, 95% CI [0.26, 0.96]) of thinking that mental health services would not help. Married respondents also had lower odds of reporting low perceived treatment effectiveness than their unmarried, divorced, or widowed counterparts (OR ⫽ 0.58, 95% CI [0.35, 0.98]). Higher education was surprisingly associated with low perceived effectiveness of mental health services. Persons with a college degree or higher had greater odds of reporting low perceived treatment effectiveness than respondents with no high school education (OR ⫽ 3.86, 95% CI [1.96, 6.24]). The odds of low perceived treatment effectiveness were much lower among respondents with substance use problems but slightly higher with increasing distress scores.
Structural Barriers Blacks were significantly more likely than Whites to indicate lack of time, transportation problems, and lack of information about where to seek mental health services as reasons for unmet need (OR ⫽ 1.55, 95% CI [1.10, 1.08]). Compared with younger adults, adults age 35 or older were less likely to report structural barriers to mental health compared with persons between the ages of 18 and 25 (OR ⫽ 0.65, 95% CI [0.47, 0.90]). Persons with at
least a high school education had lower odds of reporting structural barriers compared with their peers with no high school education. Other factors associated with greater odds of reporting structural barriers were small metro regions compared with large metro regions, and high disability scores.
Discussion According to the NSDUH, ⬃4.6% of the U.S. adult population reported perceived unmet need for mental health care in 2011. This estimate is much higher than the estimate from the 2010 National Health Interview Survey (NHIS) that suggests that the proportion of U.S. adults with perceived unmet need for mental health services was about 2.5% (Roll et al., 2013). This discrepancy reflects the measures of perceived unmet need used in both studies. While Roll and colleagues used a more restrictive measure of perceived unmet need in the NHIS—if the respondent needed mental health care or counseling but did not get it because of cost reasons, the current study uses a broader measure of unmet need—if the responded did not receive mental health services or received services that they perceived as insufficient, regardless of the reasons. With this broad measure, the present study identifies some significant disparities in causes of unmet need for mental health care in the general population. Previous studies have shown that
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CAUSES OF UNMET NEED FOR MENTAL HEALTH CARE
even with comparable insurance, needs, attitudes toward treatment and beliefs about the effectiveness of treatment, Blacks and Hispanics are less likely than Whites to use mental health services (Alegria et al., 2008; Chow, Jaffee, & Snowden, 2003). Findings of racial disparities in stigma and structural barriers to mental health services in the current study may explain some of the documented disparities in underutilization of mental health services and unmet need for care. Structural reasons such as lack of time and lack of information about where to go for mental health services were more prevalent among Blacks. One potential reason why Blacks may be more likely to lack time to seek mental health care is their disproportionately limited access to professional jobs that have flexible schedules, job control and security, and their greater likelihood of working in unstable low wage jobs with long working hours compared with Whites (Golden, 2001; Jackson et al., 2013). Structural factors contribute to underutilization of mental health services and unmet need directly through the lack of access to care and indirectly by limiting mental health literacy—the ability to recognize mental health problems and to promptly seek appropriate care (Jorm, 2000). However, utilization of mental health services with a positive outcome may change beliefs about mental health problems, increase awareness of symptoms, and facilitate entry into care among others in the community (Prokofyeva et al., 2013). This suggests that bidirectional relationships exist between mental health service utilization and mental health literacy, and that these factors have reciprocal effects on unmet need. Further research that explores these hypothesized pathways is needed to fully understand the mechanisms that underlie disparities in unmet need for mental health care. Findings that Blacks and Hispanics have higher odds of indicating that stigma prevented them from receiving treatment are consistent with previous studies that suggest that mental illness stigma is greater among members of racial minority groups (Rao, Feinglass, & Corrigan, 2007; Thompson, 2004). Blacks and Hispanics in the NSDUH may be more hesitant than Whites to access and utilize mental health services because of the fear of experiencing mental health-related discrimination in addition to discrimination that they might already experience based on race or ethnicity (Gary, 2005; Rait, Burns, & Chew, 1996). Other important findings from the current study are gender disparities in cost and stigma-related reasons for unmet need. While women were more likely to forgo mental health care because of cost, men were more likely to forgo care because of stigma. Given that factors that are correlated with financial need such as employment, health insurance, household income, and education were adjusted in the model, higher odds of cost barriers among women are informative but require further investigation. Gender disparities in wage might shed some light on higher odds of cost-related reasons for unmet need among women compared with men. Higher odds of stigma among men with unmet need might reflect gender stereotypes about mental health problems, and gender role socialization that encourages men to legitimize their strength by neither recognizing mental health problems nor seeking help (Addis & Mahalik, 2003; Leong & Zachar, 1999). Several other sociodemographic variations were observed. Regional disparities in stigma-related unmet need might reflect limited mental health literacy and mental health services in rural areas. Age was found to be associated with lower odds of reporting
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stigma, minimization, low perceived treatment effectiveness, and structural barriers as reasons for unmet mental health need. The results here appear to be intuitive and consistent with previous studies that show higher rates of mental health services utilization, more positive attitudes toward treatment, and lower unmet need among relatively older adults (Mojtabai, 2009; Wang et al., 2005). The findings that higher education was associated with increased odds of reporting low perceived treatment effectiveness as a reason for unmet need, and that employment was associated with higher odds of cost-related barriers were surprising and counterintuitive. However, recent studies found the likelihood of unmet need to be greater among persons with college education (Mojtabai, 2009) and among working age adults (Roll et al., 2013). Unfortunately, there is neither a tested explanation nor plausible hypothesis for the positive association between higher education and low perceived treatment effectiveness of mental health services. An admittedly speculative explanation of the relationship between employment and cost-related barriers is that employed persons likely to report cost-related unmet need for mental health care may be involved in precarious employment situations with health insurance policies that provide a limited range of benefits, and that have higher cost-sharing requirements. Two main health status differences in causes of unmet need were observed. Although not unexpected, the association between WHODAS scores and greater odds of reporting cost and structural barriers to mental health care is disconcerting as this would increase the burden of mental illness and disability. Similarly, the relationships between psychological distress and stigma and between distress and low perceived effectiveness of treatment may worsen mental health outcomes. More efforts should be made to address stigma and low perceived effectiveness of mental health services especially among distressed persons and persons with disabilities. Findings from this study only apply to persons with perceived unmet need and should be interpreted in light of important limitations. First, homeless persons who are more likely to have unmet need for mental health services were not included in the NSDUH. Second, discrepancies may exist in the concept of perceived need—services that individuals believe they ought to utilize, and medically defined need that consists of services providers believe an individual ought to utilize (Magi & Allander, 1981). However, the focus on perceived need is important because lack of access to health services naturally limits opportunities for detection of medically defined need, and perceived mental health need is associated with higher psychopathology and poor quality of life (Meadows et al., 2002; Sareen, Cox, Afifi, Clara, & Yu, 2005). Third, reasons for perceived unmet need are unlikely to be exhaustive as respondents might have been limited by structured responses. Finally, this study does not explore how intersecting statuses may be associated with the likelihood of reporting specific causes of perceived unmet need—another agenda for future inquiry. Despite the above limitations, important public health implications can be drawn from this study. Cost was the most common reason for unmet need, and health insurance coverage was significantly associated with lower odds of cost-related barriers. These suggest that the Medicaid expansion and EHB provisions of the ACA will reduce unmet mental health need significantly. Unfortunately, as of August, 2014, only 28 states are implementing the expansion, and a considerable number of Americans will be unable
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to purchase coverage through health exchanges. In the current study, insured persons were significantly more likely to report higher rates of stigma, minimization, and structural barriers to treatment. Therefore, access through insurance coverage alone is unlikely to resolve the problem of unmet mental health need. The ACAs provision of creating health homes to coordinate and integrate patient-centered care for people with chronic conditions including disability—persons with increased risk for mental health problems, will also reduce information and other structural barriers to mental health services. Several models are being tested to integrate behavioral health in primary care (Bao, Casalino, & Pincus, 2013). For example, because most patients interact with the health care system in the context of primary care, some primary care practices may operate as patient-centered medical homes for persons with mild to moderate behavioral health problems (Casalino et al., 2010). This model has the potential of linking persons who already receive services for other medical conditions to behavioral health care, and therefore, reduce stigma and information barriers to mental health care common among race and ethnic minority populations. More long-term integrative models of health homes will provide a continuum of care for persons with the most debilitating disorders (Casalino et al., 2010; Mechanic, 2014). If these models are adopted across the country, outcomes might include increased and sustained utilization of mental health services, mental health literacy within certain populations, and ultimately lower rates of unmet need. Psychiatric rehabilitation practitioners can develop stronger partnerships with primary care providers to form clinician cartels that will coordinate and facilitate the delivery of both medical and mental health services among populations that experience structural barriers to mental health care. More needs to be done to address mental illness stigma among men, Blacks, Hispanics, young adults, and in rural areas. Increasing the diffusion of information about mental health services especially among Blacks in important. Blacks have historically relied on the church for social support, mental health care, and directives on how to navigate political, social, and economic processes that affect daily life (Barnes, 2005; Blank et al., 2002; Holt et al., 2013). The church may then be considered a relevant forum for the dissemination of information that would increase mental health literacy. Finally, practitioners can help reduce unmet need by going the extra mile to always provide educational information about the availability, effectiveness, and benefits of psychiatric care at the clinical encounter. Educating patients and their families can reduce stigma and increase mental health literacy among patients, their care-givers, and the general population.
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¨ stün, T. B., Saxena, S., Nelson, C. B., Chatterji, S., Ivis, F., & Rehm, J., U Adlaf, E. (1999). On the development and psychometric testing of the WHO screening instrument to assess disablement in the general population. International Journal of Methods in Psychiatric Research, 8, 110 –122. http://dx.doi.org/10.1002/mpr.61 Roll, J. M., Kennedy, J., Tran, M., & Howell, D. (2013). Disparities in unmet need for mental health services in the United States, 1997–2010. Psychiatric Services, 64, 80 – 82. http://dx.doi.org/10.1176/appi.ps .201200071 Sareen, J., Cox, B. J., Afifi, T. O., Clara, I., & Yu, B. N. (2005). Perceived need for mental health treatment in a nationally representative Canadian sample. Canadian journal of Psychiatry [Revue canadienne de psychiatrie], 50, 643– 651. Simon, R. W. (2014). Twenty years of the sociology of mental health: The continued significance of gender and marital status for emotional wellbeing. In R. J. Johnson, R. J. Turner, & B. G. Link (Eds.), Sociology of mental health (pp. 21–51). New York: Springer International Publishing. Sommers, B. D. (2013). Stuck between health and immigration reform: Care for undocumented immigrants. The New England Journal of Medicine, 369, 593–595. http://dx.doi.org/10.1056/NEJMp1306636 Substance Abuse and Mental Health Services Administration (SAMHSA). (2013). Affordability most frequent reason for not receiving mental health services. The NSDUH Report. Data Spotlight. Rockville, MD: SAMHSA. Retrieved from http://www.samhsa.gov/data/spotlight/ spot075-services-affordability-2013.pdf Thompson, V. L. S., Bazile, A., & Akbar, M. (2004). African Americans’ perceptions of psychotherapy and psychotherapists. Professional Psychology, Research and Practice, 35, 19 –23. Wang, P. S., Lane, M., Olfson, M., Pincus, H. A., Wells, K. B., & Kessler, R. C. (2005). Twelve-month use of mental health services in the United States: Results from the National Comorbidity Survey Replication. Archives of General Psychiatry, 62, 629 – 640. http://dx.doi.org/10.1001/ archpsyc.62.6.629 Wells, K., Klap, R., Koike, A., & Sherbourne, C. (2001). Ethnic disparities in unmet need for alcoholism, drug abuse, and mental health care. The American Journal of Psychiatry, 158, 2027–2032. http://dx.doi.org/ 10.1176/appi.ajp.158.12.2027
Received May 28, 2014 Revision received November 13, 2014 Accepted November 13, 2014 䡲
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© 2015 American Psychological Association 1095-158X/15/$12.00 http://dx.doi.org/10.1037/prj0000113
Sociodemographic Disparities Associated With Perceived Causes of Unmet Need for Mental Health Care Sirry M. Alang
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University of Minnesota School of Public Health Objective: Mental disorders are among the leading causes of disability in the United States. In 2011, over 10 million adults felt that even though they needed treatment for mental health problems, they received insufficient or no mental health care and reported unmet need. This article assesses associations between sociodemographic characteristics and perceived causes of unmet needs for mental health care. Method: A sample of 2,564 adults with unmet mental health need was obtained from the National Survey on Drug Use and Health. Outcome variables were 5 main reasons for unmet need: cost, stigma, minimization, low perceived treatment effectiveness, and structural barriers. Each cause of unmet need was regressed on sociodemographic, health, and service use characteristics. Women had higher odds of cost-related reasons for unmet need than men. Odds of stigma and structural barriers were greater among Blacks than Whites, and among rural than metropolitan residents. Compared with the uninsured, insured persons were less likely to report cost barriers. However, insured persons had higher odds of stigma and minimization of mental disorders. Conclusions and Implications for Practice: Insurance alone is unlikely to resolve the problem of unmet need. Understanding the social epidemiology of perceived unmet need will help identify populations at risk of not receiving mental health care or insufficient care. Focusing on specific programs and services that are designed to address the causes of perceived unmet need in particular populations is important. Future research should explore how intersecting social statuses affect the likelihood of perceived unmet need. Keywords: unmet need, mental health disparities, access to mental health care, perceived need for mental health care
White, Blacks and Hispanics are less likely to have access to mental health care and more likely to report delayed or insufficient care (Alegría et al., 2008; Wells, Klap, Koike, & Sherbourne, 2001). Studies also find high probabilities of reporting unmet need among uninsured persons, poor working age adults, persons with chronic conditions, individuals with poor physical health, and among persons with mental health and substance use problems (Mojtabai, 2009; Mojtabai et al., 2011; Roll, Kennedy, Tran, & Howell, 2013; Wang et al., 2005). Although evidence points to cost and stigma as the most common reasons for unmet mental health needs (Corrigan, 2004; Mojtabai, 2005; Mojtabai et al., 2011), research has yet to assess whether cost, stigma, and other causes of unmet need vary sociodemographically. Passage of the Patient Protection and Affordable Care Act (ACA) is expected to reduce cost/affordability barriers to mental health care in states that expand Medicaid, through the inclusion of mental and behavioral treatment in the essential health benefits (EHB) for health exchanges, and by expanding mental health parity. Even after the implementation of the ACA, residual cost barriers are likely to exist. This is true for states that opt out of Medicaid expansion, undocumented immigrants who already encounter access barriers to health care, and persons unable to afford the cost of premiums in the exchanges, and who fall in the cracks between Medicaid and employer-sponsored health insurance (Jacobs, 2013; Nardin et al., 2013; Sommers, 2013). Other more comprehensive behavioral health services that might reduce perceived need but that have limited financing under provisions in the ACA include supportive employment and housing (Goldman &
Mental disorders are among the leading causes of disability in the United States, and 1 in 17 adults has a severe debilitating mental illness in any given year (Kessler, Chiu, Demler, Merikangas, & Walters, 2005). According to the Substance Abuse and Mental Health Services Administration (SAMHSA), over 10 million adults age 18 or older in the general U.S. population felt that even though they needed treatment for their mental health problems, they received insufficient or no mental health care—reporting unmet mental health needs in 2011. This article explores reasons for unmet need and examines whether there are sociodemographic disparities in reported causes of unmet need for professional mental health services. Identifying how causes of unmet need vary across populations will inform policies that address disparities in access to and utilization of mental health services, ultimately reducing rates of untreated mental illness. Although advances in treatment have the potential to improve the ability of persons with even the most severe mental illnesses to manage their symptoms such that they can lead productive lives, sociodemographic disparities and health status differences in unmet need for mental health services persist. For example, data from national surveys in the United States suggest that those who are
This article was published Online First February 9, 2015. Correspondence concerning this article should be addressed to Sirry M. Alang, Division of Health Policy and Management, University of Minnesota School of Public Health, 420 Delaware Street SE, Minneapolis, MN 55455. E-mail: [email protected] 293
ALANG
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Karakus, 2014; Hogan, Drake, & Goldman, 2014). Regardless of the ACA, challenges that result from lack of evidence around organization and delivery of pharmaceutical versus more psychosocial treatment services (Mechanic, 2014), and the lack of infrastructure for care delivery can increase barriers to mental health care within certain populations (Croft & Parish, 2013; Cummings, Wen, & Druss, 2013). In addition to the residual cost-related reason for unmet need as well infrastructural and organizational barriers to the delivery of mental health services, other significant causes of unmet need for mental health care exist. The main objective of this article is to examine whether there are sociodemographic disparities in reasons for perceived unmet need for mental health care among U.S. adults. It assesses whether race/ethnic, sex, age, income, education, and regional disparities exist in each of five general reasons for not receiving needed mental health services. These reasons are identified by SAMHSA as: cost/affordability, stigma, minimization of symptoms or low perceived need, low perceived effectiveness of treatment, and structural barriers (SAMHSA, 2013). Pinpointing group differences in the likelihood of reporting specific causes of unmet need will facilitate efforts to monitor and address untreated mental illness. It will also increase our current understanding of disparities in unmet need, and inform policies to reduce the burden of untreated and undertreated mental illness across different sociodemographic groups.
Method Data Cross-sectional data came from the 2011 sample of the National Survey on Drug Use and Health (NSDUH). Public-use data were obtained from the Interuniversity Consortium for Political and Social Research (ICPSR). Annually, the NSDUH collects data on the civilian, noninstitutionalized population of the United States, age 12 or older, using a multilevel stratified hierarchical sampling procedure. The response rate for the 2011 survey was 74·4%, with a sample of 70,109 persons representing the U.S. population age 12 or older. Because of the focus on adults, persons aged 12–17 (23,510) were dropped from the sample. The final analytic sample (N ⫽ 2,564) was limited to adults 18 or older who also reported unmet need for mental health services. To establish unmet need, adult respondents were asked whether at any time in the past 12 months, they perceived a need for mental health treatment or counseling but did not receive these services.
Measures The five dependent variables are: cost, stigma, minimization, low perceived treatment effectiveness, and structural barriers. All dependent variables are binary measures (1/0) indicating whether or not the reason was cited by the respondent. In the NSDUH, respondents who perceived need for mental health treatment or counseling but did not receive services were further asked to specify reasons for not receiving mental health services. SAMHSA has grouped reported reasons into five main categories (SAMHSA, 2013). (a) Cost indicates that respondents selected at least one of the following as reasons for unmet need: could not afford costs, health insurance does not cover any mental health treatment/
counseling, and health insurance does not pay enough for mental health treatment/counseling. (b) Stigma indicates that respondents selected at least one of the following reasons: might cause neighbors/community to have a negative opinion, might have negative effect on job, did not want others to find out, concerned about confidentiality, and concerned about being committed/having to take medications. (c) Minimization indicates that respondents either did not feel the need for treatment at the time or thought they could handle the problem without treatment. (d) Low perceived treatment effectiveness indicates that respondents did not receive treatment because they did not think services would help. (e) Structural barriers indicate that respondents cited at least one of the following reasons for unmet need: no transportation/inconvenient, did not know where to go for services, and did not have time. Independent variables include race (non-Hispanic White, nonHispanic Black, Hispanic, and all others), age (18 –25, 26 –34, 35, and older), sex, marital status (married, all others), education (less than High School, completed High School, some college, college degree or higher), region (large metro, small metro, or nonmetro), income (less than 100% of Federal Poverty Level (FPL), 100 to 199% of FPL, 200% or greater than FPL), and employment status (employed, unemployed/not in labor force). Several categorizations for age and income had already been created in the public-use data. Other categories were selected and created based on cell sizes. The small number of Asians, American Indians/Alaskan Natives (AIAN), and persons who reported multiple races led to the combination of these race groups into a single category of “others.” Marital status was collapsed into married versus all other categories because the association between being married and mental health has been more extensively documented compared with other marital statuses (Simon, 2014). It is important to see how being married may be associated with specific reasons for perceived unmet need. Where possible and theoretically justifiable, variability in measures were preserved to avoid loss of information. Based on existing literature (Meadows et al., 2002; Roll et al., 2013), a number of health status and health services factors that might affect the dependent or main independent variables were included as covariates. These variables are: overall health status (fair/poor, good/very good/excellent), substance abuse or dependence (0/1), psychological distress (K6) scores (0 –24), and World Health Organization Disability Assessment Schedule (WHODAS 2.0) (0 –24). Higher K6 and WHODAS scores indicate greater distress and disability, respectively (Kessler et al., 2003; Rehm et al., 1999). A nominal measure of health insurance was also included (uninsured, public, or private). Public insurance indicates federal health plans such as Medicaid, Medicare, and ChampVA, and private insurance consists of self-purchased or employersponsored plans.
Analyses The associations between sociodemographic variables and causes of unmet need were examined using multivariate logistic regressions. Each cause of unmet need was regressed separately on sociodemographic, health and service use characteristics of adults who reported unmet need for mental health services. Multivariate regressions adjust for effects mediated by other variables in the model. Adjusting for factors that may affect the outcome is essen-
CAUSES OF UNMET NEED FOR MENTAL HEALTH CARE
tial for identifying structurally patterned differences or disparities. The significance level was set at ⬍0.05. Sampling weights, clustering, and stratification variables were used to adjust for differential probability of selection and to ensure correct approximation of estimates. All Analyses were performed using Stata 12.
Results
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Sample Characteristics Characteristics of adults with unmet mental health needs are presented in Table 1. More females than males, and a greater proportion of persons in small or large metropolitan areas com-
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pared with rural areas reported perceived unmet need. Almost one-quarter of persons with unmet need rated their physical health as fair or poor, and another quarter met criteria for alcohol or drug abuse or dependence. About half of the sample received at least some professional mental health within the past year, and ⬃30% received alternative forms of mental health care such as care from an herbalist, a spiritual leader, or participating in peer support groups. About 26% of persons with unmet need were uninsured. As shown, more than one-half of the sample reported cost or affordability as reasons for unmet need. Odds ratios (OR) from multivariate logistic regressions assessing disparities in causes of perceived unmet need are presented in Table 2.
Cost/Affordability Table 1 Reasons for Unmet Need and Characteristics of Adults Who Reported Unmet need for mental health care in the 2011 sample of the NSDUH (N ⫽ 2,564)
Reasons for unmet needa Cost/insurance Perceived stigma Minimization Low perceived effectiveness of treatment Structural barriers Sociodemographic characteristics Non-Hispanic White Non-Hispanic Black Hispanic All others (Asian, AIAN, or multiple race) 18–25 years old 26–34 35 and older Female Married Less than high school Completed high school Some college College degree and higher Large metro Small metro Nonmetro 100% of FPL 100%–199% of FPL 200% ⫹ FPL Employed Health status Poor/fair health Substance abuse or dependence Mean K6 scores (SE) Mean WHODAS (SE) Health services utilization Professional care in the past 12 months Alternative care in the past 12 months Health insurance Uninsured Public Private
% Weighted
N (unweighted)
51.19 23.3 24.94 8.51 29.16
1,225 751 709 261 820
73.10 9.50 10.57 6.83 23.19 23.78 53.07 67.19 36.50 15.08 25.88 31.97 27.07 48.28 35.55 16.17 25.05 23.67 51.28 57.49
1,785 252 297 230 1,496 422 646 1,792 650 402 735 859 568 1,047 1,022 495 767 670 1,127 1,552
24.36 26.57 12.33 10.76
480 778 (0.01) 2564 (0.12) 2564
55.17 29.89
1,285 634
26.52 21.22 52.26
664 567 1,333
Note. NSDUH ⫽ National Survey on Drug Use and Health; AIAN ⫽ American Indians/Alaskan Natives; FPL ⫽ Federal Poverty Level; WHODAS ⫽ World Health Organization Disability Assessment Schedule. a Respondents could list more than one reason.
The “all others” race/ethnic category consisting of Asians, AIANs, and persons who reported multiple or other races were less likely than Whites to report cost-related barriers to mental health care (OR ⫽ 0.33, 95% CI [0.21, 0.69]). Compared with males, females had greater odds of having unmet need because of cost (OR ⫽ 1.55, 95% CI [1.14, 2.42]). Respondents who attended some college had higher odds of listing cost as a reason for unmet need compared with their counterparts with no high school education (OR ⫽ 1.87, 95% CI [1.15, 2.30]). Employment was associated with higher odds of costs barriers (OR ⫽ 1.51, 95% CI [1.19, 2.08]). Other factors associated with greater odds of cost barriers were high disability scores and use of alternative mental health care. As expected, health insurance was associated with lower odds of indicating cost as a reason for unmet need.
Stigma Compared with non-Hispanic Whites, both Blacks and Hispanics had significantly greater odds of reporting stigma as a reason for perceived unmet need for mental health care (OR ⫽ 1.45, 95% CI [1.10, 3.01] and OR ⫽ 1.71, 95% CI [1.30, 2.90] for Blacks and Hispanics, respectively). Persons 26 years and older had lower odds of experiencing stigma-related unmet need than younger adults between 18 and 25 years old. Women were also less likely to report stigma compared with men (OR ⫽ 0.56, 95% CI [0.40, 0.87]), and persons who live in rural areas had significantly greater odds of perceiving stigma barriers compared with their counterparts in large metropolitan areas (OR ⫽ 1.63, 95% CI [1.06, 2.10]). Additional factors associated with stigma were elevated distress scores and health insurance.
Minimization Persons 35 and older had significantly lower odds (OR ⫽ 0.68, 95% CI [.026, 0.97]) of thinking that they can handle mental health problems by themselves, compared with their younger counterparts between 18 and 25 years old. Married persons were more likely than never married, divorced/separated, or widowed persons to minimize need for treatment (OR ⫽ 1.53, 95% CI [1.09, 2.01]). Compared with persons with family income of less than 100% FPL, respondents whose household incomes are between 100% and 199% FPL had lower odds of minimization (OR ⫽ 0.55, 95% CI [0.26, 0.89]). Elevated distress scores were associated with lower odds of minimization while having public or private insurance was associated with greater odds of minimization.
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Table 2 Logistic Regressions of Reasons for Unmet Need on Sociodemographic, Health Status, and Health Services Variables
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Cost/affordability
Race (ref: White) Black Hispanic All others Age (18–25) 26–34 35 and older Female Married Education (no high school) Completed high school Some college College degree or higher Region (large metro) Small metro Nonmetro Poverty (⬍100% FPL) 100–199% FPL 200% ⫹ FPL Employed Poor/fair health Substance problem K6 scores (x ) WHODAS (x ) Professional care Alternative care Insurance (uninsured) Public Private
Stigma
Minimization
OR
95% CI
OR
95% CI
OR
95% CI
0.88 0.67 0.33ⴱⴱ
[0.61, 1.75] [0.53, 1.04] [0.21, 0.69]
1.45ⴱ 1.71ⴱⴱ 1.11
[1.10, 3.01] [1.30, 2.90] [0.91, 1.41]
0.71 0.90 1.11
[0.58, 1.13] [0.79, 1.24] [0.96, 1.31]
1.01 1.32 1.55ⴱⴱ 0.75
[0.71, 0.41] [0.95, 1.84] [1.14, 2.12] [0.44, 0.96]
0.55ⴱⴱ 0.50ⴱⴱⴱ 0.56ⴱⴱⴱ 1.02
[0.33, 0.81] [0.35, 0.71] [0.40, 0.87] [0.71, 1.34]
0.85 0.68ⴱ 1.28 1.53ⴱ
1.43 1.87ⴱⴱ 1.20
[0.93, 2.26] [1.15, 2.30] [0.83, 2.34]
1.06 1.27 1.25
[0.65, 1.71] [0.76, 2.09] [0.71, 2.17]
1.01 1.30
[0.73, 1.38] [0.94, 2.03]
1.33 1.63ⴱ
1.41 0.98 1.51ⴱ 1.51 0.93 0.97 1.15ⴱⴱⴱ 0.80 1.23ⴱ
[1.09, 2.11] [0.66, 1.43] [1.19, 2.08] [0.94, 1.96] [0.71, 1.32] [0.94, 1.01] [1.07, 1.19] [0.58, 1.07] [1.02, 1.70]
0.12ⴱⴱⴱ 0.13ⴱⴱⴱ
[0.07, 0.18] [0.08, 0.19]
Low perceived effectiveness OR
Structural barriers
95% CI
OR
95% CI
0.84 0.69 1.10
[0.62, 1.09] [0.48, 1.01] [0.88, 1.23]
1.55ⴱⴱ 1.13 1.70
[1.10, 2.08] [0.57, 1.49] [0.87, 2.50]
[0.37, 1.86] [0.26, 0.97] [0.89, 1.90] [1.09, 2.01]
0.81 0.59ⴱ 0.91 0.58ⴱ
[0.44, 1.45] [0.26, 0.96] [0.56, 1.46] [0.35, 0.98]
0.96 0.65ⴱⴱ 1.21 1.29
[0.68, 1.36] [0.47, 0.90] [0.88, 1.66] [0.91, 1.81]
1.21 0.92 1.22
[0.72, 1.99] [0.55, 1.51] [0.70, 2.12]
4.34ⴱⴱⴱ 3.55ⴱⴱⴱ 3.86ⴱⴱⴱ
[2.14, 6.82] [1.98, 5.10] [1.96, 6.24]
0.82ⴱⴱ 0.42ⴱⴱ 0.40ⴱⴱ
[0.64, 0.98] [0.32, 0.89] [0.21, 0.56]
0.93, 1.89] [1.06, 2.10]
1.01 1.16
[0.72, 1.41] [0.76, 1.74]
1.26 1.36
[0.76, 202] [0.79, 2.32]
1.32ⴱ 0.91
[1.05, 1.80] [0.59, 1.29]
0.76 0.90 1.03 0.91 1.09 1.19ⴱⴱ 1.01 0.93 0.88
[0.50, 1.14] [0.59, 1.34] [0.74, 1.42] [0.59, 1.39] [0.77, 1.51] [1.04, 1.11] [0.98, 1.10] [0.68, 1.26] [0.62, 1.25]
0.55ⴱⴱ 0.78 0.87 0.70 0.91 0.90ⴱⴱ 0.98 0.78 0.98
[0.26, 0.89] [0.53, 1.13] [0.63, 1.19] [0.47, 1.02] [0.64, 1.28] [0.75, 0.98] [0.95, 1.01] [0.56, 1.08] [0.68, 1.38]
0.96 1.35 0.92 0.73 0.57ⴱⴱ 1.17ⴱⴱ 1.01 0.73 1.24
[0.49, 1.81] [0.80, 2.24] [0.53, 1.57] [0.38, 1.38] [0.35, 0.90] [1.02, 1.31] [0.97, 1.05] [0.47, 1.12] [0.74, 2.04]
1.20 1.01 1.25 0.85 0.94 1.00 1.13ⴱⴱ 0.96 0.98
[0.80, 1.78] [0.68, 1.50] [0.90, 1.71] [0.57, 1.24] [0.68, 1.28] [0.97, 1.03] [1.01, 1.09] [0.70, 1.29] [0.70, 1.37]
2.16ⴱⴱ 2.63ⴱⴱⴱ
[1.29, 3.43] [1.76, 4.20]
1.57ⴱ 2.57ⴱⴱⴱ
[1.10, 2.49] [1.67, 2.94]
1.28 1.43
[0.62, 2.61] [0.77, 2.63]
1.32ⴱ 1.15
[1.23, 2.19] [0.98, 1.96]
Note. CI ⫽ confidence level; FPL ⫽ Federal Poverty Level; WHODAS ⫽ World Health Organization Disability Assessment Schedule. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01. ⴱⴱⴱ p ⬍ .001.
Low Perceived Effectiveness Compared with adults younger than 26, persons 35 and older had significantly lower odds (OR ⫽ 0.59, 95% CI [0.26, 0.96]) of thinking that mental health services would not help. Married respondents also had lower odds of reporting low perceived treatment effectiveness than their unmarried, divorced, or widowed counterparts (OR ⫽ 0.58, 95% CI [0.35, 0.98]). Higher education was surprisingly associated with low perceived effectiveness of mental health services. Persons with a college degree or higher had greater odds of reporting low perceived treatment effectiveness than respondents with no high school education (OR ⫽ 3.86, 95% CI [1.96, 6.24]). The odds of low perceived treatment effectiveness were much lower among respondents with substance use problems but slightly higher with increasing distress scores.
Structural Barriers Blacks were significantly more likely than Whites to indicate lack of time, transportation problems, and lack of information about where to seek mental health services as reasons for unmet need (OR ⫽ 1.55, 95% CI [1.10, 1.08]). Compared with younger adults, adults age 35 or older were less likely to report structural barriers to mental health compared with persons between the ages of 18 and 25 (OR ⫽ 0.65, 95% CI [0.47, 0.90]). Persons with at
least a high school education had lower odds of reporting structural barriers compared with their peers with no high school education. Other factors associated with greater odds of reporting structural barriers were small metro regions compared with large metro regions, and high disability scores.
Discussion According to the NSDUH, ⬃4.6% of the U.S. adult population reported perceived unmet need for mental health care in 2011. This estimate is much higher than the estimate from the 2010 National Health Interview Survey (NHIS) that suggests that the proportion of U.S. adults with perceived unmet need for mental health services was about 2.5% (Roll et al., 2013). This discrepancy reflects the measures of perceived unmet need used in both studies. While Roll and colleagues used a more restrictive measure of perceived unmet need in the NHIS—if the respondent needed mental health care or counseling but did not get it because of cost reasons, the current study uses a broader measure of unmet need—if the responded did not receive mental health services or received services that they perceived as insufficient, regardless of the reasons. With this broad measure, the present study identifies some significant disparities in causes of unmet need for mental health care in the general population. Previous studies have shown that
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CAUSES OF UNMET NEED FOR MENTAL HEALTH CARE
even with comparable insurance, needs, attitudes toward treatment and beliefs about the effectiveness of treatment, Blacks and Hispanics are less likely than Whites to use mental health services (Alegria et al., 2008; Chow, Jaffee, & Snowden, 2003). Findings of racial disparities in stigma and structural barriers to mental health services in the current study may explain some of the documented disparities in underutilization of mental health services and unmet need for care. Structural reasons such as lack of time and lack of information about where to go for mental health services were more prevalent among Blacks. One potential reason why Blacks may be more likely to lack time to seek mental health care is their disproportionately limited access to professional jobs that have flexible schedules, job control and security, and their greater likelihood of working in unstable low wage jobs with long working hours compared with Whites (Golden, 2001; Jackson et al., 2013). Structural factors contribute to underutilization of mental health services and unmet need directly through the lack of access to care and indirectly by limiting mental health literacy—the ability to recognize mental health problems and to promptly seek appropriate care (Jorm, 2000). However, utilization of mental health services with a positive outcome may change beliefs about mental health problems, increase awareness of symptoms, and facilitate entry into care among others in the community (Prokofyeva et al., 2013). This suggests that bidirectional relationships exist between mental health service utilization and mental health literacy, and that these factors have reciprocal effects on unmet need. Further research that explores these hypothesized pathways is needed to fully understand the mechanisms that underlie disparities in unmet need for mental health care. Findings that Blacks and Hispanics have higher odds of indicating that stigma prevented them from receiving treatment are consistent with previous studies that suggest that mental illness stigma is greater among members of racial minority groups (Rao, Feinglass, & Corrigan, 2007; Thompson, 2004). Blacks and Hispanics in the NSDUH may be more hesitant than Whites to access and utilize mental health services because of the fear of experiencing mental health-related discrimination in addition to discrimination that they might already experience based on race or ethnicity (Gary, 2005; Rait, Burns, & Chew, 1996). Other important findings from the current study are gender disparities in cost and stigma-related reasons for unmet need. While women were more likely to forgo mental health care because of cost, men were more likely to forgo care because of stigma. Given that factors that are correlated with financial need such as employment, health insurance, household income, and education were adjusted in the model, higher odds of cost barriers among women are informative but require further investigation. Gender disparities in wage might shed some light on higher odds of cost-related reasons for unmet need among women compared with men. Higher odds of stigma among men with unmet need might reflect gender stereotypes about mental health problems, and gender role socialization that encourages men to legitimize their strength by neither recognizing mental health problems nor seeking help (Addis & Mahalik, 2003; Leong & Zachar, 1999). Several other sociodemographic variations were observed. Regional disparities in stigma-related unmet need might reflect limited mental health literacy and mental health services in rural areas. Age was found to be associated with lower odds of reporting
297
stigma, minimization, low perceived treatment effectiveness, and structural barriers as reasons for unmet mental health need. The results here appear to be intuitive and consistent with previous studies that show higher rates of mental health services utilization, more positive attitudes toward treatment, and lower unmet need among relatively older adults (Mojtabai, 2009; Wang et al., 2005). The findings that higher education was associated with increased odds of reporting low perceived treatment effectiveness as a reason for unmet need, and that employment was associated with higher odds of cost-related barriers were surprising and counterintuitive. However, recent studies found the likelihood of unmet need to be greater among persons with college education (Mojtabai, 2009) and among working age adults (Roll et al., 2013). Unfortunately, there is neither a tested explanation nor plausible hypothesis for the positive association between higher education and low perceived treatment effectiveness of mental health services. An admittedly speculative explanation of the relationship between employment and cost-related barriers is that employed persons likely to report cost-related unmet need for mental health care may be involved in precarious employment situations with health insurance policies that provide a limited range of benefits, and that have higher cost-sharing requirements. Two main health status differences in causes of unmet need were observed. Although not unexpected, the association between WHODAS scores and greater odds of reporting cost and structural barriers to mental health care is disconcerting as this would increase the burden of mental illness and disability. Similarly, the relationships between psychological distress and stigma and between distress and low perceived effectiveness of treatment may worsen mental health outcomes. More efforts should be made to address stigma and low perceived effectiveness of mental health services especially among distressed persons and persons with disabilities. Findings from this study only apply to persons with perceived unmet need and should be interpreted in light of important limitations. First, homeless persons who are more likely to have unmet need for mental health services were not included in the NSDUH. Second, discrepancies may exist in the concept of perceived need—services that individuals believe they ought to utilize, and medically defined need that consists of services providers believe an individual ought to utilize (Magi & Allander, 1981). However, the focus on perceived need is important because lack of access to health services naturally limits opportunities for detection of medically defined need, and perceived mental health need is associated with higher psychopathology and poor quality of life (Meadows et al., 2002; Sareen, Cox, Afifi, Clara, & Yu, 2005). Third, reasons for perceived unmet need are unlikely to be exhaustive as respondents might have been limited by structured responses. Finally, this study does not explore how intersecting statuses may be associated with the likelihood of reporting specific causes of perceived unmet need—another agenda for future inquiry. Despite the above limitations, important public health implications can be drawn from this study. Cost was the most common reason for unmet need, and health insurance coverage was significantly associated with lower odds of cost-related barriers. These suggest that the Medicaid expansion and EHB provisions of the ACA will reduce unmet mental health need significantly. Unfortunately, as of August, 2014, only 28 states are implementing the expansion, and a considerable number of Americans will be unable
ALANG
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298
to purchase coverage through health exchanges. In the current study, insured persons were significantly more likely to report higher rates of stigma, minimization, and structural barriers to treatment. Therefore, access through insurance coverage alone is unlikely to resolve the problem of unmet mental health need. The ACAs provision of creating health homes to coordinate and integrate patient-centered care for people with chronic conditions including disability—persons with increased risk for mental health problems, will also reduce information and other structural barriers to mental health services. Several models are being tested to integrate behavioral health in primary care (Bao, Casalino, & Pincus, 2013). For example, because most patients interact with the health care system in the context of primary care, some primary care practices may operate as patient-centered medical homes for persons with mild to moderate behavioral health problems (Casalino et al., 2010). This model has the potential of linking persons who already receive services for other medical conditions to behavioral health care, and therefore, reduce stigma and information barriers to mental health care common among race and ethnic minority populations. More long-term integrative models of health homes will provide a continuum of care for persons with the most debilitating disorders (Casalino et al., 2010; Mechanic, 2014). If these models are adopted across the country, outcomes might include increased and sustained utilization of mental health services, mental health literacy within certain populations, and ultimately lower rates of unmet need. Psychiatric rehabilitation practitioners can develop stronger partnerships with primary care providers to form clinician cartels that will coordinate and facilitate the delivery of both medical and mental health services among populations that experience structural barriers to mental health care. More needs to be done to address mental illness stigma among men, Blacks, Hispanics, young adults, and in rural areas. Increasing the diffusion of information about mental health services especially among Blacks in important. Blacks have historically relied on the church for social support, mental health care, and directives on how to navigate political, social, and economic processes that affect daily life (Barnes, 2005; Blank et al., 2002; Holt et al., 2013). The church may then be considered a relevant forum for the dissemination of information that would increase mental health literacy. Finally, practitioners can help reduce unmet need by going the extra mile to always provide educational information about the availability, effectiveness, and benefits of psychiatric care at the clinical encounter. Educating patients and their families can reduce stigma and increase mental health literacy among patients, their care-givers, and the general population.
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Received May 28, 2014 Revision received November 13, 2014 Accepted November 13, 2014 䡲
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