Barriers to Mental Health Care and Predictors of Treatment Dropout in the South African Stress and Health Study
Abstract
Objective:
This study used data from the South African Stress and Health Study (SASH) to examine both structural and attitudinal barriers to treatment initiation among South Africans with mental disorders and to investigate predictors of treatment dropout.
Methods:
Face-to-face interviews were conducted with 4,315 adult South Africans living in households or hostel quarters. The interview included a core diagnostic assessment of past-12-month mental disorders and assessments of disorder severity, service use, and barriers to treatment. Multivariate logistic regression models were used to determine predictors of not seeking treatment in relation to disorder severity and sociodemographic characteristics, as well as factors that were predictive of premature treatment discontinuation by participants who had received mental health treatment in the previous 12 months. Predictors of dropout were identified by cross-tabulation and discrete-time survival analysis.
Results:
Of the 4,315 adults, 729 (16.9% weighted) met criteria for a mental disorder in the past 12 months. Across all levels of severity, the most frequently cited reason for not seeking professional treatment was a low perceived need for treatment. Among those who recognized the need but did not access treatment during the past 12 months (7.2%), attitudinal barriers to treatment seeking were reported more commonly than structural barriers (100% and 34%, respectively). Of the 182 respondents who received treatment (25% weighted), 20% discontinued prematurely. Various factors, such as substance use disorders and absence of health insurance, increased the odds of treatment dropout.
Conclusions:
Low rates of treatment seeking and high treatment dropout rates for common mental disorders among South Africans are a major concern. Public health efforts to improve treatment of mental disorders should consider the multiple influences on treatment initiation and discontinuation. (Psychiatric Services 62:774–781, 2011)
Although mental disorders are highly prevalent in the South African population, many of those who suffer from these conditions do not receive adequate treatment. Results from the South African Stress and Health Study (SASH), the first nationally representative study of psychiatric morbidity in South Africa, indicate that approximately 30% of adults have experienced a DSM-IV disorder in their lifetime, yet most are not treated (1–3). Low rates of treatment have been documented in many countries (4–10), and understanding impediments to the use of psychiatric services is of increasing global interest. The effectiveness of interventions is limited by patients who discontinue treatment prematurely. International studies suggest treatment dropout rates in the range of 17% to 22%, but to the best of our knowledge, treatment discontinuation rates in South Africa have not been published previously (11–14).
A number of barriers to receiving adequate mental health care, including structural and attitudinal barriers, are described in the literature. Structural barriers include financial cost of services (15–18) and lack of availability of services (19,20). Attitudinal barriers include lack of perceived need for treatment (21–23), the belief that the disorder will get better on its own (24), the view that mental illness is a result of personal weakness (25), stigma (20,24–29), and the desire to deal with the problem on one's own (11,30). Attitudinal barriers have emerged as the more critical type of barrier in many studies in developed countries (11,24,25,30).
Reasons for treatment dropout may differ from reasons for not initiating treatment (11–13). Young age, being part of an ethnic minority group, absence of health insurance, low income, unemployment, low education level, and comorbid mood disorders and substance dependence have also been shown to increase the risk of treatment dropout (11–14).
A number of nationally representative studies in the developed world have investigated barriers to mental health treatment (24,31); however, fewer data are available from developing countries, such as South Africa (32,33). In South Africa, barriers to treatment have not been researched as extensively as in other countries; however, low levels of mental health literacy (34,35), poorly developed mental health services, a limited supply of mental health professionals and staff (36–39), and a reliance on traditional medicine have been noted as contributing factors (40). We used the SASH data set to examine both structural and attitudinal barriers to treatment initiation among individuals with a mental disorder, as well as demographic and clinical predictors of treatment dropout.
Methods
Sample
The SASH collected data between January 2002 and June 2004. The research protocol was approved by the Human Subjects Committee of the University of Michigan, by the Harvard Medical School Ethics Committee, and by the ethics committee of the Medical University of South Africa. The SASH had a national probability sample of 4,315 South African adults living in households or hostels (single-sex migrant laborer group quarters). All racial and ethnic groups in South Africa were represented, and the sample was selected with use of a three-stage probability sample design. The response rate was 85.5%.
Diagnostic interview
The SASH used version 3 of the World Health Organization Composite International Diagnostic Interview (WHO CIDI) (41). Interviewers were extensively trained and conducted the interviews in several languages. Translations of the CIDI into six native South African languages were conducted in accordance with WHO requirements. Multilingual and bilingual expert panels conducted the back-translations (2,3). Mental disorders assessed included anxiety disorders (panic disorder, agoraphobia, social phobia, generalized anxiety disorder, and posttraumatic stress disorder), mood disorders (major depressive disorder and dysthymia), substance use disorders (alcohol abuse, alcohol dependence, drug abuse, and drug dependence), and intermittent explosive disorder (42,43). After a complete description of the study was provided, written informed consent was obtained from the participants.
Severity assessment
Cases that met criteria for at least one disorder were rated as severe, moderate, or mild. Cases classified as severe had at least one of the following features: substance dependence with a physiological dependence syndrome, suicide attempt in the past 12 months, severe self-reported impairment in at least two areas of functioning on the Sheehan Disability Scale (SDS) (44), and an overall self-reported functional impairment at a level consistent with a score of 50 or less on the Global Assessment of Functioning (45). Cases were classified as moderate if they had moderate role impairment in at least two SDS domains or substance dependence without a physiological dependence syndrome. The remaining cases were placed in the mild category.
Sociodemographic correlates
Sociodemographic data included age, sex, education (low, low-average, average-high, and high), marital status (married, formerly married, and never married), and household income (low, low-average, average-high, and high).
Mental health service utilization
The mental health service utilization module of the questionnaire assessed participants' treatment received in the past 12 months for problems associated with “emotions or mental health.” The list of treatment providers included a psychiatrist, other mental health professional, a general practitioner or other medical doctor, any other health professional, traditional healer, religious or spiritual advisor, and any other healer. Treatment continuity was also assessed.
Predictors of treatment dropout
Respondents who reported receiving mental health treatment in the past 12 months and who discontinued treatment before the provider indicated that they should were considered to have dropped out of treatment. Possible predictors of treatment dropout included in the assessment were insurance for treatment of mental illness (yes or no), previous mental health care utilization, number of visits, and number of different treatment sectors accessed in the past 12 months. Owing to the small sample, we excluded the complementary-alternative medicine (CAM) sector from the analysis of treatment dropout predictors. However, we examined whether adjunctive CAM in the previous 12 months had influenced treatment discontinuation from other sectors.
Data analysis
The final sample of participants was weighted to adjust for differential probabilities of selection within households and for differential nonresponse relative to demographic and geographic factors and to compensate for residual discrepancies between the sample and the population. These weights were used on all data analyses, which were carried out with SAS and SAS-Callubale SUDAAN version 8.2 software. Logistic regression analysis was conducted to examine variations in reasons for not seeking treatment in relation to sociodemographic correlates and disorder severity.
This article covers data from two separate analyses that were restricted to different samples. The analysis of reasons for seeking treatment was restricted to persons with a 12-month mental disorder, whereas the sample for the dropout models included anyone who received treatment in the previous year, even though they were not necessarily diagnosed as having a psychiatric disorder in the previous 12 months.
Treatment received in the past 12 months was aggregated into four treatment sectors (psychiatrist, other mental health professional, general medical sector, and human services treatment). The median number of visits, interquartile range of visits, and proportion of patients who completed or discontinued treatment and who were still in treatment were examined for each sector. Multivariate logistic models were run for each of the outcomes (overall, initial contact [one or two visits], later contact [three or more visits], and treatment dropout by type of provider [psychiatrist, other mental health professional, general medical, or human services]). Predictor variables included the number of visits, age, sex, marital status, education, income, insurance, previous mental health treatment, mental disorders, number of disorders, number of providers, and CAM. Dropout by number of visits was examined by using Kaplan-Meier curves. Dropout predictors for the early (first and second) visits were compared with data for later (third or more) visits. Statistical significance on the basis of two-sided tests was set at p<.05.
Results
The sample (N=4,315 adult respondents) was predominantly female (N=2,597, 53.6% weighted); 3,257 (75.2% weighted) respondents were black, 550 (10.4% weighted) of mixed race, 297 (weighted 9.4%) white, and 147 (weighted 3.1%) Indian-Asian. About half (N=2,128, 50.3% weighted) were married or cohabitating, and 2,013 (46.7% weighted) lived in a rural area. Only 1,452 (34.9% weighted) were employed. Of the 4,315 adults, 729 (16.9% weighted) met criteria for a mental disorder in the past 12 months. Only 182 (25% weighted) of these respondents had sought treatment. Regardless of mental illness severity, 20% (N=21) of participants who had received treatment dropped out.
Barriers to treatment seeking
Table 1 shows the reasons given for not seeking treatment among respondents who met criteria for a 12-month disorder. The most common reason for not accessing mental health services was a low perceived need for treatment (93%). Among respondents with a 12-month disorder who reported no use of mental health services in the past 12 months, low perceived need for treatment was defined as “the problem went away by itself, and I did not really need help.” There was no significant association between any sociodemographic variable and perceived treatment need. Only the level of clinical severity was found to be associated with perceptions of treatment need. Respondents with mild clinical severity were significantly more likely than those with moderate severity to endorse a low perceived need (p=.022).
Reasons for not seeking treatment among those who did perceive a need for treatment are shown in Table 2. Structural barriers were reported by only 34% of respondents, whereas attitudinal barriers were reported by all (100%).
Reasons for treatment dropout
The proportion of respondents who terminated treatment prematurely was highest for the CAM (89%) and human services (70%) sectors, intermediate for the general medical sector (54%), and lowest for psychiatrists (40%) and other mental health professionals (40%) (p<.001 across all providers). Of respondents who received any mental health treatment in the preceding 12 months, 54% dropped out of treatment; only 23% were still receiving treatment in any sector at the time of the survey (Table 3).
Predictors of dropout
Predictors of treatment dropout overall and by sector among those who had received treatment in the past 12 months are included in Table 4. Age, sex, marital status, education, and income did not predict overall treatment dropout. Respondents were less likely to quit treatment after one or two visits than after three or more visits (OR=.4, p=.05) (p<.05 across all providers). The odds of terminating treatment prematurely were reduced if three or four providers were involved in treatment compared with one or two (OR=.1, p<.05), if respondents had had previous mental health treatment (OR=.4, p<.05), and if treatment was provided by a psychiatrist (OR=.1) or other mental health professional (OR=.3) compared with general medical services (both p<.05). The presence of any impulse control disorder was associated with lower odds of dropout (OR=.2), whereas the presence of any substance use disorder was associated with higher odds (OR=3.7) (p<.05 for both comparisons). When comparing predictors of treatment dropout across the treatment sectors, various differences were evident (Table 4).
Discussion
As previously reported, SASH revealed low rates of treatment among South Africans who met criteria for a past-year mental disorder: 25% had accessed mental health services, and 20% of those dropped out of treatment. The United States has the highest rates of treatment of any nation, but less than half of persons with mental illness (42%) receive care (10). Data from the National Comorbidity Survey Replication indicate that 22% of patients discontinued treatment prematurely (14). Dropout rates are also unfavorable around the world; for example, in a developing country such as China, 30% of patients discontinue treatment prematurely (10).
Our data indicate that most of those who did not access mental health care did not perceive that they needed treatment. Consistent with findings of previous studies in the developed world, low perceived need for treatment was by far the most prevalent impediment (21–23). Thus despite differences in actual proportions of those accessing mental health care, similar barriers are apparent across the developed and developing worlds.
Arguably the strongest barrier to treatment in the South African population involves the knowledge and beliefs about mental illness that aid recognition, management, or prevention. Studies investigating explanatory models of mental illness in Africa have revealed that depression, for example, is not seen as an illness but rather a result of psychological difficulties resulting from a number of external factors, such as poverty, alcoholism, or poor marital relations, which are highly prevalent in the developing world (46). The few such studies conducted in South Africa (34) revealed that psychosocial stress is cited more frequently than biological etiology as a cause of psychiatric disorders, and treatments for psychiatric disorders are often perceived as ineffective. Low mental health literacy may not only decrease perceived need for treatment but also lead to stigma and perceptions that treatment is ineffective (47,48).
Among participants who acknowledged the need for care, attitudinal barriers greatly outweighed structural barriers. This is consistent with the findings of studies in the developed world (11,24,25,30). Consistent with data from the United States, Canada, and the Netherlands, prevalent attitudinal barriers were the desire to handle the problem on one's own (32%) and the perception that treatment was ineffective (30%). However, the perception that the problem was not severe (61%) and thinking that the problem would get better (82%) were the most prevalent attitudinal barriers that emerged from the SASH data (24). The combination of these attitudinal barriers may contribute substantially to the well-documented delays between onset and treatment of mental disorders (49,50).
Although acknowledged to be a consequential problem for sufferers of mental illness (51), stigmatization was relatively infrequently reported in this study, a finding supported by other work in the developed world (24). One explanation for this might be that stigmatization leads patients to conceal their illness from relatives and acquaintances rather than serving as a deterrent to seeking treatment (52).
Structural barriers, although less frequently endorsed as impeding access to services, were still notable. As might be expected, responses about structural barriers differ depending on how health care services are funded and organized. For example, in one study poorer respondents in the United States were much more likely to report structural barriers than those in the Netherlands and Canada because they were often uninsured and therefore had to bear the cost of treatment (24). South Africa's ethnic populations have distinct socioeconomic profiles and cultural identities; health services are underfunded, fragmented, and vary greatly by geographical area (37–39). It is important that when attitudinal barriers are overcome, structural and system-level problems are not an additional barrier hindering appropriate access to mental health care.
With respect to mental health treatment dropout, the overall dropout rate (20%) found in this study mirrors rates reported in the United States (19%–22%) and Canada (17%–22%) (12–14). Compared with mental health treatment dropout rates, dropout rates from the general medical sector were higher among U.S. respondents. In contrast, lower rates have been reported among Canadian respondents (13,14). We found that the highest rates of discontinuation were from the CAM and human services sectors. As in prior work (53,54), previous mental health treatment decreased the risk of premature treatment dropout. With regard to timing of dropout, discontinuation rates were less for other mental health professionals during the initial visits and for psychiatrists during later visits. This may point to the ability of providers in particular service sectors to establish therapeutic relationships and encourage participation in continued mental health care. However, it may also reflect the availability of effective treatment as well as reimbursement by medical insurance for certain providers. This study supports the finding that later visits represent a higher-risk period for treatment dropout (14).
We did not find that gender and age were significantly associated with overall dropout, which is consistent with some data (14). However, we could not replicate findings from other studies that found that younger respondents, males, and nonwhites are at increased risk of early treatment dropout (11–13,53).
Factors influencing service utilization and discontinuation also included health insurance, income status, and the number of providers involved in a person's care. Consistent with the literature (12,14), the absence of health insurance increased the risk of treatment dropout after the first or second visits, particularly from the general medical treatment sectors, most likely because of out-of-pocket expenses of continued care. Patients with serious mental illness are often burdened by social and economic disadvantage, and the lack of health insurance frequently presents an obstacle to adequate mental health care (17). Low income has also been found to increase dropout rates (12).
When considering the influence of number of providers on treatment dropout, participants were less likely to drop out of treatment when three or four providers were involved in care. At later visits, there seemed to be a higher risk of treatment dropout from psychiatrists and the human services sector when three or more providers were involved in care. This may indicate the inability to afford multiple forms of care for extended periods. In contrast, other findings suggest that psychotherapy in addition to medication can reduce dropout rates (12,53). Adjunctive CAM has been associated with lower dropout rates (14). In contrast, our findings indicated that adjunctive CAM increased the odds of treatment dropout from the human services sector at later visits. An explanation may be that some individuals who sought treatment from traditional healers had milder forms of mental illness that may have shown early recovery (that is, a nonspecific placebo effect). Alternatively, this finding may indicate that participants, particularly those with more severe illness, perceived treatment from CAM or human services as ineffective or unsuited to their needs.
Type of psychopathology affected treatment dropout; namely, substance use disorders and mood disorders increased the risk of treatment dropout from the general medical and human services sectors, respectively, whereas anxiety disorders reduced the risk of treatment dropout from the general medical sector, although not significantly. This finding is consistent with other studies (13,14) and is of concern because substance use disorders tend to require long-term treatment. Type of service provider also influenced dropout rates; respondents were less likely to drop out of treatment from a psychiatrist or other mental health professional than from the general medical sector.
Several limitations deserve mention, including the relatively short period of treatment seeking that was assessed, exclusion of CAM from the treatment dropout predictors' analysis because of the small sample, and the possibility of recall bias. Predictors of dropout were also not examined by race and ethnicity, again owing to the small number of nonblack (in particular Indian and mixed race) treatment-seeking participants (2). Finally, the diagnoses indicated by the CIDI are based on criteria developed from Western concepts of mental illness and may not detect culture-bound syndromes found among indigenous groups in South Africa; also, they may underdiagnose conditions, such as anxiety and depression, among those with predominant somatic complaints rather than overt psychiatric symptoms. Notwithstanding these weaknesses, the findings of this study are useful because they provide the first national, population-level information on barriers to treatment and predictors of dropout among South Africans.
Conclusions
The low rates of treatment seeking and high dropout rates for common mental disorders among South Africans remain a major concern. Across all levels of disorder severity, low perceived treatment need and other attitudinal barriers were the major barriers to utilization of mental health services among those with common mental disorders. When respondents do seek treatment, there are obstacles at many levels that interfere with continuing care. To have an impact on treatment utilization patterns, more targeted strategies for educating the South African public about mental disorders, attitudinal barriers, and available treatment options must be coupled with comprehensive, affordable, and accessible health care, including substance rehabilitation services and improved patient-staff ratios. In addition, health care providers should be made aware of the attitudinal barriers to treatment seeking as well as the factors that increase the risk of treatment dropout.
1 : The South African Stress and Health (SASH) Study: 12-month and lifetime prevalence of common mental disorders. South African Medical Journal 99:339–344, 2009 Medline, Google Scholar
2 : Mental health service use among South Africans for mood, anxiety and substance use disorders. South African Medical Journal 99:346–352, 2009 Medline, Google Scholar
3 : Twelve-month treatment of psychiatric disorders in South Africa Stress and Health Study (World Mental Health Survey Initiative). Psychiatric Epidemiology 38:211–220, 2008 Google Scholar
4 : Population level unmet need for mental healthcare in Europe. British Journal of Psychiatry 190:299–306, 2007 Crossref, Medline, Google Scholar
5 : Past-year use of outpatient services for psychiatric problems in the National Comorbidity Survey. American Journal of Psychiatry 156:115–123, 1999 Link, Google Scholar
6 : The prevalence of treated and untreated serious mental disorders in five countries. Health Affairs 22(3):122–133, 2003 Crossref, Google Scholar
7 : Delay and failure in treatment seeking after first onset of mental disorders in the World Health Organization's World Mental Health Survey Initiative. World Psychiatry 6:177–185, 2007 Medline, Google Scholar
8 : Prevalence and treatment of mental disorders, 1990 to 2003. New England Journal of Medicine 24:2515–2523, 2005 Crossref, Google Scholar
9 WHO World Mental Health Survey Consortium: Prevalence, severity, and unmet need for treatment of mental disorders in the World Health Organization World Mental Health Surveys. JAMA 291:2581–2590, 2004 Crossref, Medline, Google Scholar
10 : Use of mental health services for anxiety, mood and substance disorders in 17 countries in the WHO World Mental Health Surveys. Lancet 370:841–850, 2007 Crossref, Medline, Google Scholar
11 : The prevalence and correlates of untreated serious mental illness. Health Services Research 36:987–1007, 2001 Medline, Google Scholar
12 : Dropping out of mental health treatment: patterns and predictors among epidemiological survey respondents in the United States and Ontario. American Journal of Psychiatry 159:845–851, 2002 Link, Google Scholar
13 : Mental health treatment dropout and its correlates in a general population sample. Medical Care 45:224–229, 2007 Crossref, Medline, Google Scholar
14 : Dropout from outpatient mental health care in the United States. Psychiatric Services 60:898–907, 2009 Link, Google Scholar
15 : Trends in contacts with mental health professionals and cost barriers to mental health care among adults with significant psychological distress in the United States: 1997–2002. American Journal of Public Health 95:2009–2014, 2005 Crossref, Medline, Google Scholar
16 : Overcoming barriers to reducing the burden of affective disorders. Biological Psychiatry 52:655–675, 2002 Crossref, Medline, Google Scholar
17 : Utilization of specialty mental health care among persons with severe mental illness: the roles of demographics, need, insurance and risk. Health Services Research 35:277–292, 2000 Medline, Google Scholar
18 : Income differences in persons seeking outpatient treatment for mental disorders. Archives of General Psychiatry 57:383–391, 2000 Crossref, Medline, Google Scholar
19 : Budget and financing of mental health services: baseline information on 89 countries from WHO's Project Atlas. Journal of Mental Health Policy and Economics 6:135–143, 2003 Medline, Google Scholar
20 : Understanding barriers to mental health service utilization for adolescents in rural Australia. Rural and Remote Health Journal 7:624–633, 2007 Medline, Google Scholar
21 : Perceived need for alcohol, drug and mental health treatment. Social Psychiatry and Psychiatric Epidemiology 41:480–487, 2006 Crossref, Medline, Google Scholar
22 : Attitudes and illness factors associated with low perceived need for depression treatment among adults. Social Psychiatry and Psychiatric Epidemiology 41:746–754, 2006 Crossref, Medline, Google Scholar
23 : Perceived need and help-seeking in adults with mood, anxiety or substance use disorders. Archives of General Psychiatry 59:77–94, 2002 Crossref, Medline, Google Scholar
24 : Perceived barriers of mental health service utilization in the United States, Ontario, and the Netherlands. Psychiatric Services 58:357–364, 2007 Link, Google Scholar
25 : Role of stigma and attitudes toward help-seeking from a general practitioner for mental health problems in a rural town. Australia and New Zealand Journal of Psychiatry 39:514–521, 2005 Crossref, Medline, Google Scholar
26 : Community attitudes toward and knowledge of mental illness in South Africa. Social Psychiatry and Psychiatric Epidemiology 38:715–719, 2003 Crossref, Medline, Google Scholar
27 : Perceptions of a South African schizophrenia population with regards to community attitudes towards their illness. Social Psychiatry and Psychiatric Epidemiology 41:619–623, 2006 Crossref, Medline, Google Scholar
28 : Attitudes towards and beliefs about schizophrenia in Xhosa families with affected probands. Curationis 25:69–73, 2002 Crossref, Medline, Google Scholar
29 : Internalized stigma, discrimination, and depression among men and women living with HIV/AIDS in Cape Town, South Africa. Social Science and Medicine 64:1823–1831, 2007 Crossref, Medline, Google Scholar
30 : Perceived barriers to mental health service use among individuals with mental disorders in the Canadian general population. Medical Care 44:192–195, 2006 Crossref, Medline, Google Scholar
31 : Use of mental health services in Chile. Psychiatric Services 55:71–76, 2004 Link, Google Scholar
32 : The barriers preventing effective treatment of South African patients with mental health problems. South African Psychiatry Review 9:249–260, 2006 Google Scholar
33 : Barriers to treatment among members of a mental health advocacy group in South Africa. Social Psychiatry and Psychiatric Epidemiology 37:483–487, 2002 Crossref, Medline, Google Scholar
34 : Mental health literacy: focus on developing countries. African Journal of Psychiatry 11:23–28, 2008 Crossref, Google Scholar
35 : Perspectives towards mental illness in people living with HIV/AIDS in the Western Cape of South Africa. AIDS Care, Feb 24, 2011, Epub ahead of print Medline, Google Scholar
36 : Race and psychiatric services in post-Apartheid South Africa: a preliminary study of psychiatrists' perceptions. International Journal of Social Psychiatry 50:18–24, 2004 Crossref, Medline, Google Scholar
37 : Focus on psychiatry in South Africa. British Journal of Psychiatry 178:382–386, 2001 Crossref, Medline, Google Scholar
38 : South African mental health process indicators. Journal of Mental Health Policy and Economics 4:9–16, 2001 Medline, Google Scholar
39 : Bed/population ratios in South African public sector mental health services. Social Psychiatry and Psychiatric Epidemiology 37:346–349, 2002 Crossref, Medline, Google Scholar
40 : Traditional healers in the treatment of common mental disorders in South Africa. Journal of Nervous and Mental Disease 197:434–441, 2009 Crossref, Medline, Google Scholar
41 : The World Mental Health (WMH) Survey Initiative Version of the World Health Organization (WHO) Composite International Diagnostic Interview (CIDI). International Journal of Methods in Psychiatric Research 13:61–98, 2004 Google Scholar
42 World Health Organization Manual of the International Statistical Classification of Diseases, Injuries and Causes of Death, 9th rev. Geneva, World Health Organization, 1992 Google Scholar
43 Diagnostic and Statistical Manual of Mental Disorders (DSM-IV), 4th ed. Washington, DC, American Psychiatric Association, 1994 Google Scholar
44 : Assessing psychiatric morbidity in primary care with the Sheehan Disability Scale. International Journal of Psychiatry in Medicine 27:93–105, 1997 Crossref, Medline, Google Scholar
45 : The Global Assessment Scale: a procedure for measuring overall severity of psychiatric disturbance. Archives of General Psychiatry 33:766–771, 1976 Crossref, Medline, Google Scholar
46 : Explanatory models of mental illness in Sub-Saharan Africa. Social Science and Medicine 40:1291–1298, 1995 Crossref, Medline, Google Scholar
47 : “Mental health literacy”: a survey of the public's ability to recognise mental disorders and their beliefs about the effectiveness of treatment. Medical Journal of Australia 166:182–186, 1997 Crossref, Medline, Google Scholar
48 : Research on mental health literacy: what we know and what we still need to know. Australian and New Zealand Journal of Psychiatry 40:3–5, 2006 Crossref, Medline, Google Scholar
49 WHO International Consortium in Psychiatric Epidemiology: cross-national comparisons of the prevalence and correlates of mental disorders. Bulletin of the World Health Organization 78:413–426, 2000 Medline, Google Scholar
50 : Failure and delay in initial treatment contact after first onset of mental disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry 26:603–613, 2005 Crossref, Google Scholar
51 : Stigmatisation of people with mental illnesses. British Journal of Psychiatry 177:4–7, 2000 Crossref, Medline, Google Scholar
52 : Mental illness stigma and willingness to seek mental health care in the European Union. Social Psychiatry and Psychiatric Epidemiology 45:705–712, 2010 Crossref, Medline, Google Scholar
53 : Factors predicting drop-out in community mental health centres. World Psychiatry 8:173–177, 2009 Crossref, Medline, Google Scholar
54 : Predictors of treatment discontinuity in outpatient mental health care. Social Psychiatry and Psychiatric Epidemiology 37:276–282, 2002 Crossref, Medline, Google Scholar