Skip to main content Accessibility help
×
×
Home

Information:

  • Access
  • Cited by 1
  • Cited by
    This article has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Wang, Yefeng Zhao, Yunpeng Bian, Jiang and Zhang, Rui 2018. Detecting Signals of Associations Between Dietary Supplement Use and Mental Disorders from Twitter. p. 53.

    ×

Actions:

      • Send article to Kindle

        To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

        Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

        Find out more about the Kindle Personal Document Service.

        Complementary and alternative medicine contacts by persons with mental disorders in 25 countries: results from the World Mental Health Surveys
        Available formats
        ×

        Send article to Dropbox

        To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

        Complementary and alternative medicine contacts by persons with mental disorders in 25 countries: results from the World Mental Health Surveys
        Available formats
        ×

        Send article to Google Drive

        To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

        Complementary and alternative medicine contacts by persons with mental disorders in 25 countries: results from the World Mental Health Surveys
        Available formats
        ×
Export citation

Abstract

Aims.

A substantial proportion of persons with mental disorders seek treatment from complementary and alternative medicine (CAM) professionals. However, data on how CAM contacts vary across countries, mental disorders and their severity, and health care settings is largely lacking. The aim was therefore to investigate the prevalence of contacts with CAM providers in a large cross-national sample of persons with 12-month mental disorders.

Methods.

In the World Mental Health Surveys, the Composite International Diagnostic Interview was administered to determine the presence of past 12 month mental disorders in 138 801 participants aged 18–100 derived from representative general population samples. Participants were recruited between 2001 and 2012. Rates of self-reported CAM contacts for each of the 28 surveys across 25 countries and 12 mental disorder groups were calculated for all persons with past 12-month mental disorders. Mental disorders were grouped into mood disorders, anxiety disorders or behavioural disorders, and further divided by severity levels. Satisfaction with conventional care was also compared with CAM contact satisfaction.

Results.

An estimated 3.6% (standard error 0.2%) of persons with a past 12-month mental disorder reported a CAM contact, which was two times higher in high-income countries (4.6%; standard error 0.3%) than in low- and middle-income countries (2.3%; standard error 0.2%). CAM contacts were largely comparable for different disorder types, but particularly high in persons receiving conventional care (8.6–17.8%). CAM contacts increased with increasing mental disorder severity. Among persons receiving specialist mental health care, CAM contacts were reported by 14.0% for severe mood disorders, 16.2% for severe anxiety disorders and 22.5% for severe behavioural disorders. Satisfaction with care was comparable with respect to CAM contacts (78.3%) and conventional care (75.6%) in persons that received both.

Conclusions.

CAM contacts are common in persons with severe mental disorders, in high-income countries, and in persons receiving conventional care. Our findings support the notion of CAM as largely complementary but are in contrast to suggestions that this concerns person with only mild, transient complaints. There was no indication that persons were less satisfied by CAM visits than by receiving conventional care. We encourage health care professionals in conventional settings to openly discuss the care patients are receiving, whether conventional or not, and their reasons for doing so.

Introduction

Complementary and alternative medicine (CAM) is not part of conventional medicine as practiced by medical doctors and allied health professionals, but is still part of how society deals with health problems, including mental disorders (Kessler et al. 2001a, b). The use of CAM in the USA increased during the nineties to an extent that the out-of-pocket payments relating to CAM use were equal to those for hospitalisations and physician services (Eisenberg et al. 1998). In low-income countries, conventional care resources are less often available and sometimes CAM even constitutes the only resource. For instance, up to 80% of the population in Africa depends on CAM for their primary source of care (WHO Factsheet 2003). CAM includes a wide list of self-care interventions, such as taking natural products or doing meditation, tai chi or yoga, participation in self-help groups through the internet, or visits to all sort of therapists and healers, and is often differentiated from religious providers (Kessler et al. 2001a, b).

A popular definition of alternative medical treatments is that they include treatments that are neither taught widely in medical schools nor generally available in hospitals (Rössler et al. 2007). However, it should be noted that nowadays many academic medical centres and affiliate institutions actually do teach CAM treatments and offer them in their teaching hospitals and clinics. Moreover, since at least in high-income countries most CAM is being utilised by persons who are also receiving conventional medical care, unconventional therapies are often a complement rather than an alternative to conventional medicine (Paramore, 1997; Druss & Rosenheck, 1999; Rössler et al. 2007) Its definition should also be regarded in the context of a country's traditions of practicing medicine. Importantly, the World Health Organisation distinguishes CAM from traditional medicine where the latter is based on the knowledge, skill and practices based on the theories, beliefs and experiences indigenous to different cultures, while CAM refers to health care practices that are not part of that country's own tradition or conventional medicine and are not fully integrated into the dominant health-care system (http://www.who.int/medicines/areas/traditional/definitions/en). As a result, any operationalisation of CAM should be viewed as time- and culture-dependent. CAM should also be regarded in relation to spiritual-religious caregivers. Access to religious advisors does not require referral and is free of charge, and as a result for some persons the only available resource. In a recent publication on the World Mental Health Surveys data (Kovess-Masfety et al. 2017), it was shown that religious advisors play an important role in mental health care and that religious attitudes are the strongest drivers of religious advisors usage. Some of the interventions employed by religious caregivers might classify as CAM, but others not. Therefore, in the present paper, we excluded religious advisors from our definition of CAM.

Mental disorders are among the strongest contributors to the global burden of disease, and conventional therapies are not always effective (Turner et al. 2008; Cuijpers et al. 2010, 2011). In the USA it has been observed that as much as 21.3% of CAM users have mental disorders, and that many CAM users with mental disorders also receive some form of conventional care (Unützer et al. 2000) and that 9.8% of persons reporting a mental disorder made a CAM visit (Druss & Rosenheck, 2000). Several studies, all conducted in high-income countries, have found that CAM use depends on the kind and severity of disorder: anxiety and mood disorders, in particular, have been associated with increased CAM use, but also the presence of alcohol disorder (particularly with self-help groups) (Druss & Rosenheck, 2000; Honda & Jacobson, 2005; Bystritsky et al. 2012). It has been suggested that CAM use is concentrated among persons with relatively mild and transient forms of distress (Druss & Rosenheck, 2000).

For clinicians working in conventional care settings, it is important to know whether the patients they are seeing are also receiving CAM and how CAM and conventional services can be coordinated in order to prevent undesirable interactions between treatments (Wahlström et al. 2008). However, to date, only very limited data are available, and there is no report on cross-national epidemiological data regarding CAM contacts in countries of varying income levels and regions across the world (Hunt et al. 2010). The aim of this study was to provide data on CAM contacts by persons with a past 12-month mental disorder, comparing different income level countries, mental disorder types, severity levels and treatment settings.

Method

Samples

Data came from the World Mental Health Surveys (Kessler & Ustün, 2004). The WHO Composite International Diagnostic Interview (CIDI) version 3.0 was administered in 28 WMH surveys in 25 countries. These included 12 countries classified by the World Bank as low or middle income (Brazil, Bulgaria, Colombia, Iraq, Lebanon, Mexico, Nigeria, Peoples Republic of China [PRC], Peru, Romania, South Africa and Ukraine) and 13 high income (Belgium, France, Germany, Israel, Italy, Japan, the Netherlands, New Zealand, Northern Ireland, Poland, Portugal, Spain and the USA). Most surveys used stratified multistage clustered area probability household sampling with no substitution for non-participants. Data collection took place between 2001 and 2012, and response rates ranged from 45.9 to 97.2%, with an average of 70.1% (Table 1). Classification of country income categories was based on the World Bank criteria at the time of each survey which explains the different income category of the national Colombian survey and the regional Medellin survey in Colombia (The World Bank, 2009).

Table 1. World Mental Health sample characteristics by World Bank Income categoriesa

a The World Bank (2009). Some of the WMH countries have moved into new income categories since the surveys were conducted. The income groupings above reflect the status of each country at the time of data collection. The current income category of each country is available at the preceding URL.

b NSMH (The Colombian National Study of Mental Health); IMHS (Iraq Mental Health Survey); NSMHW (The Nigerian Survey of Mental Health and Wellbeing); B-WMH (The Beijing World Mental Health Survey); S-WMH (The Shanghai World Mental Health Survey); EMSMP (La Encuesta Mundial de Salud Mental en el Peru); CMDPSD (Comorbid Mental Disorders during Periods of Social Disruption); NSHS (Bulgaria National Survey of Health and Stress); MMHHS (Medellín Mental Health Household Study); LEBANON (Lebanese Evaluation of the Burden of Ailments and Needs of the Nation); M-NCS (The Mexico National Comorbidity Survey); RMHS (Romania Mental Health Survey); SASH (South Africa Health Survey); ESEMeD (The European Study Of The Epidemiology Of Mental Disorders); NHS (Israel National Health Survey); WMHJ2002-2006 (World Mental Health Japan Survey); NZMHS (New Zealand Mental Health Survey); NISHS (Northern Ireland Study of Health and Stress); EZOP (Epidemiology of Mental Disorders and Access to Care Survey); NMHS (Portugal National Mental Health Survey); PEGASUS-Murcia (Psychiatric Enquiry to General Population in Southeast Spain-Murcia);NCS-R (The US National Comorbidity Survey Replication).

c Most WMH surveys are based on stratified multistage clustered area probability household samples in which samples of areas equivalent to counties or municipalities in the US were selected in the first stage followed by one or more subsequent stages of geographic sampling (e.g., towns within counties, blocks within towns, households within blocks) to arrive at a sample of households, in each of which a listing of household members was created and one or two people were selected from this listing to be interviewed. No substitution was allowed when the originally sampled household resident could not be interviewed. These household samples were selected from Census area data in all countries other than France (where telephone directories were used to select households) and the Netherlands (where postal registries were used to select households). Several WMH surveys (Belgium, Germany, Italy, Poland, Spain-Murcia) used municipal, country resident or universal health-care registries to select respondents without listing households. The Japanese sample is the only totally un-clustered sample, with households randomly selected in each of the 11 metropolitan areas and one random respondent selected in each sample household. 18 of the 28 surveys are based on nationally representative household samples.

d The response rate is calculated as the ratio of the number of households in which an interview was completed to the number of households originally sampled, excluding from the denominator households known not to be eligible either because of being vacant at the time of initial contact or because the residents were unable to speak the designated languages of the survey. The weighted average response rate is 70.1%.

e People's Republic of China.

f For the purposes of cross-national comparisons, we limit the sample to those 18+.

g Colombia moved from the ‘lower and lower-middle income’ to the ‘upper-middle income’ category between 2003 (when the Colombian National Study of Mental Health was conducted) and 2010 (when the Medellin Mental Health Household Study was conducted), hence Colombia's appearance in both income categories. For more information, please see footnote a.

All WMH surveys were conducted face-to-face by lay interviewers who had received standardised training. Standardised translation, back-translation, harmonization and quality control procedures were applied in all of the participating survey sites (Pennell et al. 2008). Informed consent was obtained according to protocols endorsed by local Institutional Review Boards.

Measures

All respondents completed Part 1 of the WHO Composite International Diagnostic Interview (CIDI) (Kessler & Ustün, 2004) which assesses lifetime DSM-IV mood disorders (major depressive disorder and/or dysthymia, bipolar disorder), anxiety disorders (panic disorder, agoraphobia, specific phobia, social phobia, generalised anxiety disorder, post-traumatic stress disorder), substance use disorders (alcohol and drug abuse with or without dependence) and impulse control disorder (intermittent explosive disorder). Diagnostic hierarchy and organic exclusion rules were applied for all diagnoses other than substance abuse (with or without dependence). A blinded clinical reappraisal study using the Structured Clinical Interview for DSM-IV (SCID) (First et al. 2002) found good diagnostic concordance between CIDI and SCID diagnoses (Haro et al. 2006).

Part I data were weighted to adjust for the differential probability of being selected and the socio-demographic and geographic structure of each sample. Respondents identified with a disorder during the Part I assessment and an additional probability sub-sample were administered Part II of the survey, which assessed a number of other disorders and correlates. Further weightings were applied to the Part II data to adjust for the differential selection procedure and to match base population distributions on socio-demographic and geographic data.

Care utilisation

Respondents who met criteria for a particular disorder were asked at the end of the diagnostic section whether they had ever sought professional treatment for that disorder and, if so, at what age they first sought this treatment. After the disorder sections, one section of the CIDI was devoted specifically to questions on the use of services for mental health problems. First, respondents were asked if they had previously consulted anyone (medical doctors, nurses, psychologists, social workers, spiritual advisers, herbalists and any other healing professionals) for a mental health problem during the past year. Persons reporting any contact with a provider for a mental health problem were then asked to select whom they had consulted from a list of health professionals (including psychiatrists; other mental health professionals; general practitioners; other medical specialists; other health professionals) and non-health care professionals.

In accordance with previous reports (e.g. Wang et al. 2007; Gureje et al. 2015), services were divided into the following sectors: mental health specialty (psychiatrist, psychologist, other mental health professional in any setting, social worker or counsellor in a mental health specialty setting, use of a mental health hotline); general medical (primary care doctor, other general medical doctor, nurse, any other health professional not previously mentioned); human services (religious or spiritual advisor, social worker, or counsellor in any setting other than a specialty mental health setting); and complementary and alternative medicine (any other type of healer such as a herbalist, chiropractor or spiritualist, participation in an internet support group, participation in a self-help group). With respect to CAM, the latter part of the definition (internet support group or self-help group), however, was not assessed in the countries involved in the ESEMeD study (i.e. six of the European samples: Belgium, France, Germany, Italy, Netherlands, Spain).

Satisfaction with the used services was measured in 16 of the surveys (part-II sample N = 49 373: USA, Mexico, Brazil, Colombia, Shenzhen, Peru, Medellin, Japan, Israel, New Zealand, Romania, Northern Ireland, Portugal, Poland, Murcia and Iraq). In these surveys, participants were asked if they were very satisfied, satisfied, neither satisfied nor dissatisfied, dissatisfied or very dissatisfied. This was done with respect to conventional care and contacts with an alternative healer (e.g. herbalist, chiropractor, spiritualist). Although there was no linkage between the exact disorder and CAM contacts, we limited both CAM contacts and disorders to past 12 months occurrence.

Statistical analysis

Cross-tabs were calculated to analyse CAM use between low and middle, v. high-income group countries, as well as between disorder types and severity levels. Cross-tabs in the subsample of participants that received either CAM, conventional care or both were used to estimate the percentages of CAM-users that were satisfied or very satisfied with the received care and to compare this percentage to that for the other received care. The main analyses were run for CAM including internet and self-help use, in accordance with previous WMH studies. Sensitivity analyses were performed restricting CAM to the use of services by alternative healers only, to get more insight into the use of this specific subcategory of CAM (see supplementary Tables). For these analyses, we only used the samples from Belgium, France, Germany, Italy, Netherlands, Spain as in these samples a more narrow operationalisation was applied.

All analyses were weighted and because the data were clustered, standard errors were estimated using the Taylor series linearization method, using cluster, strata and weight variables with procedures for survey statistics in SAS 9.

Results

In total, 664 (3.6%) persons with a 12-month DSM-IV disorder reported visiting a CAM provider in the past year (Table 2). This proportion was lower in low- and middle-income group countries (2.3%; n  =  179) and twice as high in high income group countries (4.6%; n  =  485). CAM contacts did not vary widely across disorder types, i.e. from 3.9% (460) for anxiety disorders to 5.0% (n  =  370) for mood disorders. About two-thirds of all CAM contacts (2.4/3.6%) was reported by persons also receiving conventional care, which was about half (1.2/2.3%) in low to middle-income countries and close to three quarters (3.3/4.6%) in high-income countries.

Table 2. CAM contacts among subjects with a 12-month DSM-IV disorder, ordered by disorder type

a Other sectors are: any health care (including specialised mental health care and general health care) and human services.

b Due to a skip-error in the CIDI, substance-use was underestimated in the ESEMeD countries resulting in a smaller number of cases in this group.

c Attention Deficit Disorder, Conduct Disorder and Oppositional Defiant Disorder were only assessed in subjects aged 18–44 to prevent recall bias.

In persons with mental disorders receiving conventional care, the percentage of CAM contacts was substantially higher. Of those treated by a GP, 8.6% reported CAM contacts. The percentage of CAM contacts was 11.7% in persons treated by a mental health specialist, and 17.8% in persons treated by a human services professional (Table 3). These percentages were consistently higher in high-income countries and did not consistently differ across disorder types.

Table 3. Percentages of 12-month CAM contacts in subjects that received other types of care during the past 12 months for different disorder classes

a Due to a skip-error in the CIDI, substance-use was underestimated in the ESEMeD countries resulting in a smaller number of cases in this group.

b ADD, CD and ODD were only assessed in subjects aged 18–44 to prevent recall bias.

The percentage of CAM contacts was consistently higher as a function of increasing severity of the mental health disorder. Whereas in persons with mild to moderate severity levels, the overall proportion of CAM contacts was 2.6%, this rose to 6.4% in persons with a severe disorder. This association was observed in all treatment settings and country income groups. In persons with severe mental disorders from high-income countries, as much as 80% (6.8/8.5%) of persons reporting CAM contacts also received conventional care. This proportion was lower in low- and middle-income countries and in persons with mild to moderate disorder severity (Table 4).

Table 4. Percentages of CAM contacts among those with a 12-month disorder, ordered by severity per income group

Highly similar patterns as described above were observed for each of the different disorder types, with higher proportions of CAM contacts among those with high severity levels, and higher proportions of CAM contacts in persons already receiving treatment in conventional medical settings. About one out of every seven persons (14.0%) with a severe mood disorder who was seen by a mental health specialist also reported CAM contacts. This ratio is one out of 6 (16.2%) for anxiety and one out of 4–5 (22.5%) for behavioural disorders (Table 5).

Table 5. Percentages of CAM contacts among those with a 12-month disorder, ordered by severity for each disorder group

a Due to a skip-error in the CIDI, substance-use was underestimated in the ESEMeD countries resulting in a smaller number of cases in this group.

b ADD, CD and ODD were only assessed in subjects aged 18–44 to prevent recall bias.

Satisfaction with the services of alternative healers was investigated in a subsample of participants that reported any 12-month disorder and having received services from an alternative healer. Of those reporting only this particular service in the past 12-months (n  =  78) 82.1% were ‘satisfied/very satisfied’ with this service (Table 6). Of those 12-month disorder cases reporting both services from an alternative healer and from another provider (n  =  130), 78.3% reported being ‘satisfied/very satisfied’ with the services by the alternative healer and 75.6% reported being ‘satisfied/very satisfied’ with at least one of the other received services.

Table 6. Satisfaction with 12-month services among persons with a 12-month DSM-IV disorder that used CAM or other services

a Those reporting that they were ‘satisfied’ or ‘very satisfied’ with the services provided by the CAM provider.

b Satisfaction with services was assessed only in NCSR, Mexico, Brazil, Colombia, Shenzhen, Peru, Medellin, Japan, Israel, New Zealand, Romania, Northern Ireland, Portugal, Poland, Murcia and Iraq (part-2 sample n  =  49 373).

c Those reporting that they were satisfied or very satisfied with the services of at least one other service provider (specialty mental health, general medical, human services).

d Only includes those, who saw a CAM provider (i.e. an alternative healer) and were assessed about their satisfaction about this provider (those reporting online support groups and self-help groups not included).

Sensitivity analyses restricting CAM contacts to alternative healers only (excluding internet support and self-help groups) revealed significantly lower levels of care utilization (1.5% of those with any 12-month mental disorder, see supplementary Tables) suggesting most of the contacts took place in the context of internet support groups or self-help groups. The findings that CAM use was higher in high-income level countries, higher in persons with more severe mental disorders and higher in persons that received conventional care maintained when applying this more narrow definition of CAM.

Discussion

When estimating the proportion of persons visiting CAM providers among persons with mental disorders (3.6%), we consistently found the following three factors to be important. First, CAM contacts among persons with mental disorders are dependent on the income level of a country, with a two-fold increased proportion of CAM contacts in high-income group countries (4.6%) than in low-income group countries (2.3%). Second, most CAM contacts by persons with mental disorders are reported by persons also receiving conventional care. In patients with mental disorders reporting conventional care, about 8–18% reported CAM use as well. Third, CAM contacts are more common in persons with higher levels of severity of mental disorder severity than in those with lower levels of severity. These results confirm that CAM contacts should be considered as a complement to conventional treatment, relatively common in Western societies, in persons already in some form of treatment. It challenges the idea that CAM contacts are more often used for mild complaints. Our finding that in low income countries persons with mental disorders are less often having CAM contacts than in high income countries may be due to the fact that we restricted the analyses to contacts (while excluded self-care), but it may also reflect a stronger tendency to consider CAM as part of conventional care in low-income countries.

Our data suggest that mental health specialists can expect that about one out of seven persons with severe mood disorders (14.0%), one out of six with severe anxiety (16.2%) and one out of four–five with severe behavioural disorders (22.5%) are also visiting CAM providers, which is line with recent estimates, for instance for depression and anxiety (Hansen & Kristoffersen, 2016). There are several reasons why these figures are relevant. First, side effects of CAM therapies may occur when taken on their own, but there may also be desirable and undesirable interactions between treatments in conventional and CAM care (Walter & Rey, 1999). Several studies found that about two-thirds of persons receiving CAM in the past year did not disclose this information to their medical doctor (Eisenberg et al. 2001; Canter & Ernst, 2004; Thomson et al. 2012). This may be in part result because conventional medicine and CAM reflect different ‘schools of thought’. In conventional medicine, the scientific evidence base – a theory compatible with insights from the natural sciences and empirical data to support this theory – is considered to be the primary prerequisite for any treatment to be given. This may be different for CAM services (Gelenberg, 2010; Anlauf et al. 2015), for which the scientific evidence base is much less strong (Freeman et al. 2010; Melzer et al. 2013; Ravindran & da Silva, 2013). However, apart from the actual scientific knowledge base, negative attitudes of therapists toward CAM may be even more important (Ditte et al. 2011). There is a low probability of direct communication between conventional and unconventional therapists (37), and patients themselves are also not likely willing to disclose information regarding the use of unconventional services. This appears to be due to fear of disapproval but also to concerns about their doctor's ability to integrate CAM therapy with conventional treatment (Eisenberg et al. 2001). In recent years there has been significant and steady progress in implementing, regulating and managing CAM in most regions of the world (http://www.who.int/traditional-complementary-integrative-medicine/publications/trm_strategy14_23/en/). The results of the present study suggest that efforts to integrate conventional and unconventional care should be encouraged, as many persons treated in conventional care settings, and particularly those with severe complaints, are using CAM as a complement to conventional care.

We found that overall 82.1% of respondents reporting a CAM visit only, were satisfied. Of persons reporting both CAM and conventional care, comparable proportions were satisfied with either CAM (78.3%) or conventional care (75.6%). These data suggest that patients rate the usefulness of unconventional therapies at least similarly to conventional therapies, which is in line with the literature (Kessler et al. 2001a, b; Demling et al. 2002; D'Silva et al. 2012). At the same time, there are no indications that persons with mental health problems that are using CAM are extremely dissatisfied with conventional care, but seem to use both conventional and unconventional care option because of the severity of their complaints. Taken together, our findings thus underline the importance of addressing the care needs of persons using both conventional and unconventional care.

There are several limitations that should be considered when interpreting our findings. First of all, all data regarding care utilisation are self-reported and are not necessarily related to the disorder detected with the CIDI interview. We minimised the bias introduced by these study characteristics by selecting persons with a 12-month DSM-IV diagnosis while using the same 12-month framework for services use. Secondly, CAM was operationalised as care by herbalists, chiropractors, spiritualists, participation in an Internet support group, or participation in a self-help group except in the six European countries where these last two categories were not proposed. Our sensitivity analyses showed that considerably lower utilisation levels (1.5%) are found when restricting CAM contacts to alternative healers only, but that all patterns (more utilisation in higher income countries, severe disorders and in those receiving conventional care) were highly similar to the broader definition. We used a definition that includes internet support groups and self-help groups, although this definition was not used in a subset of six countries. The overall figure of 3.6% would have been slightly higher if all samples had included this definition, and particularly in the high-income countries, further stressing the differences between the country income levels. While this definition is in line with several previous reports, others included care that is explicitly based on non-Western theoretical models, such as Chinese medicine, acupuncture and homeopathy. We did not distinguish further between subtypes, as this would have resulted in cell numbers that were too small. Also, we did not include religious or spiritual advisors in our definition of CAM, which is in accordance with previous work on WMH data (e.g. Wang et al. 2007). Thirdly, this survey did not include self-care, such as use of natural products and yoga, which have particularly high prevalence rates in high-income countries. Taken together, these definition issues might explain the difference with very high prevalence numbers found by some (e.g 42% (2)), while being remarkably consistent with others using practitioner-based CAM as definition. For instance in the study by Druss and Rosenheck (Druss & Rosenheck, 2000), it was found that a total of 9.8% of respondents with mental disorders visited a CAM provider in the last 12 month, and 4.5% visited a CAM provider specifically to treat the mental condition. Fourth, the pooling of the countries in two global categories is putting together countries where these practices may be very different. Still, this joining of countries was necessary in order to retain sufficient numbers of subjects to warrant reliable results. Finally, as the different surveys have been conducted over a fairly long period of time, changing trends in use of CAM may have had some effects on the estimates we found. However, while all of the abovementioned limitations may have had some impact on the estimated rates, it is unlikely that they have affected the main conclusions of this paper regarding the comparisons in CAM contacts.

To conclude, our findings suggest that in persons with mental disorders, particularly among those with greater severity and in persons already receiving conventional care, contacts with CAM providers are relatively common. We, therefore, encourage health care professionals in conventional settings to discuss with their patients their care needs and the care they are already receiving either from conventional or unconventional therapists, in particular with patients reporting severe complaints.

Group Information: The WHO World Mental Health Survey collaborators are Sergio Aguilar-Gaxiola, MD, PhD, Ali Al-Hamzawi, MD, Mohammed Salih Al-Kaisy, MD, Jordi Alonso, MD, PhD, Laura Helena Andrade, MD, PhD, Corina Benjet, PhD, Guilherme Borges, ScD, Evelyn J. Bromet, PhD, Ronny Bruffaerts, PhD, Brendan Bunting, PhD, Jose Miguel Caldas de Almeida, MD, PhD, Graca Cardoso, MD, PhD, Alfredo H. Cia, MD, Somnath Chatterji, MD, Louisa Degenhardt, PhD, Giovanni de Girolamo, MD, Peter de Jonge, PhD, Koen Demyttenaere, MD, PhD, John Fayyad, MD, Silvia Florescu, MD, PhD, Oye Gureje, PhD, DSc, FRCPsych, Josep Maria Haro, MD, PhD, Yanling He, MD, Hristo Hinkov, MD, Chi-yi Hu, PhD, MD, Yueqin Huang, MD, MPH, PhD, Aimee Nasser Karam, PhD, Elie G. Karam, MD, Norito Kawakami, MD, DMSc, Ronald C. Kessler, PhD, Andrzej Kiejna, MD, PhD, Viviane Kovess-Masfety, MD, PhD, Sing Lee, MBBS, Jean-Pierre Lepine, MD, Daphna Levinson, PhD, John McGrath, PhD, Maria Elena Medina-Mora, PhD, Jacek Moskalewicz, DrPH, Fernando Navarro-Mateu, MD, PhD, Beth-Ellen Pennell, MA, Marina Piazza, MPH, ScD, Jose Posada-Villa, MD, Kate M. Scott, PhD, Tim Slade, PhD, Juan Carlos Stagnaro, MD, PhD, Dan J. Stein, FRCPC, PhD, Margreet ten Have, PhD, Yolanda Torres, MPH, Maria Carmen Viana, MD, PhD, Harvey Whiteford, PhD, David R. Williams, MPH, PhD, Bogdan Wojtyniak, ScD.

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/S2045796017000774

Conflict of interest

In the past 3 years, Dr Kessler received support for his epidemiological studies from Sanofi Aventis; was a consultant for Johnson & Johnson Wellness and Prevention, Sage Pharmaceuticals, Shire, Takeda; and served on an advisory board for the Johnson & Johnson Services Inc. Lake Nona Life Project. Kessler is a co-owner of DataStat, Inc., a market research firm that carries out healthcare research.

SEL received consulting fees from Lundbeck, not connected to this research.

Funding support

The World Health Organization World Mental Health (WMH) Survey Initiative is supported by the National Institute of Mental Health (NIMH; R01 MH070884), the John D. and Catherine T. MacArthur Foundation, the Pfizer Foundation, the US Public Health Service (R13-MH066849, R01-MH069864 and R01 DA016558), the Fogarty International Center (FIRCA R03-TW006481), the Pan American Health Organization, Eli Lilly and Company, Ortho-McNeil Pharmaceutical Inc., GlaxoSmithKline, and Bristol-Myers Squibb. We thank the staff of the WMH Data Collection and Data Analysis Coordination Centres for assistance with instrumentation, fieldwork and consultation on data analysis. None of the funders had any role in the design, analysis, interpretation of results, or preparation of this paper. The views and opinions expressed in this report are those of the authors and should not be construed to represent the views of the World Health Organization, other sponsoring organizations, agencies, or governments.

The São Paulo Megacity Mental Health Survey is supported by the State of São Paulo Research Foundation (FAPESP) Thematic Project Grant 03/00204-3. The Brazilian Council for Scientific and Technological Development supports Dr Laura Andrade (CNPq Grant # 307623/2013-0). The Bulgarian Epidemiological Study of common mental disorders EPIBUL is supported by the Ministry of Health and the National Center for Public Health Protection. The Chinese World Mental Health Survey Initiative is supported by the Pfizer Foundation. The Shenzhen Mental Health Survey is supported by the Shenzhen Bureau of Health and the Shenzhen Bureau of Science, Technology, and Information. The Colombian National Study of Mental Health (NSMH) is supported by the Ministry of Social Protection. The Mental Health Study Medellín – Colombia was carried out and supported jointly by the Center for Excellence on Research in Mental Health (CES University) and the Secretary of Health of Medellín.The ESEMeD project is funded by the European Commission (Contracts QLG5-1999-01042; SANCO 2004123, and EAHC 20081308), (the Piedmont Region (Italy)), Fondo de Investigación Sanitaria, Instituto de Salud Carlos III, Spain (FIS 00/0028), Ministerio de Ciencia y Tecnología, Spain (SAF 2000-158-CE), Departament de Salut, Generalitat de Catalunya, Spain, Instituto de Salud Carlos III (CIBER CB06/02/0046, RETICS RD06/0011 REM-TAP), and other local agencies and by an unrestricted educational grant from GlaxoSmithKline. Implementation of the Iraq Mental Health Survey (IMHS) and data entry was carried out by the staff of the Iraqi MOH and MOP with direct support from the Iraqi IMHS team with funding from both the Japanese and European Funds through United Nations Development Group Iraq Trust Fund (UNDG ITF). The Israel National Health Survey is funded by the Ministry of Health with support from the Israel National Institute for Health Policy and Health Services Research and the National Insurance Institute of Israel. The World Mental Health Japan (WMHJ) Survey is supported by the Grant for Research on Psychiatric and Neurological Diseases and Mental Health (H13-SHOGAI-023, H14-TOKUBETSU-026, H16-KOKORO-013) from the Japan Ministry of Health, Labour and Welfare. The Lebanese Evaluation of the Burden of Ailments and Needs Of the Nation (L.E.B.A.N.O.N.) is supported by the Lebanese Ministry of Public Health, the WHO (Lebanon), National Institute of Health / Fogarty International Center (R03 TW006481-01), anonymous private donations to IDRAAC, Lebanon, and unrestricted grants from, Algorithm, AstraZeneca, Benta, Bella Pharma, Eli Lilly, Glaxo Smith Kline, Lundbeck, Novartis, OmniPharma, Pfizer, Phenicia, Servier, UPO. The Mexican National Comorbidity Survey (MNCS) is supported by The National Institute of Psychiatry Ramon de la Fuente (INPRFMDIES 4280) and by the National Council on Science and Technology (CONACyT-G30544- H), with supplemental support from the PanAmerican Health Organization (PAHO). Te Rau Hinengaro: The New Zealand Mental Health Survey (NZMHS) is supported by the New Zealand Ministry of Health, Alcohol Advisory Council, and the Health Research Council. The Nigerian Survey of Mental Health and Wellbeing (NSMHW) is supported by the WHO (Geneva), the WHO (Nigeria), and the Federal Ministry of Health, Abuja, Nigeria. The Northern Ireland Study of Mental Health was funded by the Health & Social Care Research & Development Division of the Public Health Agency. The Peruvian World Mental Health Study was funded by the National Institute of Health of the Ministry of Health of Peru. The Polish project Epidemiology of Mental Health and Access to Care –EZOP Project (PL 0256) was supported by Iceland, Liechtenstein and Norway through funding from the EEA Financial Mechanism and the Norwegian Financial Mechanism. EZOP project was co-financed by the Polish Ministry of Health. The Portuguese Mental Health Study was carried out by the Department of Mental Health, Faculty of Medical Sciences, NOVA University of Lisbon, with collaboration of the Portuguese Catholic University, and was funded by Champalimaud Foundation, Gulbenkian Foundation, Foundation for Science and Technology (FCT) and Ministry of Health. The Romania WMH study projects ‘Policies in Mental Health Area’ and ‘National Study regarding Mental Health and Services Use’ were carried out by National School of Public Health & Health Services Management (former National Institute for Research & Development in Health), with technical support of Metro Media Transilvania, the National Institute of Statistics-National Centre for Training in Statistics, SC. Cheyenne Services SRL, Statistics Netherlands and were funded by Ministry of Public Health (former Ministry of Health) with the supplemental support of Eli Lilly Romania SRL. The South Africa Stress and Health Study (SASH) is supported by the US National Institute of Mental Health (R01-MH059575) and National Institute of Drug Abuse with supplemental funding from the South African Department of Health and the University of Michigan. The Psychiatric Enquiry to General Population in Southeast Spain – Murcia (PEGASUS-Murcia) Project has been financed by the Regional Health Authorities of Murcia (Servicio Murciano de Salud and Consejería de Sanidad y Política Social) and Fundación para la Formación e Investigación Sanitarias (FFIS) of Murcia. The Ukraine Comorbid Mental Disorders during Periods of Social Disruption (CMDPSD) study is funded by the US National Institute of Mental Health (RO1-MH61905). The US National Comorbidity Survey Replication (NCS-R) is supported by the National Institute of Mental Health (NIMH; U01-MH60220) with supplemental support from the National Institute of Drug Abuse (NIDA), the Substance Abuse and Mental Health Services Administration (SAMHSA), the Robert Wood Johnson Foundation (RWJF; Grant 044708), and the John W. Alden Trust.

GT is supported by the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care South London at King's College London Foundation Trust. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. GT acknowledges financial support from the Department of Health via the National Institute for Health Research (NIHR) Biomedical Research Centre and Dementia Unit awarded to South London and Maudsley NHS Foundation Trust in partnership with King's College London and King's College Hospital NHS Foundation Trust. GT is supported by the European Union Seventh Framework Programme (FP7/2007-2013) Emerald project. SEL currently holds a Starting Grant from the European Research Council (337673).

A complete list of all within-country and cross-national WMH publications can be found at http://www.hcp.med.harvard.edu/wmh/.

Data availability

The data of the WHO World Mental Health Surveys are stored centrally by the Department of Health Care Policy, Harvard Medical School, Boston, USA (http://www.hcp.med.harvard.edu/wmh/ and analysed by remote access by a trained analyst (KW). Given the complexity of the multisample dataset, access to the raw dataset to untrained researchers is not advised. For specific data requests, please contact the first or last author.

References

Anlauf, M, Hein, L, Hense, HW, Köbberling, J, Lasek, R, Leidl, R, Schöne-Seifert, B (2015). Complementary and alternative drug therapy versus science-oriented medicine. German Medical Science 23, 13.
Bystritsky, A, Hovav, S, Sherbourne, C, Stein, MB, Rose, RD, Campbell-Sills, L, Golinelli, D, Sullivan, G, Craske, MG, Roy-Byrne, PP (2012). Use of complementary and alternative medicine in a large sample of anxiety patients. Psychosomatics 53, 266272.
Canter, PH, Ernst, E (2004). Herbal supplement use by persons aged over 50 years in Britain: frequently used herbs, concomitant use of herbs, nutritional supplements and prescription drugs, rate of informing doctors and potential for negative interactions. Drugs and Aging 21, 597605.
Cuijpers, P, Smit, F, Bohlmeijer, E, Hollon, SD, Andersson, G (2010). Efficacy of cognitive-behavioural therapy and other psychological treatments for adult depression: meta-analytic study of publication bias. British Journal of Psychiatry 96, 173178.
Cuijpers, P, Clignet, F, van Meijel, B, van Straten, A, Li, J, Andersson, G (2011). Psychological treatment of depression in inpatients: a systematic review and meta-analysis. Clinical Psychology Review 31, 353360.
Demling, JH, Neubauer, S, Luderer, HJ, Wörthmüller, M (2002). A survey on psychiatric patients’ use of non-medical alternative practitioners: incidence, methods, estimation, and satisfaction. Complementary Therapy in Medicine 10, 193201.
Ditte, D, Schulz, W, Ernst, G, Schmid-Ott, G (2011). Attitudes towards complementary and alternative medicine among medical and psychology students. Psychology, Health & Medicine 16, 225237.
Druss, BG, Rosenheck, RA (1999). Association between use of unconventional therapies and conventional medical services. Journal of the American Medical Association 282, 651656.
Druss, BG, Rosenheck, RA (2000). Use of practitioner-based complementary therapies by persons reporting mental conditions in the United States. Archives of General Psychiatry 57, 708714.
D'Silva, S, Poscablo, C, Habousha, R, Kogan, M, Kligler, B (2012). Mind-body medicine therapies for a range of depression severity: a systematic review. Psychosomatics 53, 407423.
Eisenberg, DM, Davis, RB, Ettner, SL, Appel, S, Wilkey, S, Van Rompay, M, Kessler, RC (1998). Trends in alternative medicine use in the United States, 1990–1997: results of a follow-up national survey. Journal of the American Medical Association 280, 15691575.
Eisenberg, DM, Kessler, RC, Van Rompay, MI, Kaptchuk, TJ, Wilkey, SA, Appel, S, Davis, RB (2001). Perceptions about complementary therapies relative to conventional therapies among adults who use both: results from a national survey. Annals of Internal Medicine 135, 344351.
First, MB, Spitzer, RL, Gibbon, M, Williams, JBW (2002). Structured Clinical Interview for DSM-IV Axis I Disorders, Research Version, Non-patient Edition (SCID-I/NP), Biometrics Research, New York State Psychiatric Institute: New York.
Freeman, MP, Mischoulon, D, Tedeschini, E, Goodness, T, Cohen, LS, Fava, M, Papakostas, GI (2010). Complementary and alternative medicine for major depressive disorder: a meta-analysis of patient characteristics, placebo-response rates, and treatment outcomes relative to standard antidepressants. Journal of Clinical Psychiatry 71, 682688.
Gelenberg, AJ (2010). Complementary and alternative medicine in psychiatry. Journal of Clinical Psychiatry 71, 667668.
Gureje, O, Nortje, G, Makanjuola, V, Oladeji, B, Seedat, S, Jenkins, R (2015). The role of global traditional and complementary systems of medicine in treating mental health problems. Lancet Psychiatry 2, 168177.
Hansen, AH, Kristoffersen, AE (2016). The use of CAM providers and psychiatric outpatient services in people with anxiety/depression: a cross-sectional survey. BMC Complementary Alternative Medicine 16, 461.
Haro, JM, Arbabzadeh-Bouchez, S, Brugha, TS, de Girolamo, G, Guyer, ME, Jin, R, Lepine, JP, Mazzi, F, Reneses, B, Vilagut, G, Sampson, NA, Kessler, RC (2006). Concordance of the composite international diagnostic interview version 3.0 (CIDI 3.0) with standardized clinical assessments in the WHO world mental health surveys. International Journal of Methods in Psychiatric Research 15, 167180.
Honda, K, Jacobson, JS (2005). Use of complementary and alternative medicine among United States adults: the influences of personality, coping strategies, and social support. Preventive Medicine 40, 4653.
Hunt, KJ, Coelho, HF, Wider, B, Perry, R, Hung, SK, Terry, R, Ernst, E (2010). Complementary and alternative medicine use in England: results from a national survey. International Journal of Clinical Practice 64, 14961502.
Kessler, RC, Ustün, TB (2004). 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, 93121.
Kessler, RC, Davis, RB, Foster, DF, Van Rompay, MI, Walters, EE, Wilkey, SA, Kaptchuk, TJ, Eisenberg, DM (2001 a). Long-term trends in the use of complementary and alternative medical therapies in the United States. Annals of Internal Medicine 135, 262268.
Kessler, RC, Soukup, J, Davis, RB, Foster, DF, Wilkey, SA, Van Rompay, MI, Eisenberg, DM (2001 b). The use of complementary and alternative therapies to treat anxiety and depression in the United States. American Journal of Psychiatry 158, 289294.
Kovess-Masfety, V, Evans-Lacko, S, Williams, D, Andrade, LH, Benjet, C, Ten Have, M, Wardenaar, K, Karam, EG, Bruffaerts, R, Abdumalik, J, Haro Abad, JM, Florescu, S, Wu, B, De Jonge, P, Altwaijri, Y, Hinkov, H, Kawakami, N, Caldas-de-Almeida, JM, Bromet, E, de Girolamo, G, Posada-Villa, J, Al-Hamzawi, A, Huang, Y, Hu, C, Viana, MC, Fayyad, J, Medina-Mora, ME, Demyttenaere, K, Lepine, JP, Murphy, S, Xavier, M, Takeshima, T, Gureje, O (2017). The role of religious advisors in mental health care in the World Mental Health surveys. Social Psychiatry and Psychiatric Epidemiology 52, 353367.
Melzer, J, Deter, HC, Uehleke, B (2013). CAM in psychiatry. Evidence Based Complementary Alternative Medicine 2013, 293248.
Paramore, LC (1997). Use of alternative therapies: estimates from the 1994 Robert Wood Johnson Foundation National Access to Care Survey. Journal of Pain and Symptom Management 13, 8389.
Pennell, B, Mneimneh, Z, Bowers, A, Chardoul, S, Wells, J, Viana, M, Dinkelmann, K, Gebler, N, Florescu, S, He, Y, Huang, Y, Tomov, T, Vilagut, G (2008). Implementation of the World Mental Health Surveys. In The WHO World Mental Health Surveys: Global Perspectives on the Epidemiology of Mental Disorders (ed. Kessler, R and Üstün, T), pp. 3357. Cambridge University Press: Cambridge, UK.
Ravindran, AV, da Silva, TL (2013). Complementary and alternative therapies as add-on to pharmacotherapy for mood and anxiety disorders: a systematic review. Journal of Affective Disorders 150, 707719.
Rössler, W, Lauber, C, Angst, J, Haker, H, Gamma, A, Eich, D, Kessler, RC, Ajdacic-Gross, V (2007). The use of complementary and alternative medicine in the general population: results from a longitudinal community study. Psychological Medicine 37, 7384.
The World Bank (2009). Data and Statistics. Retrieved 12 May 2009 from http://go.worldbank.org/D7SN0B8YU0.
Thomson, P, Jones, J, Evans, JM, Leslie, SL (2012). Factors influencing the use of complementary and alternative medicine and whether patients inform their primary care physician. Complementary Therapy in Medicine 20, 4553.
Turner, EH, Matthews, AM, Linardatos, E, Tell, RA, Rosenthal, R (2008). Selective publication of antidepressant trials and its influence on apparent efficacy. New England Journal of Medicine 358, 252260.
Unützer, J, Klap, R, Sturm, R, Young, AS, Marmon, T, Shatkin, J, Wells, KB (2000). Mental disorders and the use of alternative medicine: results from a national survey. American Journal of Psychiatry 157, 18511857.
Wahlström, M, Sihvo, S, Haukkala, A, Kiviruusu, O, Pirkola, S, Isometsä, E (2008). Use of mental health services and complementary and alternative medicine in persons with common mental disorders. Acta Psychiatrica Scandinavica 118, 7380.
Walter, G, Rey, JM (1999). The relevance of herbal treatments for psychiatric practice. Australian and New Zealand Journal of Psychiatry 33, 482489.
Wang, PS, Aguilar-Gaxiola, S, Alonso, J, Angermeyer, MC, Borges, G, Bromet, EJ, Bruffaerts, R, de Girolamo, G, de Graaf, R, Gureje, O, Haro, JM, Karam, EG, Kessler, RC, Kovess, V, Lane, MC, Lee, S, Levinson, D, Ono, Y, Petukhova, M, Posada-Villa, J, Seedat, S, Wells, JE (2007). Use of mental health services for anxiety, mood, and substance disorders in 17 countries in the WHO world mental health surveys. Lancet 370, 841850. http://www.who.int/mediacentre/factsheets/2003/fs134/en/.