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Socioeconomic status and beliefs about depression, schizophrenia and eating disorders

  • Olaf von dem Knesebeck
  • Eva Mnich
  • Anne Daubmann
  • Karl Wegscheider
  • Matthias C. Angermeyer
  • Martin Lambert
  • Anne Karow
  • Martin Härter
  • Christopher Kofahl
Original Paper

Abstract

Purpose

The association between socioeconomic status (SES) and knowledge/belief about depression, schizophrenia and eating disorders will be analysed.

Methods

Data stem from a telephone survey in two large German cities (Hamburg and Munich, n = 2,014, response rate 51 %). Written vignettes with typical signs and symptoms suggestive of a depression, schizophrenia and eating disorders were presented to the respondents. Respondents were then asked about knowledge/belief about causes, symptoms, prevalence and treatment using a standardised questionnaire. Education, occupational position and income were used as SES indicators.

Results

Results of mixed hierarchal logistic regression analyses show that individuals with a low SES know less about symptoms and prevalences of depression, schizophrenia and eating disorders. Moreover, people with a high SES are more likely to consider medication as effective in case of depression and schizophrenia, but are less likely to believe that activities such as sports or relaxation are an effective measure to treat the three mental disorders under study. Respondents with a high SES are less likely to believe that a weak will is a possible cause of depression, schizophrenia and eating disorders. We found large similarities in the associations between SES and beliefs across the three mental disorders. Finally, associations of beliefs about mental disorders with education are stronger and more consistent than with income and occupational position.

Conclusions

Results indicate an inequality in mental health literacy and underline that information campaigns on causes, symptoms, prevalence and treatment of mental disorders should consider information needs of people with a low SES.

Keywords

Mental health literacy Socioeconomic status Depression Schizophrenia Eating disorder 

Introduction

Population-based attitude research in psychiatry made considerable progress in the last years in shedding light on public knowledge about mental illness and public attitudes towards people with mental disorders [1, 2, 3]. As social structure and social context contribute to shape beliefs and attitudes, it is important to understand the relationship between social inequality or socioeconomic status (SES) on one hand and beliefs about mental illness and attitudes towards people concerned on the other. SES is usually measured by education, occupational position and/or income [4].

A number of studies explored the association between education and attitudes towards people with mental illness. A review of Angermeyer and Dietrich [1] brought inconsistent results concerning the association between education and attitudes towards people with mental illness. About 50 % of the studies showed that persons with a higher educational level tend to distance themselves less from the mentally ill and express more liberal views. However, in the other 50 % of the studies no association was reported.

Fewer studies analysed the relationship between education and knowledge/belief about mental illness. Knowledge/belief about mental disorders can be conceptualised as ‘mental health literacy’. According to Jorm [5], mental health literacy consists of several components, including the ability to recognise specific disorders, knowledge/belief about risk factors and causes, about self help interventions and professional help. A study from Switzerland found that education is weakly associated with beliefs about causes of depression [6]. In terms of public beliefs about causes and risk factors for depression and schizophrenia, Jorm et al. [7] found that the better educated less often consider the character of the person as a cause of the disorders in Australia. A German study also showed that those with the highest educational level less often blamed the lack of will power and an immoral life-style for the manifestation of depression and schizophrenia [8]. They also were less prepared to consider biological factors (brain disease, heredity) as of etiological relevance. Moreover, there was a stronger tendency to expect a complete cure and to recommend psychotherapy for the management of the disorders with increasing educational level. In sum, results indicate that people with a higher educational level less frequently tend to make the afflicted person responsible for the illness and were more willing to recommend psychosocial interventions for treatment [1]. However, results are inconsistent depending on the mental disorder under study, and most studies on public beliefs about mental illness are focussed on depression and schizophrenia. Little is known about other mental health problems, e.g. eating disorders [9, 10].

Moreover, studies on SES and knowledge/belief about mental illness focussed on education as an indicator of SES. Therefore, it is unclear whether the results hold true for other indicators such as income or occupational position. It has been shown that different indicators of SES reflect different aspects of social inequality and that the indicators cannot be used interchangeably [11]. While it is reasonable to expect that education reflects knowledge, occupational position is related to experiences and living conditions, including the working environment that are likely to shape beliefs and attitudes. Income indicates material resources and deprivation that influence life chances which on their part are expected to have an impact on attitudes and beliefs.

Against this background, the present analyses will address the following research questions: (1) Is there an association between SES and knowledge/belief about the causes, symptoms, prevalence and treatment of depression, schizophrenia and eating disorders? (2) Do the associations vary according to the three mental disorders under study? (3) Do the associations vary according to the SES indicators used (education, income and occupational position)?

Methods

Study design and sample

Data stem from a telephone survey (computer-assisted telephone interviewing, CATI) in two large German cities (Hamburg and Munich) conducted in autumn 2011. CATI was successfully used previously in population-based attitude research in psychiatry [12, 13, 14]. The survey is part of a large project on mental health in Hamburg. A major component of this project is an information campaign on mental disorders. One purpose of the survey is to evaluate the effects of the information campaign with Munich as the control region. The present survey serves as the baseline, it will be replicated in 2,014. Sample consists of persons aged 18 years and older, living in private households with conventional telephone connection in one of the two metropolises. The sample was randomly drawn from all registered private telephone numbers, and additionally generated numbers, allowing for ex-directory households as well. Repeated calls were made on eight occasions on different days of the week until a number dropped out. Informed consent was considered to have been given when individuals agreed to complete the interview. The study was approved by the Ethics Committee of the Medical Association in Hamburg. 2,014 men and women agreed to attend the interview and participated in the study, reflecting a response rate of about 51 %. Comparison with official statistics in the two cities shows that the distribution of gender, age, family status and education in the sample is similar to that in the general population.

Written vignettes with typical signs and symptoms suggestive of a depression, schizophrenia and eating disorders were presented to the respondents (see “Appendix”). In terms of eating disorders, two vignettes were introduced (bulimia and anorexia nervosa). For the present analyses answers concerning these two vignettes were pooled to increase the number of cases. All vignettes were developed with the input of experienced clinicians based on the relevant ICD-10 criteria. Gender of the “patient” in the depression and schizophrenia vignettes was systematically varied, i.e. in 50 % of the cases the patient was female. As eating disorders are rare among men, we only used a female patient in the respective vignettes. All vignettes were recorded with a trained speaker with clear voice. In order to increase the reliability and to ‘neutralise’ the possible interviewer-associated effects these audio files were presented to the interviewees directly from the computer via telephone line. By doing this, every person was given the same stimulus, and across the different vignettes voice and speaking style were the same. To reduce the length of the questionnaire and to avoid excessive demands for the respondents, only two vignettes were included in each questionnaire. The vignettes were randomly permuted to eliminate order effects. Thus, each respondent answered questions concerning two disorders, resulting in about 1,343 cases (two third of 2,014 cases) for each vignette (Table 1).
Table 1

Distribution of beliefs about mental disorders in the sample (n = 2,014 %)

 

Depression (n = 1,342)a

Schizophrenia (n = 1,343)a

Eating disorders (n = 1,343)a

Recognition of disorder

71.9

38.5

69.1

Realistic estimation of prevalence of disorder

28.2

18.5

11.7

Disorder is treatable (well/very well)

79.9

56.5

68.2

Treatments (rather/very effective)

   

 Medication

76.2

83.4

34.5

 Psychotherapy

92.9

89.8

94.9

 Own activities

91.7

71.6

78.3

Possible causes (completely/rather correct)

   

 Disorder of the brain

56.1

86.8

27.5

 Family strain

96.0

56.6

87.8

 Job stress

97.6

53.4

68.1

 Weak will

34.0

22.3

35.4

aEach respondent answered questions concerning two vignettes

Measures

Age and gender were introduced as control variables. The mean age of the respondents is 47.4 years, 52 % are female. Education, occupational position and income are used as SES indicators. Education was measured by the highest school qualification achieved. Respondents were considered to be highly educated if they have an upper secondary or higher education. 44.3 % of the respondents have a high education according to this definition. Occupational position was assessed using 17 categories. If respondents indicated that they have a leading or a supervisor position, occupational status was defined as high (48 %). In case respondents were unemployed or retired, last position was specified. Finally, the net household income per month was assessed. In order to adjust for household size, the household income was divided by the equivalent weights of the household members (weight of respondent was 1.0, weight of every additional person was 0.5) [15]. Equivalence income of 1,500 Euro or more was considered high (55 %). In sum, the three indicators of socioeconomic status were dichotomized for the analyses, using median split.

In terms of knowledge/belief about mental illness several indicators were used. After the interviewers presented one of the vignettes, the respondents were asked what mental illness the person in the vignette has (open ended question). After that, the respondents were informed about the mental illness in question (depression, schizophrenia or eating disorder)—those with a precise and correct answer in the form of an approving feedback, those with an imprecise, wrong or “do not know” answer were told the correct diagnosis. Then they were asked about the lifetime prevalence of that illness (“What do you think, how many persons out of 100 will have such an illness at some point in their lives?”). We compared the answers with epidemiological data on lifetime prevalence of the three mental disorders in Germany. Lifetime prevalence of 10–25 % is considered correct for depression as prevalence estimates in the literature show this range [16, 17]. Respective figures for schizophrenia and eating disorders are 1–2 % [18, 19]. Thus, we were able to assess if respondents’ prevalence estimates of depression, schizophrenia and eating disorders were realistic (yes or no). Afterwards, the respondents were asked whether the mental illness in question is treatable (1 = “not at all” to 4 = “very well”). Moreover, we asked how effective medication, psychotherapy and activities such as sport or relaxation are for the treatment of the respective mental disorder with a scale ranging from 1 (“not at all effective”) to 4 (“very effective”) for each of the therapeutic measures. Finally, respondents were asked about possible causes of the mental disorders under the study [20]. Specifically, four items were used: (1) “A possible cause is a brain disease.” (2) “A possible cause is family strain.” (3) “A possible cause is stress at work.” (4) “A possible cause is a weak will.” All items measuring causal attributions were coded from 1 (“not at all correct”) to 4 (“completely correct”). As mentioned above, each respondent answered all questions concerning beliefs about two of the mental disorders under study consecutively.

Statistical analyses

Since the applied block plan was incomplete (each respondent rated only 2 of 3 vignettes/disorders), respondents’ individualities are to be controlled. Thus, to address the three research questions mentioned above, mixed hierarchical logistic regression analyses are conducted, with beliefs as dependents, respondents as random effect and age, gender, education, occupation, income and disorder as fixed effects. Odds ratios, 95 % confidence intervals and significances are reported. All analyses are conducted with the statistical programme packages SPSS 20 or SAS 9.3.

Results

Table 1 shows the distribution of the beliefs about depression, schizophrenia and eating disorders in our sample. As can be seen, all indicators of knowledge/belief were dichotomised for the analyses. About 70 % of the respondents recognised depression and eating disorders after the vignette was presented. Respective proportion for schizophrenia is 38.5 %. About 28 % gave a realistic estimation of the lifetime prevalence of depression. Correct estimation was given less often for schizophrenia and eating disorders (18.5 and 11.7 %). About half of the respondents think that schizophrenia is well or very well treatable. Respective figures for depression and eating disorders are about 80 and 68 %. A large majority of the respondents (72–95 %) think that medication, psychotherapy and own activities are rather or very effective measures to treat the three mental disorders. There is only one exception: about one third thinks that medication is effective in treating eating disorders. In terms of possible causes, schizophrenia is most often considered a disorder of the brain, whereas family strain and job stress are most often seen as potential causes of depression. About one third thinks that it is completely or rather correct that a weak will is a possible cause of depression. Respective figures for schizophrenia and eating disorders are 22 and 35 %.

SES and beliefs about depression

Table 2 shows that a high SES measured by education, income and occupational position is positively associated with illness recognition and a realistic estimation of the lifetime prevalence in case of depression. Respondents with high education (i.e. upper secondary or higher) are more likely to believe that medication is effective in treating depression. Associations between education and the belief that family strain, job stress and a weak will are possible causes for depression are negative. This is especially true for the causal attribution to a weak will, i.e. respondents with high education are significantly less likely to agree with the statement that a weak will is a potential cause of depression. Finally, respondents with a high income (1,500 Euros or more) are less likely to agree with the statement that job stress is a potential cause of depression and those with a leading occupational position are less likely to believe that a weak will is a possible cause (both associations are not significant).
Table 2

Socioeconomic status (SES) and beliefs about depression: odds ratios, significances and (95 % CI)

 

High education (upper secondary or higher)

High income (≥1,500 Euro/month)

High occupational position (leading position)

Recognition of disorder

1.91 (1.21–3.01)*

1.22 (0.79–1.87)

1.67 (1.07–2.59)**

Realistic estimation of prevalence of disorder

2.06 (1.31–3.25)**

1.80 (1.16–2.78)**

1.56 (1.01–2.41)*

Disorder is treatable (well/very well)

0.82 (0.50–1.34)

0.74 (0.47–1.18)

1.23 (0.76–1.97)

Treatments (rather/very effective)

   

 Medication

2.79 (1.54–5.05)***

1.36 (0.79–2.35)

0.99 (0.56–1.76)

 Psychotherapy

1.84 (0.77–4.38)

0.72 (0.32–1.61)

1.15 (0.50–2.61)

 Own activities

0.66 (0.32–1.40)

0.96 (0.47–1.99)

0.73 (0.35–1.53)

Possible causes (completely/rather correct)

   

 Disorder of the brain

1.23 (0.73–2.08)

0.86 (0.52–1.43)

1.25 (0.75–2.08)

 Family strain

0.45 (0.19–1.08)

1.33 (0.60–2.96)

1.47 (0.65–3.35)

 Job stress

0.44 (0.14–1.36)

0.49 (0.16–1.51)

1.00 (0.34–2.97)

 Weak will

0.29 (0.17–0.49)***

0.84 (0.50–1.40)

0.63 (0.37–1.07)

Adjusted for gender, age and all SES indicators

* p < 0.05, ** p < 0.01, *** p < 0.001

SES and beliefs about schizophrenia

Table 3 indicates that high education is significantly associated with illness recognition and a realistic estimation of the lifetime prevalence of schizophrenia. Respondents who have a leading or supervising occupational position are more likely to believe that schizophrenia is well or very well treatable. Respondents with high education are more likely to believe that medication is effective in case of schizophrenia but less likely to think that activities such as sports or relaxation are effective in this case. In terms of causal attributions, a high SES is negatively associated with the belief that a weak will is a potential cause of schizophrenia and highly educated respondents are less likely to believe that job stress is a cause of this mental disorder.
Table 3

Socioeconomic status (SES) and beliefs about schizophrenia: odds ratios, significances and (95 % CI)

 

High education (upper secondary or higher)

High income (≥1,500 Euro/month)

High occupational position (leading position)

Recognition of disorder

3.55 (2.35–5.35)***

1.45 (0.97–2.16)

0.80 (0.53–1.19)

Realistic estimation of prevalence of disorder

1.84 (1.14–2.96)*

1.26 (0.79–2.01)

0.99 (0.62–1.57)

Disorder is treatable (well/very well)

0.98 (0.65–1.47)

0.79 (0.53–1.16)

1.66 (1.12–2.48)*

Treatments (rather/very effective)

   

 Medication

2.61 (1.32–5.16)**

1.23 (0.66–2.31)

1.19 (0.61–2.31)

 Psychotherapy

0.80 (0.39–1.64)

0.76 (0.38–1.51)

1.55 (0.77–3.12)

 Own activities

0.50 (0.30–0.81)**

0.74 (0.46–1.20)

1.08 (0.67–1.75)

Possible causes (completely/rather correct)

   

 Disorder of the brain

0.69 (0.36–1.32)

1.26 (0.66–2.39)

0.83 (0.43–1.59)

 Family strain

0.77 (0.51–1.18)

0.82 (0.55–1.23)

1.00 (0.67–1.51)

 Job stress

0.62 (0.41–0.95)*

0.74 (0.50–1.11)

1.03 (0.69–1.54)

 Weak will

0.34 (0.19–0.61)***

0.48 (0.28–0.83)**

0.58 (0.33–1.02)

Adjusted for gender, age and all SES indicators

* p < 0.05, ** p < 0.01, *** p < 0.001

SES and beliefs about eating disorders

Respondents with a high SES have a higher probability to recognise eating disorders and to give a realistic estimation of the respective lifetime prevalence, although most associations are non-significant (Table 4). Moreover, respondents with a comparatively high income are less likely to believe that eating disorders are well or very well treatable. Respondents with a high SES are less likely to believe that medication is effective in case of eating disorders, especially, when education is used as SES indicator. Furthermore, high occupational status is positively associated with the evaluation of effectiveness of psychotherapy, while it is negatively associated with the opinion that activities such as sports or relaxation are effective in case of eating disorders. Finally, associations between education and the belief that family strain, job stress and a weak will are possible causes of eating disorders are negative. This is especially true for the causal attribution to a weak will.
Table 4

Socioeconomic status (SES) and beliefs about eating disorders: odds ratios, significances and (95 % CI)

 

High education (upper secondary or higher)

High income (≥1,500 Euro/month)

High occupational position (leading position)

Recognition of disorder

1.34 (0.87–2.07)

1.11 (0.74–1.68)

1.54 (1.00–2.36)

Realistic estimation of prevalence of disorder

2.32 (1.32–4.08)**

1.51 (0.87–2.64)

1.53 (0.88–2.67)

Disorder is treatable (well/very well)

0.86 (0.57–1.32)

0.56 (0.37–0.84)**

0.96 (0.63–1.45)

Treatments (rather/very effective)

   

 Medication

0.56 (0.33–0.96)*

0.88 (0.53–1.47)

0.74 (0.44–1.27)

 Psychotherapy

1.08 (0.39–3.00)

1.99 (0.78–5.10)

2.60 (0.95–7.17)

 Own activities

1.17 (0.69–1.98)

1.28 (0.76–2.13)

0.51 (0.30–0.86)*

Possible causes (completely/rather correct)

   

 Disorder of the brain

0.92 (0.53–1.62)

0.65 (0.38–1.11)

0.72 (0.41–1.25)

 Family strain

0.68 (0.38–1.21)

1.41 (0.81–2.44)

1.43 (0.80–2.53)

 Job stress

0.64 (0.42–1.00)*

0.99 (0.65–1.51)

0.74 (0.48–1.15)

 Weak will

0.30 (0.18–0.51)***

0.80 (0.49–1.30)

0.76 (0.46–1.27)

Adjusted for gender, age and all SES indicators

* p < 0.05, ** p < 0.01, *** p < 0.001

Discussion

In this study, the association between SES and knowledge/belief about the causes, symptoms, prevalence and treatment of depression, schizophrenia and eating disorders was explored. Results of telephone surveys in two large German cities (Hamburg and Munich) show that SES is positively associated with the recognition of depression, schizophrenia and eating disorders and with a realistic estimation of the respective prevalence. Thus, our findings indicate a social inequality in mental health literacy, i.e. individuals with low education, low income and a low occupational position know less about the symptoms and prevalences of depression, schizophrenia and eating disorders. Moreover, people with a high SES are more likely to consider medication as effective in case of depression and schizophrenia, but are less likely to believe that own activities such as sports or relaxation are an effective measure to treat the three mental disorders under study. In terms of causal attributions, respondents with a high SES are less likely to believe that a weak will is a possible cause of depression, schizophrenia and eating disorders.

Generally, we found large similarities in the associations between SES and beliefs across the three mental disorders under study. This is remarkable as we found marked differences in the distribution of knowledge/belief between depression, schizophrenia and eating disorders (Table 1). However, considering the associations in detail, some differences become apparent. For example, medication is considered to be less effective by respondents with a high SES only in case of eating disorders, while it is the other way round in case of depression and schizophrenia. Furthermore, people with a high SES more often believe that psychotherapy is effective in treating eating disorders. This does not hold true to the same extent for depression and schizophrenia. Thus, inequalities in public beliefs about the effectiveness of different treatment options vary according to the mental disorder under study.

In terms of variations according to the SES indicators used, associations of beliefs about mental disorders with education are stronger and more consistent than with income and occupational position. In this regard, it has to be kept in mind that the three SES indicators are introduced simultaneously into our analyses, i.e. all associations presented in Tables 2, 3 and 4 are adjusted for the other SES indicators. In bivariate analyses (not shown), equivalence income and occupational position are significantly associated with many indicators of knowledge/belief about depression, schizophrenia and eating disorders. Thus, occupational and income inequalities in beliefs about mental disorders are largely due to education. This is remarkable as the three indicators are only moderately correlated with each other (r = 0.28–0.42). Moreover, mean age of the respondents is 47.4 years, i.e. on average respondents left school many years ago. With regard to knowledge/belief about mental disorders, occupation and income, both established determinants of life conditions and chances, do not seem to reflect relevant aspects of social inequality that go beyond education. However, there are exceptions (see Tables 3, 4): some beliefs about effective treatment options are significantly associated with income and occupational position but not with education.

Compared to previous studies, our results confirm that those with the highest educational level less often blame the lack of will power for the manifestation of depression and schizophrenia [7, 8]. Findings presented here also are in line with studies indicating that the better educated are more likely to recommend psychotherapy for the management of the depression and schizophrenia [1, 8]. Our study contributes to the discussion of inequalities in mental health literacy by including a rarely investigated mental illness (i.e. eating disorders) and by considering different SES indicators simultaneously.

Limitations

Several methodological limitations should be considered when interpreting our findings. First, about half of the selected eligible persons refused to participate or were not available. However, a response rate of 51 % is quite good compared to other telephone surveys in Germany [21] and a comparison with official statistics in the two cities supports the external validity of our study. Nevertheless, we cannot rule out a selection bias due to non-response and the results should not be generalised to the entire German population. Although we consider it a strength of our study that we used vignettes that were developed with the input of clinicians based on the ICD-10 criteria, it is possible that the respondents have a notion of mental disorders that differs from the scientific conception. This has to be kept in mind when interpreting their beliefs about the causes, symptoms, prevalence and treatment options. Furthermore, in terms of mental health literacy, in some cases it is difficult to evaluate which beliefs about the effectiveness of treatment options or causes of the disorders are ‘correct’. Another methodological problem is the skewed distribution of some indicators of beliefs, especially beliefs about treatments and causes (see Table 1). Finally, as we dichotomised the variables for the logistic regression analyses, results on associations to some extent are crude. We decided to dichotomise the variables and use logistic regression models for the sake of clearness, and due to the distribution characteristics of some variables.

Implications

As mentioned before, the survey presented is part of a large project on mental health in Hamburg. In this context, an information campaign using posters will be conducted. Our results underline that a campaign on causes, symptoms, prevalence, and treatment of depression, schizophrenia and eating disorders should consider the information needs of people with a low SES. Therefore, one possible focus of the campaign should be on deprived districts.

Footnotes

  1. 1.

    Gender of the “patient” in the depression and schizophrenia vignettes was systematically varied.

  2. 2.

    For the present analyses answers concerning the two vignettes presenting eating disorders were pooled.

Notes

Acknowledgments

The study is supported by the Federal Ministry of Education and Research (01KQ1002B) in the frame of “psychenet-Hamburg network mental health” (2011–2014). Psychenet is part of the national programme in which the City of Hamburg was given the title “Health Region of the Future” in 2010. The aim of the project is to promote mental health today and in the future, and to achieve an early diagnosis and effective treatment of mental illnesses. Further information and a list of all project partners can be found at http://www.psychenet.de. We would like to thank all respondents for taking part in the study and USUMA (Berlin) for conducting the telephone survey.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Olaf von dem Knesebeck
    • 1
  • Eva Mnich
    • 1
  • Anne Daubmann
    • 2
  • Karl Wegscheider
    • 2
  • Matthias C. Angermeyer
    • 3
  • Martin Lambert
    • 4
  • Anne Karow
    • 4
  • Martin Härter
    • 5
  • Christopher Kofahl
    • 1
  1. 1.Department of Medical Sociology and Health EconomicsUniversity Medical Center Hamburg EppendorfHamburgGermany
  2. 2.Department of Medical Biometry and EpidemiologyUniversity Medical Center Hamburg EppendorfHamburgGermany
  3. 3.Centre for Public Mental HealthGösing am WagramAustria
  4. 4.Psychosis Centre, Department of Psychiatry and PsychotherapyUniversity Medical Center Hamburg EppendorfHamburgGermany
  5. 5.Department of Medical PsychologyUniversity Medical Center Hamburg EppendorfHamburgGermany

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