Attitudes towards people with depression - Wiley Online Library

Attitudes towards people with depression: effects on the public’s help-seeking and outcome when experiencing common psychiatric symptoms Anthony F. Jorm, Jo Medway, Helen Christensen, Ailsa E. Korten, Patricia A. Jacomb, Bryan Rodgers

Objective: To determine whether people’s attitudes towards a person who has experienced depression influence them in (i) the types of actions they take to help themselves if they experience common psychiatric symptoms, and (ii) the degree to which their symptoms improve. Method: A postal survey was carried out with 3109 adults to assess attitudes and symptoms of anxiety and depression. Attitudes were assessed by questions on a depressed person’s likely long-term outcome in various areas of life and whether the respondents thought the depressed person was likely to experience discrimination. A follow-up survey was carried out 6 months later with 422 persons who had a high level of symptoms at baseline. These individuals were asked about whether they had taken various actions to relieve their symptoms. Results: The attitude measures did not predict use of actions which involved someone else having to know that the person had psychiatric symptoms, nor use of actions which did not. The attitude measures also did not predict change in anxiety and depression symptoms. Conclusions: The attitude measures did not predict patterns of help-seeking or outcome for people with common psychiatric symptoms. However, attitudes towards depression were quite benign and the situation could be different for people with severe mental disorders. Key words: anxiety, attitudes, depression, help-seeking, outcome, stigma. Australian and New Zealand Journal of Psychiatry 2000; 34:612–618

Consumers and carers have identified negative public attitudes towards people with mental disorders as a major concern. In response to this concern, the Anthony F. Jorm, Professor (Correspondence); Jo Medway, Research Assistant; Helen Christensen, Senior Fellow; Ailsa E. Korten, Research Officer; Patricia A. Jacomb, Research Assistant; Bryan Rodgers, Fellow Centre for Mental Health Research, Australian National University, Canberra, Australian Capital Territory 0200, Australia. Email: Anthony.Jorm.anu.edu.au Received 8 September 1999; revised 22 December 1999; accepted 12 January 2000.

Australian Government launched a Community Awareness Program in 1995 to reduce stigma and discrimination [1]. One of the effects of stigmatising attitudes may be an unwillingness to seek help when experiencing a mental disorder, leading to the underrecognition and under-treatment of mental disorders [2,3]. For example, a UK survey found that 60% of the public thought someone would be embarrassed to consult a general practitioner (GP) about depression [4]. Another possible effect of stigma may be reduced self-esteem which affects the person’s recovery [4].

A.F. JORM, J. MEDWAY, H. CHRISTENSEN, A.E. KORTEN, P.A. JACOMB, B. RODGERS

While stigmatising attitudes might plausibly affect help-seeking and recovery, there is very little direct evidence on this issue. A USA survey found that negative attitudes in depressed people were associated with a lower likelihood of having sought professional help in rural, but not in urban, residents [5]. The authors attributed the specific effect in rural areas to a lack of anonymity when seeking help. However, this study was retrospective, so it is unclear whether the attitudes actually had a causal influence on helpseeking. Most of the evidence on the association between stigmatising attitudes and symptoms involves crosssectional data, making it impossible to determine the causal direction. Longitudinal studies are needed to determine whether stigmatising attitudes affect recovery in people with mental disorders. Only two longitudinal studies could be located in the literature. A USA study examined the 1-year outcome in men who were being treated for comorbid mental disorder and substance abuse [6]. This study found that perceived stigma and rejection experiences at baseline predicted a worse outcome for depressive symptoms. The second study, also from the USA, involved people with a mental disorder receiving outpatient treatment or in support groups who were followed up over 18 months [7]. This study found that anticipated stigma had small adverse effects on symptoms and life satisfaction. Reports of actual experiences of stigma at follow up were a better predictor of worse outcomes than anticipated stigma. No data on the effects of stigmatising attitudes on help-seeking or outcome have been reported for Australia. Here we report the results of a 6-month follow up of a community sample of persons with a high level of common psychiatric symptoms (involving anxiety and depression). Stigmatising attitudes were assessed using the method of a previous national survey of public and professional attitudes [8]. We sought to determine whether these attitude measures predicted (i) the actions the participants took over the following 6 months to relieve their symptoms (in particular, actions which required the person to reveal that they had psychiatric symptoms), and (ii) the degree to which their symptoms improved. Method Baseline survey A postal survey, Stress and Well-Being, was carried out with persons aged 20–59 on the electoral roll for

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the electorate of Farrer, which includes the city of Albury and a surrounding rural area in New South Wales. Questionnaires for self-completion were posted to 8000 people. Those who did not respond within 1 month received a reminder and another copy of the questionnaire. The questionnaire covered sociodemographic characteristics of the respondent, personality, social support, life events and psychiatric symptoms, beliefs about interventions for depression and attitudes towards people who have experienced depression. The only questions of relevance here are those on sociodemographic characteristics, history of depression and treatment, current psychiatric symptoms and attitudes. The questionnaire was based on a vignette describing a person suffering from major depression which was used in previous surveys of the public and health professionals [9,10]. In the earlier surveys, the gender of the person described was randomly assigned to be either male (‘John’) or female (‘Mary’). However, since gender of the vignette made very little difference to the findings, we used only the ‘Mary’ vignette here. The vignette was: ‘Mary is 30-year-old. She has been feeling unusually sad and miserable for the last few weeks. Even though she is tired all the time, she has trouble sleeping nearly every night. Mary doesn’t feel like eating and has lost weight. She can’t keep her mind on her work and puts off making any decisions. Even day-to-day tasks seem too much for her. This has come to the attention of Mary’s boss who is concerned about her lowered productivity.’ Respondents were asked ‘What would you say, if anything, is wrong with Mary?’ They were then asked to rate the likely helpfulness of a number of interventions. To assess attitudes towards people with depression, there was a series of questions which covered a number of long-term outcomes and the likelihood of Mary experiencing discrimination. The specific attitude questions asked of respondents were: ‘Suppose that Mary had the sort of help you think is most appropriate for her health problems. [The following questions] ask how you think she would be in the long term compared to other people in the community?’ They were then given 10 outcomes, five negative and five positive, which they had to rate as ‘More likely’, ‘Just as likely’ or ‘Less likely’. The outcomes were: ‘To be violent’, ‘To drink too much alcohol’, ‘To take illegal drugs’, ‘To have poor friendships’, ‘To attempt suicide’, ‘To be understanding of other people’s feelings’, ‘To have a good marriage’, ‘To be a caring parent’, ‘To be a productive

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ATTITUDES TOWARDS PEOPLE WITH DEPRESSION

worker’, ‘To be creative or artistic’. Responses of ‘More likely’ were coded as 1, ‘Just as likely’ as 0, and ‘Less likely’ as –1. Following previous work [8], the scores on the positive items were summed to give a positive outcomes scale and scores on the negative items to give a negative outcomes scale, both with a score range from –5 to 5. Attitudes were also assessed by the question: ‘Do you think that Mary would be discriminated against by others in the community if they knew about the problems she has had?’ The possible responses allowed were Yes and No. To assess history of depression and treatment, respondents were asked: ‘Have you ever in your life been markedly depressed; that is, for several weeks or more, you felt sad, lost interest in things and felt lacking in energy?’. If the response was Yes, they were asked: ‘Did you see a counsellor or a doctor for it at the time?’. The three symptoms mentioned in the first question are the core symptoms for Depressive Episode in ICD-10 [11]. The answers to these questions were used to determine whether respondents had a history of treated or untreated depression. Other variables used here are: age, gender, years of education, marital status, the 12-item General Health Questionnaire (GHQ-12) [12] and the anxiety and depression scales of Goldberg et al. [13]. Follow-up survey Persons with a high score on the GHQ-12 were followed up at 6 months to study actions taken to relieve their symptoms and to assess any symptom change. The mean score on the GHQ-12 at baseline was 2.0 for males and 2.3 for females, suggesting the appropriateness of a 2/3 cut-off for screening purposes [14]. We chose to use a higher threshold of 3/4 to ensure a higher probability of including people with significant morbidity. Accordingly, those who had a score of ≥ 4 on the GHQ-12 were sent a follow-up questionnaire 6 months later. This questionnaire repeated most of the questions asked in the baseline questionnaire, but with some additional questions on ‘. . . things you might have done in the past 6 months to cope with stress, anxiety, depression or other emotional problems. Thinking about the past 6 months have you sought help for such a problem from any of the following?’. The questionnaire then listed: GP or family doctor; chemist or pharmacist; counsellor; social worker; telephone counselling service (e.g. Lifeline); psychiatrist; psychologist; family; close friends; naturopath or herbalist; clergy, a minister or priest. Next the questionnaire asked whether ‘during

the past 6 months you have taken any of the following medicines to help with stress, anxiety, depression or other emotional problems?’. The medicines listed were: vitamins, minerals or tonics; herbal medicines; pain relievers such as aspirin, codeine or Panadol; anti-depressants; antibiotics; sleeping pills; anti-psychotics; tranquillisers such as Valium. Next respondents were asked whether ‘during the past 6 months you have done any of the following in an effort to reduce stress, anxiety, depression or other emotional problems?’. The activities listed were: become more active physically such as playing more sport, or doing a lot more walking or gardening; read about people with similar problems and how they have dealt with them; got out and about more; attended courses on relaxation, stress management, meditation or yoga; had sex to reduce stress; cut out alcohol altogether; had an occasional alcoholic drink to relax; gone on a special diet or avoided certain foods; taken a holiday or taken a day off work now and then; cut down on your number of commitments; had a massage or spinal manipulation; taken up new recreational activities; meditated or prayed. Finally, respondents were asked whether ‘during the past 6 months you have received any of the following treatments for stress, anxiety, depression or other emotional problems?’. The treatments were: counselling; psychotherapy; hypnosis; admission to a psychiatric ward of a hospital; electroconvulsive therapy (ECT). The number of actions taken was summed according to whether or not an action involved someone else having to know that the person had psychiatric symptoms. There were 21 actions which involved someone else having to know (telling GP, chemist, counsellor, social worker, telephone counselling service, psychiatrist, psychologist, family, close friends, naturopath or clergy; taking antidepressants, sleeping pills, antipsychotics or tranquillisers; learning relaxation; receiving counselling, psychotherapy, hypnosis, ECT or being admitted to a psychiatric ward) and 16 which did not (doing physical activity, reading about problem, getting out more, having sex, cutting out alcohol, having occasional drink, going on special diet, taking time off work, cutting commitments, having massage, taking up new recreations, meditating or praying, or taking vitamins, herbal medicines, pain relievers or antibiotics). Statistical analysis Multiple linear regression was used to ascertain whether attitudes predicted the number of actions


taken, with actions summed in two groups: those actions where someone else had to know that the person had psychiatric symptoms and those where someone else did not. Predictor variables were entered hierarchically. On the first step, the predictors entered were sociodemographic factors (age, gender, marital status, years of education) and psychiatric status (anxiety and depression symptoms, history of treated depression, history of untreated depression). On the second step the attitude measures were entered (positive and negative outcome scales, belief in discrimination). The F-test for the improvement in R2 was used to evaluate whether attitudes added to the prediction of change in symptoms. To ascertain whether attitudes predicted specific actions taken when experiencing symptoms, multiple logistic regression analysis was used. The dependent variables were whether or not particular actions were taken. Predictor variables were entered hierarchically as for the linear regressions. The chi-squared test for model improvement was used to judge whether attitudes added to the prediction of actions taken. Only actions taken by at least 10% of the follow-up sample were used as dependent variables in the logistic regression analyses. The remaining actions were too rarely taken for use as dependent measures. Multiple linear regression analysis was also used to assess whether attitudes predicted improvement in symptoms. The dependent variable was the change in symptoms from baseline to follow up. The predictors were entered hierarchically as for the logistic regression analysis. The F-test for the improvement in R2 was used to evaluate whether attitudes added to the prediction of change in symptoms. The p < 0.05 level was used for all regression analyses. Because the GHQ-12 was used to select out highly symptomatic persons, it was not appropriate to use it to measure change. Any improvement at follow up might be partly due to regression to the mean associated with measurement error. For this reason, a different symptom measure (the sum of the Goldberg anxiety and depression scales [13]) was used for measuring longitudinal change over 6 months. Because the correlation between anxiety and depression scores was so high (0.73 in the whole sample and 0.60 in the symptomatic subsample) the two were summed together in the analysis. The reliability of measures was estimated using Cronbach’s alpha. To assess the reliability of the symptom change score, the longitudinal change in each symptom (improved, no change, worse) was used in estimating alpha.

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Results Responses to the baseline questionnaire were received from 3109 persons (39% response rate). Compared with the 1996 census data for the electorate of Farrer, this sample had an over-representation of females and of people aged 50–59, and an under-representation of people aged 20–34. Of these 3109 respondents, 580 had a GHQ-12 score of ≥ 4 (19%). Follow-up questionnaires were sent to these symptomatic persons and responses were received from 422 (73%). There was a mean of 182 days (SD = 17) between completing the baseline and follow-up questionnaires. The non-responders to the follow-up questionnaire differed from the responders in that they tended to be younger and male, but they did not differ in education, marital status, anxiety and depression symptoms or residence (urban or rural). The subsample that was followed up had a significant level of psychiatric morbidity, with a mean Goldberg scale of 5.2 (SD = 2.3) depression symptoms and 6.3 (SD = 2.1) anxiety symptoms at baseline, and means of 4.4 (SD = 2.5) and 5.5 (SD = 2.7), respectively, at follow up. According to the original validation study on these scales, a score of 2 on the depression scale or 5 on anxiety scale indicates a 50% chance of clinically important disturbance [13]. The mean improvement in anxiety and depression symptoms over the 6 months was 1.71 (SD = 3.98). Cronbach’s alpha for the combined anxiety and depression symptoms was 0.81 at baseline (in the subsample), 0.87 at follow up, and 0.74 for the change score. When asked what was wrong with the person in the vignette, 13% failed to answer the question and 3% gave an irrelevant response. Of the remainder, 59% of the full sample and 66% of the subsample that was followed up labelled the person as having depression. Most of the subsample thought that the person would benefit from professional assistance, with 92% saying it would be helpful for her to see a counsellor, 81% a GP, 70% a psychologist and 67% a psychiatrist. In the total baseline sample, 46% believed discrimination was likely, compared with 58% in the subsample that was followed up. The baseline sample had quite benign attitudes on the positive and negative outcome scales: means of 2.80 (SD = 2.11) on the positive scale and –3.51 (SD = 2.01) on the negative scale. The subsample that was followed up also had benign attitudes about outcomes, with identical means of 2.80 (SD = 2.10) and –3.51 (SD = 1.96) respectively. Table 1 shows the correlations among the attitude beliefs and the reliability coefficients.

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Table 1. Correlations among the attitude measures: baseline values above the diagonal, follow-up subsample below the diagonal and reliability coefficients on the diagonal. Diagonal shown in bold. Attitude measure Positive outcomes scale Negative outcomes scale Belief in discrimination

Positive outcomes scale 0.84 –0.53* –0.18*

Negative outcomes scale 0.11* 0.84 0.07

Belief in discrimination –0.08* –0.52* ND

*p < 0.001. Cronbach’s alpha could not be calculated for Belief in discrimination because it involved only one question.

At baseline, those who believed that discrimination was likely had a significantly higher level of symptoms: means of 6.64 (SD = 5.07) compared with 5.17 (SD = 4.57), p < 0.001. However, the positive and negative outcome scale scores were not significantly correlated with symptoms at baseline. The actions taken were reported with the following frequencies: taking the occasional drink 55% or pain relievers 55%, doing physical activity 50%, seeking help from close friends 50% or family 46%, taking vitamins 40%, taking time off work 40%, getting out more 35%, seeing a GP 35%, cutting commitments 33%, having massage 30%, meditating or praying 30%, reading about problem 26%, going on a special diet 22%, having sex 21%, taking antidepressants 20% or herbal medicines 20%, seeing a chemist 18%, trying new recreations 16%, having counselling 15%, taking sleeping pills 15%, seeing a naturopath 14% or counsellor 14%, cutting out alcohol 12%, taking antibiotics 11%, learning relaxation 6%, seeing a psychologist 5% or clergy 5%, taking tranquillisers 4%, having psychotherapy 4%, seeing a social worker 4% or psychiatrist 3%, having telephone counselling 3%, taking antipsychotics 1%, having hypnosis 1%, being admitted to a psychiatric ward 1% and having ECT 0%. Respondents took a mean of 2.62 (SD = 2.53) actions which involved someone else having to know that they had psychiatric symptoms, and a mean of 4.91 actions (SD = 2.69) where someone else did not have to know. Multiple linear regression analyses were carried out to predict the number of actions taken in the two classes. For the actions where someone else had to know that the person had psychiatric symptoms, the first block of predictors (sociodemographic and psychiatric status variables) accounted for 20.3% of the variance, while the second block (attitude variables) accounted for an additional 1.0% (non-significant). Similarly, for the actions where someone else did not have to know that the person had psychiatric symptoms, the first block of predictors accounted for 8.0%

of the variance and the second block for an additional 2.3% (p = 0.025). Although the contribution of the second block was significant, none of the individual attitude variables had significant regression coefficients. These analyses were also repeated entering only the attitude measures as predictors, but the effects were also non-significant. Multiple logistic regression analyses predicting specific actions taken were carried out for those actions used by at least 10% of the followed-up subsample. These analyses found that attitudes did not significantly contribute to improvement in the model, except where the action taken was the use of vitamins. However, this was only one significant effect out of 24 analyses. Similarly, multiple linear regression analyses predicting symptom change found that attitudes did not add significantly to the prediction. The first block of predictors (sociodemographic and psychiatric history variables) accounted for 3.0% of the variance, while the second block (attitude variables) accounted for an additional 0.1% (non-significant). This analysis was also repeated with only the attitude variables as predictors, but the result was also negative. Discussion This study found that attitudes did not predict the actions taken when experiencing symptoms. To our knowledge, it is the only prospective study of a community sample to examine this issue. The study also found that attitudes did not predict symptom change, contrary to the findings from two USA studies [6,7]. An important issue to consider in interpreting this negative result is the statistical power of the study. For associations between continuous measures (such as between the positive outcome scale and number of actions taken) there was 98% power to detect a correlation of 0.2 and 54% power to detect a correlation of 0.1. For associations between binary measures (such as between belief in discrimination and


whether a particular intervention was used) the power varied depending on the frequencies. For example, with the association between the discrimination question and an intervention with a frequency of 50%, there was 90% power to detect a relative risk of 2, while for an intervention with a frequency of 10%, the power was 46% to detect this relative risk. Another issue to consider is the reliability and validity of our attitude measures. The reliability of both the positive and negative outcomes scales was high. However, we do not have reliability data on the single-item measure of discrimination beliefs. This item had only small correlations with the outcome scales. As for validity, the face content of the measures is appropriate. It would be expected that a person who believes there will be discrimination and anticipates poorer longterm outcomes might be more reluctant to reveal his or her mental health problems to others and to seek help. Construct validity is supported by a principal component analysis showing separate factors for the positive and negative outcome scales [8]. In our earlier study, attitudes towards schizophrenia were more negative than towards depression, showing the sensitivity of the measures [8]. Another possibility is that there are inadequacies with the questions on actions taken or with the symptom change measures. We have no data on the validity of the questions on actions taken. However, we can say that other baseline variables do predict actions taken in a plausible way. In other analyses of this data set, we have found that actions taken are predicted by gender, severity of symptoms, history of treatment for depression and beliefs about the helpfulness of a particular action [15]. The symptom measures used have been extensively validated as measures of psychopathology [13,16]. While the reliability of such measures can be poorer when used to measure change rather than crosssectional state, reliability of the change score was satisfactory in the present study. If the present negative findings are accepted as real, then we can ask why the earlier USA studies found effects of stigmatising attitudes on outcome. There are some important differences between the studies. In particular, the USA studies dealt with more seriously ill people. One study was carried out with patients in residential care who had dual mental disorder and substance abuse diagnoses [6]. All had had at least two psychiatric hospitalisations. The other USA study was with people receiving outpatient treatment or in self-help groups [7]. Most had at some time experienced psychiatric hospitalisation. In

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contrast, the present study was with a community sample experiencing common psychiatric symptoms, the vast majority of whom were not receiving specialised mental health services. It is plausible that stigma is much greater for people who have been hospitalised, particularly in view of the public’s very negative attitudes towards this form of treatment [9]. Differences in type of mental disorder between the samples could also be important. There is evidence from surveys of the German public that alcohol abuse is highly stigmatised, even more so than schizophrenia, while depression and anxiety disorders are the least stigmatised [17]. Similarly, in an earlier Australian survey we found that attitudes to schizophrenia were more negative than to depression [8]. Indeed, as in the present study, beliefs about the longterm outcome of depression tended to be rather positive, suggesting that the public may not realise that depression can have a relapsing course and cause continuing disability. Another difference between the studies is the duration of follow up: 6 months in the present study compared with 12 and 18 months in the USA studies. However, given the wide range in symptom change in the present study, it is not clear that a longer follow up would have affected the results. Although the present study found no effects of attitudes on symptom outcome, we did not assess experiences of discrimination over the 6 months of follow up. One of the USA studies found that discriminatory experiences mediated much of the effects of anticipated stigma [7]. Unfortunately, discriminatory experiences can only be assessed retrospectively, making it difficult to determine causality. A weakness of the present study was the low response rate at baseline (39%). Although a more representative sample is always desirable, it was not a requirement for this study. Our aim was to recruit, at low cost, a community sample which included people who were symptomatic but not in necessarily in contact with services. We succeeded in achieving this. Previous studies have all involved people in contact with services. We do not know whether highly symptomatic people were more or less likely to participate. Compared with the same age group in a Canberra community survey with a response rate of 67%, the Albury males scored around one-tenth of a standard deviation lower on the Goldberg scales, and the Albury females around one-fifth of a standard deviation lower. Assuming the prevalence of psychiatric morbidity is the same in the two communities, this difference would indicate that highly symptomatic individuals were less likely to participate.

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In conclusion, this is the first study to examine prospectively the effects of stigmatising attitudes in a community sample of people with common psychiatric symptoms. The negative findings indicate that the effects of stigma may not extend to such people. We need further evidence to assess the effects of stigma on people with severe mental disorders who are receiving specialised treatment and to assess the prevalence of discriminatory experiences. References 1. Australian Health Ministers. National mental health policy. Canberra: Australian Government Publishing Service, 1995. 2. Hirschfeld RM, Keller MB, Panico S et al. The National Depressive and Manic–Depressive Association consensus statement on the undertreatment of depression. Journal of the American Medical Association 1997; 277:333–340. 3. Commonwealth Department of Health and Aged Care and Australian Institute of Health and Welfare. National health priority areas report: mental health 1998. Canberra: Commonwealth Department of Health and Aged Care and Australian Institute of Health and Welfare, 1999. 4. Sims A. The scar that is more than skin deep: the stigma of depression. British Journal of General Practice 1993; 43:30–31. 5. Rost K, Smith GR, Taylor JL. Rural–urban differences in stigma and the use of care for depressive disorders. Journal of Rural Health 1993; 9:57–62. 6. Link BF, Struening EL, Rahav M, Phelan JC, Nuttbrock L. On stigma and its consequences: evidence from a longitudinal study of men with dual diagnoses of mental illness and substance abuse. Journal of Health and Social Behavior 1997; 38:177–190. 7. Markowitz FE. The effects of stigma on the psychological well-being and life satisfaction of persons with mental illness. Journal of Health and Social Behavior 1998; 39:335–347.

8. Jorm AF, Korten AE, Jacomb PA, Christensen H, Henderson S. Attitudes towards people with a mental disorder: a survey of the Australian public and health professionals. Australian and New Zealand Journal of Psychiatry 1999; 33:77–83. 9. Jorm AF, Korten AE, Jacomb PA, Christensen H, Rodgers B, Pollitt P. ‘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 1997; 166:182–186. 10. Jorm AF, Korten AE, Jacomb PA, Rodgers B, Pollitt P. Beliefs about the helpfulness of interventions for mental disorders: a comparison of general practitioners, psychiatrists and clinical psychologists. Australian and New Zealand Journal of Psychiatry 1997; 31:844–851. 11. World Health Organization. The ICD-10 classification of mental and behavioural disorders. Diagnostic criteria for research. Geneva: WHO, 1993. 12. Goldberg DP, Williams P. A user’s guide to the General Health Questionnaire. Windsor: NFER-Nelson, 1988. 13. Goldberg D, Bridges K, Duncan-Jones P, Grayson D. Detecting anxiety and depression in general medical settings. British Medical Journal 1988; 297:897–899. 14. Goldberg DP, Oldehinkel T, Ormel J. Why GHQ threshold varies from one place to another. Psychological Medicine 1998; 28:915–921. 15. Jorm AF, Medway J, Christensen H, Korten AE, Jacomb PA, Rodgers B. Public beliefs about the helpfulness of interventions for depression: effects on actions taken when experiencing anxiety and depression symptoms. Australian and New Zealand Journal of Psychiatry 2000; 34:619–626. 16. Mackinnon AJ, Christensen H, Jorm AF, Henderson AS, Scott R, Korten AE. A latent trait analysis of an inventory designed to detect symptoms of anxiety and depression using an elderly community sample. Psychological Medicine 1994; 24:977–986. 17. Angermeyer MC, Matschinger H. Social distance towards the mentally ill: results of representative surveys in the Federal Republic of Germany. Psychological Medicine 1997; 27:131–141.