Background: Stigma of mental illness is often related to attitude studies in social science research, cross-cultural psychology and education in social behaviour. Majority of these studies used opinion on mental illness to examine attitudes. Method: A cross-sectional survey was presented to 208 registered nurses in Australia. Principal component analyses (with oblique rotation) were used to identify underlying dimensionality in the correlations of items for negative stereotyping attitudes. Subscale score variations were analysed across nurse type and ethnicity to examine the discriminant validity of the subscales. Results: Principal component analysis (PCA) revealed one dimension accounting for 50.5% of the variations within items for negative stereotyping. Developed as scale, labelled as “Dislike Attributed to Mental Illness (DISL)”, reliability analysis indicated high internal consistency with alpha coefficient of .93. Chinese general nurses scored highest on the DISL scale than the other three groups: Chinese psychiatric nurses, Anglo general and Anglo psychiatric nurses. Conclusion: Psychometric evaluation of the Dislike Attributed to Mental Illness (DISL) indicates that it is a reliable scale for measuring negative stereotyping attitudes towards mental illness. The main statistical significance was due to nurse ethnicity.
A review of international studies on attitudes towards mental illness (for measuring stigma) remained rather negative among health professional, general public members and people with a diagnosed mental disorder. This trend spread over a period of several decades (Ucok et al., 2004 [
Stigma related to mental illness is an international concern and a long-standing challenge for research to understand its basis, mechanisms and consequences in order to be able to formulate means by which stigma and its impact may be ameliorated (Arboleda-Florez & Sartorius, 2008 [
This paper reports the development of a new approach used in measuring registered nurses’ attitudes towards mental illness, the “Dislike Attributed to Mental Illness (DISL)” Scale as part of a Master study which included contact level and cultural values for investigating nurses’ attitudes (Ku, 2007 [
The sample comprised of 208 nurses (49 Chinese-Australian and 83 Anglo-Australian psychiatric nurses, and 35 Chinese-Australian and 41 Anglo-Australian general nurses). One hundred and forty eight (148) were females and 60 were males. The mean age of the sample was 44.8 years (s.d. = 9.6), ranging from 21 to 65 years of age. For the overall sample the mean number of years working in general setting was 11.2 (s.d. = 12.0) and in psychiatric setting was 9.8 (s.d. = 11.0) respectively.
As indicated in
The DISL contained 16 items based on the first author’s experience as a psychiatric nurse. This new approach examined the nurses’ personal attitudes towards undesirable personal attributes and behaviours in general, and later in the questionnaire, the extent to which these attributes were ascribed by the respondent to people with a
#7 missing cases are excluded from the analysis in age. ***p < 0.001. For all χ2 analyses, df = 3.
“mental illness”. Each section contained 16 attributes such as “aggressiveness”, “incoherence”, “unmotivated”, “apathy”, “manipulative”, “hostile”, “avoidant”, “suspicious”, “insensitive”, “uncooperative”, “suspiciousness”, “apathy”, “unmotivated”, submissiveness”, “avoiding”, “incoherence” and “impulsiveness”. These items were conceived as part of a means of measuring stigma (viz, negative stereotyping) towards patients with a mental illness. There were four “dislike” responses for each item. A score of “1” represented “not at all”, “2” represented dislike “a little”, “3” represented “dislike much” and “4” represented “dislike very much” for a particular behaviour or attribute.
For the attribution score (to people with mental illness) each question was responded on the following response scale: “1” for “not at all”, “2” for “a little”, “3” for “much” and “4” for “very much” to the question of “To what extent do you think the following attributes describe with people with severe mental disorders?”. The product of level of dislike and level of attribution to mentally ill patients was averaged over all items to represent the “stigma” (DISL) score, referred to as negative stereotyping.
Participants were recruited through a snowballing technique. After the University of Melbourne Human Research Ethics Committee (HERC No. 020030) approved the study, an initial pool of general and psychiatric nurses (n = 20) of Chinese-Australian and Anglo-Australian backgrounds working in various institutions were identified and asked to participate in the study. Nurses in the initial pool known to the first author (Ku) were asked to approach potential participants and ask for permission to approach them to introduce the study formally. Nurses who expressed an interest in participating were asked to meet with Ku for the purpose of further explanation of the nature, purpose and procedure of the study. All participants signed a written consent form to anonymous participation. Data collection was achieved in the latter part of 2002 and early 2003.
Three hundred and forty-seven (347) surveys were disturbed. Two hundred and eight nurses out of 331 relevant participants returned the survey giving a 63% response rate (208/331 × 100).
Principal component analyses were used to identify common dimensions underlying the variation of the item scores of the DISL. Cronbach’s alpha coefficients were calculated to estimate the internal reliability of the derived DISL subscales. Two-way analysis of variance was used to examine the discriminant validity of the subscales. All analyses were conducted using the Statistical Package for the Social Sciences (SPSS Version 12).
The new approach developed in the study to measure attitudes towards the mentally ill, which proposes a score based on the product of negatively regarded personal attributes (in general) and the extent to which these are attributed to those with a mental illness.
Proportions of the sample reporting dislike for the attributes appear on the left of
A Principal Component Analysis (PCA) was conducted on the dislike scale items (that is, product scores which weight one’s ascription of a characteristic relating to mentally ill patients by one’s level of general dislike of that characteristic) to identify possible subscales. Using the Kaiser’s criterion, three components were extracted with eigenvalues higher than or equal to one. However, the first factor accounted for 50.5% of the va-
1Sum of ordinal scale, much and very much (3 + 4) of questionnaire item C; 2Sum of ordinal scale, much and very much (3 + 4) of questionnaire item F.
riance in the items suggesting that possibly one dimension might be sufficient to describe a general negative attitude towards those with mental illness. Also, higher dimensional solutions did not suggest any interpretable content themes for the various factors.
A two-way analysis of variance was conducted to explore the differences in DISL scores between ethnic groups and nurse types. The main effect of ethnicity was statistically significant (F(1,201) = 4.85, p < 0.05). Inspection of the means indicated that Chinese nurses scored higher on this scale (mean = 7.41, s.d. = 2.56) than Anglo nurses (mean = 6.60, s.d. = 2.41). The main effect for nurse type (F(1,201) = 1.01, p > 0.05) and the interaction term (F(1,201) = 0.05, p > 0.05) were not significant. It is suggested in
Correlations between al stigma and other measures (background demographics) are summarized in
In regard to DISL scores, as indicated in the Simple Model (shown in
Analysis of covariance was conducted to examine differences in DISL scores between nurse type and ethnic
*p < 0.05, ***p < 0.001; ns, not significant. YR_MH_NU = Years in Mental Health Nursing; YR_GE_NU = Years in General Nursing; CWS = Contact Through Work Situation; PHN = Patient Helps Nurse; RMI = Relative with Mental Illness; ESP = External Socialisation with Patient.
*p < 0.05, ns, not significant. 1covariates = age, sex, years of mental nursing experience, years of general nursing experience; 2covariates = age, sex, years of mental nursing experience, years of general nursing experience, current work environment, and contact levels [(CPP Scale = CWS (via work), PHN (patients helping nurse), RMI (relatives with mental illness), ESP (socializing with person with mental illness)).
groups accounting for the effects of background demographics and contact factors. As shown in Model 1 (
In Model 2, when contact type factors were added to demographics as covariates, the main effect of nurse type was not significant (F(1,182) =< 1). The main effect of ethnicity remained as significant (F(1,182) = 4.68, p < 0.05), and not appreciably altered. Examination of the means indicated that Chinese nurses (mean = 7.40, s.d. = 2.53) again reported higher attributed dislike than Anglo nurses (mean = 6.67, s.d. = 2.43). The interaction effect was not significant (F(1,182) =< 1).Thus, it would seem that factors other than background demographics and contact level are associated with higher stigma level reported by Chinese nurses as measured by negative attributes ascription to the mentally ill. Again, each demographic and contact factors alone did not account for any effect: age (F(1,182) = 3.35, p > 0.05), sex (F(1, 182) = 2.13, p > 0.05), years in mental health nursing (F(1, 182) = 1.21, p > 0.05), years in general nursing (F(1,182) = 2.00, p > 0.05), contact via work (F(1, 182) = 1.08, p > 0.05), patients helping nurse (F(1,182) =< 1), relatives with mental illness (F(1, 182) =< 1), and socialising with person with mental illness (F(1, 182) = 1.33, p > 0.05).
It would appear in general that ethnicity effect on general stigmatising attitudes, measured by the ascription of unfavourable personal attributed, is not entirely accounted for other factors measured in this study, and of importance, not accounted for contact level with mental illness.
Our focus on comparing negative stereotyping attitudes between Anglo and Chinese Australian nurses was guided by suggestion in the literature that stigma of mental illness might be related to cultural variation and contact level with mental illness.
The study by Angermeyer et al., 2004 [
Having Russians as the majority of its residents, Novosibirsk was an industrial center of Western Siberia, whereas Ulaanbaatar was the largest and capital city of Mongolia where most population adhered to Buddism. Results showed the effects of labelling on public attitudes were comparable between Russia and Mongolia. Labelling as suffering from mental illness correlated positively with endorsement of the need for help, but there was small endorsement of the stereotype of dangerousness. Small differences were noted between the two cities. In Novosibirsk, the public tended to express a less desire to help, which was related to a stronger desire for social distance, whereas in Ulaanbaatar, labelling was related to a stronger desire for social distance, consistent with a greater lack of understanding. Greater differences were observed when the data were compared with Germany, where labelling had significant effect on the endorsement of the stereotype of dangerousness, but also evoked the perception of need for help. The authors suggested wider media coverage of associating mentally ill people with violent crime in Germany than in Russia and Mongolia might have affected public attitudes (Angermeyer & Schulze, 2001 [
A national representative sample in Australia and in Japan were surveyed to obtain opinions in relation to one of four vignettes describing depression, depression with suicidal thoughts, early schizophrenia and chronic schizophrenia (Jorm, et al., 2005) [
Jorm et al.’s (2005) [
The findings generated from DISL indicated that cultural differences (Anglo-Australian versus Chinese-Austra- lian nurses) were not attributable to differences between groups in relation to backgrounds variables or contact with people having a mental illness. Contact was better placed as a mediator in this relationship, particularly among the Chinese group membership (Ku & Ha, 2015 [
The authors would like to thank Victoria University Institute of Technology and Xian Jiaotong-Liverpool University for supporting and sponsoring the publication of this paper. The first author acknowledges the substantial intellectual contribution of the late Associate Professor Steven Klimidis to the formulation of the study.
The first author carried out the study under the supervision of the late Associate Professor Steven Klimidis at The Centre for International Mental Health (CIMH), Department of Psychiatry at The University of Melbourne and co-supervised by Associate Professor Harry Minas, Director at CIMH. The first author prepared the first draft of the paper and the second author verified statistical results and edited the paper. Both authors have approved the final version of the manuscript.
Tan Kan Ku,Michael Ha, (2015) Negative Stereotyping Attitudes towards Mental Illness: Is It Culturally Related?. Journal of Biosciences and Medicines,03,32-39. doi: 10.4236/jbm.2015.312006