Health & Place 24 (2013) 216–224

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Demographic and socio-cultural correlates of medical mistrust in two Australian States: Victoria and South Australia Andre Renzaho a,b,n, Michael Polonsky c, Zoe McQuilten d, Neil Waters e a

Global Health and Society Unit, School of Public Health and Preventive Medicine, Monash University, VIC 3004, Australia Centre for International Health, Burnet Institute, Level 3, 89 Commercial Road, Melbourne, VIC 3004, Australia c School of Management and Marketing, Deakin University, 70 Elgar Road, Burwood, VIC 3125, Australia d Transfusion Medicine Services, Australian Red Cross Blood Service, PO Box 354, South Melbourne, VIC 3205, Australia e Australian Red Cross Blood, 155 Pelham Street, CARLTON VIC 3053, VIC, Australia b

art ic l e i nf o

a b s t r a c t

Article history: Received 28 February 2013 Received in revised form 19 September 2013 Accepted 25 September 2013 Available online 17 October 2013

Studies on medical mistrust have mainly focused on depicting the association between medical mistrust and access/utilization of healthcare services. The effect of broader socio-demographic and psycho-social factors on medical mistrust remains poorly documented. The study examined the effect of broader sociodemographic factors, acculturation, and discrimination on medical mistrust among 425 African migrants living in Victoria and South Australia, Australia. After adjusting for socio-demographic factors, low medical mistrust scores (i.e., more trusting of the system) were associated with refugee (β ¼  4.27, po 0.01) and family reunion (β ¼  4.01, p o0.01) migration statuses, being Christian (β¼  2.21, po 0.001), and living in rural or village areas prior to migration (β ¼  2.09, po 0.05). Medical mistrust did not vary by the type of acculturation, but was positively related to perceived personal (β¼ 0.43, po 0.001) and societal (β ¼0.38, po 0.001) discrimination. In order to reduce inequalities in healthcare access and utilisation and health outcomes, programs to enhance trust in the medical system among African migrants and to address discrimination within the community are needed. Crown Copyright & 2013 Published by Elsevier Ltd. All rights reserved.

Keywords: African refugees and migrants Medical mistrust Acculturation Discrimination

1. Introduction Since the 1940s, countries of the Organisation for Economic Cooperation and Development (OECD) have experienced a demographic transition characterised by the increased immigration that followed the end of the Second World War, the boom and bust of the guest worker migration of the 1960s through to the 1970s, and various waves of refugees and humanitarian entrants associated with global conflicts (Organisation for Economic Co-operation and Development, 2011). Current estimates suggest that the number of international migrants has increased exponentially, growing from 77 million in 1960, to 195 million in 2005, and an estimated 214 million in 2010 (Minter, 2011). This represents 3.1% of the world's population, which does not include the 33.9 million people who are displaced people (i.e., refugees, asylum seekers, and stateless persons) (Pellegrini and Smith, 1998). Australia also has had a long

n Corresponding author at: Monash University, School of Public Health and Preventive Medicine, Global Health and Society Unit, Level 3, 89 Commercial Road, Melbourne, VIC 3004, Australia. Tel.: þ61 399 030 802; fax: þ61 399 030 556. E-mail addresses: [email protected] (A. Renzaho), [email protected] (M. Polonsky), [email protected] (Z. McQuilten), [email protected] (N. Waters).

history of migration, which has transformed the demographic composition of the Australian population. Until 1973 a “White Australia” policy explicitly excluded peoples of colour. The process of dismantling this policy started in about 1949–1950, following the end of the Second World War, amid fears that uncontrolled migration would result in Australia being ‘overrun' by Asians, when the Australian government embarked on policies to populate Australia with European migrants, fearing (Strahan, 1996; Department of Immigration and Citizenship, 2012). By 1949 Australia had allowed 800 non-white refugees to apply for residency and also allowed Japanese war brides to settle in Australia (Department of Immigration and Citizenship, 2012). In 1950, the Colombo Plan was instigated, allowing students from Asian countries access to Australian universities and by 1957 all non-European migrants with 15 years' work experience were allowed to apply for citizenship. From this point onwards things changed quickly: in 1959 legislation allowing the sponsoring of Asian spouses for citizenship was introduced. The conditions of entry for people of non-European backgrounds were further relaxed in 1964, and refugees fleeing the Vietnam War were allowed to settle in Australia in 1966 (Department of Immigration and Citizenship, 2012). Enforcement of racial aspects of the immigration law was effectively abolished in 1973 (Department of Immigration and Citizenship, 2012).

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A. Renzaho et al. / Health & Place 24 (2013) 216–224

The removal of the white Australia policy resulted in a more diverse migrant pool, including accepting refugees (i.e., forced migrants) from a wider range of countries (Campbell and Crawford, 2001) in addition to voluntary migration (e.g., economic/skilled migration or family reunion) (Cooke et al., 2004a). The 2011 census revealed that 26% of the Australian population were born overseas, with African migrants constituting one of the fastest growing sub-populations, and representing almost 1% of the Australian population (Australian Bureau of Statistics, 2011). Upon arrival in Australia, most migrants from developing countries including African countries such as Somalia, Eritrea, South Sudan, or Ethiopia often have high social and health needs, as well as experiencing health inequalities arising from their generally poor socio-economic position pre-migration, relative to the average Australian (Salmon et al., 2005; Martin and Mak, 2006). It has been found that even with this increased need, migrants (Kelaher et al., 1999; Martin and Mak, 2006), including those from Africa, (Cooke et al., 2004b; Caruana et al., 2006; Neale et al., 2007) tend to underutilise available health and social services. The reason for this underutilisation is unclear and may relate to a lack of integration into Australian society. However, it may be that there is some distrust of government services, as migrants and refugees' home countries were not necessarily concerned with protecting the needs and interests of vulnerable members of their respective communities, and governmental agencies were sometimes, in fact, agents of oppressive regimes (Eidelson and Horn, 2008). For example, around the world there have been cases of forced sterilisation of minority groups whom the ‘majority’ wishes to control (Presser, 1969; Brown, 1995; Hyatt, 1998; Sills et al., 1998; Benagiano et al., 2004; Holt, 2012). Low health participation rates in some areas could also be related to the way that some health issues such as mental health are seen to be stigmatized in migrants and refugees' home countries (Corrigan and Watson, 2002), thus making migrants and refugees less likely to admit to requiring psychological support in their adopted countries (Gross, 2004). This might partly explain why ethnic minorities such as indigenous and migrant populations report significantly higher levels of medical mistrust compared with the nonindigenous and non-migrant populations (Halbert et al., 2009; Navaza et al., 2012; Cleworth et al., 2006; Newman et al., 2012). Medical mistrust could potentially help explain disparities in health and poor utilisation of health services in host countries. This breach of trust between people and governments is not unique to migrant and refugee communities, for example, the Tuskegee syphilis experiments resulted in significant breach of trust between the health system (and government) and the African-American community, as African Americans were used to investigate the long-term impacts of syphilis without their knowledge or medical intervention (Thomas and Quinn, 1991; Brandon et al., 2005). Various researchers have argued that trust has both intrinsic and instrumental values (enforceable trust) (Rogers, 1994; Safran et al., 1998; Rhodes and Strain, 2000; Hall et al., 2001). Hofstede (2006) defines intrinsic trust as: “the trust that we may feel for a person ‘just like that’. Or, more precisely, at first acquaintance the feeling is ‘I think I can trust that person’, and also, ‘I would like to trust that person’. This feeling relates to the basic needs of human beings to affiliate with one another, to be friends. Then, with time, through being tested time and again and not broken, intrinsic trust can deepen” (p. 16). The intrinsic value of trust lies in the fact that it is the core ingredient of the provider-consumer relationship, giving such a relationship some meaning and importance (Rogers, 1994; Rhodes and Strain, 2000; Hall et al., 2001). In contrast, enforceable trust refers to the “trust that exists precisely because obligations are enforceable, not through recourse to law or violence but through the power of the community” (p. 9) such as community sanctions and ostracism (Portes, 1998). Hendriks (2010) notes that enforceable trust is “the result of individual members' disciplined compliance with group expectations that are

217

based on notions of good standing and expected benefits or punishment (p. 16). Thus, instrumentally, trust is a determinant of ongoing and sustained medical encounters, and influences an array of behaviours and attitudes associated with service access and utilisation as well as adherence to treatment (Safran et al., 1998; Rhodes and Strain, 2000; Hall et al., 2001). The variance in intrinsic and instrumental components of trust could potentially explain why a number of studies have found mistrust of healthcare organisations and health professionals to be associated with lower care satisfaction, treatment adherence, and utilization of healthcare services; low levels of blood and organ donation; and low participation in preventive health programs (Boulware et al., 2002; Ward and Coates, 2006; Bickell et al., 2009; LaVeist et al., 2009; Hammond, 2010; Bynum et al., 2012; Irving et al., 2012). The effect of mistrust has been found to be exacerbated by miscommunication of the purpose of the services, for example, cancer screening. Refugees often have a lack of information about healthcare systems and poor knowledge, and are confronted with the use of medical terminologies, as well as facing broader sociocultural and political constraints such as racism and discrimination, cultural factors, or institutions that are poorly equipped to engage with peoples from different cultures and language backgrounds (Bollini and Siem, 1995; Shahid et al., 2009; Navaza et al., 2012). Given the critical role of trust in facilitating people's engagement with the health system, it is surprising that there are few studies examining the correlates of medical mistrust, especially within migrant and refugee communities. The few available studies have mainly focused on examining differences between ethnic groups (Kirby et al., 2006; Armstrong et al., 2007) and the association between medical mistrust and access and utilization of healthcare services (Boulware et al., 2002; Ward and Coates, 2006; Bickell et al., 2009; LaVeist et al., 2009; Hammond, 2010; Bynum et al., 2012; Irving et al., 2012). However, the effects of broader socio-demographic (e.g., migration status, educational attainment, level of income or religion) and psycho-social (e.g., level of acculturation and discrimination) factors on medical mistrust remain poorly documented. In studies where psycho-social factors have been examined, the emphasis has been on the role played by acculturation and discrimination in the provision of healthcare services to migrant populations in developed countries rather than their influence on medical mistrust (Van der Stuyft et al., 1989). Acculturation, defined as the process of cultural exchanges and the adoption of the beliefs and behaviours of another group that result from two or more ethnic groups coming into contact (Flannery et al., 2001), influences decisions related to accessing and utilisation of healthcare services and is associated with increased use of primary care programs (Wiking et al., 2004; Sussner et al., 2009). Similarly, there is overwhelming evidence that discrimination negatively impacts health and creates associated health disparities (Wiking et al., 2004; Williams and Mohammed, 2009). It is possible that medical mistrust among migrant populations is influenced by the level of acculturation and perceived discrimination. However, very little research has explored how acculturation and discrimination influence migrants' trust of the healthcare system. To examine these issues this study, using African migrants in Australia as a case study, examined psycho-social and demographic factors as correlates of medical mistrust. We hypothesised that medical mistrust will vary according to the type of acculturation, perceived discrimination faced in the host community, and migrants' socio-economic status.

2. Methods This was a cross-sectional study of sub-Saharan African migrants and refugees living in Victoria and South Australia. The

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A. Renzaho et al. / Health & Place 24 (2013) 216–224

study's design and protocol focused on blood donation and have been described elsewhere (Polonsky et al., 2012; Renzaho and Polonsky, 2012). The data collection was designed to cover a crosssection of sub-Saharan African migrants and refugees living in Victorian and South Australia states, Australia. Our study focused mainly on respondents in urban areas of Melbourne and Adelaide because the majority of sub-Saharan African migrants and refugees tend to settle in urban areas due to the availability and affordability of public housing and employment opportunities. However, Shepparton, a rural town in Victoria was included in the study because of a significant number of sub-Saharan African migrants and refugees are relocating there in search of work. For example, of the 67,778 sub-Saharan African migrants and refugees settling in Victoria, with 5.4% (N ¼3,672) settling in rural areas, predominantly Shepparton (Australian Bureau of Statistics, 2011). In South Australia, however, less than 3% of the 13,989 subSaharan African migrants and refugees settled in rural areas, and thus we only focused in urban settings. Data were obtained on 483 African migrants and refugees aged 16 years or older (demographics shown in Table 1). The 58 participants who had incomplete responses on more than five percent of the items were excluded, resulting in a final sample of 425 migrants. Participants were recruited through leaflets and posters (English and Arabic) distributed throughout African community associations, Migrant Resource Centres, Community Health Organisations, and religious institutions. Bilingual workers were used to ensure that the survey could be communicated effectively with all migrants and refugees, including those with low levels of literacy in English and/or other languages. While those migrating under certain visa schemes would be expected to be fluent in English, this would not apply to all members of the applicants' family, nor would it apply for other visa categories (Department of Immigration and Citizenship, 2013). Bilingual speakers were recruited from with the targeted communities, to act as research assistants and interview participants, thus overcoming any issues associated with low literacy rates. Recruiting bilingual workers from within the various communities also ensured that a cross-section of communities was reached. The process of using bilingual workers in this study has been used in other research within the African community in Australia (Renzaho et al., 2010, 2011; Renzaho and Polonsky, 2012; Polonsky et al, 2011a, 2012). Bilingual workers were trained in delivering the survey in English, but were also able to deliver the survey in languages appropriate to the targeted communities. The languages covered within the pool of bilingual workers included English, Arabic, Swahili, Kirundi, and French. Training covered data collection, data quality, interview techniques, and data recording as well as ethical issues; and was complemented with two rounds of interview practice to familiarise bilingual workers with the study instrument and maximise the functional equivalence of the concepts across languages. The study

instrument was administered in either English or the participants' first language. This approach has been successfully used in past research in this sub-population (Renzaho et al., 2010, 2011). Bilingual workers also received a training manual documenting all aspects of the data collection procedure as a reference. Each participant received a $15 gift voucher for participating in the study. Ethics approval for the study was obtained from the Australian Red Cross Blood Service and Deakin University Human Research Ethics Committees. 2.1. Study variables 2.1.1. Dependent variables Previous qualitative research looking at blood donation in Australia (Polonsky et al., 2011a, 2011b) had identified that African migrants and refugees believed they had been mistreated within the health system in their home and host countries. These findings allowed us to select and expand the most appropriate medical mistrust scale. Therefore, we integrated LaVeist, Nickerson and Bowie's (2000) seven-item medical mistrust measure (see Fig. 1 for a list of the items). The questions were answered on a 7point Likert scale (1 ¼ strongly disagree, 7 ¼strongly agree), with a low score indicating trust in the healthcare system and a high score indicating mistrust in the healthcare system. Prior to the main analyses, the psychometric properties of the scale were established. 2.1.2. Independent variables 2.1.2.1. Discrimination. Research has found that discrimination (real and perceived) impacts on migrants' willingness to participate in health-related activities (Polonsky et al., 2011a, 2011b). For this study, an integrated measure of scales proposed by Phinney et al. (1998) and Verkuyten (1998), both of which have been applied in health settings, was used. This scale has 16-items that were answered on a 7-point Likert scale (1 ¼ strongly disagree, 7 ¼strongly agree). The psychometric properties of the scale in the study population were established prior to the main analysis (Fig. 2). 2.1.2.2. Acculturation. Scales measuring acculturation take alternative perspectives (Cabassa, 2003). One perspective is that people are more home or host country focused, whereas another is that people can, in fact, vary across both home and host country orientation simultaneously (Huynh et al., 2009). The latter approach allows researchers to take into consideration both home and host country experiences (Flannery et al., 2001). For this reason, the study used the Vancouver Index of Acculturation scale, containing 10 home country items and 10 host country items. The questions were answered on a 7-point Likert scale (1 ¼strongly disagree, 7 ¼strongly agree). To identify the types of acculturation, a median split for each of the two subscales

Table 1 Goodness of fit indices for the study variables. Variable Mistrust Medical mistrust; 7 items, 1-factor model African orientation Home-African orientation 10 items, 1-factor model Australian orientation Host-Australian orientation, 10 items, 1-factor model Discrimination Perceived discrimination: 10 items, 3-factor model

χ2 (df)

GFI

AGFI

CFI

TLI

RMSEA

86 (14)

0.943

0.88

0.93

0.89

0.10

153 (35)

0.93

0.89

0.89

0.86

0.089

197 (35)

0.90

0.85

0.90

0.87

0.10

86 (14)

0.943

0.88

0.93

0.89

0.10

GFI ¼Goodness-of-fit; AGFI¼ Adjusted goodness-of-fit; CFI ¼ Comparative Fit Index; TLI¼ Tucker Lewis Index, and RMSEA ¼ Root mean square error of approximation.

A. Renzaho et al. / Health & Place 24 (2013) 216–224

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Item scale: 1=Strongly disagree …………… 7=Strongly agree Items (ordered by loading) M4: Healthcare organisations have sometimes done harmful experiments on patients without their knowledge M7: Mistakes are common in healthcare organisations M5: Healthcare organisations don’t always keep your information totally private M2: Patients have sometimes been deceived or misled by healthcare organisations M6: Sometimes I wonder if healthcare organisations really know what they are doing M3: When healthcare organisations make mistakes they usually cover it up M1: You’d better be cautious when dealing with healthcare organisations Cronbach Alpha

Loading 0.7949 0.7652 0.7618 0.7545 0.7491 0.6251 0.4521 0.83

Fig. 1. Model testing and fitting for the medical mistrust scale.

Item scale: 1=Strongly disagree…… 7=Strongly agree Factor Personal discrimination F1.3: I am discriminated against by my fellow students/work colleagues because I have an African background F1.2: I am discriminated against by people outside school/work because I have an African background F1.1: I am discriminated against by my teachers/employer because I have an African background F1.4: I feel that I am not wanted in Australian society Cronbach Alpha Societal discrimination F2.2: People of African background are called names at work/school because of their African background F2.1: People of African background are teased at work/school because of their African background F2.3: People with an African background are discriminated against within the community Cronbach Alpha Exclusion F3.2: It is very easy for me to participate in group activities (hobbies, sport) with people from non-African backgrounds F3.1: It is very easy for me to make friends with people from non-African backgrounds F3.3: It is very easy for me to talk with people from nonAfrican backgrounds in my break at work/school Cronbach Alpha

Loading 0.8470 0.8170 0.7856 0.6509 0.870 0.8995 0.8629 0.8139 0.827 0.8840 0.8552 0.8495 0.920

Fig. 2. Model testing and fitting for the perceived discrimination scale.

(Home-African and Host-Australian) (Renzaho et al., 2008) was used as the criterion for group classification. Participants scoring above or below the median score were classified as having the respective high and low orientation. This gave four acculturation categories: traditional or separation (High African-Low Australia), assimilated (High Australian-Low African), integrated or bicultural (High on both), and marginalized (low on both) (Flannery et al., 2001).

sponsored/reunion, 2¼ other), educational attainment (0¼secondary or less, 1¼tertiary/TAFE), employment (0¼employed full-time, 1¼ employment part-time or casual, 2 ¼unemployed or social security), area lived in prior to migration (0 ¼refugee camp, 1 ¼ large city/town, 3 ¼village), and African region of birth based on country of birth (0 ¼ central, 1 ¼eastern, 2 ¼western, 3 ¼ southern). 2.2. Data analysis

2.1.2.3. Demographic and socio-economic factors. Data were collected regarding participants' gender (0 ¼ female; 1 ¼male), age, and length of stay in Australia in years, religion (0 ¼Muslim; 1 ¼Christian; 2¼ other), migration status (0 ¼refugees, 1 ¼ family

A two-stage analysis was undertaken. The first stage sought to test the validity and reliability of the constructs. Although these scales have been previously tested, their psychometric properties

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A. Renzaho et al. / Health & Place 24 (2013) 216–224

have varied across studies. Exploratory factor analysis, followed by Confirmatory Factor Analysis (CFA) using Maximum Likelihood Estimation as a means of validating the factor structure, were used. The following cut-off points were used to determine the robustness and the goodness of fit of each of the multi-item scales (MacCallum et al., 1996; Hu and Bentler, 1999; Kline, 2005): Goodness-of-fit statistic (GFI) and the adjusted goodness-of-fit statistic (AGFI) Z0.90; Comparative Fit Index (CFI) and Tucker Lewis Index (TLI) Z 0.90; Root Mean Square Error of Approximation (RMSEA) r0.08. Reliability was assessed by means of internal consistency using Cronbach Alpha, with a cut-off of 0.7 or above used to define an acceptable reliability coefficient (Nunnaly, 1978). The relationship between mistrust and demographic and socioeconomic factors, the type of acculturation, and discrimination were assessed using multiple linear regressions. The level of statistical significance was set at a probability of p o0.05 for all tests. SPSS version 17 and AMOS 20 (SPSS, Chicago, IL) were used for the initial analysis testing the reliability and validity of the constructs, and Stata version 11.0 (Stata Corporation, TX) was used for the main analysis.

(β¼1.13, 95% CI: 0.03, 2.23; p o0.05). In contrast, low medical mistrust scores (i.e., more trusting of the system) was associated with family reunion (β¼  3.61, 95% CI:  6.05,  1.18; p o0.01) and refugee (β¼  4.56, 95% CI: 6.74,  2.37; p o0.001) migration statuses, having lived in a rural town (β¼  2.55, 95% CI:  4.51,  0.58; p o0.05) prior to migration, and being Christian (β¼  1.91, 95% CI: 3.21,  0.61; p o0.01). Age, gender, length of stay in Australia and employment were not associated with medical mistrust. After adjusting for demographic and socioeconomic factors in the logistic regression model, migration status, western African origin, having lived in a rural town prior to migration, and being Christian remained associated with medical mistrust scores (Table 2).

3. Results

3.2.1. Perceived discrimination The discrimination scores averaged [mean (SD)] 9.19 (3.79) for personal discrimination, 11.42 (2.60) for exclusion, and 8.04 (3.16) for societal discrimination. Medical mistrust was positively related to perceived personal (β¼0.43, 95% CI: 0.29, 0.57; po 0.001) and societal (β¼ 0.38, 95% CI: 0.21, 0.55; p o0.001) discrimination, but not to exclusion. This pattern remained consistent after adjusting for socio-demographic factors (Table 3).

3.1. Psychometric properties of scales

3.3. Acculturation

The exploratory factor analyses found that the 7 items for mistrust loaded on one factor, with item loading above 0.45. CFA found that all seven items remain within the single dimensional scale and the scale had appropriate psychometric properties χ2 (14) ¼86, (p o0.001), GFI ¼0.943, AGFI ¼0.88, CFI ¼0.93, TLI¼ 0.89 and RMSEA ¼0.10 (Fig. 1). It also had a very good internal consistency (α¼ 0.83) (Table 1). The factor analysis identified that the discrimination scale had three sub-scales (with item loading above 0.45). However, many of the items cross-loaded on more than one dimension, thus, only ten items remained across the three sub-dimensions—experienced personal discrimination (4 items), exclusion/not fitting in (3 items), and societal discrimination (3 items) (Fig. 2). The model had appropriate psychometric properties: Chi-square (11) ¼ 50.881; CFI ¼0.98; TLI¼ 0.964; RMSEA ¼0.09; and standardized RMR¼0.04. The three factors had good internal consistency with a Cronbach α of 0.87, 0.92, and 0.83, respectively (Table 1). Although the Vancouver Acculturation Index has substantially been validated in many studies (Ryder et al., 2000; Huynh et al., 2009) we checked how it fitted our data. The items loaded well on each of the cultural orientations, with items loading above 0.45: African Orientation and Australian Orientation. Separate CFAs indicated that both dimensions had appropriate psychometric properties: Traditional Orientation  χ2 (35)¼153, (po 0.001), GFI¼ 0.93, AGFI ¼0.89, CFI ¼0.89, TLI ¼0.86 and RMSEA ¼0.089, and a very good internal consistency (α¼ 0.87); Australian orientation  χ2 (35)¼197, (p o0.001), GFI¼0.90, AGFI¼0.85, CFI ¼0.90, TLI¼ 0.87 and RMSEA ¼0.10 and a very good internal consistency (α¼ 0.82) (Table 1).

Approximately a third (34%) identified themselves as bicultural or integrated (i.e., high on both Australian and African Orientation), 20% identified as traditional or separated (low on Australian and high on African Orientation), 22% identified as assimilated (high on Australian and low on African Orientation), and 24% were found to be marginalised (low on both Australian and African Orientation). The medical mistrust scores did not vary by acculturation category, averaging [mean (SD)] 21.6 (5.9) for integrated, 21.7 (6.4) for traditional, 20.7 (5.5) for assimilated, and 21.7 (5.1) for marginalised) (Fig. 3). Acculturation was not associated with medical mistrust before or after controlling for confounding factors (Table 3).

3.2. Influence of demographic and socio-economic factors on medical mistrust The demographic characteristics of our sample and their relationship with medical mistrust are summarised in Table 2. The medical mistrust scores [Mean (SD)] averaged 21.5 (5.7). In the unadjusted model high medical mistrust scores (i.e., less trusting of the system) were associated with western (β¼2.62, 95%CI: 1.09, 4.16; po 0.001) and southern (β¼3.88, 95% CI: 1.52, 6.25; p o0.001) African regions of origin, and tertiary educational level

4. Discussion This cross-sectional study of 425 African migrants in Australia explored the correlates of medical mistrust. We hypothesised medical mistrust will vary according to the type of acculturation. This hypothesis was not confirmed. We found that acculturation was not associated with medical mistrust. Our findings contradict those reported by other researchers (Thompson et al., 2004; Tarn et al., 2005). In a study examining the role of ethnic match, autonomy, acculturation, and religiosity on trust in one's physician among Japanese and Japanese-Americans, Tarn et al. (2005) found that for Japanese-Americans, assimilation was associated with more trust of the healthcare system. In addition, Japanese physicians were trusted more than non-Japanese physicians. Interestingly, the study also found that Japanese-Americans who spoke English as well as those who spoke Japanese reported more trust than Japanese living in Japan, hence highlighting environmental influences on cultural attitudes towards the healthcare system. Tarn et al. (2005) findings are similar to those reported by Thompson et al. (2004), who found that traditionally-oriented individuals were more mistrustful of the healthcare system than their assimilated counterparts. These authors suggest that such a pattern could be a result of limited contact with conventional healthcare systems among traditionally-oriented individuals, or a conflict between mainstream health information and cultural health beliefs and values (Thompson et al., 2004).

A. Renzaho et al. / Health & Place 24 (2013) 216–224

221

Table 2 Demographic and socio-economic factors and their relationship to mistrust. Adjusteda

Unadjusted

Age in years 16–24 25–44 445 Mean (SD) Gender Female Male Length of stay in Australia 5 years or less More than 5 years Mean (SD) Migration status Other Family reunion Refugee Educational attainment Secondary or less Tertiary/TAFE Employment status Unemployed Employed full or part-time Other African region of origin Central Africa Eastern Africa Western Africa Southern Africa Area lived in prior to migration Refugee camp Large city/town Rural/village Religion Muslim Christian Other a

N

%

β

95% CI

p-value

β

95%CI

127 224 74 33.0 (12.3)

29.9 52.7 17.4

Ref  0.30  0.49

 1.55  2.14

0.96 1.17

0.644 0.564

Ref  0.42  0.37

 1.73  2.04

0.88 1.30

0.525 0.660

186 239

43.8 56.2

Ref  0.06

 1.17

1.04

0.910

Ref 0.10

 0.99

1.19

0.857

234 191

55.1 44.9 6.5 (5.2)

Ref  0.01

 0.12

0.09

0.790

Ref 0.80

 0.36

1.95

0.175

28 80 317

6.6 18.8 74.6

Ref  3.61  4.56

 6.05  6.74

 1.18  2.37

0.004 o 0.001

Ref  4.27  4.01

 6.98  6.60

 1.56  1.41

0.002 0.003

239 186

56.2 43.8

Ref 1.13

0.03

2.23

0.043

Ref  0.30

 1.55

0.95

0.637

184 187 54

43.3 44.0 12.7

Ref 0.65  0.90

 0.52  2.64

1.82 0.85

0.277 0.312

Ref  0.04  0.28

 1.30  1.99

1.23 1.44

0.952 0.752

146 159 78 25

35.8 39.0 19.1 6.1

Ref  0.79 2.62 3.88

 2.04 1.09 1.52

0.47 4.16 6.25

0.218 0.001 0.001

Ref  1.29 2.28 2.11

 2.59 0.66  0.71

0.02 3.89 4.93

0.053 0.006 0.142

80 291 53

18.9 68.6 12.5

Ref 0.77  2.55

 0.63  4.51

2.17  0.58

0.280 0.011

Ref 0.03  2.09

 1.44  4.10

1.50  0.09

0.965 0.040

98 304 23

23.1 71.5 5.41

Ref  1.91  3.04

 3.21  5.63

 0.61  0.44

0.004 0.022

Ref  2.21  2.14

 3.58  4.68

 0.83 0.39

0.002 0.097

p-value

Adjusted for factors in the table.

Table 3 The influence of acculturation and perceived discrimination on medical mistrust. Adjusteda

Unadjusted

Acculturation Integration Traditional Assimilation Marginalisation Personal discrimination Not fitting in: exclusion Societal discrimination a

β

95% CI

Ref 0.14  0.89 0.08 0.43 0.00 0.38

 1.41  2.39  1.38 0.29  0.22 0.21

1.69 0.61 1.54 0.57 0.21 0.55

p-value

β

95% CI

0.859 0.243 0.917 o 0.001 0.965 o 0.001

Ref 1.09  1.11  0.13 0.42  0.04 0.40

 0.43  2.59  1.52 0.28  0.25 0.23

p-value

2.61 0.37 1.27 0.55 0.16 0.56

0.160 0.142 0.860 o 0.001 0.690 o 0.001

Adjusted for factors statistically significant in Table 2 i.e., migration status, educational attainment, religion, African region of origin, and area lived in prior to migration.

A possible explanation for the difference in our findings compared with those by Tarn et al. (2005) and Thompson et al. (2004) could be in the instruments used. Our study used the widely-accepted and validated Vancouver Acculturation Index, which is a 20-item, bi-directional and bi-dimensional scale (Ryder et al., 2000) where both traditional cultural (heritage) and mainstream cultural identities are assumed to be free to vary independently (Berry and Kim, 1988; Berry, 1990). In contrast, Thompson et al. (2004) used a 7-item unidirectional linear acculturation scale measuring separately acculturation for African-American and Latino groups. Tarn et al. (2005) also used a 6-item unidirectional linear acculturation scale. When evaluating the strength of unidimensional or bi-dimensional acculturation

scales, Ryder et al (2000) found that, “although the unidimensional measure showed a coherent pattern of external correlates, the bi-dimensional measure revealed independent dimensions corresponding to heritage and mainstream culture identification” (p. 49). They concluded that the “bi-dimensional model is a more valid and useful operationalization of acculturation” (p. 49). The robustness of the Vancouver Acculturation Index's independence has also been confirmed by Kang (2006). Similarly, our measure of medical mistrust was based on LaVeist, Nickerson and Bowie's (2000) seven-item scale, which provided a one-factor model through confirmatory factor analysis. In contrast, Thompson et al. (2004) measure of medical mistrust included 12 items borrowed from various scales, namely: seven

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Fig. 3. Medical mistrust [Mean (SD)] by acculturation categories among African migrants.

items from the Group-Based Medical Mistrust Scale, two items from the Cultural Mistrust Inventory, two items from the Perceptions of Racism Scale, and one item on disadvantages of genetic testing for cancer. While exploratory factor analyses identified three factors (suspicion, group disparities in healthcare, and lack of support from healthcare providers), the authors did not undertake a confirmatory factor analysis. Tarn et al. (2005) measure of mistrust was a 3-item scale extracted from a 10-item scale assessing the influence of payment method on trust. The construct validity of these items was not established, although their internal consistency was assessed. We hypothesised medical mistrust will be associated with perceived discrimination faced in the host community. This hypothesis was confirmed. We found that perceived personal and societal discrimination were associated with increased mistrust of health services, which is consistent with findings from other studies. For example, one study of African-American men found that those participants who had the highest levels of medical mistrust had reported experiencing racial discrimination in the social environment (Hammond, 2010) and perceived racism was the most powerful correlate of medical mistrust after controlling for other factors. Hammond (2010) study also found that recent healthcare experiences were important, with respectful and empathetic interactions related to less medical mistrust. In a qualitative study on medical mistrust and discrimination in healthcare among Hmong women and men in Oregon, the analyses of transcripts from 83 interviews suggest that most participants trusted the healthcare system in the USA, although acculturation was not assessed (Thorburn et al., 2012). Notwithstanding, some participants expressed feelings of mistrust due to differential treatment according to types of health screening because of their migration status, characterised mainly by health professionals being disrespectful and/or rude (Thorburn et al., 2012). Finally, we hypothesised that medical mistrust will be associated with migrants' socio-economic status. This hypothesis was partially confirmed. We found that the region of origin in Africa, migration status and religion were associated with the level of medical mistrust. In contrast, the level of education, age, gender, employment status and length of stay in Australia were not

significantly associated with medical mistrust. Our finding that level of education was not associated with medical mistrust does not support the limited literature available. For example, Halbert et al. (2009) found an inverse relationship between level of educational attainment and levels of mistrust. However, our finding that age is not associated with level of medical mistrust is consistent with previous studies (Brandon et al., 2005). With regard to the association of African region of origin with medical mistrust, in one study exploring enablers of and barriers to access in the Dutch healthcare system among Ghanaians in Amsterdam, Boateng et al. (2012) reported that mistrust in healthcare providers and the healthcare system was a significant barrier to accessing healthcare. This study suggests that western African migrants to developed countries may develop a certain level of mistrust of the healthcare system in their host country, but further studies are required to confirm our findings that the level of mistrust is significant among migrants from western Africa but not those from central Africa. We found that Muslims mistrusted the healthcare system more than Christians. These finding are similar to those reported in northern Nigeria (Renne, 2009; Tocco, 2010) and in developed countries (Watters, 2001; AlKhawari et al., 2005; Smith, 2011). Participants who migrated under the Refugee and Humanitarian or Family Reunion Schemes were more trusting of the system than those who migrated under other migration schemes (e.g., educational attainment or skilled migrants). It is possible that many of these refugees come to Australia from refugee camps where they have been beneficiaries of western-style medical care, exposed to intensive preventive care (e.g., immunisation) and health education, and have developed familiarity with and knowledge of the western model of healthcare. Those migrating under non-refugee migration schemes may have also been exposed to the western health systems in their home countries, but their access to and utilisation of such a system might have been mediated by the level of socio-economic positioning, educational attainment, the setting (rural vs. urban), and cultural norms, as well as limited medical infrastructure within some home African countries. Further studies are required to confirm our findings among African migrants and refugees and other migrants in general. Previous reports have suggested that refugees may underutilize healthcare services, although reasons for this are not clear. An analysis of Victorian hospital admissions by Correa-Velez et al. (2007) found that compared with the Australian-born Victorian population, people born in refugee-source countries (including from Africa) had lower rates of surgical admission and total days in hospital, but that over the study period there was an upward trend approaching Australian-born averages. Correa-Velez et al.'s study was not able to determine whether the low levels of hospitalisation were as a result of unidentified barriers or due to reduced need for these services. However, there is evidence that some common health problems, including infectious diseases, are more prevalent in newly-arrived African refugees (Tiong et al., 2006; Sheikh et al., 2009) suggesting that the low levels of hospitalization are more likely to be due to barriers rather than reduced need. Barriers to accessing healthcare by African refugees previously reported have included language, education, poor understanding of the risk of illness and lack of information about health services (Sheikh-Mohammed et al., 2006). The higher level of trust reported by refugees in our study suggests that medical mistrust may not be an important barrier in accessing and participating in healthcare, which might explain why Sheikh-Mohammed et al. (2006) found African refugees in Australia report high levels of satisfaction with Australia's healthcare system. Our study has some limitations that need to be highlighted. African migrants in Australia are a hard-to-reach population, from

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collectivist cultures (preference for interdependence rather than autonomy) (Renzaho et al., 2011). It is not possible to identify a representative sample frame through random sampling. The purposeful sampling technique used in this study was the best option and the most appropriate approach for difficult-to-access populations, even though it may not necessarily yield a representative sample. The use of multiple community language may have impacted on our results, as using bilingual workers may have resulted in some loss of richness of the data during translation. In addition, the 2011 Australian census suggest that there are 272,520 sub-Saharan African migrants in Australia, the majority of whom settled in New South Wales (25%), Western Australia (24%), Victoria (22%) and Queensland (21%) (Australian Bureau of Statistics, 2011). Only five percent settled in South Australia and three percent in Tasmania and Australian Territories. Therefore, by focusing on Victoria and South Australia, our sample may not represent the general population of sub-Saharan African migrants living in Australia. Our findings therefore may not be generalizable to all African migrants and refugees in Australia. Further studies that include a large, multi-ethnic sample that reflect the multicultural nature of the Australian population are needed to confirm our findings across ethnic groups. Available evidence suggests that collectivism and autonomy preference are strongly associated with levels of medical mistrust (Tarn et al., 2005; Halbert et al., 2009). Further studies on medical mistrust among African migrants need to consider adjusting for autonomy orientation. The majority of participants in our study were from Eastern Africa (N ¼159) followed by Central Africa (N ¼146), Western Africa (N ¼78) and Southern Africa (N ¼25), Eastern African region was made predominantly of Somalia, Ethiopia, and Eritrea who are predominantly Arabic speakers. The Central African cohort was predominantly made of South Sudanese who are Arabic speakers, and Western African migrants and refugees were from Sierra Leone, Liberia, Ghana, and Nigeria, and predominantly Muslims, hence Arabic speakers. This could explain the underrepresentation of Southern Africa and this has been acknowledged as a limitation. Notwithstanding these limitations, our findings suggest that in order to reduce inequalities in healthcare access and utilisation as well as health outcomes, programs to enhance trust among African migrants and to address discrimination are urgently needed. Such programs could include a mix of broad educational programs, antiracism policy and legislative reform to address societal racism, as well as advocacy and workforce and organisational development to address institutionalised racism.

Acknowledgements The project was funded by the Australian Red Cross Blood Service. We would like to acknowledge the Australian Red Cross Blood Service (the Blood Service), and the Australian governments that fully fund the Blood Service for the provision of blood products and services to the Australian community. We also gratefully acknowledge members of the African Review Panel for their assistance with recruitment and community mobilisation. In addition, we would like to thank the African refugee and migrant communities for endorsing and participating in the study. A/Prof. Andre Renzaho is supported by an ARC Future Fellowship. Andre Renzaho and Michael Polonsky designed the study and all instruments used in the study. Andre Renzaho undertook the data analysis and drafted the article. Michael Polonsky, Neil Waters and Zoe McQuilten made substantial contribution in the interpretation of the data, intellectual input during the write up stage and critically reviewed the manuscript. All authors have approved its submission.

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References AlKhawari, F.S., Stimson, G.V., Warrens, A.N., 2005. Attitudes toward transplantation in U.K. Muslim Indo-Asians in West London. Am. J. Transplant. 5 (6), 1326–1331. Armstrong, K., Ravenell, K.L., McMurphy, S., Putt, M., 2007. Racial/ethnic differences in physician distrust in the United States. Am. J. Public Health 97 (7), 1283–1289. Australian Bureau of Statistics, 2011. 2011 Census of Population and Housing. Counting: Persons, Place of Usual Residence. ABS TableBuilder. ABS, Canberra. Benagiano, G., Testa, G., Cocuzzi, L., 2004. The meaning of fertility control in an integrated world]. Minerva Ginecol. 56 (3), 271–281. Berry, J.W., 1990. Acculturation and adaptation: health consequences of culture contact among Circumpolar peoples. Act Med. Res. 49, 142–150. Berry, J.W., Kim, U., 1988. Acculturation and mental health. In: Dasen, P., Berry, J.W., Sartorius, N. (Eds.), Health and Cross-cultural Psychology. Sage, London. Bickell, N.A., Weidmann, J., Fei, K., Lin, J.J., Leventhal, H., 2009. Underuse of breast cancer adjuvant treatment: patient knowledge, beliefs, and medical mistrust. J. Clin. Oncol. 27 (31), 5160–5167. Boateng, L., Nicolaou, M., Dijkshoorn, H., Stronks, K., Agyemang, C., 2012. An exploration of the enablers and barriers in access to the Dutch healthcare system among Ghanaians in Amsterdam. BMC Health Serv. Res. 12 (1), 75. Bollini, P., Siem, H., 1995. No real progress towards equity: health of migrants and ethnic minorities on the eve of the year 2000. Soc. Sci. Med. (1982) 41 (6), 819–828. Boulware, L.E., Ratner, L.E., Cooper, L.A., Sosa, J.A., LaVeist, T.A., Powe, N.R., 2002. Understanding disparities in donor behavior: race and gender differences in willingness to donate blood and cadaveric organs. Med. Care 40 (2), 85–95. Brandon, D.T., Isaac, L.A., LaVeist, T.A., 2005. The legacy of Tuskegee and trust in medical care: is Tuskegee responsible for race differences in mistrust of medical care? J. Nat. Med. Assoc. 97 (7), 951–956. Brown, T.A., 1995. Forced abortions and involuntary sterilization in China: are the victims of coercive population control measures eligible for asylum in the United States? San Diego Law Rev. 32 (3), 745–769. Bynum, S.A., Davis, J.L., Green, B.L., Katz, R.V., 2012. Unwillingness to participate in colorectal cancer screening: examining fears, attitudes, and medical mistrust in an ethnically diverse sample of adults 50 years and older. Am. J. Health Promo.: AJHP 26 (5), 295–300. Cabassa, L.J., 2003. Measuring acculturation: where we are and where we need to go. Hispan. J. Behav. Sci. 25 (2), 127–146. Campbell, K., Crawford, D., 2001. Family food environments as determinants of preschool aged children's eating behaviours: implication for obesity prevention policy. Aust. J. Nutr. Diet. 58, 19–25. Caruana, S.R., Kelly, H.A., Ngeow, J.Y.Y., Ryan, N.J., Bennett, C.M., Chea, L., et al., 2006. Undiagnosed and potentially lethal parasite infections among immigrants and refugees in Australia. J. Travel Med. 13 (4), 233–239. Cleworth, S., Smith, W., Sealey, R., 2006. Grief and courage in a river town: a pilot project in the Aboriginal community of Kempsey, New South Wales. Australas. Psychiatry 14 (4), 390–394. Cooke, L., Wardle, J., Gibson, E., Sapochnik, M., Sheiham, A., Lawson, M., 2004a. Demographic, familial and trait predictors of fruit and vegetable consumption by pre-school children. Public Health Nutr. 7, 295–302. Cooke, R., Murray, S., Carapetis, J., Rice, J., Mulholland, N., Skull, S., 2004b. Demographics and utilisation of health services by paediatric refugees from East Africa: implications for service planning and provision. Aust. Health Rev. 27 (2), 40–45. Correa-Velez, I., Sundararajan, V., Brown, K., Gifford, S.M., 2007. Hospital utilisation among people born in refugee-source countries: an analysis of hospital admissions, Victoria, 1998–2004. Med. J. Aust. 186 (11), 577–580. Corrigan, P.W., Watson, A.C., 2002. Understanding the impact of stigma on people with mental illness. World Psychiatry 1, 16–20. Department of Immigration and Citizenship, 2013. Fact Sheet 94—English Courses for Eligible Migrants and Humanitarian Entrants in Australia 〈http://www. immi.gov.au/media/fact-sheets/94amep.htm〉. Accessed 7.09/2013. Department of Immigration and Citizenship, 2012. Fact Sheet 8—Abolition of the ‘White Australia' Policy. Available at: 〈http://www.immi.gov.au/media/factsheets/08abolition.htm〉. Accessed 3 August 2013. Eidelson, R.J., Horn, R., 2008. Who wants to return home: a survey of sudanese refugees in Kakuma, Kenya. Refuge 25 (1), 15–26. Flannery, W.P., Reise, S.P., Yu, J., 2001. An empirical comparison of acculturation models. Pers. Soc. Physchol. Bull. 27 (8), 1035–1045. Gross, C.S., 2004. Struggling with imaginaries of Trauma and Trust: the refugee experience in Switzerland. Cult. Med. Psychiatry 28 (2), 151–167. Halbert, C.H., Weathers, B., Delmoor, E., Mahler, B., Coyne, J., Thompson, H.S., et al., 2009. Racial differences in medical mistrust among men diagnosed with prostate cancer. Cancer 115 (11), 2553–2561. Hall, M.A., Dugan, E., Zheng, B., Mishra, A.K., 2001. Trust in physicians and medical institutions: what is it, can it be measured, and does it matter? Milbank Q. 79 (4), 613. Hammond, W.P., 2010. Psychosocial correlates of medical mistrust among African American men. Am. J. Community Psychol. 45 (1-2), 87–106. Hendriks, H., 2010. Urban Livelihoods, Institutions and Inclusive Governance in Nairobi: ‘Spaces' and their Impacts on Quality of Life, Influence and Political Rights. Amsterdam University Press.

224

A. Renzaho et al. / Health & Place 24 (2013) 216–224

Hofstede, G.J., 2006. Intrinsic and Enforceable Trust: A Research Agenda. In Trust and Risk in Business Networks. Universität Bonn-ILB Press, Bonn, pp. 15–24. Holt, E., 2012. Uzbekistan accused of forced sterilisation campaign. Lancet 379 (9835), 2415. Hu, L., Bentler, P., 1999. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct. Equ. Model.: Multi. J. 6 (1), 1–55. Huynh, Q.-L., Howell, R.T., Benet-Martínez, V., 2009. Reliability of bidimensional acculturation scores. J. Cross Cult. Psychol. 40 (2), 256–274. Hyatt, S., 1998. A shared history of shame: Sweden's four-decade policy of forced sterilization and the eugenics movement in the United States. Indiana Int. Comp. Law Rev. 8 (2), 475–503. Irving, M.J., Tong, A., Jan, S., Cass, A., Rose, J., Chadban, S., et al., 2012. Factors that influence the decision to be an organ donor: a systematic review of the qualitative literature. Nephrol. Dial. Transplant. 27 (6), 2526–2533. Kang, S.-M., 2006. Measurement of acculturation, scale formats, and language competence. J. Cross Cult. Psychol. 37 (6), 669–693. Kelaher, M., Williams, G., Manderson, L., 1999. Towards evidence-based health promotion and service provision for New Migrants to Australia. Ethnicity Health 4 (4), 305–313. Kirby, J.B., Taliaferro, G., Zuvekas, S.H., 2006. Explaining racial and ethnic disparities in health care. Med. Care 44 (5), http://dx.doi.org/10.1097/1001. mlr.0000208195.0000283749.c0000208193. (I-64-I-72). Kline, R.B., 2005. Principles and Practice of Structural Equation Modeling, second ed. The Guilford Press, New York. LaVeist, T.A., Isaac, L.A., Williams, K.P., 2009. Mistrust of health care organizations is associated with underutilization of health services. Health Serv. Res. 44 (6), 2093–2105. LaVeist, T.A., Nickerson, K.J., Bowie, J.V., 2000. Attitudes about racism, medical mistrust, and satisfaction with care among African American and White Cardiac Patients. Med. Care Res. Rev. 57 (Suppl. 4), 146–161. MacCallum, R.C., Browne, M.W., Sugawara, M., H., 1996. Power analysis and determination of sample size for covariance structure modeling. Psychol. Methods 1 (2), 130–149. Martin, J., Mak, D., 2006. Changing faces: a review of infectious disease screening of refugees by the Migrant Health Unit, Western Australia in 2003 and 2004. MJA 185, 607–610. Minter, W., 2011. African Migration, Global Inequalities, and Human Rights: Connecting the Dots. Nordiska Afrikainstitutet, Uppsala. Navaza, B., Guionnet, A., Navarro, M., Estévez, L., Pérez-Molina, J.A., López-Vélez, R., 2012. Reluctance to do blood testing limits HIV diagnosis and appropriate health care of sub-Saharan African migrants living in Spain. AIDS Behav. 16 (1), 30–35. Neale, A., Ngeow, J.Y.Y., Skull, S.A., Biggs, B.-A., 2007. Health services utilisation and barriers for settlers from the Horn of Africa. Aust. N. Z. J. Public Health 31 (4), 333–335. Newman, P., Woodford, M., Logie, C., 2012. HIV vaccine acceptability and culturally appropriate dissemination among sexually diverse Aboriginal peoples in Canada. Global Public Health 7 (1), 87–100. Nunnaly, J., 1978. Psychometric Theory. McGraw-Hill, New York. Organisation for Economic Co-operation and Development, 2011. International Migration Outlook 2011. OECD, Paris, ISBN: 9789264112612. (Sopemi ed.). Pellegrini, A., Smith, P., 1998. Physical activity play: the nature and function of a neglected aspect of playing. Child Dev. 69, 577–598. Phinney, J.S., Madden, T., Santos, L.J., 1998. Psychological variables as predictors of perceived ethnic discrimination among minority and immigrant adolescents1. J. Appl. Soc. Psychol. 28 (11), 937–953. Polonsky, M.J., Brijnath, B., Renzaho, A.M.N., 2011a. They don't want our blood: social inclusion and blood donation among African migrants in Australia. Soc. Sci.Med. 73 (2), 336–342. Polonsky, M.J., Renzaho, A.M.N., Brijnath, B., 2011b. Barriers to blood donation in African communities in Australia: the role of home and host country culture and experience. Transfusion 51 (8), 1809–1819. Polonsky, M.J., Renzaho, A.M.N., Ferdous, A., McQuilten, M., 2012. African culturally and linguistically diverse (CALD) communities' blood donation intentions in Australia: integrating knowledge into the theory of planned behaviour. Transfusion. (Accepted 20 Aug 2012). Portes, A., 1998. Social capital: its origins and applications in modern sociology. Annu. Rev. Sociol. 24, 1–24. Presser, H.B., 1969. The role of sterilization in controlling Puerto Rican fertility. Popul. Stud. 23 (3), 343–361. Renne, E., 2009. Anthropological and public health perspectives on the global polio eradication initiative in northern Nigeria. In: Hahn, R., Inhorn, M. (Eds.), Anthropology and Public Health: Bridging Differences in Culture and Society. Oxford University Press, Oxford. Renzaho, A., Swinburn, B., Burns, C., 2008. Maintenance of traditional cultural orientation is associated with lower rates of obesity and sedentary behaviours among African migrant children to developed countries. Int. J. Obes. 32, 594–600.

Renzaho, A.M.N., Green, J., Mellor, D., Swinburn, B., 2011. Parenting, family functioning and lifestyle in a new culture: the case of African migrants in Melbourne, Victoria, Australia. Child Family Social Work 16, 228–240. Renzaho, A.M.N., McCabe, M., Sainsbury, W.J., 2010. Parenting, rolereversals and the preservation of cultural values among Arabic speakingmigrant families in Melbourne, Australia. Int. J. Intercul. Relat. 35 (4), 416–424. Renzaho, A.M.N., Polonsky, M.J., 2012. Examining demographic and socio-economic correlates of accurate knowledge about blood donation among African migrants in Australia. Transfus. Med. 22 (5), 321–331. Rhodes, R., Strain, J.J., 2000. Trust and transforming medical institutions. Camb. Q. Healthc. Ethics 9 (2), 205–217. Rogers, D.E., 1994. On trust: A Basic Building Block for Healing Doctor/patient Interactions. The Pharos Of Alpha Omega Alpha-Honor Medical Society. Alpha Omega Alpha 57 (2), 2–6. Ryder, A.G., Alden, L.E., Paulhus, D.L., 2000. Is acculturation unidimensional or bidimensional? A head-to-head comparison in the prediction of personality, self-identity, and adjustment. J. Pers. Soc. Psychol. 79 (1), 49–65. Safran, D.G., Taira, D.A., Rogers, W.H., Kosinski, M., Ware, J.E., Tarlov, A.R., 1998. Linking primary care performance to outcomes of care. J. Fam. Pract. 47 (3), 213–220. Salmon, J., Timperio, A., Telford, A., Carver, A., Crawford, D., 2005. Association of family environment with children's television viewing and with low level of physical activity. Obes. Res. 13, 1939–1951. Shahid, S., Finn, L.D., Thompson, S.C., 2009. Barriers to participation of Aboriginal people in cancer care: communication in the hospital setting. Med. J. Aust. 190 (10), 574–579. Sheikh-Mohammed, M., Macintyre, C.R., Wood, N.J., Leask, J., Isaacs, D., 2006. Barriers to access to health care for newly resettled sub-Saharan refugees in Australia. Med. J. Aust. 185 (11–12), 594–597. Sheikh, M., Pal, A., Wang, S., MacIntyre, C.R., Wood, N.J., Isaacs, D., et al., 2009. The epidemiology of health conditions of newly arrived refugee children: a review of patients attending a specialist health clinic in Sydney. J. Paediatr. Child Health 45 (9), 509–513. Sills, E.S., Strider, W., Hyde, H.J., Anker, D., Rees, G.J., Davis, O.K., 1998. Gynaecology, forced sterilisation, and asylum in the USA. Lancet 351 (9117), 1729–1730. Smith, J., 2011. Removing Barriers to Therapy with Muslim-Arab-American Clients. Ph.D. Dissertation. Antioch University, New England. Strahan, L., 1996. Australia's China: Changing Perceptions from the 1930s to the 1990s. University of Cambrige Press, Cambridge. Sussner, K.M., Thompson, H.S., Valdimarsdottir, H.B., Redd, W.H., Jandorf, L., 2009. Acculturation and familiarity with, attitudes towards and beliefs about genetic testing for cancer risk within Latinas in East Harlem, New York City. J. Genet. Couns. 18 (1), 60–71. Tarn, D., Meredith, L., Kagawa-Singer, M., Matsumura, S., Bito, S., Oye, R., et al., 2005. Trust in one's physician: the role of ethnic match, autonomy, acculturation, and religiosity among Japanese and Japanese Americans. Ann. Fam. Med. 3, 339–347. Tarn, D.M., Meredith, L.S., Kagawa-Singer, M., Matsumura, S., Bito, S., Oye, R.K., et al., 2005. Trust in one's physician: the role of ethnic match, autonomy, acculturation, and religiosity among Japanese and Japanese Americans. Ann. Fam. Med. 3 (4), 339–347. Thomas, S.B., Quinn, S.C., 1991. The Tuskegee Syphilis Study, 1932 to 1972: implications for HIV education and AIDS risk education programs in the black community. Am. J. Public Health 81 (11), 1498–1505. Thompson, H.S., Valdimarsdottir, H.B., Winkel, G., Jandorf, L., Redd, W., 2004. The group-based medical mistrust scale: psychometric properties and association with breast cancer screening. Prev. Med. 38 (2), 209–218. Thorburn, S., Kue, J., Keon, K.L., Lo, P., 2012. Medical mistrust and discrimination in health care: a qualitative study of Hmong women and men. J. Community Health 37 (4), 822–829. Tiong, A.C., Patel, M.S., Gardiner, J., Ryan, R., Linton, K.S., Walker, K.A., et al., 2006. Health issues in newly arrived African refugees attending general practice clinics in Melbourne. Med. J. Aust. 185 (11–12), 602–606. Tocco, J.U., 2010. Every disease has its cure: faith and HIV therapies in Islamic northern Nigeria. Afr. J. AIDS Res. 9 (4), 385–395. Van der Stuyft, P., De Muynck, A., Schillemans, L., Timmerman, C., 1989. Migration, acculturation and utilization of primary health care. Soc. Sci. Med. 29 (1), 53–60. Verkuyten, M., 1998. Perceived discrimination and self-esteem among ethnic minority adolescents. J. Soc. Psychol. 138 (4), 479–493. Ward, P., Coates, A., 2006. 'We shed tears, but there is no one there to wipe them up for us’: narratives of (mis)trust in a materially deprived community. Health (London, England: 1997) 10 (3), 283–301. Watters, C., 2001. Emerging paradigms in the mental health care of refugees. Soc. Sci. Med. 52 (11), 1709–1718. Wiking, E., Johansson, S.-E., Sundquist, J., 2004. Ethnicity, acculturation, and self reported health. A population based study among immigrants from Poland, Turkey, and Iran in Sweden. J. Epidemiol. Community Health 58 (7), 574–582. Williams, D., Mohammed, S., 2009. Discrimination and racial disparities in health: evidence and needed research. J. Behav. Med. 32 (1), 20–47.