Introduction
It is generally accepted that having a positive view of oneself is beneficial to health and wellbeing. Those with a high self-esteem (or self-concept) can cope more efficiently with life's challenges; they feel valued, respected and generally lead happy and productive lives [
1]. Those “who feel good about themselves and their abilities are likely to be more effective than individuals with low self-concepts” and are less likely to have anxiety or depression [
2].
Links between racial identity (also referred to as cultural identity, ethnic identity, or racial-ethnic identity) and positive self-esteem have been explored by various researchers around the world. Corenblum [
3] states that “racial-ethnic identity and self-esteem are important indicators of positive mental health and adjustment among low status and minority group members”, and that positive racial identity provides a buffer against the negative impacts of prejudice and discrimination often experienced by minority groups. In general, the extent to which one’s cultural group is recognised and clearly defined in one’s mind is positively related to a clear definition of one’s self and subsequently, one’s self-esteem [
4‐
6].
Since the 1960’s, researchers have developed measures of self-esteem. These encompass relatively long scales, such as the
Piers-Harris Children’s Self-Concept Scale [
7] and the
Coopersmith Self-Esteem Inventory [
8] as well as the shorter
Rosenberg Self-Esteem Scale [
9] originally designed to measure self-esteem in high school students. In Australia, Marsh [
10] developed a
Self-Description Survey which measures nine factors specific to physical self-concept: Activity, Appearance, Body Fat, Coordination, Endurance, Flexibility, Health, Sport and Strength, as well as measures of Global Physical and Global Esteem.
Other researchers have moved away from generic measures of self-esteem to measures more explicitly centered on racial and cultural identity. The “Multi-dimensional Model of Māori Identity and Cultural Engagement” [
11] was designed specific for Māori populations in New Zealand. It was developed to measure identity and cultural engagement, but does not specifically focus on the link between racial identity and self-esteem. It was also designed and tested on adults aged 18–74 years.
The link however between self-esteem and racial identity for Australian Aboriginal children has never been made or rarely estimated. Historically, health and wellbeing frameworks have been developed using research based on general population groups. Many of the concepts in existing scales do not align themselves with Aboriginal worldview and particularly concepts of health and wellbeing. For Australian Aboriginal populations, the definition of health “is not just the physical wellbeing of an individual, but the social, emotional and cultural wellbeing of the whole community” [
12]. Hence, it is important to develop instruments specifically for the Australian Aboriginal experience, with Aboriginal involvement in all stages of research. This is “a matter of both ethics and rigor and … is considered vital if health inequalities are to be addressed” [
13]. Furthermore, any programs developed from the findings of studies using the instrument are unlikely to be effective if there is not a “high level of Indigenous ownership and community support” [
14].
The measurement of self-esteem across cultures can be difficult, particularly when one culture places a higher value on particular issues than others. For example, Western cultures tend to place a higher value on issues of independence and self-reliance, whereas more traditional societies (such as Aboriginal groups) more commonly value collectivism and a strong reliance on social support [
15]. School achievement is a good example. Self-esteem might be more valued in Western society where the emphasis is less on family and community extensions of self but on individualism and competition [
15].
A measure of self-esteem developed in Western cultures will not necessarily be valid in other societies. Purdie & McCrindle [
15] discuss a range of potential sources of error that can occur when using an instrument developed in a different culture. Firstly, concepts may be interpreted differently across cultures. Secondly, there may be a degree of method bias introduced, in terms of how the instrument is administered and whether it is culturally appropriate. Response errors increase when the instrument is designed and administered by a person from a different culture [
16]. Responses could be affected by reading ability (which may not be particularly strong in some cultures), by expected cultural norms (some societies are known to always answer in the affirmative, so as not to disagree with the interviewer) and by the race of the interviewer (if different to the respondent) [
15]. Finally, item bias may occur if questions can have different meanings for different cultural groups, for example, the use of colloquialisms may affect a respondent’s understanding [
15].
Aside from needing an instrument that is specifically designed for Aboriginal populations, the instrument needs to be suitable for children and use language that Aboriginal children will relate to. Racial identity is formed gradually, starting from as young as 4 years of age and developing more fully as a child grows. Byrd [
17] identifies three aspects of racial identity: a) awareness (the ability to distinguish between members of different races); b) identification (the ability to name one’s own race); and c) attitudes (beliefs about the characteristics between different racial groups). Awareness and identification become stable by adolescence, so studies that deal with racial issues in adults focus mainly on attitudes. However, in children awareness and identification are also important. The age at which awareness develops varies, but most children are not able to correctly classify individuals by race until they are four or five, although awareness begins as soon as they can notice differences in people’s skin colour, hair, eye colour, which can be distinguished as young as 2–3 years old [
18,
19]. Ability to self-identify comes by around four to six years of age. Knowing that one’s race will not change (racial constancy) develops somewhat later, at around ten to twelve years. Children gradually increase the complexity of their understanding of racial differences as they grow older.
It is important to be able to track how racial identity and self-esteem develop over childhood and adolescent years. Currently, most available tools for measuring self-esteem have been developed for adults or adolescents (with some modified for children) and lack specificity to Aboriginal populations. A self-report survey is not best suited to younger children who are still developing literacy skills. We report here on a self-esteem scale called the IRISE-C, designed by an Aboriginal researcher based on a literature review and Aboriginal community consultation, and using terms that would be well understood by Aboriginal children. It was administered by Aboriginal Community Research Assistants (ACRA) asking and recording the children’s answers, eliminating the need for literacy proficiency. The terminology used in the IRISE_C mirrors the language Aboriginal children use and thereby reducing misunderstanding of questions. Aboriginal Community Research Assistants asked each question and used visual score charts for the participants to indicate their responses. The purpose, content and procedures for the IRISE_C have been developed in accordance with the wider Aboriginal community’s communication protocols and culturally safe and secure practices deemed appropriate for Australian Aboriginal children aged 8–12 years.
Results
Exploratory factor analysis
Knowledge questions
A visual inspection of the correlations matrix for the knowledge questions identified several correlations above 0.3 in the dataset, with each item (other than Q.26. ‘How much do you get ‘shame’ because you are Aboriginal?’) having correlations above 0.3 with other items. The KMO was 0.873 and Bartlett’s test of sphericity was significant (chi-square (171) = 1127.3, p < 0.001), supporting factorability of the dataset.
In the analysis 2, 3 and 4 factor solutions were examined, but the 2-factor solution came closest to simple structure. An initial analysis showed all items had communalities greater than 0.2, other than Q.21. ‘Like to have a good laugh’ and Q.26. ‘How much do you get ‘shame’ because you are Aboriginal’ (reverse coded). After consultation with the survey creator, these items were excluded from this analysis as field experience indicated that the children in the study did not understand these concepts which may better apply to the racial identities of older children.
Principal Axis Factoring of the Knowledge items supported a 2-factor solution, which explained 38.7 % of variance. The correlation between the knowledge factors was 0.628. The first factor represents ‘Aboriginal culture,’ the second factor represents ‘racial identity’. Although not shown, there was also evidence to support combining all measures into an overall ‘omnibus’ measure.
Factor One (Aboriginal culture) had a Cronbach’s alpha of 0.835; Factor 2 (racial identity) had a Cronbach’s alpha of 0.800 (Table
2).
Table 2
Knowledge items (restricted item pool, excludes ‘shame’ and ‘laugh’)
Q1. How much do you know about how Aboriginal people lived in the old days? | 0.544 | | 0.253 |
Q3. How much do you know about Aboriginal Week activities? | 0.398 | | 0.169 |
Q5. How much do you like playing with Aboriginal kids? | | 0.652 | 0.447 |
Q7. How much have you learned to make Aboriginal foods like damper? | 0.739 | | 0.415 |
Q9. How much do you like being Aboriginal? | | 0.746 | 0.464 |
Q11. How much are you the same as other Aboriginal kids? | | 0.374 | 0.234 |
Q13. How much do you know about Aboriginal stories of the Dreaming (Dreamtime)? | 0.547 | | 0.340 |
Q15. How much do Aboriginal kids make you feel part of their group at school? | | 0.393 | 0.340 |
Q17. How much do you talk Aboriginal words? | 0.594 | | 0.375 |
Q19. How much does your family tell you about being Aboriginal? | 0.604 | | 0.431 |
Q23. How much do you like Aboriginal people as friends? | | 0.479 | 0.330 |
Q28. How much are you proud of being Aboriginal? | | 0.93 | 0.737 |
Q30. How much do Aboriginal kids help each other? | | 0.339 | 0.315 |
Q33. How much do you like the Aboriginal flag? | | 0.636 | 0.393 |
Q35. How much do you go bush with your family? | 0.540 | | 0.332 |
Q37. How much have you eaten Aboriginal foods, like kangaroo? | 0.546 | | 0.446 |
Q39. How much do you know about the dances Aboriginal people did in the old days? | 0.700 | | 0.554 |
Total variance explained (%) | 32.3 % | 6.3 % | |
Cronbach’s alpha | 0.835 | 0.800 | |
Correlation between factors 1& 2 (knowledge): 0.628 | | | |
Salience questions
A visual inspection of the correlations matrix identified that with each item had correlations above 0.3 with other items. The KMO was 0.913 and Bartlett’s test of sphericity was significant (chi-square (136) = 1242.85, p < 0.001), supporting factorability of the dataset.
Following the analysis of the questions relating to knowledge, the salience questions relating to having a laugh (Q.22. ‘How important is it to you to have a good laugh’) and shame (Q.27. ‘How important is it for you to not be ‘shame’ of being Aboriginal’) were excluded from the analysis.
In the analysis, 2, 3 and 4 factor solutions were examined, but the 2-factor solution came closest to simple structure. An initial analysis showed all items had communalities greater than 0.2.
Principal Axis Factoring of the salience items supported a 2-factor solution, which explained 44.6 % of variance. The correlation between the salience factors was 0.691. Only one item (Q. 38 How important is it for you to eat Aboriginal foods?) cross-loaded. The pattern of loadings was reversed relative to the knowledge items, with the second factor extracted representing ‘Aboriginal culture’, and the first factor extracted the second factor representing ‘racial identity’ (Table
3).
Table 3
Salience items (complete item pool, excludes ‘shame’ and ‘laugh’)
Q2. How important is it for you to know about how Aboriginal people lived in the old days? | 0.591 | | 0.356 |
Q4. How important is it that you to do activities for Aboriginal Week? | 0.667 | | 0.383 |
Q6. How important is it for you to play with Aboriginal kids? | | 0.743 | 0.552 |
Q8. How important is it for you to make Aboriginal foods like damper? | 0.751 | | 0.468 |
Q10. How important is it for you that you’re Aboriginal? | | 0.446 | 0.262 |
Q12. How important is it for you to be the same as other Aboriginal kids? | | 0.63 | 0.463 |
Q14. How important is it for you to know about Aboriginal stories of the Dreaming? | 0.551 | | 0.515 |
Q16. How important is it for you to feel part of the Aboriginal group at school? | | 0.787 | 0.488 |
Q18. How important is it for you to talk Aboriginal words? | 0.723 | | 0.462 |
Q20. How important is it for you that your family tells you about being Aboriginal? | 0.396 | | 0.462 |
Q24. How important is it for you to have Aboriginal people as friends? | | 0.871 | 0.678 |
Q29. How important is it for you to be proud of being Aboriginal? | | 0.62 | 0.454 |
Confirmatory factor analysis
Each model fitted has been fitted on complete (non-missing) data. Model specification was undertaken with reference to the theoretical and practical rationales for their inclusion in the design of the IRISE_C. In this sense, all models fitted here have been specified a priori.
Congeneric models were specified for each set of items and polychoric correlations along with their respective asymptotic covariance matrix were input to LISREL 9.1 and estimated via diagonally weighted least squares (DWLS). All models were identified using the procedure outlined by Joreskog and Sorbom [
23]. The distributions of item data from the IRISE_C show the majority of the items to be ordinal and with markedly non-normal distributions.
The final choice of model fit indices took into account the following properties of the data: 1) a relatively simple one-factor congeneric model with uncorrelated error; 2) a small sample (N < 250); 3) item distributions that violate assumptions of normality by a high degree; and 4) a decision to use DWLS as the estimator. In line with Hu and Bentler [
24] the principal model fit index was the Standardized Root Mean Residual (SRMR). This index is most sensitive to model misspecification in simple models (as opposed to misspecification in complex models). The SRMR was used in conjunction with the Non-Normed Fit Index (NNFI) to prevent estimation bias in the SRMR associated with smaller sample sizes [
25]. Models were deemed to have a good fit where the SRMR < 0.05 and the NNFI > 0.95 and an acceptable fit where the SRMR < 0.10 and the NNFI > 0.90.
The final model for knowledge about Aboriginal culture was good (SRMR = 0.0434; NNFI = 1.000), and item loadings ranged from 0.51 to 0.81. The item loadings between each variable and the underlying latent factor can be interpreted as a correlation, for example for every standard deviation change in the underlying construct of ‘Knowledge of Aboriginal Culture’ we expect a 0.57 of a standard deviation change in item Q1, ‘How much do you know about how Aboriginal people lived in the old days?’ The square of the item loading represents the proportion of variance in the individual item that is explained by the underlying factor; in this case, Knowledge of Aboriginal Culture explains 32.5 % (0.57
2) of variance in Q1 (Table
4).
Table 4
Confirmatory factor analysis knowledge – Aboriginal culture
Q1. How much do you know about how Aboriginal people lived in the old days? | 0.57 |
N = 195b
|
df = 27c
|
Q3. How much do you know about Aboriginal Week activities? | 0.51 |
χ
2 = 27.15d
|
Q7. How much have you learned to make Aboriginal foods like damper? | 0.74 | SRMRe = 0.0434 |
NNFIf = 1.00 |
Q13. How much do you know about Aboriginal stories of the Dreaming (Dreamtime)? | 0.65 | Good |
Q17. How much do you talk Aboriginal words? | 0.67 |
Q19. How much does your family tell you about being Aboriginal? | 0.69 |
Q35. How much do you go bush with your family? | 0.67 |
Q37. How much have you eaten Aboriginal foods, like kangaroo? | 0.79 |
Q39. How much do you know about the dances Aboriginal people did in the old days? | 0.81 |
The final model for knowledge about racial identity was acceptable (SRMR = 0.0598; NNFI = 0.987), and item loadings ranged from 0.57 to 0.91 (Table
5).
Table 5
Confirmatory factor analysis knowledge – racial identity
Q5. How much do you like playing with Aboriginal kids? | 0.72 |
N = 200 |
df = 20 |
Q9. How much do you like being Aboriginal? | 0.80 |
χ
2 = 34.64 |
Q11. How much are you the same as other Aboriginal kids? | 0.57 | SRMR = 0.0598 |
NNFI = 0.987 |
Q15. How much do Aboriginal kids make you feel part of their group at school? | 0.68 | Acceptable |
Q23. How much do you like Aboriginal people as friends? | 0.71 |
Q28. How much are you proud of being Aboriginal? | 0.91 |
Q30. How much do Aboriginal kids help each other? | 0.66 |
Q33. How much do you like the Aboriginal flag? | 0.82 |
The final model for the salience of about Aboriginal culture was acceptable (SRMR = 0.0613; NNFI = 0.985), and item loadings ranged from 0.62 to 0.82 (Table
6).
Table 6
Confirmatory factor analysis salience – Aboriginal culture
Q2. How important is it for you to know about how Aboriginal people lived in the old days? | 0.62 |
N = 188 |
df = 27 |
Q4. How important is it that you to do activities for Aboriginal Week? | 0.64 |
χ
2 = 46.15 |
Q8. How important is it for you to make Aboriginal foods like damper? | 0.78 | SRMR = 0.0613 |
NNFI = 0.985 |
Q14. How important is it for you to know about Aboriginal stories of the Dreaming? | 0.78 | Acceptable |
Q18. How important is it for you to talk Aboriginal words? | 0.73 |
Q20. How important is it for you that your family tells you about being Aboriginal? | 0.70 |
Q36. How important is it for you to go bush with your family? | 0.66 |
Q38. How important is it for you to eat Aboriginal foods? | 0.68 |
Q40. How important is it for you to know about the dances Aboriginal people did in the old days? | 0.82 |
The final model for knowledge about Aboriginal culture was good (SRMR = 0.0434; NNFI = 1.00), and item loadings ranged from 0.51 to 0.81 (Table
7).
Table 7
Confirmatory factor analysis salience – racial identity
Q6. How important is it for you to play with Aboriginal kids? | 0.78 |
N = 191 |
df = 20 |
Q10. How important is it for you that you’re Aboriginal? | 0.71 |
χ
2 = 21.10 |
Q12. How important is it for you to be the same as other Aboriginal kids? | 0.72 | SRMR = 0.0557 |
NNFI = 0.999 |
Q16. How important is it for you to feel part of the Aboriginal group at school? | 0.78 | Acceptable |
Q24. How important is it for you to have Aboriginal people as friends? | 0.86 |
Q29. How important is it for you to be proud of being Aboriginal? | 0.78 |
Q31. How important is it that Aboriginal kids help each other? | 0.68 |
Q34. How important is it for you to like the Aboriginal flag? | 0.74 |
Scoring scales
While the Confirmatory Factor Analysis provides a method for assessing the relationship between assessing the relationship between items and the underlying constructs for our study sample, a simple and more practical way of scoring is to create unweighted scores within each of the 4 scales.
The scoring for these scales is as follows:
Ninety four percent (94.8 %) of children responded to 7 or more out of the 9 questions. The proposed usage is that for children with 7 or more responses add up all scores and then divide by number of valid responses (i.e. 9 to 36 divided by 8, or 8 to 32 divided by 8, or 7 to 28 divided by 7). This gives a score from 1–4, which can be interpreted on original scale (1 = none, 2 = − a little bit, 3 = some, and 4 = a lot).
Ninety five percent (95.6 %) of children responded to 6 or more out of the 8 questions. The proposed usage is that for children with 6 or more responses add up all scores and then divide by number of valid responses (i.e. 8 to 32 divided by 8, or 7 to 28 divided by 7, or 6 to 24 divided by 6).
Ninety three percent (93.0 %) of children responded to 7 or more out of the 9 questions. The proposed usage is that for children with 7 or more responses add up all scores and then divide by number of valid responses (i.e. 9 to 36 divided by 8, or 8 to 32 divided by 8, or 7 to 28 divided by 7).
Ninety two percent (92.1 %) of children responded to 6 or more out of the 8 questions. The proposed usage is that for children with 6 or more responses add up all scores and then divide by number of valid responses (i.e. 8 to 32 divided by 8, or 7 to 28 divided by 7, or 6 to 24 divided by 6).
The characteristics of the 4 scales are described in Table
8 below. Although the scales were developed based on a hypothesis of the relationship between racial self-esteem and overall wellbeing, this study has only assessed the internal consistency of these scales, not the relationship between these scales and external measures of wellbeing. Future research however, will be conducted to test the relationship between the IRISE scales and generic measures of wellbeing in due time. Thus, interpretation of cut-points in the current scales needs to made with caution. The median of the 4 scales at the 25th percentile is 3.00, thus a simple interpretation which could be made for a child scoring 3 or less on any of the scales is that that child sits in the lowest quartile for that scale.
N | Valid | 217 | 219 | 213 | 211 |
Missing | 12 | 10 | 16 | 18 |
Mean | 2.98 | 3.51 | 3.28 | 3.46 |
Median | 3.11 | 3.62 | 3.44 | 3.62 |
Mode | 3.44 | 4.00 | 4.00 | 4.00 |
Std. Deviation | .68 | .50 | .65 | .590 |
Variance | .47 | .25 | .42 | .349 |
Range | 2.89 | 2.50 | 2.89 | 2.88 |
Minimum | 1.11 | 1.50 | 1.11 | 1.13 |
Maximum | 4.00 | 4.00 | 4.00 | 4.00 |
Percentiles | 5 | 1.67 | 2.43 | 1.86 | 2.12 |
10 | 2.00 | 2.88 | 2.38 | 2.75 |
15 | 2.22 | 3.00 | 2.62 | 2.88 |
20 | 2.33 | 3.25 | 2.89 | 3.00 |
25 | 2.44 | 3.25 | 2.89 | 3.12 |
33 | 2.67 | 3.43 | 3.07 | 3.37 |
50 | 3.11 | 3.62 | 3.44 | 3.62 |
66 | 3.44 | 3.75 | 3.67 | 3.88 |
75 | 3.56 | 3.88 | 3.78 | 3.87 |
80 | 3.64 | 3.88 | 3.89 | 4.00 |
85 | 3.67 | 4.00 | 3.89 | 4.00 |
90 | 3.78 | 4.00 | 4.00 | 4.00 |
95 | 4.00 | 4.00 | 4.00 | 4.00 |
Similarly, the median of the 4 sub-scales at the 75th percentile is 3.82. Thus, any child scoring 3.82 or above any given scale could be interpreted as sitting in the top quartile for that scale.
Table
9 below shows that the correlations between the 4 final scales suggest an inter-relationship between the 4 scales.
Table 9
Correlations between the 4 scales
Knowledge of Aboriginal Culture | Pearson Correlation | 1 | .565a
| .709a
| .526a
|
Sig. (2-tailed) | | .000 | .000 | .000 |
N | 217 | 217 | 213 | 210 |
Knowledge of Racial Identity | Pearson Correlation | .565a
| 1 | .550a
| .784a
|
Sig. (2-tailed) | .000 | | .000 | .000 |
N | 217 | 219 | 213 | 211 |
Salience of Aboriginal Culture | Pearson Correlation | .709a
| .550a
| 1 | .633a
|
Sig. (2-tailed) | .000 | .000 | | .000 |
N | 213 | 213 | 213 | 210 |
Salience of Racial Identity | Pearson Correlation | .526a
| .784a
| .633a
| 1 |
Sig. (2-tailed) | .000 | .000 | .000 | |
N | 210 | 211 | 210 | 211 |
Discussion
The IRISE_C explored the identity and related self-esteem for 8–12 year-old Australian Aboriginal children. It was developed by the first author, an Aboriginal researcher. A series of consultations, negotiations and reviews from other Aboriginal community members, Aboriginal teachers, and professionals ensured that the concepts contained in the IRISE_C were culturally sound and acceptable. Furthermore, the recruitment of Aboriginal Community Research Assistants who reside in the local research sites have also contributed to acknowledging and following Aboriginal ways of working. In following such a protocol, a high level of Aboriginal ownership has been encouraged and in doing so, the development of the IRISE_C inventory and culturally safe and secure procedures have ensured authentic and valid results. Further, the concepts captured by the instrument have been deemed of value and acceptability by the Aboriginal carers who provided a high response rate of consent for their children to participate in the study.
Statistically, this study has demonstrated that the IRISE_C is a valid and reliable instrument that captures identity and self-esteem for Australian Aboriginal children 8–12 years of age. The confirmatory factor analysis has shown that the 4 subscales: 1. knowledge of identity, 2. salience of identity, 3. knowledge of culture and 4. salience of culture represent “good” and “acceptable” fitting models. This demonstrates that each sub-scale effectively captures a single, consistent underlying factor or concept. Further, the structure of domains identified through the factor analytic approach matches the domains identified through the consultative processes as reflecting the underlying constructs of Aboriginal racial identity. As the items for each sub-scale have been developed through a multi-stage, iterative consultative process with the local community, it is likely that the concepts being assessed by each scale have meaning to the families in the communities in which the scale has been tested.
This study does have some limitations. Results may not be generalised to Aboriginal children living in remote areas as these children were not included in the study. Furthermore, the current sample size for urban, regional and rural sites may not have been large enough to adequately describe the full diversity of identity and self-esteem of Aboriginal children. In Western Australia, there are approximately 69 665 [
26] Aboriginal people however, of these numbers there are more than 250 Aboriginal communities (not including Aboriginal residents in metropolitan areas) [
27]. Within these communities are distinct Aboriginal groups with a complex and rich system of language groups and skin groups- all of which raise claim to an Aboriginal identity. In comparison, only 8 Aboriginal groups were identified and most children identified as Noongar (from the south-west of Western Australia). It is anticipated that a difference in the concepts contained in the IRISE_C may be different for other Aboriginal groups not yet researched. Another challenge is the influence of dual or multi-identities children may have of their Aboriginal identity and this may include identity with more than one Aboriginal group but also with non-Aboriginal heritage.
Lastly, the IRISE_C provides a snap-shot of identity and self-esteem at one time point. It is a static measure of identity and self-esteem however according to the current literature, identity is dynamic and self-esteem is influenced by significant others.
Conclusion
We know very little about what protects or dismantles Aboriginal identity when other identities are present. We also are unaware of the rules, protocols, values and practices children engage in to identify in the first place. What interaction do children have with their carers/kin/parents in determining identity? Who else plays a significant role and how is identity transmitted? Furthermore, since identity is dynamic, then the feelings children experience daily need to be taken into account on the day of data collection. Future research therefore, needs to take into account the environment, setting (community), cultural protocols, significant others and the dynamic nature of identity and related self-esteem. Hence, a longitudinal study is warranted that explores the growth of identity and self-esteem over time and in particular settings and environments. In this way, we can truly understand what protects and harms the identity and related self-esteem of Australian Aboriginal children over time.
Importantly, the methods used in this study have ensured Aboriginal participants and their families were not just spectators or ‘a part’ of the research process. Aboriginal participants, their families, Aboriginal reviewers and Aboriginal community research assistants were the hub of the research wheel and who determined how fast and which direction to proceed. More specifically, they were integral from the inception to dissemination and translation of the research process. The outcome is an authentic and culturally responsive instrument that has scientific validation but importantly it has cultural validation and acceptance from the Aboriginal community. Aboriginal cultural knowledge combined with Aboriginal ownership using culturally secure methods will result in authentic and sustainable outcomes when Aboriginal research is in the hands of Aboriginal people…this is the direction that future research needs to journey.
Acknowledgments
This project is partly funded by the National Health and Medical Research Council’s Centre for Research Excellence in Aboriginal Health and Wellbeing (Application 1000886) and the City of Swan with in kind support from Pindi Pindi, The Centre for Research Excellence in Aboriginal Wellbeing. Kickett-Tucker is supported with a NHMRC Fellowship (Application 546713). David Lawrence, Daniel Christenson and Stephen Zubrick are supported by the Australian Research Council Centre of Excellence for Children and Families over the Life Course (CE140100027). The Aboriginal families and their children have inspired this project and without their unconditional support, this project would not have been possible. A team of wonderful Community Research Assistants have ensured we honoured the wishes and considerations of the Aboriginal community. A heartfelt thank you is extended to Priscilla Elward, Kerry Hunt, Cheryl Hayden, Sharon Loo, Jay Tucker, Amanda Christou, Matthew Hughes and Nikki Shaw. I also would like to acknowledge Sue Renshaw for her assistance and persistence in data entry. Thank you also to Gabriela Lawrence, Tara Reid and Samantha Wright, Amy Hoogenboom, Sven Silburn, the Pindi Pindi staff and Murdoch University interns. I acknowledge the generous support and time provided by Professor David Lawrence over the years.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
CKT conceived the study, developed the research design, coordinated the data collection, performed the qualitative analyses, assisted in the quantitative analyses and contributed to the drafting of the manuscript. DC carried out the quantitative analyses and contributed the drafting of the manuscript. DL assisted in the quantitative analysis and drafting of the manuscript. SZ assisted in the quantitative analysis. DJJ provided critical editing and a review of the manuscript. FS reviewed the manuscript. All authors read and approved the final manuscript.