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|Longitudinal Study:||LSIC||Title:||Strengths-based approaches for quantitative data analysis: A case study using the Australian Longitudinal Study of Indigenous Children||Authors:||Thurber, Katherine A
|Issue Date:||12-Dec-2020||Pages:||12||Journal:||SSM - population health||Keywords:||Strengths-based analysis
|Abstract:||In Australia and internationally, there are increasing calls for the use of strengths-based methodologies, to counter the dominant deficit discourse that pervades research, policy, and media relating to Indigenous health and wellbeing. However, there is an absence of literature on the practical application of strengths-based approaches to quantitative research. This paper describes and empirically evaluates a set of strategies to support strengths-based quantitative analysis. A case study about Aboriginal and Torres Strait Islander child wellbeing was used to demonstrate approaches to support strengths-based quantitative analysis, in comparison to the dominant deficit approach of identifying risk factors associated with a negative outcome. Data from Wave 8 (2015) of the Australian Longitudinal Study of Indigenous Children were analysed. The Protective Factors Approach is intended to enable identification of factors protective against a negative outcome, and the Positive Outcome Approach is intended to enable identification of factors associated with a positive health outcome. We compared exposure-outcome associations (prevalence ratios and 95% confidence intervals (CIs), calculated using Poisson regression with robust variance) between the strengths-based and deficit approaches. In this case study, application of the strengths-based approaches retains the identification of statistically significant exposure-outcome associations seen with the standard deficit approach. Strengths-based approaches can enable a more positive story to be told, without altering statistical rigour. For Indigenous research, a strengths-based approach better reflects community values and principles, and it is more likely to support positive change than standard pathogenic models. Further research is required to explore the generalisability of these findings.||DOI:||10.1016/j.ssmph.2020.100637||URL:||https://pubmed.ncbi.nlm.nih.gov/32923575/||Research collection:||Journal Articles|
|Appears in Collections:||Journal Articles|
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