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Strengths-based approaches for quantitative data analysis: A case study using the australian Longitudinal Study of
Katherine A Thurber1, Joanne Thandrayen1, Emily Banks1,2
1National Centre for Epidemiology and Population Health, Research School of Population Health, Australian National University, Acton, ACT, 2602, Australia.
Strengths-based quantitative analysis can identify protective factors for Indigenous child wellbeing, offering a positive perspective without sacrificing statistical rigor. This approach better aligns with community values and promotes positive change.
Area of Science:
- Public Health
- Quantitative Psychology
- Indigenous Studies
Background:
- Dominant deficit discourse in Indigenous health research overlooks strengths.
- A gap exists in practical applications of strengths-based quantitative methodologies.
- Strengths-based approaches are increasingly advocated internationally and in Australia.
Purpose of the Study:
- To describe and evaluate strategies for strengths-based quantitative analysis.
- To demonstrate practical application using a case study on Indigenous child wellbeing.
- To compare strengths-based approaches with traditional deficit models.
Main Methods:
- Utilized data from Wave 8 (2015) of the Australian Longitudinal Study of Indigenous Children.
- Employed the Protective Factors Approach and the Positive Outcome Approach.
- Compared exposure-outcome associations using Poisson regression with robust variance.
Main Results:
- Strengths-based approaches identified statistically significant exposure-outcome associations, similar to the deficit approach.
- Prevalence ratios and 95% confidence intervals were calculated for comparison.
- The study demonstrated that strengths-based methods can highlight positive associations.
Conclusions:
- Strengths-based quantitative analysis can present a more positive narrative while maintaining statistical validity.
- These approaches better reflect Indigenous community values and principles.
- Strengths-based methods hold greater potential for fostering positive change in Indigenous research compared to pathogenic models.
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