Is headspace making a difference to young people’s lives?

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Appendix B Figure B14 Percentage of the youth population with access, by round (Rounds 1 – 14) Figure B15 Additional increase in the percentage of youth covered by round (Rounds 1 – 14) The distribution of need for mental health services Rationale The prevalence of mental health disorders in young people is not evenly distributed across demographic groups and is strongly associated with social disadvantage. As a result, it is likely that there are regions across Australia with greater numbers of young people who require services for mental health problems. Identifying areas of high need characterised by disadvantage and large youth populations or with an above average prevalence of youth mental health disorders may be useful in determining current access to, as well as allocation of, future centres. The current model of centre allocation gives greater weight to those areas with low SEIFA scores, reflecting higher levels of socioeconomic disadvantage, and to rural and remote areas. This model assumes that disadvantage and remoteness are associated with a higher youth mental health burden Social Policy Research Centre 2015 headspace Evaluation Final Report 140
Appendix B and less access to mainstream services, and consequently, a greater need for headspace services. However, additional factors may be associated with the prevalence of mental health disorder in young people, and identification of such factors, which can be incorporated into the model of future centre allocation, could result in more effective and efficient resource allocation. It is important to note that this modelling is constrained by data availability. Rather than providing an optimal weighting strategy for centre allocation, this analysis aims to provide an alternative methodology for consideration by the Department. Small area estimates of prevalence of mental health disorders Method YMM wave one data were used to determine socio-demographic factors associated with the prevalence of mental health disorders in young people. A Poisson regression model was fitted to the YMM data at the SA1 level to predict the prevalence of mental health disorder by socio-demographic variables which were individually associated with prevalence of disorder. Variables included in the model were limited to those which are available for all small areas across Australia and that were collected in YMM and could be matched to census data. This model was applied to census data at the small area level (SA1) to allow for estimation of the prevalence of mental health disorders in young people across the whole of Australia. In order to asses current and likely access for young people with a mental health disorder, the number of young people within 10 and 30 km of headspace centres for existing Rounds 1-8 and hypothetical Rounds 9-14, using the current model of allocation, was calculated using the method described above. It is important to note that implicit in this model, and any extrapolation based on it, is the assumption that the demographic characteristics of 4-17 year olds are similar to those of 18-25 year olds. Results Socio-demographic factors which were identified as being individually associated with the prevalence of mental health disorders in young people were: • SEIFA • income • family type • Indigenous status • housing tenure • language spoken at home • born overseas. This approach represents a potential methodological improvement over an approach which allocates resources on the basis of SEIFA and remoteness. Although SEIFA and remoteness are intended as proxies for disadvantage and potential service need, the weights applied are not clearly justified. In contrast, the small area estimation process empirically derives the association between risk factors and mental health disorders. The small area estimation process includes a mix of household and individual level factors (such as income, family type) and SEIFA, which is an area-level estimate. There are substantial differences in the prevalence of mental health disorders in young people across geographic areas in Australia, at geographic levels germane to service delivery. For example, Figure B16 indicates substantial differences in the prevalence of mental health disorders in the Sydney metropolitan area at the SA1 level. Figure B16 displays the prevalence and number of young people in Inner Sydney who are estimated to be at risk of a mental health disorder. This figure displays the catchments of five headspace centres. These centres include headspace Camperdown, headspace Ashfield, headspace Chatswood, headspace Brookvale and headspace Bondi Junction. These figures aim to demonstrate the differences between the two indicators of demand for any defined service catchment area, those indicators being the prevalence of risk of mental health disorder and number of young people residing in the area. For example, many small areas (SA1s) within the central Sydney area have a low prevalence of disorder, relative to other areas in Australia. However, Social Policy Research Centre 2015 headspace Evaluation Final Report 141
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Is headspace making a difference to
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Authors This report was written by
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5. Service Delivery Model 73 5.1 Wh
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Table 6.1 Table 6.2 Table 6.3 Main
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Figure 4.9 Figure 4.10 Figure 4.11
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Executive Summary headspace 1 aims
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Executive Summary or very high leve
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Executive Summary through mental he
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value to society of the improvement
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1. Introduction people in Australia
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2. Evaluation Methodology 2.1 Aims
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2. Evaluation Methodology Evaluatio
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2. Evaluation Methodology Table 2.3
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y three percentage points, and 2.1
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Page 145 and 146: Figure B10 Proportion of headspace
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Page 157 and 158: Figure B20 Hypothetical allocation
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Page 187 and 188: Appendix C Data Cleaning and Analys
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Page 193 and 194: Appendix C The KeySurvey software s
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Page 197 and 198: Appendix D Round State Centre Name
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Table E4 Cell Sizes for Figure 3.4
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Appendix F Figure F1 Changes in K10
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Appendix F three SEIFA quintiles. A
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Appendix F Occasion of service inte
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Appendix F Table F1 Cell sizes for
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Appendix G Supplementary material f
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Appendix G Table G3 Round 3 (10 cen
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Appendix G Table G7 Round 7 (10 cen
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State (youth population) a headspac
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Appendix G Table G12 Round 11(16 ce
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Table G16 Additional youth populati
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Round Region State Additional youth
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Appendix G Figure G1 Percentage of
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Appendix G Table G22 Australians 18
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Appendix G Synthetic small area est
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Appendix G Figure G16 Estimated pre
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Appendix G Figure G22 SA1s within 1
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Appendix G Table G25 Centres alloca
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References Atkins, D.C., Bedics, J.
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References Smith, E., Jones, T., Wa
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