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Assessing Population Need for Mental Health Care: A Review of Approaches and Predictors

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Mental Health Services Research

Abstract

This review aimed to clarify the concept of need, explore the different approaches used to assess need, and contribute to an improved understanding of predictor and intervening factors in assessing need for mental health services. Two population-based needs assessment approaches have been identified: modeling need for services and surveys of the general population. The most widely used model was that based on the Jarman-8 index of social deprivation. The population-based epidemiological surveys addressed perceived need by seeking direct, self-reported measures of individuals' perceptions of their needs for care. Although many studies have reported correlates of service use, few have attempted to identify correlates of perceived need. The fact that two-thirds to three-quarters of people were identified as meeting criteria for a mental health disorder, but did not report receiving treatment, highlighted a gap between epidemiology and service use. This gap could be explained by a number of intervening factors such as the discordance between diagnosis and disability, the determinants of and barriers to help-seeking behavior, the belief systems concerning appropriate treatments, and choice of health professionals. This review has thus identified the predictor variables which are important for a comprehensive analysis of need for mental health care. Suggestions and challenges have been put forward to address the identified gaps in assessing population need.

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Authors and Affiliations

  1. Centre for Mental Health Services Research, West Perth, Western Australia, Australia

    Samar Aoun, Duane Pennebaker & Christie Wood

  2. School of Nursing and Public Health, Edith Cowan University, Western Australia, Australia

    Samar Aoun

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  1. Samar Aoun
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  2. Duane Pennebaker
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  3. Christie Wood
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Aoun, S., Pennebaker, D. & Wood, C. Assessing Population Need for Mental Health Care: A Review of Approaches and Predictors. Ment Health Serv Res 6, 33–46 (2004). https://doi.org/10.1023/B:MHSR.0000011255.10887.59

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