在未来规划和住房研究中使用包容性研究方法和住房途径框架:试点研究

I. Belperio, F. Rillotta, Tim Adam, Ruth Walker, C. Hutchinson
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引用次数: 0

摘要

几十年来,住房和未来规划一直是智力和发育障碍研究的主要关注领域。然而,在这一研究领域,智障成人的声音并没有得到充分反映。此外,包容性研究方法在文献中的使用仍然有限。本研究试图试点使用包容性研究方法,以调查这些方法的可行性,并开始在这一工作领域建立包容性研究的证据基础。本研究采用了包容性数据分析和共同著作的方法,对一项大型研究中的小型定性数据集进行了分析,该研究调查了澳大利亚智障成人及其家庭的未来规划和离开家庭的过渡情况。我们按照解释性现象学分析的原则,采用包容性数据分析方法,对智障成人及其家庭成员就其住房偏好和规划进行的三次半结构式访谈进行了分析。然后,使用通俗易懂的住房路径框架对这些数据进行了进一步分析。试点研究的结果将用于指导项目数据集其余部分的包容性研究方法。总体而言,使用包容性方法试行概念模型以更好地理解定性数据是可行的。建议对研究过程和可及性稍作调整,以更好地支持参与研究过程。最后,建议对共同作者的方法和选择进行更深入的调查,作为未来研究的一个富有成效的调查途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using Inclusive Research Methods and the Housing Pathways Framework in Future Planning and Housing Research: A Pilot Study
Housing and future planning have been key areas of interest in intellectual and development disabilities research for a number of decades. However, the voices of adults with intellectual disabilities are underrepresented in this area of research. Furthermore, the use of inclusive research methods remains limited in the literature. This study sought to pilot the use of inclusive research approaches to investigate the viability of these methods and to begin to build an evidence base of inclusive research in this area of work. Inclusive data analysis and co-authorship approaches were used on a small qualitative dataset from a larger study investigating future planning and transitions out of the family home by adults with intellectual disabilities and their families in Australia. Three semi-structured interviews with adults with intellectual disabilities and family members regarding their housing preferences and planning were analysed using an inclusive data analysis approach following the principles of Interpretative Phenomenological Analysis. These were then further analysed using a plain language version of the housing pathways framework. The results of the pilot study will be used to inform the inclusive research methods used for the remainder of the project dataset. Overall, the use of inclusive methods to pilot a conceptual model to better understand qualitative data was found to be feasible. Small adjustments to the process and accessibility to better support engagement with the research process are recommended. Lastly, greater investigation into co-authorship approaches and options is suggested as a fruitful avenue of inquiry for future research.
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