Suchergebnisse

AbstractThe Disability Support Pension (DSP) provides financial support to more than 750,000 Australians with permanent physical, intellectual or psychiatric impairments that prevent them from engaging in employment. We sought to characterise the information, compliance and psychological costs of applying for the DSP. A cohort of 518 DSP applicants and recipients completed a questionnaire capturing medical, disability, benefit and demographic data. The questionnaire also included an Administrative Burden (AB) scale that was co‐developed with disability advocates and people with lived experience of DSP processes. Most respondents reported high or very high scores on three sub‐scales assessing information, compliance and psychological costs. In logistic regression models, DSP applicants reported greater costs than DSP recipients across all three scales. People with poorer health‐related quality of life, younger age and less education reported higher costs, consistent with the observation of an inequitable distribution of administrative burden in AB theory. All three scales had acceptable reliability. Study findings suggest that DSP applicants find the application process challenging and stressful. These effects are more pronounced in people who have applied for the DSP than those currently receiving the DSP, and in those with lower human capital.

This work was undertaken in collaboration with the Melbourne Data Analytics Platform (specifically Mr Geordie Zhang and Dr Daniel Russo-Batterham) and has been supported by funding from the Australian Research Council (FT170100011), an Australian Government Research Training Program Scholarship, and Monash University. This work formed part of the first author's PhD thesis at Monash University. Open access publishing facilitated by Monash University, as part of the Wiley - Monash University agreement via the Council of Australian University Librarians. Research into termination notice records has been approved by the Monash University Human Research Ethics Committee (Project ID: 23026). The authors acknowledge the assistance of the following individuals with this article: Professor Robert Brauneis (The George Washington University Law School) and Professor Dotan Oliar (University of Virginia School of Law) for providing their data from a previous paper and feedback, Associate Professor Sue Finch from the University of Melbourne's Statistical Consulting Centre for her input on an earlier draft of the method and results, Brianna Schofield (Authors Alliance) and Regan Smith (then-General Counsel and Associate Register of Copyrights, U.S. Copyright Office) for their input on copyright registrations and the Copyright Office Catalog, respectively, and John Jacob and Brad Williams for assisting with early coding of some data. We also acknowledge Professor R. Anthony Reese's (as yet unpublished) analysis of full termination notices obtained from the Copyright Office in Washington, DC, and anticipate that our research will complement that analysis when it is published. Furthermore, we thank the anonymous peer reviewers for their helpful comments.