PIP Kit Research Paper Accepted for CHI 2020 Conference Proceedings

Personal Independence Payment (PIP) is a UK welfare benefit to help adult citizens with the additional costs of living with a mental or physical disability or other long-term health condition. Making a claim or undertaking a PIP review, requires completion of lengthy paper form with numerous complicated questions, reflecting similarly complex award rules. The process is stressful and claimants recognise the significance of form-completion, seeking help from professionals working in the benefits, care, health and social-work areas.

To address this, we developed PIP Kit, a toolkit of components which advisors can select and make up into a customised diary for use by a claimant to prepare for a subsequent assisted form-filling appointment.

The research study’s related academic paper “PIP Kit: An Exploratory Investigation into using Lifelogging to support Disability Benefit Claimants” has been accepted for publication in the proceedings of the ACM CHI Conference on Human Factors in Computing Systems 2020 (CHI 2020), one of the most well-recognised publications in the field. The conference is organised by the Association for Computing Machinery’s Special Interest Group on Computer Human Interaction (ACM SIGCHI). SIGCHI is the world’s largest association of professionals who work in the research and practice of computer-human interaction with CHI being its flagship conference event.

The paper was jointly written by Colin Watson (Open Lab, Newcastle University, UK), Reuben Kirkham (Monash University, Australia) and Ahmed Kharrufa (also Open Lab, Newcastle University).

Today’s confirmation follows original submission in September 2019, receipt of generous and helpful feedback from reviewers in December 2019 with an updated version created, and now accepted, in January 2020.

The paper will be published in due course at the Digital Object Identifier (DOI) https://doi.org/10.1145/3313831.3376215 but there is a pre-print version available from Newcastle University’s repository at https://eprint.ncl.ac.uk/263022.

The paper is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).