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Featured researches published by Thomas Nind.


human factors in computing systems | 2011

Motivating mobility: designing for lived motivation in stroke rehabilitation

Madeline Balaam; Stefan Rennick Egglestone; Geraldine Fitzpatrick; Tom Rodden; Ann-Marie Hughes; Anna Wilkinson; Thomas Nind; Lesley Axelrod; Eric Charles Harris; Ian W. Ricketts; Sue Mawson; Jane Burridge

How to motivate and support behaviour change through design is becoming of increasing interest to the CHI community. In this paper, we present our experiences of building systems that motivate people to engage in upper limb rehabilitation exercise after stroke. We report on participatory design work with four stroke survivors to develop a holistic understanding of their motivation and rehabilitation needs, and to construct and deploy engaging interactive systems that satisfy these. We reflect on the limits of motivational theories in trying to design for the lived experience of motivation and highlight lessons learnt around: helping people articulate what motivates them; balancing work, duty, fun; supporting motivation over time; and understanding the wider social context. From these we identify design guidelines that can inform a toolkit approach to support both scalability and personalisability.


international conference on pervasive computing | 2009

A design framework for a home-based stroke rehabilitation system: Identifying the key components

Stefan Rennick Egglestone; Lesley Axelrod; Thomas Nind; Ruth Turk; Anna Wilkinson; Jane Burridge; Geraldine Fitzpatrick; Sue Mawson; Zoe Robertson; Ann-Marie Hughes; Kher Hui Ng; Will Pearson; Nour Shublaq; Penny Probert-Smith; Ian W. Rickets; Tom Rodden

We present a design framework for a sensor-based stroke rehabilitation system for use at home developed through the analysis of data collected from a series of workshops. Participants had a variety of backgrounds and included people living with stroke and health professionals who work with them. Our focus in these workshops was to learn more about the social context around stroke care, to share early project ideas and develop a design framework for developing systems. In this paper we present a detailed analysis of participant responses and use this analysis to draw specific conclusions about the components and configuration that we believe should be in future systems.


human factors in computing systems | 2010

Rehabilitation centred design

Madeline Balaam; Stefan Rennick Egglestone; Ann-Marie Hughes; Thomas Nind; Anna Wilkinson; Eric Charles Harris; Lesley Axelrod; Geraldine Fitzpatrick

Stroke is a significant cause of disability, and is predicted to become a greater burden as population demographics shift. Research suggests that the completion of rehabilitation exercises can considerably improve function in damaged limbs, yet these exercises can be both boring and frustrating for patients to complete at home. New technologies create possibilities to support rehabilitation in motivating and entertaining ways, and, in this paper, we present a case study that illustrates the work of designing such technologies for a single user. Participation in this case study has highlighted some interesting tensions between designing for rehabilitation and designing for the user.


human factors in computing systems | 2014

Assisting older adults in assessing the reliability of health-related websites

Craig D. Stewart; Vicki L. Hanson; Thomas Nind

In this work, we address the question of how older adults may integrate information about the reliability of website information in their health-related searches. In two experiments, we compared three visual reliability indicator designs; an icon set, a simple graph and a textual list combined with website preview. Our results suggest that older adults can incorporate reliability indicators into their website judgments without significantly increasing decision time. The design of the visual indicators, however, significantly affects such ability.


GigaScience | 2018

The research data management platform (RDMP): A novel, process driven, open-source tool for the management of longitudinal cohorts of clinical data

Thomas Nind; James Galloway; Gordon McAllister; Donald Scobbie; Wilfred Bonney; Christopher Hall; Leandro Tramma; Parminder Reel; Martin Groves; Philip Appleby; Alex S. F. Doney; Bruce Guthrie; Emily R. Jefferson

Abstract Background The Health Informatics Centre at the University of Dundee provides a service to securely host clinical datasets and extract relevant data for anonymized cohorts to researchers to enable them to answer key research questions. As is common in research using routine healthcare data, the service was historically delivered using ad-hoc processes resulting in the slow provision of data whose provenance was often hidden to the researchers using it. This paper describes the development and evaluation of the Research Data Management Platform (RDMP): an open source tool to load, manage, clean, and curate longitudinal healthcare data for research and provide reproducible and updateable datasets for defined cohorts to researchers. Results Between 2013 and 2017, RDMP tool implementation tripled the productivity of data analysts producing data releases for researchers from 7.1 to 25.3 per month and reduced the error rate from 12.7% to 3.1%. The effort on data management reduced from a mean of 24.6 to 3.0 hours per data release. The waiting time for researchers to receive data after agreeing a specification reduced from approximately 6 months to less than 1 week. The software is scalable and currently manages 163 datasets. A total 1,321 data extracts for research have been produced, with the largest extract linking data from 70 different datasets. Conclusions The tools and processes that encompass the RDMP not only fulfil the research data management requirements of researchers but also support the seamless collaboration of data cleaning, data transformation, data summarization and data quality assessment activities by different research groups.


Age and Ageing | 2018

Identifying care-home residents in routine healthcare datasets: a diagnostic test accuracy study of five methods

Jennifer K. Burton; Charis Marwick; James Galloway; Christopher Hall; Thomas Nind; Emma Reynish; Bruce Guthrie

Abstract Background there is no established method to identify care-home residents in routine healthcare datasets. Methods matching patient’s addresses to known care-home addresses have been proposed in the UK, but few have been formally evaluated. Study design prospective diagnostic test accuracy study. Methods four independent samples of 5,000 addresses from Community Health Index (CHI) population registers were sampled for two NHS Scotland Health Boards on 1 April 2017, with one sample of adults aged ≥65 years and one of all residents. To derive the reference standard, all 20,000 addresses were manually adjudicated as ‘care-home address’ or not. The performance of five methods (NHS Scotland assigned CHI Institution Flag, exact address matching, postcode matching, Phonics and Markov) was evaluated compared to the reference standard. Results the CHI Institution Flag had a high PPV 97–99% in all four test sets, but poorer sensitivity 55–89%. Exact address matching failed in every case. Postcode matching had higher sensitivity than the CHI flag 78–90%, but worse PPV 77–85%. Area under the receiver operating curve values for Phonics and Markov scores were 0.86–0.95 and 0.93–0.98, respectively. Phonics score with cut-off ≥13 had PPV 92–97% with sensitivity 72–87%. Markov PPVs were 90–95% with sensitivity 69–90% with cut-off ≥29.6. Conclusions more complex address matching methods greatly improve identification compared to the existing NHS Scotland flag or postcode matching, although no method achieved both sensitivity and positive predictive value > 95%. Choice of method and cut-offs will be determined by the specific needs of researchers and practitioners.


Archive | 2010

Designing for rehabilitation at home

Geraldine Fitzpatrick; Madeline Balaam; Lesley Axelrod; Eric Charles Harris; Graham McAllister; Ann-Marie Hughes; Jane Burridge; Thomas Nind; Ian W. Ricketts; Anna Wilkinson; Sue Mawson; Stefan Rennick-Egglestone; Tom Rodden; Penny Probert Smith; Nour Shublaq; Zoe Robertson


ITCH | 2017

Mapping Local Codes to Read Codes.

Wilfred Bonney; James Galloway; Christopher Hall; Mikhail Ghattas; Leandro Tramma; Thomas Nind; Louise A. Donnelly; Emily R. Jefferson; Alex S. F. Doney


Archive | 2009

Motivating Mobility - An exploration of developing upper limb rehabilitation technology tailored to individual stroke patients needs

Ann-Marie Hughes; Jane Burridge; Madelaine Balaam; Eric Charles Harris; Stefan Rennick-Egglestone; Thomas Nind; Anna Wilkinson; Sue Mawson


Archive | 2010

Motivating Mobility: participatory design case studies towards technologies that motivate stroke rehabilitation

Madeline Balaam; Stefan Rennick-Egglestone; Tom Rodden; Geraldine Fitzpatrick; Eric Charles Harris; Thomas Nind; Ann-Marie Hughes; Anna Wilkinson; Sue Mawson; Lesley Axelrod; Ian W. Ricketts

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Sue Mawson

University of Sheffield

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Geraldine Fitzpatrick

Vienna University of Technology

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Jane Burridge

University of Southampton

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Tom Rodden

University of Nottingham

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Madeline Balaam

Royal Institute of Technology

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