Langford, Thomas Richard Daniel;
(2025)
iReadMore: optimisation and personalisation of
a therapy app for acquired reading impairments.
Doctoral thesis (Ph.D), UCL (University College London).
Preview |
Text
Thesis - Thomas Richard Daniel Langford 2025.pdf - Accepted Version Download (3MB) | Preview |
Abstract
This thesis explores the development, evaluation and optimisation of a digital reading therapy for individuals with an acquired reading impairment. The app aims to improve single-word reading speed and accuracy. This research builds on prior research into the clinical efficacy of the iReadMore therapy mechanism, previously delivered via a laptop-based prototype. In Chapter 1 of the thesis, I present a qualitative study of the development of the iReadMore App, addressing the need for improved accessibility and user engagement to enable independent, home-based therapy. A co-design process involving individuals with alexia, with or without aphasia, informed the creation of the app's release version. Design recommendations for digital therapies for persons with alexia were derived from the co-design process and analysed using a framework analysis. In Chapter 2, I report preliminary findings from the ongoing clinical effectiveness trial investigating the therapeutic effects on reading accuracy and reaction time in real-world app users. This chapter highlights early indications of therapy effects. Additionally, I explore the unique challenges associated with conducting research in real-world contexts. In Chapter 3, I present two studies investigating the potential of machine learning to predict treatment outcomes for users of the iReadMore app and another digital therapy for improving speech comprehension, the Listen-In app. In these studies, I focused on training models using data that can feasibly be collected within an app, the studies provide insights into the viability of using routine, easily collected in-therapy data to support treatment outcome prediction. In the general discussion, I connect the qualitative findings, preliminary trial results, and treatment prediction insights, contextualising the findings, and exploring potential directions for future research.
| Type: | Thesis (Doctoral) |
|---|---|
| Qualification: | Ph.D |
| Title: | iReadMore: optimisation and personalisation of a therapy app for acquired reading impairments |
| Open access status: | An open access version is available from UCL Discovery |
| Language: | English |
| Additional information: | Copyright © The Author 2025. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request. |
| Keywords: | Stroke, Aphasia, Alexia, Digital therapy, Co-design, Brain injury, Neurorehabilitation |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10211555 |
Archive Staff Only
 |
View Item |
