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The Journal of Prevention of Alzheimer's Disease

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Open Access 01-10-2021 | Alzheimer's Disease | Original Research

A UK-Wide Study Employing Natural Language Processing to Determine What Matters to People about Brain Health to Improve Drug Development: The Electronic Person-Specific Outcome Measure (ePSOM) Programme

Authors: Stina Saunders, G. Muniz-Terrera, S. Sheehan, C. W. Ritchie, S. Luz

Published in: The Journal of Prevention of Alzheimer's Disease | Issue 4/2021

Abstract

Background

It is important to use outcome measures for novel interventions in Alzheimer’s disease (AD) that capture the research participants’ views of effectiveness. The electronic Person-Specific Outcome Measure (ePSOM) development programme is underpinned by the need to identify and detect change in early disease manifestations and the possibilities of incorporating artificial intelligence in outcome measures.

Objectives

The aim of the ePSOM programme is to better understand what outcomes matter to patients in the AD population with a focus on those at the pre-dementia stages of disease. Ultimately, we aim to develop an app with robust psychometric properties to be used as a patient reported outcome measure in AD clinical trials.

Design

We designed and ran a nationwide study (Aug 2019 - Nov 2019, UK), collecting primarily free text responses in five pre-defined domains. We collected self-reported clinical details and sociodemographic data to analyse responses by key variables whilst keeping the survey short (around 15 minutes). We used clustering and Natural Language Processing techniques to identify themes which matter most to individuals when developing new treatments for AD.

Results

The study was completed by 5,808 respondents, yielding over 80,000 free text answers. The analysis resulted in 184 themes of importance. An analysis focusing on key demographics to explore how priorities differed by age, gender and education revealed that there are significant differences in what groups consider important about their brain health.

Discussion

The ePSOM data has generated evidence on what matters to people when developing new treatments for AD that target secondary prevention and therein maintenance of brain health. These results will form the basis for an electronic outcome measure to be used in AD clinical research and clinical practice.

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Title: A UK-Wide Study Employing Natural Language Processing to Determine What Matters to People about Brain Health to Improve Drug Development: The Electronic Person-Specific Outcome Measure (ePSOM) Programme
Authors: Stina Saunders
G. Muniz-Terrera
S. Sheehan
C. W. Ritchie
S. Luz
Publication date: 01-10-2021
Publisher: Springer International Publishing
Keywords: Alzheimer's Disease
Alzheimer's Disease
Dementia
Dementia
Published in: The Journal of Prevention of Alzheimer's Disease / Issue 4/2021
Electronic ISSN: 2426-0266
DOI: https://doi.org/10.14283/jpad.2021.30

Keynote webinar | Spotlight on medication adherence

Springer Medicine

A UK-Wide Study Employing Natural Language Processing to Determine What Matters to People about Brain Health to Improve Drug Development: The Electronic Person-Specific Outcome Measure (ePSOM) Programme

Abstract

Background

Objectives

Design

Results

Discussion

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Objectives

Design

Results

Discussion

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