Abstract
Background: Speech and language therapy (SLT) benefits people with aphasia following stroke. Group level summary statistics from randomised controlled trials hinder exploration of highly complex SLT interventions and a clinically relevant heterogeneous population. Creating a database of individual participant data (IPD) for people with aphasia aims to allow exploration of individual and therapy-related predictors of recovery and prognosis.
Aim: To explore the contribution that individual participant characteristics (including stroke and aphasia profiles) and SLT intervention components make to language recovery following stroke.
Methods and procedures: We will identify eligible IPD datasets (including randomised controlled trials, non-randomised comparison studies, observational studies and registries) and invite their contribution to the database. Where possible, we will use meta- and network meta-analysis to explore language performance after stroke and predictors of recovery as it relates to participants who had no SLT, historical SLT or SLT in the primary research study. We will also examine the components of effective SLT interventions.
Outcomes and results: Outcomes include changes in measures of functional communication, overall severity of language impairment, auditory comprehension, spoken language (including naming), reading and writing from baseline. Data captured on assessment tools will be collated and transformed to a standardised measure for each of the outcome domains.
Conclusion: Our planned systematic-review-based IPD meta- and network meta-analysis is a large scale, international, multidisciplinary and methodologically complex endeavour. It will enable hypotheses to be generated and tested to optimise and inform development of interventions for people with aphasia after stroke.
Aim: To explore the contribution that individual participant characteristics (including stroke and aphasia profiles) and SLT intervention components make to language recovery following stroke.
Methods and procedures: We will identify eligible IPD datasets (including randomised controlled trials, non-randomised comparison studies, observational studies and registries) and invite their contribution to the database. Where possible, we will use meta- and network meta-analysis to explore language performance after stroke and predictors of recovery as it relates to participants who had no SLT, historical SLT or SLT in the primary research study. We will also examine the components of effective SLT interventions.
Outcomes and results: Outcomes include changes in measures of functional communication, overall severity of language impairment, auditory comprehension, spoken language (including naming), reading and writing from baseline. Data captured on assessment tools will be collated and transformed to a standardised measure for each of the outcome domains.
Conclusion: Our planned systematic-review-based IPD meta- and network meta-analysis is a large scale, international, multidisciplinary and methodologically complex endeavour. It will enable hypotheses to be generated and tested to optimise and inform development of interventions for people with aphasia after stroke.
| Original language | English |
|---|---|
| Pages (from-to) | 137-157 |
| Number of pages | 21 |
| Journal | Aphasiology |
| Volume | 34 |
| Issue number | 2 |
| Early online date | 25 Aug 2019 |
| DOIs | |
| Publication status | Published - Feb 2020 |
Keywords
- stroke
- aphasia
- complex intervention
- IPD
- meta-analysis
ASJC Scopus subject areas
- Clinical Neurology
- Neurology
- Developmental and Educational Psychology
- Language and Linguistics
- LPN and LVN
- Otorhinolaryngology
- Linguistics and Language
Access to Document
- Brady, M.C. et al (2019) RELEASE: a protocol for a systematic review based, individual participant data, meta- and network meta-analysis, of complex speech-language therapy interventions for stroke-related aphasia
© 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.