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How to interpret large volumes of patient feedback: methods from computer-assisted linguistics

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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How to interpret large volumes of patient feedback: methods from computer-assisted linguistics. / Brookes, Gavin; McEnery, Anthony Mark.
In: Social Research Practice, Vol. 4, No. 1, 06.2017, p. 2-13.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Brookes, G & McEnery, AM 2017, 'How to interpret large volumes of patient feedback: methods from computer-assisted linguistics', Social Research Practice, vol. 4, no. 1, pp. 2-13. <http://the-sra.org.uk/wp-content/uploads/SRA_Social_Research_Practice_Journal_Issue_04-summer-2017.pdf>

APA

Brookes, G., & McEnery, A. M. (2017). How to interpret large volumes of patient feedback: methods from computer-assisted linguistics. Social Research Practice, 4(1), 2-13. http://the-sra.org.uk/wp-content/uploads/SRA_Social_Research_Practice_Journal_Issue_04-summer-2017.pdf

Vancouver

Brookes G, McEnery AM. How to interpret large volumes of patient feedback: methods from computer-assisted linguistics. Social Research Practice. 2017 Jun;4(1):2-13.

Author

Brookes, Gavin ; McEnery, Anthony Mark. / How to interpret large volumes of patient feedback : methods from computer-assisted linguistics. In: Social Research Practice. 2017 ; Vol. 4, No. 1. pp. 2-13.

Bibtex

@article{8ef29a4e99ac4975bb36c5546c2f18ad,
title = "How to interpret large volumes of patient feedback: methods from computer-assisted linguistics",
abstract = "In this article, we demonstrate how methods from corpus linguistics can be used to interpret largecollections of patient feedback. Using a series of established corpus linguistic techniques, this studyexamines the key areas of concern in 29 million words of online patient feedback about the NationalHealth Service (NHS) in England. Focusing on the theme of staff rudeness, our analysis shows how thepower of computer-assisted textual analysis can be fruitfully synthesised with fine grained, humanledanalyses to develop a more refined picture of the complex ways that patients evaluate healthcareservices in their comments. We argue that, by affording the opportunity to study large collections ofauthentic language data, corpus linguistics methods can facilitate the types of objective and empiricalapproaches to large datasets that are now commonplace in the domain of evidence-based healthcommunication research.",
author = "Gavin Brookes and McEnery, {Anthony Mark}",
year = "2017",
month = jun,
language = "English",
volume = "4",
pages = "2--13",
journal = "Social Research Practice",
number = "1",

}

RIS

TY - JOUR

T1 - How to interpret large volumes of patient feedback

T2 - methods from computer-assisted linguistics

AU - Brookes, Gavin

AU - McEnery, Anthony Mark

PY - 2017/6

Y1 - 2017/6

N2 - In this article, we demonstrate how methods from corpus linguistics can be used to interpret largecollections of patient feedback. Using a series of established corpus linguistic techniques, this studyexamines the key areas of concern in 29 million words of online patient feedback about the NationalHealth Service (NHS) in England. Focusing on the theme of staff rudeness, our analysis shows how thepower of computer-assisted textual analysis can be fruitfully synthesised with fine grained, humanledanalyses to develop a more refined picture of the complex ways that patients evaluate healthcareservices in their comments. We argue that, by affording the opportunity to study large collections ofauthentic language data, corpus linguistics methods can facilitate the types of objective and empiricalapproaches to large datasets that are now commonplace in the domain of evidence-based healthcommunication research.

AB - In this article, we demonstrate how methods from corpus linguistics can be used to interpret largecollections of patient feedback. Using a series of established corpus linguistic techniques, this studyexamines the key areas of concern in 29 million words of online patient feedback about the NationalHealth Service (NHS) in England. Focusing on the theme of staff rudeness, our analysis shows how thepower of computer-assisted textual analysis can be fruitfully synthesised with fine grained, humanledanalyses to develop a more refined picture of the complex ways that patients evaluate healthcareservices in their comments. We argue that, by affording the opportunity to study large collections ofauthentic language data, corpus linguistics methods can facilitate the types of objective and empiricalapproaches to large datasets that are now commonplace in the domain of evidence-based healthcommunication research.

M3 - Journal article

VL - 4

SP - 2

EP - 13

JO - Social Research Practice

JF - Social Research Practice

IS - 1

ER -