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How do people describe personal recovery experiences in bipolar disorder in structured and informal settings?

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How do people describe personal recovery experiences in bipolar disorder in structured and informal settings? / Jagfeld, Glorianna; Jones, Steven; Rayson, Paul; Lobban, Fiona.

2019. Poster session presented at Advances in Data Science 2019, Manchester, United Kingdom.

Research output: Contribution to conference - Without ISBN/ISSN Poster

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@conference{8abe753ce25e4a15aabe96609b4b6e42,
title = "How do people describe personal recovery experiences in bipolar disorder in structured and informal settings?",
abstract = "Bipolar disorder is a severe mental health condition characterised by changing episodes of intense depressed and elevated mood. While these symptoms are clinically regarded as chronic, modern mental health research posits that personal recovery is possible: living a satisfying and contributing life alongside symptoms of severe mental illnesses. To date, personal recovery in bipolar disorder has been investigated qualitatively with structured interviews and quantitatively with standardised questionnaires of mainly English-speaking westerners. This PhD project aims to broaden this scientific evidence base by incorporating evidence from unstructured settings and a sample of individuals from more diverse cultural and ethnic backgrounds.Therefore, we will collect and analyse textual social media data that relate to personal recovery in bipolar disorder from Twitter, the discussion forum Reddit, and blogs. Target users on Twitter and Reddit can be identified by matching self-reported diagnosis statements such as ‘I was diagnosed with bipolar disorder’. Corpus and computational linguistic methods allow us to efficiently analyse these large-scale data. We will start with exploratory quantitative research using comparative corpus analysis tools to uncover important linguistic features, e.g., keywords and key concepts that occur with unexpected frequency in our collected datasets relative to reference corpora. This will be complemented by computational linguistic methods such as topic modelling and sentiment and emotion analysis as well as qualitative, manual investigations of fewer examples. We will compare and relate our insights to those of previous qualitative research conducted with traditional interviews.Since mental health constitutes very sensitive information, ethical considerations are important, and the proposal is reviewed by the departmental research ethics committee. Informed consent will be sought whenever possible, which is infeasible on Twitter and Reddit, but applicable in the case of manually selected blogs. To protect the anonymity of the users, we will paraphrase all social media quotes in our publications because usernames could be retrieved via web searches otherwise. Throughout the project, we will consult a panel of individuals with lived experience of bipolar disorder to guide our research and discuss ethical considerations.The results of this project will allow us to draw a more complete picture of the facets of personal recovery in bipolar disorder and the factors that facilitate or hinder it. This has direct implications for the design of mental health services, which we believe should be informed by voices of individuals as diverse as those they are supposed to serve.",
keywords = "text analytics for mental health, social media health research, bipolar disorder, personal recovery",
author = "Glorianna Jagfeld and Steven Jones and Paul Rayson and Fiona Lobban",
year = "2019",
month = "5",
day = "20",
language = "English",
note = "Advances in Data Science 2019, ADS 19 ; Conference date: 20-05-2019 Through 21-05-2019",
url = "https://www.ds-advances.org/",

}

RIS

TY - CONF

T1 - How do people describe personal recovery experiences in bipolar disorder in structured and informal settings?

AU - Jagfeld, Glorianna

AU - Jones, Steven

AU - Rayson, Paul

AU - Lobban, Fiona

PY - 2019/5/20

Y1 - 2019/5/20

N2 - Bipolar disorder is a severe mental health condition characterised by changing episodes of intense depressed and elevated mood. While these symptoms are clinically regarded as chronic, modern mental health research posits that personal recovery is possible: living a satisfying and contributing life alongside symptoms of severe mental illnesses. To date, personal recovery in bipolar disorder has been investigated qualitatively with structured interviews and quantitatively with standardised questionnaires of mainly English-speaking westerners. This PhD project aims to broaden this scientific evidence base by incorporating evidence from unstructured settings and a sample of individuals from more diverse cultural and ethnic backgrounds.Therefore, we will collect and analyse textual social media data that relate to personal recovery in bipolar disorder from Twitter, the discussion forum Reddit, and blogs. Target users on Twitter and Reddit can be identified by matching self-reported diagnosis statements such as ‘I was diagnosed with bipolar disorder’. Corpus and computational linguistic methods allow us to efficiently analyse these large-scale data. We will start with exploratory quantitative research using comparative corpus analysis tools to uncover important linguistic features, e.g., keywords and key concepts that occur with unexpected frequency in our collected datasets relative to reference corpora. This will be complemented by computational linguistic methods such as topic modelling and sentiment and emotion analysis as well as qualitative, manual investigations of fewer examples. We will compare and relate our insights to those of previous qualitative research conducted with traditional interviews.Since mental health constitutes very sensitive information, ethical considerations are important, and the proposal is reviewed by the departmental research ethics committee. Informed consent will be sought whenever possible, which is infeasible on Twitter and Reddit, but applicable in the case of manually selected blogs. To protect the anonymity of the users, we will paraphrase all social media quotes in our publications because usernames could be retrieved via web searches otherwise. Throughout the project, we will consult a panel of individuals with lived experience of bipolar disorder to guide our research and discuss ethical considerations.The results of this project will allow us to draw a more complete picture of the facets of personal recovery in bipolar disorder and the factors that facilitate or hinder it. This has direct implications for the design of mental health services, which we believe should be informed by voices of individuals as diverse as those they are supposed to serve.

AB - Bipolar disorder is a severe mental health condition characterised by changing episodes of intense depressed and elevated mood. While these symptoms are clinically regarded as chronic, modern mental health research posits that personal recovery is possible: living a satisfying and contributing life alongside symptoms of severe mental illnesses. To date, personal recovery in bipolar disorder has been investigated qualitatively with structured interviews and quantitatively with standardised questionnaires of mainly English-speaking westerners. This PhD project aims to broaden this scientific evidence base by incorporating evidence from unstructured settings and a sample of individuals from more diverse cultural and ethnic backgrounds.Therefore, we will collect and analyse textual social media data that relate to personal recovery in bipolar disorder from Twitter, the discussion forum Reddit, and blogs. Target users on Twitter and Reddit can be identified by matching self-reported diagnosis statements such as ‘I was diagnosed with bipolar disorder’. Corpus and computational linguistic methods allow us to efficiently analyse these large-scale data. We will start with exploratory quantitative research using comparative corpus analysis tools to uncover important linguistic features, e.g., keywords and key concepts that occur with unexpected frequency in our collected datasets relative to reference corpora. This will be complemented by computational linguistic methods such as topic modelling and sentiment and emotion analysis as well as qualitative, manual investigations of fewer examples. We will compare and relate our insights to those of previous qualitative research conducted with traditional interviews.Since mental health constitutes very sensitive information, ethical considerations are important, and the proposal is reviewed by the departmental research ethics committee. Informed consent will be sought whenever possible, which is infeasible on Twitter and Reddit, but applicable in the case of manually selected blogs. To protect the anonymity of the users, we will paraphrase all social media quotes in our publications because usernames could be retrieved via web searches otherwise. Throughout the project, we will consult a panel of individuals with lived experience of bipolar disorder to guide our research and discuss ethical considerations.The results of this project will allow us to draw a more complete picture of the facets of personal recovery in bipolar disorder and the factors that facilitate or hinder it. This has direct implications for the design of mental health services, which we believe should be informed by voices of individuals as diverse as those they are supposed to serve.

KW - text analytics for mental health

KW - social media health research

KW - bipolar disorder

KW - personal recovery

M3 - Poster

ER -