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Erschienen in: Quality of Life Research 6/2019

23.02.2019

Leveraging Latent Dirichlet Allocation in processing free-text personal goals among patients undergoing bladder cancer surgery

verfasst von: Yuelin Li, Bruce Rapkin, Thomas M. Atkinson, Elizabeth Schofield, Bernard H. Bochner

Erschienen in: Quality of Life Research | Ausgabe 6/2019

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Abstract

Purpose

As we begin to leverage Big Data in health care settings and particularly in assessing patient-reported outcomes, there is a need for novel analytics to address unique challenges. One such challenge is in coding transcribed interview data, typically free-text entries of statements made during a face-to-face interview. Latent Dirichlet Allocation (LDA) offers statistical rigor and consistency in automating the interpretation of patients’ expressed concerns and coping strategies.

Methods

LDA was applied to interview data collected as part of a prospective, longitudinal study of QOL in N = 211 patients undergoing radical cystectomy and urinary diversion for bladder cancer. LDA analyzed personal goal statements to extract the latent topics and themes, stratified by time, and on things patients wanted to accomplish and prevent. Model comparison metrics determined the number of topics to extract.

Results

LDA extracted seven latent topics. Prior to surgery, patients’ priorities were primarily in cancer surgery and recovery. Six months after the surgery, they were replaced by goals on regaining a sense of normalcy, to resume work, to enjoy life more fully, and to appreciate friends and family more. LDA model parameters showed changing priorities, e.g., immediate concerns on surgery and resuming employment decreased post-surgery and were replaced by concerns over cancer recurrence and a desire to remain healthy and strong.

Conclusions

Novel Big Data analytics such as LDA offer the possibility of summarizing personal goals without the need for conventional fixed-length measures and resource-intensive qualitative data coding.
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Metadaten
Titel
Leveraging Latent Dirichlet Allocation in processing free-text personal goals among patients undergoing bladder cancer surgery
verfasst von
Yuelin Li
Bruce Rapkin
Thomas M. Atkinson
Elizabeth Schofield
Bernard H. Bochner
Publikationsdatum
23.02.2019
Verlag
Springer International Publishing
Erschienen in
Quality of Life Research / Ausgabe 6/2019
Print ISSN: 0962-9343
Elektronische ISSN: 1573-2649
DOI
https://doi.org/10.1007/s11136-019-02132-w

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