Evidence map›Paper›PMID 38771557›Full record

ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2024

Extracting big data from the internet to support the development of a new patient-reported outcome measure for breast implant illness: a proof of concept study.

Sophia Hu, Jinjie Liu, Sylvie D Cornacchi, Anne F Klassen, Andrea L Pusic, Manraj N Kaur

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Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Sophia HuDepartment of Surgery, Patient-Reported Outcomes, Value and Experience (PROVE) Center, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA, 02115, USA.
Jinjie LiuInstitute for Quantitative Social Science, Harvard University, 1737 Cambridge Street, Cambridge, MA, 02138, USA.
Sylvie D CornacchiFaculty of Health Sciences, McMaster University, 1280 Main Street W, Hamilton, ON, L8S 1C7, Canada.
Anne F KlassenFaculty of Health Sciences, McMaster University, 1280 Main Street W, Hamilton, ON, L8S 1C7, Canada.
Andrea L PusicDepartment of Surgery, Patient-Reported Outcomes, Value and Experience (PROVE) Center, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA, 02115, USA.
Manraj N KaurDepartment of Surgery, Patient-Reported Outcomes, Value and Experience (PROVE) Center, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA, 02115, USA. mkaur17@bwh.harvard.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeIndividuals with health conditions often use online patient forums to share their experiences. These patient data are freely available and have rarely been used in patient-reported outcomes (PRO) research. Web scraping, the automated identification and coding of webpage data, can be employed to collect patient experiences for PRO research. The objective of this study was to assess the feasibility of using web scraping to support the development of a new PRO measure for breast implant illness (BII).

methodsNine publicly available BII-specific web forums were chosen post-consultation with two prominent BII advocacy leaders. The Python Selenium and Pandas packages were used to automate extraction of de-identified text from the individual posts/comments into a spreadsheet. Data were coded using a line-by-line approach and constant comparison was used to create top-level domains and sub-domains.

results6362 unique codes were identified and organized into four top-level domains of information needs, symptom experiences, life impact of BII, and care experiences. Information needs of women included seeking/sharing information pre-breast implant surgery, post-breast implant surgery, while contemplating explant surgery, and post-explant surgery. Symptoms commonly described by women included fatigue, brain fog, and musculoskeletal symptoms. Many comments described BII's impact on daily activities and psychosocial wellbeing. Lastly, some comments described negative care experiences and experiences related to advocating for themselves to providers.

conclusionThis proof-of-concept study demonstrated the feasibility of employing web scraping as a cost-effective, efficient method to understand the experiences of women with BII. These data will be used to inform the development of a BII-specific PROM.

Indexed as

Breast ImplantsInternetPatient Reported Outcome MeasuresBig DataFeasibility StudiesFemaleHumansProof of Concept StudyQuality of LifeBreast implant illnessPatient-reported outcomesQualitativeWeb scraping

Identifiers

PMID38771557

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.