In LingshuHu/healthforum: Scrape Patient Forum Data

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(healthforum)

On patient.info forum, there are different levels of posts.

• Main post: one individual user can initialize a post discussing his or her problems.
• Reply: other users can reply to this post providing suggestions or information.
• Nested reply: other users can also reply to the replies.
• Group: every main post belongs to a group that focuses on a specific disease or issue. For example, there are groups such as alcohol consumption, abdominal disorders, depression, and menopause.
• Category: every group belongs to a category that includes similar diseases or issues. For example, abdominal disorders belong to the category of gut, bowel and stomach, and depression belongs to the category of mental health.

This is a basic example which shows you how to scrape the discussion thread of this main post from patient.info.

## scrape pages 1-2 from thread about gastritis
gas <- scrape_one_post(
  url = "https://patient.info/forums/discuss/can-gastritis-be-cured--613999",
  From = 1, To = 2,
  get_user_info = FALSE)

## preview the returned data frame
tibble::as_tibble(gas)

This is a basic example which shows you how to scrape the discussion thread of posts from this group.

## scrape the thread of a random main posts from the group "Angiotensin II Receptor Blockers"
gas <- scrape_one_group(
  group_url = "https://patient.info/forums/discuss/browse/angiotensin-ii-receptor-blockers-3037", 
  random_post_number = 1)

## preview the returned data frame
tibble::as_tibble(gas)

You can get posts from multiple groups whose name has the same initial letter.

## scrape the thread of one random post from all groups whose names starting with the letter "x".
gas <- scrape_groups_by_initial_letter(index = "x", 
                                       post_number_per_group = 1,
                                       get_user_info = FALSE)

## preview the returned data frame
tibble::as_tibble(gas)

This is an example which shows you how to scrape the discussion thread of posts from the categroy "Health Promotion".

## scrape the thread of one random post from every group that belongs to the categroy "Health Promotion"
gas <- scrape_groups_by_category(cat = "health-promotion", 
                                 post_number_per_group = 1, 
                                 get_user_info = FALSE)

## preview the returned data frame
tibble::as_tibble(gas)

You can also scrape the posts made by a specific user.

This is an example which shows you how to scrape the posts sent by this user.

``` {r eval = FALSE}

scrape the posts sent by the user utgh4k33

userposts <- scrape_user_posts( user_profile_url <- "https://patient.info/forums/profiles/utgh4k33-1264038", type = "both")

preview the returned data frame

tibble::as_tibble(userposts)

`healthforum` contains a medical glossary dictionary which can be used to count the number of medical words used in posts. 

This is an example which shows you how to count medical words.

``` {r}
## create a text vector
medical_text <- c(
"No, it isn't possible to predict anything before the result of your biopsy is received.", 
"Thank you for the nice reply! Very thoughtful answer that did ease my fears!", 
"Can't help regards the meds.  Just want to give support."
)

## counts the medical words in this text vector
counts <- count_medical_terms(text = medical_text)

## show results
tibble::as_tibble(counts)

Disclaimer

healthforum was developed to collect publicly available data from the website patient.info. The purpose of this package is to facilitate academic research. It is the final user's responsibility to store the data securely and obey all applicable local, state, and federal laws and ethical guidelines. For informed consent procedures for using patients.info forum data, please contact their Data Protection Officer at [e-mail]. Their address is Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA. You may also want to contact your local IRB to obtain information about privacy policy.

LingshuHu/healthforum documentation built on Oct. 20, 2020, 1:22 a.m.