ASCQ-Me

[joshgilbert1994]

public domain

https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/8OFSL3

[saviranadela]

Hi @KingArthur0205 I split the items based on my understanding of the column names and the topics they covered: B3, Global, Sex, Comorbid, and Severity, while grouping the remaining individual items under "Others." What do you think of this approach? I confirmed with Ben, and he suggested removing the "Others" category, but I’d love to hear your thoughts! The codebook is in the dataverse link.

cc: @ben-domingue

ASCQME_Keller_2016.zip

library(dplyr)
library(tidyr)

df <- read.table("ascqme_ft.tab", header=TRUE, sep="\t")

df <- df %>%
  select(-c(SC_Type, Sex, Age, Pin, Clinic))

dfB3 <- df %>%
  select(rid, starts_with("B3")) %>%
  pivot_longer(starts_with("B3"),
               names_to = "item",
               values_to = "resp") %>%
  filter(!is.na(resp))

dfGlobal <- df %>%
  select(rid, starts_with("Global")) %>%
  pivot_longer(starts_with("Global"),
               names_to = "item",
               values_to = "resp") %>%
  filter(!is.na(resp))

dfComrbd <- df %>%
  select(rid, starts_with("Comrbd")) %>%
  pivot_longer(starts_with("Comrbd"),
               names_to = "item",
               values_to = "resp") %>%
  filter(!is.na(resp))

dfSev <- df %>%
  select(rid, contains("Sev")) %>%
  pivot_longer(contains("Sev"),
               names_to = "item",
               values_to = "resp") %>%
  filter(!is.na(resp))

dfSex <- df %>%
  select(rid, starts_with("Sex")) %>%
  pivot_longer(starts_with("Sex"),
               names_to = "item",
               values_to = "resp") %>%
  filter(!is.na(resp))

dfOthers <- df %>%
  select(-starts_with("Sex"), -contains("Sev"), -starts_with("Comrbd"), -starts_with("Global"), -starts_with("B3")) %>%
  pivot_longer(cols = -rid,
               names_to = "item",
               values_to = "resp") %>%
  filter(!is.na(resp))

write.csv(dfB3, "ASCQME_Keller_2016_B3.csv", row.names=FALSE)
write.csv(dfGlobal, "ASCQME_Keller_2016_Global.csv", row.names=FALSE)
write.csv(dfComrbd, "ASCQME_Keller_2016_Comorbid.csv", row.names=FALSE)
write.csv(dfSev, "ASCQME_Keller_2016_Severity.csv", row.names=FALSE)
write.csv(dfSex, "ASCQME_Keller_2016_Sex.csv", row.names=FALSE)
write.csv(dfOthers, "ASCQME_Keller_2016_Others.csv", row.names=FALSE)

[KingArthur0205]

@saviranadela Hi Savira! I'll take a look into this. Cheers : )

[KingArthur0205]

@saviranadela Hi Savira, one quick note: The id columns are called rid at the moment. Maybe we can change them?

[KingArthur0205]

@saviranadela @ben-domingue I discovered this list of scales they have on the website: https://www.healthmeasures.net/explore-measurement-systems/ascq-me/intro-to-ascq-me/list-of-measures.

I was thinking maybe we can categorize the items based on this chart. If we look at the items that start with B3_1_Sl, these probably correspond to the Sleep row in the chart. This may be more clear to the researchers when they map and compare with the original data.

Just my very initial thought and unfortunately may add a lot of workloads to Savira. sorry :( I'd like to discuss this further and open to any advice.

[ben-domingue]

splitting it based on that chart seems great

[ben-domingue]

splitting it based on that chart seems great

…

On Thu, Nov 7, 2024 at 12:40 PM Arthur Pan ***@***.***> wrote: @saviranadela <https://github.com/saviranadela> @ben-domingue <https://github.com/ben-domingue> I discovered this list of scales they have on the website: https://www.healthmeasures.net/explore-measurement-systems/ascq-me/intro-to-ascq-me/list-of-measures . I was thinking maybe we can categorize the items based on this chart. If we look at the items that start with B3_1_Sl, these probably correspond to the Sleep row in the chart. Just my very initial thought. 2024-11-07.20.37.51.png (view on web) <https://github.com/user-attachments/assets/b53842ba-ebac-436b-abca-39c5f802250b> — Reply to this email directly, view it on GitHub <#635 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AAKKMHBUOII3E3T5GHY4SP3Z7PF5DAVCNFSM6AAAAABQD5G3R2VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDINRTGE3TANRVGY> . You are receiving this because you were mentioned.Message ID: ***@***.***>

[saviranadela]

@KingArthur0205 thanks for the find Arthur! and no worries. the survey here appears to be much more detailed and comprehensive than the ASCQ-Me measures available on the website, so i'll need to review it thoroughly again. the current split seems fine, but i'll double-check to confirm

[ben-domingue]

@saviranadela not clear to me if this one is ready to be processed as-is?

[KingArthur0205]

@ben-domingue I think Savira is still working on this one as the scale table is rather comprehensive and complicated. Basically need to start from scratch. : (

[ben-domingue]

d'oh! sorry @saviranadela . at some point i always think it is ok to say "more trouble than it is worth" for the present.