cucchi_2018_scoff

1,144 responses from 229 respondents to 5 items.

One of 6 tables from the same source; this one is the scoff table. The others are listed under Related tables.

About this table

DescriptionSCOFF eating-disorder screening scale, 5 items, eating disorder / self-harm study
ReferenceCucchi A, Hampton JA, Moulton-Perkins A (2018). Using the validated Reflective Functioning Questionnaire to investigate mentalizing in individuals presenting with eating disorders with and without self-harm. PeerJ.
DOI10.7717/peerj.5756
LicenceCC BY 4.0
Source datahttps://europepmc.org/article/PMC/PMC6211265

Size and shape

Responses1,144
Respondents229
Items5
Response categories2
Responses per respondent4.996
Responses per item228.800
Density0.999
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleClinical, Internet-based
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)eng

Item text

This table has item text in the IRW: the wording administered to respondents, not just the response codes.

InstrumentSCOFF questionnaire
Mean words per item11.400
Mean characters per item58
Mean characters per response2.500
Flesch-Kincaid grade level4.175

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, cucchi_2018_rfq.py. It is our best reading, not the source’s own codebook, and it may contain mistakes. Where the two disagree, the source data are the authority. If you find an error, please tell us.

ColumnWhat it isSource column
IRW standard columns
idIRW standard Identifier for the focal unit being measured — typically a person, but sometimes another entity (e.g., a word in a lexical task).Participant
itemIRW standard Item identifier.made in the build script
respIRW standard Response value.made in the build script
Respondent covariates
cov_ageCovariate Age
cov_educationCovariate 1 = Secondary School to age 16 · 2 = Secondary school/college to age 18 · 3 = Non-degree level vocational work-based training · 4 = University degree · 5 = University postgraduate studies (e.g. Masters) · 6 = University doctoral level studies (e.g. PhD)EduAtt
cov_employmentCovariate 1 = employed · 2 = self employed · 3 = unemployed · 4 = studying · 5 = retiredEmpStat
cov_ethnicityCovariate
12 labelled values1 = white british · 2 = white irish · 3 = other white · 5 = mixed white and black african · 6 = mixed white and asian · 7 = any other mixed · 9 = asian pakistani · 12 = black caribbean · 13 = black african · 15 = chinese · 16 = any other ethnic group · 17 = not stated
Ethnicity
cov_genderCovariate 1 = female · 2 = maleGender
cov_groupCovariate 1 = Control · 2 = ED+SH · 3 = ED aloneGroup
cov_relationshipCovariate 1 = yes · 2 = noRelationship

Covariate value labels are the source’s own, as the IRW recorded them. What item codes and any unlabelled values stand for is in the source’s questionnaire, peerj-06-5756-s001.zip, which shows the item wording.

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant metadataHugging Face, Kaggle, OpenML

Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("cucchi_2018_scoff")
# Python
pip install irw

import irw
df = irw.fetch("cucchi_2018_scoff")

How to cite

@article{Cucchi_2018, title={Using the validated Reflective Functioning Questionnaire to investigate mentalizing in individuals presenting with eating disorders with and without self-harm}, volume={6}, ISSN={2167-8359}, url={http://dx.doi.org/10.7717/peerj.5756}, DOI={10.7717/peerj.5756}, journal={PeerJ}, publisher={PeerJ}, author={Cucchi, Angie and Hampton, James A. and Moulton-Perkins, Alesia}, year={2018}, month=Oct, pages={e5756} }

Version and provenance

IRW versionv549
Redivis datasetitem_response_warehouse_4 v13.0
Redivis dataset DOI10.57761/w8zx-td92
Manifest pin for this IRW versionv13.0
Metadata sourceirw_meta v39.0