gilbert_meta_101

49,598 responses from 256 respondents to 9 items.

About this table

DescriptionParticipants rated 9 depression-related symptoms daily via digital self-report during treatment.
ReferenceSchumacher, L., Klein, J. P., Elsaesser, M., Härter, M., Hautzinger, M., Schramm, E., & Kriston, L. (2023). Implications of the network theory for the treatment of mental disorders: a secondary analysis of a randomized clinical trial. JAMA psychiatry, 80(11), 1160-1168.
DOI10.1001/jamapsychiatry.2023.2823
LicenceCC BY-NC-SA 4.0
Source datahttps://osf.io/fhqmk/

Size and shape

Responses49,598
Respondents256
Items9
Response categories2
Responses per respondent193.742
Responses per item5510.889
Density21.527
LongitudinalTRUE

Classification

age rangeAdult (18+)
sampleClinical
construct typeAffective/mental health
measurement toolSurvey/questionnaire
item formatSlider/continuous
primary language(s)eng
construct nameDepression Symptom Dynamics

Item text

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

InstrumentParticipants rated 9 depression-related symptoms daily via digital self-report during treatment.
Mean words per item2.444
Mean characters per item25.556
Mean characters per response25
Flesch-Kincaid grade level13.859

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, gilbert_meta_101.R. 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).pat_id_x
itemIRW standard Item identifier.made in the build script
respIRW standard Response value.made in the build script
treatIRW standard Treatment group assignment in experimental studies.group_x
waveIRW standard Longitudinal wave indicator.session_n

What item codes and covariate values stand for is in the codebook released with the source data.

Get the data

Licence: CC BY-NC-SA 4.0 — non-commercial use only; adaptations must be shared under the same licence.

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("gilbert_meta_101")
# Python
pip install irw

import irw
df = irw.fetch("gilbert_meta_101")

How to cite

@article{Schumacher_2023, title={Implications of the Network Theory for the Treatment of Mental Disorders: A Secondary Analysis of a Randomized Clinical Trial}, volume={80}, ISSN={2168-622X}, url={http://dx.doi.org/10.1001/jamapsychiatry.2023.2823}, DOI={10.1001/jamapsychiatry.2023.2823}, number={11}, journal={JAMA Psychiatry}, publisher={American Medical Association (AMA)}, author={Schumacher, Lea and Klein, Jan Philipp and Elsaesser, Moritz and Härter, Martin and Hautzinger, Martin and Schramm, Elisabeth and Kriston, Levente}, year={2023}, month=nov, pages={1160} }

Version and provenance

IRW versionv549
Redivis datasetitem_response_warehouse_2 v33.0
Redivis dataset DOI10.57761/6m04-m698
Manifest pin for this IRW versionv33.0
Metadata sourceirw_meta v39.0