cdm_mentalhealth_tan_2023_bsi

12,223 responses from 719 respondents to 17 items.

About this table

DescriptionCognitive Diagnosis Modeling for characterizing mental health symptom profiles, Brief Symptom Inventory (BSI)
ReferenceTan, Z., De la Torre, J., Ma, W., Huh, D., Larimer, M. E., & Mun, E. Y. (2023). A tutorial on cognitive diagnosis modeling for characterizing mental health symptom profiles using existing item responses. Prevention Science, 24(3), 480-492.
DOI10.1007/s11121-022-01346-8
LicenceCC BY 4.0
Source datahttps://data.mendeley.com/datasets/97bzg6z28h/1

Size and shape

Responses12,223
Respondents719
Items17
Response categories5
Responses per respondent17
Responses per item719
Density1
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleEducational
construct typeAffective/mental health
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)eng
construct nameBrief Symptom Inventory (BSI)

Item text

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

InstrumentCognitive Diagnosis Modeling for characterizing mental health symptom profiles, Brief Symptom Inventory (BSI)
Mean words per item4.765
Mean characters per item29.353
Mean characters per response10.400
Flesch-Kincaid grade level5.352

Columns

iditemqmatrix__anqmatrix__apqmatrix__deqmatrix__horesp

Get the data

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

Or load it directly in R or Python:

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("cdm_mentalhealth_tan_2023_bsi")
# Python
pip install irw

import irw
df = irw.fetch("cdm_mentalhealth_tan_2023_bsi")

Version and provenance

IRW versionv393
Redivis datasetitem_response_warehouse v53.0
Redivis dataset DOI10.57761/4g08-xt41
Manifest pin for this IRW versionv53.0
Metadata sourceirw_meta v23.0