gilbert_meta_92

28,953 responses from 2,433 respondents to 7 items.

About this table

Description2. Maternal anxiety: General Anxiety Disorder (GAD) Questions
ReferenceArteaga, I., de Barros, A., & Ganimian, A. J. (2025). The Challenges of Scaling up Effective Child-Rearing Practices Using Technology in Developing Settings: Experimental Evidence From India. Journal of Research on Educational Effectiveness, 1-19.
DOI10.1080/19345747.2025.2450318
LicenceCC BY 4.0
Source datahttps://zenodo.org/records/14278007

Size and shape

Responses28,953
Respondents2,433
Items7
Response categories4
Responses per respondent11.900
Responses per item4136.143
Density1.700
LongitudinalTRUE

Classification

age rangeAdult (18+)
sampleProgram-based, Targeted/specific
construct typeAffective/mental health
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)hin
construct nameMaternal anxiety: General Anxiety Disorder (GAD) Questions

Item text

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

Instrument2. Maternal anxiety: General Anxiety Disorder (GAD) Questions
Mean words per item6.429
Mean characters per item37.857
Mean characters per response15.250
Flesch-Kincaid grade level6.846

Columns

block_idcov_child_agecov_child_disabilitycov_child_femalecov_mother_agecov_mother_educcov_mother_n_childreniditemresptreatwave

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("gilbert_meta_92")
# Python
pip install irw

import irw
df = irw.fetch("gilbert_meta_92")

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