gilbert_meta_54

22,560 responses from 1,880 respondents to 6 items.

One of 2 tables from the same source; this one measures knowledge, attitude, efficacy, and behavior related to menstruation, contraception, consent, and marriage.. The others are listed under Related tables.

About this table

DescriptionConsent in an RCT
ReferenceSaha, A., Dixit, A., Shankar, L., Battala, M., Khan, N., Saggurti, N., ... & Howard, S. (2023). Study protocol for an individually randomized control trial for India's first roleplay-based mobile game for reproductive health for adolescent girls. Reproductive Health, 20(1), 140. Raj, Aparna; Dixit, Anvita; Saha, Ananya; Shankar, Lalita; Howard, Susan; Battala, Madhusudana; Khan, Nizamuddin; Saggurti, Niranjan, 2024, "Go Nisha Go Randomized Controlled Trial (R4S study #1.11)", https://doi.org/10.7910/DVN/0TS1LX, Harvard Dataverse, V1, UNF:6:hoNbY3jVad2x1yxVowFamA== [fileUNF]
LicenceCC0 1.0
Source datahttps://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/0TS1LX

Size and shape

Responses22,560
Respondents1,880
Items6
Response categories4
Responses per respondent12
Responses per item3,760
Density2
LongitudinalTRUE

Classification

age rangeMixed
child age (for child-focused studies)Adolescent (12-18y)
sampleTargeted/specific
construct typeBehavioral, Cognitive/educational
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)hin, eng
construct nameknowledge, attitude, efficacy, and behavior related to menstruation, contraception, consent, and marriage.

Item text

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

InstrumentConsent in an RCT
Mean words per item17.167
Mean characters per item84.833
Mean characters per response19.750
Flesch-Kincaid grade level7.029

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, il_hte_53_54.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).not traced
itemIRW standard Item identifier.made in the build script
respIRW standard Response value.not traced
treatIRW standard Treatment group assignment in experimental studies.made in the build script
waveIRW standard Longitudinal wave indicator.not traced
Respondent covariates
cov_attend_schoolCovariate q136
cov_in_schoolCovariate q138
cov_mobile_phoneCovariate q201
cov_pursue_careerCovariate q157

What item codes and covariate values stand for is in the source’s codebook, GOC_Codebook_combined_Dictionary.pdf, GOC_Qualititive Codebook.pdf.

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("gilbert_meta_54")
# Python
pip install irw

import irw
df = irw.fetch("gilbert_meta_54")

How to cite

@misc{https://doi.org/10.7910/dvn/0ts1lx,
  doi = {10.7910/DVN/0TS1LX},
  url = {https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/0TS1LX},
  author = {Raj, Aparna and Dixit, Anvita and Saha, Ananya and Shankar, Lalita and Howard, Susan and Battala, Madhusudana and Khan, Nizamuddin and Saggurti, Niranjan},
  keywords = {Medicine, Health and Life Sciences},
  title = {Go Nisha Go Randomized Controlled Trial (R4S study #1.11)},
  publisher = {Harvard Dataverse},
  year = {2024}
}

Version and provenance

IRW versionv566
Redivis datasetitem_response_warehouse v70.0
Redivis dataset DOI10.57761/4qxs-pq87
Manifest pin for this IRW versionv70.0
Metadata sourceirw_meta v43.0