gilbert_meta_98
90,204 responses from 8,608 respondents to 6 items.
About this table
| Description | Gratitude |
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| Reference | Adam, Maya, 2025, "A short, animated storytelling video to boost psychological capital", https://doi.org/10.7910/DVN/WT7BYB, Harvard Dataverse, V1 |
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| Licence | CC0 1.0 |
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| Source data | https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/WT7BYB |
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Size and shape
| Responses | 90,204 |
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| Respondents | 8,608 |
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| Items | 6 |
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| Response categories | 6 |
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| Responses per respondent | 10.479 |
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| Responses per item | 15,034 |
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| Density | 1.747 |
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| Longitudinal | TRUE |
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Classification
| age range | Adult (18+) |
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| sample | Educational |
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| construct type | Cognitive/educational, Developmental |
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| measurement tool | Survey/questionnaire |
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| item format | Likert Scale/selected response |
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| construct name | A short, animated storytelling video to boost psychological capital |
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Item text
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Gratitude |
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| Mean words per item | 15 |
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| Mean characters per item | 72.167 |
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| Mean characters per response | 11.714 |
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| Flesch-Kincaid grade level | 5.862 |
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Columns
cov_agecov_ethcov_languagecov_nationalitycov_sexiditemresptreatwave
Get the data
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("gilbert_meta_98")
# Python
pip install irw
import irw
df = irw.fetch("gilbert_meta_98")
Version and provenance
| IRW version | v393 |
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| Redivis dataset | item_response_warehouse v53.0 |
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| Redivis dataset DOI | 10.57761/4g08-xt41 |
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| Manifest pin for this IRW version | v53.0 |
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| Metadata source | irw_meta v23.0 |
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