About this table

Description	Short Falls Efficacy Scale-International, 7 items, 1-4; N = 9,117 Iranian adults aged 60+, 2021; cov_age, cov_education, cov_marital_status, cov_job, cov_living_with, cov_fall_history, cov_needs_adl_support.
Reference	Asadollahi, A. (2022). Falls efficacy scale-international (the short version) among Iranian older people [Data set]. Harvard Dataverse, V1. https://doi.org/10.7910/DVN/3SCNGV
Licence	CC0 1.0
Source data	https://doi.org/10.7910/DVN/3SCNGV

Size and shape

Responses	63,819
Respondents	9,117
Items	7
Response categories	4
Responses per respondent	7
Responses per item	9,117
Density	1
Longitudinal	FALSE

Classification

age range	Elderly (minimum age >50)
measurement tool	Survey/questionnaire
item format	Likert Scale/selected response
primary language(s)	per
construct name	Short FES-I (fear of falling)

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, asadollahi_2022_fesi.py. 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.

Column	What it is	Source column
IRW standard columns
`id`	IRW standard Identifier for the focal unit being measured — typically a person, but sometimes another entity (e.g., a word in a lexical task).	`ID`
`item`	IRW standard Item identifier.	made in the build script
`resp`	IRW standard Response value.	made in the build script
Respondent covariates
`cov_age`	Covariate	`YO.in.2021`
`cov_education`	Covariate	`Edu`
`cov_fall_history`	Covariate	`History.of.Falls`
`cov_job`	Covariate	`Job`
`cov_living_with`	Covariate	`LivW`
`cov_marital_status`	Covariate	`MaritalS`
`cov_needs_adl_support`	Covariate	`NADLS`

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

Get the data

Download CSVno account needed Browse on Redivisexplore and query Croissant 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("asadollahi_2022_short_fesi")

# Python
pip install irw

import irw
df = irw.fetch("asadollahi_2022_short_fesi")

How to cite

@misc{https://doi.org/10.7910/dvn/3scngv,
  doi = {10.7910/DVN/3SCNGV},
  url = {https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/3SCNGV},
  author = {Asadollahi, Abdolrahim},
  keywords = {Medicine, Health and Life Sciences, Social Sciences, Falling, Older People, FES-I},
  title = {Falls efficacy scale-international (the short version) among Iranian older people},
  publisher = {Harvard Dataverse},
  year = {2022}
}

Version and provenance

IRW version	v584
Redivis dataset	item_response_warehouse_5 v8.5
Redivis dataset DOI	10.57761/41xy-5k56
Manifest pin for this IRW version	v8.5
Metadata source	irw_meta v44.0