sned_bendall_2024

4,806 responses from 801 respondents to 6 items.

About this table

DescriptionThe Salford Nature Environments Database (SNED)
ReferenceBendall, R. C., Royle, S., Dodds, J., Watmough, H., Gillman, J. C., Beevers, D., ... & Gregory, S. E. (2025). The Salford Nature Environments Database (SNED): an open-access database of standardized high-quality pictures from natural environments. Behavior Research Methods, 57(1), 1-17.
DOI10.3758/s13428-024-02556-4
LicenceCC0 1.0
Source datahttps://osf.io/qm42t/

Size and shape

Responses4,806
Respondents801
Items6
Response categories10
Responses per respondent6
Responses per item801
Density1
LongitudinalFALSE

Classification

age rangeNon-human
sampleNon-human
construct typeOther
measurement toolObservational rating
item formatLikert Scale/selected response
primary language(s)eng
construct nameThe Salford Nature Environments Database (SNED)

Item text

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

InstrumentSNED participant questionnaires: Perceived rurality-urbanity V2 (adapted from Cox et al., 2018) and MacArthur Scale of Subjective Social Status (Adler et al., 2000)
Mean words per item23.333
Mean characters per item119.667
Mean characters per response3.600
Flesch-Kincaid grade level5.901

Columns

cov_agecov_countryofbirthcov_countryofresidencecov_educationcov_ethnicitycov_gendercov_nationalityiditemresprt

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("sned_bendall_2024")
# Python
pip install irw

import irw
df = irw.fetch("sned_bendall_2024")

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