validatedtouchvideo_smit_2025_strength
10,633 responses from 355 respondents to 45 items.
About this table
| Description | The Validated Touch-Video Database - hedonic classification |
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| Reference | Smit, S., Rich, A.N. The Validated Touch-Video Database. Behav Res 57, 134 (2025). https://doi.org/10.3758/s13428-025-02655-w |
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| DOI | 10.3758/s13428-025-02655-w |
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| Licence | CC BY 4.0 |
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| Source data | https://osf.io/jvkqa/ |
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Size and shape
| Responses | 10,633 |
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| Respondents | 355 |
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| Items | 45 |
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| Response categories | 10 |
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| Responses per respondent | 29.952 |
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| Responses per item | 236.289 |
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| Density | 0.666 |
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| Longitudinal | TRUE |
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Classification
| age range | Adult (18+) |
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| sample | General/non-specific |
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| construct type | Opinion/attitude |
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| measurement tool | Survey/questionnaire |
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| item format | Likert Scale/selected response |
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| primary language(s) | eng |
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| construct name | The Validated Touch-Video Database - perceived threat rating |
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Columns
cov_agecov_ethnicitycov_gendercov_handednesscov_questionnairecov_survey_duration_secdateiditemresp
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("validatedtouchvideo_smit_2025_strength")
# Python
pip install irw
import irw
df = irw.fetch("validatedtouchvideo_smit_2025_strength")
Version and provenance
| IRW version | v393 |
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| Redivis dataset | item_response_warehouse_3 v7.0 |
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| Redivis dataset DOI | 10.57761/pqqn-pm43 |
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| Manifest pin for this IRW version | v7.0 |
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| Metadata source | irw_meta v23.0 |
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