9,526 responses from 433 respondents to 22 items.
| Description | A preliminary study of how individuals evaluate their personal risks related to health (particularly COVID-19) and resource scarcity (like financial and material shortages) on various rating scales, comparing COVID-19 health threat manipulation to relaxation manipulation (N=433). Items related to PANAS. |
|---|---|
| Reference | Isler, O., Yilmaz, O., Maule, A. J., & Gächter, S. (2024). How to activate threat perceptions in behavior research: A simple technique for inducing health and resource scarcity threats. Behavior Research Methods, 56(8), 8379-8395. |
| DOI | 10.3758/s13428-024-02481-6 |
| Licence | CC BY 4.0 |
| Source data | https://osf.io/grafm/ |
| Responses | 9,526 |
|---|---|
| Respondents | 433 |
| Items | 22 |
| Response categories | 5 |
| Responses per respondent | 22 |
| Responses per item | 433 |
| Density | 1 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | Internet-based |
| construct type | Affective/mental health |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | eng |
| construct name | Positive and Negative Afect Schedule (PANAS) |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | A preliminary study of how individuals evaluate their personal risks related to health (particularly COVID-19) and resource scarcity (like financial and material shortages) on various rating scales, testing the effects of pictures vs no pictures in the manipulations (N=433). Items related to PANAS. |
|---|---|
| Mean words per item | 1 |
| Mean characters per item | 7.500 |
| Mean characters per response | 14 |
| Flesch-Kincaid grade level | 56.274 |
iditemresptreat
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("threat_isler_2024_exp2_cog_panas")
# Python
pip install irw
import irw
df = irw.fetch("threat_isler_2024_exp2_cog_panas")
| IRW version | v393 |
|---|---|
| Redivis dataset | item_response_warehouse v53.0 |
| Redivis dataset DOI | 10.57761/4g08-xt41 |
| Manifest pin for this IRW version | v53.0 |
| Metadata source | irw_meta v23.0 |