12,516 responses from 1,043 respondents to 12 items.
| Description | High-conflict Dilemmas |
|---|---|
| Reference | Kunnari, A., Sundvall, J. R., & Laakasuo, M. (2020). Challenges in process dissociation measures for moral cognition. Frontiers in Psychology, 11, 559934. |
| DOI | 10.3389/fpsyg.2020.559934 |
| Licence | CC BY 4.0 |
| Source data | https://osf.io/vmy4q/ |
| Responses | 12,516 |
|---|---|
| Respondents | 1,043 |
| Items | 12 |
| Response categories | 7 |
| Responses per respondent | 12 |
| Responses per item | 1,043 |
| Density | 1 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | General/non-specific, Internet-based |
| construct type | Cognitive/educational |
| measurement tool | Test |
| item format | Likert Scale/selected response |
| primary language(s) | eng |
| construct name | Utilitarian Inclinations and Deontological Inclinations in moral judgment, measured via the Process Dissociation Procedure |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | High-Conflict Moral Dilemmas (Greene et al., 2004 battery) |
|---|---|
| Mean words per item | 22.750 |
| Mean characters per item | 120.167 |
| Mean characters per response | 7 |
| Flesch-Kincaid grade level | 10.326 |
iditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("CPDMMC_Kunnari_2020_HCD")
# Python
pip install irw
import irw
df = irw.fetch("CPDMMC_Kunnari_2020_HCD")
| 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 |