10,812 responses from 636 respondents to 17 items.
| Description | Boredom avoidance and escape |
|---|---|
| Reference | Bieleke, M., Ripper, L., Schüler, J., & Wolff, W. (2022). Boredom is the root of all evil—or is it? A psychometric network approach to individual differences in behavioural responses to boredom. Royal Society open science, 9(9), 211998. |
| DOI | 10.1098/rsos.211998 |
| Licence | CC BY 4.0 |
| Source data | https://osf.io/nbw95/ |
| Responses | 10,812 |
|---|---|
| Respondents | 636 |
| Items | 17 |
| Response categories | 7 |
| Responses per respondent | 17 |
| Responses per item | 636 |
| Density | 1 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | General/non-specific |
| construct type | Behavioral |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | eng |
| construct name | Boredom Avoidance and Escape Scale |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Boredom avoidance and escape |
|---|---|
| Mean words per item | 9.353 |
| Mean characters per item | 48.118 |
| Mean characters per response | 14.429 |
| Flesch-Kincaid grade level | 5.275 |
iditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("bae_boredom_bieleke2022")
# Python
pip install irw
import irw
df = irw.fetch("bae_boredom_bieleke2022")
| 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 |