720 responses from 57 respondents to 13 items.
| Description | 13-item Cognitive Fusion Questionnaire item pool- NMOSD patients and caregivers combined |
|---|---|
| Reference | Esiason DC, Ciesinski N, Nurse CN, Erler W, Hattrich T, Deshpande A, O'Hayer CV (2024). The psychological burden of NMOSD – a mixed method study of patients and caregivers. PLOS ONE, 19(3), e0300777. https://doi.org/10.1371/journal.pone.0300777 |
| DOI | 10.1371/journal.pone.0300777 |
| Licence | CC BY 4.0 |
| Source data | https://doi.org/10.1371/journal.pone.0300777.s001 |
| Responses | 720 |
|---|---|
| Respondents | 57 |
| Items | 13 |
| Response categories | 7 |
| Responses per respondent | 12.632 |
| Responses per item | 55.385 |
| Density | 0.972 |
| Longitudinal | FALSE |
| sample | Clinical, Internet-based |
|---|---|
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | eng |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Cognitive Fusion Questionnaire (CFQ13) |
|---|---|
| Mean words per item | 12.846 |
| Mean characters per item | 66.615 |
| Mean characters per response | 13.571 |
| Flesch-Kincaid grade level | 5.815 |
cov_groupiditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("esiason_2024_cfq")
# Python
pip install irw
import irw
df = irw.fetch("esiason_2024_cfq")
| IRW version | v393 |
|---|---|
| Redivis dataset | item_response_warehouse_3 v7.0 |
| Redivis dataset DOI | 10.57761/pqqn-pm43 |
| Manifest pin for this IRW version | v7.0 |
| Metadata source | irw_meta v23.0 |