muir_2025_resilience_behaviours
501 responses from 70 respondents to 8 items.
About this table
| Description | Organizational-resilience behaviours scale, university staff, 8 items, N=70 |
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| Reference | Muir, T., et al. (2025). Investigating organizational resilience in a medicine and health sciences university in United Arab Emirates. PLOS ONE. |
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| DOI | 10.1371/journal.pone.0338728 |
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| Licence | CC BY 4.0 |
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| Source data | https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0338728 |
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Size and shape
| Responses | 501 |
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| Respondents | 70 |
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| Items | 8 |
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| Response categories | 3 |
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| Responses per respondent | 7.157 |
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| Responses per item | 62.625 |
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| Density | 0.895 |
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| Longitudinal | FALSE |
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Classification
| sample | Workplace |
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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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Item text
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Conducive Organizational Response Behaviours |
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| Mean words per item | 11.375 |
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| Mean characters per item | 82.375 |
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| Mean characters per response | 8.333 |
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| Flesch-Kincaid grade level | 12.131 |
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Columns
cov_agecov_gendercov_length_of_servicecov_roleiditemresp
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("muir_2025_resilience_behaviours")
# Python
pip install irw
import irw
df = irw.fetch("muir_2025_resilience_behaviours")
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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