moe2025_erq
950 responses from 95 respondents to 10 items.
About this table
| Description | ERQ (Emotion Regulation Questionnaire), 1-7 Likert; N=95, 10 items, Italian teachers |
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| Reference | Moè, A. (2025). Self-Compassion Curbs Adoption of Demotivating Teaching Styles: The Mediation of Cognitive Reappraisal. figshare. |
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| Licence | CC BY 4.0 |
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| Source data | https://figshare.com/articles/dataset/Dataset_paper_Self-Compassion_Curbs_Adoption_of_Demotivating_Teaching_Styles_The_Mediation_of_Cognitive_Reappraisal/30385261 |
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Size and shape
| Responses | 950 |
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| Respondents | 95 |
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| Items | 10 |
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| Response categories | 7 |
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| Responses per respondent | 10 |
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| Responses per item | 95 |
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| Density | 1 |
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| Longitudinal | FALSE |
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Classification
| age range | Adult (18+) |
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| 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) | ita |
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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 | Emotion Regulation Questionnaire (ERQ) |
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| Mean words per item | 1 |
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| Mean characters per item | 2 |
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| Mean characters per response | 6.571 |
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| Flesch-Kincaid grade level | -3.400 |
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Columns
cov_agecov_gendercov_regioncov_subject_taughtcov_years_teachingiditemresp
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("moe2025_erq")
# Python
pip install irw
import irw
df = irw.fetch("moe2025_erq")
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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