gholami_2017_periodontal_knowledge
4,098 responses from 543 respondents to 3 items.
About this table
| Description | 3-item periodontal knowledge quiz (0=incorrect/1=correct), 3 waves (baseline/2 follow-ups), Iranian adults (n=543) |
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| Reference | Gholami et al. (2017). Evaluation of the Impact of a Mass Media Campaign on Periodontal Knowledge among Iranian Adults. PLOS ONE. |
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| DOI | 10.1371/journal.pone.0169668 |
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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.0169668 |
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Size and shape
| Responses | 4,098 |
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| Respondents | 543 |
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| Items | 3 |
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| Response categories | 2 |
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| Responses per respondent | 7.547 |
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| Responses per item | 1,366 |
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| Density | 2.516 |
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| Longitudinal | TRUE |
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Classification
| measurement tool | Test |
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| item format | Likert Scale/selected response |
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| primary language(s) | per |
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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 | Periodontal knowledge questionnaire (three-item subset of a validated ten-item instrument) |
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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 | 4.500 |
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| Flesch-Kincaid grade level | -3.400 |
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Columns
cov_agecov_economiccov_educationcov_employmentcov_gendercov_maritaliditemrespwave
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("gholami_2017_periodontal_knowledge")
# Python
pip install irw
import irw
df = irw.fetch("gholami_2017_periodontal_knowledge")
Version and provenance
| IRW version | v393 |
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| Redivis dataset | item_response_warehouse_4 v7.0 |
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| Redivis dataset DOI | 10.57761/cpj5-vm97 |
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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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