ali_2021_phq9
1,524 responses from 170 respondents to 9 items.
About this table
| Description | 9-item PHQ-9 depression screener (0-3 frequency scale), from a COVID-19 mental well-being survey of nurses in a tertiary hospital in Kenya (N=170). |
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| Reference | Ali S, Shah J, Talib Z (2021) COVID-19 and mental well-being of nurses in a tertiary facility in Kenya. PLoS ONE. |
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| DOI | 10.1371/journal.pone.0254074 |
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| Licence | CC BY 4.0 |
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| Source data | https://doi.org/10.1371/journal.pone.0254074.s001 |
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Size and shape
| Responses | 1,524 |
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| Respondents | 170 |
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| Items | 9 |
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| Response categories | 4 |
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| Responses per respondent | 8.965 |
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| Responses per item | 169.333 |
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| Density | 0.996 |
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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 | Patient Health Questionnaire-9 (PHQ-9; Kroenke, Spitzer & Williams, 2001) |
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| Mean words per item | 12 |
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| Mean characters per item | 69.222 |
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| Mean characters per response | 15.250 |
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| Flesch-Kincaid grade level | 7.135 |
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Columns
cov_age_catcov_genderiditemresp
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("ali_2021_phq9")
# Python
pip install irw
import irw
df = irw.fetch("ali_2021_phq9")
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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