9,477 responses from 351 respondents to 27 items.
One of 7 tables from the same source; this one is the qol table. The others are listed under Related tables.
| Description | Objectively Assessed Exercise Behavior in Chinese Patients with Early-Stage Cancer: communication, medical coping (MCMQ), social support (SSRS), benefit-finding, and quality-of-life batteries |
|---|---|
| Reference | Liu, Z., Zhang, L., Shi, S. et al. (2017). Objectively Assessed Exercise Behavior in Chinese Patients with Early-Stage Cancer. PLOS ONE. https://doi.org/10.1371/journal.pone.0169375 |
| DOI | 10.1371/journal.pone.0169375 |
| Licence | CC BY 4.0 |
| Source data | https://doi.org/10.1371/journal.pone.0169375 |
| Responses | 9,477 |
|---|---|
| Respondents | 351 |
| Items | 27 |
| Response categories | 5 |
| Responses per respondent | 27 |
| Responses per item | 351 |
| Density | 1 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | Clinical |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | chi |
These are classifications the IRW records, not the study’s own words. Some were annotated by hand and some written by an automated tagger whose output is published only where it clears a measured accuracy bar; which values came from which is not recorded per table. Coverage and accuracy per column, and what is held back, are on Tag quality.
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, liu_2017_cancer_exercise.py. It is our best reading, not the source’s own codebook, and it may contain mistakes. Where the two disagree, the source data are the authority. If you find an error, please tell us.
| Column | What it is | Source column |
|---|---|---|
| IRW standard columns | ||
id | IRW standard Identifier for the focal unit being measured — typically a person, but sometimes another entity (e.g., a word in a lexical task). | NO |
item | IRW standard Item identifier. | made in the build script |
resp | IRW standard Response value. | made in the build script |
| Respondent covariates | ||
cov_age | Covariate | AGE |
cov_gender | Covariate | GENDER |
cov_nation | Covariate | NATION |
What item codes and covariate values stand for is in the codebook released with the source data.
Respondent uniqueness. 3% of this table’s respondents are alone in their combination of the 2 covariates above — no one else in the table shares it. That is a necessary condition for re-identification and not re-identification itself, and on a sample this size it is largely arithmetic. The IRW republishes the demographics its sources published and never at finer granularity: see the data standard.
Or load it directly in R (no account needed with irw 1.4.0 or later) or Python (needs a free Redivis account; the first call opens a browser to sign in):
# R
install.packages("irw")
library(irw)
df <- irw_fetch("liu_2017_qol")
# Python
pip install irw
import irw
df = irw.fetch("liu_2017_qol")
Or in Stata, which reads the same no-account CSV as the button above:
* Stata
net install irw, from("https://raw.githubusercontent.com/itemresponsewarehouse/Stata-pkg/main/")
irw_fetch liu_2017_qol, clear
@article{Liu_2017, title={Objectively Assessed Exercise Behavior in Chinese Patients with Early-Stage Cancer: A Predictor of Perceived Benefits, Communication with Doctors, Medical Coping Modes, Depression and Quality of Life}, volume={12}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0169375}, DOI={10.1371/journal.pone.0169375}, number={1}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Liu, Zhunzhun and Zhang, Lanfeng and Shi, Songsong and Xia, Wenkai}, editor={Li, Dongmei}, year={2017}, month=Jan, pages={e0169375} }
| IRW version | v674 |
|---|---|
| Redivis dataset | item_response_warehouse_3 v15.0 |
| Redivis dataset DOI | 10.57761/6rg4-6f73 |
| Manifest pin for this IRW version | v15.0 |
| Metadata source | irw_meta v59.0 |