4,560 responses from 456 respondents to 10 items.
One of 4 tables from the same source; this one measures Smartphone Addiction Scale-Short Version (SAS-SV). The others are listed under Related tables.
| Description | Smartphone Addiction Scale-Short Version (SAS-SV), 10 items, 1-6; N = 456 students at a public junior high school in China (ages 12-15); cov_gender, cov_grade, cov_age. |
|---|---|
| Reference | Lin, W., Liang, H., Jiang, H., Mohd Nasir, M. A., & Zhou, H. (2023). Why is Smartphone Addiction More Common in Adolescents with Harsh Parenting? Depression and Experiential Avoidance's Multiple Mediating Roles. Psychology Research and Behavior Management, 16, 4817-4828. https://doi.org/10.2147/PRBM.S428167 |
| DOI | 10.2147/PRBM.S428167 |
| Licence | CC BY 4.0 |
| Source data | https://doi.org/10.6084/m9.figshare.24100509.v1 |
| Responses | 4,560 |
|---|---|
| Respondents | 456 |
| Items | 10 |
| Response categories | 6 |
| Responses per respondent | 10 |
| Responses per item | 456 |
| Density | 1 |
| Longitudinal | FALSE |
| age range | Child (<18y) |
|---|---|
| child age (for child-focused studies) | Adolescent (12-18y) |
| sample | Educational, General/non-specific |
| construct type | Behavioral |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | chi |
| construct name | Smartphone Addiction Scale-Short Version (SAS-SV) |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, lin_2023_smartphone_addiction.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). | made in the build script |
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 | T1年龄（周岁） |
cov_gender | Covariate | T1性别 |
cov_grade | Covariate | T1年级 |
What item codes and covariate values stand for is in the codebook released with the source data.
Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("lin_2023_smartphone_addiction")
# Python
pip install irw
import irw
df = irw.fetch("lin_2023_smartphone_addiction")
@article{Lin_2023, title={Why is Smartphone Addiction More Common in Adolescents with Harsh Parenting? Depression and Experiential Avoidance‘s Multiple Mediating Roles}, volume={Volume 16}, ISSN={1179-1578}, url={http://dx.doi.org/10.2147/PRBM.S428167}, DOI={10.2147/prbm.s428167}, journal={Psychology Research and Behavior Management}, publisher={Informa UK Limited}, author={Lin, Wanqing and Liang, Hanyu and Jiang, Huaibin and Mohd Nasir, Mohd Azrin and Zhou, Huiling}, year={2023}, month=Nov, pages={4817–4828} }
| IRW version | v584 |
|---|---|
| Redivis dataset | item_response_warehouse_5 v8.5 |
| Redivis dataset DOI | 10.57761/41xy-5k56 |
| Manifest pin for this IRW version | v8.5 |
| Metadata source | irw_meta v44.0 |