12,223 responses from 719 respondents to 17 items.
One of 2 tables from the same source; this one measures Brief Symptom Inventory (BSI). The others are listed under Related tables.
| Description | Cognitive Diagnosis Modeling for characterizing mental health symptom profiles, Brief Symptom Inventory (BSI) |
|---|---|
| Reference | Tan, Z., De la Torre, J., Ma, W., Huh, D., Larimer, M. E., & Mun, E. Y. (2023). A tutorial on cognitive diagnosis modeling for characterizing mental health symptom profiles using existing item responses. Prevention Science, 24(3), 480-492. |
| DOI | 10.1007/s11121-022-01346-8 |
| Licence | CC BY 4.0 |
| Source data | https://data.mendeley.com/datasets/97bzg6z28h/1 |
| Responses | 12,223 |
|---|---|
| Respondents | 719 |
| Items | 17 |
| Response categories | 5 |
| Responses per respondent | 17 |
| Responses per item | 719 |
| Density | 1 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | Educational |
| construct type | Affective/mental health |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | eng |
| construct name | Brief Symptom Inventory (BSI) |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Cognitive Diagnosis Modeling for characterizing mental health symptom profiles, Brief Symptom Inventory (BSI) |
|---|---|
| Mean words per item | 4.765 |
| Mean characters per item | 29.353 |
| Mean characters per response | 10.400 |
| Flesch-Kincaid grade level | 5.352 |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, cdm_mentalhealth_tan_2023.R. 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 |
| Other columns | ||
qmatrix__an | Not documented Item classifications for cognitive diagnostic modeling (Q-matrix). | not traced |
qmatrix__ap | Not documented Item classifications for cognitive diagnostic modeling (Q-matrix). | not traced |
qmatrix__de | Not documented Item classifications for cognitive diagnostic modeling (Q-matrix). | not traced |
qmatrix__ho | Not documented Item classifications for cognitive diagnostic modeling (Q-matrix). | not traced |
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:
# R (no account needed)
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("cdm_mentalhealth_tan_2023_bsi")
# Python (needs a free Redivis account)
pip install irw
import irw
df = irw.fetch("cdm_mentalhealth_tan_2023_bsi")
@article{Tan_2022, title={A Tutorial on Cognitive Diagnosis Modeling for Characterizing Mental Health Symptom Profiles Using Existing Item Responses}, volume={24}, ISSN={1573-6695}, url={http://dx.doi.org/10.1007/s11121-022-01346-8}, DOI={10.1007/s11121-022-01346-8}, number={3}, journal={Prevention Science}, publisher={Springer Science and Business Media LLC}, author={Tan, Zhengqi and de la Torre, Jimmy and Ma, Wenchao and Huh, David and Larimer, Mary E. and Mun, Eun-Young}, year={2022}, month=feb, pages={480–492} }
| IRW version | v540 |
|---|---|
| Redivis dataset | item_response_warehouse v70.0 |
| Redivis dataset DOI | 10.57761/4qxs-pq87 |
| Manifest pin for this IRW version | v70.0 |
| Metadata source | irw_meta v37.0 |