22,828 responses from 243 respondents to 26 items.
| Description | 26-item Predictors of Dropout in Addiction Treatment scale, 1-5; repeated assessments during admission, with a wave column. 243 respondents x 26 items = 22828 responses. |
|---|---|
| Reference | Sirvent-Ruiz, C., Miranda, M., & Moral-Jimenez, M. (2025). Prediction of therapeutic dropout in patients with addictions: Development and validation of the Predictors of Dropout in Addiction Treatment (PDAT). PLOS ONE. https://doi.org/10.1371/journal.pone.0326853 |
| DOI | 10.1371/journal.pone.0326853 |
| Licence | CC BY 4.0 |
| Source data | https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0326853 |
| Responses | 22,828 |
|---|---|
| Respondents | 243 |
| Items | 26 |
| Response categories | 5 |
| Responses per respondent | 93.942 |
| Responses per item | 878 |
| Density | 3.613 |
| Longitudinal | TRUE |
| sample | Clinical |
|---|---|
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | spa |
cov_days_admission_to_pdatcov_days_pdat_to_48h_requestcov_days_pdat_to_anticravingcov_days_pdat_to_dischargecov_reason_for_dischargeiditemrespwave
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("sirventruiz_2025_pdat")
# Python
pip install irw
import irw
df = irw.fetch("sirventruiz_2025_pdat")
| IRW version | v393 |
|---|---|
| Redivis dataset | item_response_warehouse_4 v7.0 |
| Redivis dataset DOI | 10.57761/cpj5-vm97 |
| Manifest pin for this IRW version | v7.0 |
| Metadata source | irw_meta v23.0 |