matarboumosleh_2017_spai26
16,759 responses from 683 respondents to 26 items.
About this table
| Description | Smartphone Addiction Inventory (SPAI, 26 items 4-pt Likert Strongly disagree-Strongly agree) with demographic covariates, Lebanese university students N=683 |
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| Reference | Matar Boumosleh J, Jaalouk D (2017) Depression, anxiety, and smartphone addiction in university students- A cross sectional study. PLOS ONE. |
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| DOI | 10.1371/journal.pone.0182239 |
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| Licence | CC BY 4.0 |
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| Source data | https://journals.plos.org/plosone/article/file?type=supplementary&id=10.1371/journal.pone.0182239.s001 |
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Size and shape
| Responses | 16,759 |
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| Respondents | 683 |
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| Items | 26 |
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| Response categories | 4 |
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| Responses per respondent | 24.537 |
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| Responses per item | 644.577 |
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| Density | 0.944 |
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| Longitudinal | FALSE |
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Classification
| age range | Adult (18+) |
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| sample | Educational |
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| measurement tool | Survey/questionnaire |
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| item format | Likert Scale/selected response |
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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 | Smartphone Addiction Inventory (SPAI) |
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| Mean words per item | 14.192 |
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| Mean characters per item | 81.385 |
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| Mean characters per response | 15.500 |
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| Flesch-Kincaid grade level | 8.252 |
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Columns
cov_agecov_classcov_facultycov_gendercov_personality_typeiditemresp
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("matarboumosleh_2017_spai26")
# Python
pip install irw
import irw
df = irw.fetch("matarboumosleh_2017_spai26")
Version and provenance
| IRW version | v393 |
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| Redivis dataset | item_response_warehouse_3 v7.0 |
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| Redivis dataset DOI | 10.57761/pqqn-pm43 |
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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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