9,220 responses from 461 respondents to 20 items.
| Description | Measures negative affectivity using PANAS negative affect items, divided into fear (6 items) and distress (4 items) subfactors. Reflects general emotional distress and anxiety. |
|---|---|
| Reference | Elhai, J. D., & Casale, S. (2026). Is fear of missing out (FOMO) differentially related to underlying dimensions of negative affectivity? Analyzing latent factors of rumination, depression, and negative affect. Anxiety, Stress, & Coping, 1–13. https://doi.org/10.1080/10615806.2026.2624434 |
| DOI | 10.1080/10615806.2026.2624434 |
| Licence | CC BY 4.0 |
| Source data | https://data.mendeley.com/datasets/pwfr54ss5p/1 |
| Responses | 9,220 |
|---|---|
| Respondents | 461 |
| Items | 20 |
| Response categories | 5 |
| Responses per respondent | 20 |
| Responses per item | 461 |
| 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 | Positive and Negative Affect Scale (PANAS) |
cov_agecov_sexiditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("FomoNegativeAffect_cremer_2026_panas")
# Python
pip install irw
import irw
df = irw.fetch("FomoNegativeAffect_cremer_2026_panas")
| IRW version | v393 |
|---|---|
| Redivis dataset | item_response_warehouse_2 v19.0 |
| Redivis dataset DOI | 10.57761/qtx5-4m80 |
| Manifest pin for this IRW version | v19.0 |
| Metadata source | irw_meta v23.0 |