Keywords
I/O; psychometrics; measures; single-item; multiple-item; regression
Abstract
The current study examines the use of single-item measures to assess constructs used by occupational stress researchers. Surveys are fundamental tools for I/O Psychologist practitioners, and multiple-item measures are commonly used to fulfill that purpose. However, long surveys may offer challenges to both administrators and respondents. As an effort to mitigate those challenges, single-item measures have been receiving recognition as a promising alternative to the current psychometric measures due to their benefits, such as reduced cost and higher face validity. We will discuss the previous studies on single-item measures and why it’s relevant to explore its potential by performing a multiple regression analysis. We wanted to explore more about single-item measures, and therefore analyze whether the two types of measures produce different levels of criterion-related validity. To address our question, we recruited 500 employed individuals through an online tool called CloudResearch Connect. This tool allowed us to quickly collect diverse data (i.e., participants of various professions) that can be generalized and reproduced. Participants had to fill out a survey with both single and multiple-item measures as our predictor and criteria variables. The items were I/O Psychology constructs with a focus on occupational stress. Results suggested multiple-item measures to outperform single-item measures. We hope to encourage more research on the matter to further understand the relationship between both measures.
Thesis Completion Year
2025
Thesis Completion Semester
Fall
Thesis Chair
Bowling, Nathan
College
College of Sciences
Department
Psychology
Thesis Discipline
Psychology
Language
English
Access Status
Open Access
Length of Campus Access
None
Campus Location
Orlando (Main) Campus
STARS Citation
Reis, Juliana, "The Loneliest Number: Implications for Using Single-Item Measures in Regression Analysis" (2025). Honors Undergraduate Theses. 454.
https://stars.library.ucf.edu/hut2024/454