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Multilevel performance probability: a meta-analytic integration of expectancy and self-efficacy
S H Cady1, D G Boyd, M J Neubert
1Bowling Green State University, OH 43492, USA. scady@cba.bgsu.edu
Psychological Reports
|October 13, 2001
Summary
This meta-analysis introduces the Multilevel Performance Probability measure for assessing expectancy and self-efficacy. The new measure strongly predicts performance, with a mean r of .51, outperforming existing methods.
Area of Science:
- Psychology
- Behavioral Science
Background:
- Expectancy and self-efficacy are crucial psychological constructs.
- A consistent measurement approach for both has been lacking for over 25 years.
Purpose of the Study:
- To propose and validate a unified measure for expectancy and self-efficacy.
- To introduce the "Multilevel Performance Probability" as this integrated measure.
- To conduct a meta-analysis on its predictive validity for performance.
Main Methods:
- A meta-analysis was performed on 16 studies using the Multilevel Performance Probability measure.
- Data included 7,444 subjects across 55 tests examining the measure's relationship with performance.
- Studies were drawn from both expectancy (5 studies, 8 tests) and self-efficacy (11 studies, 47 tests) research.
Main Results:
- The Multilevel Performance Probability demonstrated a strong positive relationship with performance (mean r = .51, p < .001).
- This predictive validity is significantly higher than previously reported meta-analyses within separate expectancy (r = .21) and self-efficacy (r = .38) domains.
- The findings support the integration of expectancy and self-efficacy measurement.
Conclusions:
- The proposed Multilevel Performance Probability is a robust and effective measure.
- Integrating expectancy and self-efficacy measurement enhances predictive power for performance outcomes.
- This unified approach offers a valuable tool for future research and application.