Original Research ARTICLE
The Multifactor Measure of Performance: Its Development, Norming and Validation
- 1Reuven Bar-On, Israel
This article describes the development as well as the initial norming and validation of the Multifactor Measure of Performance™ (MMP™) , which is a psychometric instrument that is designed to study, assess and enhance key predictors of human performance to help individuals perform at a higher level. It was created by the author, for the purpose of going beyond existing conceptual and psychometric models that often focus on relatively few factors that are purported to assess performance at school, in the workplace and elsewhere. The relative sparsity of multifactorial pre-employment assessment instruments exemplifies, for the author, one of the important reasons for developing the MMP™, which attempts to comprehensively evaluate a wider array of factors that are thought to contribute to performance. In that this situation creates a need in the area of test-construction that should be addressed, the author sought to develop a multifactorial assessment and development instrument that could concomitantly evaluate a combination of physical, cognitive, intra-personal, inter-personal and motivational factors that significantly contribute to performance. The specific aim of this article is to show why, how and if this could be done as well as to present and discuss the potential importance of the results obtained to date. The findings presented here will hopefully add to what is known about human performance and thus contribute to the professional literature, in addition to contribute to the continued development of the MMP™. The impetus for developing the MMP™ is first explained below, followed by a detailed description of the process involved and the findings obtained; and their potential application is then discussed as well as the possible limitations of the present research and the need for future studies to address them.
Keywords: Multifactor Measure of Performance, MMP3, Reuven Bar-On, performance, Performance measures, Measuring performance, Assessing performance, Performance models, predicting performance, Performance predictors, performance contributors., developing performance
Received: 17 Jul 2017;
Accepted: 29 Jan 2018.
Edited by:Gabriele Giorgi, Università Europea di Roma, Italy
Reviewed by:Leonidas A. Zampetakis, Technical University of Crete, Greece
Krystyna Golonka, Jagiellonian University, Poland
Copyright: © 2018 Bar-On. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: PhD. Reuven Bar-On, Reuven Bar-On, Modiin, Texas, Israel, email@example.com