Milken Institute School of Public Health Poster Presentations (Marvin Center & Video)
Developing a Self-Scoring Mechanism for the Motivation Assessment for Team Readiness, Integration, and Collaboration (MATRICx)
Poster Number
101
Document Type
Poster
Status
Graduate Student - Masters
Abstract Category
Prevention and Community Health
Keywords
collaboration, self-scoring instrument, team motivators
Publication Date
4-2017
Abstract
Objective. To develop a translational self-scoring sheet for the Motivation Assessment for Team Readiness, Integration, and Collaboration (MATRICx) instrument for individuals and teams to be able to use the tool in team reflection and maintenance.
Methods. A review of the team science literature was used to compile a list of motivators and deterrents to collaboration that were developed into 6 domains of collaborative functioning in health and biomedical teams. This list informed the development of 55 indicators representing a hierarchical spectrum of collaboration. Rasch analysis was used to investigate the rating scale structure, unidimensionality, and person-item fit of responses from 150 participants. Items were analyzed applying a 1-parameter Rasch model using Winsteps® 3.80.1. Pilot data analysis provided a hierarchy of motivators and threats which make up the MATRICx framework.
Results. Several iterations have contributed to the development of a self-scoring scale that maps individual participant motivators for collaboration against degree of collaborative experience and along the domains of collaborative functioning in a graphical context. This is usable by individuals and teams to establish the degrees and depth of collaborative motivation in order to improve collaboration for all team members.
Summary of findings. The self-scoring sheet provides the basis for technological advancement of the MATRICx tool to be designed and promoted as a mobile application for use by teams and to collect data for further research. Ultimately, the self-scoring graphical framework will be used as part of the technical development of the MATRICx mobile application
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Open Access
1
Developing a Self-Scoring Mechanism for the Motivation Assessment for Team Readiness, Integration, and Collaboration (MATRICx)
Objective. To develop a translational self-scoring sheet for the Motivation Assessment for Team Readiness, Integration, and Collaboration (MATRICx) instrument for individuals and teams to be able to use the tool in team reflection and maintenance.
Methods. A review of the team science literature was used to compile a list of motivators and deterrents to collaboration that were developed into 6 domains of collaborative functioning in health and biomedical teams. This list informed the development of 55 indicators representing a hierarchical spectrum of collaboration. Rasch analysis was used to investigate the rating scale structure, unidimensionality, and person-item fit of responses from 150 participants. Items were analyzed applying a 1-parameter Rasch model using Winsteps® 3.80.1. Pilot data analysis provided a hierarchy of motivators and threats which make up the MATRICx framework.
Results. Several iterations have contributed to the development of a self-scoring scale that maps individual participant motivators for collaboration against degree of collaborative experience and along the domains of collaborative functioning in a graphical context. This is usable by individuals and teams to establish the degrees and depth of collaborative motivation in order to improve collaboration for all team members.
Summary of findings. The self-scoring sheet provides the basis for technological advancement of the MATRICx tool to be designed and promoted as a mobile application for use by teams and to collect data for further research. Ultimately, the self-scoring graphical framework will be used as part of the technical development of the MATRICx mobile application
Comments
Poster to be presented at GW Annual Research Days 2017.