Date of Completion
Distraction, Psychology, Measurement
Field of Study
Doctor of Philosophy
Worker distraction has potential implications for task performance and other important workplace outcomes. However, most research on worker distraction has focused on identifying “distractors” (i.e. sources of distraction), while failing to recognize the distraction experience as a key proximal predictor of such outcomes.
This study addresses this gap by developing a new self-report measure, the Distraction in General Scale (DIGS). As many of the existing distraction measures are dependent on or worded to reflect the sources of the distraction (e.g. noise, family problems), this measure encompasses the broad construct of distraction at work, irrespective of the source. Based on theories of workplace interruptions, emotional distraction, and mood/affect, this study suggests that the domain of the distraction experience is multi-dimensional, including cognition-based and emotion-based (positive and negative) responses to distractors. This project provides a rationale for the multi-dimensionality of the DIGS, and builds these explicit cognitive and emotion-based components into the measure.
Pilot testing includes item development, and initial testing of the proposed factor structure of the DIGS using Multidimensional Scaling and Retranslation analyses. The dimensionality and reliability of the resulting measure was evaluated in Study One via Exploratory Factor Analyses. Finally, Study Two uses Structural Equation Modeling to confirm the dimensionality of the measure and to provide convergent, discriminant, and criterion-related validity evidence for the three DIGS subscales.
Results from the project provide preliminary support for the DIGS by suggesting a three-factor measure representing the construct of the distraction experience. Factors were broken into cognition-based, positive emotion-based, and negative-emotion based distraction experiences.
This project demonstrated the consistency and validity of the three DIGS sub-factors through high reliability scores, as well as through assessments of convergent, discriminant, and criterion-related validity. This measure is one of the first to be constructed in such a way that allows for generalizability across samples, situations, locations, etc., and due to the self-report nature of the DIGS, it has the ability to be utilized more frequently than other types of measures. With such a measure, researchers can explore the distraction construct and the ways in which it may have positive and negative impacts on the workplace.
Boyko, Nicole C., "Initial Development and Psychometric Evaluation of the Distraction in General Scale (DIGS)" (2015). Doctoral Dissertations. 701.