Self-regulation, engagement, motivation, and performance in a simulated quality control task

Area of Science:

• Cognitive Psychology
• Human Factors Engineering
• Pharmacy Practice Research

Background:

• Accurate error detection is crucial in pharmacy quality control.
• Understanding the interplay of self-regulation and motivation is key to optimizing performance in demanding tasks.
• Simulated environments provide a controlled setting to study these cognitive factors.

Purpose of the Study:

• To investigate the relationship between self-regulation, task-related motivation, and performance in a simulated prescription-checking task.
• To examine how these factors influence error detection accuracy (sensitivity and specificity) and task engagement.
• To explore the temporal dynamics of motivation and engagement throughout the task.

Main Methods:

• Ninety-one participants completed self-regulation, task engagement, and motivation assessments.
• Participants performed a simulated quality control task involving checking 80 prescriptions with embedded errors (26-38% error ratio).
• Motivation and engagement were measured at the beginning, midpoint, and end of the task; performance was assessed via sensitivity and specificity.

Main Results:

• Task-related motivation positively correlated with higher sensitivity (better error detection).
• Self-regulation correlated with lower specificity (more false alarms).
• Mid-task motivation and self-regulation predicted higher mid-task engagement.

Conclusions:

• Motivation is linked to improved accuracy in identifying errors, whereas self-regulation may lead to increased caution, potentially causing more false alarms.
• Both motivation and self-regulation contribute to sustained task engagement, particularly during the middle phase of a quality control task.
• Findings suggest targeted interventions for motivation and self-regulation could enhance pharmacy quality control performance and reduce errors.