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Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios
Published on: October 6, 2020
Exploring Subjective Well-Being in Human-Machine Interaction: Protocol for a Mixed Methods, Cross-Sectional Analysis
Giulia Bassi1,2, Valeria Orso2,3, Silvia Salcuni1,2
1Department of Developmental Psychology and Socialization, University of Padova, Padova, Italy.
Background:
Human-machine interaction (HMI) has gained significant attention in the context of advanced production technologies, especially concerning trust and acceptance. However, the investigation of the subjective well-being of operators working with these technologies in manufacturing companies has been largely overlooked. Moreover, previous research mostly relied on a single data-collection method, either quantitative or qualitative, thereby failing to capture a rich picture of their cognitive and affective states.
Objective:
This cross-sectional study protocol aimed to fill that gap by examining operators' subjective well-being and workplace dynamics, including fluency in HMI, negative attitudes toward technologies, and social relationships among coworkers in manufacturing companies.
Methods:
We adopt a mixed methods approach, incorporating both quantitative and qualitative data collection techniques. Quantitative data will be gathered via a digital survey containing self-report questionnaires. A path analysis will be performed to explore the multiple mediating roles of fluency in HMI and negative attitudes toward such technologies between cognitive and affective well-being. We further qualitatively investigate the operators' lived experience in HMI using semistructured audio-recorded interviews. A thematic analysis relying on text-mining techniques will then be conducted to explore operators' textual data.
Results:
We quantitatively expect that fluency in HMI may act as a protective factor for operators' affective well-being, while negative attitudes toward advanced production technologies may contribute to the development or worsening of operators' psychological distress. From a qualitative perspective, we intend to seamlessly merge quantitative insights to create a more comprehensive and well-grounded analysis. Moreover, the integrated interpretation of both the quantitative and qualitative data collected will generate a consensus report, which will aim to serve as a practical framework for guiding workplace policies and training programs meant to foster subjective well-being and effective HMI. At the time of publication, we have collected data from 12 participants and scheduled a further data collection session.
Conclusions:
Embracing one of the fundamental pillars of Industry 5.0, human-centricity, by detecting potential psychological issues early, organizations can create a workplace that prioritizes the well-being of operators. Early recognition and prevention are crucial to promoting operators' mental well-being involved in HMI.
International Registered Report Identifier (Irrid):
DERR1-10.2196/73896.
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