A mixed-method of the happy-productive: wellbeing and performance patterns of remote workers in Brazil
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View abstract on PubMed
Summary
This summary is machine-generated.This study explored job wellbeing and performance in remote workers, identifying four patterns: 9-to-5, entrenched, engaged, and burned-out. High performance was linked to remote work challenges like adaptability and trade-offs.
Area Of Science
- Organizational Psychology
- Remote Work Studies
- Human Resources Management
Background
- Understanding the interplay between employee wellbeing and job performance is crucial in modern workplaces.
- Remote work presents unique challenges and opportunities affecting both wellbeing and performance.
- Previous research has not fully elucidated the nuanced relationships within diverse remote work contexts.
Purpose Of The Study
- To investigate the relationship between job wellbeing and job performance among remote workers.
- To identify distinct patterns or clusters emerging from this relationship.
- To explore how specific remote work challenges correlate with these identified patterns.
Main Methods
- A mixed-method approach was employed, utilizing open-ended questions to gather qualitative data.
- The study analyzed data from 297 remote workers in Brazil.
- Cluster analysis was used to identify patterns in the relationship between job wellbeing and performance.
Main Results
- Four distinct clusters were identified: 9-to-5, entrenched, engaged, and burned-out.
- High-performance clusters demonstrated a relationship with remote work issues.
- Transversal issues like trade-offs and adaptability affected all groups, while social exchange and resource availability varied by cluster.
Conclusions
- Job wellbeing and performance in remote work are not monolithic, forming identifiable patterns.
- Addressing remote work challenges like adaptability and work-life balance is key for high performance.
- Tailored support considering factors like social exchange and resource availability is necessary for different remote worker profiles.
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