Backend
Psychological Safety in Software Engineering Teams: A Systematic Mapping Study of Team Processes and Performance
arXiv cs.SE0 views
arXiv:2610.08896v1 Announce Type: new Abstract: Context: Psychological safety is an important human and behavioral factor in software development teams, supporting collaboration, knowledge sharing, interpersonal risk-taking, and learning. However, evidence in software engineering remains fragmented across team processes, performance outcomes, contextual conditions, barriers. Objective: This study maps literature on psychological safety in software engineering, examining its conceptualization, associations with team performance and processes, contextual influences, barriers, and strengthening strategies. Method: We conducted a systematic mapping study following established software engineering guidelines. We analyzed 112 primary studies published between 2006 and June 2026 using descriptive statistics and thematic analysis across six research questions. Results: Psychological safety emerges as a multidimensional, context-dependent, team-level construct characterized by interpersonal risk-taking, open communication, collaboration, learning, trust, and supportive interaction. It is predominantly associated with productivity, software quality, innovation, team satisfaction, collaboration, communication, and decision-making. These relationships are shaped by leadership, organizational culture, work environment, trust, and sociocultural and individual conditions. Recurring barriers include communication problems, organizational constraints, leadership issues, diversity and inclusion challenges, and workload pressures. Although diverse practices are reported, evidence of their effectiveness and long-term sustainability remains limited. Conclusion: Psychological safety is a multidimensional, context-dependent team-level construct associated with team interaction and performance. This study highlights the need for longitudinal, context-sensitive research on psychological safety interventions in software development environments.
Source:https://arxiv.org/abs/2610.08896PreviousMitigating Uncertainty Interactions in GenAI-based Adaptive Systems: Vision, Challenges and Preliminary GuidelinesNextEvaluating Change Point Detection Methods for Software Performance Regression Analysis
Related posts
FiveM Script Database Migrations: What to Check Before You Install
0dev.to
The insurance edge case that breaks event-driven policy pipelines
0dev.to
The fix for an empty state isn't filling it
0dev.to UX
Five Things That Make Dependabot Painful for Terraform
0dev.to GitHub
Tracking Roblox player counts: what the public data actually gives you
0dev.to Data
Telegram gold signals this week: results to Oct 30
0dev.to Data