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What Predicts CRNA Burnout? Inside the 2022 AANA Journal Study

By FairShare Team · 3 min read

Published by FairShare: May 5, 2026 · 3 min read

Topic: Understanding Anesthesia Burnout

Audience: crna, leader

Type: study-brief

Published in the AANA Journal in April 2022, this study set out to identify what actually predicted burnout, job satisfaction, and turnover intention among CRNAs during COVID-19 patient surges — using structural equation modeling on survey data collected from CRNAs practicing in Massachusetts and Texas.

Three predictors stood out

  • A decrease in job feedback. CRNAs who felt they were getting less regular, meaningful input on their work were more likely to show signs of burnout.
  • The quality of the relationship between CRNAs and administration. Where that relationship was weaker, burnout rose.
  • Ongoing conflict between work demands and personal responsibilities — the day-to-day friction of trying to hold both together.

The authors' own conclusion is worth sitting with: burnout levels were directly correlated with both job satisfaction and turnover intention, meaning this wasn't just an individual wellbeing issue — it was a pipeline directly connected to whether a CRNA stayed or left. Their recommendation to employers was specific: build organizational strategies that improve job feedback, strengthen CRNA-administration relationships, and support work-life integration, rather than treating burnout as something CRNAs need to individually manage.

None of the three predictors identified here are about raw workload. They're about feedback, relationship quality, and the day-to-day negotiation between work and life — all things a workplace's operating structure can meaningfully shape, independent of patient volume or staffing ratios. That's the layer FairShare's wellness platform is built to instrument.

Source

  • Lea J, Doherty I, Reede L, Mahoney CB. Predictors of Burnout, Job Satisfaction, and Turnover Among CRNAs During COVID-19 Surging. AANA Journal. 2022;90(2):141–147.

Sources

  1. Predictors of Burnout, Job Satisfaction, and Turnover Among CRNAs During COVID-19 Surging (2022) · Class: primary · Tier: 1

    Structural equation modeling study of CRNAs; decreased job feedback, poor CRNA-administration relations, and work-over-personal-life prioritization predicted burnout; burnout correlated with job satisfaction and turnover intention; CRNA-administration relationship quality and job feedback quality were independently predictive.

    Population: U.S. CRNAs (during COVID-19 surging period)

    Limitations: Survey during COVID surge may overestimate steady-state burnout; cross-sectional design limits causal inference.

    Read original publication

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