Exploring the Feasibility of Appreciative Inquiry on Job Satisfaction of Intensive Care Nurses: A Mixed‐Method Study

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INTRODUCTION: The increasing nursing attrition rate has become a major concern. Job satisfaction is a key predictor of nurse turnover, yet the effectiveness of strength-based approaches remains underexplored. This study aimed to explore the feasibility and preliminary effects of implementing Appreciative Inquiry (AI) on job satisfaction among intensive care unit (ICU) nurses. METHODS: Following ethical approval, AI using the 5-D cycle was implemented over a five-month period with ICU nurses. The intervention involved a series of sessions designed to explore the nurses' best experiences, core values, and wishes through dialog and inquiry. The Minnesota Satisfaction Questionnaire (MSQ) was administered pre- and postintervention to assess job satisfaction changes, and focus group interviews were conducted to gather qualitative insights. RESULTS: Sixty-three ICU nurses participated in the study. Quantitative analysis showed no statistically significant increase in general job satisfaction (mean score: 68.8 to 70.0) and intrinsic satisfaction (43.4 to 44.2). However, specific MSQ subitems, particularly those related to receiving praise and sense of accomplishment, showed preliminary improvements (p < 0.05), although these findings are exploratory. Qualitative findings revealed that impactful nursing care often stems from personal interactions, highlighting why nurses find meaning and appreciation in their work. Many participants expressed interests in exploring more appreciative topics, suggesting AI's potential for broader workplace improvement. CONCLUSION: AI is a novel approach within the Hong Kong nursing context. While overall findings did not reach statistical significance, this study suggests AI application within an ICU setting is feasible. The preliminary feedback indicates its potential to enhance staff engagement and targeted aspects of job satisfaction. Further controlled and rigorous research is recommended to explore the AI impact on healthcare environments. IMPLICATIONS FOR NURSING MANAGEMENT: Nurse managers can practically integrate AI by using strength-based dialog and inquiry to focus on best practices during staff reviews, targeting specific workplace stressors, and implementing structured recognition practices to celebrate staff successes.

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