Evidence map›Paper›PMID 42677910›Full record

ArticleJournal of nursing management2026

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

Wai Chun Ho, Chi Tim Hung, Lung Kwan Tang

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Article in Journal of nursing management, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Wai Chun HoIntensive Care Unit, Queen Elizabeth Hospital, Hospital Authority, Hong Kong, China, qehconnect.com.ORCID https://orcid.org/0009-0002-7775-3820
Chi Tim HungThe Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China, cuhk.edu.hk.ORCID https://orcid.org/0000-0003-2103-8377
Lung Kwan TangIntensive Care Unit, Queen Elizabeth Hospital, Hospital Authority, Hong Kong, China, qehconnect.com.ORCID https://orcid.org/0009-0002-6128-2681

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe 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.

methodsFollowing 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.

resultsSixty-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.

conclusionAI 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.

Indexed as

Critical Care NursingJob SatisfactionNursesAdultAttitude of Health PersonnelFeasibility StudiesFemaleFocus GroupsHumansIntensive Care UnitsMaleMiddle AgedPersonnel TurnoverQualitative ResearchSurveys and Questionnairesappreciative inquiryjob satisfactionstrength-based

Identifiers

PMID42677910
PMCPMC13531693

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