Unraveling research self-efficacy and concerns as factors associated with psychological distress among nursing scholars in the era of artificial intelligence: a multi-campus survey

Abstract

BACKGROUND: The relentless march of artificial intelligence (AI) has emerged as a formidable catalyst, offering a toolbox of novel tools and methodologies with the potential to revolutionize the very essence of research practices. OBJECTIVES: To explore the association of levels of research self-efficacy and concerns related to artificial intelligence with psychological distress among nursing scholars. METHODS: A descriptive, multi-campus survey, cross-sectional design was adopted in this study. The study employed a clustered sampling technique to ensure representation from different regions. A sample of 1494 nursing scholars completed the nursing scholars' concerns toward the artificial intelligence questionnaire, Kessler psychological distress, and the research self-efficacy scale. RESULTS: Psychological distress is negatively correlated with researchers' self-efficacy while positively correlated with concerns regarding AI. Concerns about AI contributed to increased psychological distress. In addition, female academic staff reported significantly higher psychological distress compared to males, and those younger staff members experienced more distress than older colleagues, and lower research self-efficacy was associated with higher psychological distress, and those with less experience in publishing and fewer published articles tended to report more distress. CONCLUSION: This study underscores the critical role of research self-efficacy in the era of artificial intelligence in mitigating psychological distress, highlighting its significance as a key protective factor. These insights contribute to a deeper understanding of the factors influencing psychological well-being in academic and research settings, guiding future strategies to foster resilience and mental well-being. CLINICAL TRIAL REGISTRATION: Not applicable.

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