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To identify key communication skills for Canadian nursing practice.
Quantitative research using a nationwide survey.
Exploratory confirmatory factor analysis was used to identify factors underlying key communication skills required for nursing practice. Multiple regression analyses were used to examine differences across demographic variables, designations, roles and settings.
Dimensions of effective communication skills were identified. Demographic and contextual variables showed some impact on the perceived importance of communication skills, but low variance suggested that language demands are relatively consistent across roles and settings.
A framework describing the communication demands for Canadian nursing practice is described, contributing to the development of tailored curricula, assessments and policies.
Focusing on communication skills ensures that nurses are equipped to deliver safe healthcare and interact effectively with patients and colleagues, potentially leading to improved health outcomes.
To our knowledge, this study is the first to develop a framework for communication skills and identify key language skill factors across nursing professional designations and practice settings. The research provides a framework for developing curricula and training programmes that focus on essential communication skills.
No patient or public contribution.
The study focused on nurses' familiarity with, beliefs about, and attitudes towards artificial intelligence, aiming to identify configurations of necessary and sufficient conditions associated with strong intentions to use artificial intelligence-based health technologies in their clinical practice.
Cross-sectional survey conducted online from mid-October 2023 through early February 2024.
The fuzzy set qualitative comparative analysis method was employed to analyse the survey data.
307 members of the professional order of nurses in Québec province, Canada.
Findings from the qualitative comparative analysis show that strong intentions to use artificial intelligence are only observed when nurses perceive artificial intelligence to have a high impactfulness on their future clinical practice (necessary condition). Moreover, we observe three configurations of sufficient conditions, that is, three combinations (artificial intelligence profiles) of familiarity with, belief about, trust in, and perceived impactfulness of artificial intelligence.
Current curriculum efforts have centred on defining artificial intelligence competencies, yet competency alone does not guarantee a willingness to adopt artificial intelligence tools. Our findings indicate that a positive attitude towards artificial intelligence's potential impact is crucial, with various profiles supporting intentions to adopt artificial intelligence.
These findings suggest that nurses' preparation should go beyond developing artificial intelligence competencies and that nursing educators and trainers need to account for the different profiles associated with strong intentions to use artificial intelligence technologies. Training programmes and nursing curricula should prioritise shaping nurses' beliefs and attitudes about artificial intelligence rather than focusing solely on technical skills.
We contribute to nursing research by showing that a positive attitude towards artificial intelligence's impactfulness on nurses' future clinical practice is a necessary condition for having high intentions to use artificial intelligence technologies.
Relevant guidelines have been adhered to by employing recommended qualitative comparative analysis reporting methods.
No patient or public contribution.
Nurses confront substantial daily workloads. Coping mechanisms, including resilient behaviours at both individual and team levels, are pivotal in managing these challenges. Factors like work experience can significantly influence individual resilience. Yet, team resilience among nurses remains relatively unexplored.
Our study examined perceptions of both individual and team resilience among Dutch hospital nurses. Furthermore, we investigated the impacts of hospital type, ward type and work experience.
The Employee Resilience Scale was used to evaluate individual resilience and adapted for team contexts to assess team resilience. This study was one of three conducted under a governmental research program aimed at improving patient safety in the Netherlands. A paired t-test and correlation analysis were conducted to compare individual resilience with team resilience. A separate t-test assessed the impact of ward type on perceived individual and team resilience. Finally, post hoc analyses were used to examine the effects of hospital type and work experience.
In total, 344 nurses from 25 different wards of 17 Dutch hospitals completed the survey. In general, nurses indicated to act more resilient on the individual level (mean = 3.77, SD = 0.61) compared to the team level (mean = 3.53, SD = 0.65; t = 7.25, p = 0.00). A correlation was found between perceived individual and team resilience (r = 0.53, p = 0.00). No effects of hospital- and ward type were found on both individual or team resilience. Years of work experience did not affect individual resilience but showed a significant effect on team resilience.
Dutch hospital nurses indicated they often act resilient on both individual and team levels. However, with increasing workloads in healthcare, being able to remain resilient will become increasingly challenging and important. Organisations should therefore support employees to maintain resilience by adapting their work environment to meet more employees' needs.
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