The aim of this study is to examine the effect of problem-solving approach training on the professional readiness perception of newly hired nurses. Nursing practices are dynamic and require strong problem-solving abilities. In this context, the study will explore how the support provided through education during the transition period for new graduate nurses influences their perception of professional competence.

The hypothesis of the study is that problem-solving approach training will enhance the professional readiness perception of newly hired nurses. It is anticipated that the training will improve the nurses' professional knowledge and skills, equipping them to better handle the clinical challenges they will encounter.

The study is planned to take place between February and June 2025 at Zoom platform. The population of the study consists of newly hired nurses, and a sample size calculation has been performed using power analysis. Effect size (Cohen's d): An effect size of 0.5 (moderate effect) has been assumed for this study. Alpha level (α): A Type I error rate of 0.05 is used. Power (1 - β): A power of 0.90 (90%) has been targeted.

Using these parameters and the G*Power software, the sample size is calculated to be approximately 64 participants per group. Therefore, the target is to recruit at least 128 participants for the study.

Participants will be randomly assigned to experimental and control groups. The experimental group will receive online and interactive problem-solving approach training. Participants in the experimental group will be supported with problem-solving-based training modules, focusing on decision-making skills related to nursing practice throughout the training process. The control group will not receive any training. After the training, both groups' professional readiness perceptions will be assessed using the previously determined Personal Information Form and Professional Readiness Scale.

The data collected in the study will be analyzed using SPSS (Statistical Package for Social Sciences) for Windows 22.0 software. Kolmogorov-Smirnov test will be used to determine whether the data follows a normal distribution. If p > 0.05, the data will be considered to follow a normal distribution. If p < 0.05, the data will be considered not normally distributed, and skewness and kurtosis values will be examined. For repeated measures, if the data is normally distributed, repeated measures ANOVA will be used; if the data is not normally distributed, Friedman's test will be applied. Descriptive statistics will first be used to summarize the general characteristics of the data, and the means and distributions of pre-test and post-test scores will be determined. To evaluate the effect of the training intervention, paired samples t-test will be applied to assess the differences between pre-test and post-test scores within the same group. This analysis will be used to measure the effect of the training program on time management and procrastination behaviors. Additionally, effect size (e.g., Cohen's d) will be calculated to evaluate the magnitude and significance of the training intervention's effect. Analysis of variance (ANOVA) will be used to determine whether there are significant differences between the groups, depending on the study's needs.

Inclusion Criteria:

• Over 18 years of age
• Working for a maximum of 6 months
• Graduated from the Department of Nursing
• To know and understand Turkish at an adequate level
• Voluntary participation
• Access to online education platforms
• Participated in at least 4 out of 5 weekly trainings

Exclusion Criteria:

• Department/school change
• The student requests to leave the study
• Continuing formal education
• Not working at the hospital