The Effect of Self-Compassion Interventions on Nursing Students' Stress, Resilience, and Psychological Well-Being

Overview

The study aims to determine the impact of self-compassion-based psycho-education on supporting nursing students in managing stress, improving their resilience, and enhancing their self-compassion and psychological well-being (PWB). Self-compassion involves being kind to oneself during challenging times; it provides practical tools and knowledge to enhance personal growth and resilience. By participating in this program, nursing students may learn strategies to improve their coping with the pressure of studies, build emotional strength, and improve their psychological well-being. The study will measure the participants' levels of self-compassion, stress, resilience, and psychological well-being using a validated questionnaire before and after participation in the program and compare them to determine the program's impact on the abovementioned variables.

The below standard operating procedures will be used to make sure that the study's patient recruitment, data collection, data management, data analysis, and reporting of adverse events are all done consistently and accurately in line with ethical standards: The inclusion and exclusion criteria, which specify the eligibility criteria, will guide the recruitment of participants. The recruitment process will use various student communication channels, such as emails, social media, and classroom announcements, to invite participants to the study. The investigators will provide study details to the participants before obtaining informed consent; demographic information about the participants and their recruitment status will be kept in secure folders. The investigators will use validated instruments before and after the intervention to measure self-compassion, stress, resilience, and psychological well-being, as approved by the ethics committee and data quality control procedures. The self-compassion-based psychoeducation will be delivered according to the protocol approved by the ethics committee. Participants' identities will be confidential and kept in secure password-protected systems for storing data; the investigators will conduct regular audits during data entry to ensure consistency and accuracy. Statistical Package software for social sciences, version 25, will be used for analysis as planned in collaboration with a statistical analysis expert to ensure accurate interpretation of the results. The participants will be given information and contact information of the investigators to report adverse events, such as any unexpected psychological distress during or after the program. The research team will document, follow up with the participants, and refer them to the university counseling center if necessary. Using G power, the researchers carried out a-priori power analysis to determine the sample for the study since the literature search that the investigators conducted did not show any interventional study that assessed the effect of the self-compassion psycho-education intervention on self-compassion, stress, resilience, and psychological well-being, the investigators draw reference to methods used by Yip and Tong (2019) when conducting study, the researchers used the effect size results of self-compassion intervention meta-analysis of Zessin et al. (2015); the analysis found large effect size (g = 0.90) between self-compassion and well-being. The sample size required for 90% (1-β = 0.90) power at α=0.05 level for the assumption that the effect size will be large (d=0.90) in the study was calculated as 54 participants, 27 for each group, using G\*Power 3.1.9.2 software, t-tests - repeated measures difference between two independent means analysis: A priori: Compute required sample size Input: Effect size d = 0.9, α err prob = 0.05, Power (1-β err prob) = 0.90, allocation ratio N2/N1 Output: noncentrality parameter λ = 3.30, Critical t = 2.00, df = 52, Total sample size = 54, actual power = 0.90. Considering the withdrawal rate (attrition rate) of 17% in a study of self-compassion intervention by Yang et al. (2024), the researchers calculated 17% of the calculated sample in this study (54/100 = 0.54 \* 17 = 9.18, approximately 10). Therefore, the calculated sample size (54) and the addition of the computed attrition rate (10) will give a total of 64 participants (32 each for the intervention and the control group). Subjects will be recruited through convenience sampling. To ensure the integrity and validity of results, the investigators will use validated data collection tools, conduct periodic checks during data collection, and maintain regular communication and simple explanations to participants to encourage complete and accurate responses. Investigators will regularly check the collected data for completeness and the data entries for further review and possibly record the type and extent of missing data in a log for transparency. Depending on the type of data missing, the investigators will handle it appropriately through coding, imputation technique, or exclusion criteria; the investigators will assess the pattern of the missing data and undertake sensitivity analysis to examine the impact of missing data on results and validate conclusions; the investigators will report all the above if it occurs to ensure transparency in handling missing data without altering participants' responses. Evaluation of Data: All data will be analyzed using the study's Statistical Package for the Social Sciences (SPSS) version 25. Descriptive statistics (frequencies, percentages, mean, and standard deviation) will be used to describe the demographic data and summary of the scores of the state self-compassion scale long form (SSCS-L), stress, resilience, and PWB. For the impact of the intervention, a normality test will be conducted using the Kolmogorov-Smirnov test, and an appropriate statistical test will be applied after the test; for instance, an independent t-test will be utilized for between-group comparisons if the test satisfies the assumptions of a parametric independent t-test. The alternative nonparametric test (Mann-Whitney U Test) will be used if the assumption is unmet. For within-group comparisons, if the data satisfy the assumption of the parametric test, paired t-tests will be applied to assess changes in the intervention group between the pre-test and post-test, as well as those of the control group. The significance level will be set at p \< 0.05; if the assumption of the parametric test (paired t-tests) is not met, a nonparametric alternative (Wilcoxon signed rank test) will be used, and the significance level will be set at p \< 0.05.