multiple regression analysis

Psychological well-being is of paramount imporance for cancer patients and is affected by various factors, such as personality traits. The present study aimed to predict psychological well-being based on resilience and personality type D in cancer patients.

The current research was conducted based ona descriptive-correlatioal design. The statistical population of this research was made up of all cancer patients who were members of Maxa in Isfahan in 2021. The research sample included 220 cancer patients who were selected via aailable sampling. The data collection tools were demographic characteristics questionaire, psychological well-being questionnaire by Riff (1995), personality type D by Denault (2005), and resilience by Connor and Davidson (2003). The data were analyzed in SPSS software (version 24). Descriptive statistics included mean, standard deviation, and percentage, while inferential statistics including Pearson's correlation coefficient and multiple regression analysis. The significance level was considered to be 0.05.

The correlation matrix illustrated that psychological well-being had a significant positive correlation with the total score of resilience (r= 0.701; P=0.001) and a significant negative correlation with personality type D (r= -0.517; P=0.001). Moreover, according to the results of multiple regression analysis, 38% of the variance of psychological well-being can be predicted based on resilience and personality type D variables (P=0.001). Resilience with beta 0.38 (P=0/001; T=0.639) positively and significantly and personality type D with beta -0.25 (P=0/001; T=-1.607) can negatively and significantly predict the psychological well-being of cancer patients.

Resilience and personality type D can predict the psychological well-being of cancer patients; Therefore, the psychological well-being of cancer patients can be affected by carrying out interventions related to resilience and D personality type.