Self-care

Social support is the physical and emotional comfort given to someone in times of need or crises and it is especially important for maintaining good physical and mental health. Despite the contribution of intelligent technological devices, which have led to the availability of various types of social support systems, the latter are still not widely known to many. These support systems are currently available in many versions, such as in tablets and smartphones, where many health information systems have been created specifically to accommodate to the needs of current mobile healthcare consumers. In this paper, we systematically review the role of social support provided via health information systems and report a qualitative study that investigates the perceptions of healthcare professionals and consumers towards incorporating social support in self-care applications. The results obtained through our study reveal that social support is associated with better health management and is a vital component to be incorporated in any novel health information system. Likewise, the results are supported by our qualitative study that indicates healthcare professionals and consumers emphasize the inclusion of the social support component in self-care applications to achieve better health outcomes.

Objective: Coronary Artery Disease is a chronic and complex disease requiring continuous medical care. The current study was conducted to for predicting Health-Related Quality of Life based on Emotion Regulation with mediating to Self-Care in Patients with Coronary Artery Disease (CAD). Methods: The research method was a descriptive study and correlation type. The statistical population comprised all patients with CAD (N=350) referring to Shohadaye Tajrish Hospital in Tehran, Iran, in the second half of 2020. Based on the Tabachnick Fidell formula, 184 subjects were selected using a convenient sampling method. Research instruments were the Self-Care Scale (Jaarsma, Halfens, Tan & et al, 2003), Emotion Regulation Questionnaire of Garnefski & Graich, 2001), and HRQol Survey (Ware, Kosinski, Keller, 1996). Data analysis was done using Structural Equation Modeling (SEM) and path analysis. Results: The data indicated a positive and significant mediating role of self-care in the relationship between emotion regulation (β= 0.175, p<0.01) and HRQoL of patients with CAD. Moreover, self-care and emotion regulation had a positive impact on HRQoL. Conclusion: According to findings, a part of the mutual effect of self-efficacy and emotion regulation on HRQoL is explained by self-care. On the other hand, high emotion regulation, and self-care led to better HLQoL of CAD patients.

Background: This study aimed to design and apply a self-care training package for elementary students’ health. According to the purpose of the study, two hypotheses were posed. The first hypothesis states that the self-care training package is effective for the elementary students’ health improvement and the second hypothesis is that the self-care training package is effective in promoting the health components of elementary students. Method: This research was experimental with pretest-posttest and control group design. The statistical population of the study was all elementary students of public schools in Tehran city in the academic year 2019-2020. In this study, the health questionnaire and a researcher-made self-care questionnaire were used to collect the required data. In compiling the training package, the topics were divided into eight dimensions or topics of self-care including physical, nutritional, psychological, social, sleep, virtual, sexual, and health components. Results: The results of the study showed that the self-care training package was effective in promoting primary students’ health. Conclusion: It also was effective in promoting each health component (physical health and mental health) in primary school students.

Objective: This research investigated the mediating role of self-compassion in the relationship of type D personality with psychological well-being and self-care behaviors in patients suffering from type 2 diabetes. Research Method: The statistical population of this research included all patients with type 2 diabetes in the cities of Rasht and Rezvanshahr in 2020-2021. In this descriptive cross-sectional study, 368 patients were selected through purposive consecutive sampling. The participants completed the questionnaire of the summary of diabetes self-care activities (SDSCA), type D personality scale (DS-14), Ryff's scale of psychological well-being (RSPWB), and self-compassion scale – short form (SCS-SF). The data were processed through structural equation modeling (SEM) in AMOS-24. Bootstrapping was carried out by Preacher and Hayes’ (2008) macro to analyze the mediating relationships. Results: According to the bootstrapping analysis, self-compassion plays a significantly mediating role in the relationship of type D personality with psychological well-being and self-care behaviors (in all cases p<0.0001). The coefficient of determination of the final model demonstrated that all exogenous and medicating variables can predict 89% of the psychological well-being changes and 87% of self-care behaviors. Conclusions: Self-compassion can serve as a buffer and reduce the destructive effects of the type D personality on the psychological well-being and self-care behaviors in diabetic patients. Thus, taking measures to train and strengthen self-compassion is essential in the psychological treatment of diabetic patients.

Objective: The aim of the present study was to design a model of self-care culture for the elderly, which was conducted using a mixed approach. Methods: This research is developmental in terms of its objective and is descriptive-correlational based on its methodology, utilizing Excel software for analysis. The statistical population in the qualitative section consisted of 28 academic experts in the fields of medicine, nursing, and sociology. These experts were selected based on criteria such as experience, relevance of academic discipline, educational degree, university teaching, and research and publication background in this area, using purposive and snowball sampling methods. Findings: The output of this stage included 47 categories in the form of 6 components (self-care knowledge, self-care self-efficacy, self-care skills, spiritual self-care discipline, self-care self-centeredness, and social self-care norms). Self-care knowledge is the foundation for developing a self-care culture among the elderly. Spiritual self-care discipline and self-care self-centeredness fall into the dependent cluster, meaning they are primarily the result of the elderly self-care culture model and changes in other components of the model lead to changes in these components. Additionally, self-care self-efficacy is in the interdependent cluster, indicating that this component is dynamic and any change in it can affect the model. Self-care knowledge also lies in the independent cluster and influences other components. Conclusion: The self-care culture model provides the groundwork for creating conditions and infrastructures that lead to the empowerment of individuals and society for self-care.

Objective: This study aimed to present a structural model of the quality of life for the elderly based on self-care with the mediating role of social support. Methods: The research employed a correlational design using structural equation modeling. The study population consisted of individuals aged 60 to 75 years living in urban homes in Tehran, with 314 participants selected as the research sample. The data collection tools included the Iranian version of the Phillips Social Support Questionnaire (1986), the World Health Organization's Quality of Life Questionnaire (1989), and the Elderly Self-care Questionnaire by Younesi et al. (2020). The statistical technique used was a full latent variable structural equation model, and the data analysis was performed using SPSS version 26, AMOS version 24, and R software version 4.3.1. Examination of the model fit indices indicated that the model overall is in excellent condition for explaining and fitting the data. Findings: The results showed that both social support and self-care have a significant positive effect on the quality of life variable for the elderly. Moreover, the self-care variable also has a significant positive impact on the social support variable at a 95% confidence level. Additionally, the self-care variable significantly affects the quality of life of the elderly through the mediating variable of social support. Conclusion: According to the findings of this study, the mediating role of social support can play a significant role in examining changes in the quality of life of the elderly. It is recommended that the importance of social support be emphasized and taught in elderly care centers and other counseling and guidance centers.

Objective: The objective of this study was to propose a structural model explaining the quality of life based on early maladaptive schemas and the mediating role of self-care in female patients with type 2 diabetes. Methods: This descriptive-correlational study employed structural equation modeling. The statistical population included all female patients with type 2 diabetes in Tehran who visited medical centers in 2021. The sample consisted of 250 female patients with type 2 diabetes from Tehran in 2021, selected through convenience sampling based on inclusion and exclusion criteria. Data were collected using the short form of the World Health Organization Quality of Life Questionnaire (WHO, 1996), the short form of the Young Schema Questionnaire (Young, 1998), and the Diabetes Self-Care Activities Questionnaire (Toobert et al., 2000). Data analysis was conducted using structural equation modeling and Pearson correlation methods with SPSS.22 and AMOS.22 software. Findings: Fit indices indicated a good fit of the proposed model with the data: PCFI = 0.655, PNFI = 0.661, CMIN/DF = 2.90, RMSEA = 0.089, IFI = 0.917, CFI = 0.914, GFI = 0.903. The highest coefficient (-0.47) was related to the pathway from the domain of impaired autonomy and performance to quality of life. The determination coefficient for the marital relationship quality variable in the proposed structural model was 0.889, indicating that exogenous variables could predict 89% of the changes in quality of life, which is considered strong. Conclusion: It can be concluded that the structural model explaining quality of life based on early maladaptive schemas and the mediating role of self-care in female patients with type 2 diabetes was well-fitted.

Objective: The aim of the present study was to explain the structural model of quality of life based on early maladaptive schemas and the mediating role of self-care in women with type 2 diabetes. Methods: This research is classified as descriptive-correlational using structural equation modeling. The statistical population included all women with type 2 diabetes in Tehran who visited healthcare centers during 2021. The sample comprised 350 women with type 2 diabetes in Tehran in 2021, selected through convenience sampling based on inclusion and exclusion criteria. Data were collected using the World Health Organization Quality of Life Brief Questionnaire, the Young Schema Questionnaire-Short Form, and the Diabetes Self-Care Activities Questionnaire. Data were analyzed using structural equation modeling and Pearson correlation statistical methods with SPSS.22 and AMOS.22 software. Findings: The results showed the fit indices were PCFI=0.655, PNFI=0.661, CMIN/DF=2.90, RMSEA=0.089, IFI=0.917, CFI=0.914, and GFI=0.903, indicating a good fit of the proposed model with the data. The highest coefficient (-0.47) was attributed to the pathway from the domain of impaired autonomy and performance to quality of life. Conclusion: The coefficient of determination for the quality of marital relationship variable in the proposed structural model was 0.889, indicating that exogenous variables could predict 89% of the variations in quality of life, which is a strong prediction.