Introduction

The distribution of diseases among humans is different and knowledge and awareness of the disease is done within the framework of cultural patterns.Due to the intervention of social factors and conditions in the course and flow of treatment, social sciences partner with medicine and health and treatment and the emergence of medical sociology is necessary [1-3].

Berkman and Kawachi (2018) and Baird et al. (2016) argue that medical sociology seeks to understand how social and cultural factors affect the distribution and understanding of disease, reactions to disease, and the evolution and functioning of institutions. Health care and the development of social policies are effective [4-6]. Each disease affects not only the medical institution, but also several social levels, such as family or professional settings. Historical course of diseases, evolution of medical science, study of health status and its social determinants, cultural and social interpretations of health status and disease, physician-patient relationship, study of hospital status are among the topics studied in the community.

People with this disease experience a variety of physical and mental dysfunctions caused by the disease throughout their lives. These disorders severely affect daily functioning, family and social life, functional independence, and planning for the future [7]. Family disputes, divorce and incompatibility are common among people with MS. Also, in these patients, embarrassment and feelings of inferiority cause inappropriate patient responses so that the patient adapts to the disease in various forms, including denial, depression, deprivation and hostility. Currently, more than 2.5 million people worldwide and more than 500,000 people in the United States have MS [8]. In Iran, according to the report of the MS Association in 1989, there are about 50,000 patients. In Hamedan, according to the MS Association, the number of these patients is estimated to be than one thousand, of which 946 are members of the association. Research shows that coping strategies play an important role in the ways in which individuals they react to stressful situations and negative life events and play. Coping strategies are often used to mediate between stressful events and consequences such as anxiety, depression, mental disorder, and physical disability [9-12].

On the other hand, since MS affects the working age population, it threatens their job opportunities and leads them to degrade socioeconomic status and isolation. As a result, the morale of these people is weakened [13].

Inflammation is one of those diseases that, in addition to the sick person, affects the lives of those around him in a significant way. When a person is told that he or she has contracted an inflammatory disease, in fact, this message is not only given to one person, but also to his or her family, who have to adjust to a chronic, debilitating and, of course, unpredictable illness. Due to the specific nature of inflammatory bowel disease (unpleasant and unpredictable symptoms and drug side effects) and its prevalence among the young population, which severely affects the quality of life and that it is a chronic disease, so far, no definitive and effective treatment has been identified for it. Patients need to adapt and coordinate with their chronic disease. Their recovery depends on how they adapt to changing circumstances. Therefore, research on this issue is important so that patients can better control stressful life situations. The fact that things seem out of control can lead to negative reactions, so understanding the lack of control over the disease can lead to reactions such as feelings of helplessness and depression. Coping strategies used against stressful conditions (disease) are different in different people and are usually unique and include factors such as emotional characteristics, person, age, gender, social relationships, coping methods. What the person has used before is affected by the emotional and social support and resources available to the person. In order to improve the patient's condition and more effective rehabilitation and principled and purposeful planning for the treatment process and rehabilitation and psychological interventions of patients, focusing on coping styles affects the rate of recovery and adaptation to the disease. Effective coping styles reduce the negative effects of stress and increase the ability to manage environmental and internal stressors by applying these behaviors. Ineffective coping styles, on the other hand, increase the negative effects of stress. Effective coping is an important source for creating a sense of well-being and mental adjustment in stressful situations and affects the physical and mental health of individuals (11). Therefore, the study and diagnosis of factors that can affect patients' coping strategies, i.e., problem-oriented, emotional-oriented, and lead patients to effective coping with the disease, is essential from a medical sociological point of view and It is important. In addition to preventing the progression of this disease, the quality of life of these patients will also increase to fulfill their duties and responsibilities and to be a useful person for the society. In addition, focusing on improving behavior and strengthening healthy lifestyles and effective disease management can prevent the billions of dollars that are spent annually on health and disease [14]. In this study, we answered this question: What are the psychosocial factors affecting coping strategies in MS patients?

Method

In order to investigate the effect of psychosocial factors on coping strategies of MS patients, theories related to socioeconomic status, social relations network, social support, self-efficacy and disease perception as well as coping strategies are presented, and used to explain this process. Testing research hypotheses, answering questions, and achieving research objectives require facilities, tools, and methods that must be developed prior to the commencement of the empirical review. Due to the nature of the research, which is a survey, the data were collected using a structured questionnaire technique. Three categories of questions have been used in the questionnaire.

The first category of questions measures the dependent variable of the research, coping strategies. The second group of questions measures independent variables, i.e., socioeconomic status, social relations network, social support, self-efficacy and disease perception, and the third category of questions are contextual questions or identification in the form of which variables Because age, gender, marital status will be questioned.

In this study, the standard questionnaire of coping styles of Lazarus and Folkman (2016), with Cronbach's alpha coefficient of 0.84 and the researcher-made questionnaire of social support of chronic patients (2009) with Cronbach's alpha coefficient of 0.97 and the standard questionnaire of self-efficacy by Scherer et al. (2010) with a Cronbach's alpha coefficient of 0.81 and also a questionnaire of social relations and disease perception adapted from Rezaei Dadgar (2017) were used.

Data Analysis Method

In the present study, descriptive statistics including frequency distribution tables and relative distribution, calculation of central indices and dispersion and graphs were used to process the data [15-17]. Then, according to the explanatory or descriptive nature of the research, statistical tests appropriate to the hypotheses were used. In this research, to determine the sample size, Cochran's general formula was used in which the probability of the existence of a confrontational strategy trait and the absence of the 0.5 trait were considered [18-20].

n= =  = 270

N = statistical population size

n = sample size

p = probability of having an attribute

q = probability of not having an attribute (q = 1-p)

d = Allowed error value

n = 270

Thus, a sample population of 270 was obtained using the formula of 270 people, but about 18 questionnaires were returned unanswered. Available sampling method was used and the data were collected from patients who referred to the MS Association at intervals of two months and part of the data was collected through the website of the MS Association. In this research, an attempt was made to first define the independent and dependent variables of the research in a practical way and to determine the dimensions to be measured, then how to measure them, including the measurement tool (spectrum, single question, set) [19-21].

 Table 1. Measuring indicators of social relations network

Social support: Social support includes the acquisition of information, routine help, health plan or advice, emotional support from important others, such as spouse, relatives, friends, and social contacts with religious institutions [22-24]. In other words, the set of supports that enable people to be able to cope with everyday problems and crises in life is called social support.

Operational definition: To measure social support according to the approach of Ratus (2018), Sarasen and Pearson (2010) and Wellman (2018), three dimensions are considered: Emotional support/ emotional support, instrumental support/practical and information support/ notifier used. All three items are sequential at the level of measurement and by adding them, the index of social support at the level of distance measurement is obtained [25-27].

The social support questionnaire was developed by Khodapanahi et al. (2009), which is a scale for measuring the social support of chronic patients. The questionnaire has 79 items, 34 of which measure support, i.e., emotional, informational and instrumental, and therefore these items were extracted from the questionnaire.

The alpha coefficient obtained in the God-shelter research is 97. This questionnaire is answered in the form of Likert grade and in four forms. To quantify the answers, scores are given from one to four scores. Items 1 to 18 measure emotional support, items 19 to 28 measure information support, and 29 to 34 instrumental supports.

Table 2.  Indicators for measuring social support

Feeling of self-efficacy: Self-efficacy includes one of the set of beliefs that play a key role in balancing human life and improving the quality of human life. In this study, the general self-efficacy questionnaire (GSE) Scherer et al. (2018) was used to measure self-efficacy [28-30]. This questionnaire has been compiled on a Likert scale with 17 questions. For each question, there are 5 options from strongly agree to strongly disagree and their scores vary from 1 to 5. The lowest score is 17 and the highest score is 85. The reliability of this scale in Fooladvand (2007) research through Cronbach's alpha is 0.81 and in Beyrami research, it is 0.79 [31].

 Table 3. Self-efficacy sense items

Perception of disease: Perception of disease means a person's perception of the disease that is based on cognition. Cognition refers to a person's thoughts and interpretations about events or his relationship with them. In this study, the perception of the disease in three dimensions, namely the patient's attitude towards the disease, the initial causes of the disease, the belief in the effectiveness of treatment and controllability of the disease has been considered, which has been measured using the following items. This questionnaire was adapted from Rezaei Dadgar's (2017) dissertation.

Results and discussion

Reliability: Cronbach's alpha method was used to measure the reliability of the questionnaire. In social science research, a value above 0.5 is acceptable and a value below 0.5 indicates poor reliability and is not acceptable. If the alpha value is low, it can be increased by increasing the items, removing the heterogeneous items, and modifying the item structure. Pre-test was performed to determine the Cronbach's alpha value [32-34].

Table 4. Gender frequency distribution

Frequency distribution of marital status

For the marital status variable, the frequency and percentage were calculated and its bar chart was presented. Of the total sample, 55.9% were single and 44.1% were married.

Table 5. Frequency distribution of marital status

Frequency distribution of age group

The age distribution of respondents is shown in Table 6. As can be seen, most of the respondents were in the age group of 26-30 (76 people or 29.9%) [35-39].

Table 6. Frequency distribution of age group

Descriptive indicators of age

For the variable of age, mean, standard deviation, skewness, elongation, minimum and maximum were calculated. The mean age of the sample was 31.09 years, the minimum value was 17 and the maximum value was 47 years [40-44].

Table 7. Table of descriptive indicators of age

Frequency distribution of education

As can be seen, the literacy status of the respondents indicates that all the respondents were literate. As shown in Table 8, 3.9% of the respondents had primary education, 6.3 had secondary education, 37% of them had a diploma, 17.7% had a post-diploma and 35% had a bachelor's degree or higher [45-49].

Table 8. Distribution of education frequency

Frequency distribution of income

The lowest income of respondents was 350,000 thousand Tomans and the highest amount was 3,000,000 million Tomans.

Table 9. Frequency distribution of income

Frequency distribution of job status

Job status is the value and social weight of jobs in the eyes of individuals. In this study, to score the jobs of the respondents in the job classification, Kazemipour (1999) developed a model for determining the socio-economic status of individuals and measuring social mobility based on a case study [50-53].

Table 10. Frequency distribution of job status

According to Table 10, from the total sample population, 112 people (equivalent to 44.1%) had low job status, 132 people (equivalent to 52%) had medium job status and 10 people (equivalent to 3.9%) held high job status [54].

Frequency distribution of socio-economic base

For the variable of socio-economic base, the frequency and percentage were calculated and its bar chart was presented. Of the total sample, socio-economic status was 22% low, 72.8% medium and 5.1% high [55-59].

Table 11. Frequency distribution of socio-economic base

Descriptive Indicators of Independent Variables

For the variables of social relations network, social support, self-efficacy and disease perception, mean, standard deviation, skewness, elongation, minimum and maximum were calculated. Scores can be changed in the range of 1 to 5. The average of social network is 3.62, the minimum value is 1 and the maximum value is 5 [60-64].

Table 12. Descriptive indicators of independent variables

Descriptive Indicators of Coping Styles

For the variables of coping styles, mean, standard deviation, skewness, elongation, minimum and maximum were calculated.

Table 12. Descriptive indicators of coping styles

Checking the normality of the distribution of scores of variables

To examine the normality of the distribution of scores of variables, Kolmogorov-Smirnov test was used [65].

The null hypothesis in this test was that the distribution was normal. If the significance level of the test is greater than 0.05, the null hypothesis is confirmed and we conclude that the distribution of the desired variable was normal [66-68].

 According to the obtained levels of significance, it was concluded that all variables had an abnormal distribution (levels of significance less than 0.05). Therefore, non-parametric tests were used to test the hypotheses [69-71].

Table 13. Results of Kolmogorov-Smirnov test to check the normality of score distribution

Table 14. Results of Kruskal-Wallis test for comparison of coping styles according to socioeconomic status

Table 15. Mann-Whitney test for comparison of low and medium base coping styles

Table 16. Mann-Whitney test for comparison of low and high base coping styles

Table 17. Mann-Whitney test to compare coping styles in middle and high base

 Data analysis

To test this hypothesis, Spearman correlation test was used. The assumption of zero in this test is that the correlation coefficient is zero (no relationship). The results of Spearman correlation test showed that at the 95% probability level, there was a direct significant relationship (positive correlation coefficient and significance levels is less than 0.05) between the social relations network with the search for social support (correlation coefficient equal to 0.621), accountability (correlation coefficient equal to 0.234), prudent problem solving (correlation coefficient equal to 0.624) and facial confrontation (correlation coefficient equal to 0.438) [72-74].

There was a significant inverse relationship (negative correlation coefficient and significance levels is less than 0.05) between the network of social relations with positive re-evaluation (correlation coefficient equal to -0.488), distance seeking (correlation coefficient equal to -0.495), self-control (correlation coefficient equal to -0.274), and escape-avoidance (correlation coefficient equal to 0.524 0-).

Table 18. Spearman correlation coefficient test for social network and coping styles

The correlation matrix shows that there is a negative linear relationship between the network of social relations and positive re-evaluation, avoidance, self-control and avoidance, while the relationship between the network of social relations and avoidance, self-control and positive re-evaluation is weak.

But there is a positive linear relationship with confrontational confrontation, deliberate problem solving and seeking social support, and there is also a weak positive relationship with responsibility.

This means that patients with a high social network used more problem-oriented coping style and vice versa, patients with high social network used less emotion-oriented coping style.

Table 19. Spearman correlation test for social support and coping styles

The correlation matrix shows that there is a negative linear relationship between social support and positive re-evaluation, avoidance, self-control and avoidance-responsibility, but there is a positive linear relationship with confrontational coping, deliberate problem solving and seeking social support. This means that patients with high social support were more likely to use problem-oriented coping styles, and conversely, patients with high social support were less likely to use emotion-focused coping styles.

Table 20. Spearman correlation test for sense of self-efficacy and coping styles

Matrix correlation results show that there is a negative linear relationship between feelings of self-efficacy with positive re-evaluation, avoidance, self-control and avoidance, but there is a positive linear relationship between confrontational coping, deliberate problem solving and positive re-evaluation. There is also a weak positive relationship. This indicates that the more people feel high in self-efficacy, the more likely they are to use problem-oriented coping styles, and the lower the sense of self-efficacy, the more likely they are to use emotion-focused coping styles.

Table 21. Spearman correlation test for disease perception and coping styles