Document Type : Original Research Article

Authors

1 Researcher at the Anesthesia and Pain &Molecular and cell Biology Research cente, Faculty of Medicine Department of Anatomy, Iran university of Medical Sciences, Tehran, Iran.

2 Graduate of nursing, School of nursing and medical emergency, Alborz University of Medical ‎Sciences, Researcher of Baqiyatallah Hospital Research Center,‎ Tehran, Iran.

10.22034/EJST.2022.1.8

Abstract

Introduction: The aim of this study was to investigate the effect of various psychosocial factors on coping strategies in MS patients.
Materials and Methods: The present study is a descriptive-analytical study and the study population includes all men and women with inflammatory bowel disease and members of the inflammatory bowel association. In this study, sampling method was performed by available method. In order to collect data, the standard questionnaire of coping strategies of Lazarus and Folkman, the researcher-made questionnaire of social protection, the self-efficacy questionnaire of Scherer et al. Data analysis was performed using SPSS software.
Results: The results of Kruskal-Wallis test showed that there is a significant relationship between socioeconomic status, coping strategies and the results of Spearman correlation coefficient test indicate a significant positive relationship between social network, social support, and sense of self-efficacy. Perception of the disease was problem-oriented coping strategy and inversely related to emotion-coping coping strategy.
Conclusion: The results of Spearman correlation test show that at the level of 95% probability between social support and seeking social support (correlation coefficient equal to 0.692), problematic problem solving (correlation coefficient equal to 0.739), confrontational confrontation (correlation coefficient equal to 0.466) There is a direct significant relationship (positive correlation coefficient and significance levels is less than 0.05). Researchers such as Tuis (1982) found that people with lower socioeconomic status were more likely to use emotion-avoidance coping strategies and less problem-solving coping, so our first hypothesis is cons.

Graphical Abstract

Evaluation of Psychosocial Factors in the Coping Strategies of Patients with Inflammation

Keywords

Main Subjects

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

row

Phrases

Assessment level

 

1

I have a lot of close relationships with my MSM friends.

Distance

2

When I'm with MSM friends, the latest information about MS is exchanged between us.

Distance

3

When I get tired of my illness, I hesitate with my MS friends.

Distance

4

I cooperate and participate in MS community with other MS.

Distance

5

I do not hesitate to help other MS.

Distance

         

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

Items

row

I'm sure there is someone in the family who wants me.

1

My family is trying to get me to my previous position

2

I am sure there is someone in my family who has accepted me in any situation.

3

I am sure I feel safe enough with my family.

4

My family has given me the feeling that I am a valuable person in the family.

5

I'm sure my family is worried about my condition

6

I know I'm important to my family

7

I know there are people in my family who comfort me in any situation.

8

I know my family is interested in me when I'm in a bad mood.

9

There are people in my family who give me the confidence to rely on them.

10

My family has given me the feeling that I can trust them.

11

I have seen many times that my family has tried to create a sense of hope in me.

12

I know that when I'm sad, my family tries to keep me healthy.

13

I'm sure my illness has not changed the emotional relationship between me and my family

14

I feel the need to be encouraged to endure my family's treatment.

15

I am confident that my family treats me in a way that I consider important to others.

16

I'm sure my family will not complain about my illness.

17

My family protects me from the annoying questions and looks of others.

18

My family guides me on how to deal with my illness.

19

I understand that when it comes to my illness in the family, they have changed the subject after a short time.

20

Every time I was sad, my family distracted me.

21

My family tries to give me the right homework as much as possible.

22

My family approves of the decisions I make.

23

When I'm in a difficult situation, my family and I think about what to do.

24

My family has given me information on how other patients cope with the disease.

25

My family has offered me solutions on how to deal with my illness.

26

There is someone in my family who gives me helpful suggestions to prevent possible mistakes.

27

My family supports me in such a way that I can control my illness.

28

I can understand that my family motivates me to be able to work despite my illness.

29

I can understand how my family shows me how I succeeded in my previous difficult situations.

30

My family makes my work easier by planning.

31

There is someone in my family who supports me in making important decisions.

32

My family accompanies me during medical care so that I am not alone.

33

My family tries not to cut me off from others.

34

 

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

row

Items

Assessment level

1

When I make a plan, I'm sure I can do it

Distance

2

One of my problems is that when I have to do something, I can't do it

Distance

3

If I cannot do something the first time, I will continue to try to do it

Distance

4

When I set important goals for myself, I rarely achieve them

Distance

5

I give up before I finish my work

Distance

6

I avoid problems

Distance

7

If something seems too complicated, I will not even bother to try it.

Distance

8

When I have to do something, I persevere until I finish it

Distance

9

When I decide to do something, I seriously and accurately focus on doing the same card

Distance

10

When I try to learn something new, I give it up soon if I don't succeed.

Distance

11

When unexpected problems occur to me, I do not cope well

Distance

12

I avoid learning new things when I find it difficult

Distance

13

Failure makes me try harder

Distance

14

I do not trust my ability to do things

Distance

15

I rely on myself

Distance

16

I simply give up

Distance

17

I do not have the ability to deal with most of the problems that come my way in life

Distance

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

gender

Abundance

Percent

Man

111

43.7

Female

143

56.3

Total

254

100.0

 

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

marital status

Abundance

Percent

Single

142

55.9

Married

112

44.1

Total

254

100.0

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

Age group

Abundance

Percent

<= 20

10

3.9

21 - 25

46

18.1

26 - 30

76

29.9

31 - 35

46

18.1

36 - 40

61

24.0

Above 40

15

5.9

Total

254

100.0

 

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

 

Number

average

Standard deviation

Drawing

minim

Maxim

Age

254

31.09

6.719

-.706

17

47

 

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

Education

Abundance

Percent

Primary

10

3.9

Guidance

16

6.3

Diploma

94

37.0

Associate Degree

45

17.7

Bachelor's degree and higher

89

35.0

Total

254

100.0

 

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

Income

Abundance

Percent

500 thousand and less

30

11.8

Between 500 and 800 thousand

97

38.2

Between 800 thousand and one million

71

28.0

Between one and one and a half million

29

11.4

Over one and a half million

27

10.6

Total

254

100.0

 

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

Occupational status

Abundance

Relative frequency (percentage)

down

112

44.1

medium

132

52

Top

10

3.9

Total

254

100

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

Socio-economic base

Abundance

Percent

down

56

22.0

medium

185

72.8

Top

13

5.1

Total

254

100.0

 

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

 

Number

average

Standard deviation

Drawing

Minim

Maxim

Social Relations Network

254

3.6228

1.01776

-.474

1.00

5.00

Social support

254

4.0833

.87345

-.757

2.03

5.00

Feeling of self-efficacy

254

3.4236

.60760

-1.222

2.18

4.24

Perception of disease

254

3.2661

.97293

-.364

1.20

4.90

 

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

Positive re-evaluation

Number

average

Standard deviation

Drawing

Minim

Maxim

Dory Joey

254

4.1514

3.17231

-1.194

.00

10.00

Self-control

254

4.5801

2.52473

-1.377

1.43

9.52

Seek social support

254

4.2501

2.68501

-1.003

.48

10.00

responsibility

254

6.7563

3.01560

-.594

.00

10.00

Escape

254

6.0466

3.17491

-1.098

.00

10.00

Thoughtful problem solving

254

3.6335

3.07407

-1.050

.00

10.00

Confrontational confrontation

254

6.5070

2.92225

-.771

.00

10.00

Positive re-evaluation

254

5.8005

1.91314

-.664

.48

9.05

 

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

 

Number

Statistics Z Kolmogorov-Smirnov

The significance level

 
 

Social Relations Network

254

2.995

.000

 

Social support

254

3.235

.000

 

Feeling of self-efficacy

254

3.334

.000

 

Perception of disease

254

3.590

.000

 

Coping face to face

254

2.198

.000

 

Dory Joey

254

3.083

.000

 

Self-control

254

3.435

.000

 

Seek social support

254

3.081

.000

 

responsibility

254

2.740

.000

 

Escape

254

2.552

.000

 

Thoughtful problem solving

254

2.429

.000

 

Positive re-evaluation

254

3.049

.000

 

 

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

Coping Styles

Socio-economic base

Number

Average rating

The amount of two

Degrees of freedom

The significance level

Positive re-evaluation

 

down

56

170.41

25.130

2

.000

medium

185

114.69

Top

13

124.96

Dory Joey

 

down

56

171.02

25.616

2

.000

medium

185

115.00

Top

13

117.96

Self-control

down

56

175.04

31.294

2

.000

medium

185

114.51

Top

13

107.58

Seek social support

 

down

56

70.18

45.472

2

.000

medium

185

142.50

Top

13

160.92

responsibility

 

down

56

180.54

24.924

2

.000

medium

185

140.21

Top

13

129.81

Escape

 

down

56

176.72

32.871

2

.000

medium

185

114.09

Top

13

106.35

Thoughtful problem solving

 

down

56

69.22

47.970

2

.000

medium

185

142.25

Top

13

168.58

Confrontational confrontation

down

56

72.50

42.758

2

.000

medium

185

144.16

Top

13

127.27

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

 

Socio-economic base

Number

Average rating

Total Rankings

U Man-Whitney

The value of z

The significance level

Positive re-evaluation

 

down

56

161.35

9035.50

2920.500

-4.986

.000

medium

185

108.79

20125.50

Dory Joey

 

down

56

160.87

9008.50

2947.500

-4.927

.000

medium

185

108.93

20152.50

Self-control

 

down

56

163.65

9164.50

2791.500

-5.329

.000

medium

185

108.09

19996.50

Seek social support

 

down

56

69.29

3880.50

2284.500

-6.402

.000

medium

185

136.65

25280.50

responsibility

 

down

56

80.96

534.00

2938.000

-4.972

.000

medium

185

133.12

24627.00

Escape

 

down

56

164.69

9222.50

2733.500

-5.396

.000

medium

185

107.78

19938.50

Thoughtful problem solving

 

down

56

68.79

3852.50

2256.500

-6.475

.000

medium

185

136.80

25308.50

Confrontational confrontation

down

56

68.93

3860.00

2264.000

-6.543

.000

medium

185

136.76

25301.00

 

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

 

Socio-economic base

Number

Average rating

Total Rankings

U Man-Whitney

The value of z

The significance level

Positive re-evaluation

 

down

56

37.56

2103.50

220.500

-2.235

.025

Top

13

23.96

311.50

Dory Joey

 

down

56

38.65

2164.50

159.500

-3.193

.001

Top

13

19.27

250.50

Self-control

 

down

56

39.89

2234.00

90.000

-4.280

.000

Top

13

13.92

181.00

Seek social support

 

down

56

29.38

1645.50

49.500

-4.899

.000

Top

13

59.19

769.50

responsibility

 

down

56

32.51

1820.50

224.500

-2.178

.029

Top

13

45.73

594.50

Escape

 

down

56

40.54

2270.00

54.000

-4.825

.000

Top

13

11.15

145.00

Thoughtful problem solving

 

down

56

28.93

1620.00

24.000

-5.313

.000

Top

13

61.15

795.00

Confrontational confrontation

down

56

32.07

1796.00

200.000

-2.561

.010

Top

13

47.62

619.00

 

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

 

Socio-economic base

Number

Average rating

Total Rankings

U Man-Whitney

The value of z

The significance level

Positive re-evaluation

 

medium

185

98.90

18297.00

1092.000

-.560

.576

Top

13

108.00

1404.00

Dory Joey

 

medium

185

99.06

18327.00

1122.000

-.409

.683

Top

13

105.69

1374.00

Self-control

 

medium

185

99.42

18392.50

1187.500

-.078

.938

Top

13

100.65

1308.50

Seek social support

 

medium

185

98.85

18287.50

1082.500

-.613

.540

Top

13

108.73

1413.50

responsibility

 

medium

185

100.09

18517.00

1093.000

-.557

.578

Top

13

91.08

1184.00

Escape

 

medium

185

99.31

18372.50

1167.500

-.178

.859

Top

13

102.19

1328.50

Thoughtful problem solving

 

medium

185

98.45

18213.50

1008.500

-.994

.320

Top

13

114.42

1487.50

Confrontational confrontation

medium

185

100.40

18574.50

1035.500

-.871

.384

Top

13

86.65

1126.50

 

 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

Positive re-evaluation

Dory Joey

Social Relations Network

Correlation coefficient

The significance level

Number

Self-control

-0.488**

.000

254

Seek social support

-0.495**

.000

254

responsibility

-0.274**

.000

254

Escape

0.621**

.000

254

Thoughtful problem solving

0.234*

.000

254

Confrontational confrontation

-0.524**

.000

254

Positive re-evaluation

0.624**

.000

254

Dory Joey

0.438**

.000

254

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

Positive re-evaluation

Dory Joey

Social support

Correlation coefficient

The significance level

Number

Self-control

-0.558**

0.000

254

Seek social support

-0.526**

0.000

254

responsibility

-0.424**

0.000

254

Escape

0.692**

0.000

254

Thoughtful problem solving

0.764**-

0.000

254

Confrontational confrontation

-0.660**

0.000

254

Positive re-evaluation

0.739**

0.000

254

Dory Joey

0.466**

0.000

254

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

Positive re-evaluation

Dory Joey

Feeling of self-efficacy

Correlation coefficient

The significance level

Number

Self-control

-0.639

0.000

254

Seek social support

-0.667

0.000

254

responsibility

- 0.583

0.000

254

Escape

0.600

0.000

254

Thoughtful problem solving

0.153

0.000

254

Confrontational confrontation

-0.533

0.000

254

Positive re-evaluation

0.602

0.000

254

Dory Joey

0.568

0.000

254

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

 

Perception of disease

Correlation coefficient

The significance level

Number

Positive re-evaluation

-0.724

0.000

254

Dory Joey

-0.734

0.000

254

Self-control

-0.623

0.000

254

Seek social support

0.713

0.000

254

responsibility

-0.345

0.000

254

Escape

-0.667

0.000

254

Thoughtful problem solving

0.752

0.000

254

Confrontational confrontation

0.644

0.000

254

The results of correlation matrix show that there is a negative linear (strong) relationship between disease perception with positive re-evaluation, avoidance, restraint and avoidance-avoidance and there is a weak negative relationship with responsibility. But there is a positive linear relationship with confrontational coping, deliberate problem solving, and seeking social support. They have used problem-oriented and, on the contrary, patients who hated their disease and considered it uncontrollable and incurable, have used more emotional coping style.

Results and Discussion

In this study, our aim was to investigate the psychosocial factors affecting the coping strategies of MS patients. Coping techniques, by definition, involve a person's cognitive and behavioral efforts to reduce the stress of internal or external demands. Folkman and Lazarus (2009), as experts in coping techniques, divided coping strategies into problem-oriented and emotion-oriented.

The results of Mann-Whitney test showed that the rate of seeking social support, deliberate problem solving, and confrontational confrontation in the middle and upper socioeconomic base is significantly higher than the low socioeconomic base, but there is no significant difference between the middle and upper classes. The level of responsibility in the middle socio-economic base is significantly higher than the low socio-economic base, but there is no significant difference between the middle and upper classes. The rate of avoidance, restraint, and avoidance, which are subsets of emotion-oriented coping styles in the low socio-economic status is significantly higher than the medium and high socio-economic status, but there is no significant difference between the middle and upper classes [36].

The rate of positive re-evaluation in the low socio-economic status is significantly higher than the average socio-economic status, but there is no significant difference between the middle and upper classes and also between the lower and upper classes. Therefore, our hypothesis was confirmed.

In general, it can be said that patients with low socioeconomic status use more emotional coping style. The results of Spearman correlation test show that at the level of 95% probability, there is a direct significant relationship (positive correlation coefficient and significance levels is less than 0.05) between the network of social relations 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 confrontational confrontation (correlation coefficient equal to 0.438). There is 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), restraint (correlation coefficient equal to -0.274), and escape-avoidance (correlation coefficient equal to 0.524).

The results of this study are consistent with those of Palomar Lore (2008), showing that non-poor people use more direct coping than poor people. In addition, it can be related to the theories of Cohen, Cass and Durgi (2010). Cohen (2018) believed that people in the lower classes of society were reluctant to plan for future progress. Cass (2018) found that upper-class patients expressed a higher level of recognition of the importance of symptoms than lower-class patients, and hybridization also showed that lower social classes had less abstract and more objective ways of thinking. Therefore, it can be concluded that MS patients of the lower classes of society, due to their economic conditions, have no motivation to actively and directly deal with the disease and stressful conditions. According to Wellman (2018), social support enables people to be able to cope with everyday life problems and crises and get through them well. House (2021) argued that social support could be effective in the evaluation process by expanding the range of coping mechanisms and using effective coping methods such as social community search and problem solving. Ball et al., (2021) also showed that social support as a source of coping can help to effectively choose coping strategies, especially when a person is exposed to stressful events. Therefore, the third hypothesis of this study is consistent with these findings, and those MS patients who received more social support used problem-based coping more.

In general, several studies have shown that increasing self-efficacy is associated with positive changes in health care behaviors and increasing overall health.

Conclusion

Our results are consistent with the Lontal’s (2019) model of self-government, in which the basic tenet is that patients' perceptions of their illness shape their common sense beliefs and their own implicit beliefs about their illness. Lontal (2018) believes that disease perceptions are directly related to coping and are related to coping outcomes such as disability and quality of life through coping. The results of this study provide empirical evidence for the importance of the psychosocial model to better understand and adapt to pain in MS and have important implications for understanding and treating pain in these patients. Similarly, Kerns (2018) claims that identifying factors Psychology associated with chronic MS pain can have important therapeutic implications. The results of this study also show that the emphasis on psychosocial variables such as self-efficacy and social support, along with medical interventions and even before it, can to some extent help in controlling the disease.

[1]  S. Bal, G. Crombez, V.P. Oost, I. Debourdeaudhuij, Child Abuse & Neglect, 2003, 27, 1377-1395. [crossref], [Google Scholar], [Publisher]
[2] A.J. Christensen, E.G. Benotsch, J.S. Wiebe, W.J. Lawton, Journal of Consulting and Clinical Psychology, 1995, 63, 454-459. [crossref], [Google Scholar], [Publisher]
[3] L.N. Dyrbye, M.R. Thomas, T.D. Shanafelt, Mayo Clin. Proc., 2005, 80, 1613-1622. [crossref], [Google Scholar], [Publisher]
[4]  N.S. Endler, K.M. Coracea, L.J. Summerfeldt, J.M. Johnsona, P. Rothbart, Coping with chronic pain. Personality and individual differences, 2003, 34, 323-346. [crossref], [Google Scholar], [Publisher]
[5]  H. Ford, P. Trigwell, M. Johnson, J. Psychosom Res., 1998, 45, 33–8. [crossref], [Google Scholar], [Publisher]
[6]  J. Halper, J the Neurol Sci., 2007, 256, S34–S38. [crossref], [Google Scholar], [Publisher]
[7]  K.M.G. Schreurs, D.I.D. de Ridder, Clinical Psychology Review, 1997, 17, 89-112. [crossref], [Google Scholar], [Publisher]
[8]  P. Callaghan, Journal of advanced nursing, 2000, 31, 1518-1527. [crossref], [Google Scholar], [Publisher]
[9]  M.P. McCabe. Journal of psychosomatic Research, 2005, 59, 161-166. [crossref], [Google Scholar], [Publisher]
[10]  A.D. Sadovnick, R.A. Remick, J. Allen, E. Swartz, I.M.L. Yee, K. Eisen, R. Farquhar, S.A. Hashimoto, J. Hooge, L.F. Kastrukoff, W. Morrison, J. Nelson, J. Oger, D.W. Paty Neurol, 1996, 46, 628–632. [crossref], [Google Scholar], [Publisher]
[11] A. Solari, D. Radice, Neurological Science, 2001, 22, 307-315. [crossref], [Google Scholar], [Publisher]
[12] H.H. Wang, S.Z. Wu, Y.Y. Liu, Kaohsiung J Med. Sci., 2003, 19, 345-350. [crossref], [Google Scholar], [Publisher]
[13] F.E. Sadr, Z. Abadi, N.E. Sadr, M.M. Fard, Annals of the Romanian Society for Cell Biology, 2021, 25, 6839-6852. [crossref], [Google Scholar], [Publisher]
[14] K. Ghajarzadeh, M.M. Fard, H. Alizadeh Otaghvar, S.H.R. Faiz, A. Dabbagh, M. Mohseni, S.S. Kashani, A.M.M. Fard, M.R. Alebouyeh, Annals of the Romanian Society for Cell Biology, 2021 25, 2449–2456. [crossref], [Google Scholar], [Publisher]
[15] K. Ghajarzadeh, M.M. Fard, H. Alizadeh Otaghvar, S.H.R. Faiz, A. Dabbagh, M. Mohseni, S.S. Kashani, A.M.M. Fard, M.R. Alebouyeh, Annals of the Romanian Society for Cell Biology, 2021, 25, 2457–2465. [crossref], [Google Scholar], [Publisher]
[16] K. Ghajarzadeh, M.M. Fard, M.R. Alebouyeh, H. Alizadeh Otaghvar, A. Dabbagh, M. Mohseni, S.S. Kashani, A.M.M. Fard, S.H.R. Faiz, Annals of the Romanian Society for Cell Biology, 2021, 25, 2466-2484. [crossref], [Google Scholar], [Publisher]
[17] A. Susanabadi, S. Etemadi, M.S. Sadri, B. Mahmoodiyeh, H. Taleby, M.M. Fard, Annals of the Romanian Society for Cell Biology, 2021, 25, 2875–2887. [crossref], [Google Scholar], [Publisher]
[18] H.A. Danesh, Focus on Medical Sciences Journal, 2018, 4 (2), 9-13. [Crossref], [Google Scholar], [Publisher]
[19] S.M. Hashemi, M.Sadeghi, A. Vahedi Tabas, S. Bouya, H.A. Danesh, A. Khazaei, A. Allahyari, International Journal of Cancer Management, 2017, 10 (12) e11463. [crossref], [Google Scholar], [Publisher]
[20] A. Sargazi, P. Kumar Nadakkavukaran Jim, H.A. Danesh, F. Sargolzaee Aval, Z. Kiani, A.H. Lashkarinia, Z. Sepehri, Bulletin of Emergency & Trauma, 2016, 4 (1), 43-47. [crossref], [Google Scholar], [Publisher]
[21] S.M. Hashemi, M. Sadeghi, A.V. Tabas, S. Bouya, H.A. Danesh, HA Khazaei, A. Allahyari, Health Sciences, 2016, 5 (9S), 662-666, [crossref], [Google Scholar], [Publisher]
[22] H.A. Danesh, M. Saboury, A. Sabzi, M. Saboury, M. Jafary, S. Saboury, Medical Journal of The Islamic Republic of Iran (MJIRI), 2015, 29 (1), 105-109, [crossref], [Google Scholar], [Publisher]
[23] H.A. Danesh, M. Saboury, A. Sabzi, M. Saboury, M. Jafary, S. Saboury, Medical journal of the Islamic Republic of Iran, 2015, 29, 172- 176. [crossref], [Google Scholar], [Publisher]
[24]T.A. Izadi, A. Borjali, A. Delavar, H. Eskandari, Danesh-e-Entezami, 2009, 11 (344), 182-207. [crossref], [Google Scholar], [Publisher]
[25] A. Bozorgian, S. Zarinabadi, A. Samimi, Journal of Chemical Reviews, 2020, 2, 122-129. [crossref], [Google Scholar], [Publisher]
[26] N. Kayedi, A. Samimi, M. Asgari Bajgirani, A. Bozorgian, South African Journal of Chemical Engineering, 2021, 35, 153-158. [crossref], [Google Scholar], [Publisher]
[27] S.M.S. Mirnezami, F. Zare Kazemabadi, A. Heydarinasab, Progress in Chemical and Biochemical Research, 2021, 4, 191-206. [crossref], [Google Scholar], [Publisher]
[28] F. Zare Kazemabadi, A. Heydarinasab, A. Akbarzadehkhiyavi, M. Ardjmand, Chemical Methodologies, 2021, 5, 135-152. [crossref], [Google Scholar], [Publisher]
[29] F. Zare Kazemabadi, A. Heydarinasab, A. Akbarzadeh, M. Ardjmand, Artificial cells, nanomedicine, and biotechnology, 2019, 47, 3222-3230. [crossref], [Google Scholar], [Publisher]
[30] F. Miryousefiata, S Sangy, Journal of Medicinal and Chemical Sciences, 2021, 4, 60-74. [crossref], [Google Scholar], [Publisher]
[31] S. Sangy, F. Miryousefiata, A. Bahaoddini, H. Dimiati, Budapest International Research in Exact Sciences (BirEx) Journal, 2020, 2(4), 458-466. [crossref], [Google Scholar], [Publisher]
[32] Alireza Bozorgian, Journal of Engineering in Industrial Research, 2020, 1, 1-18. [crossref], [Google Scholar], [Publisher]
[33] F. Rebout, Journal of Engineering in Industrial Research, 2020, 1, 19-37 [crossref], [Google Scholar], [Publisher]
[34] K.L. Han, Journal of Engineering in Industrial Research, 2020, 1, 38-50. [crossref], [Google Scholar], [Publisher]
[35] F. Gharekhani Kasa, Journal of Engineering in Industrial Research, 2020, 1, 51-74. [crossref], [Google Scholar], [Publisher]
[36] M. Zbuzant, Journal of Engineering in Industrial Research, 2020, 1, 75-81. [crossref], [Google Scholar], [Publisher]
[37] M. Amirikoshkeki, Journal of Engineering in Industrial Research, 2020, 1, 82-90. [crossref], [Google Scholar], [Publisher]
[38] M. Amini Sadrodin, Journal of Engineering in Industrial Research, 2020, 1, 91-98. [crossref], [Google Scholar], [Publisher]
[39] E. Amouzad Mahdiraji; M. Sedghi Amiri, Journal of Engineering in Industrial Research, 2020, 1, 111-122. [crossref], [Google Scholar], [Publisher]
[40]  K.L. Han, Journal of Engineering in Industrial Research, 2020, 1, 123-133. [crossref], [Google Scholar], [Publisher]
[41] A. Ahmad, A.S. Reyazi, Journal of Engineering in Industrial Research, 2020, 1, 134-160. [crossref], [Google Scholar], [Publisher]
[42]  B. Barmasi, Journal of Engineering in Industrial Research, 2020, 1, 161-169. [crossref], [Google Scholar], [Publisher]
[43] M. Amirikoshkeki, Journal of Engineering in Industrial Research, 2020, 1, 170-178. [crossref], [Google Scholar], [Publisher]
[44] M. Bagherisadr, Journal of Engineering in Industrial Research, 2020, 1, 179-185. [crossref], [Google Scholar], [Publisher]
[45] H.R.A. Otaghvar, M. Hoseini, A. Mirmalek, H. Ahmari, F. Arab, N. Amiri Mohtasham, Iranian Journal of Surgery, 2014, 22, 1-11. [crossref], [Google Scholar], [Publisher]
[46] M. Zargar, H.R.A. Otaghvar, A. Danaei, M. Babaei, Razi Journal of Medicinal Science, 2017, 24, 88-98. [crossref], [Google Scholar], [Publisher]
[47] H.R.A. Otaghvar, M. Hosseini, G. Shabestanipour, A. Tizmaghz, G. Sedehi Esfahani, Case reports in surgery, 2014. [crossref], [Google Scholar], [Publisher]
[48]  M. Rohani, H.R.B. Baradaran, A. Sanagoo, M. Sarani, S. Yazdani, H.R. Alizadeh, Razi journal of medical sciences, 2016, 23, 115-124. [crossref], [Google Scholar], [Publisher]
[49]  M. Hosseini, H.R.A. Otaghvar, A. Tizmaghz, G. Shabestanipour, S. Arvaneh, Medical journal of the Islamic Republic of Iran, 2015, 29, 239. [crossref], [Google Scholar], [Publisher]
[50]  M. Hosseini, A. Tizmaghz, H.R.A. Otaghvar, M. Shams, Advances in Surgical Sciences, 2014, 2, 5-8. [crossref], [Google Scholar], [Publisher]
[51] S.A. Mirmalek, F. Tirgari, H.R. Alizadeh, Iranian Journal of Surgery, 2005, 13, 48-54. [crossref], [Google Scholar], [Publisher]
[52] H.A. Danesh, S. Javanbakht, M. Nourallahzadeh, N.M. Bakhshani, S. Danesh, F. Nourallahzadeh, F. Rezaei, H.R.A. Otaghour, International Journal of High Risk Behaviors and Addiction, 2019, 8, e66232. [crossref], [Google Scholar], [Publisher]
[53]  A. Rouientan, H.A. Otaghvar, H. Mahmoudvand, A. Tizmaghz, World journal of plastic surgery, 2019, 8, 116. [crossref], [Google Scholar], [Publisher]
[54] S.E. Hassanpour, M. Abbasnezhad, H.R.A. Otaghvar, A. Tizmaghz, Plastic surgery international, 2018. [crossref], [Google Scholar], [Publisher]
[55] M. Yavari, S.E. Hassanpour, H.A. Otaghvar, H.A. Abdolrazaghi, A.R. Farhoud, Archives of Bone and Joint Surgery, 2019, 7, 258. [crossref], [Google Scholar], [Publisher]
[56]  S.E. Hasanpour, E. Rouhi Rahim Begloo, H. Jafarian, M. Aliyari, A.M. Shariati Moghadam, H. Haghani, H.R.A. Otaghvar, Journal of Client-Centered Nursing Care, 2017, 3, 223-230. [crossref], [Google Scholar], [Publisher]
[57] M. Tarahomi, H.R.A. Otaghvar, D. Shojaei, F. Goravanchi, A. Molaei, Case reports in surgery, 2016. [crossref], [Google Scholar], [Publisher]
[58] R. Seyedian, S.M. Hosseini, N. Seyyedian, S. Gharibi, N. Sepahy, S. Naserinejad, S. Ghodrati, M. Bahtouei, H.R.A. Otaghvar, A. Zare Mir akabadi, Iranian Suth Medical Journal(ISMJ), 2013, 16, 215-224. [crossref], [Google Scholar], [Publisher]
[59] M. Sarani, M. Oveisi, H. Rahimian Mashhadi, H.R.A. Otaghvar, Weed Research, 2016, 56, 50-58. [crossref], [Google Scholar], [Publisher]
[60] GH.R. Heydari, F. Hadavand, H. Maneshi, N. Moatamed, K. Vahdat, M. Fattah, H.R.A. Otaghvar, Iranian South Medical Journal, 2014, 16, 479-485. [crossref], [Google Scholar], [Publisher]
[61] M. Hosseini, A. Tizmaghz, G. Shabestanipour, A. Aein, H.R.A. Otaghvar, Annual Research & Review in Biology, 2014, 4, 4381-4388. [crossref], [Google Scholar], [Publisher]
[62] K. Ghajarzadeh, M.M. Fard, H.R.A. Otaghvar, S.H.R.Faiz, A. Dabbagh, M. Mohseni, S.S. Kashani, A.M.M. Fard, M.R. Alebouyeh, Annals of the Romanian Society for Cell Biology, 2021, 25, 2457-2465. [crossref], [Google Scholar], [Publisher]
[63] K. Ghajarzadeh, M.M. Fard, M.R. Alebouyeh, H.R.A. Otaghvar, A. Dabbagh, M. Mohseni, S.S. Kashani, A.M.M. Fard, S.H.R. Faiz, Annals of the Romanian Society for Cell Biology, 2021, 25, 2466-2484. [crossref], [Google Scholar], [Publisher]
[64] K. Ghajarzadeh, M.M. Fard, H.R.A. Otaghvar, S.H.R. Faiz, A. Dabbagh, M. Mohseni, S.S. Kashani, A.M.M. Fard, M.R. Alebouyeh, Annals of the Romanian Society for Cell Biology, 2021 25, 2449–2456. [crossref], [Google Scholar], [Publisher]
[65] M.D. Feizollah Niazi, S. Niazi, H.R.A. Otaghvar, F. Goravanchi, Res. Bul. Med. Sci., 2018, 23, 7. [crossref], [Google Scholar], [Publisher]
[66] S.M. Moosavizadeh, H.R.A. Otaghvar, M. Baghae, A. Zavari, H. Mohyeddin, H. Fattahiyan, B. Farazmand, S.M.A. Moosavizadeh, Medical journal of the Islamic Republic of Iran, 2018, 32, 99. [crossref], [Google Scholar], [Publisher]
[67] A. Tizmaghz, S. Motamed, H.A.R. Otaghvar, F. Niazi, S.M. Moosavizadeh, B. Motaghedi, J. Clin. Diagn. Res., 2017, 11, PC05-PC07. [crossref], [Google Scholar], [Publisher]
[68] M.R. Guity, H.R.A. Otaghvar, M. Tavakolli, A.R. Farhoud, J Orthop Spine Trauma, 2016, 2. [crossref], [Google Scholar], [Publisher]
[69] H.R.A. Otaghvar, P. Soleymanzadeh, M. Hosseini, S. Karbalaei-Esmaeili, Journal of Cancer Research and Therapeutics, 2015, 11, 655. [crossref], [Google Scholar], [Publisher]
[70] H.R.A. Otaghvar, M. Baniahmad, A.M. Pashazadeh, I.Nabipour, H. Javadi, L. Rezaei, M. Assadi, Iranian Journal of Nuclear Medicine, 2014, 22, 7-10. [crossref], [Google Scholar], [Publisher]
[71] M. Hajilou, H.R.A. Otaghvar, S. Mirmalek, F. Yosefi, S. Khazrai, N. Tahery, M. Jafari, Iranian Journal of Surgery, 2013, 21, 0-0 [crossref], [Google Scholar], [Publisher]
[72] H.R.A. Otaghvar, S. Firoozbakht, S. Montazeri, S. Khazraie, M. Bani Ahmad, M. Hajiloo, ISMJ, 2011, 14, 134-139. [crossref], [Google Scholar], [Publisher]
[73] H.R.A. Otaghvar, K. Afsordeh, M. Hosseini, N. Mazhari, M. Dousti, Journal of Surgery and Trauma, 2020, 8, 156-160. [crossref], [Google Scholar], [Publisher]
[74] I.M. Zeidi, H. Morshedi, H.R.A. Otaghvar, Journal of Preventive Medicine and Hygiene, 2020, 61, E601. [crossref], [Google Scholar], [Publisher]