Wali Khulmi HEALTH BEHAVIOUR OF FOREIGN STUDENTS AT LITHUANIAN UNIVERSITY OF HEALTH SCIENCES

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LITHUANIAN UNIVERSITY OF HEALTH SCIENCES

Medical Academy

Faculty of Public Health

Department of Preventive Medicine

Wali Khulmi

HEALTH BEHAVIOUR OF FOREIGN STUDENTS AT

LITHUANIAN UNIVERSITY OF HEALTH SCIENCES

Master Thesis

Thesis Supervisor: Prof. Dr. Linas Šumskas

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TABLE OF CONTENT

1. SUMMARY ... 2 2. ACKNOWLEDGEMENTS ... 3 3. CONFLICTS OF INTEREST ... 3

4. ETHICS COMMITTEE APPROVAL ... 3

5. ABBREVIATION LIST ... 4

6. TERMS ... 5

7. INTRODUCTION ... 6

8. AIM AND OBJECTIVES... 7

9. LITERATURE REVIEW ... 8

9.1 SIGNIFICANCE OF HEALTH AMONG STUDENTS ... 8

9.2 COPING MECHANISM TO DISTRESS AMONG STUDENTS ... 9

9.3 PHYSICAL ACTIVITY AND NUTRITIONAL HABITS OF STUDENTS ... 10

9.4 SENSE OF COHERENCE ... 11

10. RESEARCH METHODOLOGY & METHODS ... 13

9.5 SAMPLING ... 13 9.6 DATA COLLECTION ... 13 9.7 QUESTIONNAIRE ... 13 9.8 ANALYSIS ... 14 11. RESULTS ... 15 11.1 SOCIO-DEMOGRAPHIC DATA ... 15 11.2 PHYSICAL ACTIVITY ... 16

11.3 SUBSTANCE ABUSE AND GAMBLING ... 18

11.4 EATING AND DRINKING HABITS ... 23

11.5 SLEEPING HABITS ... 28 11.6 GENERAL HEALTH ... 29 11.7 SENSE OF COHERENCE ... 33 12. DISCUSSION ... 44 13. CONCLUSIONS ... 46 14. RECOMMENDATIONS ... 47 15. LITERATURE LIST ... 48 16. ANNEXES ... 51

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1. SUMMARY

Khulmi W. Health behaviour of foreign at Lithuanian university of health sciences: Master thesis /Supervisor prof. L. Šumskas, Department of Preventive Medicine, Medical Academy, Lithuanian University of health Sciences. – Kaunas, 2021. – 51 p.

Aim of the study: To get better insights into the health behaviour and wellbeing of foreign students at

Lithuanian University of Health Sciences

Objectives: 1. To evaluate the profile of lifestyle in LSMU students by gender and cultural origin.

2. To compare the profile of Sense of coherence in LSMU by gender and cultural origin.

Methods: The cross-sectional survey with a self-composed questionnaire was performed. 214

international students of the Lithuanian University of Health Sciences responded to the survey, of which 207 were selected as compliant for the further analysis of the data. A statistical data analysis and interpretation was performed using IBM SPSS 26, Excel statistical packages. Chi square were used to analyze the data by assessing and comparing results by gender and by cultural origin. The statistically significant differences were established when p-value was <0.05.

Results: 66 (31.9%) of the survey respondents were male and 141 (68.1%) females. 113 (54.6%)

people were European origin, 51(24.6%) people Asians, 15 (7.2%) Africans, 24(11.6%) from Middle East. Across the sample of students 35(16.9%) people were in their 1st year of studies, 41(19.8%) people were in their 2nd_{year, 42(20.3%) people were in their 3}rd_{year, 38(18.4%) people were in their} 4th year, 29(14%) people were in 5th year and finally 22(10.6%) people were in their 6th year. Perceived health was evaluated: 170 (82.9%) of the students reported they didn’t suffer from any kind of illness. 2 (1.0%) of the respondents reported some both mental and physical illness, 16 (7.8%) - mental illness, 17 (8.3%) - physical illness. 54.2% of students reported that they did not seek medical care. Significant proportion of students were exposed to unbalanced dietary practices -more than one third of students (37,9 %) used to eat breakfast not on every day basis. Current smoking was reported by 31.8% of male and 17.8% of female students, p<0.05) In addition, among them 19.7% of males, 10.8% of females were everyday smokers. Some proportion of students used alcohol every week or several times a week (19.7% of males and 16,0% of females). When asked about change in body weight, 88 (42.5%) students responded they have gained weight, 48 (23.2%) respondents reported they have lost weight and 71(34.3%) students responded that they didn’t observe any change in their weight throughout their study period. Statistical analysis revealed that Sense of Coherence had a significant relationship with gender resulting in females scored higher than males.

Conclusion: A statistical significance was established between exercising habits and cultural origins

among European origin (p <0.05). A relation between gender and drug use is found where (p<0.05). Regarding alcohol consumption, a statistical significance has been demonstrated among cultures revealing a higher drinking culture among European students (p<0.05). It was noted that females had a clearer sense of coherence of goals in the domain of Meaningfulness than males (p <0.05).

Keyword: foreign students, self-rated health, health behaviour, nutritional habits, smoking, alcohol,

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2. ACKNOWLEDGEMENTS

I would first like to thank my supervisor Prof. dr. Linas Šumskas of the Faculty of Public Health, Department of Preventive Medicine at Lithuanian University of Health Sciences.

Prof. dr. Šumskas allowed me to work independently, nevertheless he steered me in the right direction whenever he thought there was a need for it. He was available every-time I ran into trouble or had questions.

I would also like to thank all the international students of Lithuanian University of Health Sciences for taking part in the survey. Last but not least, a big thank and show of gratitude to my family, especially my wife for all the encouragement and support throughout the process of this journey.

Author Wali Khulmi

3. CONFLICTS OF INTEREST

The author declares no conflicts of interest.

4. ETHICS COMMITTEE APPROVAL

The Bioethics Centre of Lithuanian University of Health Sciences, approved after assessing approved the documents submitted by Mr. Wali Khulmi, the students research work with the title of “Health behaviour of foreign students at Lithuanian University of Health Sciences” and with the case-number: BEC-MF-281. Issued on the 9th_{of March 2021.}

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5. ABBREVIATION LIST

LSMU Lithuanian University of Health Sciences

SOC Sense of Coherence

HPLP Health promoting lifestyle profile WHO World Health Organisation

GBD The Global Burden of Diseases, Injuries, and Risk Factors Study BMI Body mass index

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6. TERMS

Sense of Coherence

Theory of Salutogenesis is the concept on the origins and determinants of health rather than biomedical concept of pathogenesis. It was constructed by Mr. Antonovsky (1979, 1987) and it centers around reinforcing individual and social assets that secure and effectively advance wellbeing. Salutogenesis is taking aspects in establishing intelligible living conditions, reinforcing socio-natural wellbeing assets just as Sense of coherence individually and in groups. While promotion of health is vital for the promotion of Salutogenesis, it advises exploration and practice in territories as assorted as education, strategy, organisation and community development. The term Salutogenesis is regularly connected with three unique implications, which are unmistakable however inseparably entwined. 1. The salutogenic model:

The model, depicted in detail in Antonovsky's 1979 book "Health, Stress and Coping", sets that beneficial encounters help shape one's feeling of soundness and a solid feeling of intelligence assists one with activating general opposition assets to adapt to stressors and oversee pressure effectively. Through this system, the feeling of soundness decides one's development on the wellbeing Ease/Dis-ease continuum.

2. Salutogenesis and the Sense of Coherence:

Salutogenesis is compared with one piece of the model, Sense of Coherence, explained as a such core the idea: “...a global orientation that expresses the extent to which one has a pervasive, enduring though dynamic feeling of confidence that one’s internal and external environments are predictable and that there is a high probability that things will work out as well as can reasonably be expected.” (Antonovsky, 1979, p. 123).

3. The salutogenic orientation:

In broad aspect, Salutogenesis alludes to an insightful direction zeroing in consideration on the investigation of assets and resources for wellbeing prompting positive wellbeing, corresponding to the pathogenic direction that is worried about hazard factors prompting specific disease outcome [1]

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7. INTRODUCTION

In this thesis research work the importance of understanding the health behaviour of students at LSMU, its causes and consequences are analysed. In detail the profile of lifestyle in LSMU students, the Sense of coherence by gender and cultural origin, as well as the statistical relation between the positive lifestyle of students and the Sense of coherence is studied. Recent Studies have shown that mental and physical health problems among students have been reported to be continuously increasing [2,3]. The lifestyle changes are the cause of a decline in health, especially in university settings where students are under constant pressure and with little own time to and skills to adopt healthy habits. Health behaviours are directly linked to multiple and serious diseases like high blood pressure, cardiovascular diseases etc.

Lifestyle is a way used by people, groups and nations and is formed in specific geographical, economic, political, cultural and religious text. Lifestyle refers to the characteristics of inhabitants of a region in special time and place. Millions of people follow an unhealthy lifestyle. Hence, they encounter illness, disability and even death [4]. There are also regional and cultural factors that may influence health related behaviours. More developed parts of the world with better access to healthcare and better socioeconomic situation and are generally more aware of health behaviours in comparison to less developed areas of the world.

Preventive medicine is encountering these poor lifestyle choices by shedding light on the stigmatized subjects of health issues, its causes and the preventive measures. It aims at reducing the risk of exposure and enhancing the coping mechanisms.

In LSMU, there are students from all over the world with different geographical, socioeconomic, cultural, family and religious backgrounds. They come with different levels of life experience and thus as a result have different stress coping mechanisms. SOC reflects a coping capacity of people to deal with everyday life stressors and consists of three elements: comprehensibility, manageability and meaningfulness [5]. This study would not only help give us an insight regarding but would also be a stepping in the right direction to better cope through the health crises in general.

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8. AIM AND OBJECTIVES

8.1 Aim

To get better insights into the health behaviour and wellbeing of foreign students at Lithuanian University of Health Sciences

8.2 Objectives

1. To evaluate the profile of lifestyle in LSMU students by gender and cultural origin. 2. To compare the profile of Sense of coherence in LSMU by gender and cultural origin.

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9. LITERATURE REVIEW

9.1 Significance of health among students

According to appraisal of Global Burden of Diseases GBD, only in 2019 the major hazard risk-factor and cause of non-communicable diseases worldwide were high blood pressure and tobacco (both usage and second-hand exposure) with a death toll of 10.80 and 8.71 million at first and second place respectively. Other hazards associated with high number of deaths beside high blood pressure and tobacco are poor dietary-habits such as low intake in fruits and high levels of salt (7.94 million death), high level of blood sugar (6.5 million death), high BMI (5.02 million death), high LDL (2.44 million death) and alcohol (2.44 million death) among others.

Even though there is an incline in the hazards mentioned above, yet we are neglecting to change our behaviour, specifically in relation to poor nutritional habits such as fat- and calorie-rich diet and lack of physical activity. On the broader aspect strategies should be adapted to reduce the risk factors. For example, alcohol and tobacco consumption should be controlled through regulations and taxation. [6] As indicated by World Health Organisation (WHO), 60% of related elements to singular wellbeing and personal satisfaction are connected to a life style. Issues like GIT-infections, joint and skeletal issues, cardio-vascular sickness, overweight, savagery, etcetera, can be brought about by an unfortunate way of life. The relationship of lifestyle and wellbeing ought to be profoundly significant.

Stress, hunger and poor or unbalanced diet, smoking, alcohol consumption, misuse of drugs, etc., are the symptoms of an undesirable way of life that are becoming a dominating factor. Consequently, lifestyle affects physical and psychological wellness of a person. There are various types of such impacts. Incorporating everyday practices and elements of individuals’ everyday life such as studies, work, exercise, diet is among other factors with a big impact on the general wellbeing of life and its quality is correlated to health.

Alongside sound eating regimen, good physique, sleep has to be included as the bases of healthy life and has been proven to have an increased impact on health. If otherwise, it may affect social, psychological and have consequences on general physical health [4].

As it has been given more attention to stress issues and quality of life of students, a study done by the Manipal College of Medical Sciences in Pokhara assessed ‘the prevalence of psychological morbidly,

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sources and severity of stress and coping strategies’, showed that 20.9% of the participates (of total

525 students) had elevated mental dreariness [7].

Another major study conducted with a pool of over 64 thousand students both medical and non-medical - indicating that depression is highest among first year students of medicine with a rate of 33.5 percentage in first year and gradually decreasing to 20.5 percentile in year five of medical studies. Consequently, it also showed that the notion of suicide reaching 5.8 percentile and the proportion seeking for help only amount for 12.9 percentile [8].

Therefore, the studies [1-3] amplify the importance of educational institutes as well as health authorities in recognizing early alarming signs of depression and offer intercessions like social and mental help to decrease stress and improve the personal satisfaction and environment for these students.

9.2 Coping mechanism to distress among students

We are already aware that medical schools and other healthcare related institutions are the cause of challenges and stress. Students react differently to it. In the university of Alberta, Canada, a study analyzes the relation between motivational factors, stress, exhaustion and extensive learning among medical students. A total of 267 medical students participated and the results largely affirmed the conjectured relations, uncovering that neglected mental necessities and a fixed attitude were related with maladaptive discernments and mental pain [9].

High levels of stress may cause adverse psychological symptoms and use dysfunctional coping mechanisms. In University of Otago the levels, sources of stress, anger, anxiety and sadness, and associated coping mechanisms among dental and medical students were investigated. About 58.6 percent reported they frequently feel stressed. A high correlation between high levels of stress and poor quality of sleep were found. It was even more obvious among those with lower than average performance in their respective field of study [10].

The dentistry students felt more stressed compared to medical students but the majority of medical students were worse at coping with the stress and suffered more from anxiety, depressed mood and anger [11].

Stress among students within the healthcare system is seen as a typical inclination but in the long run it will eventually weaken and erode the student's mental as well as physical health. As a counterforce the students have developed different mechanisms of coping with it.

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Some mentioned their coping strategies as building relationships with people in the same field, avoiding talking about the topic, smoking, drinking while others cope with it by taking part in community therapy, music therapy, drawing, yoga and physical activity, cognitive reconstructing, among many other things [12-13].

Healthcare students do have trouble with stress-coping strategies. The existing studies prove that there is a stigma when it comes to mental health and thus a great need for stress management techniques programs.

The stress and its cofactors are diverse and therefore its management strategies should also be diversified. There is room for further research. There is a need to set up an emotional well-being supportive network that can address the need of everyone. State funded instruction on adapting systems and stress the board might be useful [14-16].

9.3 Physical activity and nutritional habits of students

In the 21st century diseases such as obesity, diabetes and cardiovascular illnesses cause major health issues and it can be reduced to education and nutritional habits. A study was conducted among healthcare institutes in the Polish University of Silesia aiming to assess dietary habits and its adverse effects in combination with healthcare measures such as physical activities.

The result was that one quarter of all the participated students skipped breakfast. Less than a third consumed fruits/vegetables and forty percent drank sweet beverages on a daily basis and 45.6 percent nibbled between main meals. It’s also mentioned that almost a third of the students consume food prior bedtime. Despite these values, the majority of the students evaluated themselves as having a sound healthy lifestyle. Majority of students, despite understanding the significance that an appropriate eating routine and sufficient degrees of physical activity impacts on wellbeing, didn't put the theory into practice [17].

In the Lithuanian University of Sports in Kaunas a study with the aim to investigate the correlation of social capital and Mediterranean diet among adolescents using Mediterranean Diet Quality index in children and adolescents was performed. Alongside social capital factors such as physical activity, body mass index were taken into consideration for the investigation. The study examined that having encouragement from family and teaching institutes improves ones’ dietary consumption of healthier nutrients.

The study revealed females being more aware about their dietary habits while the proportion of males tend to be more physically active while simultaneously having a higher BMI in comparison to females.

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Those who received support from the surrounding environment tended to minimize skipping breakfast and the utilization of natural products, fruits/vegetables, grains, sea products etc. were higher [18].

Another study was conducted to evaluate nutritional habits of students. It aimed to identify bad nutritional habits and food addiction among nutrition-conscious and non-nutrition conscious students and analyze dietary related issues and other eating disorders. The overweight participants were at a higher risk of developing bad nutritional habits. About 10.3 percent of the participants met the criteria of food addiction while 10 percent had high concerns about developing bad dietary habits. In order to combat this an early screening promoting healthy dietary education and help are potentials to improve the nutritional habits [19].

Nutritional education has a significant importance in human wellbeing as it prevents diseases and is also used in therapy. Medical and other healthcare students are relied on to advise patients about nutrition however studies show that there is a need of improvement in students’ curriculum in spite of the centrality of sustenance to sound lifestyle the students in the healthcare profession are not upheld to give superior and compelling nourishment care [20-22].

Some institutes provide nutritional classes for their clinical educational program and yet some doctors still are lacking the skill in advising and giving nutrient care. Filling the gaps of knowledge requires further contribution, collaboration, arrangement and encouragement in educational programs which would upgrade the nourishment training for future doctors.

Overall, medical students and physicians agreed that the nutrition education currently provided in medical school is inadequate. In general, it is agreed upon that in the current situation nutritional education needs improvements [22-24].

9.4 Sense of coherence

With advancement in knowledge about wellbeing and quality of life among the general population – the health professionals are looking for the determinants of individual health practices. A study was carried out in Chandigarh to investigate the participants’ health behaviours, SOC and to check the factors of promoting those behaviours. The SOC and HPLP were used. The study showed a difference in relation to gender. The female participants were generally more aware about quality of life and cared more about their health in comparison to their counterparts. The females additionally consulted physicians more and took better care of their hygiene. The males on the other hand were more physically active. However, all in all, they all had a decent health promoting lifestyle and good SOC [25].

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Another study done in Sweden wanted to check the ‘self-related health in relation to SOC and other personality traits’, despite the fact that the mean SOC score was comparable for both sexes the investigation showed a positive relationship between self- rated wellbeing and SOC mainly among the female university students. But it likewise showed a less fortunate wellbeing among the two sexes in the event if they had type A personality trait.

As the relationships were solid between SOC and the correlated measures to it, it is hard to reach any determinations about what really impacts wellbeing thus need further evaluation [26].

A three-years of follow-up study performed among polytechnic students of Finland where the relationship between SOC and alcohol consumption, smoking and physical activities were taken into consideration showed that the SOC was highest in the beginning of the studies for all participating students. The results were indicating a high level of coping with stress among the students.

The role of being physically active several times a week was found to have significance in a high SOC and the opposite was true among those being physically inactive. Also the SOC decreased slightly at the end of the three-year up, specifically among healthcare students of the three-year follow-up. But there was no affiliation found between high SOC and smoking and drinking [27].

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10. RESEARCH METHODOLOGY & METHODS

9.5 Sampling

The data was collected from a sample of around 214 international students from the LSMU. However, in the end only the data of 207 participants was included in the study, due to incomplete answering of the questionnaire. People across various national backgrounds of both genders were included in order to study lifestyle and SOC and the relation between a positive lifestyle and SOC.

9.6 Data collection

The data was collected using a self-composed online questionnaire and the Sense of Coherence Short Version (SOC-13), which was sent to all foreign students using the university E-mail network. It was explained to the students that participation is voluntarily and anonymously. Neither was the personal data collected nor saved. Furthermore, it was stated that any questions regarding the questionnaire would be answered by the author. Only the surveys from students giving their consent for it to be used for scientific research were included.

9.7 Questionnaire

The self-composed questionnaire contained questions about the following topics: socio-demographic data, perceived health, physical activity, substance abuse, experiences of communicating within the locals in Lithuania, eating and drinking habits, sleeping habits, and SOC.

The Sense of Coherence Short Version (SOC-13) questionnaire was also used. This research tool was developed by Aaron Antonovsky and is based on the Theory of Salutogenesis (Antonovsky, 1987). It consists of 13 items rated on a 7-point Likert scale. In addition to the SOC-13 total scale, it has three subscales and evaluates the Meaningfulness (4 items), Comprehensibility (5 items), and Manageability (4 items). The psychometric properties of the SOC-13 have primarily been evaluated with classical statistical methods in the general populations of students, which showed high reliability (Cronbach’s alpha reliability of p= 0.76) [28].

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9.8 Analysis

Statistical package IBM SPSS 26 was used to analyse the data by assessing and comparing results by gender and by cultural background. Chi square test was used to analyse the data and statistically significant differences were established when p-value was <0.05. The codification of SOC13 was used to measure the three main elements (comprehensibility, manageability and meaningfulness) of SOC.

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11. RESULTS

11.1 Socio-demographic data

The samples included 66 (31.9%) males and 141 (68.1%) females of whom 113 (54.6%) people were Europeans, 51(24.6%) people were Asians, 15 (7.2%) were Africans and 24(11.6%) belonged to the Middle East.

Figure 1: Prevalence of the Socio-Economic backgrounds of the students (%)

On their socio-economic status 33 (15.9%) people responded they were not very well off, 1 (0.5%) people responded they were quite poor. 149(72%) people responded that they were quite well off and 24(11.6%) people responded that they belonged to a wealthy family background.

On self-rated academic performance 17(8.2%) people reported they were excellent in studies, 82(39.6%) people reported they were good, 2(1%) people reported their academic performance was not satisfactory, 14(6.9%) people reported their academic performance was satisfactory and 92(44.4%) people reported that it was good.

Across our sample of students 35(16.9%) people were in their 1st year, 41(19.8%) people were in their 2nd year, 42(20.3%) people were in their 3rd year, 38(18.4%) people were in their 4th year, 29(14%) people were in 5th year and finally 22(10.6%) people were in their 6th year.

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11.2 Physical activity

The general health behaviours regarding physical activity across regions and across gender was investigated.

Table 1. Profile of involvement of students in different sport activities by the region of origin (%)

European

% (n) Asian % (n) African % (n) Middle Eastern % (n) Total % (n)

Jogging 12.2% (14) 3.9% (2) 6.3% (1) 0.0%(0) 8.3% (17)

Not Active 13.9% (16) 9.8% (5) 0.0% (0) 25.0% (6) 13.1% (27)

Sports (dancing,

swimming, football etc.) 5.2% (6) 11.8% (6) 6.3%(1) 4.2% (1) 6.8% (14)

Walking 8.7% (10) 2.0% (1) 25.0% (4) 4.2% (1) 7.7% (16)

Workout/Gym 59.1% (68) 72.5% (37) 62.4% (10) 62.4% (15) 63.1% (130)

Yoga 0.9% (1) 0% (0) 0.0% (0) 4.2% (1) 1.0% (2)

Total 100% (115) 100% (51) 100% (16) 100% (24) (206)

Statistical Significance χ2= 26.1, df = 15, p = 0.037

The choices of mode of exercise were significantly different (p<0.05) among the participants across regions.

Table 2. Prevalence in choice of exercise across gender

Jogging Not Active Sports Walking Gym

Workout Yoga Total % (n) Male % (n) 11.8% (2) 37.0% (10) 35.7% (5) 25.0%(4) 34.6%(45) 0.0%(0) (66) Female % (n) 88.2(15) 63.0%(17) 64.3% (9) 75.0% (12) 65.4% (85) 100.0% (2) (140) Total % (n) 100% (17) 100%(27) 100% (14) 100% (16) 100% (130) 100%(2) 100% (206) Statistical Significance χ2 = 5.30, df = 5, p= 0.38

The choices of mode of exercise were not significantly different p>0.05 among the participants across gender.

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Figure 2. Distribution of answers about self-rated weight among foreign students of LSMU (%)

With regards to self-rated weight among foreign students of LSMU, 146 (70.5%) people reported they were of normal weight, 5(2.4%) people categorized themselves under the category of obese, 34(16.4%) people reported as being overweight and 22(10.6%) reported as underweight. When asked about changes in their weight during the study period, 88(42.5%) people responded they have gained weight, 48(23.2%) people responded they have lost weight and 71(34.3%) people responded that they didn’t observe any change in their weight throughout their study period.

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Comparison between health related habits across culture and across gender:

Results revealed some of the significant differences which are described as follows:

*p<0.05 when comparing European and other cultural origins

Figure 3. Prevalence of exercising habits across cultures (%)

Figure 3 reveals that Europeans are more likely to indulge in workout and gym as their choice of exercising. While doing the statistical analysis P value was found to be 0,037 (<0,05), showing statistical significance between exercising habits and cultures.

11.3 Substance abuse and gambling

Table 3. Prevalence of smoking distribution habits across cultures (%)

European % (n) Asian % (n) African % (n) Middle Eastern % (n) Total % (n)

1 – 5 cigarettes per day 3.5% (4) 5.9% (3) 0.0% (0) 0.0% (0) 3.4% (7)

Less than 1 cigarettes per day 2.7% (3) 5.9% (3) 6.3% (1) 4.2% (1) 4.0 % (8) Less than 1 cigarettes per week 9.6% (11) 7.8% (4) 0.0% (0) 8.3% (2) 8.3% (17)

None at all 77.2% (88) 78.4% (40) 87.4% (14) 75.0% (18) 78.0% (160) Total % (n) 100%(114) 100%(51) 100% (16) 100% (24) 100% (205) Statistical Significance χ2 _{= 10.8, df = 18, p= 0.90} 6,8 7,8 2,9 4,9 33,0* 0,5 1,0 2,4 2,9 _0,5 18,0 0,0 0,5 _0,0 0,5 1,9 4,9 0,0 0,0 2,9 0,5 0,5 7,3 0,5 0,0 5,0 10,0 15,0 20,0 25,0 30,0 35,0

Jogging Not Active Sports Walking Workout/Gym Yoga

(%)

Physical Activity

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The smoking habits were significantly different (p<0.05) among the participants across genders – 31.2% of males and 17,3 %of females have reported smoking on a weekly basis.

Table 4. Prevalence of smoking habits distribution across gender (%)

1– 5 cigarettes per day 11 – 20 cigarettes per day 6 – 10 cigarettes per day Less than 1 cigarettes per day Less than 1 cigarettes per week None at all Total % (n) Male % (n) 14.3% (1) 57.1% (4) 66.7% (4) 50.0% (4) 47.0% (8) 28.2% (45) 32.2%(66) Female % (n) 85.7% (6) 42.9% (3) 33.3% (2) 50.0% (4) 53.0% (9) 71.8% (115) 67.8% (139) Total % (n) 100% (7) 100% (7) 100% (6) 100% (8) 100% (17) 100% (160) 100% (205) Statistical Significance χ2= 10.9, df = 6, p = 0.042

The smoking habits were not significantly different (p>0.05) among the participants across cultures.

Table 5. Prevalence of substance use across culture (%) European % (n) Asian % (n) African % (n) Middle Eastern % (n) Total % (n) Cannabis 50% (11) 13.7% (7) 18.7% (3) 16.7% (4) 22.1% (25) Combination drugs 18.2% (4) 7.8% (4) 0.0% (0) 0.0% (0) 7.1% (8) Ecstasy 18.2% (4) 0.0% (0) 0.0% (0) 0.0% (0) 3.5% (4) None 13.6% (3) 78.5% (40) 81.3% (13) 83.3% (20) 67.3% (76) Total % (n) 100% (22) 100% (51) 100% (16) 100% (24) 100% (113) Statistical significance χ2= 5.87, df = 9, p= 0.75

The substance use was not significantly different (p>0.05) among the participants across cultures.

Table 6. Prevalence of substance use across gender (%)

Cannabis Combination Drugs Ecstasy None Total % (n)

Male % (n) 32% (8) 77.8% (7) 0.0% (0) 29.8% (51) 32.0% (66) Female % (n) 68% (17) 22.2% (2) 100% (1) 70.2% (120) 68% (140) Total % (n) 100% (25) 100% (9) 100% (1) 100% (171) 100% (206) Statistical Significance χ2 = 9.5, df = 3, p= 0.043

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The substance use was significantly different (p<0.05) among the participants across gender.

Table 7. Prevalence of alcohol consumption across cultures (%)

European

1-2 times per week 10.5% (12) 13.7% (7) 0.0% (0) 16.7%N = 4 11.3% (23)

2-4 times per week 4.4% (5) 2.0% (1) 0.0% (0) 8.3%N = 2 3.9% (8)

3-4 times per week 2.6% (3) 0.0% (0) 0.0% (0) 0.0% (0) 1.5% (3)

4+ times per week 0.9% (1) 0.0% (0) 0.0% (0) 0.0% (0) 0.5% (1)

Monthly 54.4% (62) 31.4% (16) 14.3% (2) 41.7% (10) 44.3% (90)

Never 27.2% (31) 52.9% (27) 85.7% (12) 33.3% (8) 38.5% (78)

Total 100%(114) 100% (51) 100% (14) 100% (24) 100% (203)

Statistical Significance χ2= 31.77, df = 18, p= 0.23

The alcohol consumption was significantly different (p<0.05) among the participants across culture.

Table 8. Prevalence of alcohol consumption across gender (%)

1-2 times per week 2-4 times per week 3-4 times per week 4+ times per week

Monthly Never Total

% (n) Male % (n) 34.8% (8) 50% (4) 33.3% (1) 0.0% (0) 24.4% (22) 39.7% (31) 32.5% (66) Female % (n) 65.2% (15) 50% (4) 66.7% (2) 100% (1) 75.6% (68) 60.3% (47) 67.5% (137) Total 100% (23) 100% (8) 100% (3) 100% (1) 100% (90) 100% (78) 100% (203) Statistical Significance χ2 = 6.18, df = 5, p= 0.29

The alcohol consumption was not significantly different (p>0.05) among the participants across genders.

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Table 9. Prevalence of cultural difference in consumption of alcohol for amusement (%)

European

Always 12.6%(11) 25.0% (8) 20.0% (1) 5.5% (1) 14.8% (21) Mostly 26.4%(23) 25.0% (8) 20.0% (1) 16.7% (3) 24.6% (35) Never 20.7%(18) 28.1% (9) 60.0% (3) 22.2% (4) 23.9% (34) Seldom 11.5%(10) 3.1% (1) 0.0% (0) 0.0% (0) 7.7% (11) Sometimes 28.8%(25) 18.8% (6) 0.0% (0) 55.6% (10) 29.0% (41) Total 100% (87) 100%(32) 100% (5) 100%(18) 100% (142) Statistical Significance χ2= 28.4, df = 15, p= 0.19

The alcohol consumption for amusement was significantly different (p<0.05) among the participants across culture.

Table 10. Prevalence of gambling behaviour across culture (%)

European % (n) Asian % (n) African % (n) Middle Eastern % (n) Total % (n) Yes 7.0%(8) 0.0% (0) 14.3% (2) 4.2% (1) 6.6% (11) No 93% (106) 100% (15) 85.7% (12) 95.8% (23) 93.4% (156) Total % (n) 100% (114) 100% (15) 100% (14) 100% (24) 100% (167) Statistical Significance χ2_{= 5.71, df = 3, p= 0.12}

The behaviour of indulging in gambling was not significantly different (p>0.05) among the participants across cultures.

Table 11. Prevalence of gambling behaviour across gender (%)

Male % (n) Female % (n) Total % (n) Yes 12.1%(8) 2.2% (3) 5.4% (11) No 87.9% (58) 97.8% (134) 94.6% (192) Total % (n) 100% (66) 100% (137) 100% (203) Statistical Significance χ2= 8.57, df = 1, p = 0.003

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Figure 4. Percentage of students who reported drug consumption by gender (%)

Figure 4 indicates that females are less likely to indulge in consuming drugs than males, however the choice of drug for females is more likely cannabis whereas males are more likely to indulge in hard drugs. While doing the statistical analysis P value was found to be 0,23 (<0,05), df= 3 and χ2 _{= 9.5, showing statistical significance between gender differences in drug use.}

Figure 5. Prevalence of alcohol consumption across culture (%)

3,9 3,4 0,0 24,8 8,3 1,0 0,5 58,3 0,0 10,0 20,0 30,0 40,0 50,0 60,0 70,0

Cannabis Combination Drugs Ecstasy None

(%) Drugs Male Female 5,9 2,5 _1,5 0,5 30,5 15,3 3,4 0,5 _0,0 _0,0 7,9 13,3 0,0 0,0 0,0 0,0 1,0 5,9 2,0 _1,0 0,0 0,0 4,9 _3,9 0,0 5,0 10,0 15,0 20,0 25,0 30,0 35,0 1-2 times per week 2-4 times per week 3-4 times per week 4+ times per week Monthly Never (%) Alcohol Usage

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Figure 5 reveals that Middle Eastern countries are very less likely to consume alcohol. The statistical analysis show that alcohol consumption was significantly different χ2 (18, N=203) = 31.7, p < 0.05 among the participants across culture.

Figure 6. Prevalence of gambling habits across culture (%)

Figure 6 indicate that gambling habits are more frequently observed in males than in females. Our statistical analysis showed that gender differences were significant (p<0.05) when it came to gambling behaviours.

11.4 Eating and drinking habits

Table 12. Prevalence of having breakfast across culture (%)

European

Everyday 67.6% (77) 54.9% (28) 50.0% (7) 58.3% (14) 62.1% (126) Rarely 14.0% (16) 19.6% (10) 7.1% (1) 8.3% (2) 14.3% (29) Sometimes 18.4% (21) 25.5% (13) 42.9% (6) 33.4%(8) 23.6% (48) Total % (n) 100% (114) 100% (51) 100% (14) 100%(24) 100% (203) Statistical Significance χ2_{= 7.9, df = 6, p= 0.23} 3,9 28,6 1,5 66,0 0,0 10,0 20,0 30,0 40,0 50,0 60,0 70,0 Yes No (% Gambling behavior Male Females

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The dietary habits like having breakfast were not significantly different (p>0.05) among the participants across culture.

Table 13. Prevalence of having breakfast across gender (%)

Male % (n) Female % (n) Total % (n) Everyday 62.1%(41) 62.0% (85) 62.1% (126) Rarely 16.7% (11) 13.1% (18) 14.3% (29) Sometimes 21.2% (14) 24.9% (34) 23.6% (48) Total % (n) 100% (66) 100% (137) 100% (203) Statistical Significance χ2 = 0.63, df = 2, p= 0.73

The dietary habits like having breakfast was not significantly different (p>0.05) among the participants across gender.

Table 14. Prevalence of amount of meals per day across culture (%)

European % (n) Asian % (n) African % (n) Middle Eastern % (n) Total % (n) 1 Meal 8.8% (10) 7.8% (4) 21.4% (3) 16.7% (4) 10.3% (21) 2 Meals 36.8% (42) 43.2% (22) 50.0% (7) 41.7% (10) 39.9% (81) 3 Meals 51.8% (59) 47.0% (24) 28.6% (4) 33.3% (8) 46.8% (95) 3+ Meals 2.6% (3) 2.0%(1) 0.0% (0) 8.3% (2) 3.0% (6) Total % (n) 100% (114) (51) 100% (14) 100% (24) 100% (203) Statistical Significance χ2 = 9.4, df = 9, p= 0.39

The dietary habits like the number of meals per day was not significantly different (p>0.05) among the participants across cultures.

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Table 15. Prevalence in dietary habits of dairy consumption across cultures (%)

European % (n) Asian % (n) African % (n) Middle Eastern % (n) Total % (n) 2-4 days a week 16.7% (19) 4.0% (10) 13.0% (3) 29.2% (7) 18.5% (39) 5 – 6 days a week 18.4% (21) 12.0% (6) 4.3% (1) 20.8% (5) 15.6% (33)

Every day, more than once a day

26.2% (30) 20.0% (10) 13.0% (3) 12.5% (3) 21.8% (46) Every day, once a day 24.6% (28) 44.0% (22) 4.3% (1) 20.8% (5) 26.5% (56)

Less than once a week 5.3% (6) 0.0% (0) 0.0% (0) 0.0% (0) 2.8% (6)

Never 3.5% (4) 0.0% (0) 8.8% (2) 4.2% (1) 3.4% (7)

Once a week 5.3% (6) 4.0% (2) 56.6% (13) 12.5% (3) 11.4% (24)

Total % (n) 100% (114) 100% (50) 100% (23) 100% (24) 100% (211)

Statistical Significance χ2 = 21.0, df = 18, p= 0.27

The dietary habits like consumption of dairy products were not significantly different (p>0.05) among the participants across cultures.

Table 16. Profile of dairy product consumption of students by gender (%)

Male % (n) Female % (n) Total % (n) 2-6 days a week 18.5% (12) 19.9% (27) 19.4% (39) 5 – 6 days a week 20.0% (13) 14.7% (20) 16.4% (33)

Every day, more than once a day 18.5% (12) 25.0% (34) 22.9% (46)

Every day, once a day 27.7% (18) 29.4% (40) 28.9% (58)

Less than once a week 6.2% (4) 2.2% (3) 3.4% (7)

Never 1.5% (1) 2.9% (4) 2.5% (5)

Once a week 7.6% (5) 5.9% (8) 6.5% (13)

Total % (n) 100% (65) 100% (136) 100% (201)

The dietary habits like consumption of dairy products were not significantly different (p>0.05) among the participants across gender.

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Table 2. Prevalence in dietary habits of vegetable and fruit consumption across gender (%)

Never 3.1% (2) 0.7% (1) 1.5% (3)

Once a week 10.8% (7) 5.9% (8) 7.5% (15)

Total % (n) 100% (65) 100% (136) 100% (201)

The dietary habits like consumption of vegetables were not significantly different (p>0.05) among the participants across gender.

Table 18. Prevalence in dietary habits of sweet beverage consumption across culture (%)

European % (n) Asian % (n) African % (n) Middle Eastern % (n) Total % (n) 2-4 days a week 14.0% (16) 14.0% (7) 15.4% (2) 25.0% (6) 15.4%(31) 5 – 6 days a week 5.3% (6) 4.0% (2) 0.0% (0) 12.5% (3) 5.5% (11)

Every day, more than once a day 3.5% (4) 2.0% (1) 0.0% (0) 0.0% (0) 2.5% (5)

Every day, once a day 2.7% (3) 18.0% (9) 7.7% (1) 0.0% (0) 6.4% (13)

Less than once a week 28.0% (32) 14.0% (7) 38.4% (5) 25.0% (6) 24.9% (50)

Never 31.6% (36) 30.0%(15) 23.1% (3) 25.0% (6) 29.9% (60)

Once a week 14.9% (17) 18.0% (9) 15.4% (2) 12.5% (3) 15.4% (31)

Total % (n) 100% (114) 100% (50) 100% (13) 100% (24) 100% (201)

Statistical Significance χ2= 25.3, df = 18, p= 0.12

The dietary habits like consumption of fizzy drinks were not significantly different (p>0.05) among the participants across cultures.

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Table 19. Prevalence in dietary habits of sweet beverage consumption across gender (%)

Never 24.6% (16) 32.4% (44) 29.9% (60)

Once a week 15.5% (10) 15.4% (21) 15.3% (31)

Total % (n) 100% (65) 100% (136) 100% (201)

The dietary habits like consumption of fizzy drinks were not significantly different (p>0.05) among the participants across gender.

Table 20. Prevalence in dietary habits of sweet beverage consumption across culture (%)

European % (n) Asian % (n) African % (n) Middle Eastern % (n) Total % (n) Always 32.5% (37) 22.0% (11) 30.8% (4) 33.3% (8) 29.9% (60) Never 10.5% (12) 10.0%(5) 0.0% (0) 12.5% (3) 9.9% (20) Occasionally 57.0% (65) 68.0% (34) 69.2% (9) 54.2% (13) 60.2% (121) Total % (n) 100% (114) 100% (50) 100% (13) 100% (24) 100% (201) Statistical Significance χ2 = 3.90, df = 6, p= 0.69

The dietary habits like consumption of fast food were not significantly different (p>0.05) among the participants across cultures.

Table 21. Prevalence of watching out for healthy nutrition across gender (%)

Male % (n) Female % (n) Total % (n) Always 32.3% (21) 28.7% (39) 29.9% (60) Never 16.9% (11) 6.6% (9) 9.9% (20) Occasionally 50.8% (33) 64.7% (88) 60.2% (121) Total % (n) 100% (65) 100% (136) 100% (201) Statistical Significance χ2 = 6.30, df = 2, p= 0.43

The gender differences were not significant (p>0.05) when it came to watching out for healthy nutrition.

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Figure 7. Prevalence of watching out for healthy nutrition across gender (%)

Figure 7 reveals that females are more likely to watch out for what they eat than males do. The gender differences were significant (p<0.05) when it came to watching out for healthy nutrition.

11.5 Sleeping habits

Table 22. Prevalence of sleeping habits across culture (%)

European

5 – 6 hours 29.7% (34) 46.0% (23) 46.2% (6) 25.0% (6) 34.3% (69)

7 – 8 hours 47.4% (54) 42.0% (21) 46.2% (6) 58.3% (14) 47.3% (95) Less than 5 hours 7.9% (9) 4.0% (2) 0.0% (0) 12.5% (3) 7.0% (14)

8+ hours 15.0% (17) 8.0% (4) 7.6% (1) 4.2% (1) 11.4% (23)

Total % (n) 100% (114) 100% (50) 100% (13) 100% (24) 100% (201)

The sleeping habits people across origins were not significantly different (p>0.05) among the participants across cultures.

19,4 4,6 45,4 10,2 5,1 15,3 0,0 5,0 10,0 15,0 20,0 25,0 30,0 35,0 40,0 45,0 50,0

Always Never Occasionally

(%)

Watching Out for Healthy Nutrition

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Table 23. The profile of sleeping habits across gender (%)

Male % (n) Female % (n) Total % (n) 5 – 6 hours 40.0% (26) 31.6% (43) 34.3% (69) 7 – 8 hours 49.2% (32) 46.3% (63) 47.3% (95)

Less than 5 hours 6.2% (4) 7.4% (10) 7.0% (14)

8+ hours 4.6% (3) 14.7% (20) 11.4% (23)

Total % (n) 100% (65) 100% (136) 100% (201)

The sleeping habits people across genders were not significantly different (p>0.05) among the participants across cultures.

11.6 General health

Figure 8. Prevalence of diagnosed diseases across foreign students of LSMU (%)

Figure 8. Regarding student’s general health, 2 (1.0%) students reported they suffered from both, mental and physical illness, 16 (7.8%) people reported suffering from mental illness, 17 (8.3%)

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people reported they suffered from physical illness and 170 (82.9%) of the students reported they didn’t suffer from any kind of illness.

Table 24. Profile of self-reported health related problems of students by the area of origin (%)

European % (n) Asian % (n) African % (n) Middle Eastern % (n) Total % (n) Both Mental & Physical 0.0% (0) 0.0% (0) 4.8% (1) 4.8% (1) 1.0% (2)

Mental Illness 7.8% (9) 6.4% (3) 9.5% (2) 9.5% (2) 7.8% (16)

None 81.0% (94) 93.6% (44) 76.2% (16) 76.2% (16) 82.9% (170)

Physical Illness 11.2% (13) 0.0% (0) 9.5% (2) 9.5% (2) 8.3% (17)

Total % (n) 100% (116) 100% (47) 100% (21) 100% (21) 100% (205)

The general health, as in the presence of mental and physical illness was not significantly different (p>0.05) among the participants across culture.

Table 25. Prevalence of mental and physical health across gender (%)

Male % (n) Female % (n) Total % (n) Both Mental & Physical 1.5% (1) 0.7% (1) 1.0% (2)

Mental Illness 6.0% (4) 8.6% (12) 7.8% (16)

None 86.5% (57) 81.3% (113) 82.9% (170)

Physical Illness 6.0% (4) 9.4% (13) 8.3% (17)

Total % (n) 100% (66) 100% (139) 100% (205)

The general health, as in the presence of mental and physical illness was not significantly different (p>0.05) among the participants across gender.

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*- p<0.05, statistical difference between European and other “No categories

Figure 9. Prevalence of seeking medical care across culture (%)

Figure 9 indicate that the experiences of seeking medical attention during the period of study was significantly different (respectively 3.4%, 0.6%, 13.8% and 33.9 African, American, Asian and European responded “NO”. This suggests that Europeans were less likely to seek medical attention (p<0.05).

Table 26. Prevalence of seeking medical care across gender (%)

Male % (n) Female % (n) Total % (n) No 63.0% (41) 50.0% (70) 54.2% (111)

Yes, but not satisfied with the services 13.8% (9) 21.4% (30) 19.0% (39) Yes and satisfied with the services 23.2% (15) 28.6% (40) 26.8% (55)

Total % (n) 100% (65) 100% (140) 100% (205)

Seeking medical attention during the duration of the study was not significantly different

(p>0.05) among the participants across gender.

3,4 0,6 4,0 0,6 _0,0 _0,0 13,8 9,2 5,7 33,9* 10,3 18,4 0,0 5,0 10,0 15,0 20,0 25,0 30,0 35,0 40,0

No Yes but not satisfied with the

service Yes, satisfied with the service

(%)

Seeking Medical Care during Study Period

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Table 27. Frequency of experiencing headache in students in past 12 months by gender (%)

Male % (n) Female % (n) Total % (n) Every Month 24.6% (16) 30.0% (42) 28.3% (58) Every Week 18.5% (12) 17.9% (25) 18.0% (37) Once a Day 9.2% (6) 10.0% (14) 9.8% (20)

More than Once a Week 9.2% (6) 17.1% (24) 14.6% (30)

Rarely or Never 38.5% (25) 25.0% (35) 29.3% (60)

Total % (n) 100% (65) 100% (140) 100% (205)

The general health (students experiencing headache in the past 12 months) was not significantly different (p>0.05) among the participants across gender.

p<0.05 comparing frequency of abdominal pain (all categories) in males vs. female

Figure 10. Frequency of experiencing abdominal pain across gender (%)

Figure 10 shows that students experiencing abdominal pain in the past 12 months was significantly different (p<0.05) among the participants across gender.

22,4 8,2 4,6 6,1 28,1 6,6 1,5 1,5 0,0 20,9 0,0 5,0 10,0 15,0 20,0 25,0 30,0

About every month About every week About once a day More than once a week

Rarely or never

(%)

Feeling of Abdominal Pain during last 12 months

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Table 28. Frequency of experiencing abdominal pain across gender culture (%)

European

Every Month 26.7% (31) 26.4% (14) 66.7% (10) 19.0% (4) 28.8% (59)

Every Week 13.8% (16) 7.5% (4) 0.0% (0) 4.8% (1) 10.2% (21)

Once a Day 6.0% (7) 11.3% (6) 0.0% (0) 9.5% (2) 7.3% (15)

More than Once a

Week 6.0% (7) 5.7% (3) 0.0% (0) 9.5% (2) 5.9% (12)

Rarely or Never 47.5% (55) 49.1% (26) 33.3% (5) 57.2% (12) 47.8% (98)

Total % (n) 100% (116) 100% (53) 100% (15) 100% (21) 100% (205)

The general health (students experiencing Abdominal Pain in past 12 months) was not significantly different (p>0.05) among the participants across culture.

11.7 Sense of coherence

In the analysis of SOC-13, the average score among the participants was 54 points (on a scale of 13-91), out of which Meaningfulness, Comprehensibility and Manageability each being 18, 19 and 17 respectively.

SENSE OF COHERENCE, CULTURE AND GENDER

Figure 11. Prevalence of Comprehensibility (Surprised by the behaviour of People)

2,5 8,8 6,4 9,3 11,3 11,3 6,9 2,5 1,5 0,5 4,4 5,9 5,4 5,9 0,0 0,0 1,5 1,0 1,5 2,0 1,5 0,0 0,5 0,0 5,4 2,0 1,0 1,5 0,0 2,0 4,0 6,0 8,0 10,0 12,0

Always Usually Sometimes Neutral Infrequently Rarely Never

(%)

Surprised by the behavior of other people

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Figure 11 indicating that comprehensibility (Surprised by the behaviour of People), which is a part of Sense of Coherence was significantly different χ2_{(18, N=203) = 34.8 where p <0.05 among the} participants across culture. This trait tends to be found slightly lesser in Europeans as compared to other regions.

Table 29. Prevalence in Comprehensibility in SOC when asked if (surprised by the behaviour of other people) across culture

European

Always 4.3% (5) 9.4% (5) 0.0% (0) 0.0% (0) 4.9% (10) Usually 15.7% (18) 5.7% (3) 0.0% (0) 4.8% (1) 10.8% (22) Sometimes 11.3% (13) 1.9% (1) 20.0% (3) 0.0% (0) 8.3% (17) Neutral 16.5% (19) 17.0% (9) 13.3% (2) 52.4% (11) 20.1% (41) Infrequently 20.0% (23) 22.6% (12) 20.0% (3) 19.0% (4) 20.6% (42) Rarely 20.0% (23) 20.8% (11) 26.7% (4) 9.5% (2) 19.6% (40) Never 12.2% (14) (22.6% 12) 20.0% (3) 14.3% (3) 15.7% (32) Total % (n) 100% (115) 100% (53) 100% (15) 100% (21) 100% (204) Statistical Significance χ2 _{= 34.8, df = 18, p= 0.10}

The Comprehensibility (Surprised by the behaviour of People) was significantly different

(p<0.05) among the participants across culture.

Table 30. Prevalence of Comprehensibility (surprised by the behaviour of people) across gender (%) Male % (n) Female % (n) Total % (n) Always 0.0% (0) 7.2% (10) 4.9% (10) Usually 9.2% (6) 11.5% (16) 10.8% (22) Sometimes True 10.8% (7) 7.2% (10) 8.3% (17) Neutral 26.2% (17) 17.3% (24) 20.1% (41) Infrequently 21.5% (14) 20.1% (28) 20.6% (42) Rarely 21.5% (14) 18.7% (26) 19.6% (40) Never 10.8% (7) 18.0% (25) 15.7 % (32) Total % (n) 100% (65) 100% (139) 100% (204) Statistical Significance χ2 = 9.00, df = 6, p= 0.17

The Comprehensibility (Surprised by the behaviour of People) was not significantly different

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Table 31. Prevalence of Comprehensibility (having mixed-up feelings and ideas) across culture (%) European % (n) Asian % (n) African % (n) Middle Eastern % (n) Total % (n) Always 10.4% (12) 9.4% (5) 20.0% (3) 4.7% (1) 10.3% (21) Usually 16.5% (19) 13.2% (7) 6.7% (1) 14.3% (3) 14.7% (30) Sometimes 18.3% (21) 18.9% (10) 53.3% (8) 28.6% (6) 22.0% (45) Neutral 23.5% (27) 20.8% (11) 20.0% (3) 14.3% (3) 21.6% (44) Frequently 13.1% (15) 9.4% (5) 0.0% (0) 9.5% (2) 10.8% (22) Rarely 12.2% (14) 18.9% (10) 0.0% (0) 28.6% (6) 14.7% (30) Never 6.0% (7) 9.4% (5) 0.0% (0) 0.0% (0) 5.9% (12) Total % (n) (115) 100% (53) 100% (15) 100% (21) 100% (204) Statistical Significance χ2 = 23.4, df = 18, p= 0.17

The Comprehensibility (have very mixed-up feelings and ideas?) was not significantly different X2(p>0.05) among the participants across culture.

Table 32. Prevalence of Comprehensibility (having mixed-up feelings and ideas) across gender (%) Frequency categories Male

% (n) Female % (n) Total % (n) Always 14.0% (9) 8.5% (12) 10.3% (21) Usually 7.8% (5) 17.9% (25) 14.7% (30) Sometimes 21.9% (14) 22.2% (31) 22.1% (45) Neutral 18.8 (12) 22.9% (32) 21.6% (44) Frequently 17.2% (11) 7.8% (11) 10.8% (22) Rarely 10.9% (7) 16.4% (23) 14.6% (30) Never 9.4% (6) 4.3% (6) 5.9% (12) Total % (n) 100% (64) 100% (139) 100% (203) Statistical Significance χ2 = 11.0, df = 6, p= 0.88

The Comprehensibility (have very mixed-up feelings and ideas?) was not significantly different

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Figure 12. Prevalence Comprehensibility (feelings inside you would rather not feel) across

gender (%)

This figure shows that one aspect of the trait of comprehensibility (feelings inside you would rather not feel) was significantly different (p<0.05) among the participants across gender. It was observed higher in females than in males.

Table 33. Prevalence Comprehensibility (feelings inside you would rather not feel) across culture

European % (n) Asian % (n) African % (n) Middle Eastern % (n) Total % (n) Always 11.3% (13) 20.8% (11) 20.0% (3) 9.5% (2) 14.2% (29) Often 18.3% (21) 11.3% (6) 40.0% (6) 23.8% (5) 18.6% (38) Sometimes 19.1% (22) 15.1% (8) 20.0% (3) 23.8% (5) 18.6% (38) Neutral 14.8% (17) 9.4% (5) 6.7% (1) 9.5% (2) 12.4% (25) Infrequently 13.0% (15) 9.4% (5) 0.0% (0) 4.8% (1) 10.3% (21) Rarely 13.9% (16) 18.9% (10) 0.0% (0) 4.8% (1) 13.2% (27) Never 9.6% (11) 15.1% (8) 13.3% (2) 23.8% (5) 12.7% (26) Total % (n) 100% (115) 100% (53) 100% (15) 100% (21) 100% (204) Statistical Significance χ2 _{= 21.3, df = 18, p= 0.26}

The Comprehensibility (feelings inside you would rather not feel) was not significantly different (p>0.05) among the participants across culture.

4,4 4,4 4,4 2,5 5,4 6,9 3,9 9,8 14,2 14,2 9,8 4,9 6,4 8,8 0,0 2,0 4,0 6,0 8,0 10,0 12,0 14,0 16,0

Always Often Sometimes Neutral Infrequently Rarely Never

(%)

Comprehensibility (feelings inside you would rather not feel)

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Table 34. Prevalence Comprehensibility (feelings inside you would rather not feel) across gender (%) Male % (n) Female % (n) Total % (n) Always 13.9% (9) 14.3% (20) 14.2% (29) Often 13.9% (9) 20.9% (29) 18.6% (38) Sometimes 13.9% (9) 20.9% (29) 18.6% (38) Neutral 7.7% (5) 14.3% (20) 12.3% (25) Infrequently 16.8% (11) 7.2% (10) 10.3% (21) Rarely 21.5% (14) 9.4% (13) 13.2% (27) Never 12.3% (8) 13.0% (18) 12.8% (26) Total % (n) 100% (65) 100% (139) 100% (204) Statistical Significance χ2 = 13.0, df = 6, p= 0.43

The Comprehensibility (feelings inside you would rather not feel) was significantly different

(p<0.05) among the participants across gender.

Table 35. Prevalence of Manageability (feelings sad) across culture (%)

European

Always 1.7% (2) 7.5% (4) 0.0% (0) 4.8% (1) 3.4% (7) Often 13.0% (15) 11.4% (6) 0.0% (0) 14.3% (3) 11.7% (24) Sometimes 13.9% (16) 20.% (11) 6.8% (1) 28.6% (6) 16.7% (34) Neutral 18.3% (21) 7.5% (4) 33.3% (5) 4.8% (1) 15.2% (31) Infrequently 22.7% (26) 26.4% (14) 13.3% (2) 19.0% (4) 22.5% (46) Rarely 21.7% (25) 15.0% (8) 33.3% (5) 19.0% (4) 20.7% (42) Never 8.7% (10) 11.4% (6) 13.3% (2) 9.5% (2) 9.8% (20) Total % (n) 100% (115) 100% (53) 100% (15) 100% (21) 100% (204) Statistical Significance χ2 _{= 21.3, df = 18, p= 0.27}

The Comprehensibility (feelings inside you would rather not feel) was not significantly different (p>0.05) among the participants across culture.

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Table 36. Prevalence of Manageability (feelings sad) across gender (%)

Male % (n) Female % (n) Total % (n) Always 6.1% (4) 2.2% (3) 3.4% (7) Often 20.0% (13) 7.9% (11) 11.7% (24) Sometimes 24.6% (16) 12.9% (18) 16.7% (34) Neutral 10.8% (7) 17.3% (24) 15.2% (31) Infrequently 18.5% (12) 24.5% (34) 22.5% (46) Rarely 12.3% (8) 24.5% (34) 20.7% (42) Never 7.7% (5) 10.7% (15) 9.8% (20) Total % (n) 100% (65) 100% (139) 100% (204) Statistical Significance χ2 = 13.0, df = 6, p= 0.43

The Comprehensibility (feeling sad) was not significantly different (p>0.05) among the participants across gender.

Figure 13. Prevalence of Manageability (being aware of feeling out of control) across culture (%) Figure 13 shows that Manageability (being aware of feeling out of control) was significantly different

χ2 (18, N=204) = 34.2 where p < 05 among the participants across culture. Europeans has a higher level of self-awareness than other regions.

3,4 3,4 5,4 12,3 11,3 12,3 8,3 1,0 2,9 4,4 4,4 3,9 3,9 5,4 1,0 0,5 3,9 1,0 0,0 1,0 0,0 0,5 1,0 2,9 2,0 1,0 2,9 0,0 0,0 2,0 4,0 6,0 8,0 10,0 12,0 14,0

Always Often Sometimes Neutral Infrequently rarely never

(%)

Manageability (feelings out of control)

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Table 37. Prevalence of Manageability (being aware of feeling out of control) across culture (%)

European % (n) Asian % (n) African % (n) Middle Eastern % (n) Total % (n) Always 6.1% (7) 3.8% (2) 13.3% (2) 4.8% (1) 5.9% (12) Often 6.1% (7) 11.3% (6) 6.8% (1) 9.5% (2) 7.8% (16) Sometimes 9.6% (11) 17.0% (9) 53.3% (8) 28.6% (6) 16.7% (34) Neutral 21.7% (25) 17.0% (9) 13.3% (2) 19.0% (4) 19.6% (40) Infrequently 20.0% (23) 15.1% (8) 0.0% (0) 9.5% (2) 16.2% (33) rarely 21.7% (25) 15.1% (8) 13.3% (2) 28.6% (6) 20.0% (41) never 14.8% (17) 20.7% (11) 0.0% (0) 0.0% (0) 13.8% (28) Total % (n) 100% (115) 100% (53) 100% (15) 100% (21) 100% (204) Statistical Significance χ2 = 34.2, df = 18, p= 0.12

The Manageability (being aware of feeling out of control) was significantly different (p<0.05) among the participants across culture

Table 38. Prevalence of Manageability (being aware of feeling out of control) across gender (%)

Male Female Total

% (n) Always 4.6% (3) 6.5% (9) 5.9% (12) Often 10.8% (7) 6.5% (9) 7.8% (16) Sometimes 18.5% (12) 15.8% (22) 16.7% (34) Neutral 13.8% (9) 22.3% (31) 19.6% (40) Infrequently 18.5% (12) 15.1% (21) 16.2% (33) Rarely 16.9% (11) 21.6% (30) 20.0% (41) Never 16.9% (11) 12.2% (17) 13.8% (28) Total % (n) 100% (65) 100% (139) 100% (204) Statistical Significance x2 = 4.59, df = 6, p= 0.59

The Manageability (being aware of feeling out of control) was not significantly different

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Table 39. Prevalence of Meaningfulness (not caring about surroundings) across culture (%)

European % (n) Asian % (n) African % (n) Middle Eastern % (n) Total % (n) Always 17.4% (20) 13.2% (7) 20.0% (3) 14.3% (3) 16.2% (33) Usually True 14.8% (17) 13.2% (7) 0.0% (0) 4.8% (1) 12.5 %(25) Sometimes True 14.0% (16) 24.6% (13) 13.3% (2) 33.3% (7) 18.6% (38) Neutral 21.7% (25) 17.0% (9) 20.0% (3) 23.8% (5) 20.5% (42) Infrequently 14.0% (16) 15.1% (8) 0.0% (0) 14.3% (3) 13.2% (27) Rarely 11.2% (13) 7.5% (4) 20.0% (3) 9.5% (2) 10.7% (22) Never 6.9 % (8) 9.4% (5) 26.7% (4) 0.0% (0) 8.3% (17) Total % (n) 100% (115) 100% (53) 100% (15) 100% (21) 100% (204) Statistical Significance χ2 = 21.6, df = 18, p= 0.25

The Meaningfulness (not caring about surroundings)) was not significantly different (p>0.05) among the participants across culture.

Table 40. Prevalence of Meaningfulness (not caring about surroundings) across gender

Male % (n) Female % (n) Total % (n) Always 10.8% (7) 18.7% (26) 16.2% (33) Usually True 13.8% (9) 11.5% (16) 12.5 %(25) Sometimes True 20.0% (13) 18.0% (25) 18.6% (38) Neutral 26.1% (17) 18.0% (25) 20.5% (42) Infrequently 10.8% (7) 14.4% (20) 13.2% (27) Rarely 12.3% (8) 10.0% (14) 10.7% (22) Never 6.2% (4) 9.4% (13) 8.3% (17) Total % (n) 100% (65) 100% (139) 100% (204) Statistical Significance χ2 = 4.64, df = 6, p= 0.59

The Meaningfulness (not caring about surroundings) was not significantly different (p>0.05) among the participants across gender.

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Figure 14. Prevalence of Meaningfulness (about clear goals) across gender (%)

Figure 14 indicates that females are clearer about goals than males are. Meaningfulness (about clear goals) was significantly different (p<0.05) among the participants across gender.

Table 41. Prevalence of meaningfulness (about clear goals) across culture (%)

European % (n) Asian % (n) African % (n) Middle Eastern % (n) Total % (n) No clear goals 0.0% (0) 0.0% (0) 6.7% (1) 4.8% (1) 1% (2)

Rarely clear goals 3.4% (4) 1.9% (1) 0.0% (0) 0.0% (0) 2.4% (5)

Infrequently clear goals 3.4% (4) 7.6% (4) 6.7% (1) 9.5% (2) 5.4% (11)

Neutral 7.8% (9) 9.5% (5) 6.7% (1) 4.8% (1) 7.8% (16)

Sometimes 21.6% (25) 18.9% (10) 33.3% (5) 19.0% (4) 21.5% (44)

Usually clear goals 37.9% (44) 26.4% (14) 13.3% (2) 28.6 (6) 32.2% (66)

Always Clear Goals 25.9% (30) 35.8% (19) 33.3% (5) 33.3% (7) 29.7% (61)

Total % (n) 100% (116) 100% (53) 100% (15) 100% (21) 100% (205)

The Meaningfulness (about clear goals) was not significantly different χ(p>0.05) among the participants across culture.

0,5 1,5 2,4 4,9 8,8 _7,8 5,9 0,5 1,0 2,9 2,9 12,7 24,4 _23,9 0,0 5,0 10,0 15,0 20,0 25,0 30,0 No clear goals Rarely clear goals Infrequently clear goals

Neutral Sometimes Usually clear goals

Always Clear Goals

(%)

Meaningfulness (about clear goals)

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Table 42. Prevalence of Meaningfulness (about clear goals) across gender (%)

Male % (n) Female % (n) Total % (n) No clear goals 1.5% (1) 0.7% (1) 1% (2)

Rarely clear goals 4.6% (3) 1.4% (2) 2.4% (5)

Infrequently clear goals 7.7% (5) 4.3% (6) 5.4% (11)

Neutral 15.4% (10) 4.3% (6) 7.8% (16)

Sometimes 27.7% (18) 18.6% (26) 21.5% (44)

Usually clear goals 24.6% (16) 35.7% (50) 32.2% (66)

Always Clear Goals 18.5% (12) 35.0% (49) 29.7% (61)

Total % (n) 100% (65) 100% (140) 100% (205)

Statistical Significance x2 = 17.6, df = 6, p= 0.07

The Meaningfulness (about clear goals) was significantly different (p<0.05) among the participants across gender.

Figure 15. Prevalence of Meaningfulness (daily activities - a source of pleasure or pain) across gender (%)

Figure 15 indicating that females are more likely to report rare pleasure as compared to males. The Meaningfulness (daily activities a source of pleasure or pain) was significantly different (p<0.05) among the participants across gender.

0,5 4,4 8,3 10,8 2,9 4,4 0,0 4,4 15,2 11,3 18,1 13,2 3,9 2,5 0,0 2,0 4,0 6,0 8,0 10,0 12,0 14,0 16,0 18,0 20,0

Source of Pain Rare Pleasure Infrequent

Pain Neutral Sometimes Pleasure PleasureUsually Source of Pleasure

(%)

Meaningfulness (daily activities a source of pleasure or pain)

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Table 43. Prevalence Meaningfulness (daily activities a source of pleasure or pain) across culture (%)

European

Source of Pain 3.4% (4) 9.6% (5) 0.0% (0) 4.9% (1) 4.9% (10) Rare Pleasure 22.4% (26) 17.3% (9) 0.0% (0) 23.8% (5) 19.6% (40) Infrequent Pain 18.9% (22) 17.3 % (9) 26.7% (4) 23.8% (5) 19.6% (40) Neutral 30.2% (35) 30.9% (16) 26.7% (4) 19.0% (4) 28.9% (59) Sometimes Pleasure 14.7% (17) 11.5% (6) 40.0 (6) 19.0% (4) 16.2% (33) Usually Pleasure 7.8% (9) 11.5% (6) 0.0% (0) 9.5 %(2) 8.3% (17) Source of Pleasure 2.6% (3) 1.9% (1) 6.6% (1) 0.0% (0) 2.5% (5) Total % (n) (116) 100% (52) 100% (15) 100% (21) 100% (204) Statistical Significance χ2 _{= 18.7, df = 18, p= 0.41}

The Meaningfulness (daily activities a source of pleasure or pain) was not significantly different

(p>0.05) among the participants across culture.

Table 44. Prevalence Meaningfulness (daily activities a source of pleasure or pain) across gender (%) Male % (n) Female % (n) Total % (n) Source of Pain 1.6% (1) 6.4% (9) 4.9% (10) Rare Pleasure 14.0% (9) 22.1% (31) 19.6% (40) Infrequent Pain 26.6% (17) 16.4% (23) 19.6% (40) Neutral 34.4% (22) 26.5% (37) 28.9% (59) Sometimes Pleasure 9.4% (6) 19.3% (27) 16.2% (33) Usually Pleasure 14.0% (9) 5.7% (8) 8.3% (17) Source of Pleasure 0.0% (0) 3.6% (5) 2.5% (5) Total % (n) 100% (64) 100% (140) 100% (204) Statistical Significance χ2 = 15.4, df = 6, p= 0.01

The Meaningfulness (daily activities a source of pleasure or pain) was significantly different