Lithuanian University of Health Sciences MEDICAL ACADEMY
FACULTY OF MEDICINE
Alexander Yusupov
Sociodemographic Factors And Quality Of Life Among 2nd And 5th Year Lithuanian Medical Students At The Lithuanian University Of Health Sciences
In The Department of Psychiatry
Submitted in partial fulfillment of the requirements for the degree of
Master of Medicine
Scientific supervisor:
Virginija Adomaitiene, MD, PhD, professor.
June 2016 Kaunas
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TABLE OF CONTENTS
Summary ... 3
Conflicts of interest... 4
Ethics committee clearance ... 5
Abbreviations ... 6
Introduction... 7
The aims and objectives... 8
1. Literature review ... 9
2. Research methodology and methods ... 12
3. Results ... 14
4. Discussions ... 20
5. Conclusions ... 22
References... 23
3
SUMMARY
SOCIODEMOGRAPHIC FACTORS AND QUALITY OF LIFE AMONG 2ND AND 5TH YEAR LITHUANIAN MEDICAL STUDENTS AT THE LITHUANIAN UNIVERSITY OF HEALTH SCIENCES.
Alexander Yusupov.
SCIENTIFIC SUPERVISOR: Virginija Adomaitiene, MD, PhD, professor.
Department of Psychiatry, Faculty of Medicine, Medical Academy, Lithuanian University of Health Sciences. Kaunas; 2016, 31 pages.
Aim of the study. To test whether various domains of quality of life and their association with sociodemographic factors varies among 2nd and 5th year Lithuanian medical students at the Lithuanian University of Health Sciences (LUHS).
Objectives. 1. To evaluate and compare a set of sociodemographic factors in 2nd and 5th year Lithuanian medical students at LUHS. 2. To evaluate and compare quality of life perception in various domains among 2nd and 5th year Lithuanian medical students at LUHS. 3. To evaluate the correlation of quality of life with sociodemographic factors between 2nd and 5th year Lithuanian medical students at LUHS.
Methods. A cross-sectional survey was conducted among Lithuanian medical students from 2nd and 5th year of studies in LUHS in Kaunas. Students were approached on campus (between December 2015 and January 2016) and asked to fill out two questionnaires. A sample of 145 students (Mage = 21.61, SDage
=1.68, 68.3% females) was obtained, out of which 70 students were in 2nd year and 75 students were in 5th year of studies. Participants answered Sociodemographic questionnaire regarding their age, gender, family status, living situation, income, spending and financial support and a Lithuanian adapted version of the WHOQoL-BREF questionnaire (N. Goštautaitė Midttun and A. Goštautas, 2000), which comprised 26 items and evaluated 4 main quality of life domains (Physical health, Psychological health, Social relationships and Environment). The statistical analysis was performed using the SPSS 20.0 statistical data processing package. χ2
test and ANOVA analysis were used to evaluate the statistical differences. Statistical difference p<0.05 was considered significant.
Results. 70% reported being single in 2nd year in comparison to 42.7% in 5th year. Students in 5th year tend more to rent an apartment (40%) than to live in the students’ dormitories compared to students in 2nd year (22.9%). 70% of students’ in 2nd
year are fully supported financially by their parents in comparison to 58.7% of students in 5th year. Cronbach‘s alpha of WHOQoL questionnaire was α = .88, indicating a good reliability. Students rated their general quality of life in 2nd year as 83.2% and 79.8% in 5th year. No statistical significance was found between the domains between 2nd and 5th year (p>0.05). Negative correlation between age and general quality of life in 2nd year was found as well as positive correlation between parental support and social relationships domain in 2nd year students.
Conclusions. 1. Students in 2nd year tend to be single, fully supported financially by family, unemployed and have no loans, they have less income and spend less then 5th year students. In both 2nd and 5th courses approximately one third of the students received some kind of scholarship. Two thirds of all students were either renting an apartment or living in students’ dormitories, with twice more 5th year students that tend to rent an apartment than in 2nd year. 2. Male students in 2nd year rated their general QoL lower than females. Physical health domain in both students groups was evaluated highest among the other QoL domains. Perception of general satisfaction of students QoL was similar between 2nd and 5th year students and no significant correlations between all domains were found. 3. The older the students in 2nd year were, the lower they rated their overall quality of life and the more parental support they had, the better they rated their social relationships domain.
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CONFLICTS OF INTEREST
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ETHICS COMMITTEE CLEARANCE
Ethics committee clearance was reviced by the department of bioethics in Lithuanian University of Health Sciences. The premission was granted on the 01-12-2015, Nr. B&C-MF-106 and signed by the head of Bioethics center Doc. E. Peičius. (included in annex page 31)
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LIST OF ABBREVIATIONS
CI – Confidence interval
df – Number of degrees of freedom
EUR – Euros (currency)
KMU – Kaunas medical university
LUHS/LSMU – Lithuanian University of Health Sciences
M – Mean
MF – Medical faculty
n – Number of subjects
nr. – Number
p – Statistical significance
QOL – Quality of life
WHOQoL-BREF – The World Health Organization’s Quality of life questionnaire-short version
r – Correlation coefficient SD – standard deviation
VU – Veterinary University (in Kaunas) WHO – World Health Organization χ2
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INTRODUCTION
Quality of life has been reported to be an important component during the study period of students. QOL is being increasingly investigated in many fields; studies suggest reasonable connection between quality of life, performance and motivation of students and medical personal. Social and economic factors are known to influence on one’s QOL and they include factors as financial status, social support and living conditions. In some studies individuals of one gender and age group presented with difference perception in QOL in the same group. During the period of studies, students encounter different challenges, those may influence on their attitude, behavior and lifestyle [1].
The Helsinki statement on Health in All Policies [2] recognizes that health condition of the population influences QOL and the capacity of learning, and by promoting good health we increase both of them. Tsouros et al.[3] suggests that universities are in unique position; being a center of education, innovation and influence on many young students they can promote health and QOL.
By identifying the extent of influence of certain factors, and the vulnerable risk groups, we may suggest tactics on how to address those risks, those tactics can be implemented in the study program as well as in health promotion and psychologic support of students in order to increase students’ QOL.
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THE AIM AND OBJECTIVES
The Aim of the thesis was to test whether various domains of quality of life and their association with sociodemographic factors differs among 2nd and 5th year Lithuanian medical students at the Lithuanian University of Health Sciences (LUHS).
Objectives of the study:
1. To evaluate and compare a set of sociodemographic factors in 2nd
and 5th year Lithuanian medical students at LUHS.
2. To evaluate and compare quality of life perception in various domains among 2nd
and 5th year Lithuanian medical students at LUHS.
3. To evaluate the correlation of quality of life with sociodemographic factors between 2nd
and 5th year Lithuanian medical students at LUHS
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1. LITERATURE REVIEW
1.1. QOL, WHO assessment instrument and its’ validity
Quality of life is a subject that is widely investigated. Many studies can be found on this topic, practically in every field of medical science. Investigating the factors that influence quality of life is broadly studied. Many such factors are present and exert both negative and positive effects [4]. Quality of life is in particular interest in patient therapy. This is done in order to assess the relation of one’s health and quality of life where therapeutic treatment and outcomes and even survival [5] are investigated.
The definition of Quality of life (QOL) by World Health Organization (WHO) is: “individuals’ perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards and concerns [6]”.
This definition defines what quality of life is, but it is not practical when applied generally, because we should take into account personal factors as one’s gender, age, profession and culture. This definition rather says that one’s own perception of QOL differs from another’s. It has to do with one’s personal goals, expectations and achievement. QOL differs in different stages of life, which makes it more difficult to measure and compare [7].
The WHO has developed QOL instrument (WHOQOL-100) to overcome such issues, and is being widely used. It was developed with international collaborations - 15 centers in 14 different countries were involved in its development initially [8]. Being developed in many countries the instrument is widely accepted to apply over many cultures [9].
The WHOQOL-BREF instrument is a shorter version of the original instrument; it comprises 26 items, which evaluate 4 main domains: physical health, psychological health, social relationships, and
environment. This version has been reported to be valid in different studies [10,11]. The Lithuanian version was validated for use in university students by Dučinskienė et al.[12].
1.2. QOL influence on students
The influence of QOL on students has been evaluated in several studies,
Eckleberry-Hunt et al.[13] suggested that QOL has an important influence on students’ and medical staff’s performance. They concluded that QOL should be maintained in an optimal level that will allow
subsequently efficient function. Moreover, it is suggested that there is a connection between QOL and students’ motivation, suggesting that maintenance of adequate QOL will keep students better motivated throughout their studies which will further enable a more successful carrier [14].
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Due to the reason that QOL is a subjective perception, it fluctuates accordingly throughout the study period. Goldin et al.[15] reported such fluctuation of QOL in their study among 3rd year medical students in surgical clerkship together with students’ decline in sleep and increase in depression. 1.3. Factors influencing QOL
Among the different factors that influence QOL, stress has been reported in students throughout medical studies[16] and it has been reported to exert a negative influence[17].
Variety of stressors that may influence the mental health of medical students and staff were suggested[18], among them: accommodation to the medical school environment, study debts, high workload, inadequate sleep, financial and career concerns and others.
The influence of stressors on students’ psychological distress, anxiety and depression was reported in different works. In a cross sectional study by Jafari, Loghmani and Montazeri[19], assessment of
psychological morbidity prevalence among medical students from Isfahan University of Medical Sciences in Iran was performed. Their study evaluated psychological distress according 12-item General Health Questionnaire. They reported psychological distress to be common among medical students in their university, unfortunately this study did not investigated reasons that might contribute to such findings. In another study, indicators of psychological distress Among U.S. and Canadian medical students were investigated in a systemic review among 40 articles. This study suggested that compared to general population, medical students have a higher prevalence of anxiety and depression[20]. Those studies show that stressors are prevalent among medical students in many countries and have a negative influence.
In those studies female students exerted higher prevalence of psychological distress than male students in the same group, suggesting different perception of QOL between the genders. Schernhammer and Colditz[21] proposed in their study that females are more prone to develop depression. Additionally proposing that female social role may influence.
In a study among medical students in China[22], gender had significant association with QOL among their study group of 1686 students from 1st to 5th year of study from China Medical University. This study reported higher scores of QOL in the domains of physical and psychological health among male students in comparison to female students. This study suggested that women are more emotional and sensitive to pressure than men might be one of the reasons to such findings. In the same study a different result was reported in the social-relations domain, where female students scored higher then male students. They explained such finding from literature that showed that women are better than men at dealing with different relationships.
11 1.4. QOL among medical and non-medical students
Although studies showed that there is a presence of psychological distress among medical students in comparison to the general population, when compared with non-medical students studies show a different picture. In Henning et al.[23] study, medical students were compared with non-medical students in the same city by WHOQOL-BREF instrument. 274 medical students and 2 groups of non-medical students from a different university were assessed. In this study medical students did not show lower levels of QOL then in non-medical students. And both medical and non-medical students expressed lower levels of QOL when compared to general population (Australian general population norm was used). This study suggests that medical and non-medical students express similar QOL perceptions.
1.5. QOL and Sociodemographic factors
Other studies show that demographical and socioeconomic factors influence quality of life. Among them financial support and social relations [24], students that had lower financial support and less social relations were considered to be in the risk groups.
A different study was trying to identify medical students that are at risk of underperformance due to significant stressors, they found that various sociodemographic factors influence the students’ academic performance, especially an influence of fewer social interconnections [25].
A possible outcome associated with lower levels of quality of life and stressors influence is a burnout in medical practice. Dyrbye et al.[26] investigated burnout prevalence, quality of life, fatigue and stress among medical students from several institutions in US.
The study showed that some students were more resilient then other. Resilient students were the students who did not express burnout symptoms. Such students were reported to have a higher QOL and lower probability for depression.
This research supports the assumption that factors like social support, stress level, and other stressors may have a greater effect on vulnerable students for burnout development [27].
The understanding of factors that can influence QOL and identifying students at risk groups can be used to implement changes throughout the medical studies program [3]. Together with health promotion and psychological support, this can promote one’s QOL and in consequence have a positive influence on the motivation in studies, learning and achievements of students.
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2. RESEARCH METHODOLOGY AND METHODS
Statistical data analysis
Statistical data analysis was performed using data collection and analysis SPSS 20.0 (Statistical Package for Social Science for Windows) package and Cronbach’s α coefficient was performed to determine the internal consistency reliability. The socio-demographic characteristics of the sample were firstly described. According to descriptive data analysis, the mean of quantitative variables with a
deviation MV (SD) was presented. The characteristics of the student’s age under research were described with respect to location, dispersion and symmetry (minimum and maximum value, median).
If variable distribution met the distribution normality assumption, Student’s (t) criterion was applied to compare quantitative sizes of two independent groups. In case there were more than two groups, ANOVA dispersive was applied.
The independence of qualitative characteristics was evaluated by using χ2 criterion. The difference between groups was considered as statistically significant when p<0.05.
Methods
A sample of 145 students (Mage = 21.61, SDage =1.68, 68.3% females) was obtained, out of which 70
students were in their 2nd year and 75 students were in their 5th year of study. All students are fully integrated in the program of medicine in the medical faculty of LUHS.
Students were approached on campus (between December 2015 and January 2016) and asked to fill out two questionnaires.
Socio-demographic. Participants were asked to answer questions regarding their age, gender, family status, living situation, income, spending and financial support.
Quality-of-Life. Lithuanian adapted version of the WHOQOL-BREF questionnaire (N. Goštautaitė Midttun and A. Goštautas, 2000[28]
). Participants were asked to evaluate 26 items on a Likert-type scale from 1 to 5 measuring intensity (none to extremely), capacity (nothing to fully), frequency (never to always), and evaluation (very satisfied to very dissatisfied and very bad to very good). Two individual items reflect participants overall general evaluation of quality of life. Specifically the items ask “How would you rate your quality of life?” and “How satisfied are you with your health?”. Another 24 items evaluate 4 different quality of life domains. Physical health (7 items), Psychological health (6 items), Social relationships (3 items) and Environment (8 items). The scores are transformed into a linear scale in the range of 0 to 100, with 0 being the least favorable and 100 being the most favorable.
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Table 1. WHOQoL-BREF domains[29]
Domain Items facets integrated within domains 1. Physical health Activities of daily living
Dependence on medical substances and medical aids Energy and fatigue
Mobility
Pain and discomfort Sleep and rest Work capacity
2. Psychological Bodily image and appearance Negative feelings
Positive feelings Self-esteem
Spirituality, religion, personal belief
Thinking, learning, memory and concentration 3. Social
relationships
Personal relationships Social support
Sexual activity 4. Environmental Financial resources
Freedom, physical safety and security
Health and social care: accessibility and quality Home environment
Opportunities for acquiring new information and skills
Participation in and opportunities for recreation, leisure activities Physical environment (pollution, noise, traffic, climate)
Transport
Sociodemographic questionnaire was created by author for the purpose of this study.
Permission to use Lithuanian adapted version of WHOQoL-BREF questionnaire was given by author prof. A. Goštautas (included in annex page 30).
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3. RESULTS
145 students were assessed, out of which 70 students were in their 2nd year and 75 students were in their 5th year of study.
Table 2: Demographic presentation.
Variable Age M(SD), years 21,6(1,7) Course, n(%) 2nd course 5th course total 70(48.3) 75(51.7) 145 Gender, n(%) males females 46(31.7) 99(68.3)
Male to female ratio between 2nd and 5th course showed no significant correlation (χ2 =.62, df=1, p=.43). Family status among participants was evaluated, of which 81 students (55,9%) indicated being single and 64 (44,1%) students indicated they are in a relationship.
Among those in relationship 58 students (40%) had a boyfriend or a girlfriend, 3 students (2.1%) indicated they were married and another 3 students (2.1%) were engaged.
Table 4: Personal family status and course
Variable 2nd course 5th course
Family status, n(%) Single Boy/Girlfriend Engaged Married 49(70*) 20(28.6**) 1(1.4) 0(0) 32(42.7*) 38(50.7**) 2(2.7) 3(4)
There was significant correlation between the course and family status (χ2=12.33, df=3, p=.006, *,**p<0,05). In the 5th course more students indicated that they were in relationship then in 2nd course.
No significant correlation was noted between family status and gender (χ2=0.68, df=1, p=0.408).
Table 3: Students according gender and course
Variable 2nd course 5th course Gender, n(%) males females 20(28.6) 50(71.4) 26(34.7) 46(35.3)
Table 5: Family status by gender
Variable Males Females
Family status, n(%) Single In relationship 28(60.9) 18(39.1) 53(53.5) 46(46.5)
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Students indicated their Living arrangement during their period of studies, as following:
There was no significance between living arrangement and: the course (χ2 test =7.08, df=3, p=0.068), family status (χ2 test =2.589, df=3, p=0.459) and their gender (χ2 test =6.79, df=3, p=0.8).
We evaluated students that reported about their financial support from parents in relation with their course
Table 8: Financial support from parents according course
Variable 2nd course 5th course
Financial support, n(%) Fully support Partial/No support 49(70%) 21(30%) 44(58.7%) 31(41.3%) In total: 93(64.1%) 52(35.9%)
There is no significance between financial support and the students: course (χ2 test =2.02, df=1, p=0.2), gender (χ2=2.80, df=1, p=0,094) and living arrangement (χ2=0.941, df=3, p=0,816).
There was significant correlation between financial support from parents and family status (χ2=6.04, df=1,
p=0,014), students in relationship reported having less financial support from their parents.
Students were asked to indicate whether or not they receive any kind of scholarship during their studies.
Table 6: Living arrangements according to course and family status
Variable overall 2nd course 5th course Single In relationship Living arrangment, n(%) Hostel/Dormatory Renting appartment In own/family house Other 31(21.4) 46(31.7) 56(38.6) 12(8.3) 19(27.1) 16(22.9) 27(38.6) 8(11.4) 12(16) 30(40) 29(38.7) 4(5.3) 21(25.9) 23(28.4) 31(38.3) 6(7.4) 10(15.6) 23(35.9) 25(39.1) 6(9.4)
Table 7: living arrangements in relation with gender
Variable Males Females
Living arrangment, n(%) Hostel/Dormatory Renting appartment In own/family house Other 11(23.9) 11(23.9) 23(50) 1(2.2) 20(20.2) 35(35.4) 33(33.3) 11(11.1)
Fig.1. Students’ living arrangements 38.6% 8.3% 31.7% 21.4% Hostel Renting Own/Family House Other
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There was no significance between having or not scholarship and with: students’ course
(χ2=0.091, df=1, p=0,763), students’ family status (χ2=0.53, df=1, p=0,467), students’ living arrangement (χ2=0.58, df=3, p=0,9) and students’ gender (χ2=0.58, df=3, p=0,9).
Table 9: Overall scholarship between the genders
Variable Scholarship, n(%) Yes No 50(34.5) 95(65.5) Males, n(%) 19(41.3) 27(58.7) Females, n(%) 31(31.3) 68(68.7)
There was significant correlation between having scholarship and financial support from parents
χ2
=8.641, df=1, p=0,003, *,**p<.005; students having a scholarship are less supported by parents.
Table 10: Scholarship and Financial support from parents
Variable Full support Partial or no support In total Scholarship, n(%) Yes No 24(48*) 69(72.6**) 26(52*) 26(27.4**) 50(100) 95(100)
We asked students to indicate whether or not they have a loan:
Only 6 students (4.1%) indicated that they have a loan during their study period with no significant difference between the genders (χ2=3.528, df=1, p=0,06) and students‘ living arrangement (χ2=0.798,
df=3, p=0,85). When we evaluated if there was significant difference with family status, 1 student (16.7%)
indicated being single and 5 students (83.3%) were in relationship, we found significant difference (χ2=3.9, df=1, p=0,04). There was significant difference (χ2=6.132, df=1, p=0,013) when compared with financial support from parent and getting a loan. Those students who had a loan indicated that they receive partial or no financial support from parents. As we had very small sample of students’ with a loan the reliability regarding those findings is questionable.
Students were asked to indicate whether or not they are working during their studies:
23 students (15.9%) indicated that they are working during their studies, of whom 8 students (34.8%) were in their 2nd year and 15 (65.2%) of them were in their 5th year. There was no significant correlation between working while studying and: students course (χ2=1.993, df=1, p=0,16), family status (χ2=3.104,
df=1, p=0,08), living arrangements (χ2=3.055, df=3, p=0,383), having a loan (χ2=0.003, df=1, p=0,956) and gender (χ2=0.021, df=1, p=0,885).
Table 11: Imployment of students and gender
Variable males females
Working, n(%) Yes No 7(15.2) 39(84.8) 16(16.2) 83(83.8)
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There was significant correlation between working and financial support from parents (χ2=28.971, df=1,
p<0.01), students’ who work indicated that they are not fully supported financially by their parents.
Next we asked the students to indicate their estimated monthly income and monthly spending:
Table 12: Students overall monthly income and spendings
Variable Monthly income (EUR) Monthly spendings (EUR) Mean Median SD± 198.71 200 144.327 184.14 170 117.824
Table 13: Monthly income and spendings according gender
Variable N Mean Std. Deviation ±
Monthly income (EUR) males females Monthly spendings (EUR)
males females 46 99 46 99 220.33 188.67 200.98 176.31 174,091 127.945 130.391 111.341
There was no significant difference in the monthly income between males (M=220.33, SD=174.091) and females (M=188.67, SD=127.945); t(143)=1.23, p=.220 .
There was no significant difference in the monthly spending between males (M=200.98, SD=130.391) and females (M=176.31, SD=111.341); t(143)=1.18, p=.242 .
Table 14:Monthly income and spendings in relation with Course
Variable N Mean Std. Deviation ±
Monthly income (EUR) 2nd year
5th year Monthly spendings (EUR)
2nd year 5th year 70 75 70 75 167.17 288.15 153.14 213.07 134.390 147.903 107.276 120.528
There was a significant difference in the monthly income between 2nd year students (M=167.17,
SD=134.390) and 5th year students (M=288.15, SD=147.903); t(143)=-2.592, p=.011 .
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SD=107.276) and 5th year students (M=213.07, SD=120.528); t(143)=-3.154, p=.002 . Students in 5th year had more income and they spent more money.
Evaluation between monthly income and family status of students who were single (M=192.12,
SD=134.573) and in relationship (M=207.05, SD=156.490) indicate no statistical significant difference
(t(143)=-.617, p=.54); evaluation between monthly spending and family status of students who were single (M=181.79, SD=115.253) and in relationship (M=187.11, SD=121.850) indicate no significant difference as well (t(143)=-.269, p=.79)
Evaluation of the monthly income and parental financial support show that between students who are fully supported (M=179.91, SD=127.935) and students who get partial or no support (M=232.33, SD=165.811) there was a significant difference ( t(143)=-2.123, p=.036).
Evaluation of the monthly spending’s and parental financial support show that between students who are fully supported (M = 172.31, SD = 114.228) and students who get partial or no support (M = 205.29, SD = 122.264) there was a significant difference ( t(143) = -1.626, p = .11).
The less financial support students received from parents the more their monthly income was and the higher their monthly spending’s were.
Assessment of QOL questionnaire:
The overall reliability of the questionnaire by Cronbach‘s Alpha was evaluated (26 items, α = .88). Reliability In each domain was evaluated as well: Physical health (7 items, α = .70), Psychological health (6 items, α = .82), Social relationships (3 items, α = .47) and Environment (8 items, α = .74).
First I checked whether the two individual items differ between participants in their 2nd and 5th years. An ANOVA analyses revealed that students in their 2nd year rated their quality of life (question nr. 1) somewhat higher 83.2% (M = 4.16, SD = .63) than those in 5th year 79.8% (M = 3.99, SD = .58), F(1,143) = 2.88, p = .092. There were no differences in their satisfaction of their health (question nr. 2), F(1, 143) = .031, p = .860 (for 2nd year 75.8% (M = 3.79, SD = .88) and 5th year 75.2% (M = 3.76, SD = .86).
Students rated their overall QoL and general health (questions nr. 1 and 2) in 2nd year 79.4%(SD=12.5) and in 5th year 77.5% (SD=12.1)
Next I looked at the 4 domains. I computed the overall score of the 4 domains as instructed in Harper & Power (2013)[30]. Each participant received an individual score on each of the four domains ranges between 1 and 100, with higher scores corresponding to better quality of life. An ANOVA analyses revealed that there were no differences in any of the 4 domains between students in 2nd and 5th year. Specifically, there was no difference in Physical health among participants from 2nd year (M = 73.97, SD =
19 73.97 73.57 63.5164.22 67.6168.22 68.7 70.16 58 60 62 64 66 68 70 72 74
Physical Health Psychological Health Social Relationships Environmental Domain 2nd Year 5th Year
11.91) and 5th year (M = 73.57, SD = 12.42), F(1,143) = .041 ,p = .841. There was no difference in Psychological health (M = 63.51, SD = 14.76 and M=64.22, SD=14.53 for 2nd and 5th year respectively),
F(1,143) = .085, p =.771. Additionally there was no difference in Social relationships between participants
from 2nd year (M=67.61, SD=14.08) and 5th year (M=68.22, SD=14.67), F(1,143) = .064, p = .801, and in the Environmental domain (M=68.70 , SD=13.08 and M=70.16 , SD=13.33 for 2nd and 5th year respectively), F(1,143) = .443 , p = .507.
Next I tested whether different health items are associated with demographic information among the overall sample. Analyses showed a negative correlation between age and general quality of life, r = -.170,
p = .041. That is, the older the students were, the lower they rated their overall quality of life. Additionally
there was a correlation between parental support and social relationships, r = .154, p = .044. The more parental support participants had, the better they rated their social relationships. Lastly, males (M = 3.91,
SD = .59) rated their general quality of life slightly lower than females (M = 4.14 SD = .60), F (1, 143) =
4.53, p = .035. No other associations were found.
Lastly, I tested whether these correlations differ among students in their 2nd and 5th year. Analyses revealed that all the obtained associations were driven by students in the 2nd year. Specifically, the association between age and general quality of life was present for students in their 2nd year the (r = -.206, p = .047), but not for students in their 5th year (r = -.029, p = .808).
Moreover, the association between parental support and social relationships was present for students in their 2nd year the (r = .290, p = .015), but not for students in their 5th year (r = .057, p = .626). Additionally the difference in the general quality of life among males and females was present in the 2nd year, F(1 , 68) = 7.29, p = .009 , but not in the 5th year, F(1, 73) = .073, p =.787.
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4. DISCUSSION
The aim of the research was to test whether various domains of quality of life and their association with sociodemographic factors varies among 2nd and 5th year Lithuanian medical students at the LUHS.
We found in our study that there were no significant correlations in the 4 domains of QoL between 2nd and 5th year students. This result suggests that students’ perception of their QoL does not change throughout their study and remains quit similar. The physical health domain of the students’ QoL was evaluated positively high and was highest among the other domains, implying good activities of daily living, enough energy, less pain and discomfort, sufficient sleep and rest and good work capacity of the students’.
A similar study by Dickson[31] conducted among international medical students from all courses in our university obtained much lower results in physical health and environmental domain in comparison to our study, suggesting lower perception of QoL in those domain facets, this might be explain due to the reason that Lithuanian students study in their homeland, not far away from family and friends, being more adapted to the country. Evaluation of the other domains of this study showed slightly lower scores in psychological health and social relationships domains in comparison to our study among 2nd and 5th year Lithuanian students. In general, in our study the Lithuanian students scored higher in all the domains compared to international students from the same university. The results are presented in Fig.3 where ‘2011 international students’ represent QoL results obtained in that study compared to our study “2nd
year” and “5th year” students 74 74 49 64 64 60 68 68 65 69 70 56 0 10 20 30 40 50 60 70 80
Physical Health Psychological Health
Social Relationships Environmental Domain
2nd Year 5th Year
2011 International students
Fig.3. QoL domain results and comparison with Adedeji (2011) study.
Dučinskienė et al.[32] conducted a study among 3rd year students from several universities in Kaunas where the evaluation of QoL was performed, among them the evaluation of biomedical students that were
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scores in the physical health, psychological health and social relationship domains and significantly lower score in the environmental domain when compared to our study 2nd and 5th year medical students. The results from that research can be seen in Fig.4 and they are assigned as "2003 3rd year” students.
74 74 69 64 64 60 68 68 62 69 70 50 0 10 20 30 40 50 60 70 80
Physical Health Psychological Health Social Relationships Environmental Domain 2nd Year 5th Year 2003 3rd Year
Fig.4. QoL domain results and comparison with Dučinskienė et al. (2003) study.
Although the study group from that research was 3rd year students, we can see that the trend in Lithuanian students is quite similar, and even improved between 2003 when this study was conducted to our study.
Moreover, in the same study, we are able to evaluate between QoL perception in Medical and non-medical field students. In that study students from Technological and Humanitarian disciplines from different universities had similar scores in all the domains as students from biomedical discipline. This finding strengthen the assumption that medical and non-medical students do not differ in their perception of QoL, as was concluded in another study by Henning et al.[23] among medical and non-medical students studying in New Zealand.
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5. CONCLUSIONS
1. Students in 2nd year tend to be single, fully supported financially by family, unemployed and have no loans, they have less income and spendings than 5th year students. In both 2nd and 5th courses
approximately one third of the students received some kind of scholarship. Two thirds of all students were either renting an apartment or living in students’ dormitories with twice more 5th
year students tend to rent an apartment.
2. Male students in 2nd year rated their general QoL lower than females. Physical health domain in both students groups was evaluated highest among the other QoL domains. Perception of general satisfaction of students’ QoL was similar between 2nd
and 5th year students and no significant correlations between all domains were found.
3. The older the students in 2nd year were, the lower they rated their overall quality of life and the more parental support they had, the better they rated their social relationships domain.
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REFERENCES
1. Dyrbye LN, Thomas MR, Shanafelt TD. Medical student distress: causes, consequences, and proposed solutions. Mayo Clin Proc. 2005;80(12):1613–1622.
2. The Helsinki statement on Health in All Policies (2013). URL:
http://www.who.int/healthpromotion/conferences/8gchp/statement_2013/en/index1.html (accessed: 05/03/2016)
3. Tsouros AD, Dowding G, Thompson J, Dooris M. (2008) Health promoting Universities Chapter 2, 33. URL: http://www.euro.who.int/__data/assets/pdf_file/0012/101640/E60163.pdf (accessed: 05/03/2016) 4. Castellano-Tejedor C, Eiroa-Orosa FJ, Perez-Campdepadros M, Capdevila L, Sanchez de Toledo J, Blasco-Blasco T. Perceived positive and negative consequences after surviving cancer and their relation to quality of life. Scand J Psychol. 2015; 53(3):306-14
5. Montazeri A. Quality of life data as prognostic indicators of survival in cancer patients: an overview of the literature from 1982 to 2008. Health Qual Life Outcomes. 2009;7:102.
6. The WHOQOL Group. The World Health Organization Quality of Life Assessment (WHOQOL). Development and psychometric properties. Soc Sci Med. 1998;46:1569-1585.
7. Ulrike Ravens-Sieberer, Anne Karow, Dana Barthel & Fionna Klasen. How to assess quality of life in child and adolescent psychiatry. Dialogues Clin Neurosci. 2014 Jun; 16(2): 147–158.
8. Power, M., Bullinger, M., Harper, A., & The WHOQOL Group. The World Health Organization WHOQOL-100: Tests of the universality of quality of life in 15 different cultural groups worldwide.
Health Psychology. 1999, 18(5), 495–505.
9. Bowden, A., & Fox-Rushby, J. A. A systematic and critical review of the process of translation and adaptation of generic healthrelated quality of life measures in Africa, Asia, Eastern Europe, the Middle East, South America. Social Science and Medicine. 2003, 57(7), 1289–1306.
10. Krägeloh CU, Kersten P, Billington DR, Hsu PH-C, Shepherd D, Landon J, et al. Validation of the WHOQOL-BREF quality of life questionnaire for general use in New Zealand: Confirmatory factor analysis and Rasch analysis. Qual Life Res. 2013;22:1451–7.
11. Wang, W.C., Yao, G., Tsai, Y.J. et al. Validating, improving reliability, and estimating correlation of the four subscales in the WHOQOL-BREF using multidimensional Rasch analysis. Qual Life
24
12. D.ducinskiene, R.kalediene, J.petrauskiene, L.sumskas. Evaluation of suitability of world health organization questionnaire for assessing quality of life of university students. “Sveikatos mokslai”. 2002; 3:53-58.
13. Eckleberry-Hunt, J., Lick, D., Boura, J. and Hunt, R. ‘an exploratory study of resident burnout and wellness’. Acad Med.2009; 84(2): 269-277.
14. Collins, J. ‘Life learning in the 21st century and beyond’. Radiographics. 2009; 29: 613-622.
15. Goldin SB, Wahi MM, Farooq OS, Borgman HA, Carpenter HL, Wiegand LR, et al. Student quality-of-life declines during third year surgical clerkship. J Surg Res. 2007;143(1):151–7.
16. Moczko TR, Bugaj TJ, Herzog W, Nikendei C. Perceived stress at transition to workplace: a
qualitative interview study exploring final-year medical students’ needs. Advances in Medical Education
and Practice. 2016;7:15-27.
17. LeBlanc VR. The effects of acute stress on performance: implications for health professions education. Acad Med. 2009;84(10):S25–33.
18. Psychological stress and burnout in medical students: a five-year prospective longitudinal study. Guthrie E, Black D, Bagalkote H, Shaw C, Campbell M, Creed F. J R. Soc Med. 1998;91:237–243. 19. Jafari N, Loghmani A, Montazeri A. Mental health of medical students in different levels of training.
International journal of preventive medicine. 2012;3(Suppl 1):S107–112.
20. Dyrbye L.N., Thomas M.R., Shanafelt T.D. Systematic review of depression, anxiety, and other indicators of psychological distress among U.S. and Canadian medical students. Acad. Med.2006;81:354– 373.
21. Schernhammer ES, Colditz GA. Suicide rates among physicians: a quantitative and gender assessment (meta-analysis) Am J Psychiatry. 2004;161(12):2295–2302.
22. Zhang Y, Qu B, Lun S, Wang D, Guo Y, Liu J. Quality of life of medical students in China: a study using the WHOQOL-BREF. PLoS One. 2012;7(11):e49714.
23. Henning MA, Krageloh CU, Hawken SJ, Zhao Y, Doherty I. The quality of life of medical students studying in New Zealand: a comparison with nonmedical students and a general population reference group. Teach Learn Med. 2012;24(4):334–340.
24. Said, D.; Kypri, K.; Bowman, J. Risk factors for mental disorder among university students in Australia: Findings from a web-based cross-sectional survey. Soc. Psychiat. Psychiatr. Epidemiol. 2013,48, 935-944.
25. Wilkinson TJ, McKenzie JM, Ali AN, Rudland J, Carter FA, Bell CJ. Identifying medical students at risk of underperformance from significant stressors. BMC Medical Education. 2016;16:43.
25
26. Dyrbye LN, Power DV, Massie FS, Eacker A, Harper W, Thomas MR, et al. Factors associated with resilience to and recovery from burnout: a prospective, multi-institutional study of US medical
students. Med Educ. 2010;44:1016–1026.
27. Dyrbye LN, Thomas MR, Huschka MM, Lawson KL, Novotny PJ, Sloan JA, Shanafelt TD. A multicenter study of burnout, depression, and quality of life in minority and nonminority US medical students. Mayo Clin Proc. 2006;81(11):1435–1442.
28. World Health Organization Quality of Life - 100 questionnaire (WHOQOL-100)
Lithuanian adapted version, 2000. Prepared in accordance with WHO's translation and adaptation requirements by: N. Goštautaitė Midttun, A.Goštautas.
29. WQOQOL-BREF. Introduction, administration, scoring and generic version of the assessment. Programme on Mental Health. Geneva: WHO; 1996.
30.Harper A, Power M. Steps for checking and cleaning data and computing domain scores for the WHOQOL-bref. 2013. Available at: http://www.ufrgs.br/psiquiatria/psiq/whoqol86.html. (Access: 10-02-2016)
31. Dickson A. Health, life-style and quality of life among foreign students of Grodno State Medical University in Belarus and Kaunas University of medicine in Lithuania. eLABa.2011; D:20110628:155819-68259
32. Ducinskiene D, Kalediene R, Petrauskiene J. Quality of life among Lithuanian University Students.
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ANNEX
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Attachment 2: WHOQOL-26 (BREF) questionnaire. Lithuanian adapted version, 2000. Prepared in accordance with WHO's translation and adaptation requirements by: N. Goštautaitė Midttun,
A.Goštautas[28]
30
31 Attachment 4: Bioethics committee permission.
