Exploring Gender Distribution in Anxiety Spectrum through Factor Analysis among Dental Students

Ambrina Qureshi1                              BDS, M.Phil
Muhammad Mohsin Haider2        BDS, MS, MCPS, FCPS
Rahmatullah Khan3                          BDS, FCPS                                  

INTRODUCTION

Anxiety is an emotional state characterized by an unpleasant state of inner turmoil and often accompanied with a tendency to repetitively think about consequences of expected future threats.1,2 This may arise as a result of consequences of one’s negative emotional experiences ever occurred at any point of time; such as one’s academic performance experienced. Mental health of University students is an area of increasing worldwide concern as this population has been shown to be particularly prone to depression, anxiety and stress. Factors may be academic pressures, obstacles to their goal achievements, environmental changes and life challenges such as transition from school to university and the change in role from student to a knowledgeable physician.3

Several students admitted in medical and dental schools may experience performance pressure in order to do good in their academics due to their desire to satisfy the value of helping people, get good jobs, and accomplish a stable monetary future.4,5 Many studies have been reviewed to assess altered psychological health status among medical and dental students globally.6 A prospective study conducted on students entering into clinical training has reported burnout and psychiatric ill health as a result of psychological distress.7 Dental students plays a pivotal role in of health care system, especially when they are most of the time dealing with already much anxious patients. It is documented that when denta lstudents treat their patients with confidence, the patient feels relaxed, satisfied and show greater compliance with the treatment.8 Therefore, assessment of anxiety among dental students is a much needed area of research. A number of studies have been conducted to assess the anxiety level among dental students using self-reported anxiety questionnaire. However, none so far has attempted to cluster these variables into homogenous sets that allow gain an insight to the categories of such emotions. Therefore, this study was conducted with 2-fold objectives, that is, to establish clustered categories of anxiety related emotions among dental students and observe gender distribution with respect to the predicted categories of anxiety.

METHODOLOGY

This cross sectional observational survey was conducted based on routine institutional based feedback evaluation among a sample of dental students selected from Public Sector University of medical and dental sciences. Prior institutional permission was taken to conduct this survey and appropriate ethical approval was taken. Sample size calculated was 200 based on a previous study9 with almost equal number of male and female students. Sample size was calculated using Open Epi with appropriate formula (Z∞/2+Zβ) 2*2*σ2 /d2 ) keeping confidence interval 90% and power 80% with means (females=13.1±208; males= 11.9±209). After seeking permission for data collection students who consented were asked to participate. The data was collected in two weeks. The students who were regularly attending lectures, practical and clinical rotations who gave informed consent were included. The participation in the study was on voluntary basis, subjects were informed about the protocols of the survey and whoever wanted to withdraw even from the middle of the survey were free to quit. The participants excluded were the students who were suffering from any type of stress or psychological treatments or on drugs. Students who were irregular or did not give consent who refused to fill the questionnaire were also excluded. Corah’s Dental Anxiety Questionnaire10,11 (DASS 21) was used, which is a self-reported questionnaire consisting of 21 questions related to anxiety. The Depression, Anxiety and Stress Scale – 21 Items (DASS21) are a set of three self-report scales designed to measure the emotional states of depression, anxiety and stress. It consists of 21 questions, seven questions each on depression, anxiety and stress.

The depression scale assesses dysphoria, hopelessness, deflation of life, self-deprecation, and lack of interest/ involvement. The anxiety scale assesses autonomic arousal, skeletal muscle effects, and situational anxiety. The stress scale is sensitive to levels of chronic non-specific arousal. It assesses difficulty relaxing, nervous arousal, and being easily upset, irritable, and impatient. Scores for depression, anxiety and stress are calculated by summing the scores for the relevant items and multiplied by 2 to calculate the final score.

Statistical analysis was performed on Stata 11.0 using Exploratory Factor Analysis (EFA) after examining correlation matrix through polychoric correlation test (p < 0.05) and Kaiser-Meyer-Olkin (KMO) test of sample adequacy. KMO value > 0.5 was considered as sufficient for the sample size selected (n=200). Eigen value >1 was considered significant criteria for extraction of factors using Principal Component Analysis (PCA) and a scree graph was plotted accordingly. Varimax method was used for factor rotation and a criterion of 0.40 was used for significant factor loading according to the sample size.12After refining, the significant loaded factors were labeled. Subsequently, predicting the factors, three cutoff groups for each factor were generated in order to observe distribution of stress factors in accordance with the gender (male, female).

RESULTS

Final factor analysis was performed on n=190 (male: female= 1:1) students with a response rate of 95%. The overall significance of correlation matrix was <0.001 and KMO measure of sampling adequacy was 0.83 (minimum= 0.56, maximum= 0.91). Therefore, all questions (DASS21) were included for EFA. According to the scree graph plotted Fig. (1), six factors (factor1 – factor6) were extracted. The test of significance for the six retained factors in the model was p<0.0001 (LR Chi2=900) and variance more than 1 (range= 1.25-2.91). After re-distribution of the factors, much relevance was observed for the questions to be in the factor model, with maximum uniqueness of 73% and that too only in one variable (Q4). Table 1 presents suggested labels for respective loaded factors. Box plot Fig. (2) is given to understand the anxiety spectrum distribution with respect to gender (male, female).

DISCUSSION

DASS21 is used to assess negative psychological health aspects or simply negative emotional states namely depression, anxiety and stress. DASS21 is a 21-question scale that is comprised of 7 questions that are summed for each subscale of depression, anxiety and stress. DASS-21 has good psychometric properties, with reliability coefficients ranging from 0.82 to 0.90 in each subscale.13 Applicability of DASS21 varies across the globe. Some authors found DASS21 scale to be more effective in detecting psychiatric disorders. One such study found DASS21 to be more comprehensible and sensitive in detecting mental disorders in low socio-economic population of Vietnam.14Another study in 2011 in Australia used DASS21.

in patients with low back pain concluded that the scale was effective in demonstrating the sub-scale of depression.15 DASS has been used among different geographic locations is very effectively. A study in 2015, used DASS21 in adolescents from 4 different countries of the globe (Australia, Chile, China, Malaysia) Using Confirmatory Factor Analysis, it was concluded that DASS21 was suitable for use in these geographics.16 Variation in cultures plays important role in DASS21 application. The manner, in which people talk about distress, how they perceive and define them, will be a function of his/ her culture. Researchers need to work on proper validation when employing Western based assessments to Asian cultures.17The aim of the study was to establish clustered categories related to emotions among Pakistani dental students and assess gender distribution with respect to those categories using factor analysis. Large datasets that consist of several variables can be reduced by observing ‘clusters’ of variables that is, factor analysis assembled common variables into descriptive categories. There are two main factor analysis techniques are Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). CFA attempts to confirm hypotheses and uses path analysis diagrams to represent variables and factors, whereas EFA tries to uncover complex patterns by exploring the dataset and testing predictions18 When the factor rotation was performed, the maximum uniqueness found in the variable related to ‘breathing difficulty’ which indicates how strongly the factor influences the measured variable. Naming of factors is more of an ‘art’ as there are no rules for naming factors, except to give names that best represent the variables within the factors. One way of labeling is to observe the factor patterns and on the basis of the items which load highly on factors, determine common characteristics and whatever the items have in common will indicate the meaning of the factor.19 Some researchers found DASS to be much effective, some studies also found overall DASS, or its subscale, as a weak indicator. One Malaysian study found insignificant results using factor analysis in Malaysian adolescents.20Marianna Szabo used factor analysis in her study on young adolescents in 2010, Australia concluded that one of the sub-scale Stress/ Tension needs further refinement.21 When the gender distribution of extracted factors were observed in accordance with the gender, it was found that three of the factors “Nervousness”, “Panicky” and “Touchiness” were more dominant in females, showing higher values. Psychological and psychometric distribution between males and females has various dimensions. Presumably, males are from Mars and females are from Venus, males are strong and females are flexible, males competitive and females are cooperative, males are dominant females are submissive. Males and females are different in psychological and physiological and psychometric characteristics which is supported by gender differences hypothesis22 Meta-analysis is a pivotal tool in observing gender distribution in various dimensions23 such as math performance, cooperation, impulsivity, self-conscious emotions, language use, and interests, sexual attitudes and behaviours.24 Using psychometric tests for assess gender distribution has been done in previous studies as well. One study concluded that women with young children, living in rural low income populations had higher DASS scores.16, 25 Apart from gender depression, anxiety and stress may also be affected by other demographics like age, education, illness, occupation, marital status. A study conducted in Wazirabad city of Pakistan in 2013 is in consistent with this finding.26 This study accompanied some limitations. As no other demographics were recorded so DASS used to assess gender differences among the dental students did not precisely pinpoints why the gender differences occurred and no in-depth detailed interview was conducted to know why they experienced anxiety, depression and stress. Future recommendations should be made to assess the theories regarding the similarities and dis-similarities of gender. Separate year wise assessment of dental anxiety from first year to final year and house-job level should be made, so that a proper plan of action can be made to counteract anxiety, depression and stress at each academic level. Furthermore a detailed panoramic interview including student’s socio demographics, academic vacation schedules, tests and exam scores is recommended and confirmatory factor analysis may
be done for evaluating and establishing association with such emotional states. Similar researches may be conducted in Pakistan in order to attain anxiety level among dental students countrywide which may be presented at national level.

CONCLUSION

This factor analysis suggests that there is a room for improvement in DASS21 by defining a spectrum of anxiety. Gender distribution have been found significant with respect to self-competency and found to be related to anxiety and depression among adolescents.Female dental students were more anxious than their counterpart. Enhancing education, awareness, improving teaching methods and training of dental procedures might help alleviate anxiety.

CONFLICT OF INTEREST

None declared.

REFERENCES

1. Seligman MEP, Walker EF, Rosenhan DL. Abnormal psychology (4th edition). New York: W.W. Norton & Company 2000.
2. American Psychiatric Association; Diagnostic and Statistical Manual of Mental Disorders (5th edition). Arlington, VA: American Psychiatric Publishing 2015, p.189.
3. Saravanan C, Wilks R. Medical Students’ Experience of and Reaction to Stress: The Role of Depression and Anxiety. Sci World J 2014; 2014: 737382.
4. Al-Bitar, Z, Sonbol H, Al-Omari I. Reasons for choosing dentistry as a career by Arab dental students. Euro J Dent Edu 2008; 12: 247-251.
5. Millan L, Azevedo R, Rossi E, De Marco O, Millan M, Arruda, P. What is behind a student’s choice for becoming a doctor? Clinics 2005; 60: 143-150.
6. Dyrbye L N, Thomas M R, Shanafelt T D.Systematic review of depression, anxiety, and other indicators of psychological distress among US and Canadian medical students. Acad Med 2006; 81: 354-373
7. Dahlin M E, Runeson B. Burnout and psychiatric morbidity among medical students entering clinical training: a three year prospective questionnaire and interview-based study. BMC Med Edu 2007; 7: 6.
8. Ten Berge M, Veerkamp J, Hoogstraten J. Dentist’s behaviour in response to child dental fear. J Dent Children 1999; 66: 36-40,12.
9. Farooq I, Ali S. A cross sectional study of gender differences in dental anxiety prevailing in the students of a Pakistani dental college; Saudi J Dent Res 2015; 6: 21- 25.
10. Lovibond PF, Lovibond SH. The structure of negative emotional states: comparison of the Depression Anxiety Stress Scales (DASS) with the beck depression and anxiety inventories. BehavRes Therap 1995; 33: 335- 342.
11. Corah NL. Development of a dental anxiety scale. J Dent Res 1969; 48; 596.
12. Hair J F. Tatham R L. Anderson R E, Black W. Multivariate Data Analysis (5th Edition). Upper Saddle River, NJ; Prentice Hall 1998.
13. Henry J D, Crawford J R. The short-form version of the Depression Anxiety Stress Scales (DASS-21): Construct validity and normative data in a large non-clinical sample.Brit J Clinl Psycho 2005; 44: 227-239.
14. Thach D T, Tuan T, Jane F. Validation of the depression anxiety stress scales (DASS) 21 as a screening instrument for depression and anxiety in a rural community-based cohort of northern Vietnamese women. BMC Psychia 2013; 13:24.
15. Parkitny L, McAuley J H, Walton D, Pena Costa L O, Refshauge K M, Wand B M, Pietro F D, Moseley G L. Rasch analysis supports the use of the Depression, Anxiety, and Stress Scales to measure mood in groups but not in individuals with chronic low back pain. J Clin Epid 2011; 66: 189-198.
16. Mellor D, Vinet E, Xu X, Hidayah N, Andrew B, Francisa M. Factorial Invariance of the DASS-21 among Adolescents in Four Countries.Euro J Psychol Assess 2015; 31: 138-142.
17. Tian PSO, Sukanlaya S, Yong WG, Firdaus M. Using the Depression Anxiety Stress Scale 21 (DASS-21) across cultures. Int J Psychol 2013; 48(6): 1018-1029.
18. Child D. The essentials of factor analysis (3rdedition). New York. NY: Continuum International Publishing Group 2006.
19. Fabrigar L R, Wegener D T, MacCallum, R C, Strahan E J. Evaluating the use of exploratory factor analysis in psychological research. Psychol Meth 1999; 4: 272-299.
20. Hashim H A, Golok F, Ali R. Factorial Validity and Internal Consistency of Malaysian Adapted Depression Anxiety Stress Scale – 21 in an Adolescent Sample. Int J Collab Res Intern Med Pub Health 2011; 3.
21. Szabo M. The short version of the Depression Anxiety Stress Scales (DASS-21): Factor structure in a young adolescent sample. J Adolesc 2010; 33:1-8.
22. Gray J. Men are from Mars, women are from Venus: A practical guide for improving communication and getting what you want in your relationships. New York. NY: Harper Collins. 1992.
23. Hyde JS. Gender similarities and differences. Ann Rev Psychol 2014; 65: 373-398.
24. Ethan Z, Zlatan K, Teeter SR. Evaluating Gender Similarities and Differences Using Meta synthesis. Am Psychol Assoc 2015; 70: 10 20.
25.  Andreou E, Alexopoulos EC, Lionis C, Varvogli L, Gnardellis C, Chrousos G P, Darviri C. Perceived Stress Scale: Reliability and Validity Study in Greece; International J Environ Res Pub Health 2011; 8: 3287- 3298.
26. Riaz A, Kamal S, Butt N S. Psychometric analysis of Depression, Anxiety and Stress among Women of Wazirabad City. Casp J App Sci Res 2013; 2: 61-68, 201.

1. Professor, Department of Community Dentistry, Dr.IshratUlEbad Khan Institute of Oral Health Sciences, DUHS, Karachi, Pakistan
2. Masters Trainee, Department of Community Dentistry, Dr. IshratUlEbad Institute of Oral Health Sciences, DU HS, Karachi Pakistan.
3. Assistant Professor, Department of Operative Dentistry, Frontier Medical & Dental College, Abbottabad, Pakistan.
Corresponding author: “Dr. Ambrina Qureshi” < ambrina.qureshi@duhs.edu.pk >