Whether There Exists a Relationship between Depression and Anxiety - Report Example

Running Head: Research Report Research Report Name Instructor Date Abstract The research report is on the relation of DASS. The three variables are said to be hard to be distinguished according to the self-report measures. This research report does emphasis on the different models that have been so far been used. A literature review is given to analyze the past research on DASS. The students carried out the analysis using questionnaires. The participants were a population of different people in different occupations. The main research question was whether there exist a relationship between depression, stress and anxiety. Six hypotheses were given. The research design factors that were used are confirmatory, cross relational and cross-section. The results obtained were analyzed and discussion is carried out from the results. The research paper also gives implication and recommendations for future design and a conclusion is given too. Table of Contents 1.1 Problem statement 5 1.2 Research question 5 1.3 Hypotheses 5 2.0 Literature review 6 3.0 Method 8 3.1 Participants 8 3.2 Materials 8 3.2.1 Hospital Anxiety and Depression Scale (HADS) 8 3.2.2 Personal Disturbance Scale 9 3.2.3 Positive and Negative Affect Schedule (PANAS) 9 3.3 Data Collection/Procedures 9 3.4 Research Design and Methodology 9 3.5 Measure 11 4.0Results 11 4.1Raw Data 11 5.0 Discussions 13 5.1 Implications 14 5.2Future Research 14 6.0 Conclusion 15 REFERENCES 16 1.0 Introduction Although depression, anxiety and stress are phenomenologically distinct, distinguishing the three items has proven to be quite difficult using the normal methods such as self-report measures and clinical ratings. These methods utilize the aspect of negative affectivity (NA) whereby high NA shows that a patient is experiencing unpleasurable engagement or subjective distress while low NA indicates absence of such feelings (Seaward & Seaward, 2011). On the other hand, the tripartite model introduces another distinguishing factor in addition to the common factors, that is, both depression and anxiety have specific distinguishing factors. The model posits that a distinguishing factor in depression is low positive affectivity (PA) while that of anxiety is physiological hyperarousal. These present some of the attempts that have been explored in the past to try and discriminate depression and anxiety. In the recent past however, development in research has presented yet another instrument that is considerably effective as compared to the other methods, the Depression Anxiety Stress Scale (DASS) (Schaufeli and Kompier, 2001). The Depression Anxiety Stress Scale (DASS) is a 42-item questionnaire that was developed by Lovibond and Lovibond (1995) to assess the negative emotional effects of depression, anxiety and stress (Durand & Barlow, 2011). The instrument comprises of three scales: (1) Depression scale that measures items such as low self esteem, dysphoria and lack of incentive; (2) anxiety scale that is used to detect severe symptoms of fear in addition to subjective and somatic symptoms of anxiety; (3) stress scale used to measure items related to irritability and nervous tension (Lovibond, 1998). Each scale in DASS contains 14 items that are further subdivided into sub-scales of 2-5 items having similar content. DASS demonstrates excellent reliability in all the three scales and effectively distinguishes the three variables. In the recent past, a more simplified form of the former DASS has been developed and is referred to as DASS-21 (Henry & Crawford, 2005). This report will attempt to find out the relationship that exists between the three variables in DASS: Depression, Anxiety and stress by use of a hypothetical research approach. First, a literature review will be presented to shed more light on what literature has detailed concerning the issue under discussion. It will further discuss the research methodology that was utilized with regard to participants, instruments used, research design and procedures followed. Results of the study will be detailed and thereafter discussed. The paper concludes by proposing recommendations on future directions. 1.1 Problem statement Indeed, researchers across the globe have conducted research studies that attempt to discuss various issues underlying DASS. Examples include drawing comparison of DASS, anxiety inventories and Beck depression, confirmatory studies in DASS patients, how DASS has been used to detect depression in employees among other major studies. Drawing from the introductory part of this report, it is quite clear that depression, anxiety and depression have a close relationship and this as triggered many researchers to find ways of distinguishing them. However, very little research has been conducted to find the relationship and it is for this reason that this research was conducted. 1.2 Research question What is the relationship between depression, stress and anxiety? 1.3 Hypotheses H1. High levels of anxiety will be predictive of high level of stress H2. High levels of stress will be predictive of high level of anxiety H3. High levels of depression will be predictive of high level of anxiety H4. High levels of anxiety will be predictive of high level of depression H5. High levels of stress will be predictive of high level of depression H6. High levels of depression will be predictive of high level of stress 2.0 Literature review DASS is also similar to the tripartite model in that it also measures all the three components found in the tripartite model, that is, low affectivity (DASS-Depression), Negative affectivity (DASS-Stress) and physiological hyperarousal (DASS-Anxiety). It is however unclear if the depression and anxiety scales really represent the actual measurements of constructs they were intended to represent. Similarly, it remains debatable if DASS-Stress actually measures psychological distress, that is, negative affectivity or it measures components related to stress and not necessarily negative affectivity Crawford and Henry, 2003). In theory there are many explanations that suggest that the stress scale was indeed developed following items related to anxiety and depression. Empirical studies have showed higher correlation between stress factors with depression and anxiety (Feist & Brannon, 2009). This is contrast to the correlation between depression and anxiety that is quite low. The confirmatory factor analysis has been used to assess the factors structure of DASS-21 so as to understand the relationship between stress and negative affectivity (Routh & Amen, 2004). This study specifically employed the DASS-21 rather than the full-scale version in order to measure its validity in the adult population. Furthermore, factor analytic studies have suggested that the DASS-21 model provides more reliable factor structure in comparison to the DASS-42 model. Past evidence suggests that DASS-42 possesses adequate discriminant and convergent validity from samples acquired from the normal population (Clara et al, 2001). Reliability of the instrument has been tested using the Cronbach’s alpha and has indicated that use of full-length DASS in both non-clinical and clinical samples is acceptable. However, DASS-21reported substantially low correlation of the constructs but was associated with relatively good reliability estimates (Reevy et al, 2010). According to Portman (2009), research studies on DASS have been restricted to age and gender and had overlooked other demographic characteristics that could also be helpful. For instance, in a study conducted by Andrew et al (2000), the depression, stress and anxiety are more prevalent in the elderly and less in the young people. However, many authors have contested with this, arguing that age and gender do not have significant effect on depression, stress and anxiety but rather other mediating factors such as occupation and education (Nezu, 2000). There are four basic studies that have been conducted to measure DASS construct validity and they all have suggested that there is indeed a certain degree of misspecification in the three factor structure describing depression, stress and anxiety. This studies however, have been only been conducted on individuals and none has been done on the general population. 3.0 Method 3.1 Participants For a comprehensive research, a complete DASS data were collected from 45 members of the overall adult of 18 and above year’s population comprising of both females and males. These participants were largely recruited from different sectors namely public service and commercial organizations, recreational clubs as well as community centers. Sue to various ethical considerations that were considered, participation among individual in the selected population was entire voluntary whereby participants were not paid any form of monetary reward. 3.2 Materials Each participant within this research received a DASS form, a form to record various demographic variables as well as an introductory letter. To accompany these documents, participants were supposed to fill and complete two designed self report measures of anxiety and depression and also a measure of both negative and positive affect. These documents are namely; personal disturbance scale, hospital anxiety and depression and finally, the positive and negative affect schedule. Participants were coded in relation to their occupation. 3.2.1 Hospital Anxiety and Depression Scale (HADS) Antony et al (1998) maintain that, this scale was largely developed to provide a means in identifying and measuring severity defined in an anxiety and depression mood especially in a given non-psychiatric clinical atmosphere. The participants were to underline the most appropriate reply which closely matches on how they felt in the previous week. 3.2.2 Personal Disturbance Scale According to Beiling et al (1998), this scale is normally a brief self report measure that consists of seven depression and anxiety measures items. 3.2.3 Positive and Negative Affect Schedule (PANAS) Brown et al asserts that, this is a self report that each participant is expected to feel and it measures both negative and positive affect. This report largely provides an independent measure of both depression and anxiety constructs. 3.3 Data Collection/Procedures Data was collected through the use of survey with major focus on ensuring that the participated within the selected population filled the issued questionnaires. The lecturer was largely involved in the collection of data but was given a helping hand with his students. Further, the lecturer was largely involved in scoring raw data. To begin with, all participants were given a one hour briefing regarding the research to be carried out. Occupation for each participant will be coded basing on the various skills they practiced. Classification of various skills practiced with a participant occupation will be as followed. Retired participants as well as those claiming to be housewives will be coded using their previous job group, those that have never being employed will be coded using the number 5 standing for unskilled, 1 will stand for intermediate, 2 for skilled laborers, 3 for semi skilled laborers, 4 for previous employment (Clara et al, 2001). 3.4 Research Design and Methodology According to Cox et al (1996), to obtain comprehensive results regarding whether there exist a relationship between these three variables namely depression, anxiety and stress it was necessary to use the cross sectional, correlation and confirmatory factor analysis research design. Lovibond and Lovibond (1995) maintain that, this research design is important and it greatly shows whether there exists any form of correlation between these three variables. Also, the design will be able us to build up important facts in relation to our hypotheses namely: H1. High levels of anxiety will be predictive of high level of stress H2. High levels of stress will be predictive of high level of anxiety H3. High levels of depression will be predictive of high level of anxiety H4. High levels of anxiety will be predictive of high level of depression H5. High levels of stress will be predictive of high level of depression H6. High levels of depression will be predictive of high level of stress Based on the methodology, the best method to check if there exist a relationship in the variables stress, anxiety and depression it is the use of DASS. According to Crawford and Henry (2003), DASS will largely be used to the 45 participants’ non clinical sample to broadly represent the overall population mainly in term of variable displayed demographically. For this research, it is necessary that competing models of the latent structure of the methodology that is DASS to be widely derived from both empirical and theoretical sources and which are largely evaluated using the chosen research design that is the confirmatory factor analysis. Endler et al (2003) asserts that, from the research design, the correlation analysis will be used to determine how demographic variables largely influence DASS scores (Barlow & Duran, 2009). Further there is need to examine both the discriminant and convergent validity of the laid measure which was carried out through largely correlating the measures with two other designed measures of both anxiety and depression displayed in both the HADS and sAd as well as the measure of negative and positive affect(PANAS). 3.5 Measure DASS largely consists of three designed self report scales that are largely used in providing pure measures on the three related variable namely stress, anxiety and depression. Each of the scales in DASS comprises of 14 items that are usually subdivided into sub scales consisting of similar content. According to Nieuwenhuijsen et al (2003), the depression scale assesses a participant lack of involvement or interest, inertia, self-deprecation, life devaluation and hopelessness. The stress scale measures the participants’ nervous arousal, easily agitation, difficulty in relaxing as well as impatient and over reacting. Finally, the anxiety scale measures a participant autonomic arousal, situational anxiety, and subjective experience of created by anxious affect skeletal muscle effect and situational anxiety (Nieuwenhuijsen et al, 2003). Evidently, the DASS anxiety and depression scale widely shows good convergent validity with other given scales widely designed to discriminate between effect of both anxiety and depression. The alpha coefficients of the three variables are depression =0.91, stress= 0.90 and anxiety= 0.84 (Endler et al 2003). 4.0Results 4.1Raw Data Depression Anxiety Stress Scale (DASS 21) Population Depression Score Anxiety Score Stress Score 1 0 0 4 2 0 0 4 3 22 6 30 4 0 0 2 5 0 0 2 6 4 0 8 7 4 4 8 8 8 0 8 9 4 2 16 10 0 4 2 11 24 20 24 12 20 20 22 13 12 4 12 14 0 0 2 15 2 0 10 16 6 24 18 17 6 6 8 18 36 16 34 19 4 4 12 20 6 6 14 21 22 28 34 22 34 32 36 23 8 18 10 24 4 0 4 25 18 10 28 26 4 0 6 27 20 14 24 28 12 4 14 29 8 0 6 30 12 8 20 31 12 20 20 32 10 2 10 33 26 12 22 34 2 6 0 35 10 6 14 36 0 2 12 37 28 18 28 38 28 18 28 39 0 6 6 40 12 0 12 41 2 2 12 42 0 4 6 43 2 0 4 44 6 2 4 45 0 0 4 Population Depression Score Anxiety Score Stress Score N=45       M= 23 M=10 M=7 M=13 SD=12.884 SD=10.083 SD= 8.630 SD=9.979 5.0 Discussions The aim of this study was to do an investigation in the relation between anxiety, stress and depression. According to the data that was obtained, there is a significant relation between the variables. In addition, the relation may be stressed by the fact that one variable may be the causative of the other (Ball et al., 2002). For example, stress may be defined as the state of homeostasis disturbance inducing mental and somatic adaptive reactions. Most research done has showed that stress is a major ingredient of depression (Farmer et al., 2003). There are both clinical and preclinical data that have given evidence that stress has been major play in the etiology of depression. In addition, anxiety could also lead to depression (Adlaf et al., 2001). Of important to note is that the two variables share a common distinction in that they cause chronic illness. Anxiety, as many health scholars, has noted is said to be a normal stress response that is experienced by human and animal as well (Corruble et al., 2002). Correlations, as observed from the data have showed that DASS subscales are high. There is higher correlation between the stress factors with depression and anxiety. The correlation of between anxiety and depression is however, low. This was according to the population, that is, between the females and males. These findings are similar to earlier researches that have been carried out by various researchers. There was significant correlation of the subscales (Caplan, 2003). The research has indeed provided the evidence that there is a relation between the three variables. It is of importance to note that depression, anxiety and stress were more prevalent among the elderly and actually less in the young people. Those in occupation that were involving are said to show signs of stress, depression and anxiety as compared to those that whose occupation was not demanding (Clara et al., 2001). Equally, among students, those who had hard times with books did show signs of depression, stress and anxiety as compared to those who had easy times in schools. 5.1 Implications Indeed, given the importance, long term and sensitivity of the diagnostic assessment especially in the counseling, clinical and general settings, effective measures are needed to provide remedial and supportive services especially in the field of psychology. Therefore the study of DASS is effective in the above fields (Armstrong, et al., 2007). 5.2Future Research Several limitations need to be noted to provide basic direction for future research. The testing could have been grouped, that is, males and females. This could have provided accurate information on how the three variables are related. In addition, the testing could have involved different age groups and health occupations to give a clear relation of the variables (Malhi et al., 2007).Consequently, the study could have also investigate whether DASS is invariant across healthy, clinical and cultures populations. Samples should have taken from those people suffering from depression, anxiety and stress.This would provide adequate data on how the DASS research would be intensified to answer questions whether it showed be viewed a serious syndrome or otherwise (Newman & Newman, 2011). Another suggestion, for future research, it was also could have given the factors that cause DASS and copying with the DASS. Language could also been a major issue in answering the questions (Malhi et al, 2000). This could have resulted to distorted information. It is therefore, desirable that future study to involve translators. Also, longer version should be used rather than shorter versions. Finally as the study utilized correlational statistics, no definite statements were given on the casualties (Endler et al., 2003). 6.0 Conclusion In conclusion, the study reports that anxiety, depression and stress variable are correlated. The participants were males and females who were above the age of 18. The participants were recruited from different organizations and participation was voluntarily. Questionnaires were randomly given to the students who participated in the testing. Six hypotheses were given and the research question stated. The materials used were DASS formed that needed to be filled by the participants. From the analysis carried out it was proved that there is a relationship between stress, depression and anxiety. DASS has been defined as the measure of distress along the following axes: depression, stress and anxiety. However, it is said not to be a measure of any clinical diagnoses. The study has provided an indication of the correlation and can be used in research. However, several limitations have been evidence in the report. DASS has also proved to be a significant tool in the measurement of anxiety, depression and stress in the population. Recommendations have also been given for further research on the same study. These include involving diverse population, occupation, age, culture and health factors. REFERENCES Adlaf, E. M., Gliksman, L., Demers, A. e., & Newton-Taylor, B. (2001). The prevalence of elevated psychological distress among Canadian undergraduates: Findings from the 1998 Canadian Campus Survey. Journal of American College Health. Andrew, J., Baker, A., Kneebone, C., & Knight, L. (2000). Mood state as a predictor of neuropsychological deficits following cardiac surgery. Journal of Psychosomatic Research,volume 48, 537–546. Antony, M, Bieling, P, Cox, B, Enns, M and Swinson, R. (1998). Psychometric properties of the 42-item and 21-item versions of Depression Anxiety Stress Scales in clinical groups and a community sample. Psychological Assessment, 10, 176-181. Armstrong, L., Phillips, J., & Saling, L.,(2000). Potential determinants of heavier internet usage. International Journal of Human-Computer Studies. Ball, S., Smolin, J., & Shekhar, A. (2002). A psychobiological approach to personality: examination within anxious outpatients. Journal of Psychiatric Research, 36(2) Barlow, D, Durand, V., (2009). Essentials of Abnormal Psychology, London: Cengage Brian Beiling, P, Antony, M and Swinson, R. (1998). The State-Trait Anxiety Inventory, Trait version: Structure and content re-examined. Behaviour Research and Therapy, 36, 777-788. Brown, T, Chorpita, B, Korotitsch, W and Barlow, D. (1997). Psychometric properties of the Depression Anxiety Stress Scales (DASS) in clinical samples. Behaviour Research and Psychiatry Rep 2: 165–169. Caplan, S. E., (2003). Preference for online social interaction: A theory of problematic internet use and psychosocial well-being. Communication Research, 30, 625–648. Clara I. P., Cox, B. J., & Enns, M. W. (2001). Confirmatory factor analysis of the Depression anxiety Stress Scales in depressed and anxious patients. Journal of Psychopathol Beheavior. Corruble, E., Duret, C., Pelissolo, A., Falissard, B., & Guelfi, J. D. (2002). Early and delayed personality changes associated with depression recovery? A one-year follow-up study. Psychiatry Research, 109(1). Cox, B, Cohen, E, Direnfeld, D and Swinson, P. (1996). Does the Beck Anxiety Inventory measure beyond panic attack symptoms? Behaviour Research and Therapy, 34, 949-954. Crawford, J and Henry, J. (2003). The Depression Anxiety Stress Scales (DASS): Normative data and latent structure in a large non-clinical sample. British Journal of Clinical Psychology, 42, 111-131. Durand, M, Barlow, D., (2011). Abnormal Psychology: An Integrative Approach, London CengageBrian Endler, N, Macrodimitris, D and Kocovski, L. (2003). Anxiety and depression: Congruent, separate, or both? Journal of Applied Biobehavioural Research, 8(1), 42-60. Farmer, A., Mahmood, A., Redman, K., Harris, T., Sadler, S., & McGuffin, P. (2003). A sib-pair study of the Temperament and Character Inventory scales in major depression. Archives of General Psychiatry, 60(5), 490-496. Feist, J, Brannon, L, (2009). Health Psychology: An introduction to Behavior and Health, London: CengageBrain. Henry, J. and Crawford, J. (2005). The short-form version of the Depression Anxiety Stress Scales (DASS-21): Construct validity and normative data in a large non-clinical sample. British journal of clinical psychology, volume 44, 227-239. Lovibond, P. (1998). Long-term stability of depression, anxiety, and stress syndromes. Journal of Abnormal Psychology, volume 107, 520–526. Lovibond, S. H., & Lovibond, P. F.(1995). Manual for the Depression Anxiety Stress Scales. (2nd. Ed.). Sydney: Psychology Foundation. Malhi G, S, Moore J, McGuffin P (2000). The genetics of major depressive disorder. Curr Malhi, J. Y., Ko, C. H., Yen, C. F. et al., (2007). The comorbid psychiatric symptoms of Internet addiction: Attention deficit and hyperactivity disorder (ADHD), depression, social phobia, and hostility. Journal of Adolescent Health, 41(1). Newman, P, Newman, B., (2011). Development Trough Life: A Psychosocial approach, London: CengageBrian. Nezu, A. (2000). Practitioner’s guide to empirically based measures of depression. New York: Plenum Publishers. Nieuwenhuijsen, K, De Boer, A, Verbeek, J, Blank and Dijik, F. (2003).The Depression Anxiety Stress Scales (DASS): Detecting anxiety disorder and depression in employee absent from work because of mental health problems. Occupational Environmental Medicine, 60,177-182.Therapy, 35, 79-89. Portman, M. (2009). Generalized anxiety disorder across the lifespan: an integrative approach. New York: Springer. Reevy, G., Ozer, Y. and Ito, Y. (2010). Encylopedia of emotion. Santa Garbara: Greenwood. Routh, L, Amen, D., (2004). Healing anxiety and depression, New York: Wiley & sons, Inc Schaufeli, B. and Kompier, J. (2001). Managing job stress in the Netherlands. International Journal of Stress Management, volume 8, 15–34. Seaward, B, Seaward, L., (2011). Managing Stress: Principles and Strategies for Health and Well-Being, New York: Wiley & Sons, Inc. Read More

1.1 Problem statement Indeed, researchers across the globe have conducted research studies that attempt to discuss various issues underlying DASS. Examples include drawing comparison of DASS, anxiety inventories and Beck depression, confirmatory studies in DASS patients, how DASS has been used to detect depression in employees among other major studies. Drawing from the introductory part of this report, it is quite clear that depression, anxiety and depression have a close relationship and this as triggered many researchers to find ways of distinguishing them.

However, very little research has been conducted to find the relationship and it is for this reason that this research was conducted. 1.2 Research question What is the relationship between depression, stress and anxiety? 1.3 Hypotheses H1. High levels of anxiety will be predictive of high level of stress H2. High levels of stress will be predictive of high level of anxiety H3. High levels of depression will be predictive of high level of anxiety H4. High levels of anxiety will be predictive of high level of depression H5.

High levels of stress will be predictive of high level of depression H6. High levels of depression will be predictive of high level of stress 2.0 Literature review DASS is also similar to the tripartite model in that it also measures all the three components found in the tripartite model, that is, low affectivity (DASS-Depression), Negative affectivity (DASS-Stress) and physiological hyperarousal (DASS-Anxiety). It is however unclear if the depression and anxiety scales really represent the actual measurements of constructs they were intended to represent.

Similarly, it remains debatable if DASS-Stress actually measures psychological distress, that is, negative affectivity or it measures components related to stress and not necessarily negative affectivity Crawford and Henry, 2003). In theory there are many explanations that suggest that the stress scale was indeed developed following items related to anxiety and depression. Empirical studies have showed higher correlation between stress factors with depression and anxiety (Feist & Brannon, 2009).

This is contrast to the correlation between depression and anxiety that is quite low. The confirmatory factor analysis has been used to assess the factors structure of DASS-21 so as to understand the relationship between stress and negative affectivity (Routh & Amen, 2004). This study specifically employed the DASS-21 rather than the full-scale version in order to measure its validity in the adult population. Furthermore, factor analytic studies have suggested that the DASS-21 model provides more reliable factor structure in comparison to the DASS-42 model.

Past evidence suggests that DASS-42 possesses adequate discriminant and convergent validity from samples acquired from the normal population (Clara et al, 2001). Reliability of the instrument has been tested using the Cronbach’s alpha and has indicated that use of full-length DASS in both non-clinical and clinical samples is acceptable. However, DASS-21reported substantially low correlation of the constructs but was associated with relatively good reliability estimates (Reevy et al, 2010). According to Portman (2009), research studies on DASS have been restricted to age and gender and had overlooked other demographic characteristics that could also be helpful.

For instance, in a study conducted by Andrew et al (2000), the depression, stress and anxiety are more prevalent in the elderly and less in the young people. However, many authors have contested with this, arguing that age and gender do not have significant effect on depression, stress and anxiety but rather other mediating factors such as occupation and education (Nezu, 2000). There are four basic studies that have been conducted to measure DASS construct validity and they all have suggested that there is indeed a certain degree of misspecification in the three factor structure describing depression, stress and anxiety.

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