Psychological Assessment – A North Queensland Case Study
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This study aims to validate DASS-21, its internal consistency, convergent and discriminant validity and factor structure for North Queensland population.
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Psychological Assessment – A North Queensland Case Study By (Name of Student) (Institutional Affiliation) (Date of Submission)
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Psychometric Validation of DASS21 in North-Queensland Introduction DASS-21 is a 21-item self-report questionnaire that contains a three Seven -item scale that measures depression, stress and the anxiety (Henry & Crawford, 2005). This scale has not yet been validated for North Queensland population despite the fact that DASS-21 was found to have sufficient psychometric features (Antony, Bieling, Cox, Enns & Swinson, 1998). This work thus aims to validate DASS, its internal consistency, convergent and discriminant validity and factor structure for North Queensland population. This study established a strong positive correlation and convergent validity with BASIS-24, a mental illness measure. Also, DASS-21 established discriminant validity with MHC-SF, a measure of positive well-being.
Depressioncan be defined as a mood disorder bounded as a determined state of low mood and anhedonia (Tully, 2009). According to Clark & Watson (1991), a positive effect is either low or absent when experiencing depression and thus those people experience loss of self-esteem, a sense of hopelessness and dysphonia. Anxietyon the other hand is defined as a state of autonomic arousal and fearfulness that is out of bound and proportion.Stress is well-defined by persistent muscle tension, irritability, and a low threshold for becoming upset or frustrated (5th ed.; DSM–5; APA, 2013). It is associated to the negative effects as observed in generalized anxiety disorders (Clark & Watson, 1991). According to Kaspe (2005), anxiety and depression are believed to be the two primary roots of mental illness disorders, and often co-occur, which led to explain the common features of anxiety and depression. Many developed nations such United States and Australia, face the problem of increasing mental illnesses such as depression and anxiety (Edmunds, 2018). Accordingly, the Australia’s estimated annual expenditure on curing mental illness has now risen to a whopping twenty billion (National Mental Health report, 2013). Clark and Watson (1991) thus asserted that anxiety and depression can be notable by unique characteristics and proposed a tripartite framework of anxiety and depression that consist of positive affect,physiological hyper arousal, and general distress. This is in conformity with three psychometrically distinct factors namely depression, anxiety and stress which are also primary constructs of the Depression Anxiety Stress Scale (DASS) (Brown, Chorpita, Korotitsch & Barlow, 1997). DASS-42 was developed as a screening tool for depression and anxiety disorders. Psychometric validation has provided strong support for the scale’s internal consistency and its convergent and discriminant validity with other existing measures like Beck Depression and Anxiety Inventories in clinical and non-clinical samples (Lovibond & Lovibond, 1995).
Exploratory and confirmatory factor analyses of DASS-42 items have consistently reproduced the three-factor structure in large nonclinical samples (Antony, Bieling, Cox, Enns & Swinson, 1998). DASS-21, a shortened version of DASS-42, has fewer items, which revealed cleaner factor structure and produced smaller inter-factor correlations, and was subsequently adopted by numerous studies. DASS-21 has also been found to have strong internal consistency (Henry & Crawford, 2005), convergent validity (Le et al., 2017) and discriminant validity (Osman et al., 2012).Conducted factor analysis investigation revealed that DASS-21 components were explicitly clustered into three sub-scales which measure depression, anxiety and stress. The Depression scale measures symptoms associated with worthlessness or sadness. The Anxiety scale included symptoms of fear, panic attacks, and physical arousal. The Stress scales included symptoms such as irritability, overreaction, and tension (Henry, & Crawford, 2005). DASS-21 has been verified across a multitude of populations and proven useful (Azma, Rusli, Quek, & Noah, 2014; Tran, Tran & Fisher, 2013; Teo et al., 2018). Demographically, DASS-21 has also proven its validity through several Australian studies on various groups to analyze the severity of depression, anxiety and stress. More recent Australian studies include outpatient chemotherapy patients from Western Australia hospitals (McMullen et al., 2017), patients undergoing traumatic brain injury rehabilitation from New South Wales hospitals (Randall, Thomas, Whiting & McGrath, 2017), registered nurses (Hegney et al., 2014), Australian mothers (Lovell, Huntsman & Hedley-Ward, 2015) as well as younger and older adolescents (Tully, Zajac & Venning, 2009; Shaw, Campbell, Runions & Zubrick, 2017). Currently it is deemed that there is lack of validation in the North Queensland population. Given the potential usefulness for research and clinical screening in North Queensland, it is important to further examine the psychometric properties of the DASS-21
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and its applicability in that context. To that end, DASS-21 was equated with other scales namely MHC-SF and BASIS-24. The four hypotheses in this study were; H1:DASS-21 exhibits reliability H2: There exists convergent validity with BASIS-24 H3: There exist divergent validity with MHC-SF H4: There exist a three pure factor structure of DASS-21. Methods Participants Participants (n= 171) aged 18–62 (M= 31.09,SD= 11.27), having 75.4% of female (n= 129) respondents took part in the questionnaire. Participants were mostly native to Australia (n=149) and mostly employed (n=110). Their education level varies in nature. Table 1 indicates participants’ ethnicities. Table 1:Ethnicity of Participants AustralianAboriginal or Torres Strait Islander Another cultural group Total Number149319171 Percentage87.11.811.1100 Table 2 indicates participants’ current employment status. One of the participant’s data was missing. Table 2 Current employments Status of Participants
Employed Unemployed StudentPensionerRetired None of the Above Number110 14 39511 Percentage 64.322.82.9.6.6 Table 3 indicates education level of participants. Table 3 Education Level of Participants High School (grade 10) Senior High School (grade 12) TAFEUniversity degree - undergraduate (e.g. Bachelor) University degree - postgraduate (e.g. Honours, Masters, PhD None of the above Number27603629163 Percentage15.835.121.117.09.41.8 Measures Depression, Anxiety and Stress Scale (DASS-21):DASS-21 (Henry & Crawford, 2005) is a 21-item quantitative self-reporting questionnaire consisting of three 7-item scale measuring depression, anxiety and stress along a 4-point Likert scale with 0 –“Did not apply to me at all”to 3 –“Applied to me very much, or most of the time.”Scores for each subscale are summed and multiplied by two, where higher score signify greater severity of symptoms. Face validity appeared to be acceptable. The short form of the Mental Health Continuum (MHC-SF) Scale:The MHC-SF (Lamers, Westerhof, Bohlmeijer, Klooster & Keyes, 2010) was used to evaluate the
discriminant validity of the DASS-21. It is a 14-item quantitative self-report questionnaire measuring mental health and well-being comprising of three measures on emotional wellbeing (EWB), six on psychological well-being (PWB), and five on social well-being (SWB), rating the frequency in the past month along a 6-point Likert scale ranging from 0 – ‘‘never’’to 5 –‘‘every-day.’’Items in each dimension were summed. Higher ratings indicated higher levels of well-being. MHC-SF exhibited high internal consistency with an overall Cronbach’s alphaof above .74 for both the subscale and total scale of well-being, therefore the scale is reliable. Further, moderate test-retest reliability suggests that the MHC-SF is both sensitive and stable to changes over time. Convergent validity was established with respect to wellbeing and functioning. Discriminant validity was reported whereby mental illness was negatively and moderately correlated to positive mental health in the MHC-SF. The Behaviour and Symptom Identification Scale (BASIS-24): BASIS-24 was used to evaluate the convergent validity of the DASS-21 (Cameron et al, 2007). It is a 24-item self- reporting questionnaire measuring six subscales namely psychiatric, substance abuse and functioning such as depression, relationships, self-harm, emotional ability, psychosis, and substance abuse, rated along a 5-point Likert scale with scores ranging from 0 –“no difficulty/symptoms never present”to 4 –“extreme difficulty/symptoms always present”. Six items require reverse scoring and a mean score is calculated for each subscale and also for the total scale. Higher scores represent greater severity of the symptoms and problems. Psychometric properties of BASIS-24 suggest high internal consistency with a Cronbach’s Alpha of .75 to .91. A change of .56 had also been reported suggesting the scale being responsive to change indicating an effect size. Therefore, concurrent criterion validity was established.
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Procedure Approval for ethical compliance was first obtained from the James Cook University Human Research Ethics Committee. Upon approval, the DASS-21, MHC-SF and BASIS-24 questionnaire were uploaded on a web link which was provided to participants who were recruited via snowball sampling. Informed consent was obtained from participants. Data were collected and analyzed after response submission. Results All statistical analyses were performed using IBM SPSS Statistics version 23. Out of sample size of 171, one participant data was excluded from the analysis as it was an outlier. Therefore, sample size for analysis was 170. Descriptive statistic, reliability analysis and factor analysis were conducted. Convergent and discriminant validity were also conducted using Pearson product-moment correlation analysis. Descriptive statistic for Measures Descriptive statistics of DASS-21, BASIS-24, and MHC-SF are reported in the Subsequent tables (Table 4, 5 and 6). Table 4 Minimum and maximum values, mean and standard deviation for the DASS-21 MinimumMaximumMeanStd. Deviation Depression Subscale 7.0028.0012.03535.11049 Anxiety Subscale 7.0028.0010.53534.21486 Stress Subscale7.0028.0013.19414.71219 Total Score21.0084.0035.764712.71131 Table 5 mum values, meanand standard deviation for the MHC-SF
Minimum and maxi MinimumMaximumMeanStd. Deviation Emotional Well- 3.00 being Subscale 18.0013.69413.27271 Social Well- 5.00 being Subscale 30.0017.14716.02918 Psychological Well-being6.00 Subscale 36.0026.41186.64803 Table 6 Minimum and maximum values, mean and standard deviation for BASIS-24 MinimumMaximumMeanStd. Deviation Depression & Functioning Subscale 7.0035.0014.79646.15907 Interpersonal Relationships Subscale 5.0021.008.43533.85368 Self-harm Subscale 2.0010.002.84621.98206 Emotional Liability Subscale 3.0015.006.46472.86820 Psychotic Symptoms Subscale 4.0020.005.64123.67714 Alcohol/Drugs Subscale 4.0020.006.03533.94923 Total Score25.00111.0044.305416.99245 Total Score14.0084.0057.252914.37826
Hypothesis 1:DASS-21 exhibits reliability The Cronbach alpha for DASS-21 on overall and individual subscales were high and positive. Overall it is .951, for depression it is .927, for anxiety it is .860, for stress it is .892. Hypothesis 2:There exists convergent validity with BASIS-24 Pearson product-moment correlation coefficient between the subscales of DASS-21 and BASIS-24 were conducted to establish the convergent validity of DASS-21. All coefficients indicated that there exists moderate to strong positive correlation. It was also established that two tailed correlation was significant atp<0.01. Depression and Functioning subscale of BASIS-24 has the highest correlation with DASS-21, while the alcohol/drugs subscale of BASIS-24 has the least correlation with DASS-21. Table 7 report the correlation coefficient values between DASS-21 and BASIS-24. Table 7 Convergent Validity of the DASS-21 DASS-21 Depression Subscale DASS-21 Anxiety Subscale DASS-21 Stress Subscale DASS-21 Total BASIS-24 Depression & Functioning Subscale .792**.671**.756**.819** BASIS-24 Interpersonal Relationships Subscale .747**.602**.661**.745** BASIS-24 Selfharm Subscale .439**.295**.331**.397**
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BASIS-24 Emotional Liability Subscale .579**.537**.665**.657** BASIS-24 Psychotic Symptoms Subscale .299**.251**.296**.313** BASIS-24 Alcohol/Drugs Subscale .236**.246**.282**.281** BASIS-24 Total.731**.621**.713**.762** **Correlation is significant at the 0.01 level (2-tailed) Hypothesis Three: There exists divergent validity with MHC-SF Pearson product-moment correlation coefficientbetween the subscales of the DASS- 21 and MHC-SF were conducted which provided evidence for divergent validity of DASS-21. All coefficients indicated moderate negative correlation. Further, the established two tailed correlation was significant atp<0.01 level (see Table 8 for report of values). Table 8 Divergent Validity of DASS-21 DASS-21 Depression Subscale DASS-21 Anxiety Subscale DASS-21 Stress Subscale DASS-21 Total MHC-SF Emotional Wellbeing Subscale -.696**-.459**-.495**-.615** MHC-SF Social Well-being Subscale -.492**-.358**-.392**-.462**
MHC-SF Psychological Well-being Subscale -.678**-.414**-.475**-.586** MHC-SF Total-.678**-.446**-.497**-.605** **Correlation is significant at the 0.01 level (2-tailed) Hypothesis Four: There exist 3 factor structure of DASS-21 To investigate and explore the underlying structure of the 21-item in the DASS-21 questionnaire, principle axis factoring (PAF) with promax rotation was conducted. Prior to conducting PAF, its suitability was first examined. All variables in the correlation matrix had at least one correlation coefficient greater than 0.3, indicating that every variable correlated well with at least one other variable. The anti-image matrix indicated that values were above .05, hence supporting sampling adequacy. Overall Kaiser-Meyer-Olkin (KMO) value for each variable was 0.93 i.e. >.70 which further verified the sampling adequacy of analysis. Bartlett’s test of Sphericity indicated,X2(210) = 2550.17,p< 0.01 correlations among items were large enough for PAF, therefore it can be factorised. Therefore, factor analysis was suitable for DASS-21. PAF revealed three components had eigenvalues greater than 1 and explained 49.2%, 7.5% and 2.8% of the total variance respectively. A total of 59.5% of the total variance can be explained (Appendix A). Similarly, supported by the scree plot which had a point of inflexion and retaining 3 components (Appendix B). An oblique rotation (promax with Kaiser Normalization) was employed to aid interpretability. Factor loadings following rotation exhibited simple and complex structure. Under the DASS-21 depression subscale, seven items load highly on (> 0.65) factor one, while two items indicated complex loading on factor three. Under the DASS-21 for anxiety subscale, six items load highly on factor two while one
item loads on factor three in a complex way. Also, one item loaded on factor one. Under DASS-21 for stress subscale, five items loaded strongly on factor three while one item loads on factor two. Also, another item loaded on factor one and two in a complex manner. The rotated solution suggested that factor one, two, three corresponded to depression, anxiety and stress on the DASS-21 scale. Table 9 report the Factor Correlation matrix of the different factors relating to each other. Table 7 Factor Correlation Matrix Factor123 11.000.600.677 2.6001.000.743 3.677.7431.000 Discussion Hypothesis 1: DASS-21 exhibits reliability The results supported the first hypothesis hence it may be concluded that the DASS21 is a reliable scale for the North Queensland population. The result displayed a strong internal consistency based on high positive Cronbach alpha (>.86) for overall scale and all its subscales. This is in congruence to the findings of previous studies (Henry & Crawford, 2005). Hypothesis 2: There exists convergent validity with BASIS-24 Pearson product-moment correlat13ion analysis indicated significant positive correlation between the DASS-21 and the BASIS-24. First, DASS-21 correlates strongly with the Depression and Functioning subscale of BASIS-24, which is the scale that measures mental illness such as depression and anxiety. Second, there was also a positive but weaker correlation between DASS-21 and the
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BASIS-24 alcohol/drugs subscale. The reason of the smaller correlation magnitude could be due to the fact that alcohol and drug usage are merely comorbid disorders of depression and anxiety, but are not central to the constructs measured in DASS-21. Hence, these results support the convergent validity of DASS-21 with BASIS-24. Hypothesis 3: There exist divergent validity with MHC-SF The results showed a significant and moderately negative relationship between DASS- 21 and MHC-SF, which were developed upon different underlying theories (Osman et al., 2012). The negative correlation suggested that the two measures are measuring different constructs, that is, DASS-21 is a measurement of mental illness whereas MHC14-SF is a measurement of mental well-being. Hypothesis 4: There exist three factor structure of DASS-21 The fourth hypothesis states that factor analysis of the DASS-21would extract three factors, was also well supported. Three factors – depression, anxiety and stress – were extracted. This was congruent to the tripartite model of anxiety and depression,positive affect, physiological hyper arousal, and general distress respectively (Clark & Watson, 1991). However, complex loadings among several variables were observed (Table 9). Further, it suggested that inter-correlation among the subscales were moderately high (Table 10). The above finding corroborated with research which suggest that anxiety and depression are not the result of the scales measuring overlapping constructs. However, the correlations may reflect common causes of anxiety, depression and stress (Lovibond & Lovibond, 2015). Limitations and Future Studies There were two limitations identified in this study. First, sampling technique used in the research was snowball sampling. The biggest disadvantage of snowball sampling is that there is a high probability that the sample may be skewed towards one community having a
homogeneous demographic and psychological profile. Therefore, the sample may not be a true reflection of entire community. This is substantiated from the fact that participants were mostly females and employed individuals. Literature indicated that females are more prone to depression and anxiety symptoms (Altemus, Sarvaiya & Epperson, 2014), found to display greater emotional range, and experienced more pleasure from positive events (Wilhelm, 2014). Furthermore, the odds of having mental illness and experiencing stress amongst unemployed individuals are higher (Lo & Cheng, 2014). Thus, the participant sample in this study might not be an adequate representation of the North Queensland population which could produce biased data and unreliable results. Second, the sample size applied in the present study (N=171) can be considered small for factor analysis. A substantial sample size is needed to achieve stability in model estimation for factor analyses (Sinclair et al., 2012). For future research, the above hypotheses should be tested with a larger sample (at least N=300) using multi-method analytic techniques. In light of the identified limitations, there is limited generalizability of the overall findings. Hence, the future research should include a more representative sample of the entire population in order to increase the applicability of those discoveries. Conclusion Based on this study effectively recognised that DASS-21 is very reliable for the Queensland population. Moreover, it relates DASS-21 with other two measures that is, BASIS-24 which is a mental illness measure and MHC-SF a measure of positive well-being. These findings augmented the underlying philosophies for Queensland population. The work, though with its confines as cited in the above section, can be well-thought-out as a benchmark for psychology professionals as it gives them empirical evidence that DASS-21 may be used for Queensland population, as well as provides a way for the scientists of pertinent area to boost the findings in future.
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