The Depression Anxiety Stress Scale 8: Its Psychometric Evaluation Among Women with Chronic Non-Cancer Pelvic Pain

The Depression Anxiety Stress Scale 8: Its Psychometric Evaluation Among Women with Chronic Non-Cancer Pelvic Pain | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Depression Anxiety Stress Scale 8: Its Psychometric Evaluation Among Women with Chronic Non-Cancer Pelvic Pain Amira Ali, Amin Omar Hendawy, Rasmieh Al-Amer, Ghada Shahrour, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1212124/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract Psychiatric comorbidity and abusive experiences in chronic pelvic pain (CPP) conditions may prolong disease course. This study investigated the psychometrics of the Depression Anxiety Stress Scale 8 (DASS-8) among women with CPP (N = 214, mean age = 33.3 ± 12.4 years). The DASS-8 expressed excellent fit, invariance across age groups and menopausal status, good discriminant validity (differentiating women with psychiatric comorbidity from those without comorbidity: U = 2018.0, p = 0.001), excellent reliability (alpha = 0.90), adequate predictive and convergent validity indicated by strong correlation with the DASS-21 (r = 0.94) and high values of item-total correlations (r = 0.884 to 0.893). In two-step cluster analysis, it classified women into low and high distress clusters (n = 141 and 73), with significantly higher levels of distress, pain severity and duration, and physical symptoms in cluster 2. The DASS-8 correlated with pain severity/duration, depression/anxiety symptoms, sexual assault, fatigue, headache severity, and physical symptoms at the same level expressed by the parent scale, or even greater. Accordingly, distress may represent a target for early identification of psychiatric comorbidity, CPP severity, sexual assault, fatigue, etc. Therefore, the DASS-8 is a useful brief measure of mental symptoms among women with CPP. Psychology Health Economics & Outcomes Research psychological distress/anxiety/depression chronic pelvic pain sexual abuse/assault short form of the Depression Anxiety Stress Scale 21/Depression Anxiety Figures Figure 1 Figure 2 Introduction Pain in the pelvis unrelated to cancer, intercourse, or menstruation; which is experienced daily and persists for at least three consecutive months is known as chronic pelvic pain (CPP). CPP is commonly experienced by up to 22% of women [ 1 – 3 ]. It can be idiopathic or due to numerous urological, bowel-related, and gynecological reasons [ 3 , 4 ]. Because chronic noncancer pain conditions in women worsen over time, especially during the peak reproductive years, fluctuations in ovarian hormones are suggested to be key modulators in the pathologies underlying CPP such as endometriosis and irritable bowel syndrome [ 1 , 5 , 6 ]. Differences in CPP experience and pathology between reproductive age women and peri/postmenopausal women are reported in the literature [ 4 ]. Conditions entailing reduced levels of feminine hormones (e.g., menopause and during menses) are associated with increased sensitivity to visceral and pelvic pain [ 5 ]. In addition, ovarian collapse and subsequent reduction in estrogen during menopause is associated with numerous vegetative (e.g., hot flushes), physical (e.g., fatigue and back pain), urogenital/sexual (e.g., dyspareunia and urinary incontinence), cognitive (e.g., memory problems), and mental symptoms (e.g., depression and anxiety), which may aggravate pain sensitivity in midlife women and endanger their mental wellbeing [ 7 ]. In fact, CPP women within the age range of 25 to 35 years are reported to express less anxiety symptoms than their older counterparts [ 8 ]. The annual healthcare expenditure of CPP is enormous, exceeding 6.5 billion dollars in Australia [ 2 ]. In addition, CPP alters women’s quality of life, reproductive capacity, social relations, work performance, and sexuality. As a result, CPP women experience high levels of distress, depression, and anxiety [ 9 ]. Depression, anxiety, and mixed anxiety depression disorder (MADD) prevail in 63%, 66%, and 54% of women experiencing CPP compared with 38%, 49%, and 28% of CPP-free women [ 8 ]. Exposure to different forms of abuse during early stages of life is associated with the development and persistence of numerous physical, emotional, mental, and sexual dysfunctions during adulthood [ 10 ]. Moreover, women in different parts of the world witness the highest exposure to different forms of abusive behavior against adults, along with numerous grave consequences [ 11 ]. Physical and sexual abuse represent a major risk factor for CPP.[ 3 , 8 ] Given the traumatic origins of CPP and the distressful course of the condition, it is frequently managed within the biopsychosocial model of chronic pain—an approach that emphasizes the importance of wholistic management of chronic pain conditions “pain itself along with associated psychological and social problems” for more positive treatment outcomes [ 2 ]. However, CPP women experience varying levels of psychological distress. Greater comorbidity (e.g., depression, poor sleep, fatigue, somatic symptoms) is more common among women experiencing higher distress than those with little or no distress [ 12 ]. Therefore, careful identification of highly distressed CPP women through assessing psychopathological symptoms is extremely crucial for designing effective interventions for CPP and evaluating the outcomes of such interventions [ 2 ]. The Depression, Anxiety, and Stress Scale-21 (DASS-21) is a simple measure frequently used in research and clinical practice to capture the distinct features of depression, anxiety, and stress symptomatology [ 13 ]. However, numerous studies reported enormous flaws associated with the DASS-21: variations in its dimensional structure [ 14 – 17 ], invariance across different groups [ 18 – 20 ], and a ceiling effect [ 21 ]. As a result, many revisions of its item structure took place. Using several non-clinical samples, Osman et al. reported that the DASS-21 may be best used as a measure of psychological distress [22] —a state of emotional suffering that combines non-specific symptoms of depression and anxiety [ 23 ]. They also reported that numerous items poorly correlated with the underlying latent construct covered by the DASS-21, noting that reducing its items to 13 or nine items would remedy such flaws [ 22 ]. Subsequently, a 12-item version of the DASS-21 has been tested in non-clinical and clinical Korean samples [ 24 ]. However, this version has not been tested in another population until recently. A current study used clinical and non-clinical samples from Saudi Arabia to investigate various models of the parent scale as well as all the available shortened versions [ 25 ]. The fit of different models of the DASS-21 was considerably lower than all its short versions. An extensive revision of the item structure of the DASS-21 based on statistics and conceptual methods resulted in an 8-item version of the DASS-21. The DASS-8 expressed excellent psychometric properties compared with Osman’s 13-item/nine-item DASS and the Korean DASS-12 [ 25 ]. Likewise, another investigation involving healthy individuals from the US, Australia, and Ghana, the DASS-8 expressed a better fit and more robust discriminant and criterion validity than the DASS-12. However, both the DASS-8 and DASS-12 exhibited variance at the scalar level across English-speaking and Ghanaian participants, with the latter expressing lower levels of distress [ 26 ]. Individuals’ responses to items of the DASS-8 in different cultures may vary since individuals tend to selectively express their distress symptoms through culturally acceptable ways [ 27 ]. Brief screening instruments are intended to be used more frequently as clinical tools to facilitate the identification of pathological cases and enable assessing response to treatment. Accordingly, there is an intense need to ensure the relevance, local precision, and adequate sensitivity of these instrument [ 28 ]. To benefit from the DASS-8 as a brief measure of depression/anxiety and stress symptomatology, it needs to be evaluated in more diverse populations, including patient groups, to ensure the adequacy of its sensitivity. Therefore, this study aimed to examine the psychometrics of the DASS-8 in a sample of Australian women with CPP. We hypothesized that 1) the DASS-8 would express better fit and less variance than the DASS-12; 2) the DASS-8 would discriminate CPP women experiencing mental comorbidities from those without mental comorbidities; 3) the DASS-8 would correlate with the DASS-21 at the same level expressed by the DASS-12; and 4) the DASS-8 would correlate with pain symptoms and history of sexual assault at the same level expressed by the parent scale. Material And Methods Study design, participants, and procedure This study is a secondary analysis based on a publicly accessible dataset from a previously published cross-sectional study [ 3 ], which comprises a convenient sample of women with CPP. Data were collected via a pre-treatment self-administered questionnaire addressed to all clients attending a specialist pelvic pain clinic in South Australia over 18 months between January 2015 and July 2016. Women not signing informed consent, with several incomplete sections of the questionnaire, or solely experiencing period pain or dyspareunia were excluded from the study. Women or their guardian, if they were less than 18 years old, signed an informed consent. Because the protocol for data collection was previously approved by University of South Australia Human Research Ethics Committee (Application ID: 0000036598; 26/05/2017) [ 3 ], and the dataset was publicly accessible [ 29 ], we did not obtain an ethical approval for the current study. Measures The questionnaire used for data collection comprised a large set of questions about pain experienced, its intensity, duration, pain-free days per month, pain severity during sexual activity, severity of stabbing pelvic pain, pain severity on the day of data collection, experiencing (tiredness/fatigue, anxiety, low mood, bad headache), somatic symptoms (e.g., nausea, unusual sweating, dizziness, and bloating), history of sexual assault, current psychiatric disorders, etc. Questions addressing pain severity or intensity prompted the respondents to rate the intensity of pain on a scale from 0 (no pain) to 10 (extremely severe pain). The Depression anxiety stress scale (DASS-21) was used to measure psychological distress. It comprises 21 items, in three subscales that assess symptoms of depression, anxiety and stress. Item responses are rated on a 4-point scale ranging from 0 (did not apply to me at all) to 3 (applied to me very much or most of the time). The minimum and maximum total scores of the DASS-21 are 0 and 63 [ 17 , 30 ]. The DASS-8 comprises eight items, in three subscales: depression (three items e.g., felt down hearted and blue), anxiety (three items e.g., felt scared without reason), and stress (two items e.g., was using a lot of my mental energy) [ 25 , 26 ]. The total scores of the DASS-8 and its subscales range between 0 to 24, 0 to 9, 0 to 9, and 0 to 6, respectively. The DASS-12 comprises 12 items, in three subscales, each comprising four items. The total scores of the DASS-8 and its subscales range between 0 to 24 and 0 to 12, respectively [ 24 ]. The reliability of the DASS-21, DASS-8, and DASS-12 in this sample is excellent (coefficient alpha = 0.95, 0.90, and 0.90, respectively). Statistical analysis First, we checked the dataset for missing responses. Because multiple items of the DASS-21 had missing responses, we removed all participants with incomplete data on the DASS-8 and DASS-12, which resulted in a final sample size of 214 participants—response rate = 0.90%. The normality of different version of the DASS were tested by Shapiro Wilk W test. The statistics of non-normal variables are reported as median (MD) and interquartile range (IQR; Q1-Q3) while mean and standard deviation were used to report normally-distributed variables. Number and percentage were used to describe categorical variables. Based on a former investigation [ 25 ], the factor structures of the DASS-8 and DASS-12 were examined using confirmatory factor analysis (CFA). To evaluate model fit as good or acceptable, we used chi square (χ2) index, ideally it should be non-significant, Comparative Fit Index (CFI) and Tucker–Lewis Index (TLI) equal to or above 0.95 and 0.90, respectively, in addition to standardized root-mean-square residual (SRMR) and root mean square error of approximation (RMSEA) less than 0.06 and 0.08, respectively [ 7 , 31 ]. This combination allows parsimonious evaluation of model fit because χ 2 is largely dependent on sample size, which if used alone may disqualify well-fitting models that express minor misspecifications [ 30 , 32 ]. Based on suggestions pointed by modification indices, few error terms were correlated to improve model fit. To test measurement invariance of the DASS-8, age was categorized in two groups (156 below the age of 40 versus 58 aged 40 years and above). Then, multigroup CFA was conducted to compare invariance of the DASS-8 and DASS-12 at the configural, metric, scalar, and strict levels [ 33 , 34 ] across groups of age, menopausal status (menopausal vs premenopausal), and psychiatric comorbidity (presence of comorbidity vs no comorbidity, the number of subjects in all the categories are shown in Table 1). Significant changes in χ 2 in constrained models, along with ΔCFI and ΔRMSEA above 0.02 and 0.015, respectively were used as criteria for non-invariance [ 23 , 33 ]. To examine the discriminant validity of the DASS-21, DASS-12, DASS-8, Mann Whitney U test was used to determine whether these measures and their subscales can differentiate CPP women with comorbid psychiatric disorders from those without psychopathology. It was also used to differentiate women with depressive disorder from those with anxiety disorder. In addition, heterotrait-monotrait (HTMT) ratio of correlations of items comprising the DASS-21, DASS-12, DASS-8 were computed [ 26 , 35 ]. Moreover, two-step cluster analysis was used to determine whether the participants can be grouped according to the scores of the DASS-8 and its subscales. Two-step cluster analysis is a hybrid technique that operates via two steps. The first step (pre-clustering) employs a sequential approach to separate groups by pre-clustering cases based on a distance measure that defines dense regions in the analyzed attribute-space. In the second step (clustering), a probabilistic approach is used to statistically merge pre-clusters stepwise until the optimal subgroup model is determined. This technique is highly reliable; in terms of the number of subgroups detected, classification probability of individuals into subgroups, and reproducibility of the findings on different types of data. It has additional merits: analyzing atypical values (i.e., outliers), determining the number of clusters based on a statistical measure of fit rather than on an arbitrary choice, using categorical and continuous variables simultaneously, and handling large datasets [ 36 ]. Independent sample t-test, Mann Whitney test, and χ 2 were used to compare the differences in mental symptomatology and characteristics of the participants across clusters. The reliability of the DASS-21, DASS-12, DASS-8, and their subscales was assessed by coefficient alpha, alpha-if-item deleted, and item-total correlations. The predictive validity of the DASS-12, DASS-8, and their subscales was detected by Spearman’s r correlating these measures to the original scale and its subscales. This test was also used to evaluate the criterion validity of the three measures by correlating their scores with sexual assault experience, number of pain days/pain-free days per month, pain severity during sexual activity, pain severity on the day of data collection, severity of stabbing pelvic pain, experiencing bad headache, experiencing tiredness/fatigue, experiencing anxiety, and experiencing low mood. Additionally, a general structural equation path model (SEM) was constructed to use the DASS-8/DASS-12 and their subscales to predict these characteristics. Model fit was based on the same criteria used in CFA. Nonsignificant paths were trimmed to allow a better fit. All analyses were conducted in SPSS and Amos, and significance was considered at a probability level less than 0.05 in two-tailed tests. Results Characteristics of the participants Participants in this study (N = 214, mean age = 33.1±12.4 years) were women complaining from CPP. The participants experienced several types of pain (stabbing pelvic pain, sex pain, bowel pain, and headache), somatic symptoms (e.g., bloating, nausea, dizziness, unusual sweating), along with symptoms of low mood, anxiety, and psychiatric comorbidity. Table 1 shows more information on the sociodemographic and clinical characteristics of the participants in the overall sample as well as group differences in these variables between low distress and high distress women. Results of confirmatory factor analysis and invariance analysis As shown in Table 2, the one-factor structure of the DASS-8/DASS-12 expressed unsatisfactory fit. The crude models of the three-factor structures of the DASS-8 and the DASS-12 expressed good fit. Correlating the error terms of two items (Figure 1 ) in both models slightly improved the fit. The fit of the second order structure was similar to that of the three-factor structure of both scales (supplementary material). While the bifactor structure of the DASS-8 expressed good fit with all items significantly loading on the general factor, item 12 and item 20 failed to load on their domain-specific factors of stress and anxiety, respectively (p >.05). In addition, item 15 loaded significantly on the anxiety factor (p = .04), but its loading on this factor was weak (β = .26). All items of the anxiety subscale of the DASS-12 failed to load on their corresponding factor in the bifactor model. Therefore, the three-factor structures of the DASS-8/DASS-12 represent the best fit of the data. As shown in Table 3, the three-factor structures of the DASS-8 and DASS-12 were invariant at the configural, metric, scalar, and strict levels across groups of age and menopausal status. However, the DASS-8 was non-invariant at the scalar level across groups of psychiatric comorbidity (ΔCFI > 0.02 and ΔRMSEA >0.15). The DASS-12 was non-invariant at the strict level (ΔCFI > 0.02 and ΔRMSEA >0.15), and it also tended to be non-invariant at the scalar level across comorbidity groups (SRMR = 0.1117). Results of discriminant validity tests As noted in Table 4 , the DASS-21, DASS-8, DASS-12 differentiated between women with a current psychiatric disorder and those without at the same level of significance (p < 0.001). However, the z scores of the DASS-8 and its subscales were higher than those of the DASS-12 and the DASS-21, indicating a higher level of discriminant validity. Nonetheless, neither the DASS-21, DASS-8, DASS-12 nor their subscales could differentiate women with a diagnosis of depression from those with a diagnosis of anxiety. Likewise, the DASS-21, DASS-8, DASS-12, and their subscales significantly correlated with subjective experience of anxiety and low mood at the same levels (all p values < 0.01, Table 4 ). The HTMT ratio of correlations show that the constructs covered by the subscales of the DASS-8 and DASS-12 were distinct (< 0.85). However, the stress and anxiety subscales on the DASS-8 were overlapping (HTMT ratio = 0.95). All the subscales of the parent scale exhibited overlap, albeit it was marginal for the stress-anxiety subscales (HTMT ratio = 0.85 supplementary materials). Table 4 Descriptive statistics and discriminant validity of the Depression Anxiety Stress Scale 21 and its shortened versions among women with chronic pelvic pain DASS versions Whole sample (N = 214) Mann Whitney test z Cluster 1 (n = 141) Cluster 2 (n = 73) Mann Whitney test z MD (IQR) MD (IQR) MD (IQR) DASS-21 11.5 (6.0-23.8) 2247.5 -5.49 7.0 (4.0-11.8) 29.5 (23.0-36.8) 210.0 -11.43 Depression 2.0 (1.0-7.0) 2495.5 -5.08 1.0 (0-3.0) 9.0 (5.0-14.0) 1041.0 -9.65 Anxiety 3.0 (1.0-7.0) 2482.0 -5.11 1.0 (0-3.0) 8.0 (6.0-11.0) 728.0 -10.39 Stress 6.0 (3.0-11.0) 2641.0 -4.48 4.0 (2.0-6.0) 12.0 (10.0-16.0) 436.5 -10.91 DASS-12 7.0 (3.0-13.3) 2320.0 -5.48 4.0 (2.0-7.0) 17.0 (13.0-21.0) 397.0 -11.08 Depression 1.0 (1.0-4.0) 2266.5 -5.80 0 (0-1.0) 5.0 (3.0-8.5) 1082.0 -9.77 Anxiety 2.0 (0-4.0) 2842.0 -4.24 1.0 (0-2.0) 4.0 (3.0-6.0) 1514.5 -8.63 Stress 4.0 (2.0-7.0) 2849.5 -4.16 2.0 (1.0-4.0) 8.0 (6.0-9.5) 856.0 -10.05 DASS-8 4.0 (1.0-8.0) 2018.0 -6.27 2.0 (1.0-3.0) 12.0 (8.0-15.0) 36.0 -11.95 Depression 1.0 (0-3.0) 2346.5 -5.60 0 (0-1.0) 4.0 (2.0-6.0) 1214.0 -9.47 Anxiety 1.0 (0-3.0) 2521.0 -5.21 0 (0-1.0) 4.0 (3.0-6.0) 674.0 -10.93 Stress 2.0 (1.0-3.0) 2447.0 -5.26 1.0 (0-2.0) 4.0 (3.0-5.0) 364.0 -11.37 DASS: Depression Anxiety Stress Scale, MD: median, IQR: interquartile range, U: Mann Whitney U test, p values were all significant at 0.001 level. For the DASS-21 (N = 212). In two-step cluster analysis, the DASS-8 and its subscales classified the participants into two clusters: low distress (cluster 1: n = 141, 65.9%) and high distress (cluster 2: n = 73, 34.1%). The model expressed good fit as indicated by Silhouette measure of cohesion and separation of around 0.7 and ratio of sizes less than 3 (1.93). Values of the predictor importance of the DASS-8 followed by stress, anxiety, and depression were 1, 0.85, 0.73, and 0.5, respectively. Mann Whitney U test revealed significant differences in the level of all mental distress symptoms among participants in both clusters—they were all significantly higher in cluster 2 than in cluster 1 (all p < 0.001), with the DASS-8 and its stress subscale expressing the highest z scores (Table 4 ). Age, menopausal status, bloating, and the frequency of stabbing pelvic pain and sex pain did not vary significantly across clusters. However, participants in cluster 2 demonstrated significantly higher number of pain days (t(146.9)= -2.50, p = 0.014), less pain free days (U = 3654.0, z = -2.39, p = 0.017); more severity of stabbing pelvic pain (t(134.42) = -2.47, p = 0.015), sex pain (t(105.22) = -3.74, p = 0.001), current pelvic pain (U = 3095.0, z = -3.29, p = 0.001), concurrent headache (t(118.11) = -3.51, p = 0.001); higher frequency of bowel pain ( χ 2 (1) = 6.68, p = .010), greater occurrence of sexual assault ( χ 2 (1) = 19.06, p = .001), psychiatric co-morbidity ( χ 2 (2) = 23.61, p = 0.001), psychiatric symptoms (low mood (χ2(16) = 29.8, p = 0.001) and anxiety ( χ 2 (1) = 50.50, p = 0.001)), fatigue ( χ 2 (1) = 14.12, p = 0.001), sleep problems ( χ 2 (16) = 12.13, p = 0.001), and somatic symptoms (dizziness ( χ 2 (1) = 7.57, p = 0.006), unusual sweating ( χ 2 (1) = 9.52, p = 0.002), and nausea ( χ 2 (1) = 13.65, p = 0.001)). Results of tests of reliability, normality, and criterion validity The reliability of the DASS-21, DASS-8, and DASS-12 was excellent. Meanwhile, the reliability of the shortened subscales ranged from very good to poor (Table 5 )—poor reliability was reported only for the anxiety subscale of the DASS-12. The predictive validity of the DASS-8, DASS-12, and their subscales is depicted by their strong correlation with the original scale and its subscales (Table 5 ). The normality of the DASS-8 and the DASS-12 is comparable with that of the DASS-21 as noted by Shapiro–Wilks’ W. As shown in Table 5 , all the DASS versions and most of their subscales negatively correlated with pain-free days and positively correlated with pain experience on the survey day, pain days per month, concurrent headache, poor sleep, fatigue, somatic symptoms (nausea, bloating, dizziness, unusual sweating), experience of low mood and anxiety, as well as sexual assault experience. Notably, all the subscales of the DASS-8 correlated with sexual assault experience while the anxiety and stress subscales of the DASS-12 as well as the stress subscale of the DASS-21 could not correlate with this variable. Similarly, all subscales of the DASS-8 correlated with the severity of stabbing pelvic pain while the stress subscale of the DASS-12 and the DASS-21 failed to correlate with this variable. Table 5 Internal consistency, predictive validity, normality, and criterion validity of the Depression Anxiety Stress Scale (DASS) 21, DASS-12, DASS-8, and their subscales among women with chronic pelvic pain Criteria DASS-21 Depression Anxiety Stress DASS-12 Depression Anxiety Stress DASS-8 Depression Anxiety Stress Coefficient alpha 0.945 0.931 0.837 0.878 0.898 0.845 0.693 0.827 0.901 0.892 0.794 0.705 Range of corrected item-total correlations 0.401-0.776 0.598-0.847 0.370-0.713 0.593-0.735 0.401-0.785 0.607-0.719 0.371-0.550 0.607-0.746 0.629-0.744 0.882-0.944 0.634-0.662 0.545 Range of alpha if-item-deleted 0.940-0.946 0.914-0.939 0.795-0.853 0.851-0.869 0.881-0.902 0.787-0.833 0.585-0.708 0.742-0.809 0.884-0.893 0.831-0.870 0.702-0.733 -- Correlation with subscale of the DASS-21 -- -- -- -- -- 0.930 *** 0.919 *** 0.948 *** -- 0.934 *** 0.871 *** 0.871 *** Correlation with the DASS-21 -- 0.856 *** 0.823 *** 0.929 *** 0.966 *** 0.838 *** 0.718 *** 0.863 *** 0.943 *** 0.811 *** 0.789 *** 0.818 *** Shapiro Wilk test 0.892 *** 0.812 *** 0.848 *** 0.936 *** 0.906 *** 0.787 *** 0.843 *** 0.933 *** 0.864 *** 0.788 *** 0.790 *** 0.891 *** Correlation with sexual assault experience 0.203** 0.264*** 0.196** 0.134 0.192* 0.278*** 0.095 0.106 0.259** 0.245** 0.261*** .188* Correlation with pain days/month 0.183** 0.137 0.221** 0.183** 0.193** 0.190** 0.204** 0.136 0.180* 0.177* 0.172* .163* Correlation with pain-free days/month -0.182** -0.132 -0.217** -0.174* -0.193** -0.188** 0-.201** -0.139* -0.179* -0.173* -0.168* -.168* Correlation with severity of pain today 0.265*** 0.217** 0.331*** 0.238** 0.290*** 0.255*** 0.291*** 0.239** 0.265*** 0.225** 0.274*** .234** Correlation with severity of stabbing pelvic pain 0.200** 0.167* 0.287** 0.138 0.209** 0.174* 0.246** 0.143 0.205** 0.149* 0.246** .153* Correlation with severity of pain during sexual activity 0.262** 0.308*** 0.210* 0.222** 0.280** 0.326*** 0.187* 0.229** 0.257** 0.285** 0.218** .227** Correlation with severity of bad headache 0.387*** 0.300** 0.253** 0.378*** 0.395*** 0.324*** 0.221* 0.363*** 0.299** 0.303** 0.225* .234** Correlation with experienced anxiety 0.517** 0.430** 0.412** 0.491** 0.498** 0.427** 0.323** 0.478** 0.531** 0.425** 0.473** .467** Correlation with experienced low mood 0.487** 0.482** 0.323** 0.446** 0.478** 0.512** 0.227** 0.447** 0.514** 0.492** 0.400** .412** Correlation with experienced fatigue 0.345** 0.296** 0.333** 0.305** 0.348** 0.300** 0.346** 0.288** 0.322** 0.283** 0.231** .298** Correlation with poor sleep 0.303** 0.250** 0.337** 0.248** 0.305** 0.227** 0.329** 0.238** 0.283** 0.246** 0.240** .257** Correlation with dizziness 0.251** 0.174** 0.333** 0.191** 0.243** 0.192** 0.335** 0.150* 0.244** 0.181** 0.262** .211** Correlation with unusual sweating 0.238** 0.182** 0.280** 0.215** 0.239** 0.174* 0.306** 0.197** 0.222** 0.179** 0.189** .257** Correlation with nausea 0.256** 0.240** 0.339** 0.180* 0.259** 0.221** 0.349** 0.145* 0.236** 0.219** 0.260** .154* Correlation with bloating 0.259** 0.216** 0.255** 0.206** 0.247** 0.213** 0.234** 0.193** 0.279** 0.245** 0.234** .246** *, **, ***: correlation is significant at a level of 0.05, 0.01, 0.001, respectively. After trimming non-significant paths, SEM used to test criterion validity of the DASS-8/DASS-12 expressed good fit (χ2(16, 16) = 10.677, 6.956; p = 0.829, 0.974; both CFI= 1.00, both TLI = 1.00, both RMSEA = 0.00, SRMR = 0.0420, 0.0376). Scores of the DASS-8/DASS-12 significantly predicted current pain severity, poor sleep, and sex pain. Scores of their anxiety subscales predicted concurrent headache while scores of their stress subscales predicted the number of pain days per month (Figure 2 ). The DASS-8 and DASS-12 exerted significant indirect effects on headache through current pain severity (β = -0.055, 95% CI: -0.120 to -0.011, p = 0.023) and (β = -0.067, 95% CI: -0.142 to -0.018, p = 0.011), respectively as well as on sex pain through poor sleep (β = 0.070, 95% CI: 0.023 to 0.114, p = 0.011) and (β = 0.073, 95% CI: 0.031 to 0.118, p = 0.011, 0.007), respectively. Month pain days mediated the effect of the stress subscale of the DASS-8 and DASS-12 on sex pain (β = -0.045, 95% CI: -0.091 to -0.007, p = 0.037) and (β = -0.042; 95% CI: -0.100 to -0.009; p = 0.041), respectively. Discussion Distress symptoms are excessively experienced in CPP patients [ 2 , 8 , 9 ], and its management can considerably affect disease recovery [ 2 ]. Because not all CPP women express higher levels of distress and resources directed toward management of distress are limited [ 12 ], there is a great need for brief measures that may facilitate the identification of highly distressed patients as well as response to treatment [ 28 ]. Using numerous robust psychometric testing techniques, the present study reports usefulness of the DASS-8 as a measure of distress, depression, anxiety, and stress symptomatology among Australian women with CPP. The crude models of the three-factor structure of the DASS-8/DASS-12 expressed better fit than all other crude models. RMSEA was on the high side for the DASS-8, suggesting minor misspecifications in item loadings. The fit of this model was considerably improved by correlating the residuals of item 12 “I found it difficult to relax” on the stress subscale and item 13 “I felt down-hearted and blue” on the depression subscale. Likewise, the fit of the DASS-12 was slightly improved by correlating the residuals of item 12 and item 1 “I found it difficult to wind down” on the stress subscale. Accordingly, the final model of the DASS-8 expressed a perfect fit on all CFA fit indices, superior to the DASS-12, indicating a better construct validity of the DASS-8 as we hypothesized. Meanwhile, the fit of the second-order factor structure of both scales was similar to the three-factor structure (supplementary material), indicating usability of the total score and the score of the subscales of these scales. The three-factor structures of both scales exhibited configural, metric, scalar, and strict invariance across groups of age and menopausal status. Across groups of psychiatric comorbidity, the DASS-8 was non-invariant at the scalar level and the DASS-12 expressed misfit (indicating tendency toward non-invariance) at the scalar level and it was non-invariant at the strict level. Critical ratios for differences between parameters noted that the source of non-invariance of the DASS-8 involved: 1) lower loadings of item 20 “I felt scared without any good reason” on the anxiety subscale and item 12 on the stress subscale, 2) weaker correlation between the anxiety and depression subscales, and 3) less covariance between items 12 and 13. All were noted among participants not diagnosed with a mental disorder compared with those having a psychiatric disorder. Non-invariance of the DASS-12 involved differences in the loading of item 17 “I felt I was not worth much as a person” and the variances of items 1, 3 “I couldn’t seem to experience any positive feeling at all”, and 10 “I felt that I have nothing to look forward”—all on the depression subscale. Investigations of discriminant validity revealed significant differences in all distress scores between both groups. The DASS-8 can be a beneficial brief measure for identifying CPP women with psychiatric comorbidity, high level of distress, and other debilitating symptoms (e.g., greater pain severity, poor sleep, concurrent headache, gastrointestinal discomfort, etc.). This is because the DASS-8 expressed adequate discriminant validity by differentiating CPP women with psychiatric comorbidities from those who are mental-illness free. Although the discriminant validity of the DASS-8, DASS-12, and DASS-21 was expressed at the same level of significance (p = 0.001), the z scores associated with the DASS-8 were higher than those of the DASS-12 and DASS-21 (Table 4 ), indicating superior discriminant validity of the DASS-8. This finding is consistent with a former investigation in which the DASS-8 potently identified psychiatric patients from healthy subjects [ 25 ]. On the other side, the DASS-8 as well as the DASS-12 and the DASS-21 could not discriminate CPP women with depression disorder from those with anxiety disorder. In line, the DASS-21 and the DASS-12 have been previously reported to lack the capacity to differentiate depression disorder from anxiety disorder [ 16 , 24 , 37 ]. These findings are consistent with other results on the reported comorbidity of both depression and anxiety disorders, confirming that the DASS measure is not a clinically diagnostic tool, but it can efficiently identify individuals prone to both depression and anxiety psychopathologies [ 38 , 39 ]. This can be a merit of a brief self-administered measure. Extra diagnostic workout can be performed in a next step to attain a formal diagnosis. In two-step cluster analysis, the DASS-8 and its subscales classified CPP women into two clusters with low and high levels of distress. The DASS-8 and its stress subscale had higher predictor importance values than anxiety and depression. Mann Whitney U test revealed significant differences (all p values = 0.001) in the scores of all the DASS measures among women in both clusters, with the DASS-8 and its stress subscale exhibiting the highest z scores (Table 4 ). As shown in Table 1, participants in cluster 2 (high distress) scored significantly higher on symptoms of pain severity, bowel pain, depression, anxiety, fatigue, dizziness, nausea, and unusual sweating than participants in cluster 1. This finding is consistent with a former study, which classified women into two clusters: one cluster comprised women high on depression, fatigue, and poor sleep while the other cluster comprised women experiencing no or minimal levels of these symptoms [ 12 ]. However, Mann Whitney U test, cluster analysis, and SEM in the present study indicate stronger discriminant validity of the DASS-8 and its stress and anxiety subscales than the depression subscale. Overall, the DASS-8 can be efficiently used to differentiate highly distressed CPP women (e.g., with psychiatric comorbidity and more severity of mental symptoms, pain, and physical symptoms) from those with low levels of distress. Apart from good fit, invariance, and adequate discriminant validity, the DASS-8 demonstrates other excellent psychometric characteristics. As shown in Table 5 , the internal consistency of the DASS-8 and all its subscale was good—considerably higher than that of the DASS-12 as we hypothesized, except for the stress subscale, which comprises half the number of items on the corresponding subscale of the DASS-12. Whereas the values of alpha-if-item deleted indicated reduction in the reliability of the DASS-8, they indicated an increase in the reliability of the DASS-12 and its anxiety subscale (Table 5 ), lending support to the more robust convergent validity of the DASS-8. Consistent with our preset hypothesis, strong correlations of the DASS-8 and its subscales with the DASS-21 and its subscales convey adequate item coverage, predictive validity, and convergent validity. Generally, these results highlight the high homogeneity, specificity, and sensitivity of the items comprising the DASS-8, which have been reported among Arabs and English-speaking participants [ 25 , 26 ]. In parallel, the DASS-8 and all its subscales exhibited significant correlations with sexual assault, pain duration (pain days per months), pain-free days, pain intensity, somatic symptoms, fatigue, poor sleep, bad headache, etc. On the other hand, the stress and depression subscales of the DASS-21 failed to correlate with sexual assault and pain-free days, respectively. Likewise, the anxiety and depression subscales of the DASS-12 failed to correlate with sexual assault while the correlation of the overall DASS-12 with sexual assault was at a lower level than that expressed by the DASS-8 (r = 0.192, p = 0.05 vs r = 0.259, p = 0.01). These findings indicate better criterion validity of the DASS-8. They are also congruent with recent studies reporting significant correlations of the subscales of the DASS-21 with stabbing pelvic pain, migraine, intimate partner violence/domestic violence; as well as early childhood physical, sexual and emotional abuse among women [ 3 , 10 , 11 , 40 ]. Moreover, SEM revealed that the DASS-8/DASS-12 and their subscales, except for depression, can directly and indirectly predict pain severity, pain days, sex pain, concurrent headache, and poor sleep (Figure 2 ). Therefore, the DASS-8 can be reliably used as a valid criterion to predict different noxious symptoms and experiences in CPP. This study is the first attempt to confirm the psychometric soundness of the DASS-8 as a measure of mental symptomatology among Australian women with CPP. Results obtained from different robust testing techniques in this study emphasize excellent psychometric properties of the DASS-8; in terms of fit, invariance, predictive validity, convergent validity, discriminant validity, criterion validity, and reliability. These finding are all in line with those reported in Arab psychiatric patients as well as in healthy respondents from Saudi Arabia, Australia, the US, and Ghana.[ 25 , 26 ] Nonetheless, the study has many limitations that should be acknowledged. The generalizability of the finding is limited out of possible risk for selection bias: 1) the sample is collected from a single clinic, 2) a priori power analysis for determining the sample size is lacking, 3) data on the respondents who declined participation in the survey are lacking, 4) inclusion and exclusion criteria are not clearly defined, and 5) the results are based on a convenience sample, which may not represent all CPP women in other settings or countries. The cross-sectional design used precludes test-retest reliability testing and casts doubt on the soundness of relations predicted in SEM. Thus, future investigations may use a longitudinal design to examine the properties of the DASS-8 as well as causal direction of effects addressed in this study, along with mechanisms underlying links between psychological distress, pain, sleep problems, concurrent headache, etc. Conclusion Psychometric evaluation of the DASS-8 among CPP women by numerous robust techniques revealed its proper fit, invariance, high reliability, good convergent validity, adequate predictive validity, and good criterion validity. The results indicate usability of the DASS-8 as a brief, reliable, invariant measure of mental symptoms in reproductive age and menopausal women with CPP. The Identification of highly distressed women would encourage the use of relevant psychiatric intervention. Owing to its brevity, the DASS-8 can facilitate frequent monitoring of common mental symptomatology over the course of CPP treatment, supporting efforts directed toward improving recovery in CPP population. Declarations Ethics approval and consent to participate: The protocol of data collection was approved by University of South Australia Human Research Ethics Committee (Application ID: 0000036598; 26/05/2017). All participants or their guardians signed a written informed consent before data collection [3]. No ethical approval was obtained for the current study because the analysis is based on a publicly accessible dataset [29]. The present study was conducted according to the Declaration of Helsinki. Consent for publication: Not applicable. Availability of data and materials: The dataset [29] supporting the conclusions of this article is available in Zenodo repository, [https://zenodo.org/record/1307252#.YckoVWhBw2w], and also the datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Acknowledgements: The authors would like to thank the Deanship of Scientific Research, Qassim University, for funding the publication of this paper. References Hassan, S.; Muere, A.; Einstein, G. Ovarian hormones and chronic pain: A comprehensive review. PAIN® 2014, 155 , 2448–2460, doi: https://doi.org/10.1016/j.pain.2014.08.027 . Brooks, T.; Sharp, R.; Evans, S.; Baranoff, J.; Esterman, A. Psychological Interventions for Women with Persistent Pelvic Pain: A Survey of Mental Health Clinicians. J Multidiscip Healthc 2021, 14 , 1725–1740, doi: 10.2147/jmdh.s313109 . Brooks, T.; Sharp, R.; Evans, S.; Baranoff, J.; Esterman, A. 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Al-Hayani, M.; AboTaleb, H.; Bazi, A.; Alghamdi, B. Depression, anxiety and stress in Saudi migraine patients using DASS-21: local population-based cross-sectional survey. Int J Neurosci 2021, 1–9, doi: 10.1080/00207454.2021.1909011 . Additional Declarations No competing interests reported. Supplementary Files AppendixA..xlsx Appendix A. Supplementary excel 1 showing extra relevant analyses that are not reported in the text. Cite Share Download PDF Status: Under Review Version 1 posted Editor invited by journal 09 Jan, 2022 Submission checks completed at journal 09 Jan, 2022 First submitted to journal 28 Dec, 2021 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1212124","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":75339730,"identity":"c000d504-b491-4b14-b43e-29f6527e390f","order_by":0,"name":"Amira Ali","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABHElEQVRIie3Rv0rEMBzA8dRAuvzk1hTFNxAigarYh6lLpnRwc5BbhLjcuQs+RCdxPCi2Sx4g23EUKojDSUG8wT9Nz0Vpq6NgvkNTQj4kaRFyuf5wI7YeIyAYz5oXuv0TCdL1KHZGvootgd+SjAcT3e7YS3YvposaUET3/fOKPt3i49TI+sGcHQDys7u0g4S64FuABD2c5GFwpUlDkpsjmTcHAyFMFzGCYEDZmJmY800FLeGSNIRC2EnmVUsom9/X/FVRe7CKy7cBYsgnMbBXeorZ6+MyUQNECxxcM0GZlieLqYrtRw5xckmB9N2lyL3l42lEWVGks5V6t7+yrOXzuLFZ3kVsG8C+ThDaPnuW27yXbxN4ObDa5XK5/l8f8g9hzYo99KgAAAAASUVORK5CYII=","orcid":"","institution":"Tokyo University of Agriculture and Technology","correspondingAuthor":true,"prefix":"","firstName":"Amira","middleName":"","lastName":"Ali","suffix":""},{"id":75339731,"identity":"17fd4fec-5d36-4d6b-a890-6878a863d632","order_by":1,"name":"Amin Omar Hendawy","email":"","orcid":"","institution":"Tokyo University of Agriculture and Technology","correspondingAuthor":false,"prefix":"","firstName":"Amin","middleName":"Omar","lastName":"Hendawy","suffix":""},{"id":75339732,"identity":"1a16824f-6b44-4198-bffc-5764b11c7600","order_by":2,"name":"Rasmieh Al-Amer","email":"","orcid":"","institution":"Isra University","correspondingAuthor":false,"prefix":"","firstName":"Rasmieh","middleName":"","lastName":"Al-Amer","suffix":""},{"id":75339733,"identity":"79795b03-f36f-4fff-8573-25998984d9c8","order_by":3,"name":"Ghada Shahrour","email":"","orcid":"","institution":"Jordan University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Ghada","middleName":"","lastName":"Shahrour","suffix":""},{"id":75339734,"identity":"3214b81d-f557-4c90-b0bb-bff08e119671","order_by":4,"name":"Esraa M. Ali","email":"","orcid":"","institution":"Alexandria University","correspondingAuthor":false,"prefix":"","firstName":"Esraa","middleName":"M.","lastName":"Ali","suffix":""},{"id":75339735,"identity":"b94a8a65-1161-4f31-9c60-39894507128b","order_by":5,"name":"Abdulmajeed A. Alkhamees","email":"","orcid":"","institution":"Qassim University","correspondingAuthor":false,"prefix":"","firstName":"Abdulmajeed","middleName":"A.","lastName":"Alkhamees","suffix":""},{"id":75339736,"identity":"4cd9f6e6-795b-4ba0-a79b-407e40a464c7","order_by":6,"name":"Nashwa Ibrahim","email":"","orcid":"","institution":"Mansoura University","correspondingAuthor":false,"prefix":"","firstName":"Nashwa","middleName":"","lastName":"Ibrahim","suffix":""},{"id":75339737,"identity":"9504956c-8229-496a-a52a-7f1f19ba95d7","order_by":7,"name":"Afaf Hassan Ahmed","email":"","orcid":"","institution":"Alexandria University","correspondingAuthor":false,"prefix":"","firstName":"Afaf","middleName":"Hassan","lastName":"Ahmed","suffix":""},{"id":75339738,"identity":"2e0b3d99-4e84-4f14-9f0b-b6a8ce78b8ef","order_by":8,"name":"Sahar Mansour Taha Lamadah","email":"","orcid":"","institution":"Alexandria University","correspondingAuthor":false,"prefix":"","firstName":"Sahar","middleName":"Mansour Taha","lastName":"Lamadah","suffix":""}],"badges":[],"createdAt":"2021-12-29 01:29:00","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1212124/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1212124/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":17214906,"identity":"ae1f0b85-a55f-407f-8ec8-99f91a09b8a8","added_by":"auto","created_at":"2022-01-11 17:58:36","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":56133,"visible":true,"origin":"","legend":"\u003cp\u003eFactor structure of the short versions of the Depression Anxiety Stress Scale (DASS)-21: the DASS-8 (a) and the DASS-12 (b) among women with chronic pelvic pain.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-1212124/v1/0f8424b2b6fea51ceaafe3e7.png"},{"id":17214904,"identity":"55f1a5e2-6a04-4bae-acab-6e27a05007b6","added_by":"auto","created_at":"2022-01-11 17:58:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":70955,"visible":true,"origin":"","legend":"\u003cp\u003eStructural equation model using the Depression Anxiety Stress Scale 8 (DASS-8) (a) and the DASS-12 (b) to predict pain intensity, pain days, sex pain, poor sleep, and concurrent headache among women with chronic pelvic pain.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-1212124/v1/09b62b88288b5e83bca2647c.png"},{"id":17214907,"identity":"b8c0445c-cfd5-4a11-852e-e3fdfaf5b8ed","added_by":"auto","created_at":"2022-01-11 17:58:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":623869,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1212124/v1/9159bb5f-53d8-4398-b917-b0bf7b820b02.pdf"},{"id":17214905,"identity":"508365b3-9fd7-45b8-8278-f94d492ee1d2","added_by":"auto","created_at":"2022-01-11 17:58:35","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":933728,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAppendix A. \u003c/strong\u003eSupplementary excel 1 showing extra relevant analyses that are not reported in the text.\u003c/p\u003e","description":"","filename":"AppendixA..xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1212124/v1/384407d00e6ad3ad6b03b747.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eThe Depression Anxiety Stress Scale 8: Its Psychometric Evaluation Among Women with Chronic Non-Cancer Pelvic Pain\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePain in the pelvis unrelated to cancer, intercourse, or menstruation; which is experienced daily and persists for at least three consecutive months is known as chronic pelvic pain (CPP). CPP is commonly experienced by up to 22% of women [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. It can be idiopathic or due to numerous urological, bowel-related, and gynecological reasons [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Because chronic noncancer pain conditions in women worsen over time, especially during the peak reproductive years, fluctuations in ovarian hormones are suggested to be key modulators in the pathologies underlying CPP such as endometriosis and irritable bowel syndrome [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDifferences in CPP experience and pathology between reproductive age women and peri/postmenopausal women are reported in the literature [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Conditions entailing reduced levels of feminine hormones (e.g., menopause and during menses) are associated with increased sensitivity to visceral and pelvic pain [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In addition, ovarian collapse and subsequent reduction in estrogen during menopause is associated with numerous vegetative (e.g., hot flushes), physical (e.g., fatigue and back pain), urogenital/sexual (e.g., dyspareunia and urinary incontinence), cognitive (e.g., memory problems), and mental symptoms (e.g., depression and anxiety), which may aggravate pain sensitivity in midlife women and endanger their mental wellbeing [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In fact, CPP women within the age range of 25 to 35 years are reported to express less anxiety symptoms than their older counterparts [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe annual healthcare expenditure of CPP is enormous, exceeding 6.5 billion dollars in Australia [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In addition, CPP alters women\u0026rsquo;s quality of life, reproductive capacity, social relations, work performance, and sexuality. As a result, CPP women experience high levels of distress, depression, and anxiety [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Depression, anxiety, and mixed anxiety depression disorder (MADD) prevail in 63%, 66%, and 54% of women experiencing CPP compared with 38%, 49%, and 28% of CPP-free women [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Exposure to different forms of abuse during early stages of life is associated with the development and persistence of numerous physical, emotional, mental, and sexual dysfunctions during adulthood [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Moreover, women in different parts of the world witness the highest exposure to different forms of abusive behavior against adults, along with numerous grave consequences [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Physical and sexual abuse represent a major risk factor for CPP.[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] Given the traumatic origins of CPP and the distressful course of the condition, it is frequently managed within the biopsychosocial model of chronic pain\u0026mdash;an approach that emphasizes the importance of wholistic management of chronic pain conditions \u0026ldquo;pain itself along with associated psychological and social problems\u0026rdquo; for more positive treatment outcomes [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, CPP women experience varying levels of psychological distress. Greater comorbidity (e.g., depression, poor sleep, fatigue, somatic symptoms) is more common among women experiencing higher distress than those with little or no distress [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Therefore, careful identification of highly distressed CPP women through assessing psychopathological symptoms is extremely crucial for designing effective interventions for CPP and evaluating the outcomes of such interventions [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Depression, Anxiety, and Stress Scale-21 (DASS-21) is a simple measure frequently used in research and clinical practice to capture the distinct features of depression, anxiety, and stress symptomatology [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, numerous studies reported enormous flaws associated with the DASS-21: variations in its dimensional structure [\u003cspan additionalcitationids=\"CR15 CR16\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], invariance across different groups [\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], and a ceiling effect [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. As a result, many revisions of its item structure took place. Using several non-clinical samples, Osman et al. reported that the DASS-21 may be best used as a measure of psychological distress \u003csup\u003e[22]\u003c/sup\u003e\u0026mdash;a state of emotional suffering that combines non-specific symptoms of depression and anxiety [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. They also reported that numerous items poorly correlated with the underlying latent construct covered by the DASS-21, noting that reducing its items to 13 or nine items would remedy such flaws [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Subsequently, a 12-item version of the DASS-21 has been tested in non-clinical and clinical Korean samples [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. However, this version has not been tested in another population until recently. A current study used clinical and non-clinical samples from Saudi Arabia to investigate various models of the parent scale as well as all the available shortened versions [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The fit of different models of the DASS-21 was considerably lower than all its short versions. An extensive revision of the item structure of the DASS-21 based on statistics and conceptual methods resulted in an 8-item version of the DASS-21. The DASS-8 expressed excellent psychometric properties compared with Osman\u0026rsquo;s 13-item/nine-item DASS and the Korean DASS-12 [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Likewise, another investigation involving healthy individuals from the US, Australia, and Ghana, the DASS-8 expressed a better fit and more robust discriminant and criterion validity than the DASS-12. However, both the DASS-8 and DASS-12 exhibited variance at the scalar level across English-speaking and Ghanaian participants, with the latter expressing lower levels of distress [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Individuals\u0026rsquo; responses to items of the DASS-8 in different cultures may vary since individuals tend to selectively express their distress symptoms through culturally acceptable ways [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBrief screening instruments are intended to be used more frequently as clinical tools to facilitate the identification of pathological cases and enable assessing response to treatment. Accordingly, there is an intense need to ensure the relevance, local precision, and adequate sensitivity of these instrument [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. To benefit from the DASS-8 as a brief measure of depression/anxiety and stress symptomatology, it needs to be evaluated in more diverse populations, including patient groups, to ensure the adequacy of its sensitivity. Therefore, this study aimed to examine the psychometrics of the DASS-8 in a sample of Australian women with CPP. We hypothesized that 1) the DASS-8 would express better fit and less variance than the DASS-12; 2) the DASS-8 would discriminate CPP women experiencing mental comorbidities from those without mental comorbidities; 3) the DASS-8 would correlate with the DASS-21 at the same level expressed by the DASS-12; and 4) the DASS-8 would correlate with pain symptoms and history of sexual assault at the same level expressed by the parent scale.\u003c/p\u003e"},{"header":"Material And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design, participants, and procedure\u003c/h2\u003e \u003cp\u003eThis study is a secondary analysis based on a publicly accessible dataset from a previously published cross-sectional study [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], which comprises a convenient sample of women with CPP. Data were collected via a pre-treatment self-administered questionnaire addressed to all clients attending a specialist pelvic pain clinic in South Australia over 18 months between January 2015 and July 2016. Women not signing informed consent, with several incomplete sections of the questionnaire, or solely experiencing period pain or dyspareunia were excluded from the study. Women or their guardian, if they were less than 18 years old, signed an informed consent. Because the protocol for data collection was previously approved by University of South Australia Human Research Ethics Committee (Application ID: 0000036598; 26/05/2017) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], and the dataset was publicly accessible [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], we did not obtain an ethical approval for the current study.\u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003eMeasures\u003c/h2\u003e \u003cp\u003eThe questionnaire used for data collection comprised a large set of questions about pain experienced, its intensity, duration, pain-free days per month, pain severity during sexual activity, severity of stabbing pelvic pain, pain severity on the day of data collection, experiencing (tiredness/fatigue, anxiety, low mood, bad headache), somatic symptoms (e.g., nausea, unusual sweating, dizziness, and bloating), history of sexual assault, current psychiatric disorders, etc. Questions addressing pain severity or intensity prompted the respondents to rate the intensity of pain on a scale from 0 (no pain) to 10 (extremely severe pain).\u003c/p\u003e \u003cp\u003eThe Depression anxiety stress scale (DASS-21) was used to measure psychological distress. It comprises 21 items, in three subscales that assess symptoms of depression, anxiety and stress. Item responses are rated on a 4-point scale ranging from 0 (did not apply to me at all) to 3 (applied to me very much or most of the time). The minimum and maximum total scores of the DASS-21 are 0 and 63 [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The DASS-8 comprises eight items, in three subscales: depression (three items e.g., felt down hearted and blue), anxiety (three items e.g., felt scared without reason), and stress (two items e.g., was using a lot of my mental energy) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The total scores of the DASS-8 and its subscales range between 0 to 24, 0 to 9, 0 to 9, and 0 to 6, respectively. The DASS-12 comprises 12 items, in three subscales, each comprising four items. The total scores of the DASS-8 and its subscales range between 0 to 24 and 0 to 12, respectively [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The reliability of the DASS-21, DASS-8, and DASS-12 in this sample is excellent (coefficient alpha = 0.95, 0.90, and 0.90, respectively).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eFirst, we checked the dataset for missing responses. Because multiple items of the DASS-21 had missing responses, we removed all participants with incomplete data on the DASS-8 and DASS-12, which resulted in a final sample size of 214 participants\u0026mdash;response rate = 0.90%. The normality of different version of the DASS were tested by Shapiro Wilk W test. The statistics of non-normal variables are reported as median (MD) and interquartile range (IQR; Q1-Q3) while mean and standard deviation were used to report normally-distributed variables. Number and percentage were used to describe categorical variables.\u003c/p\u003e \u003cp\u003eBased on a former investigation [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], the factor structures of the DASS-8 and DASS-12 were examined using confirmatory factor analysis (CFA). To evaluate model fit as good or acceptable, we used chi square (χ2) index, ideally it should be non-significant, Comparative Fit Index (CFI) and Tucker\u0026ndash;Lewis Index (TLI) equal to or above 0.95 and 0.90, respectively, in addition to standardized root-mean-square residual (SRMR) and root mean square error of approximation (RMSEA) less than 0.06 and 0.08, respectively [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. This combination allows parsimonious evaluation of model fit because \u003cem\u003eχ\u003c/em\u003e \u003csup\u003e2\u003c/sup\u003e is largely dependent on sample size, which if used alone may disqualify well-fitting models that express minor misspecifications [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Based on suggestions pointed by modification indices, few error terms were correlated to improve model fit.\u003c/p\u003e \u003cp\u003eTo test measurement invariance of the DASS-8, age was categorized in two groups (156 below the age of 40 versus 58 aged 40 years and above). Then, multigroup CFA was conducted to compare invariance of the DASS-8 and DASS-12 at the configural, metric, scalar, and strict levels [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] across groups of age, menopausal status (menopausal vs premenopausal), and psychiatric comorbidity (presence of comorbidity vs no comorbidity, the number of subjects in all the categories are shown in Table 1). Significant changes in \u003cem\u003eχ\u003c/em\u003e \u003csup\u003e2\u003c/sup\u003e in constrained models, along with ΔCFI and ΔRMSEA above 0.02 and 0.015, respectively were used as criteria for non-invariance [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo examine the discriminant validity of the DASS-21, DASS-12, DASS-8, Mann Whitney U test was used to determine whether these measures and their subscales can differentiate CPP women with comorbid psychiatric disorders from those without psychopathology. It was also used to differentiate women with depressive disorder from those with anxiety disorder. In addition, heterotrait-monotrait (HTMT) ratio of correlations of items comprising the DASS-21, DASS-12, DASS-8 were computed [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Moreover, two-step cluster analysis was used to determine whether the participants can be grouped according to the scores of the DASS-8 and its subscales. Two-step cluster analysis is a hybrid technique that operates via two steps. The first step (pre-clustering) employs a sequential approach to separate groups by pre-clustering cases based on a distance measure that defines dense regions in the analyzed attribute-space. In the second step (clustering), a probabilistic approach is used to statistically merge pre-clusters stepwise until the optimal subgroup model is determined. This technique is highly reliable; in terms of the number of subgroups detected, classification probability of individuals into subgroups, and reproducibility of the findings on different types of data. It has additional merits: analyzing atypical values (i.e., outliers), determining the number of clusters based on a statistical measure of fit rather than on an arbitrary choice, using categorical and continuous variables simultaneously, and handling large datasets [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Independent sample t-test, Mann Whitney test, and \u003cem\u003eχ\u003c/em\u003e \u003csup\u003e2\u003c/sup\u003e were used to compare the differences in mental symptomatology and characteristics of the participants across clusters.\u003c/p\u003e \u003cp\u003eThe reliability of the DASS-21, DASS-12, DASS-8, and their subscales was assessed by coefficient alpha, alpha-if-item deleted, and item-total correlations. The predictive validity of the DASS-12, DASS-8, and their subscales was detected by Spearman\u0026rsquo;s r correlating these measures to the original scale and its subscales. This test was also used to evaluate the criterion validity of the three measures by correlating their scores with sexual assault experience, number of pain days/pain-free days per month, pain severity during sexual activity, pain severity on the day of data collection, severity of stabbing pelvic pain, experiencing bad headache, experiencing tiredness/fatigue, experiencing anxiety, and experiencing low mood. Additionally, a general structural equation path model (SEM) was constructed to use the DASS-8/DASS-12 and their subscales to predict these characteristics. Model fit was based on the same criteria used in CFA. Nonsignificant paths were trimmed to allow a better fit. All analyses were conducted in SPSS and Amos, and significance was considered at a probability level less than 0.05 in two-tailed tests.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eCharacteristics of the participants\u003c/span\u003e \u003c/p\u003e \u003cp\u003eParticipants in this study (N = 214, mean age = 33.1\u0026plusmn;12.4 years) were women complaining from CPP. The participants experienced several types of pain (stabbing pelvic pain, sex pain, bowel pain, and headache), somatic symptoms (e.g., bloating, nausea, dizziness, unusual sweating), along with symptoms of low mood, anxiety, and psychiatric comorbidity. Table 1 shows more information on the sociodemographic and clinical characteristics of the participants in the overall sample as well as group differences in these variables between low distress and high distress women.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eResults of confirmatory factor analysis and invariance analysis\u003c/span\u003e \u003c/p\u003e \u003cp\u003eAs shown in Table 2, the one-factor structure of the DASS-8/DASS-12 expressed unsatisfactory fit. The crude models of the three-factor structures of the DASS-8 and the DASS-12 expressed good fit. Correlating the error terms of two items (Figure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) in both models slightly improved the fit. The fit of the second order structure was similar to that of the three-factor structure of both scales (supplementary material). While the bifactor structure of the DASS-8 expressed good fit with all items significantly loading on the general factor, item 12 and item 20 failed to load on their domain-specific factors of stress and anxiety, respectively (p \u0026gt;.05). In addition, item 15 loaded significantly on the anxiety factor (p = .04), but its loading on this factor was weak (β\u0026thinsp;=\u0026thinsp;.26). All items of the anxiety subscale of the DASS-12 failed to load on their corresponding factor in the bifactor model. Therefore, the three-factor structures of the DASS-8/DASS-12 represent the best fit of the data.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs shown in Table 3, the three-factor structures of the DASS-8 and DASS-12 were invariant at the configural, metric, scalar, and strict levels across groups of age and menopausal status. However, the DASS-8 was non-invariant at the scalar level across groups of psychiatric comorbidity (ΔCFI \u0026gt; 0.02 and ΔRMSEA \u0026gt;0.15). The DASS-12 was non-invariant at the strict level (ΔCFI \u0026gt; 0.02 and ΔRMSEA \u0026gt;0.15), and it also tended to be non-invariant at the scalar level across comorbidity groups (SRMR = 0.1117).\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eResults of discriminant validity tests\u003c/span\u003e \u003c/p\u003e \u003cp\u003eAs noted in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the DASS-21, DASS-8, DASS-12 differentiated between women with a current psychiatric disorder and those without at the same level of significance (p \u0026lt; 0.001). However, the z scores of the DASS-8 and its subscales were higher than those of the DASS-12 and the DASS-21, indicating a higher level of discriminant validity. Nonetheless, neither the DASS-21, DASS-8, DASS-12 nor their subscales could differentiate women with a diagnosis of depression from those with a diagnosis of anxiety. Likewise, the DASS-21, DASS-8, DASS-12, and their subscales significantly correlated with subjective experience of anxiety and low mood at the same levels (all p values \u0026lt; 0.01, Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The HTMT ratio of correlations show that the constructs covered by the subscales of the DASS-8 and DASS-12 were distinct (\u0026lt; 0.85). However, the stress and anxiety subscales on the DASS-8 were overlapping (HTMT ratio = 0.95). All the subscales of the parent scale exhibited overlap, albeit it was marginal for the stress-anxiety subscales (HTMT ratio = 0.85 supplementary materials).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics and discriminant validity of the Depression Anxiety Stress Scale 21 and its shortened versions among women with chronic pelvic pain\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDASS versions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhole sample\u003c/p\u003e \u003cp\u003e(N = 214)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMann Whitney test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ez\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCluster 1\u003c/p\u003e \u003cp\u003e(n = 141)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCluster 2\u003c/p\u003e \u003cp\u003e(n = 73)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMann Whitney test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ez\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMD (IQR)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eMD (IQR)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eMD (IQR)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDASS-21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e11.5 (6.0-23.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2247.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-5.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c5\"\u003e \u003cp\u003e7.0 (4.0-11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c6\"\u003e \u003cp\u003e29.5 (23.0-36.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e210.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-11.43\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e2.0 (1.0-7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2495.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-5.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c5\"\u003e \u003cp\u003e1.0 (0-3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c6\"\u003e \u003cp\u003e9.0 (5.0-14.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1041.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-9.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e3.0 (1.0-7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2482.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-5.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c5\"\u003e \u003cp\u003e1.0 (0-3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c6\"\u003e \u003cp\u003e8.0 (6.0-11.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e728.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-10.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e6.0 (3.0-11.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2641.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-4.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c5\"\u003e \u003cp\u003e4.0 (2.0-6.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c6\"\u003e \u003cp\u003e12.0 (10.0-16.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e436.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-10.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDASS-12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e7.0 (3.0-13.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2320.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-5.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c5\"\u003e \u003cp\u003e4.0 (2.0-7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c6\"\u003e \u003cp\u003e17.0 (13.0-21.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e397.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-11.08\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e1.0 (1.0-4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2266.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-5.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c5\"\u003e \u003cp\u003e0 (0-1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c6\"\u003e \u003cp\u003e5.0 (3.0-8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1082.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-9.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e2.0 (0-4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2842.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-4.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c5\"\u003e \u003cp\u003e1.0 (0-2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c6\"\u003e \u003cp\u003e4.0 (3.0-6.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1514.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-8.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e4.0 (2.0-7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2849.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-4.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c5\"\u003e \u003cp\u003e2.0 (1.0-4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c6\"\u003e \u003cp\u003e8.0 (6.0-9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e856.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-10.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDASS-8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e4.0 (1.0-8.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2018.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-6.27\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c5\"\u003e \u003cp\u003e2.0 (1.0-3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c6\"\u003e \u003cp\u003e12.0 (8.0-15.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e36.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-11.95\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e1.0 (0-3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2346.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-5.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c5\"\u003e \u003cp\u003e0 (0-1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c6\"\u003e \u003cp\u003e4.0 (2.0-6.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1214.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-9.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e1.0 (0-3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2521.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-5.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c5\"\u003e \u003cp\u003e0 (0-1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c6\"\u003e \u003cp\u003e4.0 (3.0-6.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e674.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-10.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e \u003cp\u003e2.0 (1.0-3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2447.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-5.26\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c5\"\u003e \u003cp\u003e1.0 (0-2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c6\"\u003e \u003cp\u003e4.0 (3.0-5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e364.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-11.37\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eDASS: Depression Anxiety Stress Scale, MD: median, IQR: interquartile range, U: Mann Whitney U test, p values were all significant at 0.001 level. For the DASS-21 (N = 212).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn two-step cluster analysis, the DASS-8 and its subscales classified the participants into two clusters: low distress (cluster 1: n = 141, 65.9%) and high distress (cluster 2: n = 73, 34.1%). The model expressed good fit as indicated by Silhouette measure of cohesion and separation of around 0.7 and ratio of sizes less than 3 (1.93). Values of the predictor importance of the DASS-8 followed by stress, anxiety, and depression were 1, 0.85, 0.73, and 0.5, respectively. Mann Whitney U test revealed significant differences in the level of all mental distress symptoms among participants in both clusters\u0026mdash;they were all significantly higher in cluster 2 than in cluster 1 (all p \u0026lt; 0.001), with the DASS-8 and its stress subscale expressing the highest z scores (Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAge, menopausal status, bloating, and the frequency of stabbing pelvic pain and sex pain did not vary significantly across clusters. However, participants in cluster 2 demonstrated significantly higher number of pain days (t(146.9)= -2.50, p = 0.014), less pain free days (U = 3654.0, z = -2.39, p = 0.017); more severity of stabbing pelvic pain (t(134.42) = -2.47, p = 0.015), sex pain (t(105.22) = -3.74, p = 0.001), current pelvic pain (U = 3095.0, z = -3.29, p = 0.001), concurrent headache (t(118.11) = -3.51, p = 0.001); higher frequency of bowel pain (\u003cem\u003eχ\u003c/em\u003e \u003csup\u003e2\u003c/sup\u003e(1) = 6.68, p = .010), greater occurrence of sexual assault (\u003cem\u003eχ\u003c/em\u003e \u003csup\u003e2\u003c/sup\u003e(1) = 19.06, p = .001), psychiatric co-morbidity (\u003cem\u003eχ\u003c/em\u003e \u003csup\u003e2\u003c/sup\u003e(2) = 23.61, p = 0.001), psychiatric symptoms (low mood (χ2(16) = 29.8, p = 0.001) and anxiety (\u003cem\u003eχ\u003c/em\u003e \u003csup\u003e2\u003c/sup\u003e(1) = 50.50, p = 0.001)), fatigue (\u003cem\u003eχ\u003c/em\u003e \u003csup\u003e2\u003c/sup\u003e(1) = 14.12, p = 0.001), sleep problems (\u003cem\u003eχ\u003c/em\u003e \u003csup\u003e2\u003c/sup\u003e(16) = 12.13, p = 0.001), and somatic symptoms (dizziness (\u003cem\u003eχ\u003c/em\u003e \u003csup\u003e2\u003c/sup\u003e(1) = 7.57, p = 0.006), unusual sweating (\u003cem\u003eχ\u003c/em\u003e \u003csup\u003e2\u003c/sup\u003e(1) = 9.52, p = 0.002), and nausea (\u003cem\u003eχ\u003c/em\u003e \u003csup\u003e2\u003c/sup\u003e(1) = 13.65, p = 0.001)).\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eResults of tests of reliability, normality, and criterion validity\u003c/span\u003e \u003c/p\u003e \u003cp\u003eThe reliability of the DASS-21, DASS-8, and DASS-12 was excellent. Meanwhile, the reliability of the shortened subscales ranged from very good to poor (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e5\u003c/span\u003e)\u0026mdash;poor reliability was reported only for the anxiety subscale of the DASS-12. The predictive validity of the DASS-8, DASS-12, and their subscales is depicted by their strong correlation with the original scale and its subscales (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The normality of the DASS-8 and the DASS-12 is comparable with that of the DASS-21 as noted by Shapiro\u0026ndash;Wilks\u0026rsquo; W. As shown in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e5\u003c/span\u003e, all the DASS versions and most of their subscales negatively correlated with pain-free days and positively correlated with pain experience on the survey day, pain days per month, concurrent headache, poor sleep, fatigue, somatic symptoms (nausea, bloating, dizziness, unusual sweating), experience of low mood and anxiety, as well as sexual assault experience. Notably, all the subscales of the DASS-8 correlated with sexual assault experience while the anxiety and stress subscales of the DASS-12 as well as the stress subscale of the DASS-21 could not correlate with this variable. Similarly, all subscales of the DASS-8 correlated with the severity of stabbing pelvic pain while the stress subscale of the DASS-12 and the DASS-21 failed to correlate with this variable.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInternal consistency, predictive validity, normality, and criterion validity of the Depression Anxiety Stress Scale (DASS) 21, DASS-12, DASS-8, and their subscales among women with chronic pelvic pain\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCriteria\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDASS-21\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStress\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDASS-12\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eStress\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eDASS-8\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eStress\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCoefficient alpha\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.931\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.837\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.878\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.898\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.845\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.693\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.827\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.794\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.705\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRange of corrected item-total correlations\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.401-0.776\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.598-0.847\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.370-0.713\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.593-0.735\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.401-0.785\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.607-0.719\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.371-0.550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.607-0.746\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.629-0.744\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.882-0.944\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.634-0.662\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.545\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRange of alpha if-item-deleted\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.940-0.946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.914-0.939\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.795-0.853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.851-0.869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.881-0.902\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.787-0.833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.585-0.708\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.742-0.809\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.884-0.893\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.831-0.870\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.702-0.733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCorrelation with subscale of the DASS-21\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.930\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.919\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.948\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.934\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.871\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.871\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCorrelation with the DASS-21\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.856\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.823\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.929\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.966\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.838\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.718\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.863\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.943\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.811\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.789\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.818\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eShapiro Wilk test\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.892\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.812\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.848\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.936\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.906\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.787\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.843\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.933\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.864\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.788\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.790\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.891\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCorrelation with sexual assault experience\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.203**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.264***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.196**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.192*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.278***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.259**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.245**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.261***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.188*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCorrelation with pain days/month\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.183**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.221**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.183**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.193**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.190**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.204**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.180*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.177*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.172*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.163*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCorrelation with pain-free days/month\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.182**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.217**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.174*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.193**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.188**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0-.201**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-0.139*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.179*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-0.173*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e-0.168*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-.168*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCorrelation with severity of pain today\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.265***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.217**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.331***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.238**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.290***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.255***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.291***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.239**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.265***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.225**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.274***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.234**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCorrelation with severity of stabbing pelvic pain\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.200**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.167*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.287**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.209**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.174*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.246**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.205**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.149*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.246**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.153*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCorrelation with severity of pain during sexual activity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.262**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.308***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.210*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.222**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.280**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.326***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.187*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.229**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.257**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.285**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.218**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.227**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCorrelation with severity of bad headache\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.387***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.300**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.253**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.378***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.395***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.324***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.221*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.363***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.299**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.303**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.225*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.234**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCorrelation with experienced anxiety\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.517**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.430**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.412**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.491**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.498**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.427**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.323**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.478**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.531**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.425**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.473**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.467**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCorrelation with experienced low mood\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.487**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.482**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.323**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.446**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.478**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.512**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.227**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.447**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.514**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.492**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.400**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.412**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCorrelation with experienced fatigue\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.345**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.296**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.333**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.305**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.348**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.300**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.346**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.288**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.322**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.283**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.231**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.298**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCorrelation with poor sleep\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.303**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.250**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.337**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.248**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.305**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.227**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.329**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.238**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.283**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.246**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.240**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.257**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCorrelation with dizziness\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.251**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.174**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.333**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.191**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.243**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.192**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.335**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.150*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.244**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.181**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.262**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.211**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCorrelation with unusual sweating\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.238**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.182**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.280**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.215**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.239**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.174*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.306**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.197**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.222**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.179**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.189**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.257**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCorrelation with nausea\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.256**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.240**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.339**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.180*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.259**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.221**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.349**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.145*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.236**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.219**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.260**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.154*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCorrelation with bloating\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.259**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.216**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.255**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.206**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.247**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.213**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.234**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.193**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.279**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.245**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.234**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.246**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003e*, **, ***: correlation is significant at a level of 0.05, 0.01, 0.001, respectively.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAfter trimming non-significant paths, SEM used to test criterion validity of the DASS-8/DASS-12 expressed good fit (χ2(16, 16) = 10.677, 6.956; p = 0.829, 0.974; both CFI= 1.00, both TLI = 1.00, both RMSEA = 0.00, SRMR = 0.0420, 0.0376). Scores of the DASS-8/DASS-12 significantly predicted current pain severity, poor sleep, and sex pain. Scores of their anxiety subscales predicted concurrent headache while scores of their stress subscales predicted the number of pain days per month (Figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The DASS-8 and DASS-12 exerted significant indirect effects on headache through current pain severity (β = -0.055, 95% CI: -0.120 to -0.011, p = 0.023) and (β = -0.067, 95% CI: -0.142 to -0.018, p = 0.011), respectively as well as on sex pain through poor sleep (β\u0026thinsp;=\u0026thinsp;0.070, 95% CI: 0.023 to 0.114, p = 0.011) and (β\u0026thinsp;=\u0026thinsp;0.073, 95% CI: 0.031 to 0.118, p = 0.011, 0.007), respectively. Month pain days mediated the effect of the stress subscale of the DASS-8 and DASS-12 on sex pain (β = -0.045, 95% CI: -0.091 to -0.007, p = 0.037) and (β = -0.042; 95% CI: -0.100 to -0.009; p = 0.041), respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eDistress symptoms are excessively experienced in CPP patients [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], and its management can considerably affect disease recovery [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Because not all CPP women express higher levels of distress and resources directed toward management of distress are limited [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], there is a great need for brief measures that may facilitate the identification of highly distressed patients as well as response to treatment [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Using numerous robust psychometric testing techniques, the present study reports usefulness of the DASS-8 as a measure of distress, depression, anxiety, and stress symptomatology among Australian women with CPP.\u003c/p\u003e \u003cp\u003eThe crude models of the three-factor structure of the DASS-8/DASS-12 expressed better fit than all other crude models. RMSEA was on the high side for the DASS-8, suggesting minor misspecifications in item loadings. The fit of this model was considerably improved by correlating the residuals of item 12 \u0026ldquo;I found it difficult to relax\u0026rdquo; on the stress subscale and item 13 \u0026ldquo;I felt down-hearted and blue\u0026rdquo; on the depression subscale. Likewise, the fit of the DASS-12 was slightly improved by correlating the residuals of item 12 and item 1 \u0026ldquo;I found it difficult to wind down\u0026rdquo; on the stress subscale. Accordingly, the final model of the DASS-8 expressed a perfect fit on all CFA fit indices, superior to the DASS-12, indicating a better construct validity of the DASS-8 as we hypothesized. Meanwhile, the fit of the second-order factor structure of both scales was similar to the three-factor structure (supplementary material), indicating usability of the total score and the score of the subscales of these scales.\u003c/p\u003e \u003cp\u003eThe three-factor structures of both scales exhibited configural, metric, scalar, and strict invariance across groups of age and menopausal status. Across groups of psychiatric comorbidity, the DASS-8 was non-invariant at the scalar level and the DASS-12 expressed misfit (indicating tendency toward non-invariance) at the scalar level and it was non-invariant at the strict level. Critical ratios for differences between parameters noted that the source of non-invariance of the DASS-8 involved: 1) lower loadings of item 20 \u0026ldquo;I felt scared without any good reason\u0026rdquo; on the anxiety subscale and item 12 on the stress subscale, 2) weaker correlation between the anxiety and depression subscales, and 3) less covariance between items 12 and 13. All were noted among participants not diagnosed with a mental disorder compared with those having a psychiatric disorder. Non-invariance of the DASS-12 involved differences in the loading of item 17 \u0026ldquo;I felt I was not worth much as a person\u0026rdquo; and the variances of items 1, 3 \u0026ldquo;I couldn\u0026rsquo;t seem to experience any positive feeling at all\u0026rdquo;, and 10 \u0026ldquo;I felt that I have nothing to look forward\u0026rdquo;\u0026mdash;all on the depression subscale. Investigations of discriminant validity revealed significant differences in all distress scores between both groups.\u003c/p\u003e \u003cp\u003eThe DASS-8 can be a beneficial brief measure for identifying CPP women with psychiatric comorbidity, high level of distress, and other debilitating symptoms (e.g., greater pain severity, poor sleep, concurrent headache, gastrointestinal discomfort, etc.). This is because the DASS-8 expressed adequate discriminant validity by differentiating CPP women with psychiatric comorbidities from those who are mental-illness free. Although the discriminant validity of the DASS-8, DASS-12, and DASS-21 was expressed at the same level of significance (p = 0.001), the z scores associated with the DASS-8 were higher than those of the DASS-12 and DASS-21 (Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e4\u003c/span\u003e), indicating superior discriminant validity of the DASS-8. This finding is consistent with a former investigation in which the DASS-8 potently identified psychiatric patients from healthy subjects [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. On the other side, the DASS-8 as well as the DASS-12 and the DASS-21 could not discriminate CPP women with depression disorder from those with anxiety disorder. In line, the DASS-21 and the DASS-12 have been previously reported to lack the capacity to differentiate depression disorder from anxiety disorder [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. These findings are consistent with other results on the reported comorbidity of both depression and anxiety disorders, confirming that the DASS measure is not a clinically diagnostic tool, but it can efficiently identify individuals prone to both depression and anxiety psychopathologies [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. This can be a merit of a brief self-administered measure. Extra diagnostic workout can be performed in a next step to attain a formal diagnosis.\u003c/p\u003e \u003cp\u003eIn two-step cluster analysis, the DASS-8 and its subscales classified CPP women into two clusters with low and high levels of distress. The DASS-8 and its stress subscale had higher predictor importance values than anxiety and depression. Mann Whitney U test revealed significant differences (all p values = 0.001) in the scores of all the DASS measures among women in both clusters, with the DASS-8 and its stress subscale exhibiting the highest z scores (Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e4\u003c/span\u003e). As shown in Table 1, participants in cluster 2 (high distress) scored significantly higher on symptoms of pain severity, bowel pain, depression, anxiety, fatigue, dizziness, nausea, and unusual sweating than participants in cluster 1. This finding is consistent with a former study, which classified women into two clusters: one cluster comprised women high on depression, fatigue, and poor sleep while the other cluster comprised women experiencing no or minimal levels of these symptoms [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, Mann Whitney U test, cluster analysis, and SEM in the present study indicate stronger discriminant validity of the DASS-8 and its stress and anxiety subscales than the depression subscale. Overall, the DASS-8 can be efficiently used to differentiate highly distressed CPP women (e.g., with psychiatric comorbidity and more severity of mental symptoms, pain, and physical symptoms) from those with low levels of distress.\u003c/p\u003e \u003cp\u003eApart from good fit, invariance, and adequate discriminant validity, the DASS-8 demonstrates other excellent psychometric characteristics. As shown in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e5\u003c/span\u003e, the internal consistency of the DASS-8 and all its subscale was good\u0026mdash;considerably higher than that of the DASS-12 as we hypothesized, except for the stress subscale, which comprises half the number of items on the corresponding subscale of the DASS-12. Whereas the values of alpha-if-item deleted indicated reduction in the reliability of the DASS-8, they indicated an increase in the reliability of the DASS-12 and its anxiety subscale (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e5\u003c/span\u003e), lending support to the more robust convergent validity of the DASS-8. Consistent with our preset hypothesis, strong correlations of the DASS-8 and its subscales with the DASS-21 and its subscales convey adequate item coverage, predictive validity, and convergent validity. Generally, these results highlight the high homogeneity, specificity, and sensitivity of the items comprising the DASS-8, which have been reported among Arabs and English-speaking participants [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn parallel, the DASS-8 and all its subscales exhibited significant correlations with sexual assault, pain duration (pain days per months), pain-free days, pain intensity, somatic symptoms, fatigue, poor sleep, bad headache, etc. On the other hand, the stress and depression subscales of the DASS-21 failed to correlate with sexual assault and pain-free days, respectively. Likewise, the anxiety and depression subscales of the DASS-12 failed to correlate with sexual assault while the correlation of the overall DASS-12 with sexual assault was at a lower level than that expressed by the DASS-8 (r = 0.192, p = 0.05 vs r = 0.259, p = 0.01). These findings indicate better criterion validity of the DASS-8. They are also congruent with recent studies reporting significant correlations of the subscales of the DASS-21 with stabbing pelvic pain, migraine, intimate partner violence/domestic violence; as well as early childhood physical, sexual and emotional abuse among women [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Moreover, SEM revealed that the DASS-8/DASS-12 and their subscales, except for depression, can directly and indirectly predict pain severity, pain days, sex pain, concurrent headache, and poor sleep (Figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Therefore, the DASS-8 can be reliably used as a valid criterion to predict different noxious symptoms and experiences in CPP.\u003c/p\u003e \u003cp\u003eThis study is the first attempt to confirm the psychometric soundness of the DASS-8 as a measure of mental symptomatology among Australian women with CPP. Results obtained from different robust testing techniques in this study emphasize excellent psychometric properties of the DASS-8; in terms of fit, invariance, predictive validity, convergent validity, discriminant validity, criterion validity, and reliability. These finding are all in line with those reported in Arab psychiatric patients as well as in healthy respondents from Saudi Arabia, Australia, the US, and Ghana.[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] Nonetheless, the study has many limitations that should be acknowledged. The generalizability of the finding is limited out of possible risk for selection bias: 1) the sample is collected from a single clinic, 2) a priori power analysis for determining the sample size is lacking, 3) data on the respondents who declined participation in the survey are lacking, 4) inclusion and exclusion criteria are not clearly defined, and 5) the results are based on a convenience sample, which may not represent all CPP women in other settings or countries. The cross-sectional design used precludes test-retest reliability testing and casts doubt on the soundness of relations predicted in SEM. Thus, future investigations may use a longitudinal design to examine the properties of the DASS-8 as well as causal direction of effects addressed in this study, along with mechanisms underlying links between psychological distress, pain, sleep problems, concurrent headache, etc.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003ePsychometric evaluation of the DASS-8 among CPP women by numerous robust techniques revealed its proper fit, invariance, high reliability, good convergent validity, adequate predictive validity, and good criterion validity. The results indicate usability of the DASS-8 as a brief, reliable, invariant measure of mental symptoms in reproductive age and menopausal women with CPP. The Identification of highly distressed women would encourage the use of relevant psychiatric intervention. Owing to its brevity, the DASS-8 can facilitate frequent monitoring of common mental symptomatology over the course of CPP treatment, supporting efforts directed toward improving recovery in CPP population.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e The protocol of data collection was approved by University of South Australia Human Research Ethics Committee (Application ID: 0000036598; 26/05/2017). All participants or their guardians signed a written informed consent before data collection\u0026nbsp;[3]. No ethical approval was obtained for the current study because the analysis is based on a publicly accessible dataset\u0026nbsp;[29]. The present study was conducted according to the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eThe dataset\u0026nbsp;[29]\u0026nbsp;supporting the conclusions of this article is available in Zenodo repository, [https://zenodo.org/record/1307252#.YckoVWhBw2w], and also the datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e The authors would like to thank the Deanship of Scientific Research, Qassim University, for funding the publication of this paper.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHassan, S.; Muere, A.; Einstein, G. 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Depression, anxiety and stress in Saudi migraine patients using DASS-21: local population-based cross-sectional survey. \u003cem\u003eInt J Neurosci\u003c/em\u003e 2021, 1\u0026ndash;9, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/00207454.2021.1909011\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"psychological distress/anxiety/depression, chronic pelvic pain, sexual abuse/assault, short form of the Depression Anxiety Stress Scale 21/Depression Anxiety ","lastPublishedDoi":"10.21203/rs.3.rs-1212124/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1212124/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePsychiatric comorbidity and abusive experiences in chronic pelvic pain (CPP) conditions may prolong disease course. This study investigated the psychometrics of the Depression Anxiety Stress Scale 8 (DASS-8) among women with CPP (N = 214, mean age = 33.3 \u0026plusmn; 12.4 years). The DASS-8 expressed excellent fit, invariance across age groups and menopausal status, good discriminant validity (differentiating women with psychiatric comorbidity from those without comorbidity: U = 2018.0, p = 0.001), excellent reliability (alpha = 0.90), adequate predictive and convergent validity indicated by strong correlation with the DASS-21 (r = 0.94) and high values of item-total correlations (r = 0.884 to 0.893). In two-step cluster analysis, it classified women into low and high distress clusters (n = 141 and 73), with significantly higher levels of distress, pain severity and duration, and physical symptoms in cluster 2. The DASS-8 correlated with pain severity/duration, depression/anxiety symptoms, sexual assault, fatigue, headache severity, and physical symptoms at the same level expressed by the parent scale, or even greater. Accordingly, distress may represent a target for early identification of psychiatric comorbidity, CPP severity, sexual assault, fatigue, etc. Therefore, the DASS-8 is a useful brief measure of mental symptoms among women with CPP.\u003c/p\u003e","manuscriptTitle":"The Depression Anxiety Stress Scale 8: Its Psychometric Evaluation Among Women with Chronic Non-Cancer Pelvic Pain","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-01-11 17:58:34","doi":"10.21203/rs.3.rs-1212124/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvited","content":"","date":"2022-01-10T03:40:14+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2022-01-10T03:16:25+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2021-12-29T01:19:36+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e6229e9f-4e51-404a-9768-cf6e9c86789c","owner":[],"postedDate":"January 11th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":9656530,"name":"Psychology"},{"id":9656531,"name":"Health Economics \u0026 Outcomes Research"}],"tags":[],"updatedAt":"2022-06-16T05:29:25+00:00","versionOfRecord":[],"versionCreatedAt":"2022-01-11 17:58:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1212124","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1212124","identity":"rs-1212124","version":["v1"]},"buildId":"B-jG_2CBjPDmsCi4Wdhf-","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}