Depression Research and Treatment

Depression Research and Treatment / 2018 / Article

Research Article | Open Access

Volume 2018 |Article ID 9250972 | https://doi.org/10.1155/2018/9250972

Debra A. Dunstan, Ned Scott, "Assigning Clinical Significance and Symptom Severity Using the Zung Scales: Levels of Misclassification Arising from Confusion between Index and Raw Scores", Depression Research and Treatment, vol. 2018, Article ID 9250972, 13 pages, 2018. https://doi.org/10.1155/2018/9250972

Assigning Clinical Significance and Symptom Severity Using the Zung Scales: Levels of Misclassification Arising from Confusion between Index and Raw Scores

Academic Editor: Bernard Sabbe
Received20 Jun 2017
Accepted19 Dec 2017
Published21 Jan 2018

Abstract

Background. The Zung Self-Rating Depression Scale (SDS) and Self-Rating Anxiety Scale (SAS) are two norm-referenced scales commonly used to identify the presence of depression and anxiety in clinical research. Unfortunately, several researchers have mistakenly applied index score criteria to raw scores when assigning clinical significance and symptom severity ratings. This study examined the extent of this problem. Method. 102 papers published over the six-year period from 2010 to 2015 were used to establish two convenience samples of 60 usages of each Zung scale. Results. In those papers where cut-off scores were used (i.e., 45/60 for SDS and 40/60 for SAS), up to 51% of SDS and 45% of SAS papers involved the incorrect application of index score criteria to raw scores. Inconsistencies were also noted in the severity ranges and cut-off scores used. Conclusions. A large percentage of publications involving the Zung SDS and SAS scales are using incorrect criteria for the classification of clinically significant symptoms of depression and anxiety. The most common error—applying index score criteria to raw scores—produces a substantial elevation of the cut-off points for significance. Given the continuing usage of these scales, it is important that these inconsistencies be highlighted and resolved.

1. Introduction

Of the conditions contributing to the global disability burden of mental illness, anxiety and depression are the most prevalent disorders [1, 2]. However, while these are conceptually distinct constructs [3, 4], they present as highly comorbid conditions [5, 6]. Further, while an absence of positive affect is considered unique to depression, and other specific factors are unique to particular anxiety disorders (e.g., physiological arousal to posttraumatic stress disorder and panic disorder), the presence of a high level of general distress and negative affect is common to both types of disorder [7, 8]. For these reasons, researchers and clinicians often concurrently screen for the presence and severity of both disorders using self-report psychometric tools developed for this purpose.

Self-report measures of mental disorders may be criterion-referenced or norm-referenced. Criterion-referenced measures are used to make a diagnosis based on the endorsement of criteria listed in published diagnostic classification systems. Individuals are diagnosed with or without a disorder based upon the presence or absence of these criteria [9, 10]. In contrast to criterion-referenced measures, norm-referenced measures compare individuals’ test results to those of an appropriate peer or normative group. These scales typically suggest score ranges linked to symptom severity descriptors and have a “clinically significant” total scale score cut-off point beyond which scores are considered indicative of the presence of a disorder (see Table 1).


RawIndexRawIndex

Clinical cut-off40503645
Severity range
 Mild-moderate40–4750–59
 Moderate-severe48–5560–69
 Severe56+70+

Note. (1974, pp. 176-177); (1980, p. 18).

The Zung Self-Rating Depression Scale (SDS) [11] is a commonly utilized norm-referenced scale. The SDS is a 20-item Likert scale covering symptoms that were identified in factor analytic studies of the syndrome of depression [11]. Items tap psychological and physiological symptoms and are rated by respondents according to how each applied to them within the past week, using a 4-point scale ranging from 1 (none, or a little of the time) to 4 (most, or all of the time). The scale has a raw score range of 20 to 80 points. The raw score is then converted to an index score by dividing the raw score by the maximum score (80) and either expressing this as a decimal or multiplying by 100 to express it as a whole number with an index score range of 25 to 100. Index scores of 25 to 49 indicate nil depression, 50–59 indicate mild to moderate depression, 60–69 indicate moderate to severe depression, and scores over 70 indicate severe depression [12].

Zung [13] also devised a similar 20-item scale to screen for the presence of clinical anxiety: the Self-Rating Anxiety Scale (SAS). Items tap affective and somatic symptoms selected from the diagnostic criteria listed in the Diagnostic and Statistical Manual of Mental Orders (DSM II) current at the time [14]. The scoring structure and index score conversion is similar to that for the SDS. However, for the SAS, the situation regarding cut-off scores is less clear: Zung [6] noted in an early study that all “normal subjects” returned an SAS index score below 50, but later he set an index score of 45 (raw score = 36) as a cut-off point for clinically significant anxiety [15]. Moreover, score ranges for degrees of severity have not been published in the scientific literature.

Unfortunately, the literature reveals a number of discrepancies in the way the Zung scales have been used, reported, and interpreted. In particular, several researchers have mistakenly applied index score cut-offs to raw scores in assigning clinical significance and symptom severity ratings (e.g., [76, 118, 119]). In their Methods sections, these researchers describe the calculation of a total raw score and a “cut-off” score of 50 for morbidity. However, “50” is the index cut-off score set by Zung for the SDS, and this equates a raw score of 40. Using a raw score cut-off of 50 considerably reduces the proportion of cases classed as clinically significant. Another issue is that some researchers have applied severity range descriptors to the SAS when, as stated above, no such descriptors exist in the literature (e.g., [119]).

It is likely that errors in the scoring and interpretation of the Zung scales emanate from two sources that involve a failure to refer to the original publications. One is a reliance on the (erroneous) scale descriptions of other authors. The other is that some clinicians and researchers may have accessed scale information from sourcebooks of psychometric measures where distinctions between index and raw scores are imprecise. For example, both Fischer and Corcoran [120] and Schutte and Malouff [121] fail to clearly specify that recommended cut-off points are based on index and not raw scores.

This paper examines the extent to which these scales have been incorrectly interpreted in the literature. Given the scales’ continued application, it is important that these inconsistencies in interpretation are highlighted and corrected.

2. Method

To investigate the extent to which the Zung scales are being wrongly applied, a search of the ProQuest full text database was conducted. Searches were done for each of the six calendar years from 2010 to 2015, using the terms “Zung Depression Scale,” “Zung Self-Rating Depression Scale,” “Zung Anxiety Acale,” “Zung Self-Rating Anxiety Scale,” and “Zung Self-Rating Scale.” Searches were limited to scholarly articles. For each calendar year, the results were examined in the order presented by the database search engine and, for both the SDS and the SAS, the first ten articles that used that scale to collect new data were selected to form a “convenience” sample indicative of recent use of these scales. Articles reporting on studies using both the SDS and the SAS were included, but theoretical articles and meta-analyses were not. In total, 102 articles were sourced and explored for misinterpretation of both scales. The disciplines covered in the articles were psychiatry (25%), psychology (9%), cardiology (6%), oncology (5%), neurology (5%), and gynecology (5%). The remaining 45% were other medical disciplines.

The results for each paper were recorded against a checklist. Examination initially focused on whether cut-off scores and severity ranges were applied. When this was done, the usage was coded according to the following categories:(1)Consistent use of raw scores: paper uses raw scores only with cut-off scores and/or severity ranges appropriately modified.(2)Consistent use of index scores: paper details conversion to index scores and uses index score cut-offs/severity ranges.(3)Incorrect application: index cut-off scores/severity ranges are specifically applied to raw scores.(4)Unclear application: paper uses index cut-off/severity ranges without mention of conversion from raw scores: however, there was no conclusive evidence that this was not done.(5)Not utilized: cut-off scores/severity ranges are not stated or used.

Notes were also taken where the cut-off and severity ranges applied were different from Zung’s [12, 15] recommendations.

3. Results

Cut-offs for the presence of a disorder were applied in 45 of the 60 papers where the SDS was used and in 40 of the 60 where the SAS was used. For the SDS, index cut-offs were incorrectly applied to raw scores in 16 (35%) of these 45 papers, with a further 7 (16%) papers in which application was unclear. For the SAS, 8 (20%) of the 40 papers revealed incorrect application, with a further 10 (25%) being unclear (Table 2).


SDS (n = 60)SAS (n = 60)

Cut-offs not used1520
Consistent use: raw scores98
Consistent use: index scores1314
Incorrect use168
Unclear application710

As shown in Table 3, the level at which cut-offs were set did not always accord with Zung’s recommendations. In particular, alternative norms have been developed for use in Chinese populations with the cut-off for the SDS set at an index score of 53 (raw score, 42) and, for the SAS, at 50 (raw score, 40). Further, one of the SDS papers used the SAS cut-off (index 45, raw 36) and three of the SAS papers used the SDS cut-off (index 50, raw 40). Another three papers used the newly developed SDS cut-offs for a Chinese population but applied these to European samples. Finally, one of the SDS papers set a much higher cut-off index score of 60 (raw 48).


Reference details Discipline SDS SAS
Used?Cut-offSeverity rangeNotesUsed?Cut-offSeverity rangeNotes

2010

Chagas et al., 2010 [16]Neuroscience25

Friebe et al., 2010 [17]Psychiatry22

Lande et al., 2010 [18]Psychiatry22

Saban et al., 2010 [19]Psychiatry55

Ohira, 2010 [20]Cardiovascular15

Lombardi et al., 2010 [21]Immunology55

Podlipný et al., 2010 [22]Psychiatry22

Ostojic et al., 2010 [23]Rheumatology22“SAS” severity ranges

Sonikian et al., 2010 [24]Nephrology33

Biggs et al., 2010 [25]Psychiatry35

Alimohammadi et al., 2010 [26]Health55

Oishi et al., 2010 [27]Audiology15Cut-off of 48 used (i.e., index of 60)

Bitsika et al., 2010 [28]Counselling15

Sharpley et al., 2010 [29]Oncology15

Klemenc-Ketiš et al., 2010 [30]Mental health15Cut-off of 50 raw score

Tang et al., 2010 [31]Mental health55

Fernandes et al., 2010 [32]Psychometrics11Raw score ranges: up to 36 - no anxiety. 37–39 - possible anxiety: 40+ - high anxiety.

Wang et al., 2010 [33]Urology25cut-off 50 (Chinese)

Pascazio et al., 2010 [34]Nephrology55

Herbert et al., 2010 [35]Psychology33

2011

Ide, 2011 [36]Orthopedic11

Lande et al., 2011 [37]Psychiatry55

Li et al., 2011 [38]Psychology55Short 10-item version of SDS used

Huang et al., 2011 [39]Cardiology44Used index classifications with no indication of conversion

Takayama et al., 2011 [40]Dentistry11Mentions index conversion but uses raw scores correctly

Perugi et al., 2011 [41]Psychiatry44Used index scores with no indication of conversion44Used index scores with no indication of conversion: cut-off of 50. SDS ranges

Ogawa et al., 2011 [42]Gynecology55

Uji et al., 2011 [43]Psychotherapy55Only used 7 statements: “affective subscale”

Davidson et al., 2011 [44]Psychology55

Sharpley et al., 2011 [45]Oncology15SAS cut-off

Wan et al., 2011 [46]Psychiatry55

Weigold and Robitschek, 2011 [47]Psychiatry55

Li et al., 2011 [48]Opthalmology25Chinese cut-off used (50 index)

Liao et al., 2011 [49]Drugs55

Nassiri et al., 2011 [50]Env. science44Divided into normal/low/moderate/high but no indication given of cut-offs or indexing

De Tommaso et al., 2011 [51]Neurology55

Chiaffarino et al., 2011 [52]Gynecology11Raw score ranges: <40, nonanxious; 40–60 anxious symptoms; >60 clinically significant anxiety

Richards et al., 2011 [53]Psychology44Uses Index scores: no mention of conversion44Uses index scores with no mention of conversation. “SAS” ranges

2012

Yu et al., 2012 [54]Cardiology2222“SAS” severity ranges

Lei et al., 2012 [55]Psychiatry25Chinese cut-offs used (53 index)25Chinese cut-off used (50 index)

Mammadova et al., 2012 [56]Psychiatry55Calculating appropriate cut-off for different population

Trento et al., 2012 [57]Endocrinology3333“SAS” severity ratings

Adogwa et al., 2012 [58]Orthopaedics35

Gao et al., 2012 [59]Psychiatry15Use Chinese norm cut-off of 40 (raw score)

Sawa et al., 2012 [60]Psychiatry55

Chang and Koh, 2012 [61]Mental health55

Sapranaviciute et al., 2012 [62]Psychology55

de Pasquale et al., 2012 [63]General medicine3555

Shen et al., 2012 [64]Psychiatry25Chinese cut-off: index 50

Liu et al., 2012 [65]Gastroenterology25Probably used Chinese cut-off

Huang et al., 2012 [66]Gynecology25Chinese cut-off: index 50

Li et al., 2012 [67]Mental health55

Tang et al., 2012 [68]Gastroenterology55

Campbell et al., 2012 [69]Psychiatry55

2013

Adogwa et al., 2013 [70]Spinal35Other ranges used based on quartiles

Balázs et al., 2013 [71]Psychology44“SAS” severity ranges

Li et al., 2014 [72]Oncology15Chinese cut-offs used (42 raw)

Lowery et al., 2013 [73]Psychiatry55Brief instrument used. Score range indicated index scores (25 to 100) but only raw range given (1 to 4 Likert)55Score range indicated index scores (25 to 100) but only raw range given (1 to 4 Likert)

Zhang et al., 2013 [74]Urology25

Guo et al., 2013 [75]Oncology25Chinese version used25Chinese cut-off used

Nardelli et al., 2013 [76]Neurology35

Siennicki-Lantz et al., 2013 [77]Geriatric22SAS “severity rating” applied (i.e., mild depression 45–59)

Liu et al., 2013 [78]Immunology25Chinese cut-off used

Deb, 2013 [79]Pharmacology3333SAS “severity ratings”

Wang et al., 2013 [80]Psychiatry25Chinese version used

Khorvash et al., 2013 [81]Neuroscience44“SAS” severity ratings provided

Quintão et al., 2013 [82]Psychology55

Delibegovic and Sinanovic, 2013 [83]Oncology4444Uses SDS severity ratings

Klemenc-Ketiš and Peterlin, 2013 [84]Psychiatry33

Carli et al., 2013 [85]Public health55“A full description of assessment instruments and interventions was previously published”

Grandi et al., 2013 [86]Gynecology55“Higher scores indicating worst depressive symptoms.” Raw score range given (20 to 80)

Luo et al., 2013 [87]Geriatric55

2014

Akinsulore et al., 2014 [88]Psychology22

Banth and Sharma, 2014 [89]Psychology33

Bhatti et al., 2013 [90]Spinal33“SAS” severity ranges

Kaess et al., 2014 [91]Psychiatry44“SAS” severity ranges

Atteritano et al., 2014 [92]Gynecology33

Lee et al., 2014 [93]Endocrinology55“Severity score was calculated by formula conversion” and link to Zung article

Vlachos et al., 2014 [94]Gastroenterology35

Ding et al., 2014 [95]Psychiatry15Chinese cut-off used (40 raw)

Trento et al., 2014 [96]Endocrinology33“SAS” severity ranges

Fernández‐Matarrubia et al., 2014 [97]Neurology5555

Feng et al., 2014 [98]Public health45Chinese cut-offs used (53 index)45Chinese cut-offs used (50 Index)

Hou et al., 2014 [99]Nephrology25“Each scale consists of 40 items,”- incorrect description of scales provided. Chinese version used: non-Chinese cut-off25“Each scale consists of 40 items,” incorrect description of scales provided. Chinese version used: Chinese cut-off

Khorvash et al., 2014 [100]Neurology55

Liu et al., 2014 [101]Respiratory45Chinese version used45Chinese cut-off used

La Fianza et al., 2014 [102]Radiology1515`

2015

Bobić et al., 2015 [103]Psychiatry15Chinese cut-offs used (42 raw)

Chen et al., 2015 [104]Orthopedic45Chinese cut-offs used (53 index)45Chinese cut-off used (50 index)

Jiang et al., 2015 [105]Rheumatology5555

Rus Makovec et al., 2015 [106]Public health2222SDS severity ranges used

Kourkoveli et al., 2015 [107]Cardiac15

Shi et al., 2015 [108]Psychiatry25Chinese cut-off used (50 index)

Stefanidou et al., 2015 [109]Psychiatry35

Pozzi et al., 2015 [110]Psychiatry55

Yuan et al., 2015 [111]Neurology35Chinese cut-off used (50 index)

Yin et al., 2015 [112]Psychiatry33SAS severity ranges quoted but Chinese cut-offs used (53 index)33“SAS” severity ranges quoted but Chinese cut-off used (50)

Li et al., 2015 [113]Spinal33SDS standard indices applied to raw scores33SDS severity ranges applied to raw scores

Hirao, 2015 [114]Occupational therapy55Mentioned the Japanese version

Lou et al., 2015 [115]Cardiac22Chinese cut-off used (50 index): ranges: 50–59; 60–69; 70+

Yang et al., 2015 [116]Psychiatry25Mentioned the Chinese version but used standard index cut-off (50)

Trento et al., 2015 [117]Endocrinology33“SAS” severity ranges

Notes. Zung analysis classifications; 1: consistent use of raw scores; 2: consistent use of index scores; 3: inconsistent application; 4: unclear whether consistent or not; 5: not utilized.

Severity ranges were utilized considerably less often. Specifically 23 of the 60 SDS papers included them but in 9 (39%) of these cases, index score ranges were incorrectly applied to raw scores, with a further 5 (22%) cases falling into the unclear category. Figures for the SAS followed a similar pattern despite the absence of any official ranges in the scientific literature. Twenty of the 60 SAS papers include such scales, with index score ranges being incorrectly applied to raw scores in 7 (35%) of these cases, with a further 7 (35%) falling into the unclear category (Table 4).


SDS (n = 60)SAS (n = 60)

Severity ranges not used3740
Consistent use: raw scores22
Consistent use: index scores74
Incorrect use97
Unclear application57

The most common severity range applied to the SAS is based on the recommended cut-off of 45 (index). In index score terms, severity ranges are 45–59 mild to moderate anxiety, 60–74 moderate to severe anxiety, and 75+ severe anxiety. Thirteen of the 20 SAS papers utilizing severity ranges employed the above. A further four used the SDS severity ranges, while two utilized different ranges altogether and the final paper merely specified descriptors without detailing the numerical criteria. The recommended SDS severity ranges were applied in all SDS papers but two, which instead used the “unofficial” SAS ranges detailed above.

4. Discussion

This study examined a sample of recent scientific publications for the application of raw scores, index scores, and symptom severity ranges when interpreting total scores on the Zung SDS and SAS. Although the findings were based on a “convenience” rather than a random sample of papers, they provide clear evidence of a significant problem in the application of Zung scales across the literature. On the basis of the papers examined here, confusion between raw and index scores means that when cut-offs are applied to indicate the presence/absence of disorder, they are applied incorrectly in 35–51% of cases for the SDS and 20–45% of cases for the SAS (depending on the proportion of unclear cases that involve incorrect application).

This incorrect application of index score cut-offs to raw scores substantially elevates the score required to be classified in the clinical range: in index terms, from 50 to 63 on the SDS and from 45 to 56 on the SAS. The potential impact on study findings does not need elaboration.

Quite apart from the issue of cut-off scores being incorrectly applied, the inconsistency introduced by the use of two distinct sets of scores to represent the same scale makes cross-study comparisons unnecessarily difficult. (Across the studies in our sample, raw scores were used approximately 40% of the time and index scores on 60% of occasions.) Given that the transformation to index scores achieves no purpose other than to decimalize the maximum score, the simplest solution might be to abolish the use of index scores altogether.

Additionally, some confusion exists between the two Zung scales with SDS cut-offs applied to the SAS and vice versa. The same applies to severity ranges for the two scales, if one accepts that an unofficial scale for the SAS has evolved in the literature. The scientific basis of this scale remains highly questionable.

The Zung scales continue to be widely used and potentially remain a valuable means of screening for the presence of anxiety and depression. However, if scale scores are to be reliably interpreted, it is a matter of some urgency that current confusion regarding scale cut-off and severity ranges is resolved and the application of these scales is standardized in future studies.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Acknowledgments

The authors thank Natalya O’Keefe for her work as a research assistant during the data collection phase of the study.

References

  1. G. Andrews, S. Henderson, and W. Hall, “Prevalence, comorbidity, disability and service utilisation: Overview of the Australian National Mental Health Survey,” The British Journal of Psychiatry, vol. 178, pp. 145–153, 2001. View at: Publisher Site | Google Scholar
  2. R. C. Kessler, “The global burden of mental disorders: an update from the WHO World Mental Health (WMH) surveys,” Epidemiologia E Psichiatria Sociale, vol. 18, no. 1, pp. 23–33, 2009. View at: Google Scholar
  3. T. A. Brown, B. F. Chorpita, W. Korotitsch, and D. H. Barlow, “Psychometric properties of the Depression Anxiety Stress Scales (DASS) in clinical samples,” Behaviour Research and Therapy, vol. 35, no. 1, pp. 79–89, 1997. View at: Publisher Site | Google Scholar
  4. L. A. Feldman, “Distinguishing depression and anxiety in self-report: Evidence from confirmatory factor analysis on nonclinical and clinical samples,” Journal of Consulting and Clinical Psychology, vol. 61, no. 4, pp. 631–638, 1993. View at: Publisher Site | Google Scholar
  5. D. Dozois, K. Dobson, and H. Westra, “The comorbidity of anxiety and depression, and the implications of comorbidity for prevention,” in in The Prevention of Anxiety And Depression: Theory, Research And Practice, D. Dozois and K. Dobson, Eds., pp. 261–280, American Psychological Association, Washington, DC, USA, 2004. View at: Google Scholar
  6. W. W. K. Zung, “The measurement of affects: Depression and anxiety,” Modern Problems of Pharmacopsychiatry, vol. 7, pp. 170–188, 1974. View at: Google Scholar
  7. L. A. Clarke and D. Watson, “Theoretical and empirical issues in differentiating depression from anxietyaspects of mood,” in in Psychosocial Aspects of Mood Disorders, J. Becker and A. Kleinman, Eds., pp. 39–65, Lawrence Erlbaum Associates, Hillsdale, NJ, USA, 1991. View at: Google Scholar
  8. D. Watson, “Differentiating the mood and anxiety disorders: A quadripartite model,” Annual Review of Clinical Psychology, vol. 5, pp. 221–247, 2009. View at: Publisher Site | Google Scholar
  9. D. J. Kupfer, “Dimensional models for research and diagnosis: A current dilemma,” Journal of Abnormal Psychology, vol. 114, no. 4, pp. 557–559, 2005. View at: Publisher Site | Google Scholar
  10. T. J. Trull, Clinical Psychology, Cengage Learning, Belmont, CA, USA, 7th edition, 2005.
  11. W. W. Zung, “A self-rating depression scale,” Archives of General Psychiatry, vol. 12, pp. 63–70, 1965. View at: Publisher Site | Google Scholar
  12. W. W. K. Zung, “From Art to Science: The Diagnosis and Treatment of Depression,” Archives of General Psychiatry, vol. 29, no. 3, pp. 328–337, 1973. View at: Publisher Site | Google Scholar
  13. W. W. Zung, “A rating instrument for anxiety disorders,” Psychosomatic Medicine, vol. 12, no. 6, pp. 371–379, 1971. View at: Publisher Site | Google Scholar
  14. American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders, Author, Washington, DC, USA, 2nd edition, 1968.
  15. W. W. K. Zung, How normal is anxiety? Current Concepts, Upjohn, Durham, North Carolina, USA, 1980.
  16. M. H. N. Chagas, V. Tumas, S. R. Loureiro et al., “Validity of a Brazilian version of the Zung self-rating depression scale for screening of depression in patients with Parkinson's disease,” Parkinsonism & Related Disorders, vol. 16, no. 1, pp. 42–45, 2010. View at: Publisher Site | Google Scholar
  17. A. Friebe, M. Horn, F. Schmidt et al., “Dose-dependent development of depressive symptoms during adjuvant interferon-α treatment of patients with malignant melanoma,” Psychosomatics, vol. 51, no. 6, pp. 466–473, 2010. View at: Publisher Site | Google Scholar
  18. R. G. Lande, L. B. Williams, J. L. Francis, C. Gragnani, and M. L. Morin, “Efficacy of biofeedback for post-traumatic stress disorder,” Complementary Therapies in Medicine, vol. 18, no. 6, pp. 256–259, 2010. View at: Publisher Site | Google Scholar
  19. A. Saban, A. J. Flisher, and G. Distiller, “Association between psychopathology and substance use among school-going adolescents in Cape Town, South Africa,” Journal of Psychoactive Drugs, vol. 42, no. 4, pp. 467–476, 2010. View at: Publisher Site | Google Scholar
  20. T. Ohira, “Psychological distress and cardiovascular disease: The Circulatory Risk in Communities Study (CIRCS),” Journal of Epidemiology, vol. 20, no. 3, pp. 185–191, 2010. View at: Publisher Site | Google Scholar
  21. D. Lombardi, L. T. Mizuno, and A. Thornberry, “The use of the Zung Self-Rating Depression Scale to assist in the case management of patients living with HIV/AIDS,” Care Management Journals, vol. 11, no. 4, pp. 210–216, 2010. View at: Publisher Site | Google Scholar
  22. J. Podlipný et al., “Lower serum levels of interleukin-6 in a population sample with symptoms of depression than in a population sample without symptoms of depression,” Physiological Research, vol. 59, no. 1, p. 121, 2010. View at: Google Scholar
  23. P. Ostojic, S. Zivojinovic, T. Reza, and N. Damjanov, “Symptoms of depression and anxiety in Serbian patients with systemic sclerosis: impact of disease severity and socioeconomic factors,” Modern Rheumatology, vol. 20, no. 4, pp. 353–357, 2010. View at: Publisher Site | Google Scholar
  24. M. Sonikian, P. Metaxaki, D. Papavasileiou et al., “Effects of interleukin-6 on depression risk in dialysis patients,” American Journal of Nephrology, vol. 31, no. 4, pp. 303–308, 2010. View at: Publisher Site | Google Scholar
  25. Q. M. Biggs, C. S. Fullerton, J. J. Reeves, T. A. Grieger, D. Reissman, and R. J. Ursano, “Acute stress disorder, depression, and tobacco use in disaster workers following 9/11.,” American Journal of Orthopsychiatry, vol. 80, no. 4, pp. 586–592, 2010. View at: Publisher Site | Google Scholar
  26. I. Alimohammadi et al., “Factors affecting road traffic noise annoyance among white-collar employees working in Tehran,” Journal of Environmental Health Science and Engineering, vol. 7, no. 1, p. 25, 2010. View at: Google Scholar
  27. N. Oishi, S. Kanzaki, S. Shinden, H. Saito, Y. Inoue, and K. Ogawa, “Effects of selective serotonin reuptake inhibitor on treating tinnitus in patients stratified for presence of depression or anxiety,” Audiology and Neurotology, vol. 15, no. 3, pp. 187–193, 2010. View at: Publisher Site | Google Scholar
  28. V. Bitsika, C. F. Sharpley, and T. C. Melhem, “Gender differences in factor scores of anxiety and depression among Australian university students: Implications for counselling interventions,” Canadian Journal of Counselling and Psychotherapy (Online), vol. 44, no. 1, p. 51, 2010. View at: Google Scholar
  29. C. F. Sharpley, V. Bitsika, and D. R. H. Christie, “Incidence and nature of anxiety-depression comorbidity in prostate cancer patients,” Journal of Men's Health, vol. 7, no. 2, pp. 125–134, 2010. View at: Publisher Site | Google Scholar
  30. Z. Klemenc-Ketiš, J. Kersnik, and D. Novak-Glavač, “Determinants of depression and anxiety in family practice patients with comorbidities,” Wiener Klinische Wochenschrift, vol. 122, no. 2, pp. 35–39, 2010. View at: Publisher Site | Google Scholar
  31. J. Tang, Y. Yu, Y. Du, Y. Ma, H. Zhu, and Z. Liu, “Association between actual weight status, perceived weight and depressive, anxious symptoms in Chinese adolescents: A cross-sectional study,” BMC Public Health, vol. 10, article no. 594, 2010. View at: Publisher Site | Google Scholar
  32. L. Fernandes, J. Fonseca, S. Martins et al., “Association of anxiety with asthma: Subjective and objective outcome measures,” Psychosomatics, vol. 51, no. 1, pp. 39–46, 2010. View at: Publisher Site | Google Scholar
  33. W.-W. Wang, C.-H. Deng, L.-W. Chen, L.-Y. Zhao, J.-C. Mo, and X.-A. Tu, “Psychosexual adjustment and age factors in 130 men undergone hypospadias surgery in a Chinese hospital,” Andrologia, vol. 42, no. 6, pp. 384–388, 2010. View at: Publisher Site | Google Scholar
  34. L. Pascazio, I. B. Nardone, A. Clarici et al., “Anxiety, depression and emotional profile in renal transplant recipients and healthy subjects: A comparative study,” Transplantation Proceedings, vol. 42, no. 9, pp. 3586–3590, 2010. View at: Publisher Site | Google Scholar
  35. G. L. Herbert, V. McCormack, and J. L. Callahan, “An investigation of the object relations theory of depression,” Psychoanalytic Psychology, vol. 27, no. 2, pp. 219–234, 2010. View at: Publisher Site | Google Scholar
  36. M. Ide, “The association between depressive mood and pain amongst individuals with limb amputations,” European Journal of Trauma and Emergency Surgery, vol. 37, no. 2, pp. 191–195, 2011. View at: Publisher Site | Google Scholar
  37. R. G. Lande, L. B. Williams, C. Gragnani, and Albert Tsai, “Effectiveness of light therapy for depression among active duty service members: A nonrandomized controlled pilot trial,” Complementary Therapies in Medicine, vol. 19, no. 3, pp. 161–163, 2011. View at: Publisher Site | Google Scholar
  38. L. Li, L.-J. Liang, Y. Y. Ding, and G. Ji, “Facing HIV as a Family: Predicting Depressive Symptoms With Correlated Responses,” Journal of Family Psychology, vol. 25, no. 2, pp. 202–209, 2011. View at: Publisher Site | Google Scholar
  39. K. Huang, X. Deng, D. He et al., “Prognostic implication of earthquake-related loss and depressive symptoms in patients with heart failure following the 2008 earthquake in Sichuan,” Clinical Cardiology, vol. 34, no. 12, pp. 755–760, 2011. View at: Publisher Site | Google Scholar
  40. Y. Takayama, E. Miura, K. Miura, S. Ono, and C. Ohkubo, “Condition of depressive symptoms among Japanese dental students,” Odontology, vol. 99, no. 2, pp. 179–187, 2011. View at: Publisher Site | Google Scholar
  41. G. Perugi, P. L. Canonico, P. Carbonato et al., “Unexplained somatic symptoms during major depression: Prevalence and clinical impact in a national sample of italian psychiatric outpatients,” Psychopathology, vol. 44, no. 2, pp. 116–124, 2011. View at: Publisher Site | Google Scholar
  42. M. Ogawa, K. Takamatsu, and F. Horiguchi, “Evaluation of factors associated with the anxiety and depression of female infertility patients,” BioPsychoSocial Medicine, vol. 5, article no. 15, 2011. View at: Publisher Site | Google Scholar
  43. M. Uji, T. Kitamura, and T. Nagata, “Self-conscious affects: Their adaptive functions and relationship to depressive mood,” American Journal of Psychotherapy, vol. 65, no. 1, pp. 27–46, 2011. View at: Google Scholar
  44. C. L. Davidson, L. R. Wingate, D. M. Grant, M. R. Judah, and A. C. Mills, “Interpersonal suicide risk and ideation: The influence of depression and social anxiety,” Journal of Social and Clinical Psychology, vol. 30, no. 8, pp. 842–855, 2011. View at: Publisher Site | Google Scholar
  45. C. F. Sharpley, V. Bitsika, and D. R. H. Christie, “Understanding the functionality of depression among Australian breast cancer patients: Implications for cognitive and behavioural interventions,” International Journal of Behavioral Medicine, vol. 18, no. 4, pp. 319–324, 2011. View at: Publisher Site | Google Scholar
  46. Y.-H. Wan, C.-L. Hu, J.-H. Hao, Y. Sun, and F.-B. Tao, “Deliberate self-harm behaviors in Chinese adolescents and young adults,” European Child and Adolescent Psychiatry, vol. 20, no. 10, pp. 517–525, 2011. View at: Publisher Site | Google Scholar
  47. I. K. Weigold and C. Robitschek, “Agentic personality characteristics and coping: Their relation to trait anxiety in college students,” American Journal of Orthopsychiatry, vol. 81, no. 2, pp. 255–264, 2011. View at: Publisher Site | Google Scholar
  48. M. Li, L. Gong, X. Sun, and W. J. Chapin, “Anxiety and depression in patients with dry eye syndrome,” Current Eye Research, vol. 36, no. 1, pp. 1–7, 2011. View at: Publisher Site | Google Scholar
  49. Y. Liao, J. Tang, T. Liu, X. Chen, T. Luo, and W. Hao, “Sleeping problems among Chinese heroin-dependent individuals,” The American Journal of Drug and Alcohol Abuse, vol. 37, no. 3, pp. 179–183, 2011. View at: Publisher Site | Google Scholar
  50. P. Nassiri et al., “Assessment of noise induced psychological stresses on printery workers,” International Journal of Environmental Science and Technology, vol. 8, no. 1, pp. 169–176, 2011. View at: Google Scholar
  51. M. De Tommaso, A. Federici, C. Serpino et al., “Clinical features of headache patients with fibromyalgia comorbidity,” The Journal of Headache and Pain, vol. 12, no. 6, pp. 629–638, 2011. View at: Publisher Site | Google Scholar
  52. F. Chiaffarino, M. P. Baldini, C. Scarduelli et al., “Prevalence and incidence of depressive and anxious symptoms in couples undergoing assisted reproductive treatment in an Italian infertility department,” European Journal of Obstetrics & Gynecology and Reproductive Biology, vol. 158, no. 2, pp. 235–241, 2011. View at: Publisher Site | Google Scholar
  53. A. Richards, J. Ospina-Duque, M. Barrera-Valencia et al., “Posttraumatic stress disorder, anxiety and depression symptoms, and psychosocial treatment needs in colombians internally displaced by armed conflict: A mixed-method evaluation,” Psychological Trauma: Theory, Research, Practice, and Policy, vol. 3, no. 4, pp. 384–393, 2011. View at: Publisher Site | Google Scholar
  54. S. Yu, Q. Zhao, P. Wu et al., “Effect of anxiety and depression on the recurrence of paroxysmal atrial fibrillation after circumferential pulmonary vein ablation,” Journal of Cardiovascular Electrophysiology, vol. 23, no. 1, pp. S17–S23, 2012. View at: Publisher Site | Google Scholar
  55. M. Lei, C. Li, X. Xiao, J. Qiu, Y. Dai, and Q. Zhang, “Evaluation of the psychometric properties of the Chinese version of the Resilience Scale in Wenchuan earthquake survivors,” Comprehensive Psychiatry, vol. 53, no. 5, pp. 616–622, 2012. View at: Publisher Site | Google Scholar
  56. F. Mammadova, M. Sultanov, A. Hajiyeva, M. Aichberger, and A. Heinz, “Translation and adaptation of the Zung Self-Rating Depression Scale for application in the bilingual Azerbaijani population,” European Psychiatry, vol. 27, no. 2, pp. S27–S31, 2012. View at: Publisher Site | Google Scholar
  57. M. Trento, M. Raballo, M. Trevisan et al., “A cross-sectional survey of depression, anxiety, and cognitive function in patients with type 2 diabetes,” Acta Diabetologica, vol. 49, no. 3, pp. 199–203, 2012. View at: Publisher Site | Google Scholar
  58. O. Adogwa, S. L. Parker, D. N. Shau et al., “Preoperative Zung Depression Scale predicts outcome after revision lumbar surgery for adjacent segment disease, recurrent stenosis, and pseudarthrosis,” The Spine Journal, vol. 12, no. 3, pp. 179–185, 2012. View at: Publisher Site | Google Scholar
  59. Y.-Q. Gao, B.-C. Pan, W. Sun, H. Wu, J.-N. Wang, and L. Wang, “Anxiety symptoms among Chinese nurses and the associated factors: a cross sectional study,” BMC Psychiatry, vol. 12, article no. 141, 2012. View at: Publisher Site | Google Scholar
  60. M. Sawa, H. Yamashita, K. Fujimaki, G. Okada, T. Takahashi, and S. Yamawaki, “Depressive symptoms and apathy are associated with psychomotor slowness and frontal activation,” European Archives of Psychiatry and Clinical Neurosciences, vol. 262, no. 6, pp. 493–499, 2012. View at: Publisher Site | Google Scholar
  61. W. C. Chang and J. B. K. Koh, “A measure of depression in a modern asian community: Singapore,” Depression Research and Treatment, vol. 2012, Article ID 691945, 2012. View at: Publisher Site | Google Scholar
  62. L. Sapranaviciute, A. Perminas, and N. Pauziene, “Stress coping and psychological adaptation in the international students,” Central European Journal of Medicine, vol. 7, no. 3, pp. 335–343, 2012. View at: Publisher Site | Google Scholar
  63. T. De Pasquale, E. Nucera, R. Boccascino et al., “Allergy and psychologic evaluations of patients with multiple drug intolerance syndrome,” Internal and Emergency Medicine, vol. 7, no. 1, pp. 41–47, 2012. View at: Publisher Site | Google Scholar
  64. L.-L. Shen, L.-M. Lao, S.-F. Jiang et al., “A survey of anxiety and depression symptoms among primary-care physicians in China.,” International Journal of Psychiatry in Medicine, vol. 44, no. 3, pp. 257–270, 2012. View at: Publisher Site | Google Scholar
  65. M.-L. Liu, F.-R. Liang, F. Zeng, Y. Tang, L. Lan, and W.-Z. Song, “Cortical-limbic regions modulate depression and anxiety factors in functional dyspepsia: A PET-CT study,” Annals of Nuclear Medicine, vol. 26, no. 1, pp. 35–40, 2012. View at: Publisher Site | Google Scholar
  66. Z. Huang, J. Hao, P. Su et al., “The impact of prior abortion on anxiety and depression symptoms during a subsequent pregnancy: Data from a population-based cohort study in China,” Klinik Psikofarmakoloji Bülteni, vol. 22, no. 1, pp. 51–58, 2012. View at: Publisher Site | Google Scholar
  67. J. Li, Y. Shao, M. Yun, Z. Yan, K. Yu, and M. Li, “The mental health status of Chinese medical peacekeepers in Lebanon,” Social Behavior and Personality, vol. 40, no. 3, pp. 375–380, 2012. View at: Publisher Site | Google Scholar
  68. Y.-R. Tang, W.-W. Yang, Y.-L. Wang, and L. Lin, “Sex differences in the symptoms and psychological factors that influence quality of life in patients with irritable bowel syndrome,” European Journal of Gastroenterology & Hepatology, vol. 24, no. 6, pp. 702–707, 2012. View at: Publisher Site | Google Scholar
  69. M. Campbell et al., “A comparison of the psychometric strengths of the public-domain Zung Self-rating Depression Scale with the proprietary Beck Depression Inventory-II in Barbados,” West Indian Medical Journal, vol. 61, no. 5, pp. 483–488, 2012. View at: Google Scholar
  70. O. Adogwa, S. L. Parker, D. N. Shau et al., “Preoperative Zung depression scale predicts patient satisfaction independent of the extent of improvement after revision lumbar surgery,” The Spine Journal, vol. 13, no. 5, pp. 501–506, 2013. View at: Publisher Site | Google Scholar
  71. J. Balázs, M. Miklõsi, Á. Keresztény et al., “Adolescent subthreshold-depression and anxiety: Psychopathology, functional impairment and increased suicide risk,” Journal of Child Psychology and Psychiatry and Allied Disciplines, vol. 54, no. 6, pp. 670–677, 2013. View at: Publisher Site | Google Scholar
  72. R. Li, J. Yang, J. Yang et al., “Depression in older patients with advanced colorectal cancer is closely connected with immunosuppressive acidic protein,” Metabolic Brain Disease, vol. 29, no. 1, pp. 87–92, 2014. View at: Publisher Site | Google Scholar
  73. A. E. Lowery, T. Starr, L. K. Dhingra et al., “Frequency, characteristics, and correlates of pain in a pilot study of colorectal cancer survivors 1–10 years post-treatment,” Pain Medicine, vol. 14, no. 11, pp. 1673–1680, 2013. View at: Publisher Site | Google Scholar
  74. X. Zhang, J. Gao, and J. Liu, “Prevalence rate and risk factors of depression in outpatients with premature ejaculation,” BioMed Research International, vol. 2013, no. 1, Article ID 317468, 2013. View at: Publisher Site | Google Scholar
  75. Z. Guo, H. Tang, H. Li et al., “The benefits of psychosocial interventions for cancer patients undergoing radiotherapy,” Health and Quality of Life Outcomes, vol. 11, no. 1, article 121, 2013. View at: Publisher Site | Google Scholar
  76. S. Nardelli, I. Pentassuglio, C. Pasquale et al., “Depression, anxiety and alexithymia symptoms are major determinants of health related quality of life (HRQoL) in cirrhotic patients,” Metabolic Brain Disease, vol. 28, no. 2, pp. 239–243, 2013. View at: Publisher Site | Google Scholar
  77. A. Siennicki-Lantz, L. André-Petersson, P. Wollmer, and S. Elmståhl, “Depressive symptoms, atherosclerotic burden and cerebral blood flow disturbances in a cohort of octogenarian men from a general population,” BMC Psychiatry, vol. 13, article no. 347, 2013. View at: Publisher Site | Google Scholar
  78. L. Liu, R. Pang, W. Sun et al., “Functional social support, psychological capital, and depressive and anxiety symptoms among people living with HIV/AIDS employed full-time,” BMC Psychiatry, vol. 13, article no. 324, 2013. View at: Publisher Site | Google Scholar
  79. D. Deb, “Depression and anxiety in heart failure patients in a South Indian population: A pilot study,” Asian Journal of Biomedical and Pharmaceutical Sciences, vol. 3, no. 17, 2013. View at: Google Scholar
  80. Y. Wang, X. Zhao, A. O'Neil, A. Turner, X. Liu, and M. Berk, “Altered cardiac autonomic nervous function in depression,” BMC Psychiatry, vol. 13, article 187, 2013. View at: Publisher Site | Google Scholar
  81. F. Khorvash et al., “Investigating the anxiety level in Iranian medical residents in 2010-2011,” International Journal of Preventive Medicine, vol. 4, 2, p. S318, 2013. View at: Google Scholar
  82. S. Quintão, A. R. Delgado, and G. Prieto, “Validity study of the beck anxiety inventory (Portuguese version) by the rasch rating scale model,” Psicologia: Reflexao e Critica, vol. 26, no. 2, pp. 305–310, 2013. View at: Publisher Site | Google Scholar
  83. A. Delibegovic and O. Sinanovic, “The influence of palliative care on the level of anxiety and depression in lung cancer patients.,” Medical Archives, vol. 67, no. 4, pp. 263–265, 2013. View at: Publisher Site | Google Scholar
  84. Z. Klemenc-Ketiš and B. Peterlin, “Correlates of depression in the Slovenian working population,” Archives of Industrial Hygiene and Toxicology, vol. 64, no. 4, pp. 489–495, 2013. View at: Publisher Site | Google Scholar
  85. V. Carli, C. Wasserman, D. Wasserman et al., “The Saving and Empowering Young Lives in Europe (SEYLE) Randomized Controlled Trial (RCT): Methodological issues and participant characteristics,” BMC Public Health, vol. 13, no. 1, article no. 479, 2013. View at: Publisher Site | Google Scholar
  86. G. Grandi, A. Xholli, S. Ferrari, M. Cannoletta, A. Volpe, and A. Cagnacci, “Intermenstrual pelvic pain, quality of life and mood,” Gynecologic and Obstetric Investigation, vol. 75, no. 2, pp. 97–100, 2013. View at: Publisher Site | Google Scholar
  87. J. Luo, G. Zhu, Q. Zhao et al., “Prevalence and risk factors of poor sleep quality among chinese elderly in an urban community: Results from the Shanghai aging study,” PLoS ONE, vol. 8, no. 11, Article ID e81261, 2013. View at: Publisher Site | Google Scholar
  88. A. Akinsulore, O. O. Aloba, B. M. Mapayi, I. O. Oloniniyi, F. O. Fatoye, and R. O. A. Makanjuola, “Relationship between depressive symptoms and quality of life in Nigerian patients with schizophrenia,” Social Psychiatry and Psychiatric Epidemiology, vol. 49, no. 8, pp. 1191–1198, 2014. View at: Publisher Site | Google Scholar
  89. S. Banth and A. Sharma, “A study of birth order and family size differences on depression,” Indian Journal of Behaviour, vol. 5, no. 7, p. 114, 2014. View at: Google Scholar
  90. A. R. Bhatti et al., “Anxiety and depression in patients suffering from chronic low backache,” Methodology, 2013. View at: Google Scholar
  91. M. Kaess et al., “Pathological internet use among european adolescents: psychopathology and self-destructive behaviours,” European Child & Adolescent Psychiatry, vol. 23, no. 11, pp. 1093–1102, 2014. View at: Google Scholar
  92. M. Atteritano, S. Mazzaferro, A. Bitto et al., “Genistein effects on quality of life and depression symptoms in osteopenic postmenopausal women: a 2-year randomized, double-blind, controlled study,” Osteoporosis International, vol. 25, no. 3, pp. 1123–1129, 2014. View at: Publisher Site | Google Scholar
  93. I.-T. Lee, C.-P. Fu, W.-J. Lee et al., “Brain-derived neurotrophic factor, but not body weight, correlated with a reduction in depression scale scores in men with metabolic syndrome: A prospective weight-reduction study,” Diabetology & Metabolic Syndrome, vol. 6, no. 1, article no. 18, 2014. View at: Publisher Site | Google Scholar
  94. I. I. Vlachos, C. Barbatis, M. Tsopanomichalou, and L. Abou-Assabeh, “Correlation between depression, anxiety, and polymorphonuclear cells' resilience in ulcerative colitis: The mediating role of heat shock protein 70,” BMC Gastroenterology, vol. 14, p. 77, 2014. View at: Publisher Site | Google Scholar
  95. Y. Ding, J. Qu, X. Yu, and S. Wang, “The mediating effects of burnout on the relationship between anxiety symptoms and occupational stress among community healthcare workers in China: A cross-sectional study,” PLoS ONE, vol. 9, no. 9, Article ID e107130, 2014. View at: Publisher Site | Google Scholar
  96. M. Trento, M. Trevisan, M. Raballo et al., “Depression, anxiety, cognitive impairment and their association with clinical and demographic variables in people with type 2 diabetes: A 4-year prospective study,” Journal of Endocrinological Investigation, vol. 37, no. 1, pp. 79–85, 2014. View at: Publisher Site | Google Scholar
  97. M. Fernández-Matarrubia, M. L. Cuadrado, C. M. Sánchez-Barros et al., “Prevalence of migraine in patients with restless legs syndrome: A case-control study,” Headache: The Journal of Head and Face Pain, vol. 54, no. 8, pp. 1337–1346, 2014. View at: Publisher Site | Google Scholar
  98. Q. Feng, Q.-L. Zhang, Y. Du, Y.-L. Ye, and Q.-Q. He, “Associations of physical activity, screen time with depression, anxiety and sleep quality among Chinese college freshmen,” PLoS ONE, vol. 9, no. 6, Article ID e100914, 2014. View at: Publisher Site | Google Scholar
  99. Y. Hou, X. Li, L. Yang et al., “Factors associated with depression and anxiety in patients with end-stage renal disease receiving maintenance hemodialysis,” International Urology and Nephrology, vol. 46, no. 8, pp. 1645–1649, 2014. View at: Publisher Site | Google Scholar
  100. F. Khorvash et al., “The relationship between residents interest to their specialty field and their level of anxiety,” Journal of Education and Health Promotion, vol. 3, 2014. View at: Google Scholar
  101. S. Liu, R. Wu, L. Li et al., “The prevalence of anxiety and depression in Chinese asthma patients,” PLoS ONE, vol. 9, no. 7, Article ID e103014, 2014. View at: Publisher Site | Google Scholar
  102. A. La Fianza, C. Dellafiore, D. Travaini et al., “Effectiveness of a single education and counseling intervention in reducing anxiety in women undergoing hysterosalpingography: A randomized controlled trial,” The Scientific World Journal, vol. 2014, Article ID 598293, 2014. View at: Publisher Site | Google Scholar
  103. J. Bobić, S. Cvijetić, and J. Macan, “Personality and self-perception of physical and emotional health among first-year university students,” Drustvena Istrazivanja, vol. 24, no. 2, pp. 219–237, 2015. View at: Publisher Site | Google Scholar
  104. S.-B. Chen, H. Hu, Y.-S. Gao, H.-Y. He, D.-X. Jin, and C.-Q. Zhang, “Prevalence of clinical anxiety, clinical depression and associated risk factors in Chinese young and middle-aged patients with osteonecrosis of the femoral head,” PLoS ONE, vol. 10, no. 3, Article ID e0120234, 2015. View at: Publisher Site | Google Scholar
  105. Y. Jiang, M. Yang, H. Wu et al., “The relationship between disease activity measured by the BASDAI and psychological status, stressful life events, and sleep quality in ankylosing spondylitis,” Clinical Rheumatology, vol. 34, no. 3, pp. 503–510, 2015. View at: Publisher Site | Google Scholar
  106. M. Rus Makovec, N. Vintar, and S. Makovec, “Self-Reported Depression, Anxiety and Evaluation of Own Pain in Clinical Sample of Patients with Different Location of Chronic Pain/Samoocenjena Depresivnost in Anksioznost Ter Evalvacija Lastne Bolečine V Kliničnem Vzorcu Pacientov Z Različno Lokacijo Kronične Bolečine,” Slovenian Journal of Public Health, vol. 54, no. 1, pp. 1–10, 2015. View at: Google Scholar
  107. P. Kourkoveli, S. Rammos, J. Parissis, A. Maillis, D. Kremastinos, and I. Paraskevaidis, “Depressive Symptoms in Patients with Congenital Heart Disease: Incidence and Prognostic Value of Self-Rating Depression Scales,” Congenital Heart Disease, vol. 10, no. 3, pp. 240–247, 2015. View at: Publisher Site | Google Scholar
  108. M. Shi, L. Liu, Z. Y. Wang, and L. Wang, “The mediating role of resilience in the relationship between big five personality and anxiety among chinese medical students: A cross-sectional study,” PLoS ONE, vol. 10, no. 3, Article ID e0119916, 2015. View at: Publisher Site | Google Scholar
  109. A. Stefanidou, D. Bouros, M. Livaditis, A. Pataka, and P. Argyropoulou-Pataka, “Psychological Characteristics and Smoking Cessation Outcomes in a Sample of Greek Smokers,” Current Psychology, vol. 34, no. 1, pp. 66–81, 2015. View at: Publisher Site | Google Scholar
  110. G. Pozzi, A. Frustaci, D. Tedeschi et al., “Coping strategies in a sample of anxiety patients: Factorial analysis and associations with psychopathology,” Brain and Behavior, vol. 5, no. 8, Article ID e00351, 2015. View at: Publisher Site | Google Scholar
  111. L. Yuan, Y. Tian, F. Zhang et al., “Decision-making in patients with hyperthyroidism: A neuropsychological study,” PLoS ONE, vol. 10, no. 6, Article ID e0129773, 2015. View at: Publisher Site | Google Scholar
  112. W. Yin, L. Pang, X. Cao et al., “Factors associated with depression and anxiety among patients attending community-based methadone maintenance treatment in China,” Addiction, vol. 110, no. 1, pp. 51–60, 2015. View at: Publisher Site | Google Scholar
  113. S. Li, M. Qi, W. Yuan, and H. Chen, “The Impact of the Depression and Anxiety on Prognosis of Cervical Total Disc Replacement,” The Spine Journal, vol. 40, no. 5, pp. E266–E271, 2015. View at: Publisher Site | Google Scholar
  114. K. Hirao, “Difference in mental state between Internet-addicted and non-addicted Japanese undergraduates,” International Journal of Adolescent Medicine and Health, vol. 27, no. 3, pp. 307–310, 2015. View at: Publisher Site | Google Scholar
  115. Z. Lou, Y. Li, Y. Yang, L. Wang, and J. Yang, “Affects of anxiety and depression on health-related quality of life among patients with benign breast lumps diagnosed via ultrasonography in China,” International Journal of Environmental Research and Public Health, vol. 12, no. 9, pp. 10587–10601, 2015. View at: Publisher Site | Google Scholar
  116. X. Yang, L. Wang, C. Hao et al., “Sex partnership and self-efficacy influence depression in Chinese transgender women: A cross-sectional study,” PLoS ONE, vol. 10, no. 9, Article ID e0136975, 2015. View at: Publisher Site | Google Scholar
  117. M. Trento, L. Charrier, M. Salassa et al., “Depression, anxiety and cognitive function in patients with type 2 diabetes: an 8-year prospective observational study,” Acta Diabetologica, vol. 52, no. 6, pp. 1157–1166, 2015. View at: Publisher Site | Google Scholar
  118. M. M. A. Babakhanian, Z. A. M. A. Mehrjerdi, and Y. M. D. Shenaiy, “Sexual dysfunction in male crystalline heroin dependents before and after MMT: A pilot study,” Archives of Iranian Medicine, vol. 15, no. 12, pp. 751–755, 2012. View at: Google Scholar
  119. J. W. L. Ng, R. Kwan, and C. C. S. Cheok, “Clinical and Functional Outcomes in Young Adult Males With ADHD,” Journal of Attention Disorders, vol. 21, no. 6, pp. 465–474, 2017. View at: Publisher Site | Google Scholar
  120. J. Fischer and K. Corcoran, Measures for Clinical Practice And Research, Oxford University Press, New York, NY, USA, 2007.
  121. N. S. Schutte and J. M. Malouff, Sourcebook of Adult Assessment Strategies, Plenum Press, New York, NY, USA, 1995.

Copyright © 2018 Debra A. Dunstan and Ned Scott. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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