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Evaluation of the Cardiac DepressionVisual Analogue Scale in a medical andnon-medical sampleMirella Di Benedetto a & Matthew Sheehan ba School of Health Sciences, RMIT University, Melbourne, Australiab Royal Flying Doctor Service Queensland, Cairns, AustraliaVersion of record first published: 27 Mar 2013.

To cite this article: Mirella Di Benedetto & Matthew Sheehan (2013): Evaluation of the CardiacDepression Visual Analogue Scale in a medical and non-medical sample, Psychology, Health &Medicine, DOI:10.1080/13548506.2013.779728

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Evaluation of the Cardiac Depression Visual Analogue Scale in amedical and non-medical sample

Mirella Di Benedettoa* and Matthew Sheehanb

aSchool of Health Sciences, RMIT University, Melbourne, Australia; bRoyal Flying DoctorService Queensland, Cairns, Australia

(Received 26 January 2012; final version received 21 February 2013)

Comorbid depression and medical illness is associated with a number of adversehealth outcomes such as lower medication adherence and higher rates of subsequentmortality. Reliable and valid psychological measures capable of detecting a range ofdepressive symptoms found in medical settings are needed. The Cardiac DepressionVisual Analogue Scale (CDVAS) is a recently developed, brief six-item measureoriginally designed to assess the range and severity of depressive symptoms within acardiac population. The current study aimed to further investigate the psychometricproperties of the CDVAS in a general and medical sample. The sample consisted of117 participants, whose mean age was 40.0 years (SD= 19.0, range 18–84). Partici-pants completed the CDVAS, the Cardiac Depression Scale (CDS), the DepressionAnxiety Stress Scales (DASS) and a demographic and health questionnaire. TheCDVAS was found to have adequate internal reliability (α = .76), strong concurrentvalidity with the CDS (r= .89) and the depression sub-scale of the DASS (r= .70),strong discriminant validity and strong predictive validity. The principal componentsanalysis revealed that the CDVAS measured only one component, providing furthersupport for the construct validity of the scale. Results of the current study indicatethat the CDVAS is a short, simple, valid and reliable measure of depressive symp-toms suitable for use in a general and medical sample.

Keywords: depression scale; psychometric; validity; reliability; primary practice

Major and subclinical depression (depression) are more common amongst those withmedical conditions, such as cardiovascular disease (CVD) and diabetes, than the generalpopulation (World Health Organisation [WHO], 2009). For instance, the prevalence ofdepression following an acute myocardial infarction can vary from 16 to 65%, depend-ing on the measurement tool and the depression criteria used (Barefoot & Schroll,1996; Ladwig, Kieser, Konig, Breithardt, & Borggrefe, 1991). Amongst those with dia-betes, depression has ranged from 10% (Egede, Zheng, & Simpson, 2002; Fisher et al.,2007) to 24% (Gonzalez et al., 2007; Katon et al., 2005). Ranges from 10 to 67% havebeen reported for the presence of sub-threshold depressive symptoms (Diabetes Preven-tion Program Research Group, 2005; Egede et al., 2002; Gonzalez et al., 2007; Ismailet al., 2007).

Comorbid depression and the aforementioned medical conditions are associated withhigher rates of mortality, morbidity and other undesirable health-related outcomes.Those with a Beck Depression Inventory (BDI, Beck, Steer, & Brown, 1996) score as

*Corresponding author. Email: mirella.dibenedetto@rmit.edu.au

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low as four can have a worse prognosis and increased mortality compared to those withno depressive symptoms (Bush et al., 2001). The presence of depression not onlyaffects prognosis, but can also interfere with medical adherence and necessary lifestylechanges in those with CVD (Fauerbach et al., 2005; Ziegelstein et al., 2000). Quality oflife (QOL) in these patients can also be impaired (Hare & Davis, 1996). Likewise, dia-betes and comorbid depression are associated with lower levels of exercise and dietadherence (Gonzalez et al., 2007; Lin et al., 2004), medication adherence (Gonzalezet al., 2007; Kilbourne et al., 2005; Lin et al., 2004) and QOL (Erin, Erdi, & Sahin,2008; Goldney, Fisher, Phillips, & Wilson, 2004) and higher levels of health care useand health care expenditure (Egede et al., 2002). Furthermore, even mild depressivesymptoms amongst people with diabetes have been associated with poorer diet adher-ence, medication regime adherence and higher health care costs (Ciechanowski, Katon,& Russo, 2000). Moreover, comorbid depression and diabetes have been associatedwith significantly higher all-cause mortality rates compared to individuals with diabetesalone (Egede et al., 2002; Katon et al., 2005).

Depressive symptoms are prevalent in approximately 70% of patients who visit aprimary care provider (PCP), with 35% of these patients meeting the diagnostic criteriafor various forms of depression (Robinson, Geske, Prest, & Barnacle, 2005).

Despite these high prevalence rates of depression and its undesirable outcomes, upto 50% of cases of major depression go unrecognised within a primary care setting(Simon, VonKorff, & Barlow, 1995). Various reasons for the question why the detectionrates are low have been proposed as follows: Patients may not recognise symptoms ofdepression; patients may only report physical symptoms; PCPs may be under-educatedabout psychiatric diagnoses; and PCPs may not have adequate time to assess depression(Kramer & Smith, 2000). Therefore, depression scales are needed to accurately andquickly detect depression in those with and without medical conditions.

Various short scales for depression exist such as the BDI® – Short Form or FastScreen versions (Beck, Steer, & Brown, 2000). However, these incur substantial usercost and omit somatic symptoms of depression. Cassano and Fava (2002) acknowledgedthat detecting depression in primary care settings may be complicated, as patients canpresent with somatic symptoms, due to their medical condition, resembling those ofdepression. When using self-report questionnaires, one possibility is to omit some, orall, somatic items. Arguably, a lack of somatic items in depression scales may lead tothe underestimation of the impact of somatic symptoms on overall depression (Hung,Weng, Su, & Liu, 2006). However, some researchers have stated that for medicalpatients, in particular, somatic symptoms are the key indicators of depression (Hare &Davis, 1996; Koenig, Cohen, Blazer, & Krishnan, 1993).

Di Benedetto, Lindner, Hare, and Kent (2005) developed the Cardiac DepressionVisual Analogue Scale (CDVAS) to screen for depressive symptoms post-acute coronarysyndromes (ACS, Di Benedetto, Lindner, & Kent, 2008). The CDVAS was found to bea useful screening tool for depression seen in these populations. It consists of six VisualAnalogue Scales (VAS). VAS have been used for the simple, rapid, sensitive and reliablesubjective measurement of various states including mood (Aitken, 1969; Stern, Arruda,Hooper, Wolfner, & Morey, 1997), depression (Luria, 1975), distress and anxiety (Cella& Perry, 1986). They also allow for numerous repeated measurements (Cella & Perry,1986; Luria, 1975) Furthermore, compared with Likert scales and Borg scales, VAS havebeen shown to have excellent reliability and sensitivity (Grant et al., 1999).

Given the detrimental effects of comorbid depression and medical conditions, thereis value in having a short depression scale that can quickly assess for the presence of

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depression for use in medical or research settings. The broad aim of the study was todetermine the psychometric properties of the CDVAS in a broader population than pre-viously investigated, including primary care patients. The specific aims of the currentstudy were to evaluate the following: The internal reliability and the construct, concur-rent and discriminant validity of the CDVAS; and the predictive validity of the CDVASby assessing if the total and individual item scores significantly differed between thosewith or without depression.

Method

Participants

A total of 120 participants completed the questionnaire package. Three participantswere excluded due to excessive missing data. The mean age of the sample was40.0 years (SD = 19.0, range 18–84). Participant recruitment occurred at a medicalclinic, a community health centre and a university undergraduate psychology participantpool in regional Victoria, Australia. University students were provided with coursecredit for their participation.

Thirty-five participants had a current chronic medical condition. Eight participantshad CVD, five had diabetes, four had asthma and six had coexisting diabetes and CVD.Other medical conditions included: cancer, chronic fatigue syndrome, spinal injury, irondeficiency, fibromyalgia, epilepsy, multiple sclerosis, arthritis, irritable bowel syndrome,thyroid dysfunction, and one participant had coexisting cancer, asthma and arthritis.Eighty-three per cent of the participants were born in Australia.

Measures

Cardiac Depression Visual Analogue Scale

The six-item CDVAS (Di Benedetto et al., 2005) was developed based on items of theCardiac Depression Scale (CDS, Hare & Davis, 1996). The VAS consists of 100mmhorizontal lines anchored with opposite worded items. For example, I do not get anypleasure from life and I get great pleasure from life. Participants place a mark on theline to indicate the extent to which the statement applies to them. Higher scores on theCDVAS indicate worse mood, with 600 being the maximum score. A CDVASscore > 210 indicates mild depression (Di Benedetto et al., 2005). Items 1–3 and 6 arereversed scored. Scores are calculated by measuring from the left edge of the line towhere the participant has made the mark. The CDVAS has reportedly strong internalreliability (.91), strong test–retest reliability (.85–.97) and strong concurrent validitywith the BDI-II (r= .81) and the CDS (r= .82).

Cardiac Depression Scale

The CDS (Hare & Davis, 1996) measures depressive symptoms in cardiac populationsby incorporating questions that are considered by the authors to represent symptomsspecific to the depression that are typically seen in cardiac patients. The CDS is a26-item, self-report scale that utilises a seven-point Likert scale ranging from stronglydisagree (1) to strongly agree (7). Higher scores on the CDS indicate more severedepression. In the scale’s initial development, a Cronbach’s alpha value of .90 and acorrelation of .73 with the well-validated BDI-II were reported (Hare & Davis, 1996).

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More recently, the CDS has demonstrated strong internal consistency (α = .92) andstrong concurrent validity with the BDI-II (r = .69, Di Benedetto, Lindner, Hare, &Kent, 2006).

Depression Anxiety Stress Scales

The Depression Anxiety Stress Scales (DASS, Lovibond & Lovibond, 1995) consists ofthree self-report sub-scales developed to assess symptoms of depression, anxiety andstress during the previous week. The DASS was designed to effectively discriminatebetween these constructs. The DASS contains a total of 42 statements, with 14 state-ments relating to each sub-scale. Participants are asked to rate on a four-point responsescale the extent to which each statement applies to them. Zero represents did not applyto me at all, whereas three represents applied to me very much, or most of the time. Forthe depression sub-scale, scores above nine indicate mild to severe depressive symp-toms and scores above 27 indicate very severe depressive symptoms. The DASS hasdemonstrated strong internal consistency with Cronbach’s alpha values of .97, .92 and.95 being reported for the depression, anxiety and stress sub-scales, respectively. Thedepression sub-scale of the DASS has shown strong concurrent validity with the BDI(r = .77, Antony, Bieling, Cox, Enns, & Swinson, 1998).

Demographic questionnaire

A brief demographic and health questionnaire was developed by the authors to gatherinformation such as age and questions relating to the physical health of participants.They were specifically asked if they had diabetes, CVD or any other chronic illness.

Procedure

Ethical clearance for this study was obtained from the University of Ballarat HumanResearch Ethics Committee. Questionnaire packages were placed in the waiting roomof a participating medical clinic and community health centre, with an advertisementattached inviting people to take a questionnaire package. Participating general practitio-ners and other health professionals from this clinic and health centre also invited poten-tial participants to take a questionnaire package after their consultation. Questionnairepackages included a reply-paid envelope for participants to return the questionnaire bymail.

An advertisement inviting university undergraduate psychology students to takeplace in the study was placed on the University’s participant pool noticeboard. Potentialparticipants were then invited to a session time on campus where the questionnaireswere completed. The questionnaires were counterbalanced; however, the demographicquestionnaire was presented last.

Statistical analyses

The Statistical Package for the Social Sciences Version 16.0 was used for all analyses.There were 31 (0.2%) random missing data points across questionnaires. Missing datapoints were replaced with the mean score for all participants on that particular item(Tabachnick & Fidell, 1996). Internal reliability was evaluated using Cronbach’s alpha.Construct validity was determined using a principal components analysis (PCA) of the

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six CDVAS items. Components were extracted based on eigen values greater than oneand by visual examination of a scree plot. Component loadings of .3 or greater are gen-erally considered adequate (Tabachnick & Fidell, 1996). Concurrent validity for theCDVAS was determined using a one-tailed Pearson’s product moment correlationcoefficients between the CDVAS, the CDS and the depression sub-scale of the DASS.Discriminant validity was established by correlating the CDVAS with the anxiety andstress sub-scales of the DASS. A categorical depression variable was created, based onthe depression sub-scale scores of the DASS, to determine whether the CDVAS totaland item scores significantly differed between depressed and non-depressed groups. Par-ticipants with a score of 10 or greater were placed in the depressed group. There were39 participants in the depressed group and 78 participants in the non-depressed group.Predictive validity was determined using a multivariate analysis of variance (MANO-VA) to compare depressed and non-depressed participants on the six individual CDVASitems and total CDVAS scores.

Results

There were a number of significant differences on the psychometric scales betweenthose who had a medical condition and those who did not (Table 1). The largest differ-ences between the means were for age, CDS scores and the future item of the CDVAS.Those with a medical condition were older, weighed more and more likely to reportdepression than those without a medical condition. The mean total CDVAS score forthe entire sample was 244.0 (SD= 106.0). Those who were classified as depressed alsoscored significantly higher on stress and anxiety compared with the non-depressedgroup (Table 2). The internal consistency reliabilities for all scales were as follows:CDVAS .76, CDS .93, DASS depression .95, DASS anxiety .94 and DASS stress .91.The PCA extracted one component, accounting for 48% of the variance. This was con-firmed by visual inspection of the scree plot: Only one component was suitable forextraction. Most loadings were substantially >.4 (Table 3).

Inter-correlations among the scales were significant (all p< .001). The CDVAS corre-lated strongest with the CDS and stronger with the depression sub-scale than the anxiety

Table 1. Difference between those with or without a medical illness on psychological variables.

Variable Medical (n = 35) Non medical (n= 77) t df p

Weight 85.26 (31.31) 70.96 (18.37) 2.47 44 .02Age 51.34 (16.16) 33.96 (18.09) 4.87 110 <.001Stress⁄ 15.09 (8.75) 12.03 (9.16) 1.52 110 nsAnxiety⁄ 8.11 (8.34) 5.84 (6.79) 1.66 110 nsDepression⁄ 12.26 (10.06) 6.88 (8.51) 2.92 110 .004CDS 105.17 (26.50) 87.42 (24.45) 3.47 110 .001CDVAS 285.80 (108.62) 226.23 (103.08) 2.79 110 .006Sleep 40.69 (30.84) 37.60 (27.13) .54 110 nsPleasure 37.40 (26.73) 24.47 (19.55) 2.57 51 .01Irritation 62.37 (26.58) 46.40 (26.51) 2.95 110 .004Memory 52.20 (29.11) 48.44 (29.70) .62 110 nsFuture 53.91 (23.77) 36.43 (20.78) 3.94 110 <.001Activity 39.23 (29.13) 32.90 (26.52) 1.14 110 ns

Notes: ⁄Depression anxiety stress subscales; CDS – Cardiac Depression Scale; CDVAS – Cardiac DepressionVisual Analogue Scale.

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or stress sub-scales of the DASS (Table 4). The mean total CDVAS score for thedepressed group was 336.36 (SD= 92.21), whereas the mean total CDVAS score for thenon-depressed group was 197.32 (SD= 78.53). Figure 1 presents the mean and standarddeviation scores for the CDVAS items for depressed and non-depressed groups. AMANOVA confirmed that the total and individual CDVAS item scores were significantlyhigher amongst the depressed group compared with the non-depressed group (Table 5).

Discussion

The current findings indicate that the CDVAS is a valid, reliable and sensitive measureof depression, and the findings are consistent with previous research. In this study, theCDVAS had a some what lower internal consistency reliability than that found byDi Benedetto et al. (2005). However, the sample in that study consisted entirely ofparticipants post-ACS, whereas the current study used a sample largely from the generalpopulation and those with other medical conditions.

Using eigenvalues and visual examinations of the scree plot, one component wasextracted from the CDVAS data consistent with Di Benedetto et al. (2005) findings.Furthermore, both in the current study and the Di Benedetto et al. study, loadings weregreater than .4 on the extracted component for all CDVAS items, indicating that theCDVAS measures one construct.

The CDVAS had strong concurrent validity with the CDS, consistent with the find-ings of Di Benedetto et al. (2005). Strong correlations between the CDVAS and theCDS are expected as the CDVAS was developed based on a factor analysis of the itemson the CDS reported by Hare and Davis (1996). Similarly, strong concurrent validitywas also found between the CDVAS and the DASS depression sub-scale. This findingprovides further support for the overall concurrent validity of the CDVAS with otherdepression scales, as it is consistent with the Di Benedetto et al. (2005) study in whichthe CDVAS correlated highly with the BDI-II. Combined these findings indicate that

Table 2. Comparisons between depressed and non-depressed groups on psychometric scales.

Scale Depressed Non-depressed t df p

Depression⁄ 336.36 (92.21) 197.32 (78.53) �8.07 66.26 <.001CDS 114.54 (23.91) 81.65 (19.22) �8.03 115.00 <.001Anxiety⁄⁄ 12.23 (9.18) 3.62 (3.58) �5.65 43.89 <.001Stress⁄⁄ 20.67 (8.33) 9.26 (6.81) �7.41 64.10 <.001

Notes: ⁄CDVAS; ⁄⁄Depression Anxiety and Stress Subscales; CDS – Cardiac Depression Scale.

Table 3. CDVAS item factor loadings.

Item Factor loading

Sleep .65Pleasure .86Irritation .62Memory .45Future .77Activity .72

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the CDVAS measures depression as purported by studies that have examined theconcurrent validity of the DASS depression sub-scale, the CDS and the BDI-II(e.g. Antony et al., 1998; Beck et al., 1996; Hare & Davis, 1996).

Table 4. Correlations among CDVAS, CDS, and DASS subscales.

Scale CDS Depression⁄ Anxiety⁄ Stress⁄

CDVAS .89 .70 .57 .60CDS .71 .62 .62Depression⁄ .73 .72Anxiety⁄ .69

Notes: All p< .001; CDVAS – Cardiac Depression Visual Analogue Scale; CDS – Cardiac Depression Scale;DASS – Depression Anxiety and Stress Subscales⁄.

0

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Sleep Pleasure Irritation Memory Future Activity

r

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Scoe

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Figure 1. Mean and standard deviation scores for each CDVAS item for the high and lowdepressive symptom groups.

Table 5. Comparisons between depressed and non-depressed groups on the CDVAS items andtotal scores.

Items Depressed Non-depressed F(1, 116) p ηp2

Sleep 56.87 (29.76) 28.56 (21.87) 33.99 <.001 .23Pleasure 48.54 (23.50) 18.58 (13.70) 75.73 <.001 .40Irritation 66.26 (25.65) 44.27 (24.78) 19.95 <.001 .15Memory 56.64 (30.01) 45.24 (28.54) 4.00 .048 .03Future 61.44 (20.31) 32.31 (17.28) 65.60 <.001 .36Activity 46.62 (31.10) 28.36 (22.84) 12.95 <.001 .10Total CD-VAS 336.36 (92.2) 197.32 (78.53) 72.44 <.001 .39

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The CDVAS had good discriminant validity. The strength of the correlations betweenthe CDVAS and anxiety and stress DASS sub-scales were less than those that the CDVASshared with the CDS and the depression sub-scale of the DASS, indicating that theCDVAS was effective in discriminating between these different, but related, constructs.

All individual CDVAS item scores and the total CDVAS score were significantlyhigher for the depressed group than the non-depressed group, indicating that theCDVAS total and individual items scores have strong predictive validity, successfullydifferentiating between depressed and non-depressed groups. These findings are consis-tent with Di Benedetto et al. (2005) where the total and individual CDVAS items scoreshad strong predictive validity in differentiating between depressed and non-depressedparticipants determined by CDS and BDI-II scores.

The study has a number of limitations. The first is the relatively small sample size;therefore, the results of the PCA should be interpreted with some caution. Although agood sample size for PCA is considered to be approximately 300, this study had a Kai-ser-Myer-Olkin measure of sampling adequacy (KMO) of .79. A KMO greater than .6is considered good and consequently renders the data valid for PCA (Tabachnick &Fidell, 1996). Another limitation was the relatively small number of participants thathad medical conditions. Despite this small number, there was a broad range of illnessesreported among those with medical conditions. Therefore, these findings may be gener-alised to those with other medical illnesses other than ACS. The current findings indi-cate that the CDVAS is suitable for detecting depression in a non-medical sample.

Despite these limitations, this study provides support for the psychometric character-istics of the CDVAS in a broader sample than that used by Di Benedetto et al. (2005).Di Benedetto et al. suggested that the sound psychometric properties of the CDVASmake it a useful research tool in assessing depression post-ACS. As the current studyhad similar findings in a broader sample, the CDVAS may also be an effective researchtool for studies using participants from populations other than those with CVD. Further-more, the CDVAS can be used in studies that require numerous repeated measurementsof depression (Di Benedetto et al., 2008). It has the potential to serve as a tool for mon-itoring patients’ psychological well-being following major cardiac events or other medi-cal conditions. The ease of administration and interpretation of the CDVAS may allowhealth professionals to regularly monitor depressive symptoms and intervene whenneeded.

A further potential use of the CDVAS is as a screening tool for depression within aprimary care setting. It could be used as a screening tool to identify possible cases ofdepression, which would then require further clinical assessment. Similarly, it could alsobe used in hospital settings where patients are likely to experience comorbid depression.In addition to the sound psychometric characteristics, a number of practical consider-ations make the CDVAS a suitable tool for research and clinical purposes. It takes verylittle time to complete, allows repeated administration and is cost free.

ReferencesAitken, R.C.B. (1969). Measurement of feelings using visual analogue scales. Proceedings of the

Royal Society of Medicine, 62, 989–993.Antony, M., Bieling, P., Cox, B., Enns, M., & Swinson, R. (1998). Psychometric properties of

the 42-item and 21-item versions of the Depression Anxiety Stress Scales in clinical groupsand a community sample. Psychological Assessment, 10, 176–181.

Barefoot, J., & Schroll, M. (1996). Symptoms of depression, acute myocardial infarction, andtotal mortality in a community sample. Circulation, 93, 1976–1980.

8 M.D. Benedetto and M. Sheehan

Dow

nloa

ded

by [

Uni

vers

ity o

f Y

ork]

at 0

8:57

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13

Beck, A., Steer, R., & Brown, G. (1996). Manual for the Beck Depression-II. San Antonio, TX:Psychological Corporation.

Beck, A., Steer, R., & Brown, G. (2000). Manual for the Beck Depression-fastscreen for medicalpatients. San Antonio, TX: Psychological Corporation.

Bush, D., Ziegelstein, R., Tayback, M., Richter, D., Stevens, S., Zahalsky, H., & Fauerbach, J.(2001). Even minimal symptoms of depression increase mortality risk after acute myocardialinfarction. American Journal of Cardiology, 88, 337–341.

Cassano, P., & Fava, M. (2002). Depression and public health an overview. Journal of Psychoso-matic Research, 53, 849–857.

Cella, D., & Perry, S. (1986). Reliability and concurrent validity of three visual-analogue moodscales. Psychological Reports, 59, 827–833.

Ciechanowski, P.S., Katon, W.J., & Russo, J.E. (2000). Depression and diabetes: Impact ofdepressive symptoms on adherence, function, and costs. Archives of Internal Medicine, 160,3278–3285.

Diabetes Prevention Program Research Group. (2005). Depression symptoms and antidepressantmedicine use in diabetes prevention program participants. Diabetes Care, 28, 830–837.

Di Benedetto, M., Lindner, H., Hare, D., & Kent, S. (2005). A cardiac depression visual analoguescale for the brief and rapid assessment of depression following acute coronary syndromes.Journal of Psychosomatic Research, 59, 223–229.

Di Benedetto, M., Lindner, H., Hare, D., & Kent, S. (2006). Depression following acute coronarysyndromes: A comparison between the Cardiac Depression Scale and the Beck DepressionInventory-II. Journal of Psychosomatic Research, 60, 13–20.

Di Benedetto, M., Lindner, H., & Kent, S. (2008). The course of depression 10weeks post-acutecoronary syndrome: Assessment using the Cardiac Depression Visual Analogue Scale. Psy-chology, Health & Medicine, 13, 483–493.

Egede, L., Zheng, D., & Simpson, K. (2002). Comorbid depression is associated with increasedhealth care use and expenditures in individuals with diabetes. Diabetes Care, 25, 464–470.

Erin, I., Erdi, O., & Sahin, M. (2008). The effect of depression on quality of life of patients withtype-II diabetes mellitus. Depression and Anxiety, 25, 98–106.

Fauerbach, J., Bush, D., Thombs, B., McCann, U., Fogel, J., & Ziegelstein, R. (2005). Depressionfollowing acute myocardial infarction: A prospective relationship with ongoing health andfunction. Psychosomatics, 46, 355–361.

Fisher, L., Skaff, M.M., Mullan, J.T., Arean, P., Mohr, D., Masharani, U., Glasgow, R., & Lauren-cin, G. (2007). Clinical depression versus. distress among patients with type 2 diabetes notjust a question of semantics. Diabetes Care, 30, 542–548.

Goldney, R., Fisher, L., Phillips, P., & Wilson, D. (2004). Diabetes, depression, and quality of lifea population study. Diabetes Care, 27, 1066–1070.

Gonzalez, J.S., Safren, S.A., Cagliero, E., Wexler, D.J., Delahanty, L., Wittenberg, E., Blais, M.A., Meigs, J.B., & Grant, R.W. (2007). Depression, self-care, and medication adherence intype 2 diabetes: Relationships across the full range of symptom severity. Diabetes Care, 30,2222–2227.

Grant, S., Aitchison, T., Henderson, E., Christie, J., Zare, S., & McMurray, J. (1999). A compari-son of the reproducibility and the sensitivity to change of visual analogue scales, Borg scales,and Likert scales in normal subjects during submaximal exercise. Chest, 116, 1208–1217.

Hare, D., & Davis, C. (1996). Cardiac depression scale: Validation of a new depression scale forcardiac patients. Journal of Psychosomatic Research, 40, 379–386.

Hung, C., Weng, L., Su, Y., & Liu, C. (2006). Depression and somatic symptoms scale: A newscale with both depression and somatic symptoms emphasised. Psychiatry and Clinical Neu-rosciences, 60, 700–708.

Ismail, K., Winkley, K., Stahl, D., Chalder, T., & Edmonds, M. (2007). A cohort study of peoplewith diabetes and their first foot ulcer: The role of depression on mortality. Diabetes Care,30, 1473–1479.

Katon, W.J, Rutter, C., Simon, G., Lin, E.H, Ludman, E., Ciechanowski, P., Kinder, L., Young,B., & Von Korff, M. (2005). The association of comorbid depression with mortality inpatients with type 2 diabetes. Diabetes Care, 28, 2668–2672.

Kilbourne, A., Reynolds, C., Good, C., Sereika, S., Justice, A., & Fine, M. (2005). How doesdepression influence diabetes medication adherence in older patients? American Journal ofGeriatric Psychiatry, 13, 202–210.

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Koenig, H.G., Cohen, H.J., Blazer, D.G., & Krishnan, K.R. (1993). Profile of depressive symp-toms in younger and older medical inpatients with major depression. Journal of the AmericanGeriatrics Society, 41, 1169–1176.

Kramer, T.L., & Smith, R.G. (2000). Tools to improve the detection and treatment of depressionin primary care. In M. Maruish (Ed.), Handbook of psychological assessment in primary caresettings (pp. 463–490). Mahwah, NJ: Lawrence Erlbaum.

Ladwig, K.H., Kieser, M., Konig, J., Breithardt, G., & Borggrefe, M. (1991). Affective disordersand survival after acute myocardial infarction. Results from the post-infarction late potentialstudy. European Heart Journal, 12, 959–964.

Lin, E.H., Katon, W., Von Korff, M., Rutter, C., Simon, G.E., Oliver, M., Ciechanowski, P., Lud-man, E.J., Bush, T., & Young, B. (2004). Relationship of depression and diabetes self-care,medication adherence, and preventive care. Diabetes Care, 27, 2154–2160.

Lovibond, S., & Lovibond, P. (1995). Manual for the Depression Anxiety Stress Scales (2nd ed.).Sydney: Psychology Foundation of Australia.

Luria, R.E. (1975). The validity and reliability of the visual analogue mood scale. Journal of Psy-chosomatic Research, 12, 51–57.

Robinson, D., Geske, J., Prest, L., & Barnacle, R. (2005). Depression treatment in primary care.Journal of the American Board of Family Medicine, 18, 79–86.

Simon, G., VonKorff, M., & Barlow, W. (1995). Health care costs of primary care patients withrecognized depression. Archives of General Psychiatry, 52, 850–856.

Stern, R.A., Arruda, J.E., Hooper, C.R., Wolfner, G.D., & Morey, C.E. (1997). Visual analoguemood scales to measure internal mood state in neurologically impaired patients: Descriptionand initial validity evidence. Aphasiology, 11, 59–71.

Tabachnick, B.G., & Fidell, L.S. (1996). Using multivariate statistics (3rd ed.). New York, NY:HarperCollins College.

World Health Organisation. (2009). http://www.who.int/en/Ziegelstein, R., Fauerbach, J., Stevens, S., Romanelli, J., Richter, D., & Bush, D. (2000). Patients

with depression are less likely to follow recommendations to reduce cardiac risk duringrecovery from a myocardial infarction. Archives of Internal Medicine, 160, 1818–1823.

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