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The Effects of Kidney-Disease-Related Loss on Long-Term Dialysis Patients’ Depression and Quality of Life: Positive Affect as a Mediator

Ramony Chan,*† Robert Brooks,‡ Jonathan Erlich,§ Josephine Chow,† and Michael Suranyi† *Consultation Liaison Psychiatry, †Renal Unit, and ‡Centre for Population Mental Health Research, Liverpool Hospital,

and §Department of Nephrology, Prince of Wales Hospital, Sydney, New South Wales, Australia

Background and objectives: In kidney disease, the concept of loss is widely discussed but minimally researched. It appears

that dialysis patients who grieve a range of losses suffer increased depression and reduced quality of life (QoL). Limited

research is partly due to the lack of a relevant loss measure. The study presented here developed a measure and tested the

criterion validity of loss in relation to depression and QoL.

Design, setting, participants, & measurements: In a cross-sectional observational study, 151 long-term dialysis patients were

interviewed using standardized psychometric measures and the Kidney Disease Loss Scale (KDLS), developed for the study.

Factor, path and multigroup analyses were conducted.

Results: The factor structure and reliability of KDLS were supported. The path analyses supported the criterion validity of

loss. It was a stronger contributor to depression than other clinical variables. Its effect on QoL was fully mediated by depression

and positive affect (coping). The magnitude of the paths from loss to QoL through depression and positive affect was larger in

home-based dialysis patients than in hospital-based patients.

Conclusions: KDLS is a promising measure of loss. Patient-defined losses may contribute to the high level of depression and

in turn a reduction in patients’ coping and QoL. These findings suggest several points of intervention to improve long-term

dialysis patients’ QoL.

Clin J Am Soc Nephrol 4: 160 –167, 2009. doi: 10.2215/CJN.01520308

he concept of Kidney-Disease-Related Loss (KDRL) in

ESRD has been clinically and theoretically significant

for decades (1– 4). ESRD patients experience multiple

losses, both tangible and symbolic; for example, loss of physical

strengths, freedom, employment, and social life, resulting in

grief throughout the course of ESRD and dialysis (1,2,4). Re-

solving loss successfully is identified as one of the adaptational

factors in ESRD (3). Although widely discussed, there exists no

clear definition or measure of KDRL.

Loss, traditionally discussed in the context of death, has

recently been broadened to comprise loss of significant ele-

ments in a person’s life due to chronic illness (5,6). In chronic-

illness-caused losses, individual grief responses, rather than

actual losses, are of conceptual importance (6). These grief

responses, which can persist for many years and cause signif-

icant dysfunctions, are shown to be empirically and conceptu-

ally different from depression and anxiety in several studies (7–

10). The grief symptomatology is characterized by cognitive

preoccupation or rumination, yearning, disbelief, stunned re-

sponses, and nonacceptance of losses (7,9,11), which could be

summarized as cognitive and affective grief responses (6). Thus,

the study presented here defines KDRL as the cognitive and

affective grief responses after tangible and symbolic losses due

to kidney disease and its treatments. This definition will guide

the development of a measure for KDRL.

KDRL has traditionally been seen as one of the causes of

depression in ESRD patients. In the psychodynamic perspec-

tive, depression may be an extension of patients’ grief re-

sponses (1) or KDRL may increase patients’ vulnerability to

developing depression (4). In the cognitive-behavioral perspec-

tive, patients’ cognitive rumination over their losses may lead to

depression, as negative rumination has been found to be

associated with depression (12,13).

There exists a strong inverse relationship between depression

and quality of life (QoL) in ESRD patients (14,15). If KDRL is a

significant cause of depression, it may have a mediated effect on

QoL through depression or KDRL may also independently affect

both depression and QoL. Although the literature sug- gests a

direct relationship between depression and QoL, posi- tive affect

as a way of coping (16,17) may mediate the effect of depression

and loss (18). Positive affect may have adaptive

values in dealing with chronic stress (16,17) and thus moderate

Received March 31, 2008. Accepted July 23, 2008.

Published online ahead of print. Publication date available at www.cjasn.org.

Correspondence: Ramony Chan, Consultation Liaison Psychiatry, Liverpool Hos-

pital, Locked Bag 7103, Liverpool BC, New South Wales 1871, Australia. Phone: 61-

2-9616-4680; Fax: 61-2-9616-4691; E-mail: ramony.chan@sswahs.nsw.gov.au

the effect of depression and KDRL on QoL.

The clinical validity of KDRL can be understood not only by

measuring it, but also by examining its relations to clinical

variables, including medical comorbidity, length of time on

dialysis, and level of hemoglobin and its effects on hospital-

Copyright © 2009 by the American Society of Nephrology ISSN: 1555-9041/401–0160

Clin J Am Soc Nephrol 4: 160 –167, 2009 Role of Loss in Kidney Disease 161

and home-based dialysis patients. It is hypothesized that pa-

tients’ KDRL will covary with these clinical variables influenc-

ing QoL through depression and positive affect (15,19 –23).

Moreover, the clinical observation suggests that hospital-based

patients may experience more losses and become accustomed to

their effects, whereas home-based patients may regain or min-

imize some losses through the advantages of home treatments.

Thus, it is assumed that each additional loss for home-based

patients will have a greater effect on their well being and QoL, and

thus the clinical validity of the KDRL can be demonstrated.

The aim of this research is to show the criterion-related

validity of the KDRL construct by developing a measure for

KDRL, to examine its relationship with relevant psychologic

and clinical variables, and its effect on home-based dialysis

patients. It is hypothesized that (1) the proposed scale of KDRL

will consist of cognitive and affective grief responses and that

(2a) loss will lead to depression, (2b) covary with other clinical

variables to influence QoL through depression and positive

affect, and (2c) influence the home-based patients more.

Materials and Methods Participants

Participants were recruited from two major university teaching hos-

pitals in Sydney South West Area Health Service (SSWAHS) and South

Eastern Sydney & Illawarra Area Health Service (SESIAHS) Sydney,

Australia. The inclusion criteria were a diagnosis of ESRD, receiving

dialysis treatment for approximately 2 yr or more and aged 18 or above.

The main exclusion criterion was incapacity to complete questionnaires

and/or the semistructured interview with reasonable assistance. Of 209

eligible patients, 31 (14.8%) refused, 7 (3.4%) withdrew during the

interview as being too sick to continue, 16 (7.7%) did not return the

questionnaires, and 4 (1.9%) did not complete the data collection be-

cause of death, transplant, acute medical problems, or cognitive im-

pairment. Thus, 151 (72.2%) patients participated in the interview and

returned the questionnaires. The sample consisted of 90 (60%) men and

61 women (40%) with the mean age 58 ± 14.28 (SD) yr, the mean

duration of dialysis was 67.97 ± 42.84 (SD) mo (range 22 to 248 mo).

Approximately half (n 68, 45%) of the participants were doing home-

based dialysis, including home hemodialysis (n 26, 17%) and peritoneal

dialysis (n 42, 28%), and the others (n 83, 55%) were on hospital-based

dialysis including satellite (n 56, 37%) and in-center hemodialysis (n 27,

18%).

Procedures

This study was approved by the SSWAHS and SESIAHS Ethics

Committees. After being informed of the study details and having

signed a consent form, participants completed the semistructured in-

terview and returned completed questionnaires by mail. One reminder

letter and spare questionnaire were sent to those who did not return the

questionnaires. Two interviewers were trained in the application of

measures before the initiation of the study to ensure the quality of the

data collection.

Measures

Seven variables were examined in the study: QoL, depression, KDRL,

positive affect (a key component of coping), medical comorbidity, length

of time on dialysis, and hemoglobin. In addition to developing a scale

to measure KDRL, standardized measures were used in the study—the

Schedule for Evaluation of Individual Quality of Life—

Direct Weighting (SEIQoL-DW) (24), the Depression Scale of Depres-

sion Anxiety Stress Scale 21 (DASS21) (25), the Positive Affect Scale

(PAS) (18), and the Comorbidity Index (CMI) (26,27). Additional ques-

tions were included to collect participants’ demographic and dialysis

related information including length of time on dialysis (the total

number of months). Hemoglobin level was an average over 3 mo,

including the month of the research interview.

The Kidney Disease Loss Scale

The measurement context in which an individual considers their

losses will in part determine the validity of the measurement. The con-

text can be determined from individual-defined losses or from a stan-

dard set of losses. The type and importance of losses varies widely

between patients and thus a predefined set of losses may only be

partially relevant to any individual’s experience (6,24). The Kidney

Disease Loss Scale (KDLS) was constructed to first elicit the five most

important individual KDRL and second to obtain cognitive and affec-

tive grief responses. A second-order factor structure of KDLS was

hypothesized with four statements measuring cognitive rumination and

four measuring the affective response to loss.

The SEIQoL-DW

The SEIQoL-DW is a patient-centered semistructured interview to

measure individual QoL (24). It was chosen because of known limita-

tions in multidimensional measures of QoL (28) and its ability to

produce both qualitative and quantitative data. Of particular impor-

tance for renal patients are that preselected life domains may not be

relevant, and equal weighting of life domains is inconsistent with

patients’ own values (29,30).

In the SEIQoL-DW, the five most important areas of a respondent’s

life are elicited, then the level of satisfaction and relative importance of

each area is determined. Its global index score, ranging from 0 to 100, is

the sum of a product of the ratings and weightings of each nominated

area. Its reliability, validity, and utility in the medical and ESRD pop-

ulations are excellent (24,30 –33).

The DASS21

The DASS21 is a 21-item scale, comprising of three subscales: depres-

sion, anxiety, and stress (seven items each), a total score for each

subscale ranging from 0 to 21. Only scores on the depression subscale

were used in the analyses. The DASS21 focuses on the cognitive and

affective aspects of depression, limiting the methods bias of using a

measure that contains somatic elements common to depression and

kidney disease (2,34,35). Additionally, it was developed in the Austra-

lian population (the site of this study); it has strong psychometric

properties in both general and clinical populations (25,36,37); it is

relatively short, reducing administrative burden on patients; and dif-

ferentiates depression, anxiety, and stress.

PAS

The PAS is a four-item scale on a Likert scale ranging from 0 (not at

all) to 10 (very much), with a total score ranging from 0 to 40 to measure

individual positive feelings. Its reliability and discriminant and conver-

gent validities have been well established (18).

CMI

The CMI was compiled on the basis of Friedman’s Index (26) and

Charlson’s Index (27). It is in a checklist format, with scores ranging

from 0 to 15, higher scores indicating more comorbid conditions.

162 Clinical Journal of the American Society of Nephrology Clin J Am Soc Nephrol 4: 160 –167, 2009

Data Analyses Analyses were performed with SPSS 15 (38) and LISREL 8.72 (39).

Missing data were rare and nonsystematic and thus replaced using EM

(expectation-maximization) method (38,40). The first set of analyses

examined and validated the factor structure of the KDLS using confir-

matory factor analysis (CFA) and exploratory factor analysis (EFA).

Standard techniques of correlation, ANOVA, and t test were used with

a critical value of alpha set to 0.05. The final set of analyses used

structural equation modeling (SEM) to test, develop, and examine

alternative models. Multigroup analyses were used to compare hospital

and home dialysis.

The two-step approach was used with SEM (41). Composite scores of

the observed variables, using the unit-weighted addition method, were

calculated and error variances fixed in the measurement model (42,43)

before the structural model was tested. Because the distributions of the

observed variables were skewed, SEM was undertaken using “asymp-

tomatic distribution free covariance” matrices using the robust maxi-

mum likelihood and the Satorra-Bentler statistic for parameter estima-

tion (44 – 46). Several goodness-of-fit (GFI) indices were chosen to

evaluate the overall model fit (40): Satorra-Bentler x2 test (P > 0.05, in

SEM nonsignificant x2 indicates a good model fit), the GFI (>0.90),

adjusted GFI (AGFI) (>0.90), the root mean square residual (RMR; close

to 0), the root mean square error of approximation (RMSEA; <0.05, 90%

confidence interval <0.08), and the comparative fit index (CFI; >0.90).

Results Development of KDLS

The hypothesized factor structure of KDLS was not sup-

ported using CFA [x2 73.44, degrees of freedom (df) 19, P 0.00,

RMSEA 0.09, GFI 0.89, AGFI 0.80, CFI 0.99,

RMR 0.05; LISREL 8.72 39]. Re-examining the data, EFA using

SPSS (38) indicated two factors with 72.24% of the total variance

explained. There were two items loading onto both factors and

therefore excluded (42). The first factor consisted of four items

and resembled cognitive responses and the second factor

consisted of two items reflecting affective responses. The second

factor was retained for its theoretical importance and the items’

correlation was greater than 0.7 (47). The two factors were

strongly correlated (r 0.71, P < 0.01), suggesting the previously

hypothesized second-order factor. The new factor structure and

possible second-order factor model were exam- ined using CFA

(x2 12.63, df 8, P 0.128, RMSEA 0.00, GFI 0.97, AGFI 0.93,

CFI 1.00, RMR 0.03) (LISREL 8.72 39). The

first-order factors measure cognitive and affective responses

and a second-order factor reflects an overall sense of loss re-

garding self-defined KDRLs. Therefore, the KDLS comprises an

overall loss scale by summing the six items (48) and two sub-

scales (see Table 1). High scores are indicative of greater sense

of loss, with more rumination and stronger affect. The internal

consistence of KDLS was good (a 0.88 for both the cognitive and

affective subscales).

The convergent and discriminant validity of KDLS were

supported by its significant positive correlation with depres-

sion (r 0.60, P < 0.01), and negative correlation with QoL (r

-0.20, P < 0.05) and positive affect (r -0.36, P < 0.01). It was

unrelated to clinical variables (hemoglobin r 0.07, comorbid-

ity r 0.04, length of time since dialysis r -0.15). Construct

validity was examined by conducting a two-factor EFA of the

six KDLS and the seven DASS21 depression items. The depres-

sion items loaded onto one factor and KDRL items loaded onto

another without cross-loading items.

Patients’ nominated losses on KDLS were codified by two

independent coders by iteratively examining the data. The

intercoder agreement was 95% and the differences in the re-

maining 5% were resolved by consensus. In total, 109 of 151

respondents nominated 431 losses. Of the 23 types of losses

identified, the seven most common were travel (18.56% of the

total nominated losses), leisure activities (12.06%), physical

functioning (10.90%), employment/work (9.74%), family/per-

sonal relationships (6.50%), freedom (perception of being free

from constraints; 4.87%) and social life (4.87%). The mean score

difference on KDLS between those who did not nominate losses

(x- 5.41) and those who did (x- 5.84) was nonsignificant (t 0.49,

df 149, P > 0.05).

Univariate Analyses

There was no gender differences in the variables used in the

study. An examination of differences between the two hospitals

identified a significant difference in hemoglobin levels (SS-

WSAH x- 123.84 (13.88), SESIAHS x- 117.13 (14.05), P <

0.01); there were no differences on other variables. There were

no treatment modality (in-center hemodialysis, home hemodi-

alysis, peritoneal dialysis, satellite hemodialysis) differences on

any variable.

Path Analyses

Model Testing and Modification. The structural relation-

ships between length of time on dialysis, hemoglobin, comor-

bidity, loss, depression, positive affect, and individual QoL

were examined using SEM. The hypothesized path model was

not supported (x2 16.57, df 8, P 0.04, RMSEA 0.09; for all

fit statistics see Table 2). Therefore, the model modification

process was conducted to improve the model fit by examining

the t-values of path coefficients, standardized residual values,

and modification indexes. The path from hemoglobin to de-

pression was insignificant and thus deleted, and an additional

path from comorbidity to positive affect added (x2 7.91, df 13,

P 0.85, RMSEA 0.00; see Table 2 and Figure 1), indi- cating a

plausible model for the observed data.

As shown in Table 3, each variable explained a small pro-

portion of variance in QoL with positive affect (9.6%) and

hemoglobin (4.8%) having the highest direct effect. The effects

on positive affect from comorbidity and length of time since

dialysis were moderate whereas depression explained the larg-

est proportion (29.2%) of variance in positive affect. Loss ex-

plained 38.4% of variances in depression, larger than comor-

bidity (2.3%) and length of time since dialysis (5.3%), and only

had a small effect on QoL fully mediated by depression and

positive affect.

Alternative Models

In covariance structure modeling, several equivalent mod- els

may exist (40). Two theoretically based alternative mod-

Clin J Am Soc Nephrol 4: 160 –167, 2009 Role of Loss in Kidney Disease 163

Table 1. The final version of the Kidney Disease Loss Scale (KDLS)a

When you consider life as it is now with kidney disease and dialysis treatments, it is clearly different from what your life used to be or would have been. You might find yourself having lost many things. Please consider LOSSES: things that you used to do before kidney disease/dialysis and now you cannot do anymore or things that you would have been doing if you did not have kidney disease/dialysis. Please list below the five most important things you have lost because of the kidney disease/dialysis.

1: 2: 3: 4: 5: In regard to the five losses described above, please read each of the following statements carefully and circle a

number 0, 1, 2 or 3 that indicates how much the statement applied to you The rating scale is as follows: 0 Did not apply to me at all 1 Applied to me to some degree, or some of the time 2 Applied to me to a considerable degree, or a good part of time 3 Applied to me very much, or most of the time

1. I think about these losses so much that it is hard for me to do the everyday things I normally do 0 1 2 3

2. Memories of the losses upset me 0 1 2 3

3. I am preoccupied with thoughts of the losses 0 1 2 3

4. I feel myself longing for regaining what I have lost 0 1 2 3

5. I feel disbelief over what happened 0 1 2 3

6. I feel stunned or dazed over what happened 0 1 2 3

aThe first part of the KDLS that requires respondents to nominate the five most important losses must be retained when the KDLS is used, because it sets the context for rating the six items.

els were also tested. Alternative model 1 was to examine if

depression has a direct effect on QoL, and alternative model 2

was to investigate the ordinal relations between KDRL and

depression. The x2 difference statistics showed that alterna-

tive model 1 was not a better model (x2D 1.85, dfD 1,

nonsignificant, P < 0.05; also see Table 2). Alternative model 2

was rejected by the fit statistics (Table 2); depression does not

precede KDRL.

Table 2. The goodness-of-fit statistics of the hypothesized, modified, and alternative modelsa

Path Models Goodness-of-Fit Statistics

Hypothesized path model x2 df P GFI AGFI RMR RMSEA 90%CI CFI 16.57 8 0.04 0.97 0.89 16.25 0.09 0.02 to 0.14 0.95

Modified path model x2 df P GFI AGFI RMR RMSEA 90%CI CFI 7.91 13 0.85 0.99 0.97 15.81 0.00 0.00 to 0.05 1.00

Alternative model 1b x2 df P GFI AGFI RMR RMSEA 90%CI CFI 6.06 12 0.91 0.99 0.98 17.42 0.00 0.00 to 0.03 1.00

Alternative model 2c x2 df P GFI AGFI RMR RMSEA 90%CI CFI

41.20 13 0.00 0.93 0.84 13.33 0.12 0.08 to 0.16 0.84

ax2, Satorra-Bentler scaled chi-square; df, degrees of freedom; GFI, goodness-of-fit index; AGFI, adjusted GFI; RMR, root mean square residual; RMSEA, root mean square error of approximation; NNFI, non-normed fit index; CFI, comparative fit index.

bAdditional path from depression to quality of life was added in the model. cKidney-disease-related loss precedes depression, given all other parameters being constant.

164 Clinical Journal of the American Society of Nephrology Clin J Am Soc Nephrol 4: 160 –167, 2009

Figure 1. Path diagram of the final modified model of KDRL. QoL, quality of life; PA, positive affect; KDRL, kidney-disease-related loss; CM, comorbidity; LT, length of time since dialysis (months); Hb, hemoglobin level. Figures in gray are standardized coefficients. Figures in brackets are estimates.

KDRL in Relation to the Treatment Location Effect To further demonstrate the criterion validity of KDRL, a

multigroup analysis on the hospital- and home-based dialy- sis

patients was conducted. The poor global fit statistics (x2

135.66, df 38, P 0.00, RMESA 0.19) suggested

differences between the two groups. A reasonable fit (x2 43.87,

df 34, P 0.12, RMSEA 0.06) of the re-specified model

suggested that the main difference was a greater strength of

the relations between KDRL, depression, positive affect, and

QoL in home-based dialysis patients, although

Table 3. Standardized direct, indirect, total effects of the variablesa

CMI Loss Hemoglobin Length of Time Since Dialysis Positive Affect Depression

Direct effects QoLb - Positive affect -0.23 Depression 0.16

Indirect effects QoL

-0.10

-0.11

-

-0.04

-

-0.17 Positive affect -0.08 -0.34 - -0.12 - -

Depression - - - - - -

Total effects QoL

-0.10

-0.11

0.22

-0.04

0.31

-0.17

Positive affect -0.31 -0.34 - -0.12 - -0.54

Depression 0.16 0.62 - 0.23 - -

aStandardized total effect is the sum of direct and indirect effects of one variable on another variable. Its value ranges from 0 to 1 with either negative or positive direction. The larger the value is, the stronger the effect is.

bQoL, quality of life.

- -

0.22 -

- -

0.31 -

- -0.54

0.62 - 0.23 - -

Clin J Am Soc Nephrol 4: 160 –167, 2009 Role of Loss in Kidney Disease 165

mean score differences on these variables between the

groups were nonsignificant.

Discussion The study presented here provides empirical support for

KDLS and the hypotheses that loss leads to depression, cova-

ries with length of time since dialysis to influence QoL through

depression and positive affect, and has greater effect on home-

based patients. Moreover, the moderate direct effect that he-

moglobin has on QoL is consistent with previous clinical trials

showing erythropoietin treatment enhances ESRD patients’

QoL (49).

The concept of KDRL is operationalized by KDLS, which has

encouraging psychometric properties. Consistent with previ-

ous research, depressive and loss symptoms loaded onto sep-

arate factors, and the path analyses demonstrated that KDRL

precedes depression (7–10). Thus the KDRL is empirically dis-

tinct from depression. The cognitive rumination, yearning, dis-

belief, and stunned responses remain the key symptomatology

that contributes to depression.

KDRL as a strong contributor to depression is consistent with

the previous theories that loss is a significant cause of depres-

sion. Although the findings presented here may not support

depression as being an extension of KDRL, whether depression

is due to increased vulnerability or cognitive rumination over

negative contents of loss remains equivocal. Perhaps, more

cognitive rumination items contributing to the total score of

KDLS may suggest that cognitive rumination is the underlying

mechanism between KDRL and depression. Nevertheless, the

findings that travel, leisure activities, and physical functioning

are the most nominated types of losses may not be surprising

clinically, because many dialysis patients commonly describe

their dialysis experiences as being restrictive. Therefore, these

results may suggest that to improve patients’ depression and

QoL, psychosocial interventions could target loss; for example,

helping patients to regain losses by helping them to travel or

perform activities more, or to process their related thoughts and

feelings by reducing their cognitive ruminations. Encour-

agingly, these findings have already changed the educational

practice of one of the renal units where the study was con-

ducted.

Another interesting finding of the study is that the effect of

both KDRL and clinical variables on QoL is mediated by de-

pression and positive affect. This shows that disease-specific

variables may influence QoL indirectly through psychologic

states (50). However, the type of psychologic states has not been

explicitly specified, but rather implicitly assumed to be

depression in the ESRD literature. The findings presented here

suggest that both positive and negative psychologic states could

act as mediators. Positive affect may be a distinct factor and has

adaptive values buffering the effect of loss and depres- sion on

QoL (17,18).

The criterion validity of the KDRL construct is also illustrated

by the multigroup analyses showing that a stronger magnitude

of the relations between KDRL and other psychologic variables

exists for home-dialysis patients. For a small increase in their

sense of loss, home-based patients experience more depression

and greater decline in positive affect and QoL than do the

hospital-based. This may mean that psychosocial interventions

for home-based dialysis patients, especially on the KDLS and

depression, could result in greater improvement in their QoL

and potentially delay the need for hospital-based treatment.

The study presented here has several limitations. The KDLS is

a newly developed scale and awaits further research to

crossvalidate its validity and reliability. Future research may

also focus on item generation for the affective subscale of KDLS

to improve its construct validity. Because the main purpose of

the path analyses results was to examine the construct validity

of the KDLS, the substantive meaning of the model requires

replication in different samples. The sample size for the multi-

group analyses is considered small in SEM, and although con-

sistent with preliminary expectations, the interpretation of these

results should be cautious.

Overall, the study presented here demonstrated the construct

and criterion validity of KDRL and the promising psychometric

properties of KDLS. KDRL may lead to depression and through

it reduces QoL. The effect of depression is mediated by the

coping mechanism of positive affect. The development of any

new scale requires multiple studies to fully understand its

properties. Studies in different populations (e.g., pre- and early-

dialysis patients) will also add to the construct validity.

Acknowledgments

The results of this paper were presented at the American Society of

Nephrology 40th Annual Scientific Conference, San Francisco, Califor-

nia, 2007 and the 43rd Annual Scientific Meeting of the Australian and

New Zealand Society of Nephrology, Gold Coast, Australia, 2007. The

abstract of this paper has been published in Nephrology (Chan, R, Brooks,

R, Erlich, J, Chow, J, Suranyi, M: The role of kidney disease related loss

in dialysis patients’ quality of life: depression and positive affect as

mediating factors [Abstract], Nephrology 12[Suppl 2]: A6, 2007). The

authors thank all staff and patients at both participating hospitals for

their support and Ms. Ruth Orchison for reviewing this paper.

Disclosures None.

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