• Health-related quality of life;
  • Joint replacement;
  • Socioeconomic status


  1. Top of page
  2. Abstract


To determine health-related quality of life (HRQOL), psychological distress, physical function, and self efficacy in persons waiting for lower-limb joint replacement surgery.


A total of 214 patients on a waiting list for unilateral primary total knee or hip replacement at a large Australian public teaching hospital completed questionnaires after entry to the list. HRQOL and psychological distress were compared with available population norms.


Average HRQOL was extremely poor (mean ± SD 0.39 ± 0.24) and much lower (>2 SD) than the population norm. Near death-equivalent HRQOL or worse than death-equivalent HRQOL were reported by 15% of participants. High or very high psychological distress was up to 5 times more prevalent in the waiting list sample (relative risk 5.4 for participants ages 75 years and older; 95% confidence interval 3.3, 9.0). Women had significantly lower HRQOL, self efficacy, and physical function scores than men. After adjusting for age and sex, significant socioeconomic disparities were also found. Participants who received the lowest income had the poorest HRQOL; those with the least education or the lowest income had the highest psychological distress. Low self efficacy was moderately associated with poor HRQOL (r = 0.49, P < 0.001) and more strongly associated with high psychological distress (r = −0.55, P < 0.001).


Patients waiting for joint replacement have very poor HRQOL and high psychological distress, especially women and those from lower socioeconomic backgrounds. Lengthy waiting lists mean patients can experience extended and potentially avoidable morbidity. Interventions to address psychological distress and self efficacy could reduce this burden and should target women and lower socioeconomic groups.


  1. Top of page
  2. Abstract

In Australia, total knee replacement (TKR) and total hip replacement (THR) surgery are common, with the number of procedures performed increasing by ∼6% per year (1). The median waiting time for these procedures in Australian public hospitals was 137 days for TKR and 93 days for THR in 2002–2003, and 19% and 12% of patients waited longer than 1 year for TKR and THR, respectively (2). The Australian public hospital system provides free medical treatment to all permanent Australian residents under the taxpayer-funded Medicare scheme, but is associated with lengthy waiting lists for elective procedures. Large waiting lists for joint replacements are also common in many other countries, including the United Kingdom (3), Canada (4), and the Netherlands (5). The Organisation for Economic Co-operation and Development (OECD) recently reported that waiting for publicly-funded elective surgery is regarded as one of the most important problems affecting health systems in OECD countries (6). In addition, public opinion surveys have shown that waiting for specialist assessment and elective surgery are perceived as the greatest shortcomings of the health care system (7).

Waiting lists have become an increasing frustration for policy makers and health care professionals, with the expectation of growing demand in coming years due to the increasing prevalence of arthritis in aging populations (8). Increased need for joint replacement combined with limited public hospital resources means that waiting lists will continue to present a large problem for many developed countries in the years ahead. For the individual with end-stage arthritis, the period of waiting for surgery is complicated by ongoing pain and reduced physical function.

Currently, there are limited comprehensive and representative data on physical, psychosocial, and economic status of patients at entry to orthopedic waiting lists for lower-limb total joint replacement. Documentation of the status of patients on waiting lists is an important clinical issue because previous research has shown that high preoperative pain and poor physical function predict poor surgical outcomes up to 2 years following total hip or knee replacement (5, 9).

Socioeconomic status may also play a role in determining timely access to THR and TKR. Recent research from the United Kingdom showed that individuals who received means-tested welfare benefits were less likely to have knee arthritis managed by a hospital consultant and were less likely to be on a waiting list for knee replacement, compared with individuals who were not receiving benefits (10). Further research has also reported lower rates of hip and knee replacement in the United Kingdom for persons with the lowest socioeconomic background (11). A similar disparity in surgery rates also exists in the United States, with differences in health beliefs, economic, and personal resources cited as possible causes (12). If persons from lower socioeconomic groups have delayed access to orthopedic waiting lists, factors such as quality of life and physical function may be more adversely affected by waiting; this may lead to poorer outcomes from eventual surgery.

The aim of this study was to report the health-related quality of life (HRQOL), psychological distress, physical function, and self efficacy of patients waiting for lower-limb joint replacement and to examine whether these factors are associated with socioeconomic status.


  1. Top of page
  2. Abstract


All patients on the orthopedic waiting list for unilateral THR or TKR at the Royal Melbourne Hospital (a large Australian metropolitan public teaching hospital) as of December 2002 were invited to participate. Furthermore, from December 2002 to May 2004, all patients sequentially added to the waiting list for these procedures were contacted within 1 week and invited to participate. This study was approved by the Melbourne Health Human Research Ethics Committee.

Patients were eligible to participate if they were >18 years of age and if they were able to read English and complete written questionnaires. Eligible patients who provided verbal consent were mailed a consent form and questionnaires. Written informed consent was obtained from all participants. If responses to questions were omitted or incomplete, direct telephone followup was undertaken.

Between December 2002 and May 2004, 552 patients on the waiting list received an information letter and were then contacted by telephone. Of these, 232 patients were ineligible to participate; 184 could not speak or read English and the remainder were excluded for other reasons such as vision impairments or difficulty writing. Of the 320 (58%) who were eligible to participate, 46 (14%) declined to take part and 60 (19%) provided initial verbal consent but did not return a completed questionnaire despite followup phone calls and/or letters; 214 (67%) returned a completed questionnaire. For participants who had entered the waiting list prior to the commencement of the study (n = 85), median time on the waiting list prior to being contacted about the study was 176 days (interquartile range [IQR] 85–276 days). The remainder of participants (n = 129) were contacted at a median of 3 days (IQR 1–5 days) after entering the waiting list.


The Assessment of Quality of Life (AQOL) instrument is an HRQOL utility tool that was found to be sensitive and responsive in a number of health care settings (13, 14). The total score ranges from –0.04 (worst possible quality of life) to 0.00 (death equivalent) to 1.00 (full quality of life). Australian normative data were available for comparison (15, 16).

The Kessler Psychological Distress Scale (K10) has been widely used in Australian population health surveys (17, 18). The total score ranges from 10 (lowest psychological distress) to 50 (highest psychological distress). Definitions of low (K10 score <16), high (K10 score 22–29), and very high (K10 score ≥30) psychological distress were adopted from the 2001 Australian National Health Survey (19). High K10 scores have been found to be strong predictors of affective disorders such as depression and anxiety (20).

The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) is a disease-specific instrument commonly used to assess physical function in orthopedic research. Its validity and reliability have been extensively tested (21). The total score is calculated by summing each subscale (pain, stiffness, and physical function). For this study, the total score was transformed to a scale of 0 (best health) to 100 (poorest health) for ease of interpretation.

Self efficacy was measured using the modified Arthritis Self-Efficacy Scale, which has demonstrated reliability (22). The scale assesses confidence with the management of fatigue, pain, distress, and health care tasks related to arthritis. The total score ranges from 4 to 40 (higher score indicates higher self efficacy).

Demographic data were also collected to determine socioeconomic status according to level of household income, highest educational level completed, and employment status.

Statistical analyses.

Statistical analyses were performed with the Statistical Package for the Social Sciences (SPSS) Version 11.0 (SPSS, Chicago, IL). Data from the K10 scale were log transformed to approximate a normal distribution; all other data approximated normal distributions. Original K10 data were used for descriptive purposes; log transformed data were used for statistical analyses. Independent t-tests were used to examine the association between dichotomous variables (sex, marital status, and Australian born versus non-Australian born) and outcome variables (HRQOL, K10, WOMAC, and self efficacy). Analysis of covariance was used to identify whether differences in outcome variables existed across socioeconomic indicators (education, income, and employment status), while adjusting for age and sex. Pearson's correlation coefficient (r) was used to estimate the association between self efficacy and HRQOL, psychological distress and physical function. Relative risk (RR) for the presence of high psychological distress in the waiting list sample compared with population levels was calculated using Confidence Interval Analysis software (Version 2.0.0) (23).


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  2. Abstract

Participant demographics.

The mean ± SD age of the sample was 67 ± 12 years. There were more women than men (59% versus 41%), and the number of patients waiting for TKR and THR were similar (52% and 48%, respectively). Approximately two-thirds of the sample were married or in a de facto relationship. The majority of participants (61%) were born in Australia. Approximately 25% of the sample had previously had at least one other joint replaced.

Details of employment status, educational level, and annual household income are provided in Table 1; 74% of participants had not been employed in a paid job in the last 5 years. Nearly one-third of participants reported that they had stopped work because of their arthritis (81% of this subgroup were ≤65 years old). Of the 15 participants (7%) who were in a paid job, 9 (60%) were working full time.

Table 1. HRQOL, psychological distress, physical function, and self efficacy by demographic subgroup*
Socioeconomic characteristicnAQOL scoreK10 scoreTotal WOMAC scoreSelf-efficacy score
Mean ± SDFPMean ± SDFPMean ± SDFPMean ± SDFP
  • *

    HRQOL = health-related quality of life; AQOL = Assessment of Quality of Life instrument; K10 = Kessler Psychological Distress Scale; WOMAC = Western Ontario and McMaster Universities Osteoarthritis Index; AUD = Australian dollar.

  • Total numbers for each characteristic may not total 214 due to missing responses.

  • Analysis of covariance with adjustment for age and sex.

  • §

    $1 AUD = $0.75 US, £0.40 UK.

  • Includes home duties.

Highest educational level  2.330.06 3.590.01 0.530.72 2.100.08
 Primary school or less680.31 ± 0.24  22.85 ± 9.21  62.98 ± 21.17  18.83 ± 9.56  
 Year 7–10800.42 ± 0.24  19.36 ± 7.15  57.53 ± 18.80  21.54 ± 9.92  
 Year 11–12390.40 ± 0.22  19.08 ± 6.90  59.15 ± 16.43  23.09 ± 9.32  
 Trade/technical education180.43 ± 0.22  16.94 ± 6.45  53.29 ± 17.64  25.44 ± 8.89  
 University60.35 ± 0.26  21.00 ± 4.24  58.16 ± 18.27  23.42 ± 9.89  
Annual household income (AUD)§  3.470.01 3.030.02 0.480.75 0.900.47
 < $10,000390.27 ± 0.20  23.56 ± 9.61  63.00 ± 19.17  19.28 ± 10.04  
 $10,000–$19,999630.43 ± 0.24  18.95 ± 7.60  59.56 ± 18.55  21.59 ± 10.45  
 $20,000–$39,999270.43 ± 0.20  19.22 ± 7.04  57.32 ± 15.65  21.22 ± 9.79  
 $40,000–$59,99980.44 ± 0.23  15.75 ± 3.73  62.29 ± 14.02  26.63 ± 7.05  
 ≥ $60,00050.33 ± 0.19  19.80 ± 5.54  63.54 ± 21.11  20.00 ± 11.55  
Employment status  1.020.39 0.830.48 0.100.96 2.190.09
 Retired/aged pension1610.38 ± 0.24  20.26 ± 7.97  59.43 ± 19.02  20.78 ± 9.68  
 Employed150.47 ± 0.27  20.00 ± 7.73  57.83 ± 16.22  22.90 ± 7.62  
 Sickness benefits110.33 ± 0.23  23.55 ± 7.71  57.72 ± 23.15  16.82 ± 11.37  
 Other240.39 ± 0.24  19.42 ± 7.27  58.35 ± 21.04  24.11 ± 9.47  

Health-related quality of life.

AQOL scores indicated very poor HRQOL for patients awaiting surgery (mean ± SD 0.39 ± 0.24), and were much lower than those for the overall population (mean ± SD 0.83 ± 0.20) and for population subgroups ages 60–69 years (mean 0.79 ± 0.19) and 70–79 years (mean 0.75 ± 0.25) (15, 16).

The mean AQOL score for the sample was also lower than for community-dwelling individuals with osteoarthritis (24) (mean ± SD 0.52 ± 0.22) and was equivalent to individuals with recent stroke (13) (mean 0.40 ± 0.33). Figure 1 shows that the majority of AQOL scores fell below the overall population mean and that 15% of participants rated themselves at or near death-equivalent HRQOL (defined as AQOL score <0.10). Because mean scores were >2 SD below the overall population mean, the average HRQOL of this sample is in the bottom 5% of the population.

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Figure 1. Distribution of health-related quality of life scores. AQoL = Assessment of Quality of Life.

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Women had significantly poorer HRQOL than men (mean difference −0.07; 95% confidence interval [95% CI] −0.14, −0.01). After adjusting for age, a significant difference remained. There was no significant effect of marital status or country of birth on HRQOL. After adjusting for both age and sex, a significant difference in HRQOL remained between income levels; participants who earned <$10,000 (Australian) per year had the poorest HRQOL (Table 1). A significant difference remained after adjusting for physical function (data not shown).

Psychological distress.

K10 scores for the waiting list sample and data from the Victorian Population Health Survey (17) are presented in Table 2. High or very high psychological distress (K10 score ≥22) was significantly more prevalent for all age groups in the sample, compared with the general population. When stratified by age, prevalence ranged from >3 times higher for participants ages <55 years (RR 3.6; 95% CI 2.4, 5.6) to >5 times higher for participants ages ≥75 years (RR 5.4; 95% CI 3.3, 9.0).

Table 2. Prevalence of high psychological distress in patients waiting for joint replacement surgery compared with general population*
Age group (years)Orthopedic waiting listPopulationRR95% CI
K10 <22K10 ≥22K10 <22K10 ≥22
  • *

    Values are the number (percent) unless otherwise indicated. K10 = Kessler Psychological Distress Scale. RR = relative risk; 95% CI = 95% confidence interval.

  • Victorian Population Health Survey, n =7,500 (17).

  • High or very high psychological distress.

<5518 (58.1)13 (42.0)4,506 (88.5)586 (11.5)3.62.4, 5.6
55–6428 (66.7)14 (33.3)950 (92.6)76 (7.4)4.52.8, 7.3
65–7459 (71.1)24 (29.0)758 (93.3)54 (6.7)4.42.8, 6.7
≥7539 (67.2)19 (32.7)466 (94.0)30 (6.0)5.43.3, 9.0

There was no significant association between sex, marital status, or country of birth and psychological distress. After adjusting for age and sex, a significant difference in psychological distress was observed between both educational and income levels; participants who had completed primary school or less or earned <$10,000 (Australian) per year had the highest psychological distress (Table 1). A significant difference remained after adjusting for physical function (data not shown).

Self efficacy.

Mean ± SD self-efficacy score for the sample was 21.4 ± 9.7. Lower self efficacy was associated with poorer quality of life (r = 0.49, P < 0.001), poorer physical function (r = −0.41, P < 0.001), and higher psychological distress (r = −0.55, P < 0.001). Women had significantly poorer self efficacy than men (mean difference −3.45; 95% CI −6.09, −0.82). After adjusting for age, a significant difference remained. There was no significant effect of marital status or country of birth on self efficacy. After adjusting for age and sex, there was no significant difference in self efficacy between educational levels, income levels, or employment status (Table 1).

Physical function.

Mean ± SD WOMAC score for the sample was 59.11 ± 19.08. Women had significantly worse physical function than men (mean difference 8.53; 95% CI 3.27, 13.79). After adjusting for age, a significant difference remained. There was no significant effect of marital status or country of birth on physical function. After adjusting for age and sex, there was no significant difference in physical function between educational levels, income levels, or employment status (Table 1). Poor physical function was moderately associated with poor HRQOL (r = −0.64, P < 0.001) and high psychological distress (r = 0.53, P < 0.001).


  1. Top of page
  2. Abstract

This study found that patients on a waiting list for TKR or THR had extremely poor HRQOL, and a large proportion (15%) considered themselves to have a health state equivalent to or worse than death. These findings demonstrate that end-stage arthritis has a pervasive impact on psychological wellbeing and social health, in addition to physical wellbeing. Although the majority of patients have poor wellbeing, women and those in lower socioeconomic groups have the poorest wellbeing, indicating inequities in the management of patients with arthritis.

Poor HRQOL and high levels of psychological distress in this patient population are probably due to a combination of reduced physical mobility and ongoing severe pain. However, participants of lower socioeconomic status had significantly poorer HRQOL and higher psychological distress. It is well established that persons living in poor communities have worse health than persons in wealthy areas (25), and our data support this. Potential contributing factors may include increased difficulty obtaining health care information, lower health literacy, or reduced access to health professional services. Studies conducted in the United States and the United Kingdom found that patients with the lowest socioeconomic status had significantly lower rates of joint replacement, but explanations for these findings have been limited (11, 26). An increased aversion to undergo surgery is unlikely to be responsible, because a Canadian study reported that patients from lower socioeconomic backgrounds were equally willing to undergo joint replacement when compared with those of higher socioeconomic status (27). In the present study, women had poorer HRQOL, self efficacy, and physical function compared with men. This may be related to sex differences surrounding functional roles, reporting of symptoms, or in accessing medical services. In support of the latter possibility, a recent United Kingdom population survey reported that women requiring TKR were less likely than men to be under the care of either a general practitioner or a hospital consultant for their knee condition (10). This is an important area for further research to identify specific social and economic determinants of health and mechanisms to facilitate sex and social health care equity.

There have been only limited reports of the HRQOL of patients waiting for joint replacement. The EuroQol utility instrument was administered to patients entering a THR waiting list in the Netherlands with similarly poor HRQOL reported, but there was greater variability within the sample (5). Psychological distress has not been previously investigated in this patient group. Studies in a variety of settings have identified a strong link between chronic pain and high psychological distress (28). The prospect of a prolonged wait for surgery (up to 3 years in many Australian public hospitals) may have also contributed to this psychological morbidity. In addition, many patients will have already endured a protracted wait for an initial appointment with an orthopedic surgeon prior to entry to the waiting list. It is likely that protracted periods of waiting lead to substantial physical, psychological, and economic decline and may also compromise outcomes from joint replacement surgery.

A potential indicator of personal resources is self efficacy, or a person's confidence in his or her ability to perform a particular behavior (29). In the context of joint replacement surgery, self efficacy relates to how confident patients are to undertake activities to reduce symptoms, and how they might cope with the wait for surgery and the recovery process after surgery. Although causal inferences from these cross-sectional data are problematic, the substantial correlation between self efficacy and these variables supports the application of programs to improve self efficacy, such as patient education and self-management courses (22, 30, 31). The level of self efficacy prior to joint replacement surgery may also have important implications for postoperative recovery and warrants further research.

This study documented physical function with the WOMAC index. This instrument is disease specific, therefore normative data are not available for comparison. However, the mean subscale scores were similar to those reported by Kelly et al (4) and Ostendorf et al (5) in their assessments of patients entering Dutch and Canadian waiting lists, respectively, for lower-limb joint replacement surgery. In contrast to the HRQOL and psychological distress findings, the WOMAC demonstrated no differences across demographic groups. This may indicate that physical function is similarly restricted for most patients with end-stage arthritis, or that this questionnaire was not sensitive enough to detect subtle differences in common daily activities.

A limitation of this study is the large number of patients excluded due to insufficient English language skills. People from non-English speaking backgrounds tend to be immigrants and are generally poorer, with reduced access to health care. Therefore, our findings may well be a substantial underestimate of the social disparities in health in the orthopedic waiting list population.

This study has comprehensively documented the psychosocial and physical status of patients entering an orthopedic waiting list. The results clearly indicate that low socioeconomic status, low self efficacy, and female sex may compound the physical and psychological effects of arthritis. Given the protracted waiting times for joint replacement surgery in Australia and other countries, strategies to improve physical and psychological wellbeing while patients are on waiting lists are important. Although timely provision of joint replacements might be the preferred option, current economic and health system structures mitigate against this. The orthopedic waiting list population is likely to grow substantially in the near future with population aging and increased incidence of arthritis. In the meantime, interventions to reduce social and sex disparities and improve physical and psychological wellbeing are warranted.


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  2. Abstract
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