Home > RNJ > 2005 > March/April > Health-Related Quality of Life: Is It a Good Indicator of Function Post THR?

Health-Related Quality of Life: Is It a Good Indicator of Function Post THR?
Barbara Resnick, PhD CRNP FAAN FAANP • Denise Orwig, PhD • Lois Wehren, MD FACOG • William Hawkes, PhD • Richard Hebel, PhD • Sheryl Zimmerman, PhD • Jay Magaziner, PhD MSHyg

The purpose of this study was to explore the impact of health-related quality of life (HRQOL) measured with the Short Form Health Survey (SF-36) on Functional Recovery Status (physical and psychosocial recovery status) at baseline, 2 months, 6 months, and 12 months following total hip replacement (THR). A secondary analysis was performed using data gathered from a sample of 271 older adults post THR. Four empirically based hypothesized models were tested. None of the models fit the data, with each having significant χ2 values and χ2/df ratios greater than 3. Different dimensions of HRQOL at baseline, 2, 6, and 12 months were related to physical recovery status, and none of the 8 dimensions of the SF-36 was significantly related to psychosocial recovery status. Overall, the results of this study do not support the hypothesis that HRQOL, as measured by the SF-36, comprehensively explains functional recovery status following THR. Clinically, these findings may be applicable to individuals at risk for poor recovery. They also may prompt practitioners to consider alternative factors that influence psychosocial recovery.

Health-related quality of life (HRQOL) is a concept representing individual responses to the physical, mental, and social effects of illness on daily living. It is believed to influence personal satisfaction with life circumstances.

HRQOL should be differentiated from health status. Health status encompasses physical and emotional states. HRQOL is the individual’s interpretation of health status, and how it influences overall quality of life (Ware, 2003). Two women, for example, may have the same degrees of degenerative joint disease, impaired range of motion, and pain. One woman may overcome her daily challenges and report a very good quality of life, while the other perceives her quality of life as significantly decreased because of functional changes and pain. The subjective assessment of health status on quality of life complements the objective measurements (i.e., functional status) generally used to describe outcomes (Pearson, Stewart, & Rubenach, 1999). Increased awareness of the role psychological factors play in the process of recovering function drives current interest in HRQOL (Sadana, Mathers, Lopez, Murray & Iburg, 2000).

Johnson and Wolinsky (1993) conceptualized HRQOL as influenced by disease (i.e., comorbidities), disability, and functional status. As a result, HRQOL is used as an outcome variable following specific interventions or events. For example, HRQOL has been used as an outcome measure following joint replacements (Benroth & Gawande, 1999; Fortin et al., 1999; Hopman, Mantle, Towheed, & MacKenzie, 1999; Jones, Voaklander, Johnston, & Suarez-Almazor, 2000; Knutsson & Bergbom, 1999; Lieberman et al., 1997; O’Boyle, McGee, Hickey, O’Malley, & Joyce, 1992; Randell et al., 2000), hip fractures (Borgquist, Nilsson, Lindelow, Wiklund, & Thorngren, 1992; Randell et al., 2000), or other surgical procedures, such as prostatectomy or vascular surgery (Cleary, Greenfield, & McNeil, 1991; Hayward et al., 1999; Holtzman, Caldwell, Walvatne, & Kane, 1999; Mangione et al., 1997). HRQOL also has been used to assess the impact over time of specific diseases or problems, such as rheumatoid arthritis (Kosinski, Zhao, Dedhiya, Osterhaus, & Ware, 2000) or fear of falling (Cummings, Salkeld, Thomas, & Szonyi, 2000).

Age, gender, and ethnicity—in addition to acute and chronic clinical problems—influence HRQOL (Borgquist et al., 1992; Hopman et al., 2000; Johnson & Wolinsky, 1993; Jones et al., 2000). These relationships appear sample-specific, however, with differences in their strength and direction. HRQOL also has been noted as a predictor or indicator of willingness to exercise (Conn, 1998; Resnick, Palmer, Jenkins, & Spellbring, 2000), outcomes following total hip replacement (THR; Fortin et al., 1999; MacWilliam, Yood, Verner, McCarthy, & Ward, 1996), survival (Kaplan & Camacho, 1983; Idler & Angel, 1990; Idler, Kasl, & Lemke, 1990), and hospital readmission (Pearson et al., 1999). Presurgical HRQOL may help predict the success of the procedure’s outcome.

The Johnson and Wolinsky (1993) conceptual model of the relationship between physical disease and function on HRQOL was revised based on earlier research. The revised model describes the impact of HRQOL on psychosocial and physical recovery status (Figure 1). The purpose of this study was to test the revised model by exploring HRQOL’s effect on psychosocial and physical recovery at 12 months post THR. It is important to consider HRQOL’s impact on psychosocial and physical recovery following elective THR when identifying individuals at risk for poor recovery.


Design and Procedures

The study was a secondary analysis of data obtained from a longitudinal epidemiological study in which older adults were followed for the first 12 months post THR (Zimmerman et al., 2002). In the initial study, older individuals were recruited from 12 acute care facilities following THR. Baseline data collection was done in the acute care settings, and follow-up interviews were conducted by trained nurse evaluators in the home setting at 2, 6, and 12 months postsurgery. The study was approved by the University of Maryland Institutional Review Board.


The initial study included adults 65 years of age or older who underwent an elective THR. Among the 642 patients admitted for elective THRs in participating hospitals, 312 (47%) were ineligible for the study based on the following exclusion criteria: concomitant hip disease, lower extremity surgery within the last 6 months, revision of a previous THR, subsequent hip surgery on the nonstudy hip within 6 months, ineligible residence (nursing home or out-of-state), or canceled surgery. Of the 330 eligible patients, 271 (82%) consented to participate in the study. The average age of the participants was 73.3 (SD = 5.7). The majority were women (64%) and Caucasian (94%).

Measures Collected in the Initial Study

Descriptive measures (demographic and chronic illnesses): Demographic characteristics included age, gender, and ethnicity. Ten chronic medical conditions, which were discovered from medical chart review, were arthritis, heart disease, circulatory disease, diabetes mellitus, cancer, stroke, Parkinson’s disease, osteoporosis, dementia, and chronic obstructive pulmonary disease. The sum total of chronic illnesses was used as the measure of chronic illness in model testing.

HRQOL: HRQOL was defined as the individual’s interpretation of their health status and its impact on quality of life. HRQOL measurement was performed using the 36-Item Short-Form Health Survey (SF-36; Ware & Sherbourne, 1992). The SF-36, similar to other HRQOL measures, is a multi-item instrument that includes numerous dimensions of HRQOL (Fitzpatrick, Fletcher, & Gore, 1992). Specifically, SF-36 comprises 8 health dimensions: physical functioning (PF), role limitations due to physical health problems (RP), bodily pain (BP), general health perceptions (GH), vitality (VT), social functioning (SF), role limitations due to emotional problems (RE), and mental health (MH). Each of the 8 dimensions is measured by several items, ranging from 2 items on the bodily pain and social-functioning dimensions, to 10 items on the physical-functioning dimension. Likert’s method for summated ratings is used for scoring. Previous use of this scale with older adults has provided evidence of reliability and validity (Harada, Chiu, King, & Stewart, 2001; Heyland, Hopman, Coo, Tranmer, & McColl, 2000). Internal consistency ranged from a low of .59 to a high of .94 across subscales (median .75), and test-retest intraclass correlation coefficients were good (.75 to .97). Validity was based upon factor analysis (Ware & Sherbourne, 1992).

Functional recovery status: Functional recovery status (Figure 2) was conceptualized to include both psychosocial and physical recovery status at 12 months post THR (Magaziner et al., 2000). Physical recovery status was based upon assessment of (a) physical activities of daily living, including upper extremities (4 activities) and lower extremities (11 activities); (b) instrumental activities of daily living (IADLs), such as using the telephone, preparing meals, or housecleaning; and (c) neuromuscular functioning, including walking speed and the ability to rise from a chair (Table 1).

Psychosocial recovery status was based on the assessment of (a) social functioning, including the number of social activities in which the patient participated (going to movies, meetings, church, or temple, etc); (b) affective functioning, which was based on the Center for Epidemiological Studies-Depression (CES-D) scale (Radloff, 1977); and (c) cognitive ability, based on the Mini Mental State Exam (MMSE; Folstein, Folstein, & McHugh, 1975). A detailed description of the measures used to conceptualize physical and psychosocial recovery status is provided in Table 1.

Data analysis

Descriptive statistics were used to describe the sample, and repeated measures analysis of variance were used to examine changes over time in both HRQOL and functional status. Model testing of the hypothesized model (Figure 1) was done using four different models from each of the testing time points (baseline and 2, 6, and 12 months post THR). A description of the data analysis for model testing is provided in Table 2. Model A tested the relationship between descriptive variables, baseline HRQOL, and 12-month psychosocial and physical recovery status. Model B tested the relationship between descriptive variables, 2-month HRQOL, and 12-month psychosocial and physical recovery status. Model C tested the relationship between descriptive variables, 6-month HRQOL, and 12- month psychosocial and physical recovery status. Model D tested the relationship between descriptive variables, 12-month HRQOL, and 12- month psychosocial and physical recovery status. Unlike correlating between two variables (e.g., age being related to HRQOL), model testing allows researchers to consider the relationship among all variables in the model. Testing a model is more relevant for clinical situations because it is impossible to isolate a single variable such as age from all other factors that might influence HRQOL in the real world. Model testing will tell both researchers and clinicians how all variables influence HRQOL when they are considered together.


On average, participants had one chronic illness (M = .9, SD = 1.1), a mean MMSE score of 27.4 (SD = 2.8, with a scale range of 0–30), and a mean CES-D score of 11.9 (SD = 9.7, and scores of > 16 indicated depression). Mean scores for each dimension of the HRQOL scale and each component of psychosocial and physical function are shown in Table 3. There was significant improvement in all 8 dimensions of the SF-36 during the 12 months post THR. Over time, the psychosocial recovery status components showed a significant decrease in depressive symptoms and pain, and a small improvement in cognitive function. Likewise, physical recovery status components changed over time, with a decrease in chair rise time, an increase in walking speed, and a decline in the number of activities of daily living (ADLs) and IADLs with which participants needed help. Generally, the participants were functionally independent, cognitively intact, and not depressed at 12 months post THR.

The measurement model of functional recovery status (Figure 2), tested before full model testing fit the data (χ2 = 26, df = 19, p = .16, NFI = .98, RMSEA = .04), and all indicators of physical and psychosocial recovery status were significantly related to the appropriate construct. See Table 4 for results of full model testing; fit indices are reported in Table 5. None of the models (models A to D) fit the data, with each having significant χ2 values and χ2/df ratios greater than 3.

Influence of demographic variables on HRQOL

With the exception of baseline testing, increased age was associated with a decline in the SF-36 dimensions of physical functioning and energy/vitality. With the exception of a statistically significant relationship between race and the role-emotion component of the SF-36 at 6 months (those who were Caucasian tended to have higher role-emotional dimension scores), race was not significantly related to any dimensions of the SF-36 at the other tested time periods. Gender was significantly related to HRQOL; males were more likely to perceive a higher HRQOL with regard to physical functioning, general health, mental health, and energy/vitality at 2 ,6, and 12 months post THR. Chronic illness had minimal influence on HRQOL. Participants with fewer chronic illnesses were more likely to have better physical functioning at baseline, better general health at 2 months, and less impairment in role limitation due to emotional problems at 6 months.

Influence of HRQOL on psychosocial and physical recovery status

As anticipated, the physical functioning dimension of HRQOL was significantly related to 12-month physical recovery status (i.e., ADLs, IADLs, and performance measures) at all time points—those who reported limitations in physical activity due to health reasons had lower function. At baseline, 2-month, and 6-month testing, the role limitation-physical and energy/vitality dimensions of HRQOL were significantly related to 12-month physical recovery status. Those who had no role limitations due to health had better physical function. The baseline and 2-month bodily pain and general health HRQOL dimensions were significantly related to physical recovery status; those with pain and poorer health had lower physical function.

The role limitation-emotional dimension of HRQOL at 2 and 12 months was significantly related to physical recovery. Those who reported role limitations due to emotional problems had lower physical function. The dimensions of HRQOL social functioning and mental health at 12-month testing were related to physical recovery status; those who reported no impairment in social activities due to health and felt calm had better physical recovery status. None of the dimensions of the SF-36 was related to psychosocial recovery status.

Influence of demographic variables on psychosocial and physical recovery status

Table 6 shows the relationship between descriptive variables and 12-month physical and psychosocial recovery status. Age at all testing time points and number of chronic illnesses at baseline, 2-month, and 6-month testing were significantly related to physical recovery status. Those who were older and had fewer chronic illnesses had better physical function. Gender was significantly related to physical recovery status at all testing time points except for baseline, at which time women demonstrated better function. Race was not significantly related to physical recovery status, and none of the descriptive variables influenced psychosocial recovery status.


The hypothesized models tested in this study were not supported in that none of the models fit the data. Some of the paths within these models were statistically significant. Five dimensions of the SF-36 (role physical, pain, general health, physical functioning, and energy/vitality) were consistently related to physical recovery status in three out of the four models tested. With the exception of vitality, these dimensions comprise the physical health summary score of the SF-36 (Ware & Sherbourne, 1992). The energy/vitality dimension of the SF-36 was initially conceptualized by Ware and Sherbourne to contribute to the explanation of mental health. The current study, however, supports earlier research in which the SF-36 was used with older adults and energy/vitality explained physical health-related aspects of the SF-36, rather than mental health or mood (Mahoney, Stock, Donelson, & Minniti, manuscript submitted for publication; Resnick & Parker, 2001; Resnick & Nahm, 2001). Among older adults, it is likely that perceived vitality influences physical function rather than mental health.

None of the 8 dimensions of the SF-36 were significantly related to psychosocial recovery status (psychosocial recovery includes social activities, depressive symptoms, and cognition). Twelve-month social functioning, role limitation-emotional, and mental health dimensions of HRQOL influenced physical recovery status at 12 months post THR. These results may mean that psychosocial dimensions of quality of life have a greater impact on physical recovery status than on psychosocial recovery status in older adults following THR. This has been supported in prior research that found older adults with evidence of depression were less likely to exercise than those with no evidence of depression (Jette et al., 1998; Kressin, Spiro, & Skinner, 2000; Rejeski, Brawley, Ettinger, Morgan, & Thompson, 1997; Resnick et al., 2000; Simonsick, Guralnik, & Fried, 1999; Wells & Sherbourne, 1999), and were less likely to engage in functional activities (Resnick, 1999). It is not possible to determine the direction of this relationship, however, and research has likewise demonstrated that physical function influences mood and social activities (Brosse, Sheets, Lett, & Blumenthal, 2002; Pennix et al., 2002; Strawbridge, Deleger, Roberts, & Kaplan, 2002). Clearly, a relationship appears to exist between psychosocial variables and physical function in older adults.

The relationships between descriptive variables (demographics and chronic illness) and the 8 dimensions of HRQOL, and descriptive variables and physical and psychosocial recovery status noted in this study were sporadic and not always consistent with previous research (Brodie & Sloman, 1998; Bryant, Beck, & Fairclough, 2000; Diehr et al., 2001; Johnson & Wolinsky, 1993; Jones et al., 2001; Mulrow et al., 1996; Rodin & McAvay, 1992; Schnelle, MacRae, Ouslander, Simmons, & Nitta, 1995). These inconsistencies may indicate sample bias and/or differences in HRQOL measurement. Ongoing research is needed to establish if there is a consistent relationship between descriptive variables and HRQOL and/or psychosocial and physical recovery status so interventions can be targeted appropriately.

All dimensions of the SF-36 showed statistically significant improvement over the course of the study, demonstrating that the SF-36 was sensitive to change. Sensitivity to change, however, has not been reported consistently with the SF-36. In a study of patients with low back pain (Suarez-Almazor, Kendall, Johnson, Skeith, & Vincent, 2000), the research team concluded the SF-36 did not adequately reflect changes in HRQOL over time. The SF-36 was noted to have a floor effect for patients whose condition deteriorated. Conversely, ceiling effects were noted in a study of the impact of a strength training program on HRQOL in older women (Damush & Damush, 1999). The SF-36 also was less sensitive to change than the Osteoporosis Assessment Questionnaire when measuring HRQOL post hip fracture (Randell et al., 2000), and less sensitive when compared to the Western Ontario and McMaster Universities Osteoarthritis Index following joint replacements (Bachmeier et al., 2001).

As demonstrated previously (Jones, et al., 2000); Shields, Enloe, & Leo, 1999), the findings from this study showed that HRQOL, when defined by the SF-36, improved following elective THR. In addition, older adults who undergo THRs demonstrate improvements in physical as well as psychosocial recovery status in the first year post joint replacement. Specifically, there was improvement in functional activities, including the ability to rise from a chair, walking speed, upper extremity-related ADLs, and IADLs. The ability to perform lower extremity physical ADLs, however, decreased after the joint replacement (probably secondary to total hip precautions). These precautions, generally maintained for the first 2 months post THR, restrict patients from flexing beyond 90 degrees at the waist. This results in difficulty performing lower extremity activities, such as washing one’s lower body and/or putting on shoes. By 12 months post THR, these precautions generally were lifted, and participants were less dependent when performing lower extremity activities than they were presurgery.

Because the models hypothesized in this study do not mirror the data, it is possible that HRQOL is not predictive of recovery of function, and may better be conceptualized as an outcome following joint replacement. It also is possible, however, that the SF-36 may not be a comprehensive measure of HRQOL for older adults following joint replacement. Alternative dimensions or aspects of HRQOL may need to be considered. Lieberman et al. (1997) previously recommended that disease-specific measures of quality of life be used in addition to a general HRQOL measure, as the two measures capture different information. Moreover, it may be useful to consider individual aspects of quality of life, (i.e., to establish what each participant considers relevant to his or her quality of life). The Schedule for the Evaluation of Individual Quality of Life (SEIQOL) was used to explore individual perceptions of quality of life in a small group of older adults who underwent elective THRs (O’Boyle et al., 1992). During structured interviews, 20 participants were asked to list 5 areas they judged as important to their quality of life. Social and leisure activities and family life were nominated most frequently. This differs from the strong emphasis on function found in the SF-36. Ongoing analysis using statistical techniques such as Item Response Theory also will help to better understand quality of life measurement, particularly when measures are used with special populations, such as those undergoing orthopedic events (Reeve & Masse, 2004).

Although this study includes a relatively small group of older adults, the results do not support the use of the SF-36 as an indicator of psychosocial or physical recovery status in this population. The findings also raise concern about the overall utility of the SF-36 when used with older adults as a single measure of HRQOL because it focuses exclusively on function. Aspects of HRQOL that are both disease-specific and based on individual traits may not be captured completely by the SF-36, a generic HRQOL measure.

The study did help identify significant relationships among demographic variables, components of the SF-36, and outcomes post THR, and between components of the SF-36 and recovery of physical and psychosocial functioning. These relationships can help guide clinical work. Specifically, there was a consistent relationship between age and gender and the physical functioning and energy components of the SF-36. After THR, women who are older appear at particular risk for lower HRQOL in the areas of physical function and perceived energy and vitality. These women may need specific interventions that will help boost their quality of life. It may be particularly helpful to assure women that function can and likely will improve over time, particularly if they engage in recommended physical activity. Likewise, this activity will help to improve their overall energy.

The finding that there was no relationship between aspects of perceived HRQOL and psychosocial recovery (i.e., the desire to engage in social activities, mood, and cognition) suggests that other factors may affect this aspect of recovery. From a clinical perspective, an individual’s perceived function and role limitations should not necessarily limit psychosocial recovery. Individuals post THR simply may need encouragement to increase or return to social activities. Also consider other personality factors such as resilience and motivation; these traits may have a greater impact on willingness to return to activities within a senior center or overall mood than physical function, pain, or other components of the SF-36. Surprisingly, not even the psychosocial dimensions of quality of life influenced social recovery. Rather, mood and a sense of vitality had a greater impact on physical function. The influence of mood, which has been noted in other studies, reinforces mood’s effect on physical recovery following an orthopedic event. To optimize recovery, it may be helpful to improve mood and encourage a sense of vitality.

In contrast with the relationship between age and HRQOL, older individuals seem to have better functional ability post THR than their younger counterparts. This may be due in part to the fact that older people who consented to THR and passed preoperative tests were not particularly at risk for poor outcomes based on age (Jones et al., 2001). Clinicians caring for individuals post THR should not assume that age will result in poorer functional outcome. Bear in mind that those with multiple chronic illnesses are at risk for poorer outcomes, however. These individuals may benefit from additional rehabilitation interventions to optimize outcomes.

Continued research must focus on how older adults evaluate their quality of life, and the dimensions of quality of life that are important to them after orthopedic surgery. Measures that do not have ceiling and floor effects need to be developed. Determining the impact of HRQOL on outcomes after joint replacement (or other acute events) will help clinicians identify those at risk for poor outcomes, and will guide the development of interventions to facilitate recovery.

About the Authors

Barbara Resnick is an associate professor, University of Maryland School of Nursing, Baltimore, MD. Denise Orwig is an assistant professor, University of Maryland, School of Medicine, Baltimore, MD. Lois Wehren is a postdoctoral fellow, University of Maryland, School of Medicine, Baltimore, MD. William Hawkes is an assistant professor, University of Maryland, School of Medicine, Baltimore, MD. Richard Hebel is a professor, University of Maryland, School of Medicine, Baltimore, MD. Sheryl Zimmerman is an associate professor, University of North Carolina, School of Social Work Chapel Hill, NC. Jay Magaziner is a professor, University of Maryland, School of Medicine, Baltimore, MD. Address correspondence to Barbara Resnick, University of Maryland School of Nursing, 655 West Lombard Street Baltimore, MD 21201, or e-mail bresnick@umaryland.edu.


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