Magnitude and meaningfulness of change in SF-36 scores in four types of orthopedic surgery

Background: The Medical Outcomes General Health Survey (SF-36) is a widely used health status measure; however, limited evidence is available for its performance in orthopedic settings. The aim of this study was to examine the magnitude and meaningfulness of change and sensitivity of SF-36 subscales following orthopedic surgery.

Methods: Longitudinal data on outcomes of total hip replacement (THR, n = 255), total knee replacement (TKR, n = 103), arthroscopic partial meniscectomy (APM, n = 74) and anterior cruciate ligament reconstruction (ACL, n = 62) were used to estimate the effect sizes (ES, magnitude of change) and minimal detectable change (sensitivity) at the group and individual level. To provide context for interpreting the magnitude of changes in SF-36 scores, we also compared patients' scores with age and sex-matched population norms. The studies were conducted in Sweden. Follow-up was five years in THR and TKR studies, two years in ACL, and three months in APM.

Results: On average, large effect sizes (ES≥0.80) were found after orthopedic surgery in SF-36 subscales measuring physical aspects (physical functioning, role physical, and bodily pain). Small (0.20–0.49) to moderate (0.50–0.79) effect sizes were found in subscales measuring mental and social aspects (role emotional, vitality, social functioning, and mental health). General health scores remained relatively unchanged during the follow-up. Despite improvements, post-surgery mean scores of patients were still below the age and sex matched population norms on physical subscales. Patients' scores on mental and social subscales approached population norms following the surgery. At the individual level, scores of a large proportion of patients were affected by floor or ceiling effects on several subscales and the sensitivity to individual change was very low.

Conclusion: Large to moderate meaningful changes in group scores were observed in all SF-36 subscales except General Health across the intervention groups. Therefore, in orthopedic settings, the SF-36 can be used to show changes for groups in physical, mental, and social dimensions and in comparison with population norms. However, SF-36 subscales have low sensitivity to individual change and so we caution against using SF-36 to monitor the health status of individual patients undergoing orthopedic surgery.

Quality of life assessment in the community-dwelling elderly : validation of the Assessment of Quality of Life (AQoL) instrument and comparison with the SF-36

Measurement of Health-Related Quality of Life (HRQoL) of the elderly requires instruments with demonstrated sensitivity, reliability, and validity, particularly with the increasing proportion of older people entering the health care system. This article reports the psychometric properties of the 12-item Assessment of Quality of Life (AQoL) instrument in chronically ill community-dwelling elderly people with an 18-month follow-up. Comparator instruments included the SF-36 and the OARS. Construct validity of the AQoL was strong when examined via factor analysis and convergent and divergent validity against other scales. Receiver Operator Characteristic (ROC) curve analyses and relative efficiency estimates indicated the AQoL is sensitive, responsive, and had the strongest predicative validity for nursing home entry. It was also sensitive to economic prediction over the follow-up. Given these robust psychometric properties and the brevity of the scale, AQoL appears to be a suitable instrument for epidemiologic studies where HRQoL and utility data are required from elderly populations.

Impact of positively- versus negatively-worded items on the factor structure of three psychological measures: W-BQ22, W-BQ12 & SF-36

Background: The 22-item Well-being Questionnaire (W-BQ22) (Bradley, 1994) includes Anxiety, Depression, Energy and Positive Well-being subscales. However, the constructs of anxiety and depression could not be easily distinguished from each other. Consequently, the W-BQ12 was designed to include just three subscales, Negative Well-being (including only negatively-worded anxiety and depression items), Energy (2 positively- and 2 negativelyworded items) and Positive Well-being (all positively-worded items). The SF-36 (Ware & Sherbourne, 1983), a widely used health status measure, includes a 4-item vitality subscale (2 positively- and 2 negatively-worded items) and a 5-item mental health scale (2 positively worded and 3 negatively-worded items).

Method: Factor structures of W-BQ22, W-BQ12 and SF-36 were compared using data from 789 outpatients with diabetes.

Results: W-BQ22 factor analysis showed negatively-worded anxiety and depression items loading together, while positively-worded depression items loaded with positive well-being items and separately from positively-worded anxiety items. W-BQ12 loaded as intended on 3 factors, with negatively-worded anxiety and depression items loading together on one factor: negative well-being. The four energy items (2 positively- and 2 negatively-worded) loaded together (factor 3) and the four positive well-being items loaded together (factor 1). Unforced factor analysis of the SF-36 produced 5 factors and split the mental health and vitality items into two components, which could only be defined in terms of positive and negative wording. A forced 8-factor solution produced similar results, with the mental health and vitality items being split into two components according to their positive or negative wording. A forced 2-factor solution brought mental health/vitality items together, separate from physical health items.

Conclusion: The previously unrecognised influence of positive and negative wording on factor structure is clearly shown here to be of importance in conceptualising and designing measures of psychological well-being to be used with people with diabetes and may be of relevance for other populations.

Transforming the SF-36 to account for death in longitudinal studies with three-year follow-up

BACKGROUND: Analyses of longitudinal health-related quality of life data often exclude participants who die, which limits the generalizability of the results. Methods to incorporate death as a valid score in the Medical Outcomes Study Short-Form (SF-36) have been suggested but need to be evaluated in other populations. OBJECTIVES: We sought to apply a method of transforming the SF-36 Physical Component Score (PCS) to include death. A transformation to estimate the probability of being "healthy" in 3 years, based on the current PCS value, will be developed and validated. SUBJECTS: Women in the Australian Longitudinal Study on Women's Health (ALSWH), ages 70-75 years at Survey 1 in 1996 (n = 12,432), were followed-up at 3 yearly intervals for 6 years. RESULTS: The transformation derived from the ALSWH data provides evidence that the methodology for transforming the PCS to account for deaths is sound. The 3-year equation provided good estimates of the probability of being healthy in 3 years and the method allowed deaths to be included in an analysis of changes in health over time. CONCLUSIONS: For longitudinal studies involving the SF-36 in which subjects have died, we support the recommendation that both the PCS and its transformed value which includes deaths should be analyzed to examine the influence of deaths on the study conclusions. Using study data to derive empirical parameters for the transformations may be appropriate for studies with follow-up intervals of other lengths.