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International Journal for Quality in Health Care 15:337-344 (2003)
© 2003 International Society for Quality in Health Care

Paper

Interpersonal and organizational dimensions of patient satisfaction: the moderating effects of health status

MARGARET S. WESTAWAY1,, PAUL RHEEDER2, DANIE G. VAN ZYL3 and JOHN R. SEAGER1

1 Health and Development, SA Medical Research Council and School of Health Systems and Public Health, Faculty of Health Sciences, University of Pretoria, University of Pretoria, South Africa
2 Clinical Epidemiology Unit, Faculty of Health Sciences, University of Pretoria, South Africa
3 Kalafong Hospital, Faculty of Health Sciences, University of Pretoria, South Africa

Objectives. Based on Donabedian's structure, process, and outcome model, this study was conducted to identify the underlying dimensions of patient satisfaction for diabetic patients and determine the effects of demographic characteristics and health status on these dimensions.

Design. A cross-sectional analytical research design was used with a questionnaire, comprising demographic characteristics, the general and mental health items from the SF-20, and a 25-item patient satisfaction scale.

Setting and study participants. The questionnaire was administered to 263 South African black diabetic outpatients from the diabetic clinics at two hospitals. There were 174 females and 89 males, aged between 16 and 89 years (mean = 53.5, sd = 13.9). The average number of years of schooling was 6.3 (sd = 4.1).

Main outcome measure. A reliable and valid patient satisfaction scale.

Results. Factor analysis was conducted on the patient satisfaction scale and two factors, accounting for 71.6% of the variance, were extracted. The major items on Factor I were support, consideration, friendliness, and encouragement, labelled the interpersonal dimension. Factor II emphasized availability of a seat and toilet in the waiting area and cleanliness, labelled the organizational dimension. The two factors had very good reliability coefficients: 0.85 (organizational) and 0.98 (interpersonal). Multi-trait scaling showed that all items exceeded the item convergent (r>0.40) and discriminant (Z>1.96) validity criteria. Patients in poor general health were significantly less satisfied (P = 0.007) with the organizational quality of their care than patients in good health; patients in poor mental health were significantly less satisfied (P = 0.04) with the interpersonal quality of their care than patients in good mental health.

Conclusions. The findings provided support for Donabedian's model. They demonstrated that attributes of providers and settings are major components of patient satisfaction, and showed that the scale is a reliable and valid measure of patient satisfaction for this South African population.

Keywords: black diabetic patients, health status, interpersonal and organizational quality of care, patient satisfaction, South Africa

In South Africa, there is a paucity of reliable and valid satisfaction measures for specific populations. In addition, no local studies have investigated the relationship between the components of patient satisfaction and health status. In order to rectify this state of affairs, complement international research and provide a credible analysis of satisfaction findings [1], we developed and tested a patient satisfaction scale for diabetic outpatients. Based on Donabedian's [2] structure, process, and outcome model, this study was conducted to identify the underlying dimensions of patient satisfaction and determine the effects of demographic characteristics and health status on these dimensions.

Patient satisfaction is regarded as one of the desired outcomes of care, an element in health status, a measure of the quality of care, and ‘as indispensable to assessments of quality as to the design and management of health care systems’ [2, p. 1746]. It has been proposed that the effectiveness of health care is determined, to some degree, by satisfaction with the services provided [3–5]. Support for this viewpoint has been found in studies that have reported that a satisfied patient is more likely to utilize health services [6], comply with medical treatment [7], and continue with the health provider [8]. Various studies have shown that satisfaction is related to technical and interpersonal competence, more partnership building, more immediate and positive non-verbal behaviour, more social conversation, courtesy, consideration, clear communication and information, respectful treatment, frequency of contact, length of consultation, service availability, and waiting time [9–11].

Measurement of patient satisfaction fulfils three distinct functions: understanding patients' experiences of health care, identifying problems in health care, and evaluation of health care. Evaluation is regarded as the most important dimension [4]. Donabedian [2] has provided a model based on structure, process, and outcome for evaluating the quality of health care. Structure refers to the attributes of organizations delivering care and the conditions under which care is provided, process relates to the professional activities associated with providing care, and outcome denotes the effects of care. It is noteworthy that outcome includes health status, improvements in knowledge, changes in behaviour, and patient satisfaction with care [2, p. 1745]. Donabedian [2] regards satisfaction/dissatisfaction as a ‘patient's judgement on the quality of care in all its aspects, but particularly as concerns the interpersonal process’ (p. 1746). Implicit to Ware et al.'s definition of patient satisfaction as ‘a multi-dimensional concept, with dimensions that correspond to the major characteristics of providers and services’ [12, p. 262], is Donabedian's [2] interpersonal process and organizational attributes.

Ware et al. [12] argued that patient characteristics are the determinants of satisfaction, whereas interpersonal manner, technical quality, accessibility, cost, efficacy, continuity, the physical environment, and availability of resources are the components of satisfaction. Most studies on satisfaction have found that older patients report higher levels of satisfaction than younger patients [3,4,13–15]. In general, gender does not affect levels of satisfaction [4]. The evidence on the relationship between educational attainment and satisfaction is ambiguous. As expressed by Sitzia and Wood, ‘there is a notable lack of supportive evidence from the United Kingdom for this determinant, and it may be that other factors—such as income—are confounding the U.S. evidence’ [4, p. 1835].

Although age is related to satisfaction, this relationship is confounded by health status or health-related quality of life [13]. Whereas Williams and Calnan [14] found no significant relationship between health status and satisfaction in either primary or hospital care settings, Cohen [13] reported that pain and psychosocial health status, adjusting for age, was significantly related to lower satisfaction with health care. Cohen's findings suggest that patient satisfaction is susceptible to change in response to organizational, clinical, and interpersonal treatment.

Results from previous studies on the relationship between health status and patient satisfaction have found that patients in better health tend to report greater satisfaction with their health care than patients in poor health [16,17]. Some studies have shown that mental, but not physical, health status is associated with patient satisfaction [13,18]. In contrast, Da Costa et al. [19] found that general satisfaction was significantly related to both physical (r = 0.17, P<0.05) and mental (r = 0.20, P<0.01) health status. The research design used by Da Costa et al. [19] did not permit a causal inference on the direction of the relationship between health status and patient satisfaction. However, Hall et al. [20], using a longitudinal design, found evidence to support a unidirectional causal link between earlier self-reported health status and later patient satisfaction.

Although healthier patients are generally more satisfied with their care than less healthy patients, there is a lack of clarity on the relationship between health status and the various components of patient satisfaction. Identifying these relationships would assist in making more rational quality improvement strategies, thereby contributing to the increased effectiveness of health care.

Methods

Patients
All black diabetic patients attending the diabetic clinics at two hospitals for routine diabetes outpatient treatment were asked to participate in the study. Only 13 patients refused to participate in the study (a refusal rate of 5%), due to time constraints. The final consecutive sample comprised 263 patients. There were 174 females and 89 males aged between 16 and 89 years (mean = 53.5, sd = 13.9). Twenty three per cent had no formal schooling, 28% some primary level schooling, 38% some high school, and 11% had completed high school. The average number of years of schooling was 6.3 (sd = 4.1). Age was significantly related to schooling (r = –0.28, P = 0.01), indicating that older patients had limited educational opportunities. Fifty per cent were employed, usually in low-level occupations such as cleaning, making tea, and domestic work. Of those who were unemployed, 58% were supported by a pension.

Clinical information on HbA1c results, body mass index (BMI), and blood pressure (BP) was collected from the files by the medical practitioners. HbA1c results were available for 242 patients. Mean HbA1c was 10.2% (sd = 2.6), indicative of poor metabolic control. The mean BMI for 246 patients was 28.9 (sd = 5.8). Female patients were significantly more obese than male patients (P<0.001), similar to previous findings [21]. The average of three BP readings was used to establish BP control. BP control was defined as 130/85 (controlled systolic and diastolic). One hundred and fourteen patients (46%) had controlled BP. Patients with poor BP control were significantly older and more obese (P<0.001) than patients with good BP control.

Health status
Health status was measured by the general and mental health subscales from the 20-item abbreviation of the Rand Medical Outcomes Study (SF-20) [22]. Scores on the subscales were transformed linearly from 0 to 100, where 0 and 100 were assigned to the lowest and highest possible scores, respectively. The cut-off points designated by Stewart et al. [22] were used to define poor general and mental health: poor general health is a score of 70 or lower; for poor mental health the cut-off point is a score of 67 or lower. High scores denote better general and mental health [22]. Extensive reliability and validity data on the subscales are available [21–24]. In a recent South African study with black diabetic patients, reliability coefficients were 0.79 (mental health) and 0.81 (general health) [21], in the respectable range according to Arias and de Vos [25].

Patient satisfaction
In accordance with Sitzia's [1] recommendations, a 25-item patient satisfaction scale was constructed based on adaptations of previous measures, a review of the literature, and in-depth interviews with 20 patients. Twelve items measured provider characteristics (friendliness, encouragement, helpfulness, respect, consideration, support, listening skills, expectations, competence, information, and communication), and 13 items measured service characteristics (maintenance of contact, follow-up, equity, availability, waiting time, availability of a seat and toilet in the waiting area, cleanliness, privacy during consultation, thoroughness of examination, cost of attendance, medicine received, and convenience of the service). Each item was scored on a 5-point Likert scale, ranging from 1 (very dissatisfied) to 5 (very satisfied). Patients also rated their overall level of satisfaction with health care on a 10-point scale ranging from 1 (least satisfaction) to 10 (most satisfaction).

Data analysis
Descriptive statistics were the first step for data analysis. In accordance with Sitzia's [1] recommendations, factor analysis, reliability estimates (internal consistency), and multi-trait scaling were conducted on the patient satisfaction scale. Exploratory factor analysis was used to ascertain whether the underlying dimensions of patient satisfaction are interpersonal and organizational and to identify the most important dimension of patient satisfaction. A direct solution (principal components analysis) was the first step in analysing the 25-item scale [26]. Only items with communality estimates (common factor variance) >0.30 were taken into consideration, as items with unique variance (specific variance + error variance) >0.70 tend to be unreliable [27]. In order to ascertain significant loadings at the 1% level, loadings >0.50 were examined [26,27]. A forced orthogonal (VARIMAX) two-factor rotational solution was conducted to minimize the number of variables with high loadings on a factor and achieve simple structure [27].

The reliability (internal consistency) of the general health and mental health measures was assessed [28]; {alpha} coefficient of 0.70 was regarded as acceptable, between 0.71 and 0.80 as respectable, and >0.80 as very good [25,26]. Multi-trait scaling was used to test item convergent and discriminant validity of the patient satisfaction scale. This method tests whether each item in a hypothesized group is substantially related (r>0.40) to the total score computed from other items in that group (item convergent validity criterion) and whether each item correlates significantly higher with its hypothesized scale (Z>1.96) than with other scales (item discriminant validity criterion) [22].

t-tests, Pearson correlation coefficients, and one-way analysis of variance (ANOVA) were used to examine demographic effects and relationships among measures. Multiple regression was used to determine the predictors of overall satisfaction with the quality of health care. Multiple analyses of co-variance (MANCOVAs), with Bonferroni t-tests for multiple comparisons, were used to tease out general and mental health group effects on patient satisfaction.

Results

Health status
The average score on the general health subscale was 53.3 (sd = 37.7) and on the mental health subscale was 75.8 (sd = 24.0). According to Stewart et al. [24], predicted scores for diabetic patients are 59.8 for general health and 77.7 for mental health, slightly higher than was found in this study. Fifty per cent of the patients were in the poor general health category (score<=70) and 28% were in the poor mental health category (score<=67), comparable to the patient samples in the Medical Outcomes study [22]. General health and mental health were significantly related (r = 0.34, P<0.01). The two subscales had very good reliability coefficients [25], with {alpha} coefficients of 0.88 (mental health) and 0.95 (general health), very similar to previous findings with American patients [22]. As was found previously [21], older patients and those who were unemployed had significantly poorer general health than younger patients and those who were employed (P = 0.01). Mental health was significantly related to HbA1c results (r = -0.15, P = 0.02), suggesting that patients with good mental health have better metabolic control than patients in poor mental health.

Patient satisfaction
The sample size of 263 patients fulfilled Nunnally's minimum criterion for factor analysis of the patient satisfaction scale (10 persons per item) [26]. Principal components analysis, followed by a forced two factor rotational solution, was conducted on the 25 items. Six items were removed from the scale (communication understandable, availability, thoroughness of examination, cost of attendance, medicine received and convenience of the service) due to their inadequate loadings [26]. A second forced two factor solution was conducted on the remaining 19 items (Table 1). All communality estimates exceeded the criterion of 0.30 [27] and ranged between 0.43 (privacy) and 0.91 (consideration). The Kaiser–Meyer–Olkin measure of sampling adequacy of the number of items was 0.92, in the marvellous range according to Kaiser [29], and confirmed that factor analysis was the correct procedure for the data. In addition, this measure of item sampling adequacy fulfilled Sitzia's [1] requirement for content validity.


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  		Table 1 Orthogonal (VARIMAX) two-factor rotational solution for patient satisfaction

 
The total variance extracted was 71.6%, with Factor I accounting for 45.8% and Factor II accounting for 25.8% of the variance. Factor I contained 11 significant loadings (>0.50). The major items were: providers who let me talk (0.91) providers who listen to me (0.90), supportive providers (0.89), considerate providers (0.89), friendly providers (0.86), helpful providers (0.86), and encouraging providers (0.85) (Table 1). Factor I seems to represent a combination of empathy and two-way communication, and was interpreted as the interpersonal dimension of patient satisfaction. Factor II contained eight significant loadings. The most important items were: availability of a seat in the waiting area (0.73), availability of a toilet in the waiting area (0.70), and cleanliness (0.70). These findings suggested that Factor II was related to service characteristics and was interpreted as the organizational dimension of patient satisfaction.

To assess the validity of the subscales, the items measuring interpersonal and organizational constructs were further factor analysed [30]. In each case, the items always loaded on one factor only, lending support to their validity. The two factors were significantly related (r = 0.72, P<0.001). However, the correlation was significantly lower (Z<1.96) than each subscale's {alpha} coefficient, providing support for discriminant validity [31].

Mean scores, standard deviations, corrected item-total correlation coefficients, and Z scores for each of the 19 items are shown in Table 2. Responses to the items were positively skewed, indicating high levels of satisfaction. Corrected item–total correlation coefficients for the interpersonal dimension ranged between 0.81 and 0.95; these coefficients ranged between 0.54 and 0.70 for the organizational dimension. All coefficients exceeded the convergent validity criterion of>0.40 [22]. All items correlated significantly higher with their own subscale than the other subscale, exceeding the discriminant validity criterion (Z>1.96).


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  		Table 2 Mean scores, sds, corrected item–total correlation coefficients, and Z scores for the two dimensions of patient satisfaction

 
Scores on each of the subscales were transformed linearly from 0 to 100, where 0 and 100 were assigned to the lowest and highest possible scores, respectively [22]. Mean scores, sds, range, reliability coefficients, and Z scores for the two subscales are shown in Table 3. The reliability coefficients were excellent, being 0.98 (interpersonal) and 0.85 (organizational) [25]. Although the two patient satisfaction subscales were significantly related (r = 0.72, P<0.001), Z scores showed that this correlation coefficient was significantly lower than each scale's {alpha} coefficient. The interpersonal subscale was significantly related to mental health (r = 0.15, P = 0.02), whereas the organizational subscale was significantly related to both mental (r = 0.18, P = 0.003) and general (r = 0.15, P = 0.02) health.


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  		Table 3 Mean scores, sds, range, reliability coefficients, and Z scores on the two patient satisfaction subscales

 
The average overall satisfaction score was 6.6 (sd = 3.6), with a rating of 1 for 18% of the patients and 10 for 41% of the patients. Overall satisfaction was significantly related to age (r = 0.17, P = 0.005), similar to previous findings [3,4,13–15], mental health (r = 0.16, P = 0.008), and the interpersonal dimension (r = 0.16, P = 0.009). The two factors were regressed on overall satisfaction and the standardized ß coefficient for only the interpersonal factor was significant (P = 0.02), suggesting that interpersonal relationships were more important for patient satisfaction than organizational attributes [2].

Neither of the two patient satisfaction subscales was significantly related to age, gender, marital status, education, or employment status (P>0.05). The interpersonal and organizational dimensions were not related to HbA1c results, BMI, or BP control (P>0.05), suggesting that satisfaction, in comparison with metabolic control, weight control, and BP control, is an independent rather than a related outcome.

MANCOVAs showed that the adjusted mean scores for the poor general health group (controlling for mental health) were significantly lower on the organizational dimension of patient satisfaction (P = 0.007). The adjusted mean scores for the poor mental health group (controlling for general health) were significantly lower on the interpersonal dimension of patient satisfaction (P = 0.04) (Table 4). These findings suggest that patients in poor general health are less satisfied with the organizational quality of their care than patients in good general health; in contrast, patients in poor mental health are less satisfied with the interpersonal quality of their care than patients in good mental health.


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  		Table 4 Adjusted mean scores and F tests for the moderating effects of general health and mental health on patient satisfaction

 
Discussion

Irrespective of country setting (developed or developing), the highest levels of dissatisfaction are with waiting times [30,32–37], as was found in the current study. An overwhelming majority (76%) of the South African black population rely on public hospitals or clinics for their health care [38]. These facilities are overcrowded, understaffed, and under-resourced, contributing to waiting times of 1 hour or more to see a health provider [38]. Although the diabetic clinics at these hospitals are separate from other public health services, all patients make use of the same pharmacy for their treatment. It would appear that the pharmacy is creating bottlenecks to patient flow and increasing waiting time.

Additional dissatisfaction issues in developing countries are maintenance of contact, follow-up, equity or fairness, privacy, and cleanliness [32,33,36,37]. In the present study, most patients were very satisfied with maintenance of contact (73%), follow-up (69%), fairness (69%), privacy (74%), and cleanliness (68%). It would appear that these diabetic clinics provide better services for their patients than other public health services in South Africa, Bangladesh, Saudi Arabia, or Indonesia [32,33,36,37].

The multi-dimensionality of patient satisfaction [12] received support in a hospital study on service quality and patient satisfaction in Bangladesh [30]. Five service quality factors, accounting for 69% of the variance, were extracted and labelled responsiveness (caring, helpful, courteous), assurance (skilled staff, competence), communication (explanation of tests, answering questions), discipline (cleanliness of the facility and staff), and baksheesh (no services without tips) [30]. All five factors had very good reliability coefficients (>0.85) and significantly explained 63% of the variance in patient satisfaction [30].

Discipline (cleanliness) and assurance (competence) had the greatest impact on patient satisfaction, justified in a developing country context, where poor management, professional demeanour, and performance have been severely criticized [30]. The ß coefficient for the responsiveness dimension showed that interpersonal relationships were not as important for patient satisfaction as cleanliness and competence. In contrast to these findings, courtesy and respect, regarded as the interpersonal dimension of satisfaction [2,4], were the most powerful predictors of patient satisfaction in a study from rural Bangladesh [32]. In a recent South African study [33], satisfaction with family planning services was based on friendliness, encouragement, communication, and competence. Both these studies provided additional evidence for the importance of Donabedian's [2] interpersonal process.

In contrast with Andaleeb's [30] findings, factor analysis of this patient satisfaction scale provided preliminary evidence concerning the bi-dimensionality of patient satisfaction. In the present study, two factors accounting for 71.6% of the variance were extracted. The first factor accounted for most of the variance (45.8%) and was labelled the interpersonal dimension, due to high loadings on traditional aspects (support, consideration, friendliness, and helpfulness), along with the less traditional aspects of communication and competence [33]. The second factor was labelled the organizational dimension, due to high loadings on the amenities of care (availability of a seat and toilet in the waiting area and cleanliness), and more modest loadings on the attributes of care (privacy, fairness, and waiting time). These findings demonstrated the importance of assessing satisfaction ‘with specific attributes of the interpersonal relationship’ [2, p. 1746], along with the attributes of the settings in which care occurs [2].

The reliability (internal consistency) coefficients for the two patient satisfaction dimensions were very good [25,26], and satisfied Sitzia's [1] requirement for credible research. In addition, content validity was established through the Kaiser–Meyer–Olkin measure of item sampling adequacy. Preliminary evidence on construct validity [1] was provided by the multi-trait item scaling analyses [22], one-factor solutions for each of the subscales and the significantly lower correlation between the subscales than each scale's {alpha} coefficient [31].

The regression analysis of the two factors on overall satisfaction showed that only the standardized ß coefficient for the interpersonal dimension was significant, suggesting that the interpersonal dimension was more important than the organizational dimension for patient satisfaction. The modest relationship between the interpersonal dimension and overall satisfaction indicated that the two subscales were measuring specific aspects of patient satisfaction rather than a general tendency to be satisfied [39]. Older patients were more satisfied with the overall quality of their care than younger patients [3,4,13–15]. However, neither of the patient satisfaction dimensions was related to age or any other patient characteristics. This lack of demographic effects contributed to a low source of error [1], and showed that these subscales hold particular promise for assessing satisfaction with the quality of health care from a patient perspective in diverse populations and settings.

The inter-correlations among the patient satisfaction subscales, general health, and mental health were modest in size, but similar to those reported by Da Costa et al. [19]. However, these relationships tend to support the effects of mental rather than general health on patient satisfaction [13,18]. Patients in poor general health tended to be less satisfied with the organizational aspects of their care than patients in good health. In contrast, patients in poor mental health tended to be less satisfied with the interpersonal aspect of their care than patients in good mental health. These results substantiated Cohen's [13] findings on the moderating effects of health status on patient satisfaction. In addition, the findings suggested that sicker patients require more concrete organizational support, whereas less emotionally adjusted patients require more emotional support from their health care providers [15]. Therefore, measurement of health-related quality of life is concomitant with assessments of satisfaction with the quality of care.

Conclusions
The current study and a previous South African study, with very different study participants, found that patient satisfaction was a bi-dimensional construct, with an emphasis on interpersonal relationships and organizational characteristics. These findings do not negate other authors' conceptualization of the multi-dimensionality of patient satisfaction, but enhance the richness of care provider and setting characteristics. Links between empathy, communication, information, and competence are not unusual in real life, where borders are often fuzzy and indeterminate. How many of us would like our health care encounter to be with warm, caring people rather than abrupt, hardhearted people? It is not surprising then that these diabetic patients equated empathy with communication. Of even more importance to health care providers is that empathy is perceived as going hand-in-hand with competence. This finding should provide encouragement to overworked providers in South African public health facilities and motivation to develop empathetic relationships with their patients.

Amenities and attributes of care were central to the organizational dimension of patient satisfaction. Given lengthy waiting times in South Africa's public health facilities, it is not surprising that the availability of a seat and toilet in the waiting area featured so prominently. Cleanliness, maintenance of contact, and follow-up service were also perceived as important satisfaction areas. As cleanliness is a major problem in all South African health facilities, and in other developing countries, this focus on cleanliness was to be expected. Maintenance of contact and follow-up are particularly important to diabetic patients, given the complex demands of diabetes mellitus management and the long-term consequences of poor BP and metabolic control.

The reliability and validity analyses showed that the two patient satisfaction subscales were measuring the most important aspects of patient satisfaction. The significant role of empathy in patient–provider interactions was further emphasized by its importance to overall satisfaction and patients in poor mental health.

In conclusion, the findings provided support for Donabedian's structure, process, and outcome model, demonstrated that attributes of providers and settings in which care occurs are major components of patient satisfaction, and showed that the scale was a reliable and valid measure of patient satisfaction for this South African population.

We wish to thank the patients for participating in the study; Drs Elaine Pretorius and Katherine Kroeger for assistance with patient recruitment and recording clinical information; the interviewers for their commitment to the patients and the study; Nurse Golele for data coding, capture and cleaning; Piet Becker for statistical advice; the Hospital Superintendents and staff for supporting the study; and Health Systems Trust for their grant support.

Address reprint requests to M. S. Westaway, Health and Development, SA Medical Research Council, Private Bag X385, Pretoria 0001, South Africa. E-mail: mwestawa{at}mrc.ac.za Back

Accepted for publication March 7, 2003.

References

  1. Sitzia J. How valid and reliable are patient satisfaction data? An analysis of 195 studies. Int J Qual Health Care 1999; 11: 319–328.[Abstract/Free Full Text]

  2. Donabedian A. The quality of care: how can it be assessed? J Am Med Assoc 1988; 260: 1743–1748.[Abstract]

  3. Carr-Hill RA. The measurement of patient satisfaction. J Public Health Med 1992; 14: 236–249.[Abstract/Free Full Text]

  4. Sitzia J, Wood N. Patient satisfaction: a review of issues and concepts. Soc Sci Med 1997; 45: 1829–1843.[CrossRef][ISI][Medline]

  5. Fitzpatrick R. Surveys of patient satisfaction: I—Important general considerations. Brit Med J 1991; 302: 887–889.[ISI][Medline]

  6. Larsen DE, Rootman R. Physicians' role performance and patient satisfaction. Soc Sci Med 1976; 10: 29–32.

  7. Kincey JA, Bradshaw PW, Ley P. Patient satisfaction and reported acceptance of advice in general practice. J R Coll Gen Pract 1975; 25: 558–566.[Medline]

  8. Baker R. Development of a questionnaire to assess patients' satisfaction with consultants in general practice. Brit J Gen Pract 1990; 40: 487–490.

  9. Hall JA, Roter DL, Katz NR. Meta-analysis of correlates of provider behavior in medical encounters. Med Care 1988; 26: 657–675.[ISI][Medline]

  10. Singh H, Mustapha N, Haqq ED. Patient satisfaction at health centres in Trinidad and Tobago. Public Health 1996; 110: 251–255.[CrossRef][ISI][Medline]

  11. Sikosana PL. An evaluation of the quality of antenatal care at rural health centres in Matabeleland North Province. Central Afr J Med 1994; 40: 268–272.[Medline]

  12. Ware JE, Snyder MK, Wright WR, Davies AR. Defining and measuring patient satisfaction with medical care. Eval Prog Plan 1983; 6: 247–263.[CrossRef][Medline]

  13. Cohen G. Age and health status in a patient satisfaction survey. Soc Sci Med 1996; 42: 1085–1093.[CrossRef][ISI][Medline]

  14. Williams SJ, Calnan M. Convergence and divergence: assessing criteria of consumer satisfaction across general practice, dental, and hospital care settings. Soc Sci Med 1991; 33: 707–716.[CrossRef][ISI][Medline]

  15. Rahmqvist M. Patient satisfaction in relation to age, health status and other background factors: a model for comparisons of care units. Int J Qual Health Care 2001; 13: 385–390.[Abstract/Free Full Text]

  16. Patrick DL, Scriven E, Charlton JRH. Disability and patient satisfaction with medical care. Med Care 1983; 21: 1062–1075.[CrossRef][ISI][Medline]

  17. Hall JA, Feldstein M, Fretwell MD, Rowe JW, Epstein AM. Older patients' health status and satisfaction with medical care in an HMO population. Med Care 1990; 28: 261–270.[CrossRef][ISI][Medline]

  18. Marshall GN, Hays RD, Mazel R. Health status and satisfaction with health care: results from the Medical Outcomes study. J Consult Clin Psychol 1996; 64: 380–390.[CrossRef][ISI][Medline]

  19. Da Costa D, Clarke AE, Dobkin PL et al. The relationship between health status, social support and satisfaction with medical care among patients with systemic lupus erythematosus. Int J Qual Health Care 1999; 11: 201–207.[Abstract/Free Full Text]

  20. Hall JA, Milburn MA, Epstein AM. A causal model of health status and satisfaction with medical care. Med Care 1993; 31: 84–94.[CrossRef][ISI][Medline]

  21. Westaway MS, Viljoen E, Rheeder P. Does blood glucose control affect the health-related quality of life (HRQOL) of urban black South African type 2 diabetes mellitus patients? Diabetes Res 1999; 34: 209–217.

  22. Stewart AL, Hays RD, Ware JE. The MOS Short-Form General Health Survey: reliability and validity in a patient population. Med Care 1988; 26: 724–735.[ISI][Medline]

  23. McDowell I, Newell C. Measuring Health: A Guide to Rating Scales and Questionnaires. 2nd ed. Oxford: Oxford University Press, 1996, pp. 456–460.

  24. Stewart AL, Greenfield S, Hays RD et al. Functional status and well-being of patients with chronic conditions: results from the Medical Outcomes study. J Am Med Assoc 1989; 262: 907–913.[Abstract]

  25. Arias E, de Vos S. Using housing items to indicate socioeconomic status: Latin America. Soc Indic Res 1996; 38: 53–80.

  26. Nunnally JC. Psychometric Theory. 2nd ed. New York: McGraw-Hill, 1978.

  27. Child D. The Essentials of Factor Analysis. London: Holt, Rinehart & Winston, 1970, pp. 36–38.

  28. Cronbach LJ. Essentials of Psychological Testing. 3rd ed. New York: Harper & Row, 1970, pp. 160–161.

  29. Kaiser HF. An index of factorial simplicity. Psychometrika 1974; 39: 31–36.[CrossRef]

  30. Andaleeb SS. Service quality perceptions and patient satisfaction: a study of hospitals in developing countries. Soc Sci Med 2001; 52: 1359–1370.[CrossRef][ISI][Medline]

  31. Gaski JF, Nevin JR. The differential effects of exercised and unexercised power sources in a marketing channel. J Marketing Res 1985; 22: 130–142.[CrossRef]

  32. Aldana JM, Piechulek H, Al-Sabir A. Client satisfaction and quality of health care in rural Bangladesh. Bull World Health Org 2001; 79: 512–517.[ISI][Medline]

  33. Westaway MS, Viljoen E, Chabalala HP. Satisfaction with family planning services: interpersonal and organisational dimensions. Curationis 1998; 21: 3–7.[Medline]

  34. Kojo-Austin H, Malin M, Hemminki E. Women's satisfaction with maternity health care services in Finland. Soc Sci Med 1993; 37: 633–638.[CrossRef][ISI][Medline]

  35. Kersnik J. An evaluation of patient satisfaction with family practice care in Slovenia. Int J Qual Health Care 2000; 12: 143–147.[Abstract/Free Full Text]

  36. Mansour AA, Al-Osimy M. A study of health centers in Saudi Arabia. Int J Nurs Stud 1996; 33: 309–315.[CrossRef][ISI][Medline]

  37. Bernhart MH, Wiadnyana IGP, Wihardjo H, Pohan I. Patient satisfaction in developing countries. Soc Sci Med 1999; 48: 989–996.[CrossRef][ISI][Medline]

  38. The Community Agency for Social Enquiry (CASE). A National Household Survey of Health Inequalities in South Africa. Washington: The Henry J. Kaiser Family Foundation, 1995.

  39. Etter J, Perneger TV. Validating a satisfaction questionnaire using multiple approaches: a case study. Soc Sci Med 1997; 45: 879–885.[CrossRef][ISI][Medline]


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