The authors have declared that no competing interests exist.
Conceived and designed the experiments: JMF MICG GRM TGG FJPR JDB MBL AIGL. Performed the experiments: JMF GRM GAC TGG EPC FJPR MBL METB JFCL OAA MTSB. Analyzed the data: JMF MICG GAC JZ EPC. Wrote the paper: JMF MICG. Revised and approved the manuscript: GRM GAC JZ TGG EPC FJPR JDB AIGL MBL METB JFCL OAA MTSB.
Identifying the economic value assigned by users to a particular health service is of principal interest in planning the service. The aim of this study was to evaluate the perception of economic value of nursing consultation in primary care (PC) by its users.
Economic study using contingent valuation methodology. A total of 662 users of nursing consultation from 23 health centers were included. Data on demographic and socioeconomic characteristics, health needs, pattern of usage, and satisfaction with provided service were compiled. The validity of the response was evaluated by an explanatory mixed-effects multilevel model in order to assess the factors associated with the response according to the welfare theory. Response reliability was also evaluated. Subjects included in the study indicated an average Willingness to Pay (WTP) of €14.4 (CI 95%: €13.2–15.5; median €10) and an average Willingness to Accept [Compensation] (WTA) of €20.9 (CI 95%: €19.6–22.2; median €20). Average area income, personal income, consultation duration, home visit, and education level correlated with greater WTP. Women and older subjects showed lower WTP. Fixed parameters explained 8.41% of the residual variability, and response clustering in different health centers explained 4–6% of the total variability. The influence of income on WTP was different in each center. The responses for WTP and WTA in a subgroup of subjects were consistent when reassessed after 2 weeks (intraclass correlation coefficients 0.952 and 0.893, respectively).
The economic value of nursing services provided within PC in a public health system is clearly perceived by its user. The perception of this value is influenced by socioeconomic and demographic characteristics of the subjects and their environment, and by the unique characteristics of the evaluated service. The method of contingent valuation is useful for making explicit this perception of value of health services.
Definition of health policies must be accompanied by the knowledge of the preferences of the citizens who will benefit from them, since this has been shown to be related to efficiency and quality of health care
The opinions expressed by users of health systems about their preferences can be studied from several perspectives. One way of approaching the problem, which provides comparable results with expressed preferences for services or goods of different nature, is to study the perception of economic value. Specific methodologies exist to study the economic value of non-market goods, such as Contingent Valuation (CV). The CV method, which is based on economic theory and was developed into cost-benefit analysis (CBA), attempts to simulate a hypothetical market by surveying consumers with questionnaires. The objective of the questionnaire is to build a hypothetical scenario where interviewed subjects represent the demand and the interviewer plays the role of supply. In comparison with other evaluation techniques, such as cost-effectiveness analysis, and similarly to cost-benefit analysis, the CV method, has the advantage that benefits for a program or service can be compared directly with costs because they are both in monetary units. The CV method assumes that preferences of individuals can be interpreted in the form of a utility function, where two states (initial and final) can be compared in terms of the changes of the utility function. If people apply their preferences under a social point of view, we could estimate the social welfare function defined by the sum of individual perceptions. The CV method is particularly appropriate when valuing health care because of its ability to include both use and non-use values, that is, the value derived from considering the service as a commodity and the value as a public good
The perception of a value of a service can be studied for the whole service or for the elements that comprise it. The basic care pillar in PC is the Basic Care Unit, also called Family Care Unit, composed of a family physician and a family or community nurse. It is known that, in our setting, users of family medical care consultation perceive an economic value for the service, despite the lack of a direct payment at the moment of using it, called “price signal”
In this work, we intended to evaluate the perception of economic value expressed by users of nursing services in PC, the validity of the measured parameters by assessing their agreement with the economic theory of welfare, and their reliability. The validity of the results was also studied within the context of this theoretical framework
This study employed economic valuation, using the Contingent Valuation (CV) method to estimate Willingness to Pay (WTP) and Willingness to Accept [Compensation] (WTA) for the health care service received during primary care (PC) nursing consultations, within the public health system of the Community of Madrid.
The criteria of inclusion were: 18 years of age or older, properly understanding Spanish, previous experiences in goods exchange within market conditions in order to be able to understand the posed scenarios, and written consent to be interviewed. The criteria of exclusion were: not understanding the language, not being qualified to give consent, or not understanding the purpose of the questionnaire.
The centers were selected in the Community of Madrid. This is one of the seventeen autonomous communities (regions) of Spain. It is located in the middle of the country and it is a community with only one province. Its capital is the city of Madrid, which is also the national capital of Spain. It has a population of 6,369,167 (2011), more than 80% concentrated in the city of Madrid and its metropolitan area. The selection of the health centers was carried out so that both rural and urban environments were represented, as well as the upper and lower terciles of the income distribution in the Community of Madrid. Twenty-three centers were included, from 6 of the 7 areas in which PC of the CM is administratively divided. Of these, 6 centers were located in rural areas and 17 in urban areas (inside the city of Madrid, the capital, or its metropolitan area), 12 belonged to high-income areas and 11 to low-income areas. Within each center, systematic sampling of attendance records was used to select the subjects, obtaining 90% of patients from in-center consultations and 10% from home visits.
Sample size was calculated in order to estimate WTP and WTA parameters, so that the range of the confidence interval should not be more than 30% of the standard deviation (precision 15%), for a confidence limit of 95%. Using the standard formula for this calculation
The CV method requires individual questionnaires to estimate WTP and WTA. In all cases, the interview was performed at the time patients exited the nursing consultation by the same interviewer, previously trained and knowledgeable in the method, at a location within the health center but outside the care area. In the case of home visits, the interview was done over the telephone, a format previously tested and used in other studies
The monetary measure of the change in the communicated utility will refer to a compensatory variation framework of the classification proposed by O'Brien and Gafni (compensation required so that, following the change, the utility remains the same as before the change)
The format used for the payment was direct payment through a “payment card”, as it is assumed that this allows the user to behave as they would in a context where a product is sold at different prices
Answers were collected through a system of payment cards in 2 phases. The first card contained 3 possible values: less than €20, €20–40, and more than €40. The second payment card contained the following values: €0, €5, €10, €15, €20, €25, €30, €35, €40, €45, €50, €55, €60 and more than €60. The answer to the second payment card had to be consistent with the first answer. If an answer of €0 was stated, the patient was asked for the reason, using a multiple-answer question with 4 possible answers: “I cannot afford to pay for this service”, “I am not willing to pay for this service”, “I do not find this question to be pertinent”, and “Other reasons”. If the answer was “over €60”, the subject was asked to provide the exact value. The values of the first payment card were chosen after a pilot study of the questionnaire in a group of 19 health professionals and patients.
To be able to validate the answer given for the perceived value, variables grouped by characteristics of the health center, of the consultation, and of the patient were collected.
The health center characteristics depended on its urban or rural environment and on the available data regarding the area's average income, classified as upper and lower tercile (based on data from 2008, Statistics Institute, Community of Madrid). The characteristics of the consultation were: the place of assistance (in-center or home visit), type of service (preventive, chronic disease follow-up, care plans follow-up, or diagnostic and therapeutic procedures), time elapsed to obtain the appointment (same day, or 1, 2, 3, or >3 days), waiting time at the center prior to being attended (<15, 16–30, 31–60, or >60 minutes), perceived duration time of consultation (<1, 1–5, 6–10, 11–15, 16–30, or >30 minutes), and origin of consultation (patient initiated, self-appointment by the nurse, initiated by different nurse, initiated by other health professionals). Demographic and socioeconomic characteristics of the included patients were: age, sex, nationality, education level (illiterate, no education, primary education, secondary education, superior education), “social class” in a 6-category classification
With respect to health needs and utilization of health services, we studied the existence of chronic pathologies (those requiring continued health care for >6 months), hospital admissions during the previous year (including emergency room stays >24 hours), number of medical and nursing consultations during last year, and perception of health condition measured by EuroQol-5D. The results of EuroQol-5D were expressed in the visual scale and transformed into analog as proposed by Herdman et al.
To evaluate satisfaction with the provided service, a questionnaire validated in our setting was used to measure 3 dimensions: care provided by the health professional, consultation duration, and depth of the relationship with the health professional
Since WTP is subject to the patient's ability to pay, as has been shown in previous studies
The descriptive analysis was expressed by measures of central tendency and dispersion and by their 95% confidence intervals. Median and interquartile ranges were used in cases of asymmetric distributions.
Several explanatory models were built in which the dependent variable was the WTP, specifically represented by the smoothed function ln (WTP) (natural logarithm of WTP) due to its asymmetric distribution. Multilevel models were chosen as they allow studying aggregated data, evaluating not only the explanatory capacity of the variables, but also the influence of groups in the variability of the measures
The main independent variable chosen was the adjusted family income, as it can represent the ability to pay, while the rest of the variables were studied as covariables. This variable was used in the model in its “centered” form, that is to say, it was obtained by subtracting the mean from every value of the distribution
Three models were built. Model 1, termed “empty model”, was built without explanatory variables, and represented the variability of the answer, WTP, in the studied health centers. The second model included all the explanatory variables as fixed effects and the random effects, in order to assess the association of different variables with WTP and whether the mean of WTP was different in each center. The explanatory variables were introduced in the model in an attempt to maximize its explanatory capability and in accordance with the parsimony principle. The third model studied the variability of the slope of the main variable among different groups, that is, if the relationship between the adjusted family income and WTP were different in different centers.
STATA software version 12 was used for statistical analysis and Restricted Maximum Likelihood (REML) methods were employed to build the models.
To evaluate the reliability of the answers, the questionnaire was repeated on the telephone to 1 of every 5 subjects included in the study and the ICC was calculated (absolute agreement) for the initial and final measures of WTP and WTA.
The entire research process has been governed by the ethical principles contained in the Declaration of Helsinki (Sixth Revision, Seoul 2008). Included patients were asked for written consent to participate in the study. All the information was processed and subsequently stored in an anonymous way, accomplishing the requirements established in national legislation. The study relies on the favorable report by the Ethics Review Board of the Hospital Universitario Fundación Alcorcón, Madrid, Spain.
Seven hundred and fifty-seven subjects were asked to take part in this study, out of which 95 declined to participate (12.6% of total, CI 95%: 10.1–15.0%). The reasons for not participating were: lack of time (63), lack of interest in the study (12), other reasons (11), and no provided reason (9). The 95 subjects who declined to participate differed from the 662 subjects included in study only in the type of obtained consultation, which more frequently consisted of diagnostic and therapeutic procedures (78.7% of cases, CI 95%: 69.9–87.5%).
Mean (CI 95%) | Median (IQ range) | Percentages (CI 95%) | ||
65.4 (64.1−66.6) | 69 (55−78) | |||
60.7% (56.9−64.5%) | ||||
95.2% (93.5−96.9%) | ||||
16.3% (13.4−19.2%) | ||||
82.9% (79.9−85.9%) | ||||
65.6 (63.9−67.4) | 70 (50−80) | |||
0.68 (0.66−0.71) | 0.76 (0.48−1.00) | |||
16.6 (14.6−18.7) | 10 (5−16) | |||
29.2% (25.7−32.8%) | ||||
8.7 (8.6−8.9) | 10 (8−10) | |||
3.9% (2.4−5.5%) | ||||
24.5% (21.1−27.8%) | ||||
34.1% (30.5−37.8%) | ||||
23.4% (20.1−26.7%) | ||||
14.0% (11.3−16.7%) | ||||
9.1% (6.8−11.3%) | ||||
13.3% (10.6−16.0%) | ||||
26.3% (22.9−29.7%) | ||||
23.0% (19.7−26.2%) | ||||
11.3% (8.8−13.8%) | ||||
17.1% (14.1−20.0%) | ||||
0.873 (0.833−0.912) | 0.707 (0.600−1.000) |
CI 95%: Confidence interval 95%.
IQ Range: Interquartile range (25–75 percentile).
VAS-EuroQol-5D. Visual Analog Scale of EuroQol-5D questionnaire.
Family APGAR : Scores under seven point suggest dysfunctional family.
Adjusted by means of the Organisation for Economic Co-operation and Development (OECD), proposed methodology.
Percentages (CI95%) | Mean (CI 95%) | Median (IQ range) | |
12.5% (9.9−15.1%) | |||
21.3% (18.1−24.5%) | |||
2.6% (1.3−3.8%) | |||
63.6% (59.9−67.3%) | |||
24.3% (21.0−27.7%) | |||
65.4% (61.7−69.1%) | |||
0.5% (0.1−1.3%) | |||
9.8% (7.5−12.2%) | |||
81.3% (78.2−84.3%) | |||
6.3% (4.4−8.3%) | |||
4.8% (3.1−6.5%) | |||
1.8% (0.7−2.9%) | |||
5.7% (3.9−7.6%) | |||
84.9% (82.1−87.7%) | |||
12.1% (9.5−14.6%) | |||
2.65 (1.3−3.8%) | |||
0.5% (0.1−1.3%) | |||
0.6% (0.2−1.5%) | |||
18.1% (15.2−21.1%) | |||
42.4% (38.6−46.3%) | |||
23.0% (19.7−26.2%) | |||
12.5% (9.9−15.1%) | |||
3.3 (1.9−4.8%) | |||
13.3 (12.7−13.9) | 10.0 (10.0−15.0) | ||
4.89 (4.85−4.92) | 5.00 (5.00−5.00) | ||
4.76 (4.72−4.80) | 5.00 (4.75−5.00) | ||
4.48 (4.43−4.54) | 5.00 (4.00−5.00) | ||
3.34 (3.23−3.45) | 3.67 (2.33−4.67) |
CI 95%: Confidence interval 95%.
IQ Range: Interquantile range (percentile 25-percentile 75).
1 worst possible score, 5 best possible score.
Of the total of interviewed subjects, 81 people (12.2%) stated a WTP of €0. Out of these, 63 (77.8%) indicated inability to pay, 17 (21.0%) declared unwillingness to pay for the service, and 1 (1.2%) did not find the question to be pertinent. People expressing a WTP equal to €0 did not show any difference in the number of consultations or the perceived satisfaction, even though they had a lower adjusted family income (€−169.1, CI 95%: €−159.5 to −178.7). When asked about their WTA, 14 people (2.1%) did not provide any answer and 13 subjects (2.0%) gave an answer of €0. Of those who stated a WTP greater than €0, only 2 did not answer the question about WTA and other 2 gave it a €0 value.
Percentile 10 | Percentile 25 | Percentile 50 | Percentile 75 | Percentile 90 | Mean |
Mean |
|
0 | 5 | 10 | 20 | 30 | 14.4 (13.2−15.5) | 16.4 (16.4−17.7) | |
5 | 10 | 20 | 30 | 40 | 20.9 (19.6−22.2) | 21.3 (20.0−22.7) |
Including the 662 responses.
Excluding €0 values (581 DAP responses and 635 DAC responses).
The explanatory model was built using ln (WTP) as the dependent variable, so only those subjects stating a WTP higher than €0 were included. All 3 models described in the data analysis section are presented.
A variability of 6.56% in the value of ln (WTP) can be attributed to clustering by health center (model 1,
Model | Parameter | Coefficient | P value | CI 95% |
Constant | 2.509 | <0.001 | 2.412−2.606 | |
Constant | 2.328 | <0.001 | 1.986−2.669 | |
High-income | 0.198 | 0.019 | 0.033−0.363 | |
Home visit | 0.227 | 0.036 | 0.015−0.439 | |
Duration of consultation (min) | 0.011 | 0.020 | 0.002−0.020 | |
Relationship with health professional (1–5) | 0.057 | 0.008 | 0.015−0.099 | |
Age (years) | −0.007 | <0.001 | −0.011−−0.003 | |
Sex (female) | −0.188 | 0.002 | −0.305−−0.070 | |
Secondary or superior education | 0.183 | 0.012 | 0.040−0.326 | |
Centered adjusted family income (€1,000) | 0.127 | 0.038 | 0.007−0.246 | |
Constant | 2.233 | <0.001 | 1.991−2.674 | |
High-income | 0.194 | 0.022 | 0.028−0.360 | |
Home visit | 0.224 | 0.039 | 0.012−0.435 | |
Consultation duration (min) | 0.011 | 0.020 | 0.002−0.020 | |
Relationship with health professional (1–5) | 0.057 | 0.008 | 0.015−0.099 | |
Age (years) | −0.007 | <0.001 | −0.011−−0.003 | |
Sex (female) | −0.188 | 0.002 | −0.305−−0.070 | |
Secondary or superior education | 0.183 | 0.012 | 0.040−0.325 | |
Centered adjusted family income (€1,000) | 0.122 | 0.069 | −0.009−0.254 |
Deviance −632.7. Significance for the Chi2 test <0.001.
Deviance −618.5. Significance for the Chi2 test <0.001.
Deviance −618.3 Significance for the Chi2 test <0.001.
CI 95%: Confidence interval 95%.
Model | Parameter | Estimation | CI 95% | Sig. (Chi2) | ICC | |
Constant | Variance | 0.036 | 0.014−0.091 | <0.001 | 0.0656 | |
Residual | Variance | 0.511 | 0.454−0.575 | |||
Constant | Variance | 0.019 | 0.006−0.063 | 0.005 | 0.0396 | |
Residual | Variance | 0.468 | 0.415−0.527 | |||
Income dependent | Variance | 0.014 | 3×10−4−0.543 | 0.029 | ||
Constant | Variance | 0.020 | 0.006−0.064 | |||
Residual | Variance | 0.464 | 0.411−0.524 |
CI 95%: Confidence interval 95%.
Sig (Chi2): Significance for the Chi2 test.
ICC. Intraclass Correlation Coefficient.
After introducing fixed effects into the model, the variability of ln (WTP) attributed to clustering is 3.96% relative to 6.56% in the empty model. This further explains a residual variability of 8.41% (model 2,
When looking at the fixed effects, and taking into account that the response variable is ln (WTP), it can be inferred that living in high income areas increases WTP by a mean of 22% (CI 95%: 3–44%). With respect to the characteristics of the consultation: WTP for home visit consultation has a 25% higher mean (CI 95%: 2–55%), every increase of 10 minutes in consultation duration produces an 11% higher WTP (CI 95%: 2–22%), and every increase of one point on the satisfaction scale in the relationship with the health professional increases WTP by a mean of 6% (CI 95%: 2–10%). Women express a mean WTP that is 17% lower than men (CI 95%: −7 to −26%), and for every additional 10 years of age the WTP decreases by 7% (CI 95%: −3 to −11%). Subjects with a higher level of education show a 20% higher mean WTP (CI 95%: 4–39%). Finally, for every €1,000 of higher adjusted family income versus the mean, average WTP increases by 14% (CI 95%: 1–28%).
In order to describe the combined influence of the explanatory variables, if we compared the expected WTP for a female, 70 years of age, lacking education, attending a 10 minute consultation with a satisfaction score of 1 in the proposed scale, with an adjusted family income of €600, and who lives in a low income area, with the expected WTP for a male, 40 years of age, with superior education, home visited for 30 minutes, with a satisfaction score of 5 in the same scale, with an adjusted family income of €2,600, and from a high income area, the average expected WTP would be 5.5 times higher in the second case.
Finally, model 3 (
Previously, the existence of covariance between the mean WTP in each group and the slope of the income variable was hypothesized; however, this was ruled out (data not provided). The magnitude and significance of the response grouping are similar to those of model 2, confirming that the mean ln (WTP) is different in each group, and it is observed that the influence of family income changes in each group as well, since its slope varies from group to group (
To calculate the part of the variability due to clustering in model 3, we must fix specific values of the independent variable since the slope is different in every group. This way, considering mean values of family income, the model's ICC is 4.10%, similar to that of model 2. As for values far apart from the mean (percentiles 25 and 75 of the family income distribution, €600 and €1,000 respectively), the effect of the clustering is more marked, having an ICC value of 4.29% and 4.12% for an income of €600 and €1,000 respectively. Only in extreme values of family income (€1,000 above the mean), the variability due to grouping, measured by the model's ICC, approaches similar or higher values than those of the empty model (6.85%).
In order to estimate ICCs for the expressed WTP and WTA, we used 127 pairs of measures for WTP and 125 for WTA. The ICC of the answer for WTP was 0.952 (CI 95%: 0.932–0.966) and 0.893 for WTA (CI 95%: 0.850–0.924).
The presented data allow us to assure that the studied population has a clear perception of the economic value for the received service at the nursing consultation, despite the lack of explicit payment at the moment of use. This perception seems to depend on personal characteristics of the subject, characteristics of the consultation, and, to a certain degree, the characteristics of the environment where the consultation takes place. Finally, it seems that the expression of perceived value using CV methodology is reliable.
As for the value of the WTP, the perception seems to be quite realistic, having a reported mean of €14.4 (median €10), which represents 80% of the value established by the Community of Madrid when re-invoicing other entities for nursing consultation (€18 in 2009, ORDER 629/2009, of August 31st B.O.C.M. Num. 215, September 10th 2009). Although the expressed value outcomes of WTA are usually consistently higher than those of WTP
The characteristics explaining variations in the obtained answers are those expected a priori within the frame of the economic welfare theory. It was expected that subjects with higher payment ability and those who live in high-income neighbourhoods would show higher WTP. The role of financial capability as an explanatory factor of WTP was anticipated from the theoretical point of view
Out of the studied variables, educational level was chosen as the explanatory variable for the model, and not “social class”, because the correlation of the latter with available income data was greater than that of the educational level and prejudiced global explanative capacity by increasing the co-linearity. Moreover, social class by itself strongly correlates with WTP for the studied service, as has been observed in other studies
The negative correlation between female gender and age with WTP for health services and products has been referred to in the literature
Visit duration and location are the consultation characteristics that are related to WTP. This is consistent with the theoretical framework that the greater the quantity of product received, and under more favorable conditions for the user, the higher their WTP will be. The same can be said about satisfaction. It is expected that the greater the satisfaction the higher the WTP, as has been observed using the scale measuring satisfaction in the relationship with the health professional.
Variables found to not be explanatory are those related to rural/urban environment of the center, nationality, accessibility, and type of consultation. However, regarding accessibility, it must be pointed out that more than 80% of interviewed subjects obtained the appointment the day of requesting it and had a waiting time prior to being attended of <15 minutes.
The lack of association between some variables correlating to health needs and WTP are difficult to interpret. In the chosen model, there does not appear to be any correlation between the number of chronic pathologies, hospitalizations, or the perception of their own health condition as measured by EuroQol-5D, by subjects and their expressed WTP. This fact may be partially explained by the way need is measured in the health setting, by the high percentage of patients with “chronic conditions”, or by the higher probability of selecting patients having more frequent consultations. On the other hand, both measures of health related quality of life by EuroQol-5D and chronic conditions are well correlated with age and adjusted family income (inversely correlated). This situation could cause a collinearity problem, which could lack signification for these variables in the explanatory model.
Nevertheless, some indirect indicators of health need, such as the necessity for consultations to be held at home (patients with mobility issues), have been clearly associated with WTP.
The reliability of WTP and WTA expressions had largely not been studied in health care literature and there was little information about test-retest reliability
The limitations of this study are determined by the employed method. They have been correlated with the validity of the response and its reliability
Other biases such as the existence of a possible strategic bias, namely the one that leads to undervaluing a good when the subject believes the final price can get lowered, cannot be evaluated with certainty. This is becoming particularly relevant at the present time, when the co-payment of health services is a debated issue in the whole country. The percentage of zero value answers (12.2%) may be influenced by this fact, even though this percentage is similar or even inferior to that observed in literature when assessing WTP for health services
We find that these results have several implications for designing health policies. First, it is proven once again that the absence of payment at the moment of use does not make the user's perception of its value disappear. The recipient of public health services behaves as consumer choice theory predicts, valuing more, in economic terms, services taking more time, producing higher satisfaction, obtained under more pleasant circumstances, or implying a higher effort from the person providing it (such as home visit consultation). Income, level of education, age, and sex modify this perception of value, which has implications for populations that are predominantly female and in need of more care at an advanced age in life. On the other hand, there is a group of people who, although making use of the services and being as satisfied with them as the rest of users, feel they do not have the ability to pay at the moment of use, which could turn them into an excluded population in a different setting of service provision.
In addition, the perception of value is explained to a certain degree by the characteristics of the group of individuals enjoying them, and this influence is more important for extreme values of income distribution.
Both individual and inter-center variability should be of special interest for health organizations, since they would have to be taken into account for planning clinic and/or community interventions to a similar degree as when assigning resources. Knowing what determines the valuation users make of health services can also guide health managers in care-quality incentivisation policies, as the perception of value diminishes in identified groups.
Moreover, these differences in the expression of perceived value and how they adjust to economic theory can be considered a test of the usefulness of the CV method for eliciting preferences.
In conclusion, health services provided by the nurse in the framework of a public health system are perceived by the user as an element with real value in economic terms. The recipient of public health services behaves as a “rational” consumer, expressing different perceived values depending on the individual and environmental socioeconomic characteristics, on other personal characteristics, and on intrinsic attributes of the valued service.
The authors are grateful to nurses and patients from the following health centers: Almendrales, Cadalso de los Vidrios, Condes de Barcelona, Entrevías, Espronceda, Francia, Goya, Orcasitas, Orcasur, San Juan de la Cruz, San Martín de la Vega, Villanueva de la Cañada, Villaviciosa de Odón, Las Rozas de Madrid, Majadahonda, San Blas, San Fermín, Torrelodones, Villa del Prado, Alpedrete, Cobeña, Valdemorillo, and Villaconejos.