1. Introduction
The WHO describes a sustainable health system as a health system that ensures equitable access to essential medicines, vaccines, and technologies, while raising adequate funds for health to ensure that people can use needed services and are protected from financial catastrophe or impoverishment associated with having to pay for them.
To achieve the Sustainable Development Goals and deliver quality universal health coverage, health systems in low- and middle-income countries need more resources to be redesigned around the core elements of high-quality primary care. In addition, it is necessary to have data and information that allow continuous improvement [1,2,3,4,5,6]. Without health, there is no sustainable development. Healthy people are more likely to learn, work, and contribute positively to their economies and societies. Similarly, sustainable development will produce healthier individuals and families. A country’s sustainable development is based on energy, agriculture, health, labor, transportation, and housing. When these needs are met, it is possible to enter a virtuous circle that leads to positive indicators.
In the Americas region, care models have not consistently responded to the differentiated health needs of individuals and communities [7]. The Argentine health system is fragmented and segmented. It has three subsectors: private, social works, and public. The latter, of a federal nature, grants each province the power to define functions, infrastructure and competencies in the health area. In this context, primary health care (PHC) became one of the fundamental pillars for fulfilling the right to health. The public subsector of the city of Rosario is made up of effectors that depend on the provincial and municipal jurisdiction. Both networks extend throughout the territory and serve populations with similar characteristics, manifested in the coexistence of multiple institutions, both financially and in the provision of services, without forms of coordination that facilitate an adequate distribution of the different levels of care and avoid overlaps or lack of availability. The heterogeneity defines the existence of particular organizational norms, which suppose differences in the capture of resources, the forms of use, and the rights recognized by the population in charge.
Health systems around the world face different limitations in providing a high standard of care for their patients [8,9,10,11,12,13,14,15].
On the other hand, although PHC is stated as a strategy and goal in official documents, it is considered equivalent to the first level of care in practice. Likewise, its development is heterogeneous because the benefits of the first level, fundamentally sustained in the state subsector, depend mainly on the provincial or municipal governments in a federal country. The Ministry of Health of the Nation, which practically does not have direct effectors or authority to intervene in provincial health decisions, has tried to increase its stewardship capacity through spaces for inter-jurisdictional agreement and through the development of programs monitored in agreement with the provinces and municipalities, for which it provides resources. Effective primary care must guarantee first contact access, continuity, coordination of care, and comprehensiveness, which offers significant objectives for the policies and planning of primary care in low- and middle-income countries [16]. It is in primary health care where, after detecting risk factors in the population, an improvement in citizens’ health-related quality of life (HRQoL) can be produced, added to decompression of the demand on the public system, and promote self-care in health based on professional’s advice.
Health literacy empowers people and enables their participation in collective health promotion initiatives. Highly literate health decision-makers and investors contribute to their greater involvement in favor of health outcomes, co-benefits, and effective interventions for health determinants [17,18,19,20]. Disparities in access to care have been shown to exist between and within countries [21,22,23,24,25,26,27,28,29,30]. These disparities in access to primary care, in turn, contribute to health disparities, while improving access for vulnerable groups helps reduce gaps in health outcomes [31,32,33,34,35,36]. The demographic transition of the population towards a longer life expectancy, increasingly lower birth rates, and, added to the lower infant and general mortality rate [26,37,38], forces health services to set short- and long-term goals to deal with the impacts generated [36,39,40,41,42]. Moreover, air pollution impacts people and healthcare costs [43]. The increase in the prevalence of chronic noncommunicable diseases (CNCD) can be mentioned as one of the most important [44,45] due to inadequate nutrients and bioactive compounds intake [46,47,48]. In Argentina, there is a high prevalence of risk factors in its population to develop CNCD, added to their poor early detection, and they constitute the leading cause of death and disability [49]. The demographic transition of the population generates increasing amounts of NCDs that require treatment for long periods, within which medicalization emerges as one of the most critical actors [38]. Around 30% of health resources are allocated to the pharmaceutical industry, despite evidence of the irrational use of drugs [22,50,51,52,53]. This high expense within the health system that derives from excessive consumption or insufficient consumption forces policies so that the production of health in the population is not more expensive than necessary [54].
It is of great importance to consider the user’s perceptions through works that measure satisfaction to evaluate the results of the health care process and adapt the services that are provided accordingly, since this evaluation for organizations should be considered a priority [55]. The trust in the patient–professional relationship can directly influence well-being and satisfaction [56]. Trust, in turn, is directly related to the revisit intention, that is, to choose the same professional and the same organization to achieve well-being in health [57]. Loyalty is an essential indicator of the quality of care, but empirical evidence to support this claim is limited. In addition, patient loyalty is closely aligned with access and continuity in health care [58]. Therefore, evaluating patients’ satisfaction with their care is a valuable indicator of the quality of medical care [59]. An evaluation process is required to monitor processes within organizations to sustain good quality in the work of professionals. Patients’ subjectivity is the best way to do it [60].
Currently, no study evaluates the quality of care in primary health care centers in Rosario, Argentina. The research question formulated for the present work is: What is the influence of the quality of health services, through satisfaction and trust, on the revisit intention of patients who attend health programs in the city of Rosario? As a general objective of this work, it has been proposed to analyze the influence of the quality of health services to answer this question, through satisfaction and confidence, in the intention of revisiting patients who attend health programs in the city of Rosario. It is essential to understand the barriers and facilitators experienced by professionals and patients and how often they are experienced to support the development and implementation of health service models in primary care [21].
2. Theoretical Framework and Hypothesis
2.1. Quality → Satisfaction
Perceived quality is considered the antecedent of satisfaction and customer loyalty. Customers’ perceptions of service quality result from a comparison of their before-service expectations with their actual service experience. The effect of quality on customer satisfaction is a relation shown in many studies in different sectors, such as electronic banks [61] and healthcare facilities [62,63,64,65,66,67]. Based on this relationship, the following hypothesis is established.
The quality of health services has a positive effect on the satisfaction of patients who attend health programs in the city of Rosario.
2.2. Quality → Trust
Users demand more every day in terms of attention and service, and organizations make great efforts to provide the appropriate facilities for the development of a satisfactory experience with the brand. Trust is conceptualized as one party’s expectation of the other party’s motives and behaviors. Trust is directly influenced by what is received from the person or company providing the service or product. According to this relationship, quality’s effect on trust has been reported in previous studies [28,29,30,31]. The following hypothesis is accordingly proposed.
The quality of health services has a positive effect on the trust of patients who attend health programs in the city of Rosario.
2.3. Quality → Revisit (Repurchase)
The perceived quality of a product or service can generate in the user the intention to buy again, regardless of the effects that quality has on trust and satisfaction. The concept of intention to repurchase applies to products or services. In the case of health services, there is talk of revisit to explain the intention that the client/patient has the intention of returning to see the health professionals in the same healthcare facility. The effect of quality on trust has been described in previous research [68,69,70,71,72,73,74].
The quality of health services has a positive effect on the revisit intention of patients who attend health programs in the city of Rosario.
2.4. Satisfaction → Revisit (Repurchase)
Customer satisfaction is a prerequisite for creating and strengthening continuous company-customer relationships, aiming at increasing their loyalty to the same and even new services and products [75,76,77,78]. For that, companies must engage in offers that positively affect customer satisfaction to promote and achieve customer loyalty [79]. It is agreed that customer satisfaction can lead to customer loyalty. Customer loyalty is a deep commitment to repurchase a product or service repetitively in the future, even if external factors may influence the customers to shift from one provider to another [80]. The effect of satisfaction on repurchase was described in the literature [81,82,83].
Satisfaction has a positive effect on the revisit intention of patients who attend health programs in the city of Rosario.
2.5. Satisfaction → Trust
Satisfaction generates a sense of tranquility in the consumer why he knows that the payments he makes for the product offered by the company that generated the satisfaction can satisfy his expectations. This confidence that the consumer generates is dynamic since, although trust can be developed, it is expected that the service of the provided product or service is not significantly altered so that the trust does not vary. Some studies showed the relationship between satisfaction and trust [84,85,86,87].
Satisfaction has a positive effect on the trust of patients who attend health programs in the city of Rosario.
2.6. Trust → Revisit Intention
A consumer’s confidence gives the company the certainty of future repeat purchases, which is also valid for health services. Although it may be thought that the patient is forced without any chance to go to the healthcare facility as the only option this is not the case since, given the lack of satisfaction and confidence, they can decide not to be served anywhere. There is scientific evidence of the effect of trust on the intention to revisit [62,88,89]
Trust has a positive effect on the revisit intention of patients who attend health programs in the city of Rosario.
3. Methodology
3.1. Study Design
A correlational, cross-sectional, and non-experimental study has been carried out. The number of patients that ensure the detection of statistically significant differences with a margin of error of 5% and a confidence level of 95% was calculated to obtain a representative sample of the study population. A total of 431 completed questionnaires were obtained, of which 14 were excluded due to errors or omissions in the data, giving a total sample of 407 individuals. This calculation was performed in the online program OPENEPI. The subjects were systematically enrolled until achieving the calculated size to evaluate the quality of care.
3.2. Instrument
The evaluation instrument was a SERVPERF-type self-administered questionnaire with a 5-point Likert scale which is a questionnaire that initially asks for demographic information. This questionnaire was delivered physically in printed form to each research participant. The quality of care was measured considering four dimensions that make up this construct: quality of the use of health programs, patient satisfaction, patient trust, and intention to revisit the patient (Table 1). In addition, the following variables have been measured to determine the demographic profile and the frequency of chronic noncommunicable diseases and medicalization that the population studied presents: age, sex, educational level, marital status, occupation, history of pathologies, and use of medication.
3.3. Validity and Analysis
The statistical validity and reliability of the questionnaire were verified through (1) internal consistency (Cronbach’s alpha and composite reliability); (2) convergent validity (reliability of the indicator and the average variance extracted [AVE, for its acronym in English]); (3) the discriminant validity (Fornell–Larcker criterion) and cross loads between indicators and latent variables and the heterotrait–monotrait ratio (HTMT). In addition, discriminant validity was determined using the Fornell–Larcker criterion. Regarding the data analysis, to determine the population’s demographic profile, the information of each variable investigated was presented through tables and figures of their respective frequencies and percentages. To evaluate the perception of Healthcare Quality by patients who come to the health service, the SEM-PLS technique was applied. The novelty of the methodology is that the data have been evaluated using second-generation statistics through multivariate evaluation using partial least squares structural equation modeling (SEM-PLS) to calculate the correlation values between the study variables. This technique allowed to confirm the significance of a structural model of variables and the value of the correlation between variables. Using the SEM-PLS, reliability and statistical validity were evaluated by analyzing the results.
3.4. Ethical Considerations
The Provincial Bioethics Committee of the Ministry of Health of the Province of Santa Fe (R. P. 1153) and the Universidad Internacional Iberoamericana Ethics Committee (CR-125) approved this study.
4. Results
4.1. Demographic Data
The sample was composed of patients who attended public health system effectors located in the north, south, and west of the city of Rosario, Argentina. A total of 431 participants completed questionnaires, of which 24 were excluded due to errors or omissions in the data, giving a total sample of 407 individuals. The demographic data are shown in Table 2.
The information regarding the prevalence of chronic non-communicable (CNCD) is shown in Table 3.
Regarding the distribution of drug use frequencies, the results were as follows: NSAIDs n = 69; Metformin n = 59; Losartan n= 40; Enalapril n = 40; Other n = 38; Amlodipine n = 28; Levothyroxine n= 20. The following medications were grouped under the “other” label: Antiretrovirals, Levodopa, Levetiracetam, Omeprazole, Prednisone, Folic Acid, Fluticasone, Budesonide, Sulfamethoxazole, Hydrocortisone, Simvastatin. The methodology applied for analyzing the data and evaluating the direct and indirect routes that make up the determinants of the intention to revisit has been used successfully by various scientific studies found in the recent literature [58,82,83]. The present study evaluated the quality of care through a self-administered questionnaire, the most suggested methodology [82]. The validation process of the instrument by SEM-PLS included a reliability analysis of each item, the internal consistency of dimensions through composite reliability, analysis of the average variance extracted, and discriminant validity. The composite reliability coefficients of the subscales of each instrument were between 0.859 and 1.000 (Table 4). Thus, the instrument’s reliability can be confirmed according to the values reached in the subscales.
4.2. Discriminant Validity Using SEM-PLS
Discriminant validity was calculated using the Fornell–Larcker criterion, as shown in Table 5. In the first column, the square root of the extracted variance that appears at the top in parentheses must be greater than the correlations in the same column on subsequent lines of the same column.
Table 6 presents the model fit of the current research, showing SRMR, d_ULS, d_G, Chi-Square and NFI. A value less than 0.10 for SRMR is considered a good fit. For d_ULS, d_G, and Chi-square, a nonsignificant result for this test indicates good model fit. The values of NFI must be between 0 and 1 for a good fit.
It can be seen in Table 7 that all values are significant (p values < 0.01), except for the direct relationship between quality and intention to revisit (p = 0.821).
The indirect routes between the measured variables have been evaluated using the bootstrapping technique, obtaining statistically significant results (p < 0.05), as shown in Table 8.
Figure 1 shows the tested research model. The results confirm that satisfaction and trust influenced revisit intention, while quality did not directly influence revisit intention. In addition, quality directly influences satisfaction and trust, and in turn, satisfaction directly influences trust.
4.3. Test of Hypothesis
According to the analysis based in Table 8, quality has a significant and positive effect of 0.721 (p-value: 0.000) on satisfaction. Hypothesis 1 was accepted. Quality has a significant and positive effect of 0.246 (p-value: 0.000) on trust. Hypothesis 2 was accepted. Quality has neither a positive nor significant effect on revisit intention. Hypothesis 3 was not accepted. Satisfaction has a significant and positive effect of 0.239 (p-value: 0.001) on revisit intention. Hypothesis 4 was accepted. Satisfaction has a significant and positive effect of 0.679 (p-value: 0.000) on trust. Hypothesis 5 was accepted. Trust has a significant and positive effect of 0.533 (p-value:0.000) on revisit intention. Hypothesis 6 was accepted. The variables in the model explained 57.3% of revisit intention.
5. Discussion
In this study, 100% of the patients who were asked to complete the survey participated, which coincides with a study that evaluated the acceptance by patients to participate in this type of work, which found a high correlation, without influencing questions regarding the patient’s age, sex, and race, affirming that the interviewer’s treatment is usually kind and respectful [93]. The present study was conducted in various health institutions with geographical differences in the region. It is rare to find cross-sectional studies in the scientific literature on several institutions with the same methodology, which makes it difficult to make comparisons and identify areas for improvement and, in turn, causes an additional difficulty by making it impossible to identify and determine what users interpret as minimal care sizeable [94]. The SERVPERF methodology [95], selected for the questionnaire, has been widely validated in the scientific literature for its superiority compared to other similar scales, such as the SERVQUAL scale [96,97,98], confirmed by the creators of this scale, stating that perceived quality is directly related to the perceptions obtained [99]. The use and application of the SERVPERF method have been widely developed in Latin America, which affirms the conceptual power, internal flexibility, and external adaptability of this methodology to assess the quality of care in various health services and organizations, which add to its superiority methodological [100,101]. In addition, the SERVPERF has a high discriminant validity [102] and requires less application time [103], confirmed in the present study since the time required was an average of 6 min. The questionnaire instructions have been shown to have internal consistency through partial least squares structural equation modeling (PLS-SEM). In contrast, favorable results have been obtained when analyzing the discriminant validity of the subscales according to the Fornell–Larcker criterion.
It has been shown that social determinants in health, such as educational level, occupation, and issues related to socioeconomic status, have a direct impact on the perception of health [104], and therefore, health systems must be provided with high-quality to improve the well-being of the population in primary care. Demographic transition is due to people over 60 years of age having an increased burden of diseases, ailments, and functional limitations [105]. This average age obtained is in dissonance with the pronounced aging of the population and its greater use of health services, which is widely described in the literature, in which it can be found that health services are subject to a greater demand in this population.
The educational levels of the sample obtained in this study have been substantially low since 23.8% have completed secondary education and only 7.7% have completed higher education (tertiary and university). The knowledge of these demographic variables allows for characterizing the population. It can broaden the understanding of the problems related to the objective and subjective components that affect the quality of life-related to the patient’s health, guiding the actions taken to improve these aspects in the future [104].
A high prevalence of chronic noncommunicable diseases (CNCD) was found in the sample studied (40.3%). In South America, chronic diseases cause approximately 77% of deaths. In Argentina, chronic diseases account for 81% of deaths [106]. In this country, there is a high prevalence of risk factors in its population to develop CNCD, added to its poor early detection, making CNCD the leading cause of death and disability, representing 13% of potentially lost years of life and are associated with its time to a greater demand for resources from the health system [49].
Regarding the results obtained, the most frequent CNCD was hypertension, in line with most reports indicating that it is the most frequent in Argentina and causes 62% of cerebrovascular disorders and 49% of coronary diseases [107]. It would be important to develop strategies to act on the risk factors for developing hypertension, such as female sex, obesity, alcohol consumption, salt consumption, sedentary lifestyle, low socioeconomic level, and exposure to a state of constant stress. Secondly, diabetes could be found, which can be prevented through three types of strategies: primary (detect risk factors), secondary (once the risk factors are detected, prevent it from progressing or delay its process), and tertiary (prevent complications) [108].
Argentina has a medium–high incidence of cancer [109], but this type of health condition has not been reported in this study because interventions for this type of pathology mainly focus on applying high technologies to increase survival [110]. Within this context, it should be taken into account that there are a large number of risk factors that are transversal to all types of cancer: exposure to tobacco, alcohol consumption, potentially malignant lesions, metabolic syndrome [111], advanced age, hormonal imbalance changes, exposure to radiation, family history [112], changes in nutrition, lack of physical activity, excessive body weight [113], immunosuppression, and exposure to ultraviolet rays [114]. Therefore, primary health care is fundamental in providing prevention and holistic care to people to modify harmful habits [110].
Obesity is considered a risk factor for the development of pathologies, such as dyslipidemia, cardiovascular disease, type II diabetes, various types of cancer, and arthritis [115]. Only four people have been found who have reported obesity as a chronic non-communicable disease in the self-administered questionnaire. Nine people completed the survey mentioning that they have high cholesterol values in their blood, which allows inducing that more people could have presented obesity, but that they do not consider it internally as a chronic non-communicable disease. One study states that in Argentina, more than half of the adult population is overweight [116]. Obesity is directly related to a sedentary lifestyle as one of its leading causes [117]. Another effective intervention that could be applied to reduce the risk factors for developing NCDs is to promote the consumption of fruits and vegetables [116].
Regarding non-steroidal anti-inflammatory drugs (NSAIDs), the prevalence of habitual and chronic consumption has been approximately 17%. Most people tend to self-medicate with this type of drug when presenting intermittent pain, and many times consultations are received regarding pain and discomfort that does not respond to a specific and demonstrable cause. It would be essential to develop prevention, education, and health promotion strategies to reduce risk factors to prevent injuries and NCDs. Adverse drug reactions (ADR) are a massive problem for public health since there is a high rate of morbidity and mortality, representing one of the six most frequent causes of death in some countries, in addition to the fact that the majority of patients do not comply with the indicated treatment correctly. According to drug surveillance studies, more than 80% of ADRs occur in primary health care, and almost 20% of the rest come from the secondary care system, i.e., in the hospital setting, where the ADRs occur. ADRs are considered moderate, severe, and fatal, causing additional costs to the health system [118,119]. Considering the state, pharmacovigilance policies must be established that allow the evaluation and prevention of ADRs, allow the risks and benefits of consumption to be balanced, and allow decisions to be made [120].
Regarding the limitations of this study, it can be mentioned that sometimes some people who had been given the survey did not have the ability to read, which is why they were initially excluded from the study. In addition, providing closed answers in a self-administered questionnaire causes people to limit themselves to answering what is established, for which it would be pertinent to carry out studies with a qualitative approach that allows expressing the personal needs and interests of each individual. The variability of the demographic and culture of the people who reside in the city of Rosario limits the extrapolation of the results obtained to all the health effectors.
6. Conclusions
This study contributes significantly to understanding how users determine the intention to re-choose a health service, explaining the indirect routes through which the quality of care relates to the intention to revisit. The increase in the intention to revisit, based on the improvement of the quality of care, satisfaction, and trust, allow to guarantee continuity in health care, reflected in better metrics in the evaluations, which improve accessibility and the achievement of high-quality universal health coverage. It has been shown that greater satisfaction with the medical practice service has a mediating effect on the revisit intention to the health center [82,121]. Quality, comprised of indicators, such as staff competencies, trust, genuine concern for people’s needs, and satisfaction, has also been found to have important effects on revisit intention in ambulatory care settings [122]. The healthcare system in Argentina has evidence to use in the planning process for the care of their population and to generate satisfaction and trust between their patients and promote revisits towards the optimal control of their disease process.
Conceptualization, M.P. and A.A.-R.; methodology, M.P. and A.A.-R.; validation, M.P. and A.A.-R.; formal analysis, M.P. and A.A.-R.; investigation, M.P.; data curation, M.P. and A.A.-R.; writing—original draft preparation, M.P., A.A.-R., S.D.-A.-A., M.R.-O. and J.A.Y.; writing—review and editing, M.P., A.A.-R., S.D.-A.-A., M.R.-O. and J.A.Y.; visualization, M.P., A.A.-R., S.D.-A.-A., M.R.-O. and J.A.Y. All authors have read and agreed to the published version of the manuscript.
This study was approved by the Provincial Bioethics Committee of the Ministry of Health of the Province of Santa Fe (R. P. 1153) and the Ethics Committee of the Universidad Internacional Iberoamericana (CR-125).
All the survey participants were well versed on the study intentions and were required to consent before enrollment.
The data presented in this study are available on request from the corresponding author.
The authors declare no conflict of interest.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Description of the questions included in the questionnaire.
| Variable | Items | Source |
|---|---|---|
| Quality of use of health programs | The health clinics I usually go to give me detailed information about my illnesses |
Adapted from Rahmad et al. (2018) [ |
| Patient satisfaction | I enjoy going to the health clinics that I usually go to |
Adapted from Hassanein and Head (2007) [ |
| Patient trust | The health offices I usually go to protect their patients. |
Adapted from Rahmad et al. (2018) [ |
| Patient revisit intention | I intend to continue going to the same offices that I usually visit | Adapted from Gefen et al. (2003) [ |
Demographic data.
| Healthcare Facilities | |
|---|---|
| Health Center No. 17 “Cáritas Guadalupe” | 14.3% |
| Northwest District Municipal Health Center “Olga and Leticia Cossettini” | 24.6% |
| Health Center “Dr. Roque Coullin” | 12.8% |
| Health Center No. 5 “Dr. Pedro Fiorina” | 10.3% |
| C.I.C. “La Cerámica” | 11.8% |
| Health Center “Dr. Luis Pasteur” | 11.1% |
| Center No. 13 “FONAVI” | 15.1% |
| Sex | |
| Female | 62.9% (n = 256) |
| Male | 37.1% (n = 151) |
| Age | |
| Between 18 and 35 years old | 22.9% (n = 93) |
| Between 36 and 50 years old | 37.8% (n = 154) |
| Between 51 and 65 years old | 30.5% (n = 124) |
| More than 65 years old | 8.8% (n = 36) |
| Average age | 45.64 |
| Marital status | |
| Single | 55.0% (n = 224) |
| Married | 37.3% (n = 152) |
| Divorced | 4.4% (n = 18) |
| Widowed | 3.2% (n = 13) |
| Educational level | |
| None | 19.4% (n = 79) |
| Primary | 49.1% (n = 200) |
| Secondary | 23.8% (n = 97) |
| Tertiary | 5.7% (n = 23) |
| University | 2.0% (n = 8) |
| Occupation | |
| Housewife | 25.1% (n = 102) |
| Unemployed | 25.6% (n = 104) |
| Commercial employee | 9.8% (n = 40) |
| Domestic worker | 10.3% (n = 42) |
| Bricklayer | 6.9% (n = 28) |
| Cook | 3.2% (n = 13) |
| Metallurgical employee | 2.2% (n = 9) |
| Retired | 3.2% (n = 13) |
| Teacher | 2.2% (n = 9) |
| Other | 11.3% (n = 46) |
Prevalence of chronic non-communicable diseases (CNCD).
| Chronic Non-Communicable Diseases | N |
|---|---|
| Hypertension | 102 |
| Diabetes | 61 |
| Hypothyroidism | 24 |
| Chronic lung diseases | 12 |
| Hypercholesterolemia | 9 |
| H.I.V. | 9 |
| Other (Chagas disease, rheumatoid arthritis, asthma…) | 26 |
Internal consistency analysis using partial least squares structural equation modeling (PLS-SEM).
| Variables | Factor Loading | Cronbach’s Alpha | rho_A | Composite Reliability | AVE |
|---|---|---|---|---|---|
| Quality | Q1: 0.897 | 0.862 | 0.871 | 0.901 | 0.649 |
| Q2: 0.824 | |||||
| Q3: 0.788 | |||||
| Q4: 0.831 | |||||
| Q5: 0.669 | |||||
| Trust | T1: 0.878 | 0.878 | 0.880 | 0.916 | 0.639 |
| T2: 0.852 | |||||
| T3: 0.875 | |||||
| T4: 0.817 | |||||
| Satisfaction | RIN1: 0.767 | 0.859 | 0.872 | 0.898 | 0.733 |
| RIN2: 0.834 | |||||
| RIN3: 0.828 | |||||
| RIN4: 0.732 | |||||
| RIN5: 0.829 | |||||
| Revisit Intention | S: 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
Discriminant validity of the subscales according to the Fornell-Larcker criterion.
| Variables | Quality | Revisit Intention | Satisfaction | Trust |
|---|---|---|---|---|
| Quality | 0.805 | |||
| Revisit intention | 0.576 | 1.000 | ||
| Satisfaction | 0.721 | 0.704 | 0.856 | |
| Trust | 0.736 | 0.746 | 0.675 | 0.799 |
Goodness of fit.
| Saturated Model | Estimated Model | |
|---|---|---|
| SRMR | 0.077 | 0.077 |
| d_ULS | 0.716 | 0.716 |
| d_G | 0.386 | 0.386 |
| Chi-Square | 853.148 | 853.148 |
| NFI | 0.912 | 0.912 |
Significance of direct path coefficients.
| Original | Sample | Standard | T | p-Value | Hypothesis | |
|---|---|---|---|---|---|---|
| H1: Quality → Satisfaction | 0.721 | 0.722 | 0.01 | 23.117 | 0.000 | Accepted |
| H2: Quality → Trust | 0.246 | 0.248 | 0.040 | 6.121 | 0.000 | Accepted |
| H3: Quality → Revisit intention | 0.012 | 0.012 | 0.054 | 0.226 | 0.821 | No Accepted |
| H4: Satisfaction → Revisit intention | 0.239 | 0.0237 | 0.074 | 3.233 | 0.001 | Accepted |
| H5: Satisfaction → Trust | 0.679 | 0.678 | 0.040 | 17.092 | 0.000 | Accepted |
| H6: Trust → Revisit intention | 0.533 | 0.534 | 0.080 | 6.643 | 0.000 | Accepted |
Significance of indirect trajectory coefficients.
| Original | Sample | Standard | T | p-Value | |
|---|---|---|---|---|---|
| Quality → Trust → Revisit intention | 0.131 | 0.132 | 0.030 | 4.412 | 0.000 |
| Calidad → Satisfaction → Trust | 0.489 | 0.489 | 0.033 | 14.912 | 0.000 |
| Quality → Satisfaction → Revisit intention | 0.172 | 0.172 | 0.055 | 3.130 | 0.002 |
| Satisfaction → Trust → Revisit intention | 0.362 | 0.362 | 0.058 | 6.211 | 0.000 |
| Quality → Satisfaction → Trust → Revisit intention | 0.261 | 0.261 | 0.042 | 6.136 | 0.000 |
Bootstrapping technique (5000 times) using Smart PLS. p-value < 0.01. Sample: 407 people.
References
1. Lozada-Urbano, M.; Huamán, F.; Xirinachs, Y.; Rivera-Lozada, O.; Alvarez-Risco, A.; Yáñez, J.A. Poverty, Household Structure and Consumption of Foods Away from Home in Peru in 2019: A Cross-Sectional Study. Foods; 2022; 11, 2547. [DOI: https://dx.doi.org/10.3390/foods11172547] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/36076733]
2. Leclercq-Machado, L.; Alvarez-Risco, A.; Gómez-Prado, R.; Cuya-Velásquez, B.B.; Esquerre-Botton, S.; Morales-Ríos, F.; Almanza-Cruz, C.; Castillo-Benancio, S.; de las Mercedes Anderson-Seminario, M.; Del-Aguila-Arcentales, S. et al. Sustainable Fashion and Consumption Patterns in Peru: An Environmental-Attitude-Intention-Behavior Analysis. Sustainability; 2022; 14, 9965. [DOI: https://dx.doi.org/10.3390/su14169965]
3. Leclercq-Machado, L.; Alvarez-Risco, A.; Esquerre-Botton, S.; Almanza-Cruz, C.; Anderson-Seminario, M.L.M.; Del-Aguila-Arcentales, S.; Yáñez, J.A. Effect of Corporate Social Responsibility on Consumer Satisfaction and Consumer Loyalty of Private Banking Companies in Peru. Sustainability; 2022; 14, 9078. [DOI: https://dx.doi.org/10.3390/su14159078]
4. Gómez-Prado, R.; Alvarez-Risco, A.; Cuya-Velásquez, B.B.; Anderson-Seminario, M.d.l.M.; Del-Aguila-Arcentales, S.; Yáñez, J.A. Product Innovation, Market Intelligence and Pricing Capability as a Competitive Advantage in the International Performance of Startups: Case of Peru. Sustainability; 2022; 14, 10703. [DOI: https://dx.doi.org/10.3390/su141710703]
5. Biswas, R.K.; Farzana, M.; Bhar, S.; Bhowmik, J. Contraceptive use in South and South-East Asian region: Assessment of sustainable development goal 3.7 through indicator 3.7.1. J. Public Health; 2022; fdac105. [DOI: https://dx.doi.org/10.1093/pubmed/fdac105]
6. Deng, J. Sustainable Development Research of Green Smart Park in High-End Manufacturing Based on Internet of Things. J. Environ. Public Health; 2022; 2022, 3961647. [DOI: https://dx.doi.org/10.1155/2022/3961647]
7. Sundewall, J.; Forsberg, B.C. Understanding health spending for SDG 3. Lancet; 2020; 396, pp. 650-651. [DOI: https://dx.doi.org/10.1016/S0140-6736(20)30963-6]
8. Abou, J.; Crutzen, S.; Tromp, V.; Heringa, M.; Van Marum, R.; Elders, P.; Taxis, K.; Denig, P.; Hugtenburg, J. Barriers and Enablers of Healthcare Providers to Deprescribe Cardiometabolic Medication in Older Patients: A Focus Group Study. Drugs Aging; 2022; 39, pp. 209-221. [DOI: https://dx.doi.org/10.1007/s40266-021-00918-7]
9. Zinatsa, F.; Engelbrecht, M.; van Rensburg, A.J.; Kigozi, G. Voices from the frontline: Barriers and strategies to improve tuberculosis infection control in primary health care facilities in South Africa. BMC Health Serv. Res.; 2018; 18, 269. [DOI: https://dx.doi.org/10.1186/s12913-018-3083-0]
10. Trinka, E.; Kwan, P.; Lee, B.; Dash, A. Epilepsy in Asia: Disease burden, management barriers, and challenges. Epilepsia; 2019; 60, pp. 7-21. [DOI: https://dx.doi.org/10.1111/epi.14458]
11. Martina, D.; Lin, C.-P.; Kristanti, M.S.; Bramer, W.M.; Mori, M.; Korfage, I.J.; van der Heide, A.; van der Rijt, C.C.D.; Rietjens, J.A.C. Advance Care Planning in Asia: A Systematic Narrative Review of Healthcare Professionals’ Knowledge, Attitude, and Experience. J. Am. Med. Dir. Assoc.; 2021; 22, pp. e341-e349. [DOI: https://dx.doi.org/10.1016/j.jamda.2020.12.018] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33421371]
12. Blackwood, D.H.; Walker, D.; Mythen, M.G.; Taylor, R.M.; Vindrola-Padros, C. Barriers to advance care planning with patients as perceived by nurses and other healthcare professionals: A systematic review. J. Clin. Nurs.; 2019; 28, pp. 4276-4297. [DOI: https://dx.doi.org/10.1111/jocn.15049] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/31494997]
13. O’Connor, S.R.; Connaghan, J.; Maguire, R.; Kotronoulas, G.; Flannagan, C.; Jain, S.; Brady, N.; McCaughan, E. Healthcare professional perceived barriers and facilitators to discussing sexual wellbeing with patients after diagnosis of chronic illness: A mixed-methods evidence synthesis. Patient Educ. Couns.; 2019; 102, pp. 850-863. [DOI: https://dx.doi.org/10.1016/j.pec.2018.12.015] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/30578104]
14. Abdel-Rahman, O. Patient-related barriers to some virtual healthcare services among cancer patients in the USA: A population-based study. J. Comp. Eff. Res.; 2021; 10, pp. 119-126. [DOI: https://dx.doi.org/10.2217/cer-2020-0187]
15. Haleem, A.; Javaid, M.; Singh, R.P.; Suman, R. Telemedicine for healthcare: Capabilities, features, barriers, and applications. Sens. Int.; 2021; 2, 100117. [DOI: https://dx.doi.org/10.1016/j.sintl.2021.100117]
16. Schwarz, D.; Hirschhorn, L.R.; Kim, J.-H.; Ratcliffe, H.L.; Bitton, A. Continuity in primary care: A critical but neglected component for achieving high-quality universal health coverage. BMJ Glob. Health; 2019; 4, e001435. [DOI: https://dx.doi.org/10.1136/bmjgh-2019-001435]
17. WHO. 9th Global Conference on Health Promotion: Global Leaders Agree to Promote Health in Order to Achieve Sustainable Development Goals. Available online: https://www.who.int/news/item/21-11-2016-9th-global-conference-on-health-promotion-global-leaders-agree-to-promote-health-in-order-to-achieve-sustainable-development-goals (accessed on 4 April 2022).
18. Kirchhoff, S.; Dadaczynski, K.; Pelikan, J.M.; Zelinka-Roitner, I.; Dietscher, C.; Bittlingmayer, U.H.; Okan, O. Organizational Health Literacy in Schools: Concept Development for Health-Literate Schools. Int. J. Environ. Res. Public Health; 2022; 19, 8795. [DOI: https://dx.doi.org/10.3390/ijerph19148795]
19. Yáñez, J.A.; Remsberg, C.M.; Takemoto, J.K.; Vega-Villa, K.R.; Andrews, P.K.; Sayre, C.L.; Martinez, S.E.; Davies, N.M. Polyphenols and Flavonoids: An Overview. Flavonoid Pharmacokinetics: Methods of Analysis, Preclinical and Clinical Pharmacokinetics, Safety, and Toxicology; Davies, N.M.; Yáñez, J.A. John Wiley & Sons: Hoboken, NJ, USA, 2012; pp. 1-69.
20. Ramos-Escudero, F.; Santos-Buelga, C.; Pérez-Alonso, J.J.; Yáñez, J.A.; Dueñas, M. HPLC-DAD-ESI/MS identification of anthocyanins in Dioscorea trifida L. yam tubers (purple sachapapa). Eur. Food Res. Technol.; 2010; 230, pp. 745-752. [DOI: https://dx.doi.org/10.1007/s00217-010-1219-5]
21. Lurie, I.; Maree, S.; Mendlovic, S.; Shefet, D. Psychiatrists’ awareness of the cost of medication, rates of social disability pension, and their attitudes regarding knowledge of treatment costs. Isr. J. Health Policy Res.; 2022; 11, 35. [DOI: https://dx.doi.org/10.1186/s13584-022-00545-6]
22. Villena-Tejada, M.; Vera-Ferchau, I.; Cardona-Rivero, A.; Zamalloa-Cornejo, R.; Quispe-Florez, M.; Frisancho-Triveño, Z.; Abarca-Meléndez, R.C.; Alvarez-Sucari, S.G.; Mejia, C.R.; Yañez, J.A. Use of medicinal plants for COVID-19 prevention and respiratory symptom treatment during the pandemic in Cusco, Peru: A cross-sectional survey. PLoS ONE; 2021; 16, e0257165. [DOI: https://dx.doi.org/10.1371/journal.pone.0257165]
23. Gigli, K.H.; Graaf, G. Changes in Use and Access to Care for Children and Youth With Special Health Care Needs During the COVID-19 Pandemic. J. Pediatr. Health Care; 2022; [DOI: https://dx.doi.org/10.1016/j.pedhc.2022.09.008]
24. Alvarez-Risco, A.; Del-Aguila-Arcentales, S.; Yáñez, J.A.; Rosen, M.A.; Mejia, C.R. Influence of Technostress on Academic Performance of University Medicine Students in Peru during the COVID-19 Pandemic. Sustainability; 2021; 13, 8949. [DOI: https://dx.doi.org/10.3390/su13168949]
25. Alvarez-Risco, A.; Del-Aguila-Arcentales, S.; Yanez, J.A. Telemedicine in Peru as a Result of the COVID-19 Pandemic: Perspective from a Country with Limited Internet Access. Am. J. Trop. Med. Hyg.; 2021; 105, pp. 6-11. [DOI: https://dx.doi.org/10.4269/ajtmh.21-0255] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33999847]
26. Yáñez, J.A.; Alvarez-Risco, A.; Delgado-Zegarra, J. Covid-19 in Peru: From supervised walks for children to the first case of Kawasaki-like syndrome. BMJ Clin. Res.; 2020; 369, m2418. [DOI: https://dx.doi.org/10.1136/bmj.m2418] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32571770]
27. Khazanchi, R.; Heard-Garris, N.J.; Winkelman, T.N.A. Health Care Access and Use Among Children & Adolescents Exposed to Parental Incarceration—United States, 2019: Short title: Parental Incarceration and Child/Adolescent Access to Care. Acad. Pediatr.; 2022; [DOI: https://dx.doi.org/10.1016/j.acap.2022.10.001]
28. Serchen, J.; Mathew, S.; Hilden, D.; Southworth, M.; Atiq, O. Supporting the Health and Well-Being of Indigenous Communities: A Position Paper From the American College of Physicians. Ann. Intern. Med.; 2022; [DOI: https://dx.doi.org/10.7326/M22-1891]
29. Haider, K.A.; Gulam, O.; Adamjee, R.; Balouch, B.; Hoodbhoy, Z. Health workers’ experience of a digital health intervention implemented in peri-urban communities in Karachi, Pakistan. Digit. Health; 2022; 8, 20552076221129076. [DOI: https://dx.doi.org/10.1177/20552076221129076]
30. Cheng, W.; Zhang, Z.; Hoelzer, S.; Tang, W.; Liang, Y.; Du, Y.; Xue, H.; Zhou, Q.; Yip, W.; Ma, X. et al. Evaluation of a village-based digital health kiosks program: A protocol for a cluster randomized clinical trial. Digit. Health; 2022; 8, 20552076221129100. [DOI: https://dx.doi.org/10.1177/20552076221129100]
31. Corscadden, L.; Levesque, J.F.; Lewis, V.; Strumpf, E.; Breton, M.; Russell, G. Factors associated with multiple barriers to access to primary care: An international analysis. Int. J. Equity Health; 2018; 17, 28. [DOI: https://dx.doi.org/10.1186/s12939-018-0740-1]
32. Osae, S.P.; Chastain, D.B.; Young, H.N. Pharmacists role in addressing health disparities—Part 1: Social determinants of health and their intersectionality with medication use, health care utilization, and health outcomes. JACCP J. Am. Coll. Clin. Pharm.; 2022; 5, pp. 533-540. [DOI: https://dx.doi.org/10.1002/jac5.1565]
33. Bonin, A.M.; Yáñez, J.A.; Fukuda, C.; Teng, X.W.; Dillon, C.T.; Hambley, T.W.; Lay, P.A.; Davies, N.M. Inhibition of experimental colorectal cancer and reduction in renal and gastrointestinal toxicities by copper-indomethacin in rats. Cancer Chemother. Pharmacol.; 2010; 66, pp. 755-764. [DOI: https://dx.doi.org/10.1007/s00280-009-1220-5]
34. Vega-Villa, K.R.; Remsberg, C.M.; Ohgami, Y.; Yanez, J.A.; Takemoto, J.K.; Andrews, P.K.; Davies, N.M. Stereospecific high-performance liquid chromatography of taxifolin, applications in pharmacokinetics, and determination in tu fu ling (Rhizoma smilacis glabrae) and apple (Malus x domestica). Biomed. Chromatogr.; 2009; 23, pp. 638-646. [DOI: https://dx.doi.org/10.1002/bmc.1165] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/19267323]
35. Yáñez, J.A.; Miranda, N.D.; Remsberg, C.M.; Ohgami, Y.; Davies, N.M. Stereospecific high-performance liquid chromatographic analysis of eriodictyol in urine. J. Pharm. Biomed. Anal.; 2007; 43, pp. 255-262. [DOI: https://dx.doi.org/10.1016/j.jpba.2006.06.027]
36. Agarwal, S.; Simmonds, I.; Myers, A.K. The Use of Diabetes Technology to Address Inequity in Health Outcomes: Limitations and Opportunities. Curr. Diab. Rep.; 2022; 22, pp. 275-281. [DOI: https://dx.doi.org/10.1007/s11892-022-01470-3] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/35648277]
37. Coles, E.; Anderson, J.; Maxwell, M.; Harris, F.M.; Gray, N.M.; Milner, G.; MacGillivray, S. The influence of contextual factors on healthcare quality improvement initiatives: A realist review. Syst. Rev.; 2020; 9, 94. [DOI: https://dx.doi.org/10.1186/s13643-020-01344-3] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32336290]
38. Lázaro Pérez Peña, J.; Jiménez Rodríguez, D. The discreet charm of medicines [El discreto encanto de los medicamentos]. Rev. Cuba. Salud Pública; 2014; 40, pp. 349-360.
39. Jain, R.; Tobey, M. The Indian Health Service can meet its goals for hepatitis C virus treatment through telehealth expansion. J. Rural. Health Off. J. Am. Rural. Health Assoc. Natl. Rural. Health Care Assoc.; 2022; [DOI: https://dx.doi.org/10.1111/jrh.12718]
40. Soliman, A.A.; Akgün, K.M.; Coffee, J.; Kapo, J.; Morrison, L.J.; Hopkinson, E.; Schulman-Green, D.; Feder, S.L. Quality of Telehealth-Delivered Inpatient Palliative Care During the Early COVID-19 Pandemic. J. Pain Symptom. Manag.; 2022; [DOI: https://dx.doi.org/10.1016/j.jpainsymman.2022.09.014]
41. Salameh, A.A.; Amin, S.; Danish, M.H.; Asghar, N.; Naveed, R.T.; Munir, M. Socio-economic determinants of subjective wellbeing toward Sustainable Development Goals: An insight from a developing country. Front. Psychol.; 2022; 13, 961400. [DOI: https://dx.doi.org/10.3389/fpsyg.2022.961400]
42. Kooshkebaghi, M.; Emamgholipour, S.; Dargahi, H. Explaining specific taxes management and use in the health sector: A qualitative study. BMC Health Serv. Res.; 2022; 22, 1220. [DOI: https://dx.doi.org/10.1186/s12913-022-08556-4]
43. Xu, X.; Yang, H.; Li, C. Theoretical Model and Actual Characteristics of Air Pollution Affecting Health Cost: A Review. Int. J. Environ. Res. Public Health; 2022; 19, 3532. [DOI: https://dx.doi.org/10.3390/ijerph19063532] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/35329214]
44. García Salman, J.D. Considerations on Natural and Traditional Medicine, the scientific method and the Cuban health system [Consideraciones sobre la Medicina Natural y Tradicional, el método científico y el sistema de salud cubano]. Rev. Cuba. Salud Pública; 2013; 39, pp. 540-555.
45. Seliger, C.; Luber, C.; Gerken, M.; Schaertl, J.; Proescholdt, M.; Riemenschneider, M.J.; Meier, C.R.; Bogdahn, U.; Leitzmann, M.F.; Klinkhammer-Schalke, M. et al. Use of metformin and survival of patients with high-grade glioma. Int. J. Cancer; 2019; 144, pp. 273-280. [DOI: https://dx.doi.org/10.1002/ijc.31783] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/30091464]
46. Lapuente, M.; Estruch, R.; Shahbaz, M.; Casas, R. Relation of Fruits and Vegetables with Major Cardiometabolic Risk Factors, Markers of Oxidation, and Inflammation. Nutrients; 2019; 11, 2381. [DOI: https://dx.doi.org/10.3390/nu11102381]
47. Salvadó, M.J.; Casanova, E.; Fernández-Iglesias, A.; Arola, L.; Bladé, C. Roles of proanthocyanidin rich extracts in obesity. Food Funct.; 2015; 6, pp. 1053-1071. [DOI: https://dx.doi.org/10.1039/C4FO01035C]
48. Roupe, K.A.; Helms, G.L.; Halls, S.C.; Yanez, J.A.; Davies, N.M. Preparative enzymatic synthesis and HPLC analysis of rhapontigenin: Applications to metabolism, pharmacokinetics and anti-cancer studies. J. Pharm. Pharm. Sci.; 2005; 8, pp. 374-386.
49. Konfino, J.; Linetzky, B.; Ferrante, D. Evolution and current status of non-communicable diseases in Argentina [Evolución y estado actual de las enfermedades no transmisibles en Argentina]. Rev. Argent. Salud Pública; 2010; 1, pp. 27-39.
50. García Milian, A.J.; López Verde, L.; Pría Barros, M.C.; Cabrera, P.L. Drug use and living conditions [Consumo de medicamentos y condiciones de vida]. Rev. Cuba. Salud Pública; 2016; 42, pp. 442-450.
51. İlhan, S.; Yıldız, M.; Tüzün, H.; Dikmen, A.U. Evaluation of irrational drug use of individuals over the age of 18 who applied to a university hospital. Turk. J. Med. Sci.; 2022; 52, pp. 484-493. [DOI: https://dx.doi.org/10.55730/1300-0144.5337] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/36161621]
52. Yang, Q.; Yuan, F.; Li, L.; Jin, J.; He, J. Effects of monthly evaluations on the rates of irrational antimicrobial prescription in the outpatient and emergency departments at Ningbo No. 6 Hospital, Ningbo, China. Eur. J. Med. Res.; 2022; 27, 98. [DOI: https://dx.doi.org/10.1186/s40001-022-00728-6]
53. Liu, H.; Li, H.; Teuwen, D.E.; Sylvia, S.; Shi, H.; Rozelle, S.; Yi, H. Irrational Use of Medicine in the Treatment of Presumptive Asthma Among Rural Primary Care Providers in Southwestern China. Front. Pharmacol.; 2022; 13, 767917. [DOI: https://dx.doi.org/10.3389/fphar.2022.767917] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/35242030]
54. Cañás, M.; Buschiazzo, H.O.; Urtasun, M.A. Therapeutic value and price of new drugs marketed in Argentina: Are they worth what they cost? [Valor terapéutico y precio de los nuevos fármacos comercializados en Argentina: ¿valen lo que cuestan?]. Salud Colect.; 2019; 15, e1962. [DOI: https://dx.doi.org/10.18294/sc.2019.1962] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/31141093]
55. Nieto-Blasco, J.; Vicente-Blanco, M.V.; Calvo-Vera, A.B.; Lobato-Benito, L.; Rubio-Gil, F.J.; Mendoza-García, J.L.; Rodríguez-Pérez, M.P. Satisfaction study of patients treated at the CAUSA Rehabilitation Service [Estudio de satisfacción de los pacientes atendidos en el Servicio de Rehabilitación del CAUSA]. Rehabilitación; 2018; 52, pp. 28-37. [DOI: https://dx.doi.org/10.1016/j.rh.2017.09.009]
56. Jimeno-Serrano, F.J.; Medina-Mirapeix, F.; Escolar-Reina, P.; DelBaño-Aledo, M.E. Patient satisfaction and experiences in rehabilitation centers associated with their trust in the professionalism of physical therapists [Satisfacción y experiencias de los pacientes en centros de rehabilitación asociados con su confianza en la profesionalidad de los fisioterapeutas]. Rehabilitación; 2012; 46, pp. 227-235. [DOI: https://dx.doi.org/10.1016/j.rh.2012.06.004]
57. Osuna Pérez, C. Therapeutic Information, Satisfaction and Confidence in Physiotherapy: Measurement Instruments and Correlational Study in Physiotherapy Centers in Eastern Andalusia [Información Terapéutica, Satisfacción y Confianza en Fisioterapia: Instrumentos de Medida y Estudio Correlacional en Centros de Fisioterapia de Andalucía Oriental]. Ph.D. Thesis; Universidad de Jaén: Japen, Spain, 2012.
58. Kijima, T.; Matsushita, A.; Akai, K.; Hamano, T.; Takahashi, S.; Fujiwara, K.; Fujiwara, Y.; Sato, M.; Nabika, T.; Sundquist, K. et al. Patient satisfaction and loyalty in Japanese primary care: A cross-sectional study. BMC Health Serv. Res.; 2021; 21, 274. [DOI: https://dx.doi.org/10.1186/s12913-021-06276-9] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33766027]
59. Goetz, K.; Jossen, M.; Rosemann, T.; Hess, S.; Brodowski, M.; Bezzola, P. Is patient loyalty associated with quality of care? Results of a patient survey over primary care in Switzerland. Int. J. Qual. Health Care; 2019; 31, pp. 199-204. [DOI: https://dx.doi.org/10.1093/intqhc/mzy142]
60. Revilla Arias, H.; González Mustelier, D.; Valenzuela Fonseca, L.M. Quality of health care provided in a comprehensive community-based rehabilitation service [Calidad de la atención de salud brindada en un servicio de rehabilitación integral de base comunitaria]. Medisan; 2016; 20, pp. 313-319.
61. Khatoon, S.; Zhengliang, X.; Hussain, H. The Mediating Effect of Customer Satisfaction on the Relationship Between Electronic Banking Service Quality and Customer Purchase Intention: Evidence From the Qatar Banking Sector. SAGE Open; 2020; 10, 2158244020935887. [DOI: https://dx.doi.org/10.1177/2158244020935887]
62. Nguyen, T.L.H.; Nagase, K. The influence of total quality management on customer satisfaction. Int. J. Healthc. Manag.; 2019; 12, pp. 277-285. [DOI: https://dx.doi.org/10.1080/20479700.2019.1647378]
63. Fatima, T.; Malik, S.A.; Shabbir, A. Hospital healthcare service quality, patient satisfaction and loyalty. Int. J. Qual. Reliab. Manag.; 2018; 35, pp. 1195-1214. [DOI: https://dx.doi.org/10.1108/IJQRM-02-2017-0031]
64. Ng, J.H.Y.; Luk, B.H.K. Patient satisfaction: Concept analysis in the healthcare context. Patient Educ. Couns.; 2019; 102, pp. 790-796. [DOI: https://dx.doi.org/10.1016/j.pec.2018.11.013] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/30477906]
65. Javed, S.A.; Liu, S.; Mahmoudi, A.; Nawaz, M. Patients’ satisfaction and public and private sectors’ health care service quality in Pakistan: Application of grey decision analysis approaches. Int. J. Health Plan. Manag.; 2019; 34, pp. e168-e182. [DOI: https://dx.doi.org/10.1002/hpm.2629] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/30160783]
66. Suhail, P.; Srinivasulu, Y. Perception of service quality, satisfaction, and behavioral intentions in Ayurveda healthcare. J. Ayurveda Integr. Med.; 2021; 12, pp. 93-101. [DOI: https://dx.doi.org/10.1016/j.jaim.2020.10.011] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33309436]
67. Radu, F.; Radu, V.; Turkeș, M.C.; Ivan, O.R.; Tăbîrcă, A.I. A research of service quality perceptions and patient satisfaction: Case study of public hospitals in Romania. Int. J. Health Plan. Manag.; 2022; 37, pp. 1018-1048. [DOI: https://dx.doi.org/10.1002/hpm.3375]
68. Chen, L.; Li, Y.-Q.; Liu, C.-H. How airline service quality determines the quantity of repurchase intention—Mediate and moderate effects of brand quality and perceived value. J. Air Transp. Manag.; 2019; 75, pp. 185-197. [DOI: https://dx.doi.org/10.1016/j.jairtraman.2018.11.002]
69. Nasir, M.; Adil, M.; Dhamija, A. The synergetic effect of after sales service, customer satisfaction, loyalty and repurchase intention on word of mouth. Int. J. Qual. Serv. Sci.; 2021; 13, pp. 489-505. [DOI: https://dx.doi.org/10.1108/IJQSS-01-2021-0015]
70. Antwi, S. “I just like this e-Retailer”: Understanding online consumers repurchase intention from relationship quality perspective. J. Retail. Consum. Serv.; 2021; 61, 102568. [DOI: https://dx.doi.org/10.1016/j.jretconser.2021.102568]
71. Tandon, A.; Aakash, A.; Aggarwal, A.G. Impact of EWOM, website quality, and product satisfaction on customer satisfaction and repurchase intention: Moderating role of shipping and handling. Int. J. Syst. Assur. Eng. Manag.; 2020; 11, pp. 349-356. [DOI: https://dx.doi.org/10.1007/s13198-020-00954-3]
72. Chang, W.-J.; Liao, S.-H.; Chung, Y.-C.; Chen, H.-P. Service quality, experiential value and repurchase intention for medical cosmetology clinic: Moderating effect of Generation. Total Qual. Manag. Bus. Excell.; 2020; 31, pp. 1077-1097. [DOI: https://dx.doi.org/10.1080/14783363.2018.1463156]
73. Ali, A.; Bhasin, J. Understanding Customer Repurchase Intention in E-commerce: Role of Perceived Price, Delivery Quality, and Perceived Value. Jindal J. Bus. Res.; 2019; 8, pp. 142-157. [DOI: https://dx.doi.org/10.1177/2278682119850275]
74. Amoako, G.K.; Caesar, L.D.; Dzogbenuku, R.K.; Bonsu, G.A. Service recovery performance and repurchase intentions: The mediation effect of service quality at KFC. J. Hosp. Tour. Insights; 2021; ahead-of-print [DOI: https://dx.doi.org/10.1108/JHTI-06-2021-0141]
75. Anderson, E.W.; Sullivan, M.W. The Antecedents and Consequences of Customer Satisfaction for Firms. Mark. Sci.; 1993; 12, pp. 125-143. [DOI: https://dx.doi.org/10.1287/mksc.12.2.125]
76. Bloemer, J.; de Ruyter, K. On the relationship between store image, store satisfaction and store loyalty. Eur. J. Mark.; 1998; 32, pp. 499-513. [DOI: https://dx.doi.org/10.1108/03090569810216118]
77. Levesque, T.; McDougall, G.H.G. Determinants of customer satisfaction in retail banking. Int. J. Bank Mark.; 1996; 14, pp. 12-20. [DOI: https://dx.doi.org/10.1108/02652329610151340]
78. Zeithaml, V.A.; Berry, L.L.; Parasuraman, A. The Behavioral Consequences of Service Quality. J. Mark.; 1996; 60, pp. 31-46. [DOI: https://dx.doi.org/10.1177/002224299606000203]
79. Chiguvi, D.; Guruwo, P. Impact of Customer Satisfaction on Customer Loyalty in the Banking Sector. Int. J. Sci. Eng. Res.; 2017; 5, pp. 55-63.
80. Oliver, R.L. Whence Consumer Loyalty?. J. Mark.; 1999; 63, pp. 33-44. [DOI: https://dx.doi.org/10.1177/00222429990634s105]
81. Lee, M.A.; Yom, Y.-H. A comparative study of patients’ and nurses’ perceptions of the quality of nursing services, satisfaction and intent to revisit the hospital: A questionnaire survey. Int. J. Nurs. Stud.; 2007; 44, pp. 545-555. [DOI: https://dx.doi.org/10.1016/j.ijnurstu.2006.03.006]
82. Woo, S.; Choi, M. Medical service quality, patient satisfaction and intent to revisit: Case study of public hub hospitals in the Republic of Korea. PLoS ONE; 2021; 16, e0252241. [DOI: https://dx.doi.org/10.1371/journal.pone.0252241]
83. Park, S.; Kim, H.-K.; Choi, M.; Lee, M. Factors affecting revisit intention for medical services at dental clinics. PLoS ONE; 2021; 16, e0250546. [DOI: https://dx.doi.org/10.1371/journal.pone.0250546]
84. Assaker, G.; O’Connor, P.; El-Haddad, R. Examining an integrated model of green image, perceived quality, satisfaction, trust, and loyalty in upscale hotels. J. Hosp. Mark. Manag.; 2020; 29, pp. 934-955. [DOI: https://dx.doi.org/10.1080/19368623.2020.1751371]
85. Fauzi, A.A.; Suryani, T. Measuring the effects of service quality by using CARTER model towards customer satisfaction, trust and loyalty in Indonesian Islamic banking. J. Islamic Mark.; 2019; 10, pp. 269-289. [DOI: https://dx.doi.org/10.1108/JIMA-04-2017-0048]
86. Kalia, P.; Kaushal, R.; Singla, M.; Parkash, J. Determining the role of service quality, trust and commitment to customer loyalty for telecom service users: A PLS-SEM approach. TQM J.; 2021; 33, pp. 377-396. [DOI: https://dx.doi.org/10.1108/TQM-04-2021-0108]
87. Martínez-Navalón, J.G.; Gelashvili, V.; Saura, J.R. The impact of environmental social media publications on user satisfaction with and trust in tourism businesses. Int. J. Environ. Res. Public Health; 2020; 17, 5417. [DOI: https://dx.doi.org/10.3390/ijerph17155417] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32731381]
88. Mohd Isa, S.; Lim, G.S.S.; Chin, P.N. Patients’ intent to revisit with trust as the mediating role: Lessons from Penang Malaysia. Int. J. Pharm. Healthc. Mark.; 2019; 13, pp. 140-159. [DOI: https://dx.doi.org/10.1108/IJPHM-10-2017-0056]
89. Sun, T.; Zhang, J.; Zhang, B.; Ong, Y.; Ito, N. How trust in a destination’s risk regulation navigates outbound travel constraints on revisit intention post-COVID-19: Segmenting insights from experienced Chinese tourists to Japan. J. Destin. Mark. Manag.; 2022; 25, 100711. [DOI: https://dx.doi.org/10.1016/j.jdmm.2022.100711]
90. Wijaya, R.; Farida, N.; Andriyansah,. Determinants of Repurchase Intentions at Online Stores in Indonesia. Int. J. E-Bus. Res. (IJEBR); 2018; 14, pp. 95-111. [DOI: https://dx.doi.org/10.4018/IJEBR.2018070106]
91. Hassanein, K.; Head, M. Manipulating perceived social presence through the web interface and its impact on attitude towards online shopping. Int. J. Hum.-Comput. Stud.; 2007; 65, pp. 689-708. [DOI: https://dx.doi.org/10.1016/j.ijhcs.2006.11.018]
92. Gefen, D.; Karahanna, E.; Straub, D.W. Trust and TAM in Online Shopping: An Integrated Model. MIS Q.; 2003; 27, pp. 51-90. [DOI: https://dx.doi.org/10.2307/30036519]
93. Pozdnyakova, A.; Laiteerapong, N.; Volerman, A.; Feld, L.D.; Wan, W.; Burnet, D.L.; Lee, W.W. Impact of Medical Scribes on Physician and Patient Satisfaction in Primary Care. J. Gen. Intern. Med.; 2018; 33, pp. 1109-1115. [DOI: https://dx.doi.org/10.1007/s11606-018-4434-6]
94. Villagarcía Trujiilo, E.X.; Delgadillo Guzmán, L.G.; Argüello Zepeda, F.J.; González Villanueva, L. User perception of the quality of the ISSEMyM health services [Percepción usuaria de la calidad en los servicios de salud del ISSEMyM]. Horiz. Sanit.; 2017; 16, pp. 46-54. [DOI: https://dx.doi.org/10.19136/hs.a16n1.1446]
95. Cronin, J.J.; Taylor, S.A. Measuring Service Quality: A Reexamination and Extension. J. Mark.; 1992; 56, pp. 55-68. [DOI: https://dx.doi.org/10.1177/002224299205600304]
96. Babakus, E.; Mangold, W.G. Adapting the SERVQUAL scale to hospital services: An empirical investigation. Health Serv. Res.; 1992; 26, pp. 767-786. [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/1737708]
97. Bolton, R.N.; Drew, J.H. A Multistage Model of Customers’ Assessments of Service Quality and Value. J. Consum. Res.; 1991; 17, pp. 375-384. [DOI: https://dx.doi.org/10.1086/208564]
98. Shafei, I.; Walburg, J.; Taher, A. Verifying alternative measures of healthcare service quality. Int. J. Health Care Qual. Assur.; 2019; 32, pp. 516-533. [DOI: https://dx.doi.org/10.1108/IJHCQA-05-2016-0069]
99. Boulding, W.; Kalra, A.; Staelin, R.; Zeithaml, V.A. A Dynamic Process Model of Service Quality: From Expectations to Behavioral Intentions. J. Mark. Res.; 1993; 30, pp. 7-27. [DOI: https://dx.doi.org/10.1177/002224379303000102]
100. Gómez-Besteiro, M.I.; Somoza-Digón, J.; Einöder-Moreno, M.; Jiménez-Fraga, M.N.; Castiñeira-Pereira, S.; Feijoo-Fuentes, M.L. Quality of health care perceived by patients in an urban health center in La Coruña [Calidad de atención en salud percibida por los pacientes en un centro de salud urbano de La Coruña]. Enfermería Clínica; 2012; 22, pp. 182-190. [DOI: https://dx.doi.org/10.1016/j.enfcli.2012.04.004]
101. Bustamante, M.A.; Zerda, E.; Obando, F.; Tello, M. Fundamentals of service quality, the SERVQUAL model [Fundamentos de la calidad de servicio, el modelo SERVQUAL]. Rev. Empresarial; 2019; 13, pp. 1-15.
102. Jain, S.K.; Gupta, G. Measuring Service Quality: Servqual vs. Servperf Scales. Vikalpa; 2004; 29, pp. 25-38. [DOI: https://dx.doi.org/10.1177/0256090920040203]
103. Torres Navarro, C.; Jélvez Caamaño, A.; Vega-Pinto, F. Quality assessment in an emergency service using the Servperf model [Evaluación de la calidad en un servicio de urgencia utilizando el modelo Servperf]. Univ. Cienc. Tecnol.; 2014; 18, pp. 38-49.
104. Buitron de la Vega, P.; Losi, S.; Sprague Martinez, L.; Bovell-Ammon, A.; Garg, A.; James, T.; Ewen, A.M.; Stack, M.; DeCarvalho, H.; Sandel, M. et al. Implementing an EHR-based Screening and Referral System to Address Social Determinants of Health in Primary Care. Med. Care; 2019; 57, pp. S133-S139. [DOI: https://dx.doi.org/10.1097/MLR.0000000000001029] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/31095052]
105. Rodríguez Cabrera, A.; Collazo Ramo, M.; Calero Ricard, J.L.; Álvarez Vázquez, L.; Castañeda Abasca, I. Perceptions of older adults and providers about accessibility to health services [Percepciones de adultos mayores y prestadores acerca de la accesibilidad a servicios de salud]. Rev. Cuba. Salud Pública; 2017; 43, pp. 1-12.
106. Olivares, D.E.V.; Chambi, F.R.V.; Chañi, E.M.M.; Craig, W.J.; Pacheco, S.O.S.; Pacheco, F.J. Risk Factors for Chronic Diseases and Multimorbidity in a Primary Care Context of Central Argentina: A Web-Based Interactive and Cross-Sectional Study. Int. J. Environ. Res. Public Health; 2017; 14, 251. [DOI: https://dx.doi.org/10.3390/ijerph14030251] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/28257087]
107. Viego, V.N.; Luján Temporelli, T. Socioeconomic and environmental determinants of arterial hypertension in the adult population of Argentina [Determinantes socioeconómicos y ambientales de la hipertensión arterial en población adulta de Argentina]. Rev. Cuba. Salud Pública; 2016; 42, pp. 27-36.
108. Licea Puig, M.E.; González Calero, T.M. Strategies for the prevention of type 1 diabetes mellitus [Estrategias para la prevención de la diabetes mellitus tipo 1]. Rev. Cuba. Salud Pública; 2013; 39, pp. 733-751.
109. Instituto Nacional del Cáncer. Statistics—Incidence [Estadísticas—Incidencia]. Available online: https://www.argentina.gob.ar/salud/instituto-nacional-del-cancer/estadisticas/incidencia (accessed on 21 April 2022).
110. López Verde, F.; Esteva, M.; Vela Vallespín, C. The family doctor in cancer patient care [El médico de familia en la atención al paciente con cáncer]. Aten Primaria; 2016; 48, pp. 277-278. [DOI: https://dx.doi.org/10.1016/j.aprim.2016.04.001]
111. Esposito, K.; Chiodini, P.; Colao, A.; Lenzi, A.; Giugliano, D. Metabolic Syndrome and Risk of Cancer: A systematic review and meta-analysis. Diabetes Care; 2012; 35, pp. 2402-2411. [DOI: https://dx.doi.org/10.2337/dc12-0336]
112. Abdelwahab Yousef, A.J. Male Breast Cancer: Epidemiology and Risk Factors. Semin. Oncol.; 2017; 44, pp. 267-272. [DOI: https://dx.doi.org/10.1053/j.seminoncol.2017.11.002]
113. Theodoratou, E.; Timofeeva, M.; Li, X.; Meng, X.; Ioannidis, J.P.A. Nature, Nurture, and Cancer Risks: Genetic and Nutritional Contributions to Cancer. Annu. Rev. Nutr.; 2017; 37, pp. 293-320. [DOI: https://dx.doi.org/10.1146/annurev-nutr-071715-051004]
114. Willenbrink, T.J.; Ruiz, E.S.; Cornejo, C.M.; Schmults, C.D.; Arron, S.T.; Jambusaria-Pahlajani, A. Field cancerization: Definition, epidemiology, risk factors, and outcomes. J. Am. Acad. Dermatol.; 2020; 83, pp. 709-717. [DOI: https://dx.doi.org/10.1016/j.jaad.2020.03.126]
115. Elgart, J.; Pfirter, G.; Gonzalez, L.; Caporale, J. Obesity in Argentina: Epidemiology, morbidity and mortality and economic impact [Obesidad en Argentina: Epidemiología, morbimortalidad e impacto económico]. Rev. Argent. Salud Pública; 2010; 1, pp. 6-12.
116. Castronuovo, L.; Tiscornia, M.V.; Gutkowski, P.; Allemandi, L. Obstacles and perceived facilitators for the consumption of fruits and vegetables: A qualitative study [Obstáculos y facilitadores percibidos para el consumo de Frutas y verduras: Estudio cualitativo]. Rev. Arg. Salud Pública; 2019; 10, pp. 14-21.
117. Huang, H.; Yan, Z.; Chen, Y.; Liu, F. A social contagious model of the obesity epidemic. Sci. Rep.; 2016; 6, 37961. [DOI: https://dx.doi.org/10.1038/srep37961] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/27892501]
118. Furones Mourelle, J.A.; Cruz Barrios, M.A.; López Aguilera, A.F.; Broche Villarreal, L.; Jova Boulí, A.P.; Pérez Piñer, J. Adverse drug reactions in Cuban elderly (2003–2013) [Reacciones adversas por medicamentos en ancianos cubanos (2003–2013)]. Rev. Cuba. Salud Pública; 2016; 42, pp. 510-523.
119. Xu, X.; Wang, Q.; Li, C. The Impact of Dependency Burden on Urban Household Health Expenditure and Its Regional Heterogeneity in China: Based on Quantile Regression Method. Front. Public Health; 2022; 10, 876088. [DOI: https://dx.doi.org/10.3389/fpubh.2022.876088]
120. Santos Muñoz, L.; Jiménez López, G.; Alfonso Orta, I. Characterization of adverse drug reactions of low frequency of appearance [Caracterización de las reacciones adversas medicamentosas de baja frecuencia de aparición]. Rev. Cuba. Salud Pública; 2018; 44, pp. 71-85.
121. Amarantou, V.; Chatzoudes, D.; Kechagia, V.; Chatzoglou, P.D. The Impact of Service Quality on Patient Satisfaction and Revisiting Intentions: The Case of Public Emergency Departments. Qual. Manag. Healthc.; 2019; 28, pp. 200-208. [DOI: https://dx.doi.org/10.1097/QMH.0000000000000232]
122. Aliman, N.K.; Mohamad, W.N. Linking Service Quality, Patients’ Satisfaction and Behavioral Intentions: An Investigation on Private Healthcare in Malaysia. Procedia—Soc. Behav. Sci.; 2016; 224, pp. 141-148. [DOI: https://dx.doi.org/10.1016/j.sbspro.2016.05.419]
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; Alvarez-Risco, Aldo 2
; Del-Aguila-Arcentales, Shyla 3
; Rojas-Osorio, Mercedes 3
; Yáñez, Jaime A 4
1 Espacio de Salud y Rehabilitación, Universidad del Gran Rosario, Rosario CP2000, Argentina
2 Carrera de Negocios Internacionales, Facultad de Ciencias Empresariales y Económicas, Universidad de Lima, Lima 15023, Peru
3 Escuela de Posgrado, Universidad San Ignacio de Loyola, Lima 15024, Peru
4 Vicerrectorado de Investigación, Universidad Norbert Wiener, Lima 15046, Peru; Gerencia Corporativa de Asuntos Científicos y Regulatorios, Teoma Global, Lima 15073, Peru