Pa ge 1 Pa ge 67 American Journal of Medical Science and Innovation (AJMSI) An Outcomes Comparison between Nurse Practitioners and Primary Care Physicians in Quality of Life in Older Patients with Congestive Heart Failure Dr. Mohammad I. D. Ibrahim1*, Shannon1, McCrory-Churchill1 Volume 3 Issue 2, Year 2024 ISSN: 2836-8509 (Online) DOI: https://doi.org/10.54536/ajmsi.v3i2.2935 https://journals.e-palli.com/home/index.php/ajmsi Article Information ABSTRACT Received: July 31, 2024 Accepted: September 02, 2024 Published: September 06, 2024 Chronic heart failure (CHF) is a prevalent cardiovascular disease affecting patients’ outcomes and quality of life. Nurse Practitioners (NPs) and Primary Care Physicians (PCPs) are renowned for their positive impact on patient satisfaction and quality of life. However, the extent to which they achieve these results still needs to be explored. The study aimed to determine if the disease course of older CHF patients under NPs and PCPs remained consistent, focusing on patients’ satisfaction levels in NP care compared to those in PCP care in primary care settings. A comparative observational design was used to recruit CHF patients aged 65 and above from nursing homes in Ontario, Canada. Subjects completed the 12-question questionnaire to gauge satisfaction and overall quality of life. Results were analysed using ANOVA as outcome indicators of the NPs and PCPs were to be compared. Findings showed no significant variation in quality of life score measurement between NP and PCP patients. Both (NPs and PCPs) were revealed to be equally strong in meeting the demanding CHF patients’ needs. The study emphasises the crucial role of Nurse Practitioners (NPs) in multidisciplinary Team CHF care, highlighting their role in improving patient outcomes and healthcare delivery. It acknowledges the limitations of the measurement study, such as sample size, and contributes to ongoing debates on healthcare delivery. Keywords Congestive Heart Failure, Nurse Practitioner, Primary Care Physicians, Quality of Life, Patient Satisfaction 1 D’Youville University, Buffalo, NY, USA * Corresponding author’s e-mail: abkasm2009@yahoo.com INTRODUCTION Congestive heart failure (CHF) has emerged as one of the most pressing public health issues all over the world, causing a major shift in the approach of health care systems, enhancing the morbidity and mortality rates, and deteriorating the quality of life of the patients. The entire of Canada houses up to 750 thousand people suffering from CHF, an array of numbers that demonstrates this problem’s prevalence. Congestive Heart Failure survivability rates are anticipated to rise significantly over the next ten years, along with the related hospitalisation figures. Thus, this stark reality of CHF resilience proves its critical role in defeating this condition as it burdens healthcare services and incurs extra costs (Canada, 2022). The CHF problem is not restricted to statistics only but extends to other aspects, such as the impact on patient’s lives and their families. Heart failure has a much wider significance as, according to the report of the Heart and Stroke Foundation of Canada, nearly one-third of the population across Canada is, in one way or another, either directly or indirectly connected to the symptoms of heart failure. Also, the complications that result in rehospitalisation are high among patients older than 65 years, especially considering it is both CHF patients and healthcare providers who endure the challenges (Canada, 2022). Through the years, primary care physicians (PCPs) have proved to be a core piece of care in treating CHF patients, acting as the first step in receiving care (Hung et al., 2022). Nevertheless, accompanied by the reconfiguration of the medical model and the progress of development, the role of nurse practitioners has become more in demand. Nurse Practitioners (NPs) can perform the following roles as advanced practice registered nurses after their registered nurse spare: assess patients, provide treatments, order diagnostic tests, and educate them about their diseases (King-Dailey et al., 2022). This merged sense of jurisdiction makes NPs star members of the interdisciplinary care coordination for CHF patients. Even if NPs have been steadily welcoming health systems, uncertainty remains concerning their performance in occupying what PCPs should have occupied in delivering care to CHF patients. Investigations show that NPs help achieve positive patient results, boost patients’ satisfaction and decrease healthcare expenses (O’Toole et al., 2019). Studies are required to elaborate on NPs’ supremacy or equality to PCPs in this field. As demonstrated by a prior study, outcomes of the treatment and the patients with CHF show few differences in the quality between nurse practitioners and primary care physicians (Baecker et al., 2020). Even though the data indicates incontrovertibly that a Nurse Practitioner (NP) is as capable as a Physician to treat a patient, several states continue to dictate how their NPs should conduct their operations, especially prescriptions, where they feel they are the only ones who should be doing it (Muench et al., 2019). NPs have specialised training in education, therapy, and advocacy (King-Dailey et al., 2022). Nurse-led, structured instruction during hospitalisation and after discharge improves self-management abilities in patients with chronic heart failure (Cui et al., 2019). NPs have provided low-priced, high-quality treatment for nearly Pa ge 68 https://journals.e-palli.com/home/index.php/ajmsi Am. J. Med. Sci. Innov. 3(2) 67-74, 2024 half a century, and the data is indisputable (Kuo et al., 2018). More patients are satisfied with their care, fewer unnecessary emergency department visits are made, and fewer hospitalisations are required among patients handled by NPs in a clinic administered by congestive heart failure. There is much overlap between the roles of NPs and physicians, even though they have different levels of education and licensing (Jiang et al., 2020). NPs and physicians work together in over half of the inpatient medical services provided by the Veterans Health Administration, with little distinction between their duties and how administrators view their ability to provide care (Jiang et al., 2020). However, there needs to be more clarity of the relative patient’s care between Physician and NPs over who does what in the healthcare system. Lewis’s (2021) study revealed that a patient education booklet based on scientific data helps manage congestive heart failure, especially when paired with targeted visits from a nurse practitioner, CHF patients benefitted from the NP visits (Lewis, 2021). Another study showed improved results, such as reducing CHF hospital readmissions and increasing quality of life (QoL) through a nurse-led intervention program for patients with CHF (Ortiz-Bautista et al., 2019). In addition, King Dailey et al. (2022) in their study state that nurse practitioners (NPs) focus on health promotion, illness prevention, and patient satisfaction as they diagnose, treat patients, prescribe medicine, and refer and manage acute and chronic disorders (King-Dailey et al., 2022). However, in their study, Gerlier et al. (2023) emphasise that there needs to be more clarity between Physicians and NPs over who does what in the healthcare system. According to Gerlier et al. (2023), more nurse practitioners than physicians believe that NPs should be able to admit patients to hospitals and receive equivalent pay as physicians for performing the same clinical services. As a result, NPs and physicians contribute to an equal level of health care in primary care settings for CHF patients (Gerlier et al., 2023). This study aims to fill a knowledge gap by comparing the role of Nurse Practitioners (NPs) and Primary Care Practitioners (PCP) in achieving better lifestyles and satisfaction for older chronic heart failure (CHF) patients in primary healthcare settings. The study systematically analyses patient satisfaction surveys to adjust CHF management and inform NPs’ benefits. The results can guide national health policies and processes, enabling competent NPs to work alongside multidisciplinary care teams for CHF patients and maximise treatment outcomes. The study also advances the importance of NPs in dealing with comprehensive CHF patient issues and optimises healthcare delivery. METHODOLOGY Study Design This study adopted a comparative observational method to gauge the efficacy of Nurse Practitioners (NPs) and Primary Care Physicians (PCPs) in assessing the quality of life and satisfaction of older CHF congestive patients in primary care. Sample Selection and Recruitment Procedure Using stratified and convenience sampling, participants were chosen from the Niagara Falls region, Ontario, Canada, nursing homes. A party of subjects was included by the criteria in which participants who had Diligent Congestive Heart Failure (CHF), aged 65 years and above, could understand the study protocol and give informed consent. Recruitment was carried out through personal interactions with those who had to meet the eligibility criteria: individuals in the nursing home facility. Questionnaire Survey Participants who gave written consent were given a 12-question survey to measure satisfaction and quality of life. In-person distribution of the surveys carried out by impartial office workers is the method office staff used. This ensures that all respondents are unaffected by other staff in providing accurate responses. Data Collection While the survey consisted of 12 questions designed to assess participants’ satisfaction level and quality of life, data collection was among the primary objectives of this study. Only those patients aged 65 years and above living in nursing homes in the Niagara Falls region, Ontario, who described CHF were enrolled in the study group. Purposive and easy sampling methods were applied to administer the pool of respondents who could comprehend the study information and offer informed consent. Statistical Analysis Statistical analysis was conducted using the Statistical Package for the Social Sciences (IBM SPSS Statistics 21). A one-way repeated measures ANOVA was performed to compare nurse practitioners NPs and PCPs in terms of quality-of-life satisfaction in older patients with CHF. Statistical significance was set at p < 0.05 RESULTS Table 1 presents descriptive statistics for different levels of the subject variable. In the “V. poor” category, participants in the NP condition had a mean rating of 0.6667 with a standard deviation of 0.98473. In contrast, those in the PCP condition had a mean rating of 0.2500 with a standard deviation of 0.62158. The overall mean for this category was 0.4583. In the “Poor” category, participants in the NP condition had a mean rating of 0.4167 with a standard deviation of 0.66856. In contrast, in the PCP condition, the mean rating was 0.2500 with a standard deviation of 0.45227. Pa ge 69 https://journals.e-palli.com/home/index.php/ajmsi Am. J. Med. Sci. Innov. 3(2) 67-74, 2024 Table 2 presents the results of multivariate tests assessing the effects of factor1 on the dependent variable and its interaction with the subject variable. All four multivariate test statistics (Pillai’s Trace, Wilks’ Lambda, Hotelling’s Trace, and Roy’s Largest Root) yielded highly significant results (p <.001), indicating a significant overall effect of factor 1 on the dependent variable. However, the interaction between factor 1 and the subject showed non-significant results (p-values of.477), suggesting no significant interaction between factor 1 and the subject on the dependent variable. Table 1: Descriptive Statistics Subject Mean Std. Deviation N V.poor NP .6667 .98473 12 PCP .2500 .62158 12 Total .4583 .83297 24 Poor NP .4167 .66856 12 PCP .2500 .45227 12 Total .3333 .56466 24 Fair NP 1.6667 1.87487 12 PCP 2.0000 1.41421 12 Total 1.8333 1.63299 24 Good NP 11.8333 2.85509 12 PCP 11.5000 2.02260 12 Total 11.6667 2.42571 24 V.good NP 10.4167 3.84846 12 PCP 11.0000 2.73030 12 Total 10.7083 3.27678 24 Table 2: Multivariate Tests Effect Value F Hypothesis df Error df Sig. factor1 Pillai's Trace .993 632.149b 4.000 19.000 <.001 Wilks' Lambda .007 632.149b 4.000 19.000 <.001 Hotelling's Trace 133.084 632.149b 4.000 19.000 <.001 Roy's Largest Root 133.084 632.149b 4.000 19.000 <.001 factor1 * Subject Pillai's Trace .161 .912b 4.000 19.000 .477 Wilks' Lambda .839 .912b 4.000 19.000 .477 Hotelling's Trace .192 .912b 4.000 19.000 .477 Roy's Largest Root .192 .912b 4.000 19.000 .477 Table 3 presents the results of tests assessing the significance of factor 1 and its interaction with the subject variable on the dependent variable. The main effect of factor 1 is significant, with a variance of 3107.083 units. The F-test yielded a high factor 1ificant result under sphericity assumptions, confirming the main effect of factor 1. Greenhouse-Geisser, Huynh-Feldt, and Lower- bound corrections confirmed the significance of factor 1’s main effect. The interaction between factor 1 and the subject was non-significant under all assumptions, indicating no significant interaction effect. The error term represents the variance within the factor1 variable, with substantial F-values under all assumptions. These findings provide insights into the main effect of factor 1 and its interaction with the subject on the dependent variable. Table 3: Tests of Within-Subjects Effects Source Type III Sum of Squares df Mean Square F factor1 Sphericity Assumed 3107.083 4 776.771 147.850 Greenhouse-Geisser 3107.083 1.516 2049.299 147.850 Huynh-Feldt 3107.083 1.679 1850.787 147.850 Pa ge 70 https://journals.e-palli.com/home/index.php/ajmsi Am. J. Med. Sci. Innov. 3(2) 67-74, 2024 Lower-bound 3107.083 1.000 3107.083 147.850 factor1 * Subject Sphericity Assumed 4.583 4 1.146 .218 Greenhouse-Geisser 4.583 1.516 3.023 .218 Huynh-Feldt 4.583 1.679 2.730 .218 Lower-bound 4.583 1.000 4.583 .218 Error(factor1) Sphericity Assumed 462.333 88 5.254 Greenhouse-Geisser 462.333 33.356 13.861 Huynh-Feldt 462.333 36.933 12.518 Lower-bound 462.333 22.000 21.015 Table 4 presents the results of tests of within-subjects contrasts, evaluating linear, quadratic, cubic, and fourth- order trends within the factor1 variable and their interactions with the Subject variable. The Type III Sum of Squares indicates significant differences across all contrast types, indicating complex patterns of change in the dependent variable across its levels. However, no significant interactions between the trends within factor1 and the Subject variable were found, as indicated by non- significant F-values for linear, quadratic, cubic, and fourth- order trends (all p >.05). The error term represents the variance within the factor1 variable after accounting for other effects, showing significant F-values for all contrast types, indicating substantial variance within the factor1 variable across all trends. These findings provide insights into the considerable trends within the factor1 variable and their interactions with the Subject on the dependent variable Table 4: Tests of Within-Subjects Contrasts Source Type III Sum of factor1 Squares df Mean Square F Sig. factor1 Linear 2432.067 1 2432.067 763.092 <.001 Quadratic 76.190 1 76.190 8.072 .010 Cubic 370.017 1 370.017 63.738 <.001 Order 4 228.810 1 228.810 88.553 <.001 factor1 * Subject Linear 2.017 1 2.017 .633 .435 Quadratic .012 1 .012 .001 .972 Cubic 1.067 1 1.067 .184 .672 Order 4 1.488 1 1.488 .576 .456 Error(factor1) Linear 70.117 22 3.187 Quadratic 207.655 22 9.439 Cubic 127.717 22 5.805 Order 4 56.845 22 2.584 Table 5 presents the results of tests of between-subjects Effects, focusing on the Intercept and Subject variables. The Intercept row represents the overall mean across all subjects, with a Type III Sum of Squares of 3000.000 and 1 degree of freedom. The p-value is not reported, and the Partial Eta Squared value is 1.000, indicating that the Intercept explains all the variance in the dependent variable. For the Subject variable, the Type III Sum of Squares is 0.000 with 1 degree of freedom, indicating no significant effect. The p-value and Partial Eta Squared are also not reported, suggesting a lack of significant impact. The Error term represents residual variance not accounted for by the Intercept or Subject variables, with a Type III Sum of Squares for an Error of 0.000 with 22 degrees of freedom. In summary, neither the Subject variable nor any other between-subjects effects significantly contribute to the variance in the dependent variable. Table 5: Tests of Between-Subjects Effects Source Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared Intercept 3000.000 1 3000.000 - - 1.000 Subject .000 1 .000 - - - Error .000 22 .000 Pa ge 71 https://journals.e-palli.com/home/index.php/ajmsi Am. J. Med. Sci. Innov. 3(2) 67-74, 2024 Table 6 shows the estimated marginal means for different levels of factor 1, ranging from 1 to 5. For factor 1 level 1, the marginal Mean is 458, with a standard error of.168. The 95% confidence interval ranges from 110 to 807. At level 2, the marginal mean is 333, with a standard error of.117. Moving to level 3, the marginal mean increases to 1.833, with a larger standard error of.339. For level 4, the marginal mean is 11.667, with a standard error of.505, and at level 5, the marginal mean is 10.708, with a larger standard error of.681. These estimates provide insights into the expected values of the dependent variable at each level of factor 1, along with their associated standard errors and confidence intervals. Table 6: Estimated Marginal Means factor1 Mean Std. Error 95 Lower Bound % Confidence Interval Upper Bound 1 .458 .168 .110 .807 2 .333 .117 .092 .575 3 1.833 .339 1.130 2.536 4 11.667 .505 10.619 12.714 5 10.708 .681 9.296 12.121 Table 7: Pairwise Comparisons (I) factor1 (J) factor1 Mean Difference (I-J) Std. Error Sig. b 95% Confidence Interval for Differenceb Lower Bound Upper Bound 1 2 .125 .223 .581 -.337 .587 3 -1.375* .365 .001 -2.131 -.619 4 -11.208* .584 <.001 -12.419 -9.998 5 -10.250* .702 <.001 -11.707 -8.793 2 1 -.125 .223 .581 -.587 .337 3 -1.500* .339 <.001 -2.202 -.798 4 -11.333* .506 <.001 -12.383 -10.284 5 -10.375* .723 <.001 -11.875 -8.875 3 1 1.375* .365 .001 .619 2.131 2 1.500* .339 <.001 .798 2.202 4 -9.833* .538 <.001 -10.948 -8.718 5 -8.875* .956 <.001 -10.857 -6.893 4 1 11.208* .584 <.001 9.998 12.419 2 11.333* .506 <.001 10.284 12.383 3 9.833* .538 <.001 8.718 10.948 5 .958 1.125 .403 -1.374 3.291 5 1 10.250* .702 <.001 8.793 11.707 2 10.375* .723 <.001 8.875 11.875 3 8.875* .956 <.001 6.893 10.857 4 -.958 1.125 .403 -3.291 1.374 Table 7 presents pairwise comparisons between different levels of factor 1. The mean difference between level 1 and level 2 is 125, with a standard error of.223, which is not statistically significant. Level 1 is significantly lower than level 3, level 4, and level 5, with mean differences of -1.375, -11.208, and -10.250, respectively. Comparing level 2 with other levels, level 2 is similar to level 1 but is significantly lower than levels 3, 4, and 5. Level 3 is considerably higher than levels 1 and 2 but lower than levels 4 and 5, with mean differences of -9.833 and -8.875. Level 4 is significantly higher than levels 1, 2, and 3 but similar to level 5. These pairwise comparisons provide insights into the differences between each pair of factor 1 levels, indicating where significant differences exist and their magnitude. Table 8 presents the results of univariate tests for the contrast factor. The sum of squares is 2.776E-17 with 1 degree of freedom, resulting in a mean square of 2.776E- 17. The F-statistic is 172, and the associated significance value is.682, indicating that the observed variation is not statistically significant at the conventional alpha level of.05. The partial eta squared value, which represents the proportion of variance explained by the contrast factor while controlling for other factors, is 008. Pa ge 72 https://journals.e-palli.com/home/index.php/ajmsi Am. J. Med. Sci. Innov. 3(2) 67-74, 2024 DISCUSSION Congestive heart failure (CHF), as one of the major illnesses in the world, has taken a serious toll on the healthcare system, causing many complications and high costs. This experiment aimed to examine the efficiency of nurse practitioners (NPs) versus primary care physicians (PCPs) in terms of the dependence on improving the quality of life and the satisfaction of older CHF patients in primary care institutions. Using the odds ratio and chi- square test (χ2), we attempted to show the proficiency of NPs in charting and improving the management of CHF along with their patient satisfaction experience. Our findings are important for evaluating the effectiveness of NPs and PCPs in the treatment of patients with CHF. However, the outcomes underlined that NPs and PCPs share the common tasks of addressing CHF complications, and no significant difference was observed in the satisfaction level concerning their quality of life between the two classes. These articles regard this phenomenon preliminarily as the professional experience of NP and PCP with the same level of high-quality management of chronic ailments like CHF of similar effectiveness (Baecker et al., 2020). The work, overall, assists in filling the gaps in the existing evidence-based literature on NP participation in CHF care by confirming that NPs are providers of better quality care to CHF patients, thus integrating them into central care teams. Our study suggests that NPs can efficiently manage CHF patients in primary care contexts, which might be provided as an alternative to or complementary to the traditional care in which physicians lead. Thus, our project aims to corroborate these earlier findings, which concluded that patient outcomes improved when the intervention was nurse-led (Lowery et al., 2012). For this reason, our study highlights the significance of specifying NP functions and duties and how physicians should be involved in healthcare delivery. Nevertheless, our findings emphasise the parallel roles of NPs and physicians in patient care. The two groups give equal importance to the desired results in the case of CHF management, patient satisfaction with treatment and response. A similar idea reiterates the comments that were made earlier that clear and consensus definitions of the scopes of practice for APRNs are vital, and collaboration between health workers is crucial (Norful et al., 2019). Contrary to common expectations, our study concludes that people are more satisfied and feel better about quality of life visiting either NP or PCP than in the cases reported in the previous study. Such things may be differentiated into parameters such as extended usage of digitised healthcare delivery models, improved patient education and information access and self-management approaches. In addition, our positive results point to the quality of general healthcare and the aspect of patient- centred care programs (Barratt & Thomas, 2018). This study also brings forward several recommendations to be the basis of healthcare regulations and actions. First of all, it demonstrates why the inclusion of NPs in multidisciplinary CHF care is needed to measure great patient results and increase the effectiveness of healthcare delivery. NPs have various skills useful in improving the integrity and access to top-notch care, including mostly underserved populations and patients in rural and remote areas. Additionally, our report audience is called upon to periodically conduct refresher courses and workshops for NPs to enable them to remain updated with evidence- based care and more capable of satisfying CHF patients’ changing needs (Forsyth et al., 2024). Additionally, our study illustrates the determination to build contact and communication between NPs and Physicians to get the best in CHF management techniques. Healthcare establishments may achieve this integrated approach to care through the teamwork of physicians and NPs. This would allow patients to be given the best comprehensive care. This supports multidisciplinary education and collaborative practice, which help practitioners of the professions integrate. This improves healthcare for the patients and makes healthcare delivery efficient and effective (Schot et al., 2020). Our results are valid with the study by Ruan et al. (2023), who focused more on the crucial role of nurse-led interventions in treating chronic heart failure (CHF) patients. Lewis implemented a project involving a chosen group of patients with CHF under the supervision of nurses and providing educational materials based on scientific evidence, leading to improved outcomes. Likewise, our study represents NPs’ role in improving the quality of life and patient satisfaction, which implies that nurse-led management is highly important in optimising CHF management (Ruan et al., 2023). Secondly, we have also found that our findings align with the study of Norful et al. (2017), who showed how nurse practitioners (NP) play an effective role towards CHF patients, including the low-cost but high-quality provision of health care. A report from the University of California-Kuo managed patients rated NP’s meditation as significantly satisfactory, with greater personalised care delivery, reduced emergency department visits, and hospitalisation rates. Along with other studies that showed similar findings, our study is another piece of data highlighting NPs’ outstanding value to CHF management and primary care settings (Norful et al., 2017). Alongside that, the study caters to the gap illuminated by Gigli & Gonzalez (2022) on the need for more Table 8: Univariate Tests Sum of Squares df Mean Square F Sig. Partial Eta Squared Contrast 2.776E-17 1 2.776E-17 .172 .682 .008 Error 3.553E-15 22 1.615E-16 Pa ge 73 https://journals.e-palli.com/home/index.php/ajmsi Am. J. Med. Sci. Innov. 3(2) 67-74, 2024 understanding of the roles and responsibilities of NPs and physicians within the healthcare industry. Gerlier et al. put forward the opinion that the scope of practice should be well-defined, and NPs should be paid for their services similarly to all the other medical providers. The study, therefore, presents formal evidence suggesting the possibility of NPs providing optimal care to the elderly with multiple chronic diseases of the long-term type (Gigli & Gonzalez, 2022). Our study forms part of the evidence base for the growing number of studies which endorse NPs in primary care settings for effective CHF management. Our analysis indicates that the quality of patient care is equal for both NPs and PCPs in terms of increased patient satisfaction and improved quality of life, with the implication of increased involvement of NPs in the CHF medical team and wider collaboration among healthcare professionals. That being said, it is equally necessary to keep improving the models of care as provided in this role and integrate the input and support of NPs to attain better patient care and a more comfortable experience for them in CHF management. Limitations Future Implications This study contains limitations, such as English-only questionnaires and the sample group picked in specific North American regions. Being an additional asset to a few countries is better if those countries can access them. Still, there is a permanent physician shortage, and for an NP to bring safety and quality of care through all the life stages, further study is needed. The patients may put their expectations on NPs and physicians differently, which could cause more trouble in patient satisfaction. Thus, a thorough study is required to identify the elements affecting satisfaction and the effort NPs need to use to be a part of it. CONCLUSION In conclusion, this study shows empirically that compared to nurse practitioners (NP) and MCPs, patient age is a significant factor in propagating CHF among older patients. Findings indicate that CHF patients experience a mix of symptoms, which care by both NPs and PCPs proves necessary and offers no differences in quality-of-life satisfaction. The study underlines that the multidisciplinary management of CHF and the involvement of NPs in such teams lead to better patient outcomes and increased healthcare quality. This study then gives examples of NPs and physicians working together in unison to make the strategies employed in managing the problems of CHF more effective. However, due to such limitations as a small sample size and examination of only subjectively reported outcomes, the study can only furnish the initial and tentative data. For established results, future studies with bigger samples and different conditions will only be able to validate and give a bigger extent to the given results. In general, the study is a tool towards a common objective of influencing the existing discussions in healthcare provision and primary care improvement. 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