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Keywords:

  • cancer;
  • disparities;
  • satisfaction;
  • psychometrics;
  • measurement;
  • patient navigation;
  • race-ethnicity

Abstract

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. CONFLICT OF INTEREST DISCLOSURES
  7. REFERENCES

BACKGROUND:

Patient satisfaction is an important outcome measure of quality of cancer care and 1 of the 4 core study outcomes of the National Cancer Institute (NCI)-sponsored Patient Navigation Research Program to reduce race/ethnicity-based disparities in cancer care. There is no existing patient satisfaction measure that spans the spectrum of cancer-related care. The objective of this study was to develop a Patient Satisfaction With Cancer Care measure that is relevant to patients receiving diagnostic/therapeutic cancer-related care.

METHODS:

The authors developed a conceptual framework, an operational definition of Patient Satisfaction With Cancer Care, and an item pool based on literature review, expert feedback, group discussion, and consensus. The 35-item Patient Satisfaction With Cancer Care measure was administered to 891 participants from the multisite NCI-sponsored Patient Navigation Research Program. Principal components analysis (PCA) was conducted for latent structure analysis. Internal consistency was assessed using Cronbach coefficient alpha (α). Divergent analysis was performed using correlation analyses between the Patient Satisfaction With Cancer Care, the Communication and Attitudinal Self-Efficacy–Cancer, and demographic variables.

RESULTS:

The PCA revealed a 1-dimensional measure with items forming a coherent set explaining 62% of the variance in patient satisfaction. Reliability assessment revealed high internal consistency (α ranging from 0.95 to 0.96). The Patient Satisfaction With Cancer Care demonstrated good face validity, convergent validity, and divergent validity, as indicated by moderate correlations with subscales of the Communication and Attitudinal Self-Efficacy–Cancer (all P < .01) and nonsignificant correlations with age, primary language, marital status, and scores on the Rapid Estimate of Adult Literacy in Medicine Long Form (all P > .05).

CONCLUSIONS:

The Patient Satisfaction With Cancer Care is a valid tool for assessing satisfaction with cancer-related care for this sample. Cancer 2011. © 2010 American Cancer Society.

Patient satisfaction reflects a core dimension of healthcare quality and patient-centered care.1-3 Patient satisfaction indicates the extent to which patients' healthcare experiences match their expectations.4, 5 The construct of patient satisfaction has been linked to health status, quality of life, adherence to recommended treatment and medical advice including cancer treatment, initiation of complaints, and patient-healthcare provider communication in the clinical dyad.6-16 Patient satisfaction with care represents an important outcome measure for healthcare in general and cancer care in particular.17

Patient satisfaction is 1 of the primary study outcomes of the National Cancer Institute (NCI)-supported Patient Navigation Research Program to reduce disparities in cancer care for individuals from racial/ethnic minorities and lower socioeconomic groups. The Patient Navigation Research Program involves 9 independent research programs operating under cooperative agreements with the NCI Center to Reduce Cancer Health Disparities to evaluate the impact of patient navigation on outcomes among patients with cancer screening abnormalities or diagnosed cancer.18

Although there are numerous patient satisfaction measures, including several measures related to cancer treatment, none of these measures spans the spectrum of cancer-related care from screening to treatment of diagnosed cancer.19-25 For example, the widely used EORTC-IN-PATSAT32 is designed to assess satisfaction with the inpatient cancer care, and FAMCARE assesses satisfaction among those with advanced cancer.20, 24

In the present study, we aimed to develop a Patient Satisfaction With Cancer Care measure that had: 1) sufficient breadth (ie, addressing satisfaction with care during evaluation of screening abnormalities and treatment), 2) the ability to address many of the challenges confronted by poor and minority individuals receiving cancer-related care, and 3) relevance for evaluation of care among both navigated and un-navigated patients.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. CONFLICT OF INTEREST DISCLOSURES
  7. REFERENCES

Development of the Patient Satisfaction With Cancer Care

The scale development team included investigators from different Patient Navigation Research Program sites with content and technical expertise in clinical care of patients from diverse cultural and socioeconomic backgrounds, as well as measurement development and psychometrics. The team reviewed existing patient satisfaction measures, considered various domains of satisfaction (access/logistical, interpersonal/relational, communicational/informational, and coordination of care), and selected and modified existing items for inclusion in the new Patient Satisfaction With Cancer Care scale. One additional item was administered only to participants with a confirmed diagnosis of cancer: “My treatment was explained in a way I could understand.”

Response Options and Scoring

Patients responded to each scale item on a 5-point Likert scale (1 = Strongly Agree to 5 = Strongly Disagree). A total scale score was obtained by adding scores on all items, with lower scores indicating higher satisfaction with cancer care.

Participants

The Patient Navigation Research Program methods have been previously published.18 Briefly, the Patient Navigation Research Program is a cooperative program funded by the NCI and the American Cancer Society to rigorously evaluate the role and benefits of patient navigation among participants with abnormal cancer screening findings or diagnosed cancer-breast, cervical, colorectal, or prostate cancer within 9 largely racial/ethnic minority and low-income communities across the country. Study design and type of cancer differ by participating site.

The satisfaction items were administered to a subsample of the 8075 participants in the Patient Navigation Research Program. In all, 891 English-fluent participants from the multisite NCI-sponsored Patient Navigation Research Program completed the Patient Satisfaction With Cancer Care measure. Survey participants were similar in age, but more likely to be female, minority, lower income, and less educated.

Procedures

Medical staff at the Patient Navigation Research Program recruiting sites (eg, clinics or hospitals) was informed about the study and referred eligible patients to speak with a trained research assistant or patient navigator about participating in the study. To minimize possible effects of low literacy, surveys were read out loud to participants in English.

Eligibility and Exclusion Criteria

Eligibility for the present study included having an abnormal breast, cervical, colorectal, and prostate cancer test finding or a new diagnosis of these cancers without any prior history of cancer treatment other than nonmelanoma skin cancer.18

Additional Measures

Demographic characteristics

Demographic characteristics included age, sex, race, ethnicity, primary language, income, education, marital status, and whether the patient received care related to evaluation of cancer screening abnormalities or treatment of cancer, and type of cancer being evaluated or treated (breast, cervical, colorectal, or prostate).

Communication and Attitudinal Self-Efficacy–Cancer

The Communication and Attitudinal Self-Efficacy–Cancer is a psychometrically validated multidimensional measure (ie, understanding and participating in care, maintaining a positive attitude, seeking and obtaining information) of communication and attitude. Structural analysis of the Communication and Attitudinal Self-Efficacy–Cancer revealed high internal consistency and construct validity.26 Given overlap in constructs, we expected that the Patient Satisfaction With Cancer Care would correlate with the Communication and Attitudinal Self-Efficacy–Cancer.

Data Analysis

Dimensionality analysis of the Patient Satisfaction With Cancer Care

Latent structural and psychometric validation analyses were conducted using the SPSS version 17.0 statistical software package for Microsoft Windows (SPSS Inc., Chicago, Ill). Data from our multisite sample were randomly divided into 2 separate datasets (Sample 1, N1 = 453; Sample 2, N2 = 438) using SPSS. One dataset was used to test the latent structure of the Patient Satisfaction With Cancer Care, and the second dataset was used to validate the said structure. We had a very large sample that facilitated calculation of reliable correlation coefficients for the Patient Satisfaction With Cancer Care. This approach is in accordance with guides on sample sizes for factor analysis/principal components analysis.27, 28 In addition, the principal components analysis (PCA) solutions include many high variables markers and therefore could have facilitated stable and reliable estimates of correlation coefficients with even a smaller sample size.29 Before conducting the PCA, suitability of the data for dimensionality analysis was assessed using various criteria (eg, examination of the correlation matrix for correlations of.30 and above). The PCA was conducted to reduce the data to a few components that could be more easily described. We performed an initial PCA, using Sample 1 data, without rotation to facilitate extraction and examination of meaningful components, based on eigenvalues and scree plot criteria that more accurately describe the latent structure of the Patient Satisfaction With Cancer Care. The Kaiser-Meyer-Olkin value (KMO), an index of sampling adequacy, was used to determine the suitability of the data for dimensionality analysis.30, 31 In addition, we examined the scree plot of eigenvalues to help determine the number of components to retain. We subsequently rotated the initial factor solution using the VARIMAX technique. Items from Sample 2 were also subjected to a PCA to replicate and test the evidence of the structure of the PCA obtained from Sample 1 through successive unconstrained exploratory procedures. We conducted similar PCA for Sample 2 (N2) as described above for Sample 1 (N1).

Measurement reliability analysis

Scale reliability assessment was conducted to determine the degree to which items of the Patient Satisfaction With Cancer Care represent a coherent set that measures the same underlying construct. Cronbach coefficient alpha was used as an index of internal consistency of the Patient Satisfaction With Cancer Care. Measurement reliability analysis was conducted separately for Sample 1 and Sample 2.

RESULTS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. CONFLICT OF INTEREST DISCLOSURES
  7. REFERENCES

The mean age of the analytic sample was 51 years (range, 18-98 years). Most of the sample was female (approximately >80%) and included participants from diverse racial/ethnic backgrounds, including white (43%), black (32%), Hispanic/Latino (23%), Asian (1%), American Indian/Alaska Native (0.5%), and other (0.5%). Half of the sample reported only a high school education or less. Participants presented with abnormal test findings or diagnosis from various types of cancer, including approximately 64% breast, 11% cervix, 12% colorectal, 13% prostate, and 0.5% multiple concurrent cancer sites. Detailed demographic and clinical characteristics of study participants are provided in Table 1. All participants provided informed consent for participation. The institutional review board of all participating institutions approved this study.

Table 1. Demographic and Clinical Characteristics of 891 Participants
CharacteristicNo.Mean (SD)
  1. SD indicates standard deviation.

Age, 18–98 y84351.43 (13.77)
 No.%
Cancer site
 Breast57264.2
 Cervix9610.77
 Colorectal10712.01
 Prostate11212.57
 Multiple concurrent cancer sites40.45
Sex
 Female68681.28
 Male15818.72
Race/ethnicity
 White36043.22
 Black/African American26631.93
 Asian91.08
 American Indian/Alaska Native40.48
 Hispanic or Latino19022.81
 Other40.48
Primary language
 English74087.78
 Spanish8710.32
 Other161.9
Birth country
 United States64782.32
 Other13917.68
Marital status
 Single/never married25630.51
 Married/living as married33940.41
 Divorced/separated19022.65
 Widowed546.44
Education
 8th grade or less698.93
 Some high school10613.71
 High school diploma (including equivalency)19625.36
 Some college/vocational after high school18223.54
 Associate degree587.5
 College graduate10012.94
 Graduate or professional degree628.02
Household income
 Less than $10,00021930.85
 $10,000 to $19,99913418.87
 $20,000 to $29,9998812.39
 $30,000 to $39,999699.72
 $40,000 to $49,999385.35
 $50,000 or more16222.82
Employment status
 No current employment44356.58
 Part-time employment10613.54
 Full-time employment23429.89
Health insurance coverage
 Yes68183.15
 No13816.85

Sample 1, N1—Testing of Patient Satisfaction With Cancer Care Latent Structure

Suitability for factor analysis (Sample 1, N1)

Examination of the items correlation matrix revealed the presence of many correlation coefficients of.30 and higher. In addition, the KMO value was 0.95, exceeding the recommended value of 0.60.30, 31 The Bartlett Test of Sphericity also reached statistical significance (chi-square [2378] = 7850.920; P = .001), which also supported the appropriateness of dimensionality analyses of the correlation matrix.32 Values were skewed toward favorable ratings, with a mean coefficient of skewness of 1.45 (range, −2.2 to −0.5).

Construct validity (Sample 1, N1)

The initial unrotated PCA revealed the presence of 5 components with eigenvalues >1 (λ>1): 12.698, 1.734, 1.383, 1.087, and 1.081, which explained 45.35%, 6.19%, 4.94%, 3.88%, and 3.86% of the total cumulative variance (64.22%), respectively. Inspection of the scree plot revealed a clear break after the second component. Cattell's scree plot test and the eigenvalues criteria suggested that 2 components could be retained for further investigation.33 The components matrix showed that approximately 82% of the items (the first 23 items) loaded on the first component, with factor or component loadings ranging from 0.51 to 0.86. Of these 23 items, 5 loaded on factors 3 to 5, with component loadings ranging from −0.31 to 0.44. Another set of 5 additional items loaded moderately to strongly on factors 2 to 4, with component loadings ranging from 0.33 to 0.92. This second set of 5 items seems related primarily to time waiting at the hospital, transportation and money concerns, and explication of medical tests and health condition. Subsequently, we removed items with moderate loadings on multiple components because of plausible overlapping contributions. We also decided to not include components defined by just 1 or 2 variables, because such components are unstable, generally account for a very small percentage of the variance, and are difficult to correctly interpret.34 On the basis of these criteria, we ended up with a 1-dimensional 18-item Patient Satisfaction With Cancer Care measure, as indicated by a single-component structure with items forming a coherent set that explained 62% of the variance in patient satisfaction with cancer-related care (Table 2). The results of our psychometric analyses support the validity of Patient Satisfaction With Cancer Care for this sample.34, 35

Table 2. Component Loadings for Sample 1 (N1 = 453) and Sample 2 (N2 = 438): Correlations Between Individual Items and the Underlying Component
Patient Satisfaction With Cancer Care Scale ItemsComponent Loadings
Eigenvalue (λ) 14.58Eigenvalue (λ) 15.25
Sample 1Sample 2
  1. Extraction method: principal components analysis.

1. I felt that my health concerns were understood.0.7820.756
2. I felt that I was treated with courtesy and respect.0.7620.739
3. I felt included in decisions about my health.0.8160.751
4. I was told how to take care of myself.0.7410.725
5. I felt encouraged to talk about my personal health concerns.0.7580.715
6. I felt I had enough time with my doctor.0.7740.790
7. My questions were answered to my satisfaction.0.8050.815
8. Making an appointment was easy.0.5490.577
9. I knew what the next step in my care would be.0.6700.745
10. I feel confident in how I deal with the health care system.0.7440.791
11. I was able to get the advice I needed about my health issues.0.8170.851
12. I knew who to contact when I had a question.0.6950.747
13. I received all the services I needed.0.7980.780
14. I am satisfied with the care I received.0.8550.829
15. The doctors seemed to communicate well about my care.0.8300.792
16. I received high-quality care from my regular doctor.0.7230.752
17. I received high-quality care from my specialists.0.8110.803
18. My regular doctor was informed about the results of the tests I got.0.5410.630

Sample 2, N2—Validation of Patient Satisfaction With Cancer Care Latent Structure

Suitability for Factor Analysis (Sample 2, N2)

We tested the emergent structure of the data in Sample 1 by conducting another PCA on data from Sample 2. This approach is based on the notion that successful replication through successive unconstrained exploratory procedures will substantiate the underlying structure of the Patient Satisfaction With Cancer Care beyond any constrained confirmatory procedure. Similar to Sample 1, examination of the correlation matrix for Sample 2 revealed the presence of many correlation coefficients of .30 and higher. In addition, the KMO value was 0.95, exceeding the recommended value of 0.6.30, 31 The Bartlett Test of Sphericity also reached statistical significance (chi-square [2378] = 7853.56; P = .001), supporting the appropriateness of dimensionality analyses of the correlation matrix.32

Construct validity (Sample 2, N2)

The initial unrotated PCA revealed the presence of 5 components with eigenvalues >1 (λ>1): 13.12, 1.76, 1.39, 1.20, and 1.03, which explained 46.87%, 6.31%, 4.96%, 4.28%, and 3.66% of the total cumulative variance (66.09%), respectively. Inspection of the scree plot revealed a clear break after the second component. Cattell's 1966 scree plot test and the eigenvalues criteria supported the retention of 2 components for further investigation.33 Similar to the PCA for Sample 1, the components matrix showed that approximately 82% of the items (the first 23 items) loaded on the first component, with factor or component loadings ranging from 0.48 to 0.86. Of these 23 items, 8 loaded on factors 2, 4, and 5, with component loadings ranging from −0.41 to 0.47. Another set of 5 additional items loaded moderately to strongly on factors 2 to 5, with component loadings ranging from −0.62 to 0.68. Similar to the structure of the Patient Satisfaction With Cancer Care in Sample 1, the second set of 5 items in Sample 2 seemed to involve time waiting at the hospital, transportation and money concerns, and explication of medical tests and health condition. As previously described for Sample 1, we removed items with moderate loadings on multiple components (2 or more) because of issues related to overlapping contribution in Sample 2. Just as in Sample 1, we did not include components defined by just 1 or 2 variables, because such components are unstable, account for a small percentage of the variance, and are difficult to reliably interpret.34 On the basis of these criteria, we also ended up with an 18-item 1-dimensional measure for Sample 2 as indicated by a 1-component structure (Table 2). Results of our structural analyses supported the use of the Patient Satisfaction With Cancer Care as a valid measure for this sample and more importantly confirmed the underlying structure of the Patient Satisfaction With Cancer Care through successive unconstrained exploratory procedures.34, 35

Patient Satisfaction With Cancer Care Reliability and Convergent and Divergent Validity

Scale reliability assessment conducted for the 18-item Patient Satisfaction With Cancer Care

Internal consistency—the degree to which items that make up this scale represent a coherent set that measures the same underlying construct—was evaluated using Cronbach coefficient alpha. The results showed Cronbach coefficient alphas of approximately 0.95 and 0.96 based on standardized items for the Patient Satisfaction With Cancer Care for Sample 1 and Sample 2, respectively. The scale reliability assessment supported the use of the Patient Satisfaction With Cancer Care as a reliable tool of satisfaction with cancer care for this sample.36

Convergent and divergent validity

The Patient Satisfaction With Cancer Care total score for Sample 1 (N1 = 453) correlated with subscales of the Communication and Attitudinal Self-Efficacy–Cancer (Understand and Participate in Care [r = 0.40, P = .001] and Seek and Obtain Information [r = 0.32, P = .004]). The results, however, did not reveal any statistically significant correlation between the Patient Satisfaction With Cancer Care total score and age, primary language, marital status, and scores on the REALM long form (all P values >.05). Likewise, the Patient Satisfaction With Cancer Care total score for Sample 2 (N2 = 438) positively correlated with subscales of the Communication and Attitudinal Self-Efficacy–Cancer: Understand and Participate in Care (r = 0.51, P = .001), Maintain a Positive Attitude (r = .30, P = .01), and Seek and Obtain Information (r = 0.39, P = .001). Again, the analysis revealed no statistically significant correlation between the Patient Satisfaction With Cancer Care total score and age, primary language, or marital status (all P values >.05). Convergent and divergent validity analyses examined the degree to which the Patient Satisfaction With Cancer Care correlates with measures that assess related constructs (eg, the Understand and Participate in Care and the Seek and Obtain Information subscales of the Communication and Attitudinal Self-Efficacy–Cancer) and differ from measures or indices of other unrelated constructs (eg, age, primary language, or marital status), hence confirming that the items of the Patient Satisfaction With Cancer Care formed a coherent set that assesses the specific construct of patient satisfaction with the cancer-related care they received.

DISCUSSION

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. CONFLICT OF INTEREST DISCLOSURES
  7. REFERENCES

We designed the Patient Satisfaction With Cancer Care to be a simple and easy to administer tool to assess satisfaction with cancer-related care for individuals from diverse cultural and socioeconomic populations. An important goal for developing the Patient Satisfaction With Cancer Care was to ensure that the measure assesses experiences common to all patients regardless of whether they were navigated. This approach is expected to ensure the applicability and relevance of this measure to people from comparable racial, ethnocultural, and socioeconomic backgrounds.

The results of our structural analysis and psychometric validation revealed a parsimonious and reliable 1-component solution for the Patient Satisfaction With Cancer Care. This measure provides a milieu-specific patient-oriented approach for assessing perceived relevance and satisfaction with cancer care for individuals from diverse racial, ethnocultural, and socioeconomic backgrounds. The Patient Satisfaction With Cancer Care demonstrates high construct validity. The degree to which the items of the Patient Satisfaction With Cancer Care constitute a coherent set that assesses the underlying construct of patient satisfaction with cancer care was demonstrated by high indices of internal consistency and reliability.

The Patient Satisfaction With Cancer Care differs from previous generic scales in that it focuses on satisfaction with cancer-related care rather than the broader concept of healthcare in general or the narrower concept of cancer treatment for a particular cancer, disease stage, or location (hospital or ambulatory).37-40 The Patient Satisfaction With Cancer Care addresses the broad domain of cancer-related care, including diagnostic testing in addition to treatment rather than focusing on particular or specific aspects of cancer care.41-43

The limitations of these findings merit comment. First, we adapted and modified items from existing instruments, but we did not conduct cognitive interviewing.44 However, a pilot study of the questionnaire revealed no problem that would have indicated a need to modify questionnaire items to help improve participants' understanding or interpretation of the items. In addition, the Patient Satisfaction With Cancer Care scale was administered orally to minimize effects of low literacy; therefore, it is not certain that similar results would be obtained from participants who self-administer the scale.

Second, consistent with previous satisfaction measures, we observed significant skewing or a tendency toward the higher end of satisfaction.45 Whether this represents truly favorable experiences or reflects low expectations is unknown.3 We did not specifically query patients about expectations. For many patients, their abnormal screening/diagnosis may have been their first experience with cancer-related care. Thus, they may have used a priori general healthcare experiences to form their expectations, which could explain the trend toward the higher end of reported satisfaction. This could also represent a social desirability response bias related to interview format.46 Further studies are needed to help determined if this finding will remain if patients respond anonymously and whether this ceiling effect will affect the sensitivity of the scale.

Furthermore, about 80% of the sample were women. Further studies are needed to confirm generalizability of the Patient Satisfaction With Cancer Care to men. Also, the Patient Satisfaction With Cancer Care accounted for 60% of the variance in patient satisfaction. Follow-up studies are needed to identify plausible factors that could account for the unexplained portion of this variance.

Lastly, we did not assess the responsiveness of the measure to change and/or how well it matches clinical impression. That is, we do not know how well the Patient Satisfaction With Cancer Care will capture differences in healthcare processes. Some aspects of care such as interpersonal processes may have a much greater impact on satisfaction than technical aspects.46-48

The strengths of the study include psychometric assessment of the Patient Satisfaction With Cancer Care measure with medically underserved and underrepresented individuals from racial/ethnic minorities and lower socioeconomic populations across different types of healthcare systems (eg, community health centers, Veterans Administration, and university- and community-based oncology practices). The development of the Patient Satisfaction With Cancer Care represents an initial attempt to develop and assess the validity and reliability of a context-specific measure of satisfaction with cancer-related care that is applicable to underserved and traditionally underrepresented racial/ethnic minorities and lower income individuals who face a variety of barriers to cancer care.

Validation of this Patient Satisfaction With Cancer Care measure will facilitate examination of the impact of patient navigation on cancer-related care.12 Further studies should examine the predictive validity of the Patient Satisfaction With Cancer Care for treatment-related outcomes within longitudinal research settings. Our analyses showed divergent and convergent capabilities of the Patient Satisfaction With Cancer Care. Additional studies that examine divergent and convergent characteristics of the Patient Satisfaction With Cancer Care with other relevant psychometrically valid and reliable health measures will provide evidence of the strength of the Patient Satisfaction With Cancer Care and further inform the underlying structure and validity of this measure for cancer patients. This scale, the Patient Satisfaction With Cancer Care, should prove useful for evaluation of patient navigation not only in the participating 9 sites of the NCI funded Patient Navigation Research Program, but in other cancer navigation programs as well.

CONFLICT OF INTEREST DISCLOSURES

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. CONFLICT OF INTEREST DISCLOSURES
  7. REFERENCES

Supported by grants from the National Cancer Institute (3U01CA116924-03S1, U01 CA116924-01, 1R25CA10261801A1, U01CA116892, U01CA 117281, U01CA116903, U01CA116937, U01CA116885, U01CA116875, and U01CA116925) and the American Cancer Society (SIRSG-05-253-01). The contents are solely the responsibility of the authors and do not necessarily represent the official views of the Center to Reduce Cancer Health Disparities, NCI.

REFERENCES

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. CONFLICT OF INTEREST DISCLOSURES
  7. REFERENCES