The results of the data analysis over 150 study samples revealed that 75% of women were 34 years old. The majority (43%) of the women and their spouses didn’t have a high school diploma (43%). Most of the women (90.7%) were housewives, and their husbands’ were self-employed (39.7%). Most women (76.8%) reported insufficient income for living cost.
Internal Reliability And Internal Consistency
The analysis of internal reliability of the original tool and related dimensions showed that the original RMC tool was achieved an overall high internal consistency and reliability (α = 0.839). (Table 1). With the exception of the subscale of friendly care, other subscales of the instrument did not have a good internal consistency score in the target population (Table 1).
Table 1
Internal reliability for the Respectful Care Questionnaire and its subscales (N = 150)
| Item-total correlation (r) | Cranach’s Alpha if Item Deleted | Cranach’s Alpha for subscales | Total Cronbach alpha |
Friendly care | 0.839 N = 150 |
Q. 1 I felt that health workers cared for me with a kind approach | 0.709 | 0.764 | 0.813 |
Q. 2 The health workers treated me in a friendly manner | 0.644 | 0.777 |
Q. 3 The health workers talked positively about pain and relief | 0.614 | 0.787 |
Q. 4 The health worker showed his/her concern and empathy | 0.784 | 0.747 |
Q.5All health workers treated me with respect as an individual | 0.552 | 0.795 |
Q. 6The health workers spoke to me in a language that I could understand | 0.343 | 0.825 |
Q. 7The health provider called me by my name | 0.276 | 0.830 |
Abuse- discrimination- Free Care |
Q.8 The health worker responded to my needs whether or not I asked | 0.264 | 0.598 | 0. 469 |
Q.9 The health provider slapped me during delivery for different reasons | 0.458 | 0.332 |
Q.10 The health workers shouted at me because I haven’t done what I was told | 0.347 | 0.283 |
Free Care |
Q.11 I was kept waiting for a long time before receiving service. | 0.646 | -0.010 | 0. 580 |
Q.12I was allowed to practice cultural rituals in the facility. | -0.063 | 0.795 |
Q.13Service provision was delayed due to the health facilities’ internal problem. | 0.675 | -0.059 |
Timely Care |
Q.14Some of the health workers did not treat me well because of some personal attribute. | 0.452 | - | 0.516 |
Q.15 Some health workers insulted me and my companions due to my personal attributed. | 0.452 | - |
Factor Analysis Of The Tool
Factor analysis was used to analyze the questionnaire. The fitness indices obtained Chi-Square = 647/51, Df = 84, p value < 0.0001. As it is presented in Table 2, the results reported that the instrument did not have appropriate fitness indices (Table 2).
Table 2
The Fitting index of Original RMC Tool
Chi-square | 674/51 |
P value | 0/0000 |
df | 84 |
RMSEA | 0.123 |
SRMR | 0.14 |
GFI | 0.84 |
AGFI | 0.77 |
Table 3
Kaiser- Mayer- Olkin Measure of sampling Adequacy | 0.734 |
Barlte’s Test Sphericity Approx. Chi - Square | 1262.405 |
df | 91 |
sig | 0.000 |
LIZREL’s proposed paths for model correction also had little effect on the fitness indices. Therefore, the obtained data were evaluated by exploratory factor analysis. At first, the sample size and its functionality were evaluated using KMO tests, BARTLET TEST OF SPHERCITY (Table 3). The results (Table 3) showed that the KMO was 734, indicating the suitability of the sample size. Bartlett test was significant (p < 0.0001). Next, MAXIMUM LIKELIHOOD and VARIMAX ROTATION were used for exploratory factor analysis (Table 4).
Table 4
Explanatory factor analysis for original version of RMC Tool
factor | Initial Eigen values | Extraction sums of squared loading |
total | % of variance | Cumulative % | total | % of variance | Cumulative % |
RMC 1 | 5.144 | 34.293 | 34.293 | 3.375 | 22.499 | 22.499 |
RMC2 | 2.232 | 14.878 | 49.171 | 2.211 | 14.740 | 37.239 |
RMC3 | 1.466 | 9.774 | 58.944 | 1.983 | 13.221 | 50.461 |
RMC4 | 1.244 | 8.295 | 67.240 | 1.297 | 8.644 | 59.105 |
RMC5 | 1.082 | 7.215 | 74.455 | 0.711 | 4.740 | 63.844 |
RMC6 | 0. 801 | 5.343 | 79.797 | | | |
RMC7 | 0.771 | 5.138 | 84.935 | | | |
RMC8 | 0.525 | 3.502 | 88.437 | | | |
RMC9 | 0.434 | 2.895 | 91.332 | | | |
RMC10 | 0.388 | 2.588 | 93.920 | | | |
RMC11 | 0.286 | 1.905 | 95.826 | | | |
RMC12 | 0.254 | 1.695 | 97.521 | | | |
RMC13 | 0.187 | 1.247 | 98.768 | | | |
RMC14 | 0.152 | 1.017 | 99.784 | | | |
RMC15 | 0.032 | 0.216 | 100.00 | | | |
Table 5
| Factora |
1 | 2 | 3 | 4 | 5 |
RMC 9 | 0.971 | | | | |
RMC 15 | 0.961 | | | | |
RMC 10 | 0.472 | | | 0.353 | |
RMC 4 | | 0.783 | | | |
RMC 3 | | 0.699 | | | |
RMC 5 | | 0.531 | 0.398 | | |
RMC 14 | 0.398 | 0.441 | | | |
RMC 13 | | | 0.913 | | |
RMC 11 | | | 0.722 | | |
RMC 8 | | | 0.526 | | |
RMC 6 | | | 0.423 | | |
RMC 1 | | 0.550 | | 0.639 | |
RMC 2 | | 0.451 | | 0.626 | |
RMC 12 | | | | 0.541 | |
RMC 7 | | | | | 0.949 |
Extraction Method: Maximum Likelihood
Rotation Method: Varimax with Kaiser Normalization
a Rotation Converged in 6 iteration
The results clarified 5 factors with EIGEN VALUES to be higher than one were extracted (Fig. 1) (Table 5) which explained 63.84% of the variance in the references. Examination of the ROTATED FACTOR MATRIX table showed that the Factor 5 had a factor loading only with item 7, and item 7 had no factor loading with any of the items. Since a single item could not form a scale item, it was excluded from the study and a re-exploratory factor analysis was performed with the remaining items (N = 14).
Note
All structural relationships are statistically significant (p < 0.01). For the sake of clarity correlations among exogenous variables and errors are not shown.
In the 14- items instrument, 4 factors with higher eigenvalues were extracted, which explained 60.16% of the variance. (PLOTSCREE chart 1) and ROTATED FACTOR MATRIX table of these factors are as follows (Tables 6, 7, and Chart 1). Obviously, items number 9, 10, 14, and 15 had a factor loading on number one, so the items were defined as Abusive Care. Items 6, 8, 11, and 13 had a factor loading on the number two. Therefore, the above items were defined as the Effective Care dimension. Items number 3, 4, and 5 items had a factor loading on number 3, so the above items were named as Friendly Care. Also, items 12, 2, and1 had a factor loading on number 4, defined as the Respectful Communication dimension.
Table 6
Explanatory factor analysis for Revised version of RMC Tool (14 items)
Factor | Initial Eigen values | Extraction Sums of Squared Loading |
Total | % of Variance | Cumulative (%) | Total | % of Variance | Cumulative (%) |
RMC 1 | 5.080 | 36.285 | 36.285 | 3.661 | 26.150 | 26.150 |
RMC2 | 2.206 | 15.754 | 52.039 | 2.778 | 19.840 | 45.990 |
RMC3 | 1.465 | 10.461 | 62.500 | 1.250 | 8.930 | 54.920 |
RMC4 | 1.156 | 8.259 | 70.759 | .734 | 5.240 | 60.160 |
RMC5 | .802 | 5.727 | 76.486 | 3.661 | 26.150 | 26.150 |
RMC6 | .798 | 5.699 | 82.185 | 2.778 | 19.840 | 45.990 |
RMC7 | .603 | 4.309 | 86.494 | | | |
RMC8 | .520 | 3.716 | 90.210 | | | |
RMC9 | .434 | 3.102 | 93.312 | | | |
RMC10 | .286 | 2.046 | 95.358 | | | |
RMC11 | .267 | 1.906 | 97.264 | | | |
RMC12 | .189 | 1.349 | 98.612 | | | |
RMC13 | .153 | 1.092 | 99.704 | | | |
RMC14 | .041 | .296 | 100.000 | | | |
Table 7
ROTATED FACTORE MATRIX for Revised version of RMC Tool
| Factora |
1 | 2 | 3 | 4 |
RMC 15 | 0.966 | | | |
RMC 9 | 0.961 | | | |
RMC 10 | 0.479 | | | 0.392 |
RMC 14 | 0.411 | | | |
RMC 13 | | 0.913 | | |
RMC 11 | | 0.725 | | |
RMC 8 | | 0.516 | | |
RMC 6 | | 0.426 | | |
RMC 4 | | | 0.846 | |
RMC 3 | | | 0.683 | |
RMC 5 | | 0.400 | 0.531 | |
RMC 1 | | | 0.508 | 0.652 |
RMC 2 | 0.356 | | 0.417 | 0.647 |
RMC 12 | | | | 0.537 |
Extraction Method: Maximum Likelihood
Rotation Method: Varimax with Kaiser Normalization
a Rotation Converged in 5 iteration