Study design
The present research is a cross-sectional study that was conducted with the aim of translating and psychometrically evaluating the Persian version of the “quality of woman-centered midwifery care” labor and childbirth from January to May 2024 in Ahvaz, Southwest Iran.
Demographic questionnaire
Demographic characteristics included age, education, job, income, place of residence, parity and ethnicity of the mothers. These demographic variables were considered important factors for obtaining a comprehensive understanding of sample characteristics and their potential impact on research results.
QWC_MC Scale translation
The QWC_MC Scale was translated following the model proposed by Wild et al (10). Permission for use and translation was obtained from the original developers through email correspondence. This approach included the following steps: translation, reverse translation, expert review, pilot study, correction and summary. The above steps were also followed in the present study. Two translators, proficient in German and Persian, translated the scale into Persian. Their translations were compared and modified to make a final version. Two additional translators, fluent in both the Persian and German languages, back-translated the Persian translation into German. Then, the original tool designer accredited the translated version. The facial validity, content validity, construct validity, internal consistency and scale stability of the translated scale were subsequently validated.
Ethical consideration
The research proposal was approved by the Ethics Committee of Ahvaz Jundishapur University of Medical Sciences (Ethics code: IR.AJUMS.REC.1402.506). After obtaining permission from the main designer of the tool and informed written consent from the participant’s study, the objectives of the research and the confidentiality of the information were shared with the participants.
Sample size
According to researchers, the minimum sample size required is 100-250 people (11); however, some studies determine the size according to the number of items; in this way, they choose 10-20 people for each item or, to determine construct validity, 3 to 10 people are needed for each item in the instrument (11-12). Therefore, considering 10 samples for each item, a sample size of 350 people was calculated.
Participants
The participants included all women who underwent vaginal delivery and who were admitted to the postpartum ward of hospitals (Imam Khomeini, Taleghani and Sina) affiliated with the University of Medical Sciences Ahvaz/Iran and who were selected by the available sampling method. A sample of 350 women completed the Persian version of the QWC-MC Scale for psychometric evaluation. The participants were selected based on the eligibility criteria of the study by means of convenience and purposeful sampling. The inclusion criteria were as follows: age > 18 years, singleton, gestational age > 37 weeks, vaginal delivery, literacy in reading-writing and willingness to participate in the study. The exclusion criteria were high-risk pregnancy (any medical or obstetric problems such as diabetes, high blood pressure, or intrauterine fetal death), hospitalization of the infant and incomplete questionnaires.
Introduction of the QWC-MC Tool
The QWC-MC scale was first developed by Schulz and Wirtz (2021) in Germany to measure the QWC-MC during prenatal care. The scale comprises 33 items categorized into 4 subscales: SDM-Q-9-M with a six-point Likert scale (0 = completely disagree all, 1 = Disagree, 2 = Somewhat disagree, 3 = Somewhat agree, 4 = Agree, 5 = completely agree); E-Q-11-M with a five-point Likert scale and reverse-coded (1 = Fully applies, 2 = Mostly applies, 3 = Occasionally applies, 4 = Hardly applies, 5 = Not apply at all); and TC-Q-5 and PC-Q-8-M with a six-point Likert scale (1 = Not apply at all, 2 = Mostly not apply, 3 = Somewhat not apply, 4 = Somewhat applies, 5 = Mostly applies, 6 = fully applies). The questionnaire scores are in the range of 24–178. Higher scores indicate better QWC-MC. The original scale showed good fit and reliability, with omega coefficients ranging from 0.84 to 0.92 for components and ≥ 0.86 for the overall scale (Table 1) (8).
Table 1
Subscales and scores for the QWC-MC questionnaire
Subscales
|
items
|
Score range
|
Shared Decision-Making
|
9
|
0–45
|
Empathy Midwife
|
11
|
11–55
|
Internal Team cooperation
|
5
|
5–30
|
Professional competence
|
8
|
8–48
|
TOTAL
|
33
|
24–178
|
Table 1- shows that the midwifery care questionnaire is centered on women with 4 scales and scores in the range of 24 to 178.
Descriptive statistics
Data analysis was performed using SPSS version 26 and STATA version 14 software. Descriptive statistics, including frequencies and percentages, were used to report the characteristics of the participants, and the Kolmogorov‒Smirnov test was used to assess the normality of the distribution of the data. Cronbach's alpha coefficient was used for the internal consistency of all questionnaires and subscales. The mean and standard deviation were used to analyze quantitative variables, and the frequency and percentage were used for qualitative variables.
Validity
Face validity
The scale was retranslated into Persian to 20 mothers to evaluate face validity using a qualitative method, and the items were evaluated in terms of difficulty level, appropriateness level and word ambiguity. The quantitative face validity was determined using the item impact method. At this stage, a number of people from the target group are asked to evaluate each item in terms of importance and give each item a score of 1 to 5 according to the importance level. For this purpose, a five-point Likert scale was used for each scale item: 5 = completely important, 4 = important, 3 = moderately important, 2 = slightly important and not 1 = important at all.
In the impact score method, an impact score is obtained by multiplying the frequency of an item (Impact Score = Frequency (%) * Importance). An impact score above 1.5 means that the item was fit for subsequent analyses and will be retained(13).
Content validity
To measure the validity of the content using a qualitative method, 10 university professors (specialists in midwifery and with a background in research in the field of instrument psychometrics from Iran's top universities) were asked to check the scale in terms of the appropriate time for completion, the correctness of the language, the appropriateness of the words and their correction points in writing. After carefully reading their comments, appropriate corrections were made by the research team. Finally, the writing of some items was changed and modified. To evaluate the validity of the quantitative content, two indices, the content validity ratio (CVR) and the content validity index (CVI), were used. A checklist with two sections was designed for each specialist. The first part of the checklist is designed to calculate CVI, and the second section is designed for CVR. The first section of the checklist evaluates the lucidity, simplicity and relation of the items based on a 4-point Likert scale. The second section evaluates the necessity of each item based on a 3-point Likert scale (3 = It is necessary, 2 = it is useful, but it is not necessary, 1 = it is not necessary). The minimum acceptable scores for the CVI and CVR were considered to be higher than 0.79 and 0.62, respectively(14) .
Construct validity
The construct validity is measured using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) (1). EFA was conducted on a sample of 350 mothers. The suitability of the data for EFA was assessed using the Kaiser–Meyer–Olkin (KMO) measure and Bartlett’s test of sphericity. A KMO correlation above 0.60–0.70 is considered adequate for analyzing the EFA output(15). CFA was conducted using STATA version 14 software. Model fit was assessed using several indices, including the no normed fit index (NNFI or TLI), comparative fit index (CFI), chi-square to degrees of freedom ratio, standardized root mean squared residual (SRMR), coefficients of determination (CD), and root mean square error of approximation (RMSEA). These indices are often used to appraise the fit of the CFA model (16). Principal component analysis was used to extract factors, and the eigenvalue method and scree plot were used to determine the number of factors. Varimax rotation was used to determine which variables belonged to which factor and to make the factors interpretable—confirmatory factor analysis.
Reliability
In this study, the internal consistency and consistency reliability methods were used to evaluate the reliability of the questionnaire. To determine the reliability and internal consistency of the instrument, the Cronbach’s α coefficient and the time stability or repeatability of the method (test-retest) were checked. The internal consistency of the scale was calculated using the Cronbach’s α coefficient for the whole questionnaire and then for each subscale. The considered scale will have adequate reliability when the Cronbach’s α coefficient is greater than or equal to 0.7 be(17). with the test-retest method to determine the repeatability. The time interval between the two tests is suggested to be two weeks to one month (18).
For this purpose, the researcher administered the questionnaire to 30 mothers in the postpartum ward in two shifts at an interval of 4 weeks. In the first stage, the questionnaire was completed 24 hours after delivery in the postpartum ward, and in the second stage, it was completed 28 days after delivery when the patients visited health centers with prior coordination or phone calls. This number of mothers was included in the sample. The Spearman-Brown correlation test was used to compare the results of two tests. The correlation between the scores obtained from the two tests was determined with the correlation coefficient (ICC) test, which is the most acceptable test for determining the stability of the test. When this index is between 0.7 and 0.8, the level of stability is favorable (19).