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. 2025 Jul 31;25:1007. doi: 10.1186/s12913-025-13155-0

Development and validation of tool to assess respectful maternity care practices among healthcare providers

Radha Devi Dhakal 1,2,✉, Regidor III Poblete Dioso 3, Kalpana Sharma 4, Govinda Prasad Dhungana 5
PMCID: PMC12312277  PMID: 40745649

Abstract

Background

Respectful maternity care in healthcare facilities during childbirth is a growing concern around the world. It is more than just an important component of care quality; it is also a human right. The aim of this study was to develop and validate a tool to assess respectful maternity care practices among healthcare providers in Nepal.

Methods

This is a cross-sectional study as part of an explanatory sequential mixed-method research design. The tool was developed using 9 steps in three phases: item development, scale development, and scale evaluation. Tool is a five-point Likert scale containing 36 items. Each item was rated on a 1–5 scale ranging from 1 (strongly disagree) to 5 (strongly agree). The participants were healthcare providers working in maternity units of various healthcare centers of Madhesh Province. The items were analyzed for validity and reliability with exploratory factor analysis. The data were analyzed via the Statistical Package for Social Science version 22.

Results

The content validity index (CVI = 0.895), kappa index and content validity ratio (CVR) were calculated for each item and they were within an acceptable range. Analysis of internal consistency revealed an acceptable Cronbach’s alpha value (0.925) for the 36 item RMCP scale, and seven subscales. The suitability of the data for factor analysis was confirmed by Kaiser-Meyer‐Olkin (0.801), and Bartlett’s test of sphericity was significant (0.000). Principal component analysis with varimax with Kaiser normalization rotation identified 7 factors with eigenvalues greater than one, accounting for 74.55% of the observed variance.

Conclusion

A new tool for respectful maternity care practices has been developed through a rigorous process of item generation and validity-reliability assessment in addition to confirmatory factor analysis to assess the respectful maternity care practices of healthcare providers in Nepal which is statistically proven to be valid and reliable, with an appropriate range of confirmatory factor analysis results. Assessing the RMC practices of health care providers during facility-based maternity care may be relevant.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-025-13155-0.

Keywords: Healthcare provider, Practices, Respectful maternity care, Tool and validity

Background

Respectful maternity care (RMC) in health care facilities during childbirth is an increasing global concern [1]. Respectful maternity care is not only a crucial aspect of quality care; [2]. It is also a human right, and implementing basic nursing care requires respectful care, informed decisions, compassion, and the promotion of human rights [3, 4] Every expected mother in the world deserves to get dignified maternity care [5]. Many women across the world face various forms of abusive, rude, violent, or inattentive care during childbirth in facilities where physical abuse, non consented care, non-confidential, non dignified care, discrimination on the basis of specific patient characteristics is constitute a widespread form of disrespect and abuse (D&A) [6–8].

RMC is an essential component of quality care. Disrespect and abuse; are serious obstacles to the utilization of facility-based maternal health services and diminish the quality of maternity care. Recognizing and addressing mistreatment is a critical component of promoting RMC in health institutions [9, 10]. Intrapartum mistreatment of during childbirth by health professionals is a widespread global public health challenge [11]. Multiple factors at different levels of policy, facility, community, and the individual are also associated with disrespect and abuse [12]. Poor interpersonal communication between client and providers during maternity care at health facilities in low-resource settings is increasingly recognized as a barrier to accessing skilled care for routine and complicated births [13].

The World Health Organization (WHO) guidelines emphasize positive birth experiences through RMC [5]. Healthcare providers and midwives are expected to apply the concept of RMC in their practice setting [14]. Providing friendly, abusive-free, timely, and discriminative-free care is the basis improving the uptake of institutional delivery [15]. Respectful maternity care practices andexperiences during labor and postpartum were previously investigated in Nepal [16–18]. However, a context suitable for RMCP tool development has not yet been developed and validated. Hence this study aimed to develop and validate a tool to assess RMCP among healthcare providers.

Methods

Study design

The study design was cross-sectional as a part of an explanatory sequential mixed method design. The tool was developed using seven categories of disrespect and abuse in childbirth [8], 12 domains of RMC [19], universal rights of childbearing women; adapted [20] and RMC categories by the WHO [7]. This study was done from March 1 st to August 30th, 2024, in various healthcare settings in Madhesh Province. The participants were male and female healthcare practitioners such as auxiliary nurse midwives (ANM), nurses, and midwives who are registered with the Nursing Council of Nepal and currently work in maternity units of various health care centers.

Tool development

The processes described in developing and validating scales for Health, Social, and Behavior Science by Boateng et al. [21]. served as the foundation for our tool’s development. There are 9 steps classified into three main phases: item development (2 steps), scale development (4 steps) and scale evaluation (3steps). In the first phase, items are generated and the validity of the generated content is evaluated. During the second phase, the scale is built including pretesting the questions, administering the survey, reducing the number of items, and extracting the items. In the third phase the number of dimensions, reliability, and validity are all checked. We also adhered to DeVellis‘ [22] guidelines while developing the tool.

Phase one: item development

Step 1: Identify the domain(s) and generate items

Initially, different items are constructed and the domains are defined on the basis of RMC component. A well-defined domain provides an overview of the phenomenon under study, establishes the domain’s limits, and makes item generation and content validation more efficient [23]. An initial broad scoping search was conducted in the primary medical and educational databases. The comprehensive search included both electronic and non-electronic sources. Multiple Medline searches were carried out, along with expert reviews and recommendations. The titles, abstracts, and full texts of relevant papers were selected, screened, and reviewed. Electronic searches of databases including CINAHL, PubMed,, EMBASE, Global Health Library, MEDLINE (Ovid), PsycINFO, Google Scholar, and the Cochrane Library, were perfomed. The Medline search strategy combined MeSH terms that described aspects of the keywords included in the searches were “respectful maternity care”, “respect”, “dignity”, “humanized care”, “disrespect and abuse”, “mistreatment”, “obstetric violence”, “childbirth”, labor, “intrapartum period”, “factors affecting”, “RMC”, “perception, knowledge, attitudes, and practices”, and “healthcare provider”. Following screening, relevant papers were chosen and read thoroughly to locate relevant items. The first author created the initial set of items. A list of common components and RMC items was developed that accurately matched the questionnaire concept.

Step 2: content validity

There is no statistical test to determine the adequacy of content that adequately represents a construct, Content validity usually depends on the judgment of experts in the field. We reviewed our content with 8 experts from Nepal, Malaysia, and India with experience in obstetrics and gynecology, research, midwifery education, SBA trainers, maternity wards in charge, and Biostats. The content validity ratio was calculated with the formula CVR = (Ne-N/2)/(N/2) with 8 expert panel. The experts consulted had between 10 and 45 years of experience in their respective fields. The experts evaluated the instrument items on a 4-point scale for clarity and its relevance 1[not relevant],2[somewhat relevant], 3[quite relevant], and 4[highly relevant]). For six to eight experts at least 0.83 is an acceptable CVI value [24, 25]. The quantitative content validity method was used for the most important and correct content in an instrument, which is quantified by the content validity ratio (CVR), content validity index (CVI) and Kappa coefficient (see Table 2) [25, 26]. Items were changed, amended, added, merged or removed on the basis of recommendations from experts.

Table 2.

Evaluation of content validity index, content validity ratio and modified kappa with different numbers of experts

Items Number of relevancy of item CVR I-CVI* pc** K*** Evaluation
I. Care during Admission
 1. 8 1 1 0.0039 1 Excellent
 2. 7 0.75 0.875 0.031 0.8707 Excellent
 3. 6 0.50 0.75 0.1093 0.719 Good
 4. 8 1 1 0.0039 1 Excellent
 5. 8 1 1 0.0039 1 Excellent
 6. 5 0.25 0.625 0.2187 0.5208 Eliminated
II. Availability of Resources for Care
 7. 8 1 1 0.0039 1 Excellent
 8. 7 0.75 0.875 0.031 0.8707 Excellent
 9. 8 1 1 0.0039 1 Excellent
 10. 5 0.25 0.625 0.2187 0.5208 Eliminated
 11. 6 0.50 0.75 0.1093 0.719 Good
 12. 8 1 1 0.0039 1 Excellent
 13. 8 1 1 0.0039 1 Excellent
III. Care during Labor
 14. 8 1 1 0.0039 1 Excellent
 15. 7 0.75 0.875 0.031 0.8707 Excellent
 16. 8 1 1 0.0039 1 Excellent
 17. 8 1 1 0.0039 1 Excellent
 18. 7 0.75 0.875 0.031 0.8707 Excellent
 19. 6 0.50 0.75 0.1093 0.719 Good
 20. 8 1 1 0.0039 1 Excellent
 21. 7 0.75 0.875 0.031 0.8707 Excellent
 22. 8 1 1 0.0039 1 Excellent
 23. 5 0.25 0.625 0.2187 0.5208 Eliminated
IV Care during Childbirth
 24. 8 1 1 0.0039 1 Excellent
 25. 7 0.75 0.875 0.031 0.8707 Excellent
 26. 5 0.25 0.625 0.2187 0.5208 Eliminated
 27. 8 1 1 0.0039 1 Excellent
 28. 6 0.50 0.75 0.1093 0.719 Good
 29. 8 1 1 0.0039 1 Excellent
V. Immediate Care after Childbirth
 30. 8 1 1 0.0039 1 Excellent
 31. 7 0.75 0.875 0.031 0.8707 Excellent
 32. 8 1 1 0.0039 1 Excellent
 33. 8 1 1 0.0039 1 Excellent
 34. 6 0.50 0.75 0.1093 0.719 Good
 35. 7 0.75 0.875 0.031 0.8707 Excellent
 36. 7 0.75 0.875 0.031 0.8707 Excellent
 37. 8 1 1 0.0039 1 Excellent
VI. Postpartum care
 38. 8 1 1 0.0039 1 Excellent
 39. 7 0.75 0.875 0.031 0.8707 Excellent
 40. 8 1 1 0.0039 1 Excellent
 41. 7 0.75 0.875 0.031 0.8707 Excellent
 42. 8 1 1 0.0039 1 Excellent
VII. Continuity of care
 43. 7 0.75 0.875 0.031 0.8707 Excellent
 44. 6 0.50 0.75 0.1093 0.719 Good
 45. 8 1 1 0.0039 1 Excellent
 46. 8 1 1 0.0039 1 Excellent
 47. 5 0.25 0.625 0.2187 0.5208 Eliminated
 48. 7 0.75 0.875 0.031 0.8707 Excellent
Overall scale S-CVI/Ave 0.895
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*I-CVI: item-level content validity index,**pc (probability of a chance occurrence), ***K (Modified Kappa)

Phase 2: scale development

In Step 3, the questions were pretested. Pre-testing ensures that survey items are meaningful to the target group [22]. Pretesting a questionnaire helps ensure that the respondents understand the questions with phrasing, clarity, simplicity, comprehensibility, and acceptance in use [27]. The subsequent draft version of the questionnaire was pretested on 10% of the target population’s characteristics [28]. The response options were evaluated via a 5-point Likert scale on the RMCP, with the assumption of equal distance between answer items. Following the pretesting, the questionnaire was further refined. Few items were removed after the cognitive interviews due to a lack of clarity and less importance in context. On the basis of responses, we modified the grammar, word choice, and answer alternatives. In Step 4, the survey administration and sample size estimation were completed. The survey was carried out via a self-administered questionnaire. The researcher visited the health care facility and asked the participants to complete the questionnaire. Little statistical research in education and behavior science has shed light on the challenge of determining a minimum desired sample size [29]. Various sample size estimation approaches provide different explanations for scale development. Because our study population was limited in size and had to meet particular inclusion criteria, obtaining a large sample population was difficult, thus we used 100 similar populations as a sample size. The rule of 100 is also supported by the literature, of which [30] recommended at least 100 sample populations. Even if there are just 20 variables, no sample size should be less than 100 [31].

In Step 5 and Step 6 involve item reduction and item extraction which were is performed to ensure that only necessary, functional, and internally consistent items are included [32]. IBM SPSS 22 was used for the statistical analysis, and each item was specified for loading. Exploratory factor analysis (EFA) was used for extraction based on principal component analysis (PCA), as was rotation method which is based on Varimax with Kaiser normalization (See Table 4). In the factor analysis scree plots, exploratory factor analysis, and inter item/item communality analysis were performed (shown in Table 3.) Here we used the Kaiser criterion (eigenvalues > 1) along with the scree plot to determine the number of components.

Table 4.

KMO and bartlett’s test

KMO and Bartlett’s Test
Kaiser-Meyer Olkin Measure of Sampling Adequacy. 0.801
Bartlett’s Test of Sphericity Approx. Chi-Square 4333.534
df 630
Sig. 0.000
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Table 3.

Factor loading of each item based on varimax matrix rotation

S. N Items Loading Com
I. Care during Admission
 1. I speak politely and in an understandable language with the laboring woman and her companion. 0.709 0.963
 2. I allow laboring woman to keep companion as her preference. 0.750 0.916
 3. I orient the laboring woman around the maternity unit. 0.646 0.945
 4. I obtain consent before the procedure. 0.648 0.942
II. Availability of Resources for Providing Care
 5. I provide delay service due to a lack of admission beds and supplies 0.914 0.947
 6. I leave laboring women alone in the waiting room when I am busy in the labor room due to a lack of staff 0.789 0.914
 7. I pay attention to laboring women’s safety and shout for help if any emergency arises 0.816 0.90
 8. I conduct postpartum counseling sessions in a private area 0.776 0.977
 9. I refer the mother or newborn due to a lack Special care (ICU, NICU) 0.769 0.893
III. Care during Labor
 10. I introduce myself to the laboring woman 0.742 0.903
 11. I allow laboring women to move during labor. 0.788 0.677
 12. I provide laboring women with correct and clear information about care, procedures, and interventions. 0.879 0.667
 13. I provide periodic updates about the progress of labor to the laboring woman and her companion. 0.704 0.570
 14. I cover the laboring woman’s body during examinations 0.884 0.645
 15. I support laboring women by encouraging and calming touch. 0.786 0.943
IV Care during Childbirth
 16 I allow laboring women to choice her birthing position 0.627 0.919
 17. I threat laboring women with poor outcomes if they did not comply with instructions 0.798 0.837
 18. I shout at laboring women if she does not cooperate. 0.813 0.927
 19. I push the woman’s abdomen down (fundal pressure) to facilitate the fetal head delivery 0.916 0.552
 20. I use local anesthesia to suture the woman’s perineum 0.876 0.838
V. Immediate Care after Childbirth
 21. I put the newborn on skin-to-skin contact with laboring women in normal delivery 0.766 0.881
 22. I do not discriminate against the baby in terms of gender 0.883 0.804
 23. I perform newborn examinations and consultations if need. 0.870 0.896
 24. I keep the mother clean and comfortable, immediate after childbirth 0.537 0.820
 25. I respect the beliefs and culture of a childbirth woman and her companions. 0.850 0.848
 26. I keep the immediate childbirth records 0.772 0.932
 27. I provide equal care to all women, irrespective of their socioeconomic status, ethnicity, education, residence, language, disease, etc. 0.697 0.904
VI. Postpartum care
 28. I encourage the mother and her companion to ask if any help and care required for the mother and baby. 0.902 0.807
 29. I encourage mothers to early breastfeeding and its importance. 0.751 0.629
 30. I instruct mother to maintain perineal hygiene and for regular urine void. 0.664 0.733
 31. I encourage mother to take high fiber and protein rich diet 0.876 0.729
 32. I explain mothers about maternal and newborn danger signs. 0.816 0.828
VII. Continuity of care
 33. I suggest mother to visit nearest MCH clinic for newborn vaccination and family planning services 0.855 0.914
 34. I encourage mother for postnatal visit as per protocol and in any emergency condition. 0.887 0.861
 35. I ensure that mother receive an institutional delivery incentives during discharge. 0.774 0.971
 36. I ensure that the mother’s files is stored in the record section at the time of discharge 0.855 0.844
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Notes: Extraction Method - Principal Component Analysis; Rotation Method - Varimax with Kaiser Normalization,Com = Communalities in Table 3 Exploratory factor analysis (Table 3) and Cronbach’s alpha (Table 6) for internal consistency are employed to extract the dimensions and to test the validity and reliability of scale. Prior to conducting the PCA inter-item correlation coefficients were calculated. Four additional items were omitted for (2) less than 0.5 coefficients values, and during the extraction process, two items were deleted due to cross-factor loading issues (< 0.4) (see Table 3). The values of KMO range between 0 and 1. Any value close to 1 indicates that the patterns of correlation are compact and reliable factors [37]. According to Kaiser [38], KMO values between 0.7 and 0.8 are good; values between 0.8 and 0.9 are great; and values above 0.9 are superb. Table 4 shows that Kaiser-Meyer Olkin (KMO) was used to measure sampling adequacy (MSA) > 0.60, which is mediocre [39]. The suitability of data for factor analysis was confirmed by KMO, (0.801) and Bartlett’s test of sphericity was significant (0.000) [40]

Phase III: scale evaluation

This phase includes steps 7, 8 and 9; In step 7 the dimensionality findings were analyzed to validate whether the preceding hypothetical structure fits the items. Scale scores for substantive analysis include the reliability and validity of the scale [23]. In step 8 reliability is checked, which is the ability of tool testing to maintain the consistency of outcomes over multiple testing [33]. The internal consistency of each item of different subscales was assessed via Cronbach’s alpha as intercorrelation coefficient (see Table 5) In step 9, validity refers to the extent to which a test will measure what it is designed to measure [33]. In this study, it was determined by looking at and measuring face validity, and content validity. Eight experts were consulted to measure whether each of the items constituted the domain for content relevance, representativeness, and technical quality and the CVR, CVI and kappa were calculated.

Table 5.

Total variance explained by initial eigenvalues

Component Initial Eigenvalues
Total % of Variance Cumulative %
1 10.688 29.688 29.688
2 4.369 12.136 41.825
3 3.470 9.639 51.463
4 2.952 8.199 59.662
5 2.118 5.883 65.545
6 1.666 4.628 70.174
7 1.577 4.382 74.555
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Data management and analysis

The researcher checked, reviewed, and categorized the collected data on a daily basis to ensure accuracy and completeness. The responses from the completed questionnaires were coded and entered into EPI Info 7 and exported in SPSS version 22 for analysis. The data were analyzed via both descriptive (frequency, mean, standard deviation) and inferential statistics. Descriptive statistics were used to analyze participant demographic details. Scale items were analyzed for validity by testing for content, and construct validity, reliability, and exploratory factor analysis (EFA). The internal consistency reliability was calculated via Cronbach’s alpha coefficient for the total scale and subscales, using values above 0.7 [34]. In this study Cronbach’s alpha coefficient of overall RMCP scale was above 0.883 and each four scale has above 0.70 score. Exploratory Factor Analysis (EFA) has used for extraction based on principal component analysis (PCA) and the rotation method which is based on Varimax with Kaiser normalization. The Kaiser-Meyer‐Olkin (KMO) test was used to measure sampling adequacy.

Ethical considerations

Ethical approval was obtained from the Nepal Health Research Council (NHRC -Registration No. 71-2024). Written informed consent was obtained prior to data collection. The data were collected from March 1 st to August 30th, 2024 via a self-administered questionnaire. The purpose and objectives of the study were clearly and understandably communicated to the participants. Prior to data collection, confidentiality was guaranteed by keeping information private unless it was needed for the study. The study permitted participants to opt out if they desired.

Results

As shown in Table 1, the majority (56%) of the participants were under the age of 30. The participants’ average age was 33.01years (SD = 11.39, range = 20–65 years). The most of the participants, (66%) were married. Only half (54) of the participants worked as staff nurses, with 55% having temporary jobs. In terms of training, 53% had received SBA training, where as 49% had less than 5 years of experience.

Table 1.

Characteristics of participants (n = 100)

Characteristic Categories Frequency(Percent)
Age group in years < 30 56
≥ 30 44
Mean:33.01,SD:11.39,Min;20 max 65
Marital status Married 66
Unmarried 34
Qualification Master 7
PBN/BSN 19
Staff Nurse 50
ANM 24
Work experience Up to 5 year 49
6–10 year 17
11–15 year 13
16–20 year 10
Above 20 year 11
SBA Trained Yes 53
No 47
Working position Maternal and child worker 2
ANM 35
Staff nurse 54
Nursing officer 5
Nursing Administrator 4
Work status Permanent 39
Temporary 55
Daily wages 6
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Table 2 summarizes the CVR, I-CVI, S-CVI, and modified Kappa values. First the questionnaire included 58 items, which were reviewed by 8 experts. All the feedback and suggestions were adopted in the questionnaire for qualitative content validity. After the first round of expert judgment, only 48 items were considered. The content validity ratio was calculated with the formula CVR = (Ne-N/2)/(N/2) with 8 expert panel. The items with a CVR greater than 0.49 remained on the tool and the remaining 5 items were eliminated. The overall scale S-CVI/Ave value was 0.895. The kappa statistic is an important supplement to the CVI because it provides information about the degree of agreement beyond chance [26, 35]. For kappa calculation pc (probability of a chance occurrence) was computed via following the formula: pc= [N!/A! (N -A)!] 0.5 N where N = number of experts and A = number of experts who agree that the item is relevant. Kappa was subsequently computed by entering the numerical values of the probability of chance agreement (PC) via the following formula: K= (I-CVI - PC)/(1- PC). Out of 43 items 37 had excellent Kappa values. The evaluation criteria for kappa are values above 0.74, between 0.60 and 0.74, and those between 0.40 and 0.59 are considered excellent, good, and fair, respectively [26, 36]. Three items with good values were further merged with similar type items resulting in a total of 40 items.

In Table 3 Principal component analysis (PCA) with a rotation method based on Varimax revealed nine factors with eigenvalues exceeding 1 that accounted for 81.37% of the observed variance. Some criteria say that the total variance explained by all components should be between 50 − 60% variance [28]. However, the scree plot graph suggested that a nine-factor solution could be considered. We included only seven factors which has 74.55% of the observed variance because they provided more meaningful and theoretical support. Components with larger eigenvalues explain more variance.

In Table 5, the first component has highest percentage (29.688) of total variance, and the last component has 4.382%, as shown in Fig. 1 where the largest drop Component 4, where we can see an “elbow” joint [28]. This is the marking point where it’s perhaps not too beneficial to continue further component extraction [41].

Fig. 1.

Fig. 1

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Scree plot

In Table 6, reliability was calculated via internal consistency method and Cronbach’s alpha values above 0.7 were considered acceptable [34]. The Analysis of internal consistency revealed a good Cronbach’s alpha value of 0.925 for 36 items RMCP scale, and the subscales have 0.790, 0.764, 0.707, 0.779, 0.738, 0.704, and 0.818 respectively for care during admission, the availability of resources for care, care during labor, care during childbirth, immediate care after childbirth, postpartum care and continuity of care after childbirth respectively.

Table 6.

Descriptive statistics, and reliability of RMC scale

Scale No. of Item Mean SD Min Max Range Cronbach’s Alpha
RMCP (Total) 36 67.91 14.700 46 101 55 0.925
Care during admission 4 6.51 2.410 4 12 8 0.790
Availability of resources for care 5 9.74 3.937 5 18 13 0.764
Care during labor 6 11.64 3.865 6 21 15 0.707
Car4 during childbirth 5 9.70 4.073 5 21 18 0.779
Care Immediate after birth 7 13.06 4.672 7 25 18 0.738
Postpartum care 5 9.92 3.873 5 20 15 0.704
Continuity of car 4 7.34 3.450 4 17 13 0.818
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Discussion

In this study, we developed a tool to assess healthcare providers’ respectful maternity care practices (RMCP-tool) at a healthcare institution in Nepal. We obtained the tool’s face validity, content validity, and reliability, as well as a confirmatory factor analysis, which revealed an acceptable range. Initially, the experts examined the draft tool, consisting of 58 items, on a 4-point scale for clarity and relevancy of the items to the local context. The final RMCP tool has 36 items with seven subscales: care during admission, availability of resources, care during labor, care during childbirth, immediate care after childbirth, postpartum care and continuity of care after childbirth. Analysis of internal consistency revealed an acceptable Cronbach’s alpha value for the 36 item RMCP scale, and its seven subscales. This RMCP tool is statistically valid and reliable, with an appropriate range of confirmatory factor analysis.

Previous RMC tool related studies have been conducted in Iran, Ghana, USA, Austerilia, and Ethiopia [42–46] aimed address care recpients perspectives and experiences with RMC care. Most of the scales examine women’s experiences with decision-making during maternity care, quality, safety, and human rights during childbirth; verbal abuse-free, discriminatory-free, and dignified care; physical and psychological abuse-free care; and compassionate care throughout labor, delivery, and postpartum.

There is no analogous tool for assessing the RMCP. There was only study on the Midwives’ Knowledge and Practice Scale on Respectful Maternity Care (MKP-RMC), which assessed RMC knowledge and practice in midwives by Moridi, M. et al. [47]. The scale contains 23 items in the knowledge section and 23 items in the practice section, which are grouped into three categories: providing emotional support, providing safe care, and preventing mistreatment. However, our tool includes a variety of items and subscales to measure RMCP by health care providers in the health care setting.

The study’s limitations include the fact that it only took place at the selected health facilities in province 2. This research focuses only on healthcare providers’ perceptions and practices. The questionnaire includes additional categorized elements, but the experiences of care recipient who have received care from diverse healthcare providers are not included. Their inputs help to determine the overall quality of RMC, which is lacking in this study. However, the study with a large sample from different settings might require for further validation.

Conclusion

This new RMCP tool, containing 36 items, was formulated to assess respectful maternity care practices by healthcare providers at health institutions in Nepal. This tool is statistically valid and reliable, with an appropriate range of confirmatory factor analysis. It can be useful to assess the RMC practices of healthcare providers during maternal care in healthcare settings. The findings of this study can be helpful in better understanding the challenges and solutions to implementing RMC services effectively. Further findings of the study may be useful to future scholars as a reference for future research in the same area.

Supplementary Information

Supplementary Material 1. (44.3KB, docx)

Acknowledgements

The researchers thank all the participants and assisted in data collection for the study. The researchers are extremely grateful to all the participants who took part in this study.

Authors' contributions

RD contributed to the conception and design of the work, to data analysis and interpretation, drafted and critically revised the manuscript. RPD contributed to the analysis of data and critically revised the manuscript. KS contributed to data acquisition and interpretation and critically revised the manuscript. GD contributed to the design of the work, data analysis to interpretation and critically revised the manuscript. All authors reviewed the manuscript and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All the authors read and approved the final version of the manuscript.

Funding

self-funded.

Data availability

The data that support the findings of this study are availability from the corresponding author on reasonable request because the scope of the data and consent obtained from study participants restricts our ability to share the data on ethical and legal rules.

Declarations

Ethics approval and consent to participate

The study was conducted in accordance with ethical standards of Nepal Health Research Council and institutional research committee, as well as with the 1964 Helsinki declaration and with its later amendments. Ethical approval was obtained from Nepal Health Research Council (NHRC -Registration No. 71-2024). Written informed consent was obtained prior to data collection.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  • 1.Ige WB, Cele WB. Barriers to the provision of respectful maternity care during childbirth by midwives in South-West, nigeria: findings from semi-structured interviews with midwives. Int J Afr Nurs Sci. 2022;17:100449. [Google Scholar]
  • 2.Reis V, Deller B, Catherine Carr CN, Smith J. Respectful maternity care. Country experience. 2012. https://content.sph.harvard.edu/wwwhsph/sites/2413/2016/12/RMC-Survey-Report_0.pdf.
  • 3.International Council of Nurses. The ICN code of ethics for nurses. https://www.icn.ch/sites/default/files/2023-06/ICN_Code-of-Ethics_EN_Web.pdf. Accessed March 2024.
  • 4.International Confederation of Midwives. Philosophy and model of midwifery care. https://policycommons.net/artifacts/1763154/cd2005_001-v2014-eng-philosophy-and-model-of-midwifery-care/2494800/(2014). Accsessed Jan 2024.
  • 5.Ministry of Public Health.Respectful Maternity Care Orientation Package for Health Care. Providers Participants Guide. 2017. https://platform.who.int/docs/default-source/mca-documents/policy-documents/operational-guidance/afg. Accesed Oct 2023.
  • 6.Silal SP, Penn-Kekana L, Harris B, Birch S, McIntyre D. Exploring inequalities in access to and use of maternal health services in South Africa. BMC Health Serv Res. 2012;12:1–2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.World Health Organization. WHO recommendations on intrapartum care for a positive childbirth experience. World Health Organization; 2018. [PubMed]
  • 8.Bowser D, Hill K. Exploring evidence for disrespect and abuse in facility-based childbirth: report of a landscape analysis. Washington, DC: USAID–TRAction Project; Harvard School of Public Health; University Research Co. LLC; 2010. https://collective.coloradotrust.org/wp-content/uploads/sites/2/2020/02/Respectful_Care_at_Birth_9-20-101_Final1.pdf.
  • 9.World Health Organization. WHO recommendations on antenatal care for a positive pregnancy experience. In WHO recommendations on antenatal care for a positive pregnancy experience. 2016. [PubMed]
  • 10.Nyirenda HT, Mulenga D, Nyirenda T, Choka N, Agina P, Mubita B, Chengo R, Kuria S, Nyirenda HB. Status of respectful maternal care in Ndola and Kitwe districts of Zambia.
  • 11.Sheferaw ED, Kim YM, Van Den Akker T, Stekelenburg J. Mistreatment of women in public health facilities of Ethiopia. Reproductive Health. 2019;16:1–0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Nawab T, Erum U, Amir A, Khalique N, Ansari MA, Chauhan A. Disrespect and abuse during facility-based childbirth and its sociodemographic determinants–A barrier to healthcare utilization in rural population. J Family Med Prim Care. 2019;8(1):239–45. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Gebrehiwot T, Goicolea I, Edin K, Sebastian MS. Making pragmatic choices: women’s experiences of delivery care in Northern Ethiopia. BMC Pregnancy Childbirth. 2012;12:1–1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Dzomeku VM, Mensah AB, Nakua EK, Agbadi P, Okyere J, Donkor P, Lori JR. Promoting respectful maternity care: challenges and prospects from the perspectives of midwives at a tertiary health facility in Ghana. BMC Pregnancy Childbirth. 2022;22(1):451. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Bante A, Teji K, Seyoum B, Mersha A. Respectful maternity care and associated factors among women who delivered at Harar hospitals, Eastern ethiopia: a cross-sectional study. BMC Pregnancy Childbirth. 2020;20:1–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Poudel S, Deepti KC, Shrestha S. Perceived experience of respectful maternity care among mothers attending a selected teaching hospital of Kaski district. J Gandaki Med College-Nepal. 2022;15(1):74–9. [Google Scholar]
  • 17.Munikar S, Chalise M, Dhungana R, Shrestha DL, KC NP, Dhungana A, Clark RB, Visick MK, Thapa K. Perceived disrespect and abuse among women delivering at a tertiary care center in Nepal. medRxiv. medRxiv. 2021;27:2021–1. [Google Scholar]
  • 18.Pathak P, Ghimire B. Perception of women regarding respectful maternity care during facility-based childbirth. Obstet Gynecol Int. 2020;2020(1):5142398. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Shakibazadeh E, Namadian M, Bohren MA, Vogel JP, Rashidian A, Nogueira Pileggi V, Madeira S, Leathersich S, Tunçalp Ӧ, Oladapo OT, Souza JP. Respectful care during childbirth in health facilities globally: a qualitative evidence synthesis. BJOG: Int J Obstet Gynecol. 2018;125(8):932–42. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Alliance WR. Respectful maternity care: the universal rights of women and newborns. Suite: One Thomas Circle NW; 2019. p. 200. [Google Scholar]
  • 21.Boateng GO, Neilands TB, Frongillo EA, Melgar-Quiñonez HR, Young SL. Best practices for developing and validating scales for health, social, and behavioral research: a primer. Front Public Health. 2018;6:149. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.DeVellis RF, Thorpe CT. Scale development: theory and applications. 5th ed. Thousand Oaks, CA: Sage Publications; 2021. https://elib.vku.udn.vn/bitstream/123456789/5114/1/2022.%20Scale%20Development%20Theory%20and%20Applications%20%28Fifth%20E.
  • 23.McCoach DB, Gable RK, Madura JP. Instrument development in the affective domain. New York: Springer; 2013. p. 9. [Google Scholar]
  • 24.Lynn MR. Determination and quantification of content validity. Nurs Res. 1986;35(6):382–6. [PubMed] [Google Scholar]
  • 25.Polit DF, Beck CT. The content validity index: are you sure you know what’s being reported? Critique and recommendations. Res Nurs Health. 2006;29(5):489–97. [DOI] [PubMed] [Google Scholar]
  • 26.Polit DF, Beck CT, Owen SV. Is the CVI an acceptable indicator of content validity? Appraisal and recommendations. Res Nurs Health. 2007;30(4):459–67. [DOI] [PubMed] [Google Scholar]
  • 27.Sekaran U. Research methods for business: A skill building approach.
  • 28.A Practical Introduction to Factor Analysis. Exploratory Factor Analysis. https://stats.oarc.ucla.edu/spss/seminars/introduction-to-factor-analysis/a-practical-introduction-to-factor-analysis/. Accessed Oct 2024.
  • 29.MacCallum RC, Widaman KF, Zhang S, Hong S. Sample size in factor analysis. Psychol Methods. 1999;4(1):84. [Google Scholar]
  • 30.Gorsuch RL. Factor analysis: classic edition. Routledge; 2014. p. 27.
  • 31.Hatcher L, O’Rourke N. A step-by-step approach to using SAS for factor analysis and structural equation modeling. Sas Institute; 2013. p. 1.
  • 32.Thurstone LL. Multiple factor analysis. Psychol Rev. 1931;38(5):406. [Google Scholar]
  • 33.Kimberlin CL, Winterstein AG. Validity and reliability of measurement instruments used in research. Am J health-system Pharm. 2008;65(23):2276–84. [DOI] [PubMed] [Google Scholar]
  • 34.Bland JM, Altman DG. Measuring agreement in method comparison studies. Stat Methods Med Res. 1999;8(2):135–60. [DOI] [PubMed] [Google Scholar]
  • 35.Fakhr-Movahedi A, Salsali M, Negharandeh R, Rahnavard Z. A qualitative content analysis of nurse–patient communication in Iranian nursing. Int Nurs Rev. 2011;58(2):171–80. [DOI] [PubMed] [Google Scholar]
  • 36.Cicchetti DV, Sparrow SA. Developing criteria for Establishing interrater reliability of specific items: applications to assessment of adaptive behavior. Am J Ment Defic. 1981;86(2):127–37. [PubMed] [Google Scholar]
  • 37.Field AP. Is the meta-analysis of correlation coefficients accurate when population correlations vary? Psychol Methods. 2005;10(4):444. [DOI] [PubMed] [Google Scholar]
  • 38.Kaiser HF. An index of factorial simplicity. Psychometrika. 1974;39(1):31–6. [Google Scholar]
  • 39.Cerny BA, Kaiser HF. A study of a measure of sampling adequacy for factor-analytic correlation matrices. Multivar Behav Res. 1977;12(1):43–7. [DOI] [PubMed] [Google Scholar]
  • 40.Dhakal B, Sthapit AB, Khanal SP. Factor analysis of local residents’ perceptions towards social impact of tourism in Nepal. Int J Stat Appl Math. 2017;2(6):1–8. [Google Scholar]
  • 41.Wetzel AP. Factor analysis methods and validity evidence: a systematic review of instrument development across the continuum of medical education. Virginia Commonwealth University; 2011. [DOI] [PubMed]
  • 42.Taavoni S, Zahra Goldani M, Gooran NR, Haghani H. Development and assessment of respectful maternity care questionnaire in Iran. Int J Community Based Nurs Midwifery. 2018;6(4):334. [PMC free article] [PubMed] [Google Scholar]
  • 43.Dzomeku VM, Boamah Mensah AB, Nakua EK, Agbadi P, Lori JR, Donkor P. I wouldn’t have hit you, but you would have killed your baby: exploring midwives’ perspectives on disrespect and abusive care in Ghana. BMC Pregnancy Childbirth. 2020;20:1–2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Vedam S, Stoll K, Martin K, Rubashkin N, Partridge S, Thordarson D, Jolicoeur G. Changing childbirth in BC steering council. The mother’s autonomy in decision making (MADM) scale: Patient-led development and psychometric testing of a new instrument to evaluate experience of maternity care. PLoS ONE. 2017;12(2):e0171804. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Jenkinson B, Kearney L, Kynn M, Reed R, Nugent R, Toohill J, Bogossian F. Validating a scale to measure respectful maternity care in australia: challenges and recommendations. Midwifery. 2021;103:103090. [DOI] [PubMed] [Google Scholar]
  • 46.Sheferaw ED, Mengesha TZ, Wase SB. Development of a tool to measure women’s perception of respectful maternity care in public health facilities. BMC Pregnancy Childbirth. 2016;16:1–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Moridi M, Pazandeh F, Hajian S, Potrata B. Development and psychometric properties of midwives’ knowledge and practice scale on respectful maternity care (MKP-RMC). PloS one. 2020;15(11):e0241219. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1. (44.3KB, docx)

Data Availability Statement

The data that support the findings of this study are availability from the corresponding author on reasonable request because the scope of the data and consent obtained from study participants restricts our ability to share the data on ethical and legal rules.

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