Exploring Respectful Maternity Care and its determinants: a mixed methods cross-sectional study from a rural area in central India

Abstract

Introduction

This study investigates Respectful Maternity Care (RMC) and its determinants in a rural area of Central India. RMC, which is crucial for reducing maternal mortality, emphasizes dignity, privacy, and autonomy during childbirth. The study aligns with the Sustainable Development Goals (SDG) to improve maternal health outcomes.

Methodology

A mixed methods study with a convergent parallel design was conducted in the Obedullaganj block of Raisen district in Madhya Pradesh. Participants were mothers who had recently given birth in healthcare facilities of the district. Data measuring Respectful Maternity care was collected using the Person-Centered Maternity Care (PCMC) Scale and in-depth interviews. Descriptive data is presented in frequency tables. Quantitative data were analyzed using logistic regression and qualitative data through thematic analysis.

Results

The mean PCMC score was 48.6, with 26.3% of women experiencing good Respectful Maternity Care. Significant determinants of poor RMC included delivery in government health facilities (OR:4.58, 95% CI: 1.79 – 11.66), fewer than four antenatal care visits (OR: 2.5, 95% CI: 1.47 – 4.26), vaginal delivery (OR: 5.59, 95% CI: 3.01 – 10.38), and normal birth weight babies (OR: 2.82, 95% CI: 1.44 – 5.52). Qualitative analysis revealed themes around perceived knowledge of Respectful Maternity Care, barriers to delivering respectful care, and health system factors related to the provision of maternity care.

Conclusion

Respectful maternity care is vital for maternal and child health. The findings highlight that health system constraints such as human resources and their sensitization and training in RMC, among other logistics, must be addressed systematically to ensure respectful maternity care for mothers. The study also revealed that patient-related factors such as social status, economic worth, cultural barriers, illiteracy, lack of autonomy, and gender bias are also predictors of respectful care for mothers. The study’s findings emphasize the need for policy and practice changes to ensure respectful maternity care, particularly in rural healthcare settings in India.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12884-025-07454-x.

Background

Maternal mortality is an indirect measure of health services provided during the antenatal and postpartum period to women [1]. At times, it is seen that women’s status in society becomes an essential determinant of the quality of this care [2, 3]. The health services delivered to women during this vulnerable time are a reflection of the reach and quality of the health system of a country at large [4, 5]. The SDG (Sustainable Development Goals) target of 3.1 envisages to reduce by 2030 the global maternal mortality ratio to less than 70 per 100,000 live births. The related indicators are 3.1.1 of the Maternal Mortality Ratio (MMR) and 3.1.2, the proportion of births attended by skilled health personnel. According to the WHO, there was only a slight decrease in the global MMR from 227 to 223 maternal deaths per 100,000 live births from 2015 to 2020, which is far behind the SDG target [6]. Every two minutes, a woman dies from preventable causes related to pregnancy and childbirth, which indicates that almost 800 maternal deaths occur per day, and nearly 95% of these deaths happen in low- and middle-income countries [6]. The percentage of pregnancies attended by skilled health personnel in 2015 was about 81% globally.

In India, according to the Registrar General of India (RGI), Sample Registration System (SRS) report, there has been a 77% decrease in maternal mortality from 552 per 1,00,000 live births in 1990 to 97 per 1,00,000 in 2018–2020 [2]. A state-wise analysis of Indian data reveals that the state of Madhya Pradesh, where this study was conducted, had an MMR of 173 per 1,00,000 live births in 2016–18 [7].

Addressing maternal mortality requires a multifaceted approach combining healthcare infrastructure improvements, skilled healthcare providers, and community engagement [8]. Quality and respectful maternity care (RMC) are crucial components of this approach. When women are treated with disrespect and abuse, they are less likely to seek timely and appropriate care for themselves and their unborn babies. This, along with traditional barriers to seeking care, leads to poor health outcomes for both the mothers and their newborns [9–13]. Respectful maternity care (RMC) emphasizes care that respects women’s dignity, privacy, and autonomy and is free from mistreatment and abuse. It aligns with a human rights-based approach and aims to improve women’s experiences during labor and childbirth and the overall quality of care. Disrespect and abuse during childbirth are common, and addressing these issues is essential for encouraging women to seek healthcare and improve their health-seeking behaviors [12, 14, 15]. The LaQshya (Labor Room & Quality Improvement Initiative) by the Government of India is one such initiative to ensure respectful maternity care at public health facilities in India [16]. Respectful Maternity care can improve maternal and child health outcomes by promoting trust and building relationships between healthcare providers and mothers [17]. Mothers who feel respected and valued are more likely to trust healthcare providers and follow their advice.

Overlapping with the concept of Respectful Maternity Care is Person-Centered Maternity Care (PCMC). It is a primary domain of quality of care that focuses on care that is respectful of and responsive to women’s needs and preferences [18]. Person-centered maternity Care recognizes the need to involve women in their care. It emphasizes the interpersonal aspects of treatment to increase patient satisfaction. Relationships between patients and healthcare providers are crucial to person-centered care because they promote improved treatment compliance, continuity of care, and patient satisfaction [10]. Person-centered maternity care can be conceptualized as a broader construct that includes the domains of dignity, autonomy, privacy/confidentiality, communication, social support, trust, and supportive care [18–20]. Similarly, twelve areas of Respectful Maternity Care have been identified, which include protecting women from harm and mistreatment, maintaining privacy and confidentiality, preserving women’s dignity, providing information in advance and seeking informed consent, ensuring ongoing access to family and community support, improving the infrastructure quality and the quality of resources, offering equitable maternity care, and engaging in gender-sensitive communication [20].

This study aimed to estimate the proportion of women receiving Respectful Maternity Care as measured by the Person-Centered Maternity Care Scale during facility-based childbirth in public and private healthcare facilities in a rural block in central India. Additionally, we explored the other factors associated with maternity care, such as awareness and knowledge regarding respectful maternity care among healthcare providers, postpartum mothers, and their caregivers, using a mixed methods study design. The literature on respectful maternity care in India comprises quantitative and qualitative studies separately. Still, our study uses the mixed methods approach to study this topic comprehensively and in all its complexities.

Methodology

Study design

We used a mixed methods study with a convergent parallel design that involved collecting both quantitative and qualitative data simultaneously, analyzing the data separately, and then merging the results to provide a complete understanding of the determinants of Respectful Maternity Care.

Study setting

This study was conducted in the Obedullaganj block of Raisen district, in Madhya Pradesh. It is the rural field practice area of the Department of Community and Family Medicine of a tertiary care hospital in central India. The district has a population of approximately 14 lakhs (1.4 million) people living in 7 blocks of Raisen district. It has 176 sub-centers, 19 primary health centers (PHCs), nine community health centers (CHCs), and 1 district hospital. One of the blocks was selected considering operational feasibility. Also, it serves a population of approximately 2,38,000 residing in 240 villages. Per the administrative nomenclature, the block’s health facilities include 2 CHCs, 1 upgraded PHC, 3 PHCs, and 32 health and wellness centers (HWC/Sub centers) [21].

Study period

The entire study duration was two years, from August 2021 to May 2023. The data collection period was from January 2022 to December 2022. The data was collected after receiving a letter of permission from the Institutional Ethical Committee for Student Research (Reference No: IHEC-PGR/2020/PG/July/09 dated 27/08/2021).

Study population

All mothers residing in the Obedullaganj block who had delivered in the health care facilities of the Raisen district were the study participants. We included all mothers with children aged 12 to 14 weeks who consented to participate in the study. Mothers were excluded if they delivered in healthcare facilities outside the Raisen district, or they were unavailable despite two follow-up visits for data collection, or if they had themselves or their babies hospitalized at the time of data collection.

Sampling and sample size

The expected number of births per year according to the population of the 2011 Census was calculated, considering the birth rate of rural areas of Madhya Pradesh as 26.6 per 1000 people [22]. The villages with more births due to the larger population were selected for data collection for the quantitative part of the study. This was done to ensure that study participants, as per the calculated sample size, were available during the data collection period of one year.

During the one-year data collection period from January 2022 to December 2022, all the births occurring after September 2021 in the selected villages were considered for recruiting mothers as participants. The reason is that the mothers who delivered in September 2021 would have been eligible for study participation at 12 to 14 weeks (3 months) after the birth of their baby. Therefore, the expected number of births for nine months was calculated. The sample size for the quantitative analysis was calculated using the following equation:

$$n=\frac{{(1.96)}^2\times p\times (1-p)}{d^2}$$

where 1.96 = the Z value for the 95% confidence interval. Considering the prevalence of Respectful Maternity Care in India as 23% [8], with an absolute precision of 5% and an expected non-response rate of 20%, the sample size was calculated to be 326. We approached 402 participants; 24 were excluded because they did not meet the eligibility criteria. The non-response rate was 11%, with informed consent received from 335 participants. The final data analysis was done for 331 study participants due to missing data for four study participants.

The qualitative data collection was done using purposive sampling. In-depth interviews were conducted with eight mothers who reported poor respectful maternity care during the time of quantitative data collection, six family members of the study participants, and 13 healthcare providers, which included doctors, staff nurses, cleaning staff, and administrative officers.

Data collection

Quantitative data was collected using paperless and pen-and-paper modes. The literate study participants were asked to fill out the Hindi-validated version of the Person-Centered Maternity Care (PCMC) Scale, and the scores were calculated. If the study participant was illiterate, the investigator filled out the questionnaire. A separate questionnaire also recorded the details about the sociodemographic factors and information about the antenatal period, postnatal period, marital status, and obstetric history. The validated Indian version of the PCMC scale was used in the present study; it consists of 27 questions distributed under three subscales: Dignity and Respect (6 items), Communication and Autonomy (9 items), and Supportive Care (12 items) [19]. The scale comprises 27 items with response options ranging from 0 to 3. Negatively worded items were reverse-coded. A total PCMC score was calculated by summing responses across all items, yielding a possible score range of 0 to 81, where higher scores indicate better PCMC. The total scores for each of the three subscales were also calculated separately. The PCMC scores were analyzed as continuous variables. However, since the scale does not have a defined cut off’s for defining respectful care and based on previous use of this scale by the developers of this scale, categorical variables were created by classifying the total PCMC and subscale scores as “high,” “medium,” and “low.” The scores in the upper 75th percentile and lower 25^th percentile were defined as “high” and “low”, respectively. The scores in between were classified as “medium” [17]. The low and medium PCMC scores indicated poor RMC.

The interview guides for in-depth interviews were prepared based on conceptual frameworks developed after the literature review for determinants of Respectful Maternity Care. The purpose of the study was explained to all the participants through the Patient Information Sheet (PIS), and written informed consent was obtained before both qualitative and quantitative data collection. Assurance of the confidentiality of the information was ensured, and all the data were anonymized before analysis and reporting. All the interviews were audio recorded with the study participants’ permission, and observation notes were added to the notebook. A phenomenological approach was used for qualitative data analysis. The socioeconomic status was measured using the Modified BG Prasad Scale (2022), which includes classification according to the per-capita monthly income in Indian currency [23].

Statistical analysis

The quantitative survey data was collected using Kobo Toolbox, an online data collection tool. The data from the quantitative survey was downloaded as a spreadsheet from the Kobo toolbox. Further, data cleaning, data validation, and re-coding of the variables were performed using Microsoft Excel (Office 365 Version 2023). Descriptive statistics from the quantitative data are presented as the mean with standard deviation (SD), median with interquartile range (IQR), and frequency with percentage using Jamovi software. (Jamovi Team. (2022). Jamovi, Version 2.2.5). Additionally, bivariate and multivariable logistic regression analyses were performed to assess the associations of various sociodemographic characteristics with pregnancy and childbirth.

The audio-recorded in-depth interviews were transcribed by active listening. The descriptive narratives were written and organized into sections according to the stakeholders. After reading and rereading the transcripts, we became acquainted with the data. Coding was performed for each verbatim transcription, and the data were analyzed using an inductive approach to identify themes and subthemes.

Results

Quantitative results

Table 1 summarizes the sociodemographic and obstetrics characteristics of the study population. The mean age of the study participants in years was 24.9 (3.77), with an IQR (interquartile range) of 5 (22,27). The minimum and maximum ages of the study participants were 18 and 29 years, respectively. It was seen that 92.8% of the population belonged to the age group of 19 to 30 years; the majority was Hindu by religion. About 14% of the population was illiterate, and 41% had completed education until high school. It was seen that 70% of the population belonged to the lower class as per the BG Prasad classification (2022) for socioeconomic status. Most (92%) of these women in the study population had had their first pregnancy before the age of 24, with 20.8% being teenage pregnancies. About 80% of the deliveries were done in a government health facility, with about 69% at a community health center. As seen in Table No.1, anemia was detected in 51% of these pregnant women, and 74% delivered their babies at term. Most (84 %) of the population had their babies through the vaginal route, and 12.4 % of babies were found to be of low birth weight (less than 2500 grams).

Table 1.

Distribution of study participants according to their sociodemographic details and characteristics related to pregnancy and childbirth (n =331)

Characteristics	N (331)	(%)
Age
≤ 18	1	0.3
19–24	173	52.3
25- 30	134	40.5
30–35	17	5.1
> 35	6	1.8
Religion
Hindu	256	77.3
Muslim	75	22.7
Social Class (Caste)
Other Backward Castes	169	51.1
Scheduled Tribes	61	18.4
Scheduled Caste	57	17.2
General	44	13.3
Educational Qualification
Illiterate	47	14.2
Primary School	16	4.8
Middle School	89	26.9
High school	138	41.7
Higher Secondary	25	7.6
Graduate	16	4.8
Socioeconomic class (BG Prasad Classification 2022)
Lower Class (Class V)	232	70.1
Lower middle Class (Class IV)	86	26
Middle Class (Class III)	10	3
Upper middle Class (Class II)	2	0.6
Upper Class (Class I)	1	0.3
Type of family
Joint family	184	55.6
Extended family	60	18.1
Nuclear family	87	26.3
Age at marriage (in years)
< 18	91	27.5
19–24	228	68.9
25–30	12	3.6
Age at first pregnancy (in years)
< 18	69	20.8
19–24	238	71.9
25–30	22	6.6
> 30	2	0.6
Obstetric Historya
Women who had pregnancies without any adverse events	262	79.2
History of at least one miscarriage before 24 weeks of gestation	44	13.3
History of at least one intrauterine death after 24 weeks of gestation	15	4.5
History of any neonatal death (Death within 28 days after delivery)	6	1.8
History of any child death after 28 days of delivery	4	1.2
Type of Health Facility for delivery
Govt health facility	280	84.6
Private health facility	51	15.4
Place of Delivery
District Hospital	22	6.6
Community Health Centre	231	69.8
Primary Health Centre	27	8.2
Private Hospital	45	13.6
Nursing Home	2	0.6
Private Clinic	1	0.3
Charitable Trust	3	0.9
Number of ANC visits to a health facility
Less than 4 ANC visits	143	43.2
At least 4 ANC visits or more	188	56.8
Gestational age in months at 1st ANC visit
1	16	4.8
2	98	29.6
3	104	31.4
4	38	11.5
5	62	18.7
≥ 6	13	3.9
Problems during pregnancy
No complaints	117	35.4
Anemia	169	51.1
Increased tiredness	60	18.1
Pain abdomen	37	11.2
Gestational Hypertension	21	6.3
Bleeding per vagina	16	4.8
Fever	16	4.8
Swelling over face and legs	7	2.1
Visual disturbances	7	2.1
Unconsciousness	6	1.8
Others	6	1.8
Foul-smelling discharge per Vagina	4	1.2
Convulsions	2	0.6
Gestational Diabetes Mellitus	1	0.3
Gestational age at the time of delivery
Term	247	74.6
Preterm	58	17.5
Post-term	26	7.9
Type of delivery
Normal delivery	278	84.0
Emergency LSCS	32	9.7
Elective LSCS	18	5.4
Instrumental delivery	3	0.9
Birth weight of the baby
Normal Birth Weight	290	87.6
Low Birth Weight	41	12.4
Sex of the baby
Male	148	44.7
Female	183	55.3
NICU admission
No	289	87.3
Yes	42	12.7

^aNo women had more than one adverse event

The mean total PCMC score among the study population was 48.6 ± 9.5, with maximum and minimum PCMC scores of 76 and 17, respectively. The maximum and minimum possible scores on the Indian version of the PCMC scale were 81 and 0, respectively. The median score for our study population was 42, with IQR at 12.5 (42.5, 55). Each subscale’s 25th, 50th and 75th centile values were also calculated and used for categorization. Figure 1 shows a bar diagram depicting the distribution of the study participants according to total PCMC and subscale scores.

Fig. 1.

Distribution of the study participants according to total PCMC and subscale scores (n = 331)

In Fig. 1, according to the total PCMC score, 87 participants (26.3%) experienced good RMC, scoring above 55 (75^th percentile) on the total PCMC scale. A score below 12.5 (25^th percentile) was considered a poor RMC. Similarly, percentiles and scores of individual subscales were used to categorize low, medium, and high RMC within each subscale. Notably, only 69 women (20.8%) received respectful care in the “dignity and respect” subscale, which included items such as verbal abuse, privacy, and confidentiality. On the other hand, the highest proportion of respectful care (37.2%) was observed in the “communication and autonomy” subscale, which included components such as consent, being called by one’s name, choice of delivery position, and clear explanations of procedures, among others.

Table 2 shows the results of univariable logistic regression analysis. Some categories of the variables were merged for logistic regression analysis. The low and medium PCMC score categories were merged as poor RMC and analyzed in the model. According to univariable logistic regression analysis, government health facilities, low social hierarchy or class, impoverished economic status, normal vaginal delivery, fewer than four ANC visits, and normal birth weight were determinants of poor RMC scores. However, all the other variables were controlled for in the multivariable logistic regression.

Table 2.

Univariable logistic regression analysis to determine factors associated with respectful maternity care (N = 331)

Variable and category		Total	Good RMC (High Total PCMC) n (%)	Poor RMC (Low and Medium Total PCMC) n (%)	Unadjusted OR	95% CI	p-value
Type of Health Facility for delivery	Private hospital (Ref)	51	33 (64.7)	18 (35.3)	-
	Government Hospital	280	54 (19.3)	226 (80.7)	7.67	4.02 - 14.65	< .001
Age group (in years)	≤ 25 years	174	45 (25.9)	129 (74.1)	-
	> 25 years	157	42 (26.8)	115 (73.2)	0.96	0.58 – 1.56	0.854
Religion of the mother	Hindu (Ref)	256	66 (25.8)	190 (74.2)	-
	Muslim	75	21 (28.0)	54 (72.0)	0.89	0.50 – 1.59	0.701
Social Class (Caste)	Unreserved (Ref)	44	16 (36.4)	28 (63.6)	-
	OBC (Other Backward Classes)	169	50 (29.6)	119 (70.4)	1.36	0.68 – 2.73	0.388
	SC-ST (Scheduled Castes and Scheduled Tribes)	118	21 (17.8)	97 (82.2)	2.64	1.22 – 5.73	0.014
Highest level of education attained by mothers	High school or above (Ref)	179	56 (31.3)	123 (68.7)	-
	Below high school	152	31 (20.4)	121 (79.6)	1.78	1.07 – 2.95	0.026
Employment status of mothers	Currently working (Ref)	40	5 (12.5)	35 (87.5)
	Not working currently	291	82 (28.2)	209 (71.8)	0.36	0.14 – 0.96	0.041
Family type	Extended family (Ref)	244	67 (27.5)	177 (72.5)	-
	Nuclear family	87	20 (23.0)	67 (77.0)	1.27	0.72 – 2.25	0.417
Socioeconomic class (Modified BG Prasad classification 2022)	Middle class and above (Ref)	13	5 (38.5)	8 (61.5)	-
	Below middle class	318	82 (25.8)	236 (74.2)	1.8	0.57 – 5.65	0.315
Availability of BPLa Ration Card	No (Ref)	119	41 (34.5)	78 (65.5)	-
	Yes	212	46 (21.7)	166 (78.3)	1.9	1.15 – 3.13	0.012
Gravidity status	Primigravida (Ref)	109	33 (30.3)	76 (69.7)	-
	Multigravida	222	54 (24.3)	168 (75.7)	1.35	0.81 – 2.25	0.25
Antenatal care (ANC) Visits	At least 4 ANC visits or more (Ref)	188	63 (33.5)	125 (66.5)	-
	Less than 4 ANC visits	143	24 (16.8)	119 (83.2)	2.5	1.47 – 4.26	< .001
Antenatal Complaints	Yes (Ref)	214	53 (24.8)	161 (75.2)	-
	No	117	34 (29.1)	83 (70.9)	0.80	0.49 – 1.33	0.397
Same ANC care and Delivery Center	Yes (Ref)	208	50 (24.0)	158 (76.0)	-
	No	123	37 (30.1)	86 (69.9)	0.74	0.45 – 1.21	0.228
Gestational Age at the time of Delivery	Term (Ref)	247	63 (25.5)	184 (74.5)	-
	Preterm	58	18 (31.0)	40 (69.0)	0.76	0.41 – 1.42	0.392
	Post-term	26	6 (23.1)	20 (76.9)	1.14	0.44 – 2.97	0.786
Type of delivery	Assisted delivery (Ref)	53	31 (58.5)	22 (41.5)	-
	Normal delivery	278	56 (20.1)	222 (79.9)	5.59	3.01 – 10.38	< .001
Complications during delivery	Yes (Ref)	68	19 (27.9)	49 (72.1)	-
	No	263	68 (25.9)	195 (74.1)	1.11	0.61 – 2.02	0.728
Birth weight of the baby	Low Birth weight (Ref)	41	19 (46.3)	22 (53.7)	-
	Normal Birth weight	290	68 (23.4)	222 (76.6)	2.82	1.44 – 5.52	0.002
NICU admission	Yes (Ref)	42	11 (26.2)	31 (73.8)	-
	No	289	76 (26.3)	213 (73.7)	0.99	0.48 – 2.08	0.988
Sex of the baby	Female (Ref)	148	43 (29.1)	105 (70.9)	-
	Male	183	44 (24.0)	139 (76.0)	1.29	0.79 – 2.11	0.304

^aBPL Below Poverty Line, NICU Neonatal Intensive Care Unit, ANC Antenatal Care

The results of multivariable logistic regression are shown in Table 3. Variables considered for multivariable analysis included those with p values less than 0.25 in univariable analysis. After adjusting for the variables in the multivariable analysis, women who delivered in government health facilities were four times more likely to receive poor RMC care. Women who attended fewer than four ANC visits were twice as likely to receive poor RMC. Another finding was that women with normal vaginal deliveries were twice as likely to receive poor RMC than women with assisted deliveries. As normal vaginal deliveries require continuous interaction with the health care providers, there is a higher likelihood of experiencing disrespect or lapses in care. This has been further explained in the qualitative analysis. The multivariable logistic regression revealed that the mothers of babies with normal birth weights were twice as likely to receive disrespectful maternity care than were those with low birth weights. As the scale measured aspects of maternity care post-delivery, it could be that having a baby with a low birth weight might have made the healthcare providers more empathetic towards the mother during and after the delivery process.

Table 3.

Multivariable logistic regression analysis to determine factors independently associated with poor respectful maternity care (Low PCMC scores)

Variable and category		Adjusted OR	95% CI	P value
Type of Health Facility for delivery	Private health facility (Ref)	-
	Government Health Facility	4.58	1.79 - 11.66	0.001
Social Class (Caste)	Unreserved (Ref)	-
	OBC (Other Backward Castes)	0.90	0.38—2.13	0.817
	SC/ST (Scheduled Castes/ Scheduled Tribes)	1.19	0.47—3.01	0.716
Highest level of education attained by mother	High school or above (Ref)	-
	Below high school	1.03	0.56 – 1.89	0.932
Employment status of mother	Currently working (Ref)
	Not working currently	0.56	0.19 – 1.58	0.272
Availability of BPLa Ration Card	No (Ref)	-
	Yes	0.89	0.46 – 1.72	0.724
Number of ANCb Visits	At least 4 ANC visits or more (Ref)	-
	Less than 4 ANC visits	2.0	1.10 – 3.63	0.022
Same ANC care and Delivery Center	Yes (Ref)	-
	No	1.75	0.91 – 3.36	0.091
Type of delivery	Assisted delivery (Ref)	-
	Normal delivery	2.78	1.16 – 6.15	0.021
Birth weight of the Baby	Low Birth weight (Ref)	-
	Normal Birth weight	2.78	1.29 – 5.93	0.008

^aBPL Below Poverty Line

^bANC Ante Natal Care

Results of qualitative analysis

A phenomenological approach was used to explore the experiences of women, their caregivers, and healthcare providers regarding respectful maternity care. A total of 27 in-depth interviews (IDIs) were conducted and included in this analysis; eight were with mothers, six were with family members of study participants, six were with doctors, five were with midwives, and two IDIs were with health care administrators.

The analysis was performed using thematic analysis. Context-specific codes were extracted and allocated into subthemes and themes. After the final analysis, all the codes were distributed under three themes and 12 subthemes. Some interesting and relevant quotes are mentioned in Table 4. The subthemes are described in Fig. 2 and Supplementary files.

Table 4.

Themes of qualitative analysis with relevant quotes

Theme	Quotes
Theme 1: Perceived knowledge of Respectful Maternity Care and its importance	“It is necessary to scold them a little bit too. Then only we will be able to conduct the delivery. We tell them that if she is not cooperating, then there will be chances of operation” (SN-P) “I didn’t receive any training regarding this…I’m hearing this term for the first time” (SN-C2) “They did not tell me what was happening. They do not tell anything.” (M-24)
Theme 2: Perceived problems regarding the provision of Respectful Maternity Care	“This was my 3rd pregnancy, and they were like, I do not need any help for delivering the baby” (M-28) “Some staff asked us for money saying that now you have a male baby, give me 1000rs…rich people may be giving that much, but how can they demand such an amount from poor people like us” (M-29) “I don’t wish to go there again, but we don’t have any other option…if something emergency happens, we don’t have that much money to go to any private hospital or any other place” (M-29) “Here, women don’t make decisions alone; they always depend on husbands and mother-in-law or someone else, which creates problems; most of the time, we have to talk to their husbands or mothers-in-law to get consent for PPIUCD, etc.” (SN-P)
Theme 3: Health System Factors Related to Respectful Maternity Care	“There should be a sufficient number of staff in every cadre…we can’t expect a staff nurse to clean the labour room after delivery” (MO-C3) “We don’t always have the equipment or supplies we need to provide the best possible care, and that can be frustrating for both us and our patients.” (O–CH) “Almost every guideline is made out of patients’ perspective… it is indeed for them…but they should consider our perspectives also while creating such things as we are the service providers” (MO-C3) “We don’t get enough time to educate or counsel the women since we are always engaged in some other activities” (SN-C1) “We did not receive the incentive money” (M-24)

M Mothers-(Age), CG Caregiver (Male/Female); Age, O - Obstetrician DH (District Hospital), CH Civil Hospital, PH Private Hospital, MO Medical Officer, P PHC, C CHC, SN Staff Nurse, P PHC, C CHC, CS Cleaning Staff CHC

Fig. 2.

Themes and subthemes with corresponding codes derived from qualitative analysis

Discussion

Our study had two main objectives: first, to estimate the proportion of women receiving Respectful Maternity Care (RMC) during facility-based childbirth and second, to identify factors associated with RMC. As mentioned previously, we defined good RMC as those mothers who had high scores on the PCMC Scale. The proportion of women receiving good RMC in our study population was only 26.3% when considering all the subscales of the PCMC scale. When individual subscales of the PCMC scale were studied, the one which measures the Communication and Autonomy domain of respectful care, it was seen that about 37.2% of women had received good (respectful) maternity care in this domain. By comparing our findings to the literature, we found similar proportions of disrespectful care reported in previous studies from India and other countries. A systematic review and meta-analysis from India in 2020, reported the pooled prevalence of disrespectful care during childbirth in community-based studies as 77.3% [15]. The results from hospital-based studies from India show that the prevalence of any form of disrespectful maternity care during childbirth ranges between 20.9% and 96.5% [24–27].

Our study revealed several factors significantly associated with Respectful Maternity Care (RMC). A more significant proportion of women who delivered at private healthcare facilities than at government facilities had respectful care. A facility-based cross-sectional study from Ethiopia [28] also showed a significant association between the type of delivery center and respectful maternity care. They reported that delivering at a private hospital was significantly associated with RMC. Similarly, a cross-sectional study from Odisha also mentioned the association between delivery facilities and RMC [29].

Antenatal visits, type of delivery, and birth weight were also significantly associated with RMC after we adjusted for other independent variables. Participants with more antenatal care (ANC) visits reported good RMC. A facility-based cross-sectional study from Ethiopia reported a similar association between respectful maternity care and ANC visits [30]. In our study, we asked women whether they delivered at the same health facility where they received their antenatal care. It was seen that 37.1% of the mothers delivered at a health facility, which was different from the facility where they received antenatal care (not shown in the table). The interaction between women and healthcare providers during the antenatal period may offer opportunities for building rapport and trust, establishing comfort, and strengthening connections with health providers. In addition, counseling and early detection of complications can also positively influence respectful care during delivery. However, certain other factors, such as poor staff attitudes and dissatisfaction with the facilities’ services, affect women’s willingness to use the same facility for future healthcare needs.

In our study, we found a significant association between RMC and type of delivery, where women who underwent normal vaginal delivery were twice as likely to receive poor RMC. Similarly, the association between RMC and the birth weight of the baby was also significant. This implies that the women with complicated deliveries and babies with low birth weight were treated with more respectful care than the others. The reason could be increased empathy of health care providers towards weak babies or taking better care of women who had to undergo a cesarean section.

To understand the factors contributing to RMC, we explored health system constraints, including inadequate infrastructure, human resources, and availability of medical supplies. Such constraints can directly impact women’s perception of respectful care and indirectly affect healthcare workers' behavior due to stressful working environments. Improving the quality of maternity care requires skilled healthcare professionals, appropriate training, and adequate resources. The qualitative analysis in our study provides evidence that respectful care is neither demanded as a right nor is provided as an essential element of quality care. The constraints are both patient-driven, provider- and health system-driven. This is seen in the subthemes of unfavorable patient behavior, normalization of disrespect and abuse, lack of knowledge among healthcare providers about respectful care, staff dissatisfaction, infrastructure constraints, etc. A cross-sectional study from Nigeria reported that poor staff attitudes, described as being rude or disrespectful and using abusive words, were a reason for the non-use of services at primary healthcare centers, including ANC and delivery services, by 29.5% of the women [27]. Additionally, the familiarity developed between healthcare professionals and women during ANC visits might also contribute to appropriate, respectful care being given during delivery. We also extracted codes and subthemes related to this topic based on our qualitative exploration. Although socioeconomic status/poverty was not significant in the multivariable analysis as a determinant of RMC provision, it still emerged as an important theme for providing respectful care to parturient women. The gender disparity in families and lack of autonomy for women were also responsible for the normalization of disrespectful care.

Several studies have shown that the main reason for these constraints is the increased proportion of institutional deliveries, and most related studies have focused on improving clinical care until recently. To ensure good quality maternity care, skilled and competent healthcare professionals should receive appropriate obstetrics and maternal care training and adequate infrastructure and other essential resources [27, 31–33]. In our study, many staff members were not trained in RMC. Some were even unaware of the concept of respectful care for women, as seen in the subtheme of perceived knowledge of RMC and its importance. (Table 4, Fig. 2) In a resource-constrained health system such as ours, the focus has been mainly on preventing deaths; therefore, providing quality and respectful care is not considered essential by both providers and beneficiaries. The predominance of cultural practices and family ties in maternal and child health care can sometimes be perceived by healthcare providers as a barrier to the delivery of medical care as well as adherence to medical advice, as is seen in the qualitative analysis.

Strengths and limitations

We employed a parallel convergent mixed methods approach, integrating quantitative and qualitative data, to comprehensively understand respectful maternity care. By involving stakeholders from different cadres, such as healthcare professionals, mothers, and caregivers, in qualitative interviews, we captured diverse perspectives and experiences, enhancing the validity and relevance of the findings. Conducting the study in a rural community setting allowed us to consider the social, cultural, and environmental factors affecting outcomes and obtain rich narratives that quantitative measures alone may miss. Moreover, the study’s practical implications for the community and the potential to inform policymakers and practitioners add value to the research. The sizable sample size of 331 mothers adds to the reliability and validity of the study.

However, some limitations should be considered. The use of convenience sampling in a specific rural setting may limit the generalizability of the findings to other populations or settings. Selection bias could occur due to participants’ accessibility or willingness to participate, affecting the validity of the results. The reliance on self-reported outcome variables in the quantitative questionnaire may have introduced social desirability bias, leading to biased or inaccurate information. Moreover, response bias or social hierarchy bias might have occurred among healthcare professionals, inhibiting them from expressing their accurate opinions or experiences during the interviews. Additionally, potential recall bias could affect the accuracy of the data collected after three months of delivery.

Conclusion

This study provides valuable insights into the prevalence and factors associated with respectful maternity care during facility-based childbirth in India. The findings highlight the importance of addressing the health system constraints of human resources, logistics, top-down planning, and lack of sensitization and orientation training on RMC. The study also revealed that patient-related factors such as social status, economic worth, cultural barriers, illiteracy, lack of autonomy, and gender bias are also predictors of respectful care for mothers. Thus, ensuring that women receive good quality and respectful care has many complex layers and requires individual, community, and health system interventions. Understanding these factors can guide policy changes and interventions to improve maternal and child health outcomes and enhance the overall childbirth experience for women in India and other low-middle-income countries.

Abbreviations

ANC

Antenatal Care

ANM

Auxiliary Nurse Midwife

ASHA

Accredited Social Health Activist

CFM

Community and Family Medicine

CHC

Community Health Centre

D&A

Disrespect and Abuse

DH

District Hospital

EAG

Empowered Action Group

HCW

Healthcare worker

HWC

Health and Wellness Centre

ICMR

Indian Council of Medical Research

IMR

Infant Mortality Rate

MMR

Maternal Mortality Ratio

MoHFW

Ministry of Health and Family Welfare

PCMC

Person-Centred Maternity Care

PHC

Primary Health Centre

PIS

Patient Information Sheet

PNC

Postnatal care

RGI

Registrar General of India

RMC

Respectful Maternity Care

SDG

Sustainable Development Goals

SRS

Sample Registration System

WHO

World Health Organization

WRA

White Ribbon Alliance

Authors’ contributions

CA, who is the first author of this manuscript was the Principal Investigator of the study and contributed to the design, implementation, analysis and reporting. Review, cross-validation and editing of all the sections was done by the last author DD who also provided insights for background, discussion and recommendations. AM, RS, BS, PT and AR contributed in development of ideas, analysis and interpretation of results and recommendations.

Funding

The study received financial assistance for the MD Thesis from the Indian Council of Medical Research (ICMR) No:3/2/December-2021/PG-Thesis-HRD (19); Reference ID: MD21DEC-0063.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

The study was conducted in accordance with the ethical principles as mentioned in the Declaration of Helsinki (2013). The study was approved by the Institutional Human Ethics Committee- Post-Graduate Research (IHEC-PGR) of the All India Institute of Medical Sciences, Bhopal (Reference Number: IHEC- PGR/2020/PG/July/09 dated 27/08/2021). The purpose of the study was explained to all the participants through the Patient Information Sheet (PIS), and written informed consent was obtained. Assurance of the confidentiality of the information was ensured, and all the data were anonymized before analysis and reporting.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.