**3. Results**

**2.7. Pre-test and quality assurance**

70 Selected Topics in Midwifery Care

**2.8. Data processing and analysis**

inconsistencies and errors were resolved.

*2.8.1. Data entry and processing*

*2.8.2. Variables*

*2.8.3. Statistical analysis*

**2.9. Ethical issues**

follow up interviews were made to correct any such errors.

egories of mistreatment in **Table 1** was considered mistreated.

The questionnaires were pre-tested in the CWC of another public health facility in the Tema Metropolis using 20 randomly selected mothers who gave birth between November 2017 and April 2018. The pretest enabled ambiguities in the wording of some questions to be corrected. The pretest also enabled us estimate the average time required to complete each questionnaire. In addition to the pretesting, other quality assurance measures were implemented. Data collected by the second author were checked every day by the first author to ensure accuracy and completeness. Errors that were detected were discussed and where needed,

The completed questionnaires were hand-coded and entered into Microsoft Excel. The data were then exported to Stata 15 version software for further cleaning. Cleaning of the data was done by running frequencies on each variable. This checked inconsistently coded data. Inconsistently coded data were double checked with raw data from the questionnaire, and all

The dependent variable in this study is mistreatment of women during childbirth. Mistreatment was defined as specific behaviours of providers, which are related to any of the seven categories of mistreatment listed in **Table 1**, and expressed towards mothers in ways that are disrespectful or humiliating [23]. Questions on mistreatments were measured as dichotomous, such that any respondent who reported experiencing any of the seven cat-

A number of independent variables expected to influence mistreatment were also measured. These included socio-demographic characteristics such as age, marital status, income level, educational level and religion. Other maternal and health system factors included mode of delivery, type of birth attendant, HIV status and antenatal care (ANC) attendance during pregnancy.

Descriptive statistical analysis (frequency, mean and standard deviation) was performed to describe important characteristics of respondents as well as estimate prevalence and forms of mistreatment women received during childbirth. Bivariate and logistic regression analyses were then performed to examine factors associated with mistreatment of women during childbirth. Statistical significance was considered at 95% confidence level and a p < 0.05.

Ethical approval was sought and obtained from the Ghana Health Service Ethical Review Committee. In addition, administrative consent and approval to conduct the study in the hospital was sought and obtained from the director of medical services of the Tema General

#### **3.1. Socio-demographic characteristics of respondents**

Questionnaires were successfully completed for all the 253 respondents. **Table 2** shows the background characteristics of respondents. The mean age was 28.1 years (SD = ± 6.0). The majority (34.4%) were aged 24–29 years. The majority (32.4%) also attained secondary school education, while only 9.9% had no formal education. Also, 69.6% were heterosexually married, and most marriages (65.7%) were monogamous. Christians were in the majority (87.4%). In terms of parity, majority (86.2%) of the respondents had between 1 and 3 children.


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**Characteristics Frequency Percent (%)** 4–7 dependants 28 14.21

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No formal education 17 6.85 Primary 17 6.86 JHS 62 25.00 Secondary 99 39.92 Tertiary 53 21.37

None 21 8.30 Trading 49 19.37 Civil servant 39 15.42 Farmer 16 6.32 Others 128 50.59

100–500 111 50.45 500–1000 77 35.00 1000–1500 21 9.55 2000–2500 11 5.00

*Husbands' level of education*

*Husband's occupation*

*Husband's monthly income (GHȻ)*

**Table 2.** Socio-demographic characteristics.

**Figure 1.** Prevalence of mistreatment.

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**Table 2.** Socio-demographic characteristics.

**Characteristics Frequency Percent (%)** Co-habiting 28 11.07 Single 35 13.83

Monogamous 134 65.69 Polygamous 70 34.31

Christianity 221 87.35 Islamic 29 11.46 Traditional 3 1.19

Urban 241 95.26 Rural 12 4.74

Ga 54 21.43 Twi 56 22.22 Fante 36 14.29 Ewe 47 18.65 Others 59 23.41

Trading 100 39.53 Housewife 53 20.95 Seamstress 28 11.07 Hairdresser 23 9.09 Civil servants 25 9.88 Others 24 9.49

No salary 57 22.53 <GHc500 165 65.22 GHc500–1000 22 8.70 >GHc1000 9 3.56

1–3 children 218 86.17 4–7 children 35 13.83

1–3 dependants 169 85.79

*Type of marriage*

72 Selected Topics in Midwifery Care

*Religious affiliation*

*Residence*

*Ethnicity*

*Occupation*

*Monthly income (GHȻ)*

*Parity*

*Dependents*

**Figure 1.** Prevalence of mistreatment.

#### **3.2. Prevalence of mistreatment**

**Figure 1** summarises the prevalence of mistreatment among the women surveyed. The overall prevalence of mistreatment was 83.0%. This included those who suffered at least one form of mistreatment in the facility during their most recent childbirth. The most common form of mistreatment was detention for long hours for non-payment of medical bills (43.1%), followed by non-confidential care (39.5%), abandonment (30.8%), verbal abuse (25.3%), discrimination (21.3%) and physical abuse (14.2%) (see **Table 3**).

**Characteristics Mistreated**

*Age*

*Marital status*

*Type of marriage*

*Level of education*

*Residence*

*Religious affiliation*

*Occupation*

**Yes No Chi-square**

Mistreatment of Women in Health Facilities by Midwives during Childbirth in Ghana: Prevalence…

15–19 7(58.33) 5(41.67) 0.046\*

Married 140(79.55) 36(20.45) 0.205

Monogamous 105(78.36) 29(21.64) 0.072

No formal education 20(80.00) 5(20.00) 0.048\*

Urban 198(82.16) 43(17.84) 0.228

Christianity 181(81.10) 40(18.10) 0.677

Trading 85(85.00) 15(17.0) 0.384

20–24 58(92.06) 5(7.94) 25–29 74(85.06) 13(14.94) 30–34 36(73.47) 13(26.53) 35–39 19(73.08) 7(26.92) 40–44 10(66.67) 5(33.33)

Separated 9(64.29) 5(35.71) Co-habiting 20(74.43) 8(28.57) Single 30(85.71) 5(14.29)

Polygamous 62 (88.57) 8(11.43)

Primary 72(88.89) 9(11.11) JHS 30(83.33) 6(16.67) Secondary 65(79.27) 17(20.73) Tertiary 19(65.52) 10(34.48)

Rural 7(58.33) 5(41.67)

Islamic 22 (75.86) 7(24.14) Traditional 6(54.55.00) 5(45.45)

Housewife 46(86.79) 7(13.21) Seamstress 22(78.57) 6(21.43) **P-value**

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**Table 3.** Types of mistreatment women received.


**Table 4.** Multiple experiences of mistreatments.

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**3.2. Prevalence of mistreatment**

74 Selected Topics in Midwifery Care

(21.3%) and physical abuse (14.2%) (see **Table 3**).

**Table 3.** Types of mistreatment women received.

**Table 4.** Multiple experiences of mistreatments.

**Figure 1** summarises the prevalence of mistreatment among the women surveyed. The overall prevalence of mistreatment was 83.0%. This included those who suffered at least one form of mistreatment in the facility during their most recent childbirth. The most common form of mistreatment was detention for long hours for non-payment of medical bills (43.1%), followed by non-confidential care (39.5%), abandonment (30.8%), verbal abuse (25.3%), discrimination



**Characteristics Mistreated**

*Husband's monthly income (GHȻ)*

*ANC attendance*

*Mode of delivery*

*Birth attendant*

*HIV status*

*Had episiotomy*

*Had a bed*

*Age of the baby (n = 200)*

**Yes No Chi-square**

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**Yes No Chi-square**

100–500 97(87.39) 14(12.61) 0.002\*

**Table 5.** Socio-demographic factors associated with mistreatments (bivariate analyses). \*p < 0.05

Yes 201(84.10) 38(15.90) 1.000

1–3 months and below 120(85.71) 20(14.29) 0.201

Vaginal delivery 141(85.98) 23(14.02) 0.088

Obstetrician/gyneacologist 64(77.11) 19(22.89) 0.000\*

Negative 151(95.32) 9(4.68) 0.009\*

Yes 193(83.55) 38(16.45) 1.000

Yes 202(84.17) 38(15.83) 0.220

**Table 6.** Maternal and health system factors associated with mistreatment (bivariate analyses). \*p < 0.05

No 9(62.29) 5(35.71)

4–6 months 90(79.65) 23(20.35)

Caesarean section 69(77.53) 20(22.47)

Midwife 146(85.88) 24(14.12)

Positive 73(78.49) 20(21.51)

No 6(54.55) 5(45.45)

No 8(61.54) 5(38.46)

500–1000 64(83.12) 13(16.88) 1000–1500 12(57.14) 9(42.86) 2000–2500 6(54.55) 5(45.45)

**Characteristics Mistreated**

**P-value**

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**P-value**

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**Table 5.** Socio-demographic factors associated with mistreatments (bivariate analyses). \*p < 0.05

**Characteristics Mistreated**

*Monthly income (GHȻ)*

76 Selected Topics in Midwifery Care

*Ethnicity*

*Parity*

*Dependents*

*Husbands' level of education*

*Husband's occupation*

Hairdresser 17(73.91) 6(26.09) Civil servants 17(68.00) 8(32.00) Others 18(75.00) 6(25.00)

<GHc500 138(83.64) 27(16.36) GHc500–1000 16(72.73) 6(27.27) >GHc1000 6(54.55) 5(45.45)

Twi 46(82.14) 10(17.86) Fante 29(80.56) 7(19.44) Ewe 39(82.98) 8(17.02) Others 52(88.14) 7(11.86)

4–7 children 30(85.71) 5(14.29)

4–7 dependants 21(75.00) 7(25.00)

Primary 11(64.71) 6(35.29) JHS 57(91.94) 5(8.06) Secondary 77(77.47) 22(22.22) Tertiary 40(75.47) 13(24.53)

Trading 43(87.76) 6(12.24) Civil servant 30(76.92) 9(23.08) Farmer 10(62.50) 6(37.50) Others 103(80.47) 25(19.53)

No salary 51(89.47) 6(10.53) 0.045\*

Ga 44(81.48) 10(18.52) 0.849

1–3 children 180(82.57) 38(17.43) 0.646

1–3 dependants 138(81.66) 31(18.34) 0.425

No formal education 11(64.71) 6(35.29) 0.056

None 14(66.67). 7(33.33) 0.151

**Yes No Chi-square**

**P-value**


**Table 6.** Maternal and health system factors associated with mistreatment (bivariate analyses). \*p < 0.05

As shown in **Table 4**, many women experienced multiple forms of mistreatment during their most recent health facility delivery. The majority of women (25.7%) suffered from two types of mistreatment; 17.4% suffered three types of mistreatment; 11.1% suffered four different types of mistreatment; and 5.5% suffered five types of mistreatment. Only 0.8% of the women suffered six types of mistreatment, with no respondent reporting suffering all the seven types of mistreatment studied.

for potential confounders, husband's income, HIV status and type of birth attendant during childbirth independently predicted mistreatment. Specifically, the odds of being mistreated were significantly lower for HIV negative women compared to HIV positive women (cOR: 0.22; 95% CI = 0.065–0.746; p = 0.015). This relationship was still statistically significant after potential confounders were adjusted for (aOR: 0.11; 95% CI = 0.022–0.608; p = 0.011). Women whose births were attended by obstetricians/gyneacologists were also significantly less likely to report mistreatment compared to those whose birth were attended by midwives (cOR: 0.09; 95% CI = 0.026–0.291; p < 0.01). This relationship was still strongly statistically significant after other factors were adjusted for (aOR: 0.07; 95% CI = 0.018–0.279; p < 0.01). Also, as a woman's husband's monthly income increases, the odds of the woman reporting mistreatment reduces,

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This study is among the first in Ghana to quantitatively estimate the prevalence of mistreatment of women during health facility-based childbirth and associated factors. Findings suggest that, the overall prevalence of mistreatment of women during their most recent childbirth in the Tema General Hospital was high (83%), with most of the mothers experiencing detention (43.1%) due to lack of fee payment, non-confidential care (39.5%), neglect/abandonment (31.8%), verbal abuse (25.3%), discrimination (21.3%), physical abuse (14.2%), and non-consented care (13.3%). Many women also experienced multiple forms of mistreatment. The main factors that significantly predicted mistreatment were being HIV positive, being attended by a midwife rather than an obstetrician/gyneacologist, and a woman's husband

A number of our findings above deserves further commentary. Compared to other previous studies in Africa [8, 9], the 83% prevalence of mistreatment in this study is relatively high. It is however not surprising as evidence from a recent systematic review suggests that mistreatment is increasing in many low-income settings especially in urban areas [13]. With increasing population in many urban areas in SSA amid declining human and financial resources for health as well as deteriorating health infrastructure, there are suggestions that congestion in maternity wards, under-staffing, and over working of health staff, may be compromising quality of maternity care, including mistreatment of women during childbirth [21, 24–26]. It is also possible that mistreatment may not be increasing per se; just that many urban women are becoming increasingly aware of their rights as patients partly because of improvements in formal education. This is more likely in the present study given that the majority of women had some formal education. Be that as it may, the relatively high prevalence of mistreatment in this study is a cause for concern. Mistreatment of women in health facilities during childbirth does not only violate the rights of women to respectful care, but can also threaten women's rights to life, health, bodily integrity, and freedom from institutional violence [5]. Thus, not only is mistreatment a public health issue but it also becomes a human rights and an equity issue [10]. As a number of studies have shown, women who experience mistreatment from midwives or other maternity care providers in a health facility setting are often less likely

although the relationship was generally very weak.

**4. Discussion**

earning lower monthly income.

#### **3.3. Factors associated with mistreatment**

**Table 5** presents information on bivariate analysis investigating the association between socio-demographic factors and mistreatment based on chi-square test of independence. Age of mother (p = 0.046), mother's level of education (p = 0.048), mother's monthly income (p = 0.045), and husband's monthly income (p = 0.002) were statistically significantly associated with mistreatment of women during their most recent childbirth in the Tema General Hospital. In addition to the socio-demographic factors, other maternal and health system factors were assessed. The results are shown in **Table 6**. A woman's HIV status (p = 0.009), as well as type of birth attendant during childbirth (p < 0.01) were statistically associated with mistreatment.

In total, six (6) factors showed statistical association with mistreatment at the bivariate level. These were pulled into a logistic regression model in a second round of analysis. A simple logistic regression analyses model, followed by a multiple logistic regression analyses model, were then performed on the six variables. The results are shown in **Table 7**. After adjusting


**Table 7.** Predictors of mistreatment during childbirth (logistic regression analysis). \*p < 0.05

for potential confounders, husband's income, HIV status and type of birth attendant during childbirth independently predicted mistreatment. Specifically, the odds of being mistreated were significantly lower for HIV negative women compared to HIV positive women (cOR: 0.22; 95% CI = 0.065–0.746; p = 0.015). This relationship was still statistically significant after potential confounders were adjusted for (aOR: 0.11; 95% CI = 0.022–0.608; p = 0.011). Women whose births were attended by obstetricians/gyneacologists were also significantly less likely to report mistreatment compared to those whose birth were attended by midwives (cOR: 0.09; 95% CI = 0.026–0.291; p < 0.01). This relationship was still strongly statistically significant after other factors were adjusted for (aOR: 0.07; 95% CI = 0.018–0.279; p < 0.01). Also, as a woman's husband's monthly income increases, the odds of the woman reporting mistreatment reduces, although the relationship was generally very weak.
