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\title{Influence of Clinic-Based Health Education on Pregnant Women's Knowledge and Attitudes in Relation to Pregnancy Management: Evidence from Ogun State, Nigeria}
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\begin{document}

             \author[1]{Agbede C  O}

             \affil[1]{  Babcock University Nigeria}

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\date{\small \em Received: 11 December 2014 Accepted: 5 January 2015 Published: 15 January 2015}

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\begin{abstract}
        


The study assessed the influence of clinic-based health education on women?s knowledge and attitudes in relation to pregnancy management in Ogun State. Stratified sampling method was used to allocate 48 pregnant women each to experimental and control groups, making a total of 96 respondents. Structured questionnaire was used to gather data from the respondents. The women in the experimental group were exposed to two hours of health education discussion addressing pertinent maternal health issues weekly for five weeks. Data were analyzed using descriptive statistics and independent t-test. All tests were measured at p?0.05 level of significance.

\end{abstract}


\keywords{clinic-based, health education, pregnant women, knowledge and attitudes, pregnancy management}

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\let\tabcellsep& 	 	 		 
\section[{Introduction}]{Introduction}\par
everal studies have shown the nexus between pregnant women's decision to use the primary health care facility especially for delivery and their knowledge of normal signs and symptoms of pregnancy, labour and puerperium, danger signs and symptoms of pregnancy, labour and puerperium, birth preparedness and complication readiness plans during pregnancy, labour and puerperium (JHPIEGO, 2004; \hyperref[b18]{Ujah et al., 2005;}\hyperref[b0]{Abass, 2008)}. Further studies have shown that about 75\% of all maternal deaths, globally, are those associated directly and indirectly with some Author ? ? : Department of Public Health, Babcock University, Ilishan-Remo, Ogun State, Nigeria. e Author ? : Department of Nursing Science, Babcock University, Ilishan-Remo, Ogun State, Nigeria.\par
-mail: akindan15ster@gmail.com sort of health care facility particularly during delivery and the week immediately after \hyperref[b7]{(Choudhry, 2005;} {\ref FMOH, 2009)}. The situation is particularly bad in developing countries like Nigeria \hyperref[b4]{(Bale, Stoll and Lucas, 2003}; Ekele, Bello, \hyperref[b1]{Adamu, 2003)}.\par
Nigeria is still one of the forty countries that had high Maternal Mortality Ratio (MMR) (defined as MMR ? 300 maternal death per 100,000 live births) giving a life time risk of maternal death 1 in 18 (WHO, UNICEF, UNFPA and the World Bank, 2010). When these rates are viewed globally, approximately 1 in 9 maternal deaths occur in Nigeria alone  {\ref (USAID, 2009)}. Beyond mortality cases, many other women suffer from injuries, infections or diseases related to pregnancy basically from lack of adequate knowledge (WHO, UNICEF, UNFPA, 2012). It is estimated that for every maternal death, at least thirty women suffer short to long term disabilities such as Vesico-Vaginal Fistula (VVF). For example, Nigeria accounts for 40\% of the global burden of VVF  {\ref (FMOH, 2007)}. This condition arises from prolonged unmanaged labour and complicated deliveries. For example, when the pregnant woman is still contemplating on going to the health facilities for delivery, she encounters three other delays according to Thaddeus and Mane (1994):\par
1. Delay at home in recognizing complications and deciding to seek for care. A woman may delay in deciding to seek care because of ignorance, inability to recognize danger signs or because of cultural inhibitions. 
\section[{Delay in accessing the appropriate health facilities.}]{Delay in accessing the appropriate health facilities.}\par
A further delay occurs when a woman is unable to reach a health facility due to distance, poor communication, inability to mobilize transport or to pay for transportation. 3. The delay in receiving care. The third delay occurs at the health facility when trained personnel and supplies are not immediately available to provide critical, life-saving care.\par
All these have a lot of bearing on the health and well-being of families, communities and in the social and economic situations of the societies. Each year an S estimated US \$15.5 billion is lost in potential productivity due pregnancy complications or when women and newborns die  {\ref (WHO 2007)}. Every year an additional two million children worldwide are maternal orphans  {\ref (WHO, 2007)}. Children without a mother are less likely to be immunized and are more likely to suffer from malnutrition (WHO, 2007).\par
Many intervention projects, programmes and policy strategies have been initiated globally and nationally in many countries including Nigeria to reduce complications surrounding pregnancy and parturition such as the Safe Motherhood Initiative \hyperref[b6]{(Berer, 1988)}  
\section[{Theoretical Framework}]{Theoretical Framework}\par
The study focused on health information dissemination necessary to equip selected pregnant women with the necessary knowledge and skills that will bring about changes in their attitudes and decrease in intervention complied with the information delivered and thus increased their knowledge level leading to decisions for better patronage of the healthcare facility was employed. The Comprehensive Health Education model (CHEM) was employed.\par
Following \hyperref[b8]{Farotimi (2011)} the CHEM model was applied following six steps thus:\par
Step I: The participants (pregnant women) were involved in an active learning process.\par
Step II: At the end of the program, these pregnant women were able to have in-depth understanding on Normal Symptoms of Pregnancy, Labour, Delivery and Puerperim; have better understanding as regards birth Preparedness and Complication Readiness (BP/CR) and to demonstrate positive attitudes towards Birth Preparedness and Complication Readiness (BP/CR).\par
Step III: The a priori expectation was that significant increase in knowledge of the participant will improve their attitudes and responses to health care services and consequently reduce complications associated with pregnancy and maternal mortality.\par
Step IV: The sampled women for the study were categorized into experimental and control groups. The experimental group were exposed to the motivational education and compared with the control group for knowledge increase.\par
Step V: Necessary resources were acquired and utilized to implement the program\par
Step VI: Evaluation was done with the use of questionnaire.  
\section[{To reduced the level of poverty in Nigeria}]{To reduced the level of poverty in Nigeria}\par
The National Reproductive Health Policy (NRHP) developed by FMOH in 2001. 
\section[{a)}]{a)}\par
To "achieve quality reproductive and sexual health for all Nigerians b)\par
To "reduce maternal morbidity and mortality due to  There are also eight registered Private Hospitals/Clinics, some Traditional Birth Attendants and religious Health Care Centres within the Local Government Area. 
\section[{IV.}]{IV.} 
\section[{Sampling Technique and Data Collection}]{Sampling Technique and Data Collection}\par
The multi-stage sampling technique was used to select a total of 96 participants from the five healthcare centres in the study area offering maternity care. The healthcare facilities were stratified into two for the control and experimental groups. Ikenne PHC ward II, Ilisan town PHC ward VII and Irolu PHC ward X were in the control groups while Iperu PHC, ward V and Ogere PHC VII were in the experimental group. Forty eight pregnant women were purposively selected from each group to represent the sample frame. Structured questionnaires designed in line with the developed Motivational Health Education Information (MHE) and with study objectives were used to gather data from the respondents. Reliability analysis was applied to test the internal consistency of the questionnaire. Result of the analysis showed that the average Cronbach's alpha value for the instrument was 0.82. Items of an instrument were considered to represent a measure of high internal consistency if the total Cronbach's alpha value was more than 0.7 \hyperref[b11]{(Graham, 2008 and}\hyperref[b13]{Muhamad, 2010)}. The intervention group was exposed to 5 weeks of intervention education following the focus group discussions.\par
V. 
\section[{Method of Data Analysis}]{Method of Data Analysis}\par
Both descriptive and inferential statistics were employed in analyzing data collected in the study. Frequency tables were used to present results for the descriptive analysis. Each construct of the questionnaire was coded along the appropriate ranking scale. Maximum point-scales were generated for each construct to measure the stated research variables, mean scores were also computed. The t-test was used to determine significant difference in the mean of the analyzed variables in the experimental and control groups. All statistical analysis were done using the statistical package for social science (SPSS version 17) and set at P? 0.05 levels of significances. Ethical clearance was obtained from the Ethical Review Committee, Babcock University and consent forms were filled by all participants.\par
VI. 
\section[{Results and Discussion}]{Results and Discussion}\par
a) Socio-demographic information of respondents Results in Table \hyperref[tab_1]{1} show that the respondents generally were below 35 years old (79\% for control and 92\% for experimental groups), mostly married (96\% for control and 100\% for experimental groups), from Yoruba ethnic group (75\% for control and 76\% for experimental groups) and largely Christians (50\% for control and 57\% for experimental groups). The result for educational level showed that the respondents had relatively good level of education with majority having secondary education and above (92\% for control and 72\% for experimental groups). The nexus between education and adoption of innovations for behavioral change has been detailed in previous studies \hyperref[b3]{(Babalola et al., 2013;} {\ref Omeonu et al., 2014;}\hyperref[b2]{Babalola, 2014)}. Thus the intervention is expected to have a significant impact on knowledge and attitude of the respondents. However, most of them were artisans (41\% for control and 38\% for experimental groups) and their monthly income was below N16,000 (<\$81) (42\% for control and 66\% for experimental groups) which is clearly below the national minimum wage of N18,000. This implies that although, most of these women may depend on their husbands for household financial sustenance, poverty level is likely high among the women. This may pose a challenge to the women's capacity to afford certain financial requirements for necessary healthcare.\par
Further results in Table \hyperref[tab_1]{1} showed that within the control group the majority of the respondents (67\%) had 1-2 children and also in the experimental group (45.2\%) had 1-2 children. Thus the women are expected to have certain knowledge about pregnancy management since they have had children before. Results of antenatal care (ANC) showed that most of the women (67\% for control and 74\% for experimental groups) had their first visit to the healthcare center between 20 th and 24 th weeks of pregnancy. However, the majority of the respondents (63\% for control and 62\% for experimental groups) visited the healthcare facility up to 4 times during ANC. 
\section[{VII. Result of the Intervention Effort}]{VII. Result of the Intervention Effort}\par
The women in the experiment group were exposed to 5weeks of intervention education as earlier stated. The knowledge levels and attitude, with respect to the earlier stated pregnancy management factors and practices, for both the control and experimental groups were assessed both at the beginning (baseline) and at the end of the intervention exercise. Results are in Tables \hyperref[tab_4]{3 and 4}.\par
Generally, at baseline, the knowledge levels for all variables were relatively low compared to the respective maximum point on scale of measure (MPS). The knowledge variable about signs and symptoms about normal pregnancy for the experimental group measured at baseline (MPS =20) had a mean score of 14.26 ± 1.64 while the control group had a mean of 13.98 ± 1.67.\par
Comparing the two mean scores, there was no significant difference between these mean scores (P=0.348). However, at immediate post-intervention, the experimental group had a mean score of 16.9405 ± 1.07 which was significantly higher than that of the control group (14.08 ± 1.72)(P=0.04). The knowledge variable about signs and symptoms of normal child birth measured at baseline (MPS = 20) showed no significant difference in respondents' knowledge level for experimental group (mean score of 16.45 ± 2.69) and the control group (mean of 16.2±2.16) (P=0.281). At immediate postintervention, there was a significant difference between the mean score of the knowledge level of the experimental group (18.88±1.03) and the control group (16.47±2.10) (P=0.001). The knowledge variable about signs and symptoms of normal puerperium measured at baseline (MPS = 20) also showed no significant difference in the respondents' level of knowledge for experimental (mean score of 16.20±2.24) and the control groups (mean of 16.50±1.82) (P=0.409). The knowledge variable for the experimental group measured at immediate post-intervention increased to 17.92±1.66 which was significantly higher than that of the control group (16.45±1.80) (P=0.048).\par
The knowledge variable about danger signs during pregnancy, measured at baseline (MPS = 24), had mean scores of 17.17 ± 2.84 and 16.83 ± 2.25 for the experimental and control groups respectively. There was no significant difference in the knowledge level for both groups at baseline (P=0.459). However, after the intervention, the mean scores knowledge level measured were 18.85 ± 0.96 and 16.83 ± 2.14 for the experimental and control groups respectively. Comparing the two mean scores, there was a significant difference between the mean scores (P=0.041). The knowledge variable about danger signs during labour, measured at baseline (MPS =12) on scale, had mean scores of 7.12 ± 1.81 and 6.67 ± 1.23 for the experimental and control groups respectively. The test statistics for significant difference showed no statistical significant difference between these two mean scores (P=0.09). After intervention, mean scores changed to 6.02±0.15 and 6.79±1.30 for the experimental and control groups respectively. The test statistics for significant difference showed statistically significant difference between the two mean scores (P=0.001). The knowledge variable about danger signs 7 days after delivery, measured at baseline (MPS =12), had mean scores of 7.69 ± 2.09 and 7.33 ± 1.81 for the experimental and control groups respectively. There was no significant difference between the mean scores for the two groups (P=0.306). After the intervention, the knowledge mean scores for experimental group became significantly higher (9.00 ± 0.01 and 7.25 ± 1.83 for the experimental and control groups respectively) (P=0.001). The knowledge variable about birth preparedness and complication readiness measured at baseline (MPS = 30), had mean scores of 19.81 ± 1.90 and 21.25 ± 2.21 for the experimental and control groups respectively. The test statistics for significant difference showed no significant difference between the two mean scores (P=0.126). When measured at immediate post-intervention, the mean scores were 26.18 ± 1.13 and 21.79 ± 1.87 for the experimental and control groups respectively indicating significantly higher knowledge level for experimental group (P=0.001).  significantly higher than that for the control group (24.83±4.12) (P=0.001). This result confirmed that the intervention influenced the participants by improving their knowledge and attitudes towards pregnancy management, birth preparedness and complication readiness. 
\section[{Volume}]{Volume} 
\section[{VIII. Conclusion and Recommendation}]{VIII. Conclusion and Recommendation}\par
This study assessed the influence of clinic based education on pregnant women's knowledge on normal pregnancy, danger signs and symptoms of pregnancy, labour and puerperium and their attitudes towards Birth Preparedness and Complication Readiness. The participants were selected from Ikenne LGA of Ogun state Nigeria. The investigation concluded by affirming significant impact of the motivational education on the stated knowledge variables and the attitudes of the respondents. Based on the findings of the study, the following recommendations have been suggested for policy action: o Corroborative intervention programme initiatives, directed at creating more awareness and necessary education for pregnant women should be encouraged o There is the need for improvement in the education given to pregnant women for general pregnancy management and care during delivery especially following recommended benchmark by WHO. o Pregnant women should be encouraged to start ANC appointments earlier and any cost implication subsidized to motivate use of healthcare facilities.\begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-2.png}
\caption{\label{fig_0}}\end{figure}
  \begin{figure}[htbp]
\noindent\textbf{} \par 
\begin{longtable}{P{0.85\textwidth}}
II.\end{longtable} \par
 
\caption{\label{tab_0}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{1} \par 
\begin{longtable}{P{0.85\textwidth}}
Polices\end{longtable} \par
 
\caption{\label{tab_1}Table 1 : Policies to Reduce Maternal Morbidity and Mortality in Nigeria}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{} \par 
\begin{longtable}{}
\end{longtable} \par
 
\caption{\label{tab_2}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2} \par 
\begin{longtable}{P{0.4486111111111111\textwidth}P{0.07870370370370369\textwidth}P{0.1086111111111111\textwidth}P{0.09916666666666667\textwidth}P{0.1149074074074074\textwidth}}
\tabcellsep \tabcellsep \tabcellsep Groups\tabcellsep \\
Variables\tabcellsep \multicolumn{2}{l}{Control (n= 48)}\tabcellsep \multicolumn{2}{l}{Experimental (n= 48)}\\
\tabcellsep Freq\tabcellsep \%\tabcellsep Freq\tabcellsep \%\\
Age\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
19-24yrs\tabcellsep 16\tabcellsep 33.3\tabcellsep 15\tabcellsep 31.0\\
25-29yrs\tabcellsep 10\tabcellsep 20.8\tabcellsep 11\tabcellsep 23.8\\
30-34yrs\tabcellsep 12\tabcellsep 25.0\tabcellsep 18\tabcellsep 38.1\\
35-39yrs\tabcellsep 4\tabcellsep 8.3\tabcellsep 4\tabcellsep 7.1\\
?40\tabcellsep 6\tabcellsep 12.5\tabcellsep 0\tabcellsep 0\\
Marital status\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
Married\tabcellsep 46\tabcellsep 95.8\tabcellsep 48\tabcellsep 100.0\\
Tribe\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
Yoruba\tabcellsep 36\tabcellsep 75\tabcellsep 37\tabcellsep 76.2\\
Non-Yoruba\tabcellsep 12\tabcellsep 25\tabcellsep 11\tabcellsep 23.8\\
Religion\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
Christianity\tabcellsep 24\tabcellsep 50\tabcellsep 27\tabcellsep 57.1\\
Islam\tabcellsep 22\tabcellsep 45.8\tabcellsep 18\tabcellsep 38.1\\
Traditional\tabcellsep 2\tabcellsep 4.2\tabcellsep 3\tabcellsep 4.8\\
Education\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
Below Secondary\tabcellsep 4\tabcellsep 8.3\tabcellsep 14\tabcellsep 28.6\\
Secondary and above\tabcellsep 44\tabcellsep 91.8\tabcellsep 34\tabcellsep 71.5\\
Husbands' Education\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
Below Secondary\tabcellsep 6\tabcellsep 12.5\tabcellsep 10\tabcellsep 21.4\\
Secondary and above\tabcellsep 44\tabcellsep 87.5\tabcellsep 38\tabcellsep 78.6\\
Occupation\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
Farming\tabcellsep 14\tabcellsep 28.8\tabcellsep 16\tabcellsep 32.4\\
Civil Servant\tabcellsep 8\tabcellsep 16.8\tabcellsep 9\tabcellsep 19.5\\
Artisans\tabcellsep 20\tabcellsep 40.8\tabcellsep 18\tabcellsep 38.4\\
Housewives\tabcellsep 7\tabcellsep 13.6\tabcellsep 5\tabcellsep 9.7\\
Income level (N)\tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_3}Table 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.35591133004926107\textwidth}P{0.0161505981703026\textwidth}P{0.007178043631245602\textwidth}P{0.008374384236453201\textwidth}P{0.007178043631245602\textwidth}P{0.09152005629838142\textwidth}P{0.02871217452498241\textwidth}P{0.18423645320197046\textwidth}P{0.05443349753694582\textwidth}P{0.06759324419422942\textwidth}P{0.02871217452498241\textwidth}}
\multicolumn{3}{l}{Variables}\tabcellsep \tabcellsep \tabcellsep Groups\tabcellsep Max\tabcellsep Mean\tabcellsep ±SD\tabcellsep Std. Error\tabcellsep Level of\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{points on}\tabcellsep Mean\tabcellsep Sig\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{scale of}\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{measure}\\
\multicolumn{4}{l}{Knowledge symptoms of normal preg about signs}\tabcellsep \&\tabcellsep control experiment\tabcellsep 20\tabcellsep 14.0833 16.9405\tabcellsep 1.723 1.068\tabcellsep .24882 .11655\tabcellsep 0.049\\
\multicolumn{5}{l}{Knowledge about signs and symptoms of normal labour}\tabcellsep control experiment\tabcellsep 20\tabcellsep 16.4667 18.8810\tabcellsep 2.096 1.026\tabcellsep .30267 .22109\tabcellsep 0.001\\
\multicolumn{5}{l}{Knowledge about signs and}\tabcellsep control\tabcellsep \tabcellsep 16.4583\tabcellsep 1.797\tabcellsep .25950\tabcellsep 0.048\\
symptoms\tabcellsep about\tabcellsep \tabcellsep \multicolumn{2}{l}{normal}\tabcellsep experiment\tabcellsep 20\tabcellsep 17.9286\tabcellsep 1.663\tabcellsep .18146\\
puerperium\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{5}{l}{Knowledge about danger signs and symptoms during preg}\tabcellsep control experiment\tabcellsep 24\tabcellsep 16.8333 18.8452\tabcellsep 2.137 0.963\tabcellsep .30847 .10508\tabcellsep 0.041\\
\multicolumn{5}{l}{Knowledge about danger signs and symptoms during labour}\tabcellsep control experiment\tabcellsep 12\tabcellsep 6.7917 9.0238\tabcellsep 1.303 0.153\tabcellsep .18821 .01673\tabcellsep 0.001\\
\multicolumn{5}{l}{Knowledge about danger signs}\tabcellsep control\tabcellsep \tabcellsep 7.2500\tabcellsep 1.827\tabcellsep .26380\tabcellsep 0.001\\
\multicolumn{5}{l}{and symptoms after delivery}\tabcellsep experiment\tabcellsep 12\tabcellsep 9.0000\tabcellsep 0.010\tabcellsep .00100\\
(puerperium)\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
Knowledge\tabcellsep \multicolumn{2}{l}{about}\tabcellsep \tabcellsep birth\tabcellsep control\tabcellsep \tabcellsep 21.7917\tabcellsep 1.867\tabcellsep .26955\tabcellsep 0.001\\
\multicolumn{5}{l}{preparedness and complication}\tabcellsep experiment\tabcellsep 30\tabcellsep 26.1786\tabcellsep 1.131\tabcellsep .12349\\
readiness\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
Attitudes\tabcellsep \multicolumn{2}{l}{towards}\tabcellsep \tabcellsep birth\tabcellsep control\tabcellsep \tabcellsep 24.3750\tabcellsep 4.123\tabcellsep .59521\tabcellsep 0.001\\
preparedness\tabcellsep \&\tabcellsep \multicolumn{3}{l}{complication}\tabcellsep experiment\tabcellsep 52\tabcellsep 41.3690\tabcellsep 4.250\tabcellsep .46377\\
\multicolumn{2}{l}{readiness plans}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{6}{l}{Source: Computed from field survey (2013)}\tabcellsep \tabcellsep \\
The\tabcellsep \multicolumn{2}{l}{attitude}\tabcellsep \multicolumn{2}{l}{variable}\tabcellsep towards\tabcellsep birth\tabcellsep \multicolumn{2}{l}{group had a mean of 24.83±4.41. There was no}\\
\multicolumn{7}{l}{preparedness and complication readiness for the}\tabcellsep \multicolumn{2}{l}{significant difference between these mean scores}\\
\multicolumn{7}{l}{experimental group measured at baseline (MPS = 52)}\tabcellsep \multicolumn{2}{l}{(P=0.324). At immediate post-intervention, the mean}\\
\multicolumn{7}{l}{had a mean score of 22.73±4.85 while the control}\tabcellsep \multicolumn{2}{l}{score for the experimental group (41.37±4.85) was}\end{longtable} \par
 
\caption{\label{tab_4}Table 4 :}\end{figure}
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