Effect of social support on fetal movement self-monitoring behavior in Chinese women: a moderated mediation model of health beliefs

Abstract

Objective

Strengthening the management of women’s self-monitoring during pregnancy is important to reduce fetal death in utero and improve maternal and infant outcomes. However, due to the lack of awareness among pregnant women about the importance of self-monitoring fetal movement, resulting in low behavioral compliance, adverse pregnancy outcomes remain common in China. This study aimed to investigate the relationship between social support and health beliefs and the self-monitoring behavior of fetal movement. In addition, we examined the moderating and mediating effects of health beliefs on fetal movement self-monitoring.

Methods

This cross-sectional study was conducted on 200 postpartum mothers in a tertiary hospital in China. The mothers were asked to complete a socio-demographic questionnaire, the fetal movement self-monitoring behavior questionnaire, the fetal movement self-monitoring health beliefs questionnaire, and the social support rating scale. Data from the questionnaires were analyzed and compared using SPSS 24.0 and PROCESS 3.2.

Results

The results of this study showed that the total scores of social supports, health beliefs, fetal movement self-monitoring were 42.98 ± 11.65, 78.605 ± 13.73, and 11.635 ± 2.86, respectively. The study found that when social support and health beliefs were included in the regression equation, both social support and health beliefs showed a positive correlation with fetal movement self-monitoring. Health beliefs partially mediated the effect of social support on fetal movement self-monitoring, accounting for 37.5% of the total effect.

Conclusion

Social support and health beliefs play a crucial role in influencing the self-monitoring behavior of fetal movements. Therefore, strengthening social support and health beliefs during pregnancy has the potential to improve compliance with fetal movement self-monitoring behaviors for pregnant women.

Keywords:

• Pregnant women
• fetal movement
• fetal movement counting
• social support
• health beliefs

Introduction

Maternal and child health is the foundation of the health of the entire population and an important indicator of a country’s health-care capacity. Core indicators include maternal mortality, under-five mortality and infant mortality [1]. With the advancement of medical technology and people’s awareness of perinatal safety, maternal and newborn mortality rates show a significant downward trend, but stillbirths have not received sufficient attention [2].

Normal fetal movement is considered an important indicator of fetal health [3]. While decreased fetal movement (DFM) is a risk factor for several adverse perinatal outcomes, such as restriction of intrauterine growth, preterm birth, or stillbirth [4–6]. Study on the causes of stillbirth showed that about a quarter of women experienced a reduction or disappearance of fetal movement during pregnancy [7]. Stacey T also reported that the presence of DFM is associated with a more than two-fold increased risk of stillbirth [8]. Therefore, real-time monitoring of fetal movement is very important to reduce or avoid adverse perinatal outcomes [9,10].

Compared with high-tech technologies such as electronic fetal heart monitoring (electronic fetal monitoring, EFM), color Doppler ultrasound and other fetal blood flow monitoring, fetal movement self-monitoring is the only effective means to assess the fetal health by pregnant women without the intervention of medical staff [11]. There are many kinds of fetal movement counting methods in clinical practice, but there are two kinds that are widely used. One is the 12-h fetal movement counting method developed on the basis of the fetal movement counting method proposed by Sadovsky. Pregnant women are required to count fetal movements once in the morning, in the middle and in the evening, each for an hour. The sum of three fetal movements is multiplied by 4, which is the total fetal movement of pregnant women for 12 h [12]. The other is the Count-10 Method, which refers to the method of counting only one fetal movement per day, counting from the first fetal movement, and recording the time used for 10 consecutive fetal movements [13]. Based on the comprehensive consideration of various guidelines, this study believes that pregnant women can choose the specific counting method of fetal movement according to their own conditions on the basis of adhering to the daily monitoring of fetal movement [14,15]. However, the clinical recommendation in China has been the earliest proposal of fetal movement counting scheme, which has not been updated in the methods, methods and warning values of fetal movement self-monitoring, and is obviously in a lagging state in the field of fetal movement monitoring.

Although the guidelines recommend that pregnant women begin daily self-monitoring of fetal movement at 28–32 weeks gestation, current implementation is not ideal [16]. A Nigerian study designed to determine maternal awareness, behavior, and concerns about abnormal fetal movement in the third trimester of pregnancy found that more than half of pregnant women incorrectly answered questions about abnormal fetal movement, and only 35.6% knew that at least one abnormal fetal movement could lead to an adverse pregnancy outcome [17]. The survey of Chinese scholar Wu JH et al. also showed that pregnant women had poor knowledge of fetal movement monitoring, and only 8.6% of pregnant women could perform daily fetal movement counting according to medical advice and fetal movement monitoring requirements. The vast majority of pregnant women are only occasionally counted during the third trimester, even 18.6% of pregnant women never count during the third trimester [18]. These studies suggest that most pregnant women still have significant limitations in their knowledge of fetal movement. Compliance with fetal movement monitoring behavior was also not optimistic.

During pregnancy, pregnant women have varying degrees of physiological, psychological and lifestyle changes. It may affect the attitudes, decisions and behaviors of pregnant women, and ultimately affect the health of pregnant women and the fetus [19,20]. Good external and family support plays a vital role in preventing and improving their health problems. Growing evidence shows that adequate social support from spouses, family members, and health care providers has a positive impact on pregnant women’s health, quality of life, and behavior [21–23]. Conversely, a lack of effective social support may lead to poor health outcomes and negative mental states [24]. It can be seen that social support exhibits positively effect on the behavior of pregnant women.

Health beliefs are individuals’ efforts to promote and maintain their own health in order to achieve the best state of well-being [25]. Previous studies have mostly focused on its impact on patient medical compliance [26,27]. While studies of pregnant women have found that continuous adjustment and improvement of women’s health beliefs can greatly improve their behavior [28]. To sum up, health beliefs play a crucial role in the formation of self-monitoring behaviors in pregnant women.

Although social support and health beliefs have been shown to influence pregnant women’s self-monitoring of fetal movement, few studies have included these three variables in a single study to study their relationship. In this study, we aim to explore the relationship between fetal movement monitoring behavior, social support, and health beliefs in Chinese women during the third trimester of pregnancy. In addition, explore the possible mediating role of health beliefs between pregnant women’s social support and self-monitoring of fetal movement. It will provide theoretical basis for clinical workers to better carry out maternal health education and improve the compliance of self-monitoring fetal movement during pregnancy.

Method

Description of sample

This cross-sectional study was conducted from January to June in Yangzhou City, China in 2023. We selected women who were not discharged after childbirth in the maternity ward of a hospital in this area as study subjects. The questionnaire is distributed and collected by the researchers themselves. Participants were provided with a secure room to fill out anonymous paper questionnaires. If participants have any questions during the filling process, researchers will answer them on the spot. The paper questionnaire included questions about socio-demographic variables and three validated self-report questionnaires. A total of 205 questionnaires were sent out, 205 were collected, and 200 were effectively answered, with an effective response rate of 97.6%. This study was conducted with the approval of the appropriate Ethics Committee, registration number: YZUHL20220105.

The inclusion criteria were: (1) full-term pregnancies; (2) conscious and able to communicate normally; (3) pregnant women and their families giving informed consent to the investigation; (4) all pregnant women included in this study had undergone regular antenatal examinations prior to admission. Exclusion criteria were as follows: pregnant women with serious diseases such as heart disease and malignant tumors.

Measurement instrument

Fetal movement self-monitoring behavior questionnaire

The fetal movement self-monitoring behavior questionnaire, a validated self-assessment questionnaire, was used to measure fetal movement self-monitoring behavior [29]. The questionnaire includes weekly monitoring days: 0 to 2 days is recorded as 1 point, 3–4 days is recorded as 2 points, 5–7 days is recorded as 3 points. Starting monitoring time: 31–32 weeks is recorded as 2 points; 28–30 weeks is recorded as 3 points. Fetal movement monitoring period: irregular time is recorded as 1-point, fixed time is recorded as 2 points, regular monitoring is recorded as 3 points. Post-treatment of abnormal fetal movement: 1 point for no treatment, 2 points for non-medical treatment on the same day, 3 points for medical treatment on the same day. The total score was 18, the higher the score, the better the self-monitoring behavior of fetal movement. Scores of 1–6, 7–12, and 13–18 indicated poor, good, and excellent fetal movement self-monitoring behavior, respectively. Internal consistency was revealed as good in the questionnaire (Cronbach’s α = 0.80).

Fetal movement self-monitoring health beliefs questionnaire

The fetal movement self-monitoring health beliefs questionnaire compiled by Chinese scholar Zhang Wen et al. [29]. The questionnaire was used to measure the level of self-monitoring of pregnant women’s health beliefs. It includes 5 dimensions: positive attitude, disease threat perception, subjective norms, perceived behavior control, and negative attitude, with a total of 21 items. The total score ranges from 21 to 105, and the higher the score, the higher the pregnant woman’s health beliefs in self-monitoring fetal movement. Each item was rated on a 6-point Likert-type scale ranging from 1 (always disagree) to 6 (always agree), generating a score range of 21–105 points. The Cronbach’s α coefficient of this questionnaire was 0.860 [24]. The questionnaire has good reliability and validity.

Social Support Rating scale(SSRS)

The Social Support Rating Scale was developed by Chinese scholar Xiao SY and was used to measure an individual’s social support [30]. It consists of 3 dimensions and 10 items, with a total score of 12–66 points. The higher the score, the better the social support level of the research object. The Cronbach’s α coefficient of this scale was 0.760. The scale has been shown to be reliable and effective.

Statistical analysis

All data were processed and analyzed using SPSS24.0 and PROCESS3.2. Descriptive analysis was used to assess the demographic and sociological characteristics of the participants, including age, education, occupation, etc. Correlation analysis was used to examine the relationship between key variables. In addition, PROCESS was used to investigate the moderated mediation model of health beliefs.

Results

General characteristics of study participants

Among the 200 participants invited to participate, 94.5% were between 18 and 35 years of age, and 5.5% were >35 years of age. Most women have university or post-secondary education (54.5%) and are employed (88%). Most participants lived in cities (65%). About 46.5% of women had a monthly household income of between 6,000 and 10,000 yuan. Only 11% of study participants were diagnosed with a high-risk pregnancy during pregnancy (≥35 years of age at delivery [31]). About 65.5% of the women had never experienced birth. About 78% of women reported receiving health education on fetal movement monitoring (78%). Most pregnant women do not use tools to measure fetal movement counts (89%). 84% of pregnant women chose the 12-h fetal movement count method, and only 16% chose the count-10 method. (See Table 1 for more information on demographics).

Table 1. Demographically characteristics of the sample (n = 200).

Characteristic	N (%)
Age (years)
18–35	189(94.5%)
>35	11(5.5%)
Residence
Rural	70(35%)
City	130(65%)
Highest degree
Other	11(5.5%)
High school	53(26.5%)
Bachelor degree	109(54.5%)
Master degree	27(13.5%)
Monthly household income
<3000	9(4.5%)
3000–5999	48(24%)
6000–10,000	93(46.5%)
>10,000	50(25%)
Occupation
Unemployed	24(12%)
Related to medicine	20(10%)
Unrelated to medicine	156(78%)
Birth experience
Never	131(65.5%)
Spontaneous abortion	16(8%)
Induced abortion	10(5%)
Have given birth	43(21.5%)
High-risk pregnancy
No	178(89%)
Yes	22(11%)
Receive health education
Yes	156(78%)
No	44(22%)
Use assistive tools to monitor fetal movement
Yes	22(11%)
No	178(89%)
Mode of fetal movement counting
12-h Fetal movement count method	168(84%)
Count-10 method	32(16%)

Note: Monthly household income (Chinese Yuan).

Level of social support, health beliefs, and fetal movement self-monitoring

First, we analyzed fetal movement self-monitoring scores, social support scores, and health beliefs. The results showed that the mean score (standard deviation) of social support was 42.98 ± 11.65 points. The mean score (standard deviation) of health beliefs was 78.605 ± 13.73, and the mean score (standard deviation) of fetal movement self-monitoring was 11.635 ± 2.86, all at the medium level. The results are shown in Table 2.

Table 2. Social support, health beliefs, and fetal movement self-monitoring of subjects.

Contents	Mean ± SD	Total
Social support	42.98 ± 11.65	66
Objective support	24.13 ± 5.71	31
Subjective support	10.48 ± 3.89	23
Support utilization	8.38 ± 2.24	12
Health beliefs	78.605 ± 13.73	105
Subjective norm	15.64 ± 2.65	20
Perceptual behavioral control	27.35 ± 3.29	35
Positive attitude	15.65 ± 2.65	20
Negative attitude	8.73 ± 3.27	15
Disease threat perception	11.25 ± 2.24	15
Fetal movement self-monitoring	11.635 ± 2.86	18

To further explore the correlation between social support, health beliefs and self-monitoring of fetal movement, we used Pearson correlation method for analysis. The results showed that the self-monitoring behavior of fetal movement was positively correlated with social support and health beliefs (r = 0.974–0.978, p < 0.01). The total score of social support was positively correlated with the total score of fetal movement monitoring behavior (r = 0.987, p < 0.01). Details can be found in Table 3.

Table 3. Correlations between social support, health beliefs and fetal movement self-monitoring.

	Fetal movement self-monitoring	Social support	Health beliefs
Fetal movement self-monitoring	1.000	–	–
Social support	0.978***	1.000	–
Health beliefs	0.974***	0.987***	1.000

Note: ***p<0.001.

Mediating and mediating effects of health beliefs in the relationship between social support and fetal movement self-monitoring

According to Bootstrap’s deviation-corrected percentile method, the mediating effect test was performed with the total score of fetal movement self-monitoring behavior of pregnant women in the third trimester as the dependent variable, social support as the independent variable, and health beliefs as the mediating variable (Figure 1). The results of the mediation model (Table 4) showed that social support could significantly positively predict health beliefs (β = 1.16, t = 85.33, p < 0.001). When both social support and health beliefs scores were included in the regression equation, both social support (β = 0.24, t = 66.05, p < 0.001) and health beliefs (β = 0.07, t = 4.06, p < 0.001) could positively predict fetal movement self-monitoring behavior. Furthermore, bootstrap 95% CI of the mediation effect did not contain 0 ([0.05, 0.12]), indicating that the mediation effect was significant, and the mediation action path diagram was shown in Table 4.

Figure 1. The final model and standardized model paths.

Table 4. Regression analysis of the relationship between variables in the mediation model.

Variable	Model 1		Model 2		Model 3
	β	t	β	t	β	t
Social support	0.24	66.05***	1.16	85.33***	0.15	7.15***
Health beliefs					0.07	4.06
R^2	0.96		0.97		0.96
F	4362.18***		7281.95***		2360.08***

(1) Each variable in the model is brought into the regression equation with standardized variables. (2) Model 1 – compliance of social support prediction behavior; Model 2 – social support predicts health beliefs; Model 3 – social support and health beliefs co-predict fetal movement self-monitoring. *** p<0.001

Health beliefs plays a role in partially mediating the impact of social support on behavioral compliance, and the mediating effect accounts for 37.5% of the total effect, which verifies hypothesis 2 (Table 5).

Table 5. Mediating effects of health beliefs.

Section	Effect	S.E.	Bootstrap 95% CI		Ratio of total effect
			LLCI	ULCI	37.5%
Total effect	0.24	0.00	0.23	0.25
Direct effect	0.15	0.02	0.11	0.20
Indirect effect	0.09	0.02	0.05	0.12

LLCI: lower level for confidence interval; ULCI: upper level for confidence interval.

Discussion

Pregnancy is an important event in a woman’s life. The death of a fetus in the womb can be a huge blow to the mother’s body and mind, causing irreparable trauma to the family [20]. Self-monitoring of fetal movement is the most simple, economical and effective method for pregnant women to self-evaluate fetal status in utero. This study found that the self-monitoring behavior of Chinese women’s fetal movement needs to be improved. Social support can serve as an external environment to regulate the self-monitoring behavior of fetal movements in pregnant women. The fuller social support, the more positive the self-monitoring behavior of pregnant women is. In addition, health beliefs play a mediating role in the relationship between maternal social support and self-monitoring behaviors, confirming that external social support can help pregnant women establish health beliefs, improve their confidence, and thus help them better implement self-monitoring and fetal movement behavior.

With the improvement of obstetric medical technology, the method of self-monitoring fetal movement is also constantly updated. But it is worth noting that most pregnant women in China choose the 12-h fetal movement count method for fetal exercise monitoring. Compared to the Count-10 method, pregnant women are prone to fatigue and low counting intent, which reduces compliance with self-monitoring of fetal movement [32]. It is suggested that clinical staff should update the study of fetal movement self-monitoring methods in time to help pregnant women choose the appropriate fetal movement counting method. Health care providers can also recommend mobile apps to pregnant women and encourage pregnant women to learn about fetal self-monitoring information from the official website [33,34]. Ensure that pregnant women correctly count fetal movement and help them complete fetal movement monitoring more easily and more effectively. In addition, pregnant women will have different knowledge of fetal movement monitoring due to individual differences. This requires clinical staff to provide personalized guidance to pregnant women according to their age, education level, family income and pregnancy complications, so that pregnant women can find their own rules of fetal movement and better complete self-monitoring of fetal movement. For example, medical staff can provide standardized courses for pregnant women. After completing the assessment of maternal mastery, failed pregnant women need to complete the next batch of maternity courses to increase maternal awareness of self-monitoring of fetal movement [35].

In our study, health belief scores were moderate. This may be due to the fact that pregnant women do not have a comprehensive understanding of the relevant knowledge of fetal self-monitoring. They did not realize the importance of fetal self-monitoring for fetal health. Indeed, maternal health beliefs can influence their self-monitoring behavior of fetal movements, and women with low health beliefs do not adhere to medical guidance during pregnancy [36]. Medical staff informing pregnant women of the importance and benefits of self-monitoring fetal movements, and providing individualized guidance on an individual basis, can improve women’s overall health belief level, thus increasing their awareness and motivation for self-monitoring behaviors [5]. It is very necessary for medical personnel to provide one-on-one guidance according to the specific situation of pregnant women, such as encouraging pregnant women to record the time and frequency of fetal activity in detail, and to answer pregnant women’s questions in a timely manner. At the same time, encouraging family members to participate in monitoring and enhancing pregnant women’s awareness and motivation for self-monitoring behavior can also promote pregnant women to follow the guidance of medical personnel [37]. In addition, our model shows that better social support predicts better health beliefs. It is consistent with Guo XJ et al. [35]. This may be because social support provides the strongest support for pregnant women. Not only improve their physical health, but also enhance their ability to manage stress and cope effectively. Make them more confident about pregnancy events [38]. Moreover, it is worth noting that the highest score in the total score of social support is subjective support. It indicates that good subjective support is a protective factor in reducing pregnancy stress in pregnant women. Pregnancy is an important transitional stage in the life of pregnant women. Compared to objective material assistance, such subjective emotional support from family and friends is more important for pregnant women [39]. Therefore, medical personnel need to strengthen the emotional companionship of family members and companions for pregnant women during the intervention process. For example, organizing group salon activities to encourage spouses to participate together, and through a good social atmosphere, further help pregnant women build confidence and motivation to self-monitor fetal movement.

Limitations

Due to regional, time and resource constraints, the samples in this study were from only one hospital in China, which may have a risk of selection bias. It is suggested that the sample size be increased and that joint multi-regional and multi-center studies be conducted in the future. In addition, this study did not consider self-efficacy, personality traits, maternal-fetal attachment, and other factors that may also affect women’s self-monitoring behavior in the third trimester of pregnancy [40,41]. In the future, qualitative and quantitative methods should be combined to further reveal the influencing factors for self-monitoring fetal movement in pregnant women. In the meantime, more specific interventions are needed to promote self-monitoring of fetal movement by pregnant women.

Conclusions

This study investigated the relationship between social support and self-monitoring of fetal movement in pregnant women, and the moderating and mediating role of health beliefs. The findings highlight the need for more large-scale sample studies in the future to understand the impact of other factors on self-monitoring fetal movement in pregnant women. Medical staff should start from the perspective of pregnant women, strengthen the emotional support of peers and family members to reduce their negative emotions. At the same time, improve the awareness of fetal self-monitoring of pregnant women, encourage them to master the intensity and regularity of fetal movement, timely detect fetal abnormalities and report, and help them form the correct understanding and healthy behavior of fetal self-monitoring, so as to obtain the best pregnancy outcome.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to restrictions, e.g. their containing information that could compromise the privacy of research participants.

Additional information

Funding

This work was supported by Postgraduate Research & Practice Innovation Program of Jiangsu Province, China [Grant number SJCX22_1828];Science and Technology Innovation Fund of Yangzhou University [X20220781];National Natural Science Foundation of China [Grant number 82101674];Natural Science Foundation of Jiangsu Province, China [Grant number BK20210815].