PRENATAL CARE EDUCATION

1

Prenatal Care Education in an Urban Underserved Population

Yana Alexander
Edson College of Nursing and Health Innovation, Arizona State University

Author Note
Yana Alexander is a registered nurse at Banner Health in the nursing department.
She has no known conflict of interest to disclose.
Correspondence should be addressed to Yana Alexander, Edson College of Nursing and Health
Innovation, Arizona State University, Downtown Campus, 550 N. 3rd Street, Phoenix, AZ 85004.
Email: yshoniya@asu.edu

PRENATAL CARE EDUCATION

2

Prenatal Care Education in an Urban Underserved Population
Background and Purpose: Across the United States, there are low adherence rates of prenatal
care visits, primarily among the low-income and ethnic populations. Inadequate prenatal care
education contributes to low appointment adherence and missed prenatal care during their first
trimester. The project aim is to assess the current use of paper-based prenatal education in a
Federally Qualified Health Center (FQHC) in southwestern Arizona and inquire if patients would
elect to engage in a phone application for prenatal education with appointment reminders.
Approach/Methods: The Theory of Planned Behavior was the theoretical framework utilized to
guide this project. The Quality Improvement (QI) project gathered information regarding patient
technology use and accessibility as well as utilization of FQHC prenatal booklet, collected with a
13-question survey. A non-identifying demographic questionnaire was also distributed during the
prenatal visit.
Results: Survey responses indicated that patients find utility in prenatal education and
appointment reminders provided through a phone application. Out of the total participants
(n=23), only 18 had received the prenatal care booklet and completed the entire survey. 80% of
participants expressed they would use the phone application while 84% find prenatal education
on the phone helpful. In comparison, less than 28% of respondents planned to continue to use the
prenatal booklet they were provided at the clinic during their pregnancy.
Outcomes: There is potential in utilizing digital platform and appointment reminders at FQHC
to improve appointment adherence and early entry to prenatal care. The results will be used to
inform FQHC on decisions regarding continuing prenatal booklet use and integration of techbased education formatting.
Keywords: prenatal, education, underserved, appointment adherence, early entry to prenatal care,
phone application, FQHC.

PRENATAL CARE EDUCATION

3

Prenatal Care Education in an Urban Underserved Population
Obtaining early and regular prenatal care is paramount to a healthy pregnancy.
Consistent/recurring obstetric (OB) visits allow for early detection of any health-related issues
that may harm the baby or mother. Unfortunately, there are significant financial, cultural, and
educational barriers that decrease adequate prenatal supervision and early entry prenatal care.
Adverse patient outcomes such as low birth weight, preterm births, conditions associated with
prematurity, and mortality have been linked with delayed entry into prenatal care, highlighting
how important establishing care early into a pregnancy is (Boerledier et al., 2015; Shah et al.,
2018).
Problem Statement
According to the Centers for Disease Control and Prevention (CDC), (2018), only 77.1%
of women who gave birth in 2016 initiated prenatal care in the first trimester of pregnancy,
which is defined as the first 12 weeks starting from day of conception. Prenatal care is vital to
prevent complications and inform women about important steps they can take to keep themselves
and their baby healthy. Research indicates that women who do not receive prenatal care in the
first three months are less likely to ever receive care during their pregnancy (Frayne et al., 2016;
Kingston et al., 2017).
There are several barriers to accessing prenatal care, such as socioeconomic
disadvantages, pregnancy-related stress, and limited health education, which can result in women
obtaining late prenatal care or not seeing a physician until they deliver. This is disastrous as
women without prenatal care are more likely to give birth to premature babies. A number of
peer-reviewed studies conclude that early and ongoing prenatal care is an accepted strategy to
improve health outcomes of pregnancy for mothers and infants (CDC, 2018; Osterman & Martin,

PRENATAL CARE EDUCATION

4

2018; Vitner et al., 2020). There are numerous benefits of early and regular prenatal care, which
include decreased risk of preterm delivery, lower risk of adverse maternal outcomes, and
improved birth weight.
The American College of Obstetricians and Gynecologists (ACOG), (2019) reports that
inadequate prenatal care is associated with adverse pregnancy outcomes; factors related to late
prenatal care include unintended pregnancy, rural residence, maternal age, and socioeconomic
background. According to the most recent data from ACOG (2019), approximately 45% of the
pregnancies in the United States are unintended. Women of child-bearing age who do not intend
to become pregnant are less likely to receive preconception education and schedule prenatal care
in the first trimester (ACOG, 2019). Therefore, the National Preconception Healthcare Initiative
(NPHI) recommends that health care systems adopt nine preconception wellness measures to
drive improvements in birth outcomes along with initiatives for early prenatal care (CDC, 2018).
Additionally, although prenatal care use has increased in recent years, significant
disparities continue to exist, especially among African American, Hispanic, and American
Indian/Alaska Native women (Selchau et al., 2017; Wyst et al., 2019). Hispanic women living
along or close to the U.S.-Mexico border have a lower first trimester prenatal care initiation
(FTPCI) than non-border or non-Hispanic women (Selchau et al., 2017). This inequality
highlights the need for preconception care and early entry into prenatal care, particularly among
the nulliparous population, defined as women who have never had a live birth.
Purpose and Rationale
Inadequate or absent prenatal care is not only a risk factor for poor pregnancy and poor
infant outcomes, it also significantly impacts the newborn’s best chance at a healthy start in life
and the woman’s transition into motherhood (Peahl et al., 2020; Selchau et al., 2017).

PRENATAL CARE EDUCATION

5

Considering new challenges to accessing early prenatal care, such as the recent global pandemic,
there is a demand to address the FTPCI rates in the United States, specifically in the southwest
region.
There is an increasing need for new methods and strategies to improve maternal and
newborn health outcomes through preconception and prenatal education. The purpose of this
literature review is to identify barriers to early prenatal care and promising strategies for getting
OB patients into pregnancy care sooner. Guidelines from ACOG (2019) emphasize that the first
visit for prenatal care typically occurs in the first trimester, with earlier entry and preconception
counseling resulting in positive maternal and infant outcomes regarding first and subsequent
pregnancies.
Background and Significance
Female Obstetric Patients
The problem that most southwest region prenatal care facilities are experiencing with OB
patients are low numbers of early entry prenatal care and a lack of consistency in patient visits
across the pregnancy timeline. The populations affected by this problem are the female OB
patients, their infants if proper screening and prenatal visits are not incorporated, their providers
who may miss important details of pregnancy due to missed appointments or late entry into
prenatal care, and the agencies overall from lack of adherence to prenatal visits and follow-up
(Oliveira et al., 2017). The ethnic, immigrant, and young adult OB populations are most at risk
for late entry pregnancy care (Warri & George, 2019; Wyst et al., 2019).
In regard to current literature available related to this problem, there are several studies
recently done on the barriers of early entry prenatal care that help shed some light on this
particular facility’s gap, most of them reporting on underserved and rural populations. The

PRENATAL CARE EDUCATION

6

findings illustrate that the financial, cultural, and educational elements are the most common and
reliable predictors of early prenatal care numbers on a global level (Boerledier et al., 2015;
Heaman et al., 2015). The literature highlights the importance of timely intervention and
development of strategies that will address barriers women may face in obtaining early prenatal
care and continuing this care throughout their pregnancy and postpartum (Shah et al., 2018;
Warri & George, 2020).
Social Media Interventions
The approach to the presentation of information to OB patients is just as important as the
information itself. Adults, especially soon-to-be mothers, have shown high levels of participation
in social media interventions related to health behaviors and education, emphasizing the value of
technology in future patient education (Chatwin et al., 2021; Heaman et al., 2015; Marko et al.,
2019). The utilization of technology and social media in providing early prenatal awareness to
the target population is promising. Literature suggests that social media appears to have the
potential to reach high-risk women (Wyst et al., 2019).
Furthermore, a strength of utilizing the technology model to provide preconception and
prenatal education is its adaptability with current unprecedented challenges (Chatwin et al.,
2021). Technology has the ability to reach, educate, and inform large portions of women,
especially those who have significant barriers in accessing quality prenatal care. Women of
child-bearing age report high satisfaction with the accessibility and platform by which maternal
education through social media is presented (Chen et al., 2020; Kingston et al., 2017). A strength
of prenatal social media utilization in this arena is the ability to reach multiparous women,
mothers with full-time jobs, and pregnant patients residing in rural areas. There is evidence to
suggest that even in the upcoming post-pandemic years, the supplemental antenatal care

PRENATAL CARE EDUCATION

7

provided through technology and social media will continue to support women who are pregnant
or will become pregnant (Marko et al., 2019).
Current Practices
Current practices consist of in-office paper pamphlets produced with the goal of
providing prenatal education at the visit and as a resource for the patient to take home (Chen et
al., 2020). Additionally, annual well women appointments and prenatal visits are considered the
most appropriate time to provide information to pregnant patients and those who may become
pregnant (Desta et al., 2019). This current process of providing preconception and prenatal
education excludes patients who cannot meet in-person for their prenatal appointments or women
who have yet to schedule an introductory first trimester prenatal appointment (Robbins &
Martocci, 2020).
Desired or Future State (DoFS)
There are compelling reasons to ensure timely and quality prenatal care. It is also
imperative to improve performance to optimize the health outcomes of pregnancy for expecting
mothers (Desta et al., 2019; Warri & George, 2020). The expected outcomes of this project are
increased adherence to prenatal and postnatal care visits, increased early entry prenatal care
numbers at the facility, and improved pregnancy and postpartum education to facilitate further
communication between provider and patient.
The ideal situation if the problem is solved would be all OB patients receiving early
prenatal care, which would have the potential to decrease complications in later trimesters. Early
entry into prenatal care is defined as establishing care within thirteen weeks of the mother’s last
menstrual period, and this would be the targeted early enter date (Robbins & Martocci, 2020;
Shah et al., 2018). If the first visit is done early, the patient will not only be established for

PRENATAL CARE EDUCATION

8

prenatal care and more likely to adhere to scheduled appointments throughout the pregnancy, but
also more educated and empowered in their current or future pregnancy status.
Internal Data
The agency is a federally qualified health center (FQHC) providing full prenatal care,
including postpartum visits, to the underserved obstetric population in the southwest region of
the United States. According to the family nurse practitioner who sees the discussed population,
70% of this agency’s patients are uninsured, and can count on services regardless of their
Medicaid or private insurance status (L. Maurer, personal communication, November 24, 2020).
This particular patient population has low FTPCI rates; therefore, the FQHC is looking to
promote preconception counseling and early prenatal care.
In recent communications with the family nurse practitioner in this practice, OB patients
reported, through surveys and word of mouth, not understanding the need for so many prenatal
appointments, feelings of having missed vital pregnancy information in the first trimester, and a
sense of regret for not establishing prenatal care earlier in the pregnancy (L. Maurer, personal
communication, November 24, 2020). The hard data consists of deidentified reports discussed
during a zoom call with the site’s family nurse practitioner, showing missed appointments in
between of trimesters and a significantly lower number of early entry prenatal care patients
compared to late entry prenatal care (L. Maurer, personal communication, November 24, 2020).
Factors that contribute to this problem identified in the literature are socioeconomic and
sociocultural status, age, number of pregnancies, educational level, and poor obstetric and
gynecological history (Boerledier et al., 2015; Desta et al., 2019; Heaman et al., 2015; Shah et
al., 2018). Preliminary interest in this problem led to an inquiry of current evidence to determine
the best strategies for establishing early prenatal care visits. This literature review has led to the

PRENATAL CARE EDUCATION

9

clinically relevant PICOT question, “In women of child-bearing age, how does prenatal
education presented through technology compare with the current prenatal educational format
improve early entry to prenatal care?"
Search Strategy
An extensive search for the most current evidence was performed in the electronic
databases PubMed, EBSCOhost, and PsycINFO. These databases were selected for their
relevancy to the topics of early entry to prenatal care and technologically based prenatal
education and peer review. Keywords included: pregnant women, prenatal, early, care, female,
underserved, childbearing age, obstetric-gynecologic, technological, education, social media,
online application, virtual learning, current methods, and standard of care. Search limits were
set to include publication dates between 2015-2021 and English language. Exclusion criteria
included articles prior to 2015, articles that were not peer-reviewed, articles addressing
gynecologic patients who have never been pregnant, and articles only addressing paper and
presentation-based prenatal education. Studies included data from multiple countries such as
United Kingdom, Ethiopia, China, United States, and Mexico. Inclusion and exclusion criteria
were the same for all databases. The initial search of female OR obstetric-gynecologic AND
underserved AND early prenatal care AND social media OR technological education yielded a
total of 1096 results in PubMed, 751 results in EBSCOhost, and 347 in PsycINFO.
To further narrow the search, a combination of the keywords was changed to include
tech-based intervention, online education, social media, first trimester prenatal care, and
current practice. After hand searching results, screening for relevance, and removing duplicates,
38 studies remained for further review; 19 of these were from PubMed, 16 from EBSCOhost,
and 3 from PsycINFO database. Grey literature of government publications from the Centers for

PRENATAL CARE EDUCATION

10

Disease Control and Prevention (CDC) and American College of Obstetricians and
Gynecologists (ACOG) were also searched. Additional applicable studies were searched for in
the reference lists. Following rapid critical appraisals, 10 studies were selected for this literature
review. This included four systematic reviews, three randomized controlled trials, and three cross
sectional studies. The chosen studies addressed the PICO appropriately and examine the
relationship between current prenatal education formats and technology-based prenatal education
in relation to early entry to care.
Critical Appraisal & Synthesis of Evidence
Study quality and level of evidence was determined through rapid critical appraisal
(RCA) tools (Melnyk & Fineout-Overholt, 2019). Although both qualitative and quantitative
studies (see Appendix A, Table A1) were found during the literature search, only quantitative
studies were included in the evaluation and synthesis tables (see Appendix B, Table A2) due to
the higher level of evidence and applicability. The majority of the studies had relatively large
samples with heterogenous measurement tools used. The subjects within the studies had widely
varying demographics in relation to socioeconomic background and education level; however,
the sample characteristics were relatively homogenous as all participants were females of childbearing age between 15 and 44 years old. There was heterogeneity observed with study settings
as some were conducted in rural, underserved locations or in countries outside of the United
States. At least half of the studies targeted barriers for access to early prenatal care.
Six studies focused on the barriers women have in accessing quality prenatal care and
early access to prenatal care, primarily in disadvantaged and rural populations. Five of 10 studies
examined the role of technological interventions, including web-based, phone application, social
media, telehealth, or remote monitoring, in advancing early access to prenatal care. Two studies

PRENATAL CARE EDUCATION

11

investigated the role of mental health in maternal and child outcomes as well as successful
strategies in providing access to support services. Most interventions resulted in positive
behavioral and health outcomes and high participant satisfaction scores. Improved access to
prenatal education, support, and services was noted in several studies, which are important
factors in maternal empowerment and promoting health and pregnancy outcomes for both mother
and child (see Theory Application).
Conclusions from Evidence
The evidence suggests that empowering pregnant women through prenatal education and
providing tech-based prenatal care for physical and mental well-being addresses significant
barriers related to early and consistent prenatal care. Additionally, it is abundantly clear that
utilizing online and virtual interventions improves maternal and neonatal health outcomes,
especially in hard-to-reach populations including disadvantaged and low-socioeconomic
backgrounds. From the included studies, evidence clearly displays the importance of early entry
to prenatal care. However, there is a lack of initiative in employing online, social media, and ehealth strategies to build awareness around pre-conception and early pregnancy stages.
Therefore, programs applying tech-based education and awareness which target women of childbearing age and in their first trimester of pregnancy should be considered to increase early entry
to prenatal care.
Theory Application
The theory of planned behavior (TPB) was instrumental for this project because it
assumes that behavior is planned and thus predicts deliberate behavior. This theory assists in
successfully predicting and explaining health behaviors and intentions, which can be especially
helpful in guiding prenatal health promotion and disease prevention (see Appendix C, Figure 1).

PRENATAL CARE EDUCATION

12

Overall, the TPB has shown more utility in public health compared to the Health Belief Model;
however, it is still limiting regarding environmental and economic influences of behavior (Ajzen,
1991). The TPB states that behavioral achievement depends on both intention or motivation and
ability or behavioral control (Ajzen, 1991).
This model demonstrates exceptional utility in effectively preventing high-risk behaviors
among pregnant women and introducing more perceived power and behavioral control over
prenatal care visits. Additionally, it is often used in healthcare settings to understand behavioral
intent and thereby influence the likelihood of a behavior. This theoretical framework is
appropriate for the planned intervention as it will aid in generating positive and impactful
prenatal behavior and perception change. With the project purpose in mind, the TPB is an
excellent framework for helping patients believe the necessity for change and taking the
appropriate cues to action as a result. To ensure success with this model, it is critical to identify
intentions and behaviors that are appropriate and meaningful to women looking to become
pregnant or in early stages of pregnancy.
Implementation Framework
The Iowa Model (IM), which serves as a guide for nurses to use research findings to
improve patient care, is an essential pathway to evidence-based practice (Iowa Model
Collaborative, 2017). The model was used in the execution of this project because it focuses on
the emergence of implementation science with an emphasis on patient engagement, a central
focus of the project purpose (see Appendix D, Figure 2). The IM helps identify issues, research
solutions, and implement changes (IMC, 2017)

PRENATAL CARE EDUCATION

13

This model will be fitting for this project as it provides ample time in which to reassess
and adjust the change based on patient population and organizational structure (IMC, 2017)
the gap was identified by a clinician at the project site and continues to be an organizational
initiative. The question or purpose is then stated, which has been finalized for implementation
(IMC, 2017). The consideration of the topic being a priority is the next step, which it is for the
clinic. Furthermore, a team has been formed and during this time a synthesized body of evidence
formulated. After concluding that there is sufficient evidence, which in this case there is, the
following step on the IM is to design a way to gather useful information for whether the
intervention is needed or not. through engagement with patients (IMC, 2017). This is the current
protocol in place. Once the change is deemed appropriate for adoption in practice by clinic
higher-ups, it can begin to be piloted, integrated and sustained as a practice change. Finally,
results are disseminated on the EBP tool to promote excellence in health care (IMC, 2017).
Methods
Ethical Considerations
Human subjects’ protection was thoroughly considered for this project with minimal
direct patient contact, thereby limiting risk of HIPPA violations. No identifiable information was
collected from patients during the consenting and survey process. Therefore, completed surveys
were not linked to participants in any way. The project meets duties set forth by the American
Nurses Association Code of Ethics which calls for nurses to work to reduce health disparities
among vulnerable populations in provision 8 (2015).
Population and Setting
The FQHC has two locations in Southwestern United States with both locations included
in the project. This FQHC sees both uninsured and undocumented patients. The prenatal

PRENATAL CARE EDUCATION

14

population that attends this center is primarily Hispanic/Latino and Spanish-speaking. Most
patients have limited health literacy in either Spanish or English. The inclusion criteria for the
project consisted of prenatal patients ages 18-40, English and Spanish-speaking, and must have
had at least one prenatal visit prior. Exclusion criteria for the project included postpartum and
preconception patients.
Project Description, Instrument, and Timeline
This project aimed to assess current state of paper-based prenatal education and if patient
population are good candidates for digital platforms of prenatal education at a FQHC in Phoenix,
AZ. There are barriers with patients at this facility including the lack of knowledge for needing
multiple appointments resulting in missed appointments and missing vital pregnancy
information. The QI project gathered information regarding patient technology use and
accessibility as well as utilization of FQHC prenatal booklet, collected with a 13-question survey
(see Appendix M, Figure 11). The prenatal care education survey also has a Spanish version on
the second side (see Appendix N, Figure 12). A non-identifying demographic questionnaire was
also distributed during the prenatal visit which collected information such as age, insurance
status, number of pregnancies, number of living children, and educational background to assess
this for barriers to prenatal care (see Appendix G, Figure 5). This demographics survey was also
provided in Spanish (see Appendix H, Figure 6).
For recruitment, a list of prenatal patients meeting inclusion criteria was presented to coinvestigator and the site champion at the start of the day. Eligible individuals received a project
flyer during check-in by office staff with project information, both in English and Spanish (see
Appendix I, Figure 7; see Appendix J, Figure 8). They were recruited prior to their prenatal
appointment at the clinic or during their wait for a clinician. Recruitment included 2-3 sentence

PRENATAL CARE EDUCATION

15

explanation of project goal and its relation to clinic, a prompt was provided to the staff and
providers in English and Spanish (see Appendix K, Figure 9; see Appendix L, Figure 10).
Recruitment and distributing consent form took approximately 2-5 minutes. The consent form
was reviewed/provided to each participant to keep in both English and Spanish (see Appendix E,
Figure 3; see Appendix F, Figure 4).
Participants completed a 13-question survey at their prenatal visit in order to collect this
information. Assessing what format of prenatal care education will be best utilized by the patient
population helps to identify the clinic’s next steps regarding their prenatal education. The survey
was reviewed by 3 experts consisting of three DNP faculty, one of which works at a FQHC.
Surveys and demographic information were stored in a locked drawer at the clinic. They have
since been shredded along with the demographic information collected.
Literature search and project design was initiated in summer of 2021. IRB ASU exempt
status approval was obtained on November 22, 2021. Data collection at the two FQHC sites took
place over 8 weeks starting in February 2022 and ending in April 2022. Spring of 2022 is when
data analysis and dissemination took place, with 2 weeks in April 2022 used to organize data in
Excel and analyze through Intellectus Software using descriptive statistics. Dissemination
wrapped by May 2022 with final reports, results, poster, executive summary, and presentation
provided to stakeholders of the clinic and Arizona State University. No funding was received for
this project. Printing costs associated with paper materials and translation services were paid for
by project site and co-investigator.
Results
Demographic Results

PRENATAL CARE EDUCATION

16

The population are prenatal patients (n=23) being seen in a primary care setting. The
most frequently observed category of Age Range was 25-35 [8(35%)]. The most frequently
observed category of Number_of_living_children was 2 [6(26%)]. The most frequently observed
category of Insurance Status was AHCCCS [10(43%)]. The most frequently observed category
of Level_of_Education was High School [15(65%)]. Frequencies and percentages are presented
in Appendix O, Table 1.
Phone Application Survey Results
The following results reflect data collected from answers to questions 1-9 on the Prenatal
Care Education Survey. Frequencies and percentages were calculated for Use_Portal,
Have_SmartPhone, Internet_Access_on_Phone, Would_use_Phone_App, Missed_Visit,
X24_hour_reminder, X2_hour_reminder, App_Helpful, and Received_Prenatal_Booklet. Most
of the sample reported that they do not use the patient portal [13(57%)]. The most frequently
observed category of Have_SmartPhone was Yes (n = 20, 86.96%). The most frequently
observed category of Internet_Access_on_Phone was Yes [18(78%)]. The most frequently
observed category of Would_use_Phone_App was Yes [20(87%)]. The most frequently observed
category of Missed_Visit was No [17(74%)]. The most frequently observed category of
X24_hour_reminder was Yes [17(74%)]. The most frequently observed category of
X2_hour_reminder was Yes [15(65%)]. The most frequently observed category of App_Helpful
was Yes [21(91%)]. The most frequently observed category of Received_Prenatal_Booklet was
Yes [18(78%)]. Frequencies and percentages are presented in Appendix P, Table 2.
Prenatal Booklet Survey Results
The following results reflect data collected from answers to questions 10-13 on the
Prenatal Care Education Survey. If at question 9, the participant answered no, they would not

PRENATAL CARE EDUCATION

17

continue to question 10-13 of the survey. 18 participants finished the survey (question 10-13).
Frequencies and percentages were calculated for Read_Booklet, Booklet_Helpful,
Booklet_Easy_to_read_and_understand, and Plan_to_use_booklet. The most frequently observed
category of Read_Booklet was No [(10, 56%)]. The most frequently observed category of
Booklet_Helpful was No [11(61%)]. The most frequently observed category of
Booklet_Easy_to_read_and_understand was No [11(61%)]. The most frequently observed
category of Plan_to_use_booklet was No [13(72%). Frequencies and percentages are presented
in Appendix Q, Table 3.
Impact of Project
For FQHCs, a program such as this may not only be cost-effective, but also supplemental
in reaching young women in the pre-conception stage or first trimester despite identified barriers
in access to prenatal care. Providing empowerment and education to women early in their
pregnancy can significantly improve continuity of prenatal care, postpartum follow-up
attendance, access to resources, and adherence to positive pregnancy health behaviors. This also
has the potential to decrease pregnancy, maternal, and infant complications and pregnancyrelated stress and anxiety.
The design and implementation of this project adapts to the recent health and societal
state of the world, providing the ability to reach women regardless of rural location,
socioeconomic background, and education level. Lastly, the technology-based intervention can
be used to provide education and awareness in other arenas of women’s health in FQHCs. The
outcomes will now inform FQHC on decisions regarding continuing prenatal booklet use and
integration of tech-based education formatting. Since the patient population are good candidates

PRENATAL CARE EDUCATION

18

for this technology-based education, the facility may plan to adopt the phone application and
implement it into practice in the future.
Discussion
Summary, Facilitators, and Limitations
Following data analysis, there is clear potential in utilizing digital platforming and
appointment reminders with the prenatal patient population at the FQHC to improve appointment
adherence and early entry to prenatal care (see Appendix R, Graph 1). Out of 10 total
participants, 18 received the prenatal care booklet and completed the entire survey. 87% of
participants reported that they would use the phone application at the site for prenatal care
education and appointment reminders. 91% of participants reported that they would find prenatal
education on the phone helpful. 87% of participants have smart phone with application capability
and 78% of participants have internet access on their phone. Lastly, out of 18 participants who
received the prenatal booklet and continued past question 9, 44% reported reading the booklet,
39% found it helpful, easy to read and understand, and only 29% plan to use the booklet during
the rest of their pregnancy.
The demographics results highlighted that 81% of participants were 35 years or younger,
44% were insured under AHCCCS and 39% were uninsured, and only 72% completed High
School with 11% never finishing High School (see Appendix S, Graph 2). These demographic
results indicate the need to assess the prenatal booklet for appropriateness to patient literacy and
health literacy.
The strengths of this project include a cost-effective, reliable, and versatile survey.
Another strength noted were that participants were receptive to data collection and Spanishspeaking patients were included. Furthermore, the demographic questions provided perspective

PRENATAL CARE EDUCATION

19

to any potential barriers in prenatal education and appointment adherence, which showed
significant findings in analysis. Alternatively, the barriers of the project included small sample
size and time constraint in data collection between IRB approval and project deadline.
Recommendations
Assessment of prenatal care education is completed at the FQHC site. The next steps
include continued research with a prototype phone application or existing phone application that
meets the qualifications of the education necessary for patients and appointment reminders.
There are several applications currently on the market which can be utilized for an ongoing
project. However, these applications, such as myJourney Pregnancy App and Glow Nurture are
limited in the educational content they provide, and it is not to the extent of the prenatal booklet
currently being utilized by the facility (Coughlin, 2021). Additionally, the applications do not
contain an appointment reminder feature and the only application which does is iPregnancy
Tracker, created solely for this purpose (Coughlin, 2021). The ongoing research may be
conducted by DNP students as a legacy project with the site.
-

PRENATAL CARE EDUCATION

20
References

American College of Obstetricians and Gynecologists. (2019, January). Prepregnancy
counseling. https://www.acog.org/clinical/clinical-guidance/committeeopinion/articles/2019/01/prepregnancy-counseling
American Nurses Association. (2015). Code of ethics for nurses with interpretative statements.
American Nurses Association. Retrieved from: nursingworld.org/coe-view-only
Ashford, M. T., Olander, E. K., & Ayers, S. (2016). Computer- or web-based interventions for
perinatal mental health: A systematic review. Journal of Affective Disorders, 197, 134146. https://doi.org/10.1016/j.jad.2016.02.057
Boerledier, A. W., Mannien, J., Cherelle, M. V., Wiegers, T. A., Feijen-de Jong, E. I., Spelten, E.
R., & Deville, W. L. J. (2015). Explanatory factors for first and second-generation nonwestern women’s inadequate prenatal care utilization: A prospective cohort study. British
Medical Journal Pregnancy and Childbirth, 15(1), 98-108. https://doi.org/
10.1186/s12884-015-0528-x
Chatwin, J., Butler, D., Jones, J., James, L., Choukri, L., & McCarthy, R. (2021). Experiences of
pregnant mothers using a social media based antenatal support service during the
COVID-19 lockdown in the UK: Findings from a user survey. BMJ Open, 11(1), 271278. https://doi.org/10.1136/bmjopen-2020-040649
Catherine, N. L. A., Lever, R., Sheehan, D., Zheng, Y., Boyle, M. H., McCandless, L., Gafni, A.,
Gonzalez, A., Jack, S. M., Tonmyr, L., Varcoe, C., MacMillan, H. L., & Waddell, C.
(2019). The British Columbia healthy connections project: Findings on socioeconomic
disadvantage in early pregnancy. BMC Public Health, 19(1161) 1-11,
https://doi.org/10.1186/s12889-019-7479-5

PRENATAL CARE EDUCATION

21

Chen, M., Liu, X., Zhang, J., Sun G., Gao Y., Shi, Y., Baker, P., Zeng, J., Zheng, Y., Luo, X., &
Qi, H. (2020). Characteristics of online medical care consultation for pregnant women
during the COVID-19 outbreak: Cross-sectional study. British Medical Journal, 10(11),
1-10. https://doi.org/10.1136/bmjopen-2020-043461
Desta, M., Kassie, B., Chanie, H., Mulugeta, H., Yirga, T., Temesgen, H., Leshargie, C. T.,
Merkeb, Y. (2019). Adherence of iron and folic acid supplementation and determinants
among pregnant women in Ethiopia: A systematic review and meta-analysis.
Reproductive Health, 16(1), 182-196. https://doi.org/10.1371/journal.pone.0223120
Frayne, D. J., Verbiest, S., Chelmow, D., Clarke, H., Dunlop, A., Hosmer, J., Menard, K. M.,
Moos, M. K., Ramos, D., Stuebe, A., & Zephyrin, L. (2016). Health care system
measures to advance preconception wellness. American College of Obstetricians and
Gynecologists, 127(5), 863-872. https://doi.org/10.1097/AOG.0000000000001379
Heaman, M. I., Sword, W., Elliot, L., Moffatt, M., Helewa, M. E., Morris, H., Gregory, P.,
Tjaden, L., & Cook, C. (2015). Barriers and facilitators related to use of prenatal care by
inner-city women: Perceptions of health care providers. British Medical Journal
Pregnancy and Childbirth, 15(2), 1-13 10.1186/s12884-015-0431-5
Hochbaum, G., Rosenstock, I., & Kegels, S. (1952). Health belief model. Washington, DC: U.S.
Public Health Service.
Kingston, D., Biringer, A., Veldhuyzen van Zanten, S., Giallo, R., McDonald, S., MacQueen, G.,
Vermeyden, L., & Austin, M.P. (2017) Pregnant women’s perceptions of the risks and
benefits of disclosure during web-based mental health e-screening versus paper-based
screening: Randomized controlled trial. JMIR Publications, 4(4), e42-e53.
https://doi.org/10.2196/mental.6888

PRENATAL CARE EDUCATION

22

Marko, K. I., Ganju, N., Krapf J. M., Gaba, N. D., Brown, J. A., Benham, J. J., Oh, J., Richards,
L. M., & Meltzer, A. C. (2019). A mobile prenatal care app to reduce in-person visits:
Prospective controlled trial. JMIR Publications, 7(5), 1-7. https://doi.org/10.2196/1052
Melnyk, B. M., & Fineout-Overholt, E. (2019). Evidence-based practice in nursing and
healthcare: A guide to best practice (4th ed.). Wolters Kluwer.
Ngo, E., Truong, M. B., & Nordeng, H. (2020). Use of decision support tools to empower
pregnant women: Systematic review. Journal of Medical Internet Research, 22(9), 1-10.
https//doi.org/10.2196/19436
Oliveira, I. B. B., Leal, L. P., Coriolano-Marinus, M. W., Santos, A. H., Horta B. L., & Pontes,
C. M. (2017). Meta-analysis of the effectiveness of educational interventions for
breastfeeding promotion directed to the woman and her social network. Journal of
Advanced Nursing 73(2), 323-335. https://doi.org/10.1111/jan.13104
Osterman, M. J. K., & Martin, J. A. (2018). Timing and adequacy of prenatal care in the United
States, 2016. Centers for Disease Control and Prevention.
https://www.cdc.gov/nchs/data/nvsr/nvsr67/nvsr67_03.pdf
Peahl, A. F., Smith, R. D., & Moniz, M. H. (2020). Prenatal care redesign: Creating flexible
maternity care models through virtual care. American Journal of Obstetrics and
Gynecology, 223(3), 389-392. https://doi.org/10.1016/j.ajog.2020.05.029
Robbins, C., & Martocci, S. (2020). Timing of prenatal care initiation in the health resources and
services administration health center program in 2017. Annals of Internal Medicine,
173(11), S29-S36. https://doi.org/10.7326/M19-3248

PRENATAL CARE EDUCATION

23

Rosswurm, M. A., & Larrabee, J. H. (1999). A model for change to evidence-based practice.
Image: Journal of Nursing Scholarship, 31(4), 317–322. https://doi.org/10.1111/j.1547
5069.1999.tb00510.x
Selchau, K., Babuca, M., Bower, K., Castro, Y., Coakley, E., Flores, A., Garcia, J. O., Reyes, M.
L. F., Rojas, Y., Rubin, J., Samuels, D., & Shattuck, L. (2017). First trimester prenatal
care initiation among Hispanic women along the U.S. – Mexico border. Maternal and
Child Health Journal, 21(1), 11-18. https://doi.org/10.1007/s10995-017-2374-0
Shah, J. S., Revere, F. L., & Toy, E. C. (2018). Improving rates of early entry prenatal care in an
underserved population. Maternal and Child Health Journal, 22(12), 1738-1742.
https://doi.org/ 10.1007/s10995-018-2569-z
Tobah, Y. S. B., LeBlanc, A., Branda, M. E., Inselman, J. W., Morris, M. A., Ridgeway, J. L.,
Finnie, D. M., Theiler, R., Torbenson, V. E., Brodrick, E. M., Mooij, M. M., Gostout, B.,
& Famuyide, A. (2019) Randomized comparison of a reduced-visit prenatal care model
enhanced with remote monitoring. American Journal of Obstetrics and Gynecology,
221(6), 638.e1-638.e8. https://doi.org/10.1016/j.ajog.2019.06.034
Vitner, D., Barrett, J., Katherine, W., White, S. W., Newnham, J. P. (2020). Community-based,
population-focused preterm birth prevention programs – A review. Archives of
Gynecology and Obstetrics, 302(6), 1317-1328. https://doi.org/10.1007/s00404-02005759-0
Warri, D., & George, A. (2020). Perceptions of pregnant women of reasons for late initiation of
antenatal care: A qualitative interview study. BMC Pregnancy and Childbirth, 20(70),
183-195. https://doi.org/10.1186/s12884-020-2746-0

PRENATAL CARE EDUCATION

24

Wyst, K. B. V., Vercelli, M. E., O’Brien, K. O., Cooper, E. M., Pressman, E. K., & Whisner, C.
M. (2019). A social media intervention to improve nutrition knowledge and behaviors of
low income, pregnant adolescents and adult women. PloS ONE, 14(10), 328-346.
https://doi.org/10.1371/journal.pone.0223120

PRENATAL CARE EDUCATION

25
Appendix A
Evaluation Tables

Table A1
Evaluation Table Quantitative Studies
Citation

Theory/
Conceptual
Framework

Design/
Method/
Purpose

Sample/ Setting

Major
Variables &
Definitions

Measurement/
Instrumentation

Data
Analysis
(stats used)

Findings/
Results

Desta et al.
(2019).
Adherence of
iron and folic
acid
supplementation
and determinants
among pregnant
women in
Ethiopia: A
systematic
review and metaanalysis.

NS; inferred
Health Belief
Model

Design:
systematic
review and
meta-analysis

NA=1350
NPA= 1345
NUA= 5
FNA =20

Purpose:
estimate the
pooled national
level adherence
to iron & folic
acid
supplements
and its
determinants
among PW in
Ethiopia

Demographics:
PW who have
received IFA
supplementation
during their ANC
visit.

IV1: PW
IV2:
knowledge
related factors
& hx of anemia
IV3: timing of
ANC visit
IV4: frequency
of ANC visit

Online literature
review in several
databases,
Newcastle-Ottawa
Scale QAT

Metaregression
model,
random effect
model, forest
plot and OR.

DV1 –
Adherence by region:
Addis Abeba (60%),
Tigray (58.9%)
Pooled national level
IFA adherence (46.15%)
p-value = <0.05
95% CI

Country:
Ethiopia

Setting: The
university
repositories Addis
Abeba and
Haramya

DV1Adherence to
IFA
supplements
DV2 – barriers
to IFA
adherence

IV1: PW with 4 or more
ANC visits were 2.59
times more likely to
adhere to recommended
IFA supplementation.
P=<0.001
DV2- FOS: 46.4% (95%

Level/ Evidence;
Decision for
practice/
application to
practice
Level of
Evidence: LOE I
Strengths:
High level
evidence, strong
analysis tools,
moderate sample.
Weaknesses:
Homogeneity
(limits
generalizability)
Conclusions:
Receiving
supplemental

Key: ACQ – asthma control questionnaire; ANC – antenatal care; AQQ – asthma quality of life questionnaire; AZ – Arizona; BC – British Columbia; BF – breastfeeding; BG – blood
glucose; BP – blood pressure; BS – benefit score; CA – California; CI – confidence interval; CG – control group; CMCHR – center for maternal and child health research; DHS –
demographic health survey; DST – decision support tool; DV – dependent variable; FNA – final number of articles; FSE – fear of side effects; FT – first trimester; FTPNC – first
trimester prenatal care; f/u – follow up; GA – gestational age; GD – gestational diabetes; HS – high school; IFA – iron and folic acid; IV – independent variable; MD – mean group
difference; MEA – mild epidemic area; MH – mental health; MHS – mental health screening; ModEA – moderate epidemic area; N – number of participants; NA – number of articles;
NM-1 – Dona Ana County; NM-2 – Four County area; NMEA – sample from mild epidemic area; NModEA – sample from moderate epidemic area; NPA – number of published
articles; NS – not stated; NSEA – sample from severe epidemic area; NSS – number of participants who completed satisfaction survey; NUA – number of unpublished articles; OB –
obstetric; OBN – OB nest; OOC – online obstetric consultation; OR – odds ratio; PB – paper-based; PCDST – patient-centered decision support tool; PHE – preventative health exam;
PNC – prenatal care; PRISMA – preferred reporting items for systematic review and meta-analysis; PS – post-secondary; PW – pregnant women; PWA – pregnant women’s
satisfaction; QA – quality assessment; QAT – quality assessment tool; QI – quality improvement; QQS – quality of quantitative studies; RCT – randomized controlled trial; RDPCM –
reduced-frequency prenatal care model; ROC – risk of coronavirus; RS – risk score; SEA – severe epidemic area; SN – social network; SP – screening process; ST – second trimester;
TT – third trimester; TNR – total number of records; TSI – total studies included; TX – Texas; UC – usual care; WG – weight gain; YTT – Yue Yi Tong

PRENATAL CARE EDUCATION
Citation

Funding:
No funding
sources for this
review.
Bias:
No evidence of
bias (Egger’s
tests used).

Theory/
Conceptual
Framework

Design/
Method/
Purpose

26
Sample/ Setting

University of
studies in primary
care in Ethiopia.
Inclusion: Studies
that reported the
adherence of IFA
supplementation or
the determinants of
IFA
supplementation or
the barriers of
adherence among
PW in Ethiopia,
high quality
studies, studies
from 2015-2019.
Exclusion: studies
conducted within
the study
populations other
than PW, case
reports,
surveillance data
(DHS), conference

Major
Variables &
Definitions

Measurement/
Instrumentation

Data
Analysis
(stats used)

Findings/
Results

CI)
Forgetfulness: 30.74%
(95% CI)

Level/ Evidence;
Decision for
practice/
application to
practice
counseling,
knowledge of the
supplement; early
registration and
frequent ANC
visit were
significantly
associated with
adherence of the
IFA
supplementation.
Feasibility:
provision of
strengthened
supplemental
counselling
service, antenatal
care services, and
improving the
knowledge of the
supplementation
are crucial
strategies to
increase

Key: ACQ – asthma control questionnaire; ANC – antenatal care; AQQ – asthma quality of life questionnaire; AZ – Arizona; BC – British Columbia; BF – breastfeeding; BG – blood
glucose; BP – blood pressure; BS – benefit score; CA – California; CI – confidence interval; CG – control group; CMCHR – center for maternal and child health research; DHS –
demographic health survey; DST – decision support tool; DV – dependent variable; FNA – final number of articles; FSE – fear of side effects; FT – first trimester; FTPNC – first
trimester prenatal care; f/u – follow up; GA – gestational age; GD – gestational diabetes; HS – high school; IFA – iron and folic acid; IV – independent variable; MD – mean group
difference; MEA – mild epidemic area; MH – mental health; MHS – mental health screening; ModEA – moderate epidemic area; N – number of participants; NA – number of articles;
NM-1 – Dona Ana County; NM-2 – Four County area; NMEA – sample from mild epidemic area; NModEA – sample from moderate epidemic area; NPA – number of published
articles; NS – not stated; NSEA – sample from severe epidemic area; NSS – number of participants who completed satisfaction survey; NUA – number of unpublished articles; OB –
obstetric; OBN – OB nest; OOC – online obstetric consultation; OR – odds ratio; PB – paper-based; PCDST – patient-centered decision support tool; PHE – preventative health exam;
PNC – prenatal care; PRISMA – preferred reporting items for systematic review and meta-analysis; PS – post-secondary; PW – pregnant women; PWA – pregnant women’s
satisfaction; QA – quality assessment; QAT – quality assessment tool; QI – quality improvement; QQS – quality of quantitative studies; RCT – randomized controlled trial; RDPCM –
reduced-frequency prenatal care model; ROC – risk of coronavirus; RS – risk score; SEA – severe epidemic area; SN – social network; SP – screening process; ST – second trimester;
TT – third trimester; TNR – total number of records; TSI – total studies included; TX – Texas; UC – usual care; WG – weight gain; YTT – Yue Yi Tong

PRENATAL CARE EDUCATION
Citation

Ashford et al.
(2016).
Computer-or
web-based
interventions for
perinatal mental
health: A
systematic
review.
Country:
United Kingdom
Funding:
No funding
sources stated
for this review.
Bias:
Possible
sampling bias
from use of self-

Theory/
Conceptual
Framework

Cognitive
Behavioral
Theory

Design/
Method/
Purpose

Design:
systematic
review
Purpose:
provide a first
overview of
computer- or
web-based
interventions
for women’s
perinatal MH
issues

27
Sample/ Setting

abstracts, and
articles without
full access.
TNR – 9,008
TSI – 11
Demographics:
women in the
perinatal period
Setting: twelve
electronic
databases
systematically
searched at
CMCHR
Inclusion:
programs that (a)
targeted women in
pregnancy – 1 year
postpartum; (b)
were designed to
prevent/improve
MH issues; (c)
delivered via

Major
Variables &
Definitions

Measurement/
Instrumentation

Data
Analysis
(stats used)

Findings/
Results

Level/ Evidence;
Decision for
practice/
application to
practice
adherence among
PW in Ethiopia.

IV1:
intervention
format
IV2: targeted
MH issue
IV3:
intervention
characteristics
IV4: origin and
languages

Online literature
review in twelve
databases
supplemented by
hand searching, 14item checklist for
assessing QQS,
PRISMA

Forest plot,
QA scores,

DV1 –
Medium (d=0.55, 95%
CI 0.33-0.76) to large
(d=1.03, 95% CI 0.351.67)(Mdn=0.46)
DV2 – (d=0.61, 95% CI
1.20-0.01 to d=0.51,
95% CI 0.01-1.02;
Mdn=0.02)
DV3 – (d=0.98, 95% CI
0.30-1.61)

Level of
Evidence: LOE I
Strengths:
High level
evidence,
methodological
quality of studies
assessed by two
independent
assessors

DV1 –
Depression
DV2 – Anxiety
DV3 – Other
MH outcomes

Weaknesses:
Meta-analysis
could not be
completed;
strength of
evidence limited
by small
recruitment
strategies, small
sample size, and
high attrition

Key: ACQ – asthma control questionnaire; ANC – antenatal care; AQQ – asthma quality of life questionnaire; AZ – Arizona; BC – British Columbia; BF – breastfeeding; BG – blood
glucose; BP – blood pressure; BS – benefit score; CA – California; CI – confidence interval; CG – control group; CMCHR – center for maternal and child health research; DHS –
demographic health survey; DST – decision support tool; DV – dependent variable; FNA – final number of articles; FSE – fear of side effects; FT – first trimester; FTPNC – first
trimester prenatal care; f/u – follow up; GA – gestational age; GD – gestational diabetes; HS – high school; IFA – iron and folic acid; IV – independent variable; MD – mean group
difference; MEA – mild epidemic area; MH – mental health; MHS – mental health screening; ModEA – moderate epidemic area; N – number of participants; NA – number of articles;
NM-1 – Dona Ana County; NM-2 – Four County area; NMEA – sample from mild epidemic area; NModEA – sample from moderate epidemic area; NPA – number of published
articles; NS – not stated; NSEA – sample from severe epidemic area; NSS – number of participants who completed satisfaction survey; NUA – number of unpublished articles; OB –
obstetric; OBN – OB nest; OOC – online obstetric consultation; OR – odds ratio; PB – paper-based; PCDST – patient-centered decision support tool; PHE – preventative health exam;
PNC – prenatal care; PRISMA – preferred reporting items for systematic review and meta-analysis; PS – post-secondary; PW – pregnant women; PWA – pregnant women’s
satisfaction; QA – quality assessment; QAT – quality assessment tool; QI – quality improvement; QQS – quality of quantitative studies; RCT – randomized controlled trial; RDPCM –
reduced-frequency prenatal care model; ROC – risk of coronavirus; RS – risk score; SEA – severe epidemic area; SN – social network; SP – screening process; ST – second trimester;
TT – third trimester; TNR – total number of records; TSI – total studies included; TX – Texas; UC – usual care; WG – weight gain; YTT – Yue Yi Tong

PRENATAL CARE EDUCATION
Citation

referral
recruitment
strategies

Theory/
Conceptual
Framework

Design/
Method/
Purpose

28
Sample/ Setting

computer- or webbased; (d) included
self-help
component.
Exclusion: studies
that investigated
(a) online support
groups only; (b) ecounseling, and
were (c)
qualitative, case
studies, systematic
reviews, or study
protocols

Major
Variables &
Definitions

Measurement/
Instrumentation

Data
Analysis
(stats used)

Findings/
Results

Level/ Evidence;
Decision for
practice/
application to
practice
rates;
heterogeneity
(limits
generalizability)
Conclusions:
Systematic
review is first
synthesis of its
kind and provides
preliminary
support this could
be promising
form of
treatment.
Feasibility:
Further research
needed in current
evidence-base
before
implementation,
gaps in well
designed and
large RCT
studies exist and

Key: ACQ – asthma control questionnaire; ANC – antenatal care; AQQ – asthma quality of life questionnaire; AZ – Arizona; BC – British Columbia; BF – breastfeeding; BG – blood
glucose; BP – blood pressure; BS – benefit score; CA – California; CI – confidence interval; CG – control group; CMCHR – center for maternal and child health research; DHS –
demographic health survey; DST – decision support tool; DV – dependent variable; FNA – final number of articles; FSE – fear of side effects; FT – first trimester; FTPNC – first
trimester prenatal care; f/u – follow up; GA – gestational age; GD – gestational diabetes; HS – high school; IFA – iron and folic acid; IV – independent variable; MD – mean group
difference; MEA – mild epidemic area; MH – mental health; MHS – mental health screening; ModEA – moderate epidemic area; N – number of participants; NA – number of articles;
NM-1 – Dona Ana County; NM-2 – Four County area; NMEA – sample from mild epidemic area; NModEA – sample from moderate epidemic area; NPA – number of published
articles; NS – not stated; NSEA – sample from severe epidemic area; NSS – number of participants who completed satisfaction survey; NUA – number of unpublished articles; OB –
obstetric; OBN – OB nest; OOC – online obstetric consultation; OR – odds ratio; PB – paper-based; PCDST – patient-centered decision support tool; PHE – preventative health exam;
PNC – prenatal care; PRISMA – preferred reporting items for systematic review and meta-analysis; PS – post-secondary; PW – pregnant women; PWA – pregnant women’s
satisfaction; QA – quality assessment; QAT – quality assessment tool; QI – quality improvement; QQS – quality of quantitative studies; RCT – randomized controlled trial; RDPCM –
reduced-frequency prenatal care model; ROC – risk of coronavirus; RS – risk score; SEA – severe epidemic area; SN – social network; SP – screening process; ST – second trimester;
TT – third trimester; TNR – total number of records; TSI – total studies included; TX – Texas; UC – usual care; WG – weight gain; YTT – Yue Yi Tong

PRENATAL CARE EDUCATION

29

Citation

Theory/
Conceptual
Framework

Design/
Method/
Purpose

Sample/ Setting

Major
Variables &
Definitions

Measurement/
Instrumentation

Data
Analysis
(stats used)

Findings/
Results

Ngo et al.
(2020).
Use of decision
support tools to
empower
pregnant
women:
Systematic
review

NS; inferred
Health Belief
Model

Design:
systematic
review
Purpose:
provide
overview of
studies
investigating
the effect of
patientcentered DST
for PW

TNR – 10,726
TSI – 25

IV1: PCDST

Literature search of
5 online databases,
PRISMA, Data
extraction form

Excel
spreadsheet

DV1 – (n=10)
(digital:32%; paperbased:15%;
P= 0.87)

Country:
Norway
Funding:
Funded by
Foundation Dam
through
Norwegian
Women’s Public
Health
Association

Demographics:
Pregnant women
who used one or
several PCDST
Setting: online
search of 5
databases at
University of Oslo
Inclusion: RCT,
cohort studies,
register-based
studies, casecontrol studies;
full-texts in
English,
Norwegian,
Swedish, or

DV1 – Prenatal
Screening
DV2 – GD and
WG
DV3 –
Lifestyle
DV4 – BP and
Preeclampsia
DV5 –
Depression
DV6 – Asthma
DV7 –
psychological
well-being

DV2 – (n=7)
FBG (web-chat and
feedback: 4.3; control:
5.3, P<.001)
2-hr postprandial BG
(web-chat and feedback:
5.8; control: 6.9,
P<.001)
DV3 – (n=3) decreased
alcohol consumption in
pregnancy (SMS text
messages: 3.5%;
standard maternity care:
1.1%, P<.098)
DV4 – (n=2) knowledge

Level/ Evidence;
Decision for
practice/
application to
practice
therefore require
review before
pursuing further.
Level of
Evidence: LOE I
Strengths:
High level
evidence,
moderate sample
Weaknesses:
Few PCDST
within each topic,
higher
sociodemographi
c female status
overrepresented,
possible selection
bias.
Conclusions:
opportunities
created by
digitalization and

Key: ACQ – asthma control questionnaire; ANC – antenatal care; AQQ – asthma quality of life questionnaire; AZ – Arizona; BC – British Columbia; BF – breastfeeding; BG – blood
glucose; BP – blood pressure; BS – benefit score; CA – California; CI – confidence interval; CG – control group; CMCHR – center for maternal and child health research; DHS –
demographic health survey; DST – decision support tool; DV – dependent variable; FNA – final number of articles; FSE – fear of side effects; FT – first trimester; FTPNC – first
trimester prenatal care; f/u – follow up; GA – gestational age; GD – gestational diabetes; HS – high school; IFA – iron and folic acid; IV – independent variable; MD – mean group
difference; MEA – mild epidemic area; MH – mental health; MHS – mental health screening; ModEA – moderate epidemic area; N – number of participants; NA – number of articles;
NM-1 – Dona Ana County; NM-2 – Four County area; NMEA – sample from mild epidemic area; NModEA – sample from moderate epidemic area; NPA – number of published
articles; NS – not stated; NSEA – sample from severe epidemic area; NSS – number of participants who completed satisfaction survey; NUA – number of unpublished articles; OB –
obstetric; OBN – OB nest; OOC – online obstetric consultation; OR – odds ratio; PB – paper-based; PCDST – patient-centered decision support tool; PHE – preventative health exam;
PNC – prenatal care; PRISMA – preferred reporting items for systematic review and meta-analysis; PS – post-secondary; PW – pregnant women; PWA – pregnant women’s
satisfaction; QA – quality assessment; QAT – quality assessment tool; QI – quality improvement; QQS – quality of quantitative studies; RCT – randomized controlled trial; RDPCM –
reduced-frequency prenatal care model; ROC – risk of coronavirus; RS – risk score; SEA – severe epidemic area; SN – social network; SP – screening process; ST – second trimester;
TT – third trimester; TNR – total number of records; TSI – total studies included; TX – Texas; UC – usual care; WG – weight gain; YTT – Yue Yi Tong

PRENATAL CARE EDUCATION
Citation

Theory/
Conceptual
Framework

Design/
Method/
Purpose

Bias:
Possible
selection bias
(motivation to
participate/low #
of participants)

Oliveira et al.
(2017). Metaanalysis of the

30
Sample/ Setting

Major
Variables &
Definitions

Measurement/
Instrumentation

Data
Analysis
(stats used)

Danish.

scores higher for app
users (app user:78.1;
control:15.8; P<.001)
DV5 – (n=1)
Referral rate using app:
(P=.03)
Referral rate check-ups:
(P=.02)

Exclusion: fulltext not available,
foreign language,
wrong publication
type, wrong study
design, does not
investigate DST,
study does not
include pregnant
women or
irrelevant outcome

Joanna Briggs
Institute Model

Design:
systematic
review and

TNR – 7201
TSI – 11

Findings/
Results

DV6 – (n=1) IG
Better control of
symptoms (ACQ: -0.30
vs. 0.06, P=.02)
Quality of life
(AQQ:0.51 vs -0.22,
P=.002)

IV1:
Educational BF
interventions

Three stage search
strategy; Tool
adapted from JBI-

Stata version
13, fixed
effects

DV7 – (n=1) lower
anxiety scores (2.8 vs
4.9, P=.002) and higher
confidence scores (8.9
vs 7.8, P=.001)
(P<0.001) and I²
(93.4%)
95% CI 5 out of 12

Level/ Evidence;
Decision for
practice/
application to
practice
technology
should be used to
develop
innovative
PCDST tailored
to support PW
Feasibility:
effect of tools on
clinical outcomes
to be tested
before
recommending or
implementing to
supplement
maternity care.

Level of
Evidence: LOE I

Key: ACQ – asthma control questionnaire; ANC – antenatal care; AQQ – asthma quality of life questionnaire; AZ – Arizona; BC – British Columbia; BF – breastfeeding; BG – blood
glucose; BP – blood pressure; BS – benefit score; CA – California; CI – confidence interval; CG – control group; CMCHR – center for maternal and child health research; DHS –
demographic health survey; DST – decision support tool; DV – dependent variable; FNA – final number of articles; FSE – fear of side effects; FT – first trimester; FTPNC – first
trimester prenatal care; f/u – follow up; GA – gestational age; GD – gestational diabetes; HS – high school; IFA – iron and folic acid; IV – independent variable; MD – mean group
difference; MEA – mild epidemic area; MH – mental health; MHS – mental health screening; ModEA – moderate epidemic area; N – number of participants; NA – number of articles;
NM-1 – Dona Ana County; NM-2 – Four County area; NMEA – sample from mild epidemic area; NModEA – sample from moderate epidemic area; NPA – number of published
articles; NS – not stated; NSEA – sample from severe epidemic area; NSS – number of participants who completed satisfaction survey; NUA – number of unpublished articles; OB –
obstetric; OBN – OB nest; OOC – online obstetric consultation; OR – odds ratio; PB – paper-based; PCDST – patient-centered decision support tool; PHE – preventative health exam;
PNC – prenatal care; PRISMA – preferred reporting items for systematic review and meta-analysis; PS – post-secondary; PW – pregnant women; PWA – pregnant women’s
satisfaction; QA – quality assessment; QAT – quality assessment tool; QI – quality improvement; QQS – quality of quantitative studies; RCT – randomized controlled trial; RDPCM –
reduced-frequency prenatal care model; ROC – risk of coronavirus; RS – risk score; SEA – severe epidemic area; SN – social network; SP – screening process; ST – second trimester;
TT – third trimester; TNR – total number of records; TSI – total studies included; TX – Texas; UC – usual care; WG – weight gain; YTT – Yue Yi Tong

PRENATAL CARE EDUCATION
Citation

effectiveness of
educational
interventions for
breastfeeding
promotion
directed to the
woman and her
social network
Country:
Brazil
Funding:
No funding
sources for this
review.
Bias: No
evidence of bias
(Cochrane
Collaboration
risk of bias tool
used)

Theory/
Conceptual
Framework

31

Design/
Method/
Purpose

Sample/ Setting

Major
Variables &
Definitions

Measurement/
Instrumentation

Data
Analysis
(stats used)

Findings/
Results

meta-analysis

Demographics:
Pregnant and/or
nursing mother
who have received
some guidance
from health
services on
breastfeeding.

IV2: Routine
BF
interventions

MAStARI software
was used. Two
reviewers
performed data
extraction.

model,
random
effects model

interventions effective in
promoting exclusive BF
at 6 months compared
with CG.

Purpose:
Determine
effectiveness
of educational
interventions
focusing on
women and
their SN for
promotion of
exclusive BF
first 6 months.
.

Setting: three step
online search of
six databases at
Federal University
of Pernambuco
Inclusion: RCTs,
studies with
appropriate CG
and IG,
interventions
promoting BF.
Exclusion: studies
developed
exclusively with

DV – exclusive
BF at 6 months
old.

Level/ Evidence;
Decision for
practice/
application to
practice
Strengths:
High level
evidence, no bias
identified, current
data.
Weaknesses:
Few studies
contemplated SN
of nursing
mother, high
heterogeneity
among RCTs
identified.
Conclusions:
Perceived need to
develop new
strategies
including SN of
pregnant women.
Important to offer
five types of
support
(informative,

Key: ACQ – asthma control questionnaire; ANC – antenatal care; AQQ – asthma quality of life questionnaire; AZ – Arizona; BC – British Columbia; BF – breastfeeding; BG – blood
glucose; BP – blood pressure; BS – benefit score; CA – California; CI – confidence interval; CG – control group; CMCHR – center for maternal and child health research; DHS –
demographic health survey; DST – decision support tool; DV – dependent variable; FNA – final number of articles; FSE – fear of side effects; FT – first trimester; FTPNC – first
trimester prenatal care; f/u – follow up; GA – gestational age; GD – gestational diabetes; HS – high school; IFA – iron and folic acid; IV – independent variable; MD – mean group
difference; MEA – mild epidemic area; MH – mental health; MHS – mental health screening; ModEA – moderate epidemic area; N – number of participants; NA – number of articles;
NM-1 – Dona Ana County; NM-2 – Four County area; NMEA – sample from mild epidemic area; NModEA – sample from moderate epidemic area; NPA – number of published
articles; NS – not stated; NSEA – sample from severe epidemic area; NSS – number of participants who completed satisfaction survey; NUA – number of unpublished articles; OB –
obstetric; OBN – OB nest; OOC – online obstetric consultation; OR – odds ratio; PB – paper-based; PCDST – patient-centered decision support tool; PHE – preventative health exam;
PNC – prenatal care; PRISMA – preferred reporting items for systematic review and meta-analysis; PS – post-secondary; PW – pregnant women; PWA – pregnant women’s
satisfaction; QA – quality assessment; QAT – quality assessment tool; QI – quality improvement; QQS – quality of quantitative studies; RCT – randomized controlled trial; RDPCM –
reduced-frequency prenatal care model; ROC – risk of coronavirus; RS – risk score; SEA – severe epidemic area; SN – social network; SP – screening process; ST – second trimester;
TT – third trimester; TNR – total number of records; TSI – total studies included; TX – Texas; UC – usual care; WG – weight gain; YTT – Yue Yi Tong

PRENATAL CARE EDUCATION
Citation

Kingston et al.
(2017). Pregnant
women’s
perceptions of
the risks and
benefits of
disclosure during
web-based MH
ES versus PB
screening:
Randomized
controlled trial.

Theory/
Conceptual
Framework

Health Belief
Model

Design/
Method/
Purpose

Design: RCT
Purpose: to
compare the
perceptions of
PW
randomized to
a Web-based
screening
intervention
group and a PB
screening CG
on the level of

32
Sample/ Setting

premature
newborns &
mothers and/or
children with
diseases/physical
characteristics
preventing BF;
manuals, book
chapters,
monographs and
editorials
excluded.
N=636
IG=305
CG=331
Demographics:
100% of N female
and pregnant
age – <25 (13.9%),
25-34 (72.2%),
35+ (13.6%)
Edu: HS or less
(15.8%), PS or
more (84.2%)

Major
Variables &
Definitions

IV1: ES
IV2: PB
screening
IV3: MHS
DV1perceived risk
of screening
DV2 –
perceived
benefit of
screening
DV3-

Measurement/
Instrumentation

8-item DES with 5point Likert scale.

Data
Analysis
(stats used)

Chi-square
tests,
independent t
tests,
multivariable
model,
multiple
linear
regression

Findings/
Results

DV1- paper, mean (SD)
= 8.57 (3.73); ES, mean
(SD) = 8.51(3.59); p
value
DV2 -paper, mean (SD)
= 14.17(4.03); ES, mean
14.11(4.05); p value –
0.85
DV3- NS

Level/ Evidence;
Decision for
practice/
application to
practice
emotional, faceto-face,
instructional, and
self-support).
Feasibility:
Strategies of
holistic support
can be used to
promote maternal
BF in clinical
setting.
Level of
Evidence: LOE
II
Strengths:
Strong
methodology,
reliable
instruments,
double-blind,
large N
Weaknesses:

Key: ACQ – asthma control questionnaire; ANC – antenatal care; AQQ – asthma quality of life questionnaire; AZ – Arizona; BC – British Columbia; BF – breastfeeding; BG – blood
glucose; BP – blood pressure; BS – benefit score; CA – California; CI – confidence interval; CG – control group; CMCHR – center for maternal and child health research; DHS –
demographic health survey; DST – decision support tool; DV – dependent variable; FNA – final number of articles; FSE – fear of side effects; FT – first trimester; FTPNC – first
trimester prenatal care; f/u – follow up; GA – gestational age; GD – gestational diabetes; HS – high school; IFA – iron and folic acid; IV – independent variable; MD – mean group
difference; MEA – mild epidemic area; MH – mental health; MHS – mental health screening; ModEA – moderate epidemic area; N – number of participants; NA – number of articles;
NM-1 – Dona Ana County; NM-2 – Four County area; NMEA – sample from mild epidemic area; NModEA – sample from moderate epidemic area; NPA – number of published
articles; NS – not stated; NSEA – sample from severe epidemic area; NSS – number of participants who completed satisfaction survey; NUA – number of unpublished articles; OB –
obstetric; OBN – OB nest; OOC – online obstetric consultation; OR – odds ratio; PB – paper-based; PCDST – patient-centered decision support tool; PHE – preventative health exam;
PNC – prenatal care; PRISMA – preferred reporting items for systematic review and meta-analysis; PS – post-secondary; PW – pregnant women; PWA – pregnant women’s
satisfaction; QA – quality assessment; QAT – quality assessment tool; QI – quality improvement; QQS – quality of quantitative studies; RCT – randomized controlled trial; RDPCM –
reduced-frequency prenatal care model; ROC – risk of coronavirus; RS – risk score; SEA – severe epidemic area; SN – social network; SP – screening process; ST – second trimester;
TT – third trimester; TNR – total number of records; TSI – total studies included; TX – Texas; UC – usual care; WG – weight gain; YTT – Yue Yi Tong

PRENATAL CARE EDUCATION
Citation

Country:
Canada
Funding:
Provided by
Canadian
Institutes of
Health Research
and authors of
study
contributed to
final grant.
Bias:
None

Theory/
Conceptual
Framework

Design/
Method/
Purpose
risk and benefit
they perceive
in disclosing
MH concerns
to their
prenatal care
provider.

33
Sample/ Setting

Setting:
maternity clinics
and an inpatient,
high-risk antenatal
unit in a tertiary
care hospital in
Edmonton, Alberta
Inclusion: female,
currently pregnant,
ability to speak
and write English,
willing to be
randomized to escreening, willing
to
Exclusion: women
not currently
pregnant, men, pts
residing outside of
Alberta.

Major
Variables &
Definitions
perceived
benefits of
MHS

Measurement/
Instrumentation

Data
Analysis
(stats used)

Findings/
Results

Level/ Evidence;
Decision for
practice/
application to
practice
sample
demographically
homogeneous, f/u
info NS.
Conclusions:
MH assessment
is generally
perceived as
beneficial.
However, some
participants felt
vulnerable during
the SP for MH
issues. Future
research is
required to
explore women’s
views of MHS.
Feasibility:
Recommended
for use by
clinicians and
women’s health

Key: ACQ – asthma control questionnaire; ANC – antenatal care; AQQ – asthma quality of life questionnaire; AZ – Arizona; BC – British Columbia; BF – breastfeeding; BG – blood
glucose; BP – blood pressure; BS – benefit score; CA – California; CI – confidence interval; CG – control group; CMCHR – center for maternal and child health research; DHS –
demographic health survey; DST – decision support tool; DV – dependent variable; FNA – final number of articles; FSE – fear of side effects; FT – first trimester; FTPNC – first
trimester prenatal care; f/u – follow up; GA – gestational age; GD – gestational diabetes; HS – high school; IFA – iron and folic acid; IV – independent variable; MD – mean group
difference; MEA – mild epidemic area; MH – mental health; MHS – mental health screening; ModEA – moderate epidemic area; N – number of participants; NA – number of articles;
NM-1 – Dona Ana County; NM-2 – Four County area; NMEA – sample from mild epidemic area; NModEA – sample from moderate epidemic area; NPA – number of published
articles; NS – not stated; NSEA – sample from severe epidemic area; NSS – number of participants who completed satisfaction survey; NUA – number of unpublished articles; OB –
obstetric; OBN – OB nest; OOC – online obstetric consultation; OR – odds ratio; PB – paper-based; PCDST – patient-centered decision support tool; PHE – preventative health exam;
PNC – prenatal care; PRISMA – preferred reporting items for systematic review and meta-analysis; PS – post-secondary; PW – pregnant women; PWA – pregnant women’s
satisfaction; QA – quality assessment; QAT – quality assessment tool; QI – quality improvement; QQS – quality of quantitative studies; RCT – randomized controlled trial; RDPCM –
reduced-frequency prenatal care model; ROC – risk of coronavirus; RS – risk score; SEA – severe epidemic area; SN – social network; SP – screening process; ST – second trimester;
TT – third trimester; TNR – total number of records; TSI – total studies included; TX – Texas; UC – usual care; WG – weight gain; YTT – Yue Yi Tong

PRENATAL CARE EDUCATION

34

Citation

Theory/
Conceptual
Framework

Design/
Method/
Purpose

Sample/ Setting

Major
Variables &
Definitions

Measurement/
Instrumentation

Data
Analysis
(stats used)

Findings/
Results

Tobah et al.
(2019).
Randomized
comparison of a
reduced-visit
prenatal care
model enhanced
with remote
monitoring

Digital Health
Interventions
Framework

Design: RCT
Purpose: to
evaluate
acceptability
and
effectiveness
of OBN
(RDPCM)
enhance with
remote home
monitoring
devices &
nursing
support.

N=300
CG=150
IG=150

IV1: OBN
IV2: UC

Modified validated
30-item Prenatal
Interpersonal
Processes of Care
scale; 9-item
PreNatal Maternal
Stress survey;
modified Littlefield
and Adams 16-item
self-reported;
Satisfaction
subscale survey,
evaluated on 5point Likert-type
scale.

Fisher exact
test statistic
for
categorical
outcomes and
t test for
continuous
outcomes
(SAS
software
version 9.4
used)

DV1- OBN=93.90 vs
UC=78.89; MD 15.01,
95% CI, 13.38-16.64

Country:
United States
Funding:
No funding
sources for this
review.
Bias:
None

Demographics:
Pregnant women
aged 18-36 years;
majority
Caucasian, 97%
married, and
mostly educated.
Setting:
Single-center
outpatient obstetric
tertiary academic
center in the
Midwest United
States.
Inclusion:
English-speaking
pregnant women,

DV1satisfaction rate
DV2 –
maternal/fetal
complications
DV3pregnancyrelated stress

DV2 – no differences
with exception of
gestational diabetes
(OBN=6 [4.5%] vs
UC=0 [0.0%], P<.01)
DV3- 14 weeks
(OBN=0.32 vs
UC=0.41; MD=-0.09,
95% CI, -0.14 to -0.04)
and 36 weeks
(OBN=0.34 vs
UC=0.40; MD=-0.06,
95% CI, -0.11 to -0.01)

Level/ Evidence;
Decision for
practice/
application to
practice
clinics that are
deciding between
PB and ES.
Level of
Evidence: LOE
II
Strengths:
Rigorous
randomized trial
design with
optimal
allocation
concealment,
high survey
completion rates.
Weaknesses:
does not examine
RDPCM in
sociodemographically
diverse
population

Key: ACQ – asthma control questionnaire; ANC – antenatal care; AQQ – asthma quality of life questionnaire; AZ – Arizona; BC – British Columbia; BF – breastfeeding; BG – blood
glucose; BP – blood pressure; BS – benefit score; CA – California; CI – confidence interval; CG – control group; CMCHR – center for maternal and child health research; DHS –
demographic health survey; DST – decision support tool; DV – dependent variable; FNA – final number of articles; FSE – fear of side effects; FT – first trimester; FTPNC – first
trimester prenatal care; f/u – follow up; GA – gestational age; GD – gestational diabetes; HS – high school; IFA – iron and folic acid; IV – independent variable; MD – mean group
difference; MEA – mild epidemic area; MH – mental health; MHS – mental health screening; ModEA – moderate epidemic area; N – number of participants; NA – number of articles;
NM-1 – Dona Ana County; NM-2 – Four County area; NMEA – sample from mild epidemic area; NModEA – sample from moderate epidemic area; NPA – number of published
articles; NS – not stated; NSEA – sample from severe epidemic area; NSS – number of participants who completed satisfaction survey; NUA – number of unpublished articles; OB –
obstetric; OBN – OB nest; OOC – online obstetric consultation; OR – odds ratio; PB – paper-based; PCDST – patient-centered decision support tool; PHE – preventative health exam;
PNC – prenatal care; PRISMA – preferred reporting items for systematic review and meta-analysis; PS – post-secondary; PW – pregnant women; PWA – pregnant women’s
satisfaction; QA – quality assessment; QAT – quality assessment tool; QI – quality improvement; QQS – quality of quantitative studies; RCT – randomized controlled trial; RDPCM –
reduced-frequency prenatal care model; ROC – risk of coronavirus; RS – risk score; SEA – severe epidemic area; SN – social network; SP – screening process; ST – second trimester;
TT – third trimester; TNR – total number of records; TSI – total studies included; TX – Texas; UC – usual care; WG – weight gain; YTT – Yue Yi Tong

PRENATAL CARE EDUCATION
Citation

Theory/
Conceptual
Framework

Design/
Method/
Purpose

35
Sample/ Setting

Major
Variables &
Definitions

Measurement/
Instrumentation

Data
Analysis
(stats used)

Findings/
Results

between 18 and 36
years old, at <13
weeks of gestation,
without concurrent
medical or OB
complications,
with ability to
provide informed
consent.
Exclusion:
diagnoses of any
chronic medical
conditions or OB
judgement
pregnancy is high
risk for
complications.

Catherine et al.
(2019). The

NS; inferred
Social

Design: RCT

N=739
14-19 years=361

IV1: low
income

Home interviews &
verbally

Chi-square
test, Fisher’s

DV1Primary healthcare (past

Level/ Evidence;
Decision for
practice/
application to
practice
Conclusions:
PW randomized
to RDPCM had
significantly
higher
satisfaction with
care, lower
prenatal-related
stress, & saved
average of 2.8
OB clinician
appointments per
patient compared
to UC model.
Feasibility:
RDPCM with
remote
monitoring as
effective as
standard 12-14
traditional visits
model.
Level of
Evidence: LOE

Key: ACQ – asthma control questionnaire; ANC – antenatal care; AQQ – asthma quality of life questionnaire; AZ – Arizona; BC – British Columbia; BF – breastfeeding; BG – blood
glucose; BP – blood pressure; BS – benefit score; CA – California; CI – confidence interval; CG – control group; CMCHR – center for maternal and child health research; DHS –
demographic health survey; DST – decision support tool; DV – dependent variable; FNA – final number of articles; FSE – fear of side effects; FT – first trimester; FTPNC – first
trimester prenatal care; f/u – follow up; GA – gestational age; GD – gestational diabetes; HS – high school; IFA – iron and folic acid; IV – independent variable; MD – mean group
difference; MEA – mild epidemic area; MH – mental health; MHS – mental health screening; ModEA – moderate epidemic area; N – number of participants; NA – number of articles;
NM-1 – Dona Ana County; NM-2 – Four County area; NMEA – sample from mild epidemic area; NModEA – sample from moderate epidemic area; NPA – number of published
articles; NS – not stated; NSEA – sample from severe epidemic area; NSS – number of participants who completed satisfaction survey; NUA – number of unpublished articles; OB –
obstetric; OBN – OB nest; OOC – online obstetric consultation; OR – odds ratio; PB – paper-based; PCDST – patient-centered decision support tool; PHE – preventative health exam;
PNC – prenatal care; PRISMA – preferred reporting items for systematic review and meta-analysis; PS – post-secondary; PW – pregnant women; PWA – pregnant women’s
satisfaction; QA – quality assessment; QAT – quality assessment tool; QI – quality improvement; QQS – quality of quantitative studies; RCT – randomized controlled trial; RDPCM –
reduced-frequency prenatal care model; ROC – risk of coronavirus; RS – risk score; SEA – severe epidemic area; SN – social network; SP – screening process; ST – second trimester;
TT – third trimester; TNR – total number of records; TSI – total studies included; TX – Texas; UC – usual care; WG – weight gain; YTT – Yue Yi Tong

PRENATAL CARE EDUCATION

36

Citation

Theory/
Conceptual
Framework

Design/
Method/
Purpose

Sample/ Setting

Major
Variables &
Definitions

Measurement/
Instrumentation

Data
Analysis
(stats used)

Findings/
Results

British Columbia
healthy
connections
project: Findings
on
socioeconomic
disadvantage in
early pregnancy

Disadvantage
Framework

Purpose: to
inform early
intervention
planning by
describing
health & social
adversities
experienced by
a cohort of
girls and young
women in early
pregnancy in
BC, Canada.

20-24 years=378

IV2: limited
education
IV3: preparing
to parent while
single
IV4: Age
IV5:
psychological
resources
IV6: cognitive
functioning
IV7: executive
functioning
IV8:
maltreatment
experiences
DV1- health
services for
physical health
DV2 – social
services
received

administered
questionnaires and
cognitive tests inperson; sensitive
items prone to bias
administered using
audiotaped
questions with
responses written
in sealed envelopes
for later
processing.

exact test for
cell sizes <5,
Student’s ttest (for
continuous
variables)

month)
N: 76.7% (567/739)
14-19 years: 289/361
(80.1%)
20-24 years: 278/378
(73.5%)
p-value = 0.045

Country:
Canada
Funding:
BC Ministry of
Health with
support from the
BC Ministry of
Children and
Family
Development,
additional
funding support
from Djavad
Mowafaghian
and Stern family

Demographics:
young females in
early pregnancy
from
disadvantaged &
low socioeconomic
backgrounds; 91%
single, 84% lowincome, 52%
limited education
Setting: public
health units at four
regional BC Health
Authorities. Nurseled home visits in
BC
Inclusion: women
less than 28 weeks
pregnant &
experiencing
socioeconomic

Prenatal classes (past
month)
N: 28.4% (210/739)
14-19 years: 116/361
(32.1%)
20-24 years: 94/378
(24.9%)
p-value = 0.035
DV2 –
Income assistance (past
month) – N: 28.7%
(212/739)
14-19 years:
71/361(19.7%)
20-24 year: 141/378
(37.3%)
p-value<0.001

Level/ Evidence;
Decision for
practice/
application to
practice
II
Strengths:
Randomized trial
design with
reliable
instruments, large
N
Weaknesses: 2/3
of eligible young
women not
reached through
recruitment
efforts, data on
education levels
does not account
for HS.
Conclusions:
Young women in
the study are not
adequately being
reached by social
services; study

Key: ACQ – asthma control questionnaire; ANC – antenatal care; AQQ – asthma quality of life questionnaire; AZ – Arizona; BC – British Columbia; BF – breastfeeding; BG – blood
glucose; BP – blood pressure; BS – benefit score; CA – California; CI – confidence interval; CG – control group; CMCHR – center for maternal and child health research; DHS –
demographic health survey; DST – decision support tool; DV – dependent variable; FNA – final number of articles; FSE – fear of side effects; FT – first trimester; FTPNC – first
trimester prenatal care; f/u – follow up; GA – gestational age; GD – gestational diabetes; HS – high school; IFA – iron and folic acid; IV – independent variable; MD – mean group
difference; MEA – mild epidemic area; MH – mental health; MHS – mental health screening; ModEA – moderate epidemic area; N – number of participants; NA – number of articles;
NM-1 – Dona Ana County; NM-2 – Four County area; NMEA – sample from mild epidemic area; NModEA – sample from moderate epidemic area; NPA – number of published
articles; NS – not stated; NSEA – sample from severe epidemic area; NSS – number of participants who completed satisfaction survey; NUA – number of unpublished articles; OB –
obstetric; OBN – OB nest; OOC – online obstetric consultation; OR – odds ratio; PB – paper-based; PCDST – patient-centered decision support tool; PHE – preventative health exam;
PNC – prenatal care; PRISMA – preferred reporting items for systematic review and meta-analysis; PS – post-secondary; PW – pregnant women; PWA – pregnant women’s
satisfaction; QA – quality assessment; QAT – quality assessment tool; QI – quality improvement; QQS – quality of quantitative studies; RCT – randomized controlled trial; RDPCM –
reduced-frequency prenatal care model; ROC – risk of coronavirus; RS – risk score; SEA – severe epidemic area; SN – social network; SP – screening process; ST – second trimester;
TT – third trimester; TNR – total number of records; TSI – total studies included; TX – Texas; UC – usual care; WG – weight gain; YTT – Yue Yi Tong

PRENATAL CARE EDUCATION
Citation

Theory/
Conceptual
Framework

Design/
Method/
Purpose

37
Sample/ Setting

Major
Variables &
Definitions

Measurement/
Instrumentation

Data
Analysis
(stats used)

Findings/
Results

disadvantage.
Bias:
None

Selchau (2017).
First trimester
prenatal care
initiation among
Hispanic women
along the U.S.Mexico Border

Exclusion:
Women in later
pregnancy, over
the age of 24
years, high-income
households,
second-time
mothers.

Quality of Care
Framework

Design: crosssectional
Purpose:
identify
demographic,
knowledge and
care-seeking

N=403
CA=65
AZ=56
NM-1=134
NM-2=96
TX=52
Demographics:
Hispanic women

IV1: Race
IV2: Age
IV3: #
pregnancies
IV4: location
of PNC
DV1- FTPNC

12-question survey
to assess key
factors related to
PNC

Chi square
analyses,
logistic
regression
model

DV1- multiparity
associated with FTPNC,
living in Texas
negatively associated
with FTPNC (R2 =
0.066, F(9,340) = 2.662,
p = .005)

Level/ Evidence;
Decision for
practice/
application to
practice
suggests
unacceptably
high levels of
socioeconomic
disadvantages
exist for young
and pregnant
BCs.
Feasibility:
Information can
be used for
greater health and
social supports &
services for
young mothers
and their children
Level of
Evidence: LOE
IV
Strengths:
Well-designed
selection process,
sample

Key: ACQ – asthma control questionnaire; ANC – antenatal care; AQQ – asthma quality of life questionnaire; AZ – Arizona; BC – British Columbia; BF – breastfeeding; BG – blood
glucose; BP – blood pressure; BS – benefit score; CA – California; CI – confidence interval; CG – control group; CMCHR – center for maternal and child health research; DHS –
demographic health survey; DST – decision support tool; DV – dependent variable; FNA – final number of articles; FSE – fear of side effects; FT – first trimester; FTPNC – first
trimester prenatal care; f/u – follow up; GA – gestational age; GD – gestational diabetes; HS – high school; IFA – iron and folic acid; IV – independent variable; MD – mean group
difference; MEA – mild epidemic area; MH – mental health; MHS – mental health screening; ModEA – moderate epidemic area; N – number of participants; NA – number of articles;
NM-1 – Dona Ana County; NM-2 – Four County area; NMEA – sample from mild epidemic area; NModEA – sample from moderate epidemic area; NPA – number of published
articles; NS – not stated; NSEA – sample from severe epidemic area; NSS – number of participants who completed satisfaction survey; NUA – number of unpublished articles; OB –
obstetric; OBN – OB nest; OOC – online obstetric consultation; OR – odds ratio; PB – paper-based; PCDST – patient-centered decision support tool; PHE – preventative health exam;
PNC – prenatal care; PRISMA – preferred reporting items for systematic review and meta-analysis; PS – post-secondary; PW – pregnant women; PWA – pregnant women’s
satisfaction; QA – quality assessment; QAT – quality assessment tool; QI – quality improvement; QQS – quality of quantitative studies; RCT – randomized controlled trial; RDPCM –
reduced-frequency prenatal care model; ROC – risk of coronavirus; RS – risk score; SEA – severe epidemic area; SN – social network; SP – screening process; ST – second trimester;
TT – third trimester; TNR – total number of records; TSI – total studies included; TX – Texas; UC – usual care; WG – weight gain; YTT – Yue Yi Tong

PRENATAL CARE EDUCATION
Citation

Country:
United States
Funding:
U.S. Department
of Health and
Human Services,
Health
Resources and
Services
Administration,
Maternal and
Child Health
Bureau, Division
of Healthy Start
Bias:
None

Theory/
Conceptual
Framework

38

Design/
Method/
Purpose

Sample/ Setting

factors
influencing
FTPNC among
Hispanic
women in
border counties
and what
FTPNC
barriers may be
unique to this
target
population.

of reproductive age
(15-44 years)
residing along the
U.S.-Mexico
border
Setting: five
Healthy Start
clinical project
sites along
southwest border
towns in United
States.
Inclusion:
Hispanic female,
reproductive age,
living in counties
on border areas.
Exclusion:
Outside of
reproductive age,
not meeting border
residency or
Hispanic ethnicity
requirements

Major
Variables &
Definitions

Measurement/
Instrumentation

Data
Analysis
(stats used)

Findings/
Results

Primiparious women
less likely to start
FTPNC than
Multiparious women
(χ2 = 6.8372, p =
0.0089)

Level/ Evidence;
Decision for
practice/
application to
practice
representative of
study population
Weaknesses:
generalizability
limited, not all
potential risk
factors identified
Conclusions:
First-time
pregnancies have
lower FTPNC,
strong
association
between delayed
PNC and late
pregnancy
recognition.
Feasibility:
Strengthened
investments in
preconception
planning could

Key: ACQ – asthma control questionnaire; ANC – antenatal care; AQQ – asthma quality of life questionnaire; AZ – Arizona; BC – British Columbia; BF – breastfeeding; BG – blood
glucose; BP – blood pressure; BS – benefit score; CA – California; CI – confidence interval; CG – control group; CMCHR – center for maternal and child health research; DHS –
demographic health survey; DST – decision support tool; DV – dependent variable; FNA – final number of articles; FSE – fear of side effects; FT – first trimester; FTPNC – first
trimester prenatal care; f/u – follow up; GA – gestational age; GD – gestational diabetes; HS – high school; IFA – iron and folic acid; IV – independent variable; MD – mean group
difference; MEA – mild epidemic area; MH – mental health; MHS – mental health screening; ModEA – moderate epidemic area; N – number of participants; NA – number of articles;
NM-1 – Dona Ana County; NM-2 – Four County area; NMEA – sample from mild epidemic area; NModEA – sample from moderate epidemic area; NPA – number of published
articles; NS – not stated; NSEA – sample from severe epidemic area; NSS – number of participants who completed satisfaction survey; NUA – number of unpublished articles; OB –
obstetric; OBN – OB nest; OOC – online obstetric consultation; OR – odds ratio; PB – paper-based; PCDST – patient-centered decision support tool; PHE – preventative health exam;
PNC – prenatal care; PRISMA – preferred reporting items for systematic review and meta-analysis; PS – post-secondary; PW – pregnant women; PWA – pregnant women’s
satisfaction; QA – quality assessment; QAT – quality assessment tool; QI – quality improvement; QQS – quality of quantitative studies; RCT – randomized controlled trial; RDPCM –
reduced-frequency prenatal care model; ROC – risk of coronavirus; RS – risk score; SEA – severe epidemic area; SN – social network; SP – screening process; ST – second trimester;
TT – third trimester; TNR – total number of records; TSI – total studies included; TX – Texas; UC – usual care; WG – weight gain; YTT – Yue Yi Tong

PRENATAL CARE EDUCATION

39

Citation

Theory/
Conceptual
Framework

Design/
Method/
Purpose

Sample/ Setting

Major
Variables &
Definitions

Measurement/
Instrumentation

Data
Analysis
(stats used)

Findings/
Results

Chen et al.
(2020).
Characteristics
of online
medical care
consultation for
pregnant women
during the
COVID-19
outbreak: Crosssectional study.
Country:
China

NS, inferred
Cognitive
Behavioral
Model

Design: crosssectional

N=2599
NSS=957
NMEA=164
NmodEA=644
NSEA=149

IV1 : PW
IV2 : ANC

E-health
questionnaires,
online surveys,
ANC consultations

Chi-squared
test, logistic
regression.

DV1e-health saves time:
79.94%
e-health reduces ROC:
82.45%
e-health is comfortable:
39.81%
e-health can save
money: 41.17%

Funding:
Provided by
National Natural
Science
Foundation of
China and the
National Key
Research and

Purpose:
to assess the
needs of PW
regarding
online obstetric
consultation in
representative
areas with
various
severity of the
epidemic.

Demographics:
100% of female
and pregnant,
residing in a
province of China.
Setting: YTT
throughout
provinces in China
Inclusion: All PW
residing in a
province of China
who submitted
their online
obstetric
evaluation were

DV1- PWS
DV2distribution of
OOC in
different areas
DV3distribution of
OOC in
different
trimesters

DV2 – MEA: 448
(17.24%)
ModEA: 1332 (51.25%)
SEA: 819 (31.51%)
p<0.001
DV3 –
FT: 417 (16.04%)
ST: 1054 (40.55%)
TT: 1128 (43.40%)
p<0.001

Level/ Evidence;
Decision for
practice/
application to
practice
improve FTPNC
in this
population.
Level of
Evidence: LOE
IV
Strengths:
Multiple centers
involved in
design, current
evidence, and
discusses
prenatal e-health
recent events.
Weaknesses:
short duration of
data collection,
collection
possibly hindered
by outbreak in
China, low LOE.
Conclusions:

Key: ACQ – asthma control questionnaire; ANC – antenatal care; AQQ – asthma quality of life questionnaire; AZ – Arizona; BC – British Columbia; BF – breastfeeding; BG – blood
glucose; BP – blood pressure; BS – benefit score; CA – California; CI – confidence interval; CG – control group; CMCHR – center for maternal and child health research; DHS –
demographic health survey; DST – decision support tool; DV – dependent variable; FNA – final number of articles; FSE – fear of side effects; FT – first trimester; FTPNC – first
trimester prenatal care; f/u – follow up; GA – gestational age; GD – gestational diabetes; HS – high school; IFA – iron and folic acid; IV – independent variable; MD – mean group
difference; MEA – mild epidemic area; MH – mental health; MHS – mental health screening; ModEA – moderate epidemic area; N – number of participants; NA – number of articles;
NM-1 – Dona Ana County; NM-2 – Four County area; NMEA – sample from mild epidemic area; NModEA – sample from moderate epidemic area; NPA – number of published
articles; NS – not stated; NSEA – sample from severe epidemic area; NSS – number of participants who completed satisfaction survey; NUA – number of unpublished articles; OB –
obstetric; OBN – OB nest; OOC – online obstetric consultation; OR – odds ratio; PB – paper-based; PCDST – patient-centered decision support tool; PHE – preventative health exam;
PNC – prenatal care; PRISMA – preferred reporting items for systematic review and meta-analysis; PS – post-secondary; PW – pregnant women; PWA – pregnant women’s
satisfaction; QA – quality assessment; QAT – quality assessment tool; QI – quality improvement; QQS – quality of quantitative studies; RCT – randomized controlled trial; RDPCM –
reduced-frequency prenatal care model; ROC – risk of coronavirus; RS – risk score; SEA – severe epidemic area; SN – social network; SP – screening process; ST – second trimester;
TT – third trimester; TNR – total number of records; TSI – total studies included; TX – Texas; UC – usual care; WG – weight gain; YTT – Yue Yi Tong

PRENATAL CARE EDUCATION
Citation

Development
Program of
China.
Bias: Possible
due to selfreporting and a
questionnaire not
commonly
structured.

Theory/
Conceptual
Framework

Design/
Method/
Purpose

40
Sample/ Setting

eligible.
Exclusion: women
not currently
pregnant, women
with impossible
GA, women who
recently gave birth,
pts residing outside
provinces of
China.

Major
Variables &
Definitions

Measurement/
Instrumentation

Data
Analysis
(stats used)

Findings/
Results

Level/ Evidence;
Decision for
practice/
application to
practice
OOC is highly
accepted and
satisfied PW
during the
COVID-19
outbreak. Study
indicates that ehealth played an
important role in
ANC during
PHE.
Feasibility:
The novel model
of ANC plan can
make notable
contributions not
only in China but
emerging
epidemic centers
worldwide and
future PHEs.

Key: ACQ – asthma control questionnaire; ANC – antenatal care; AQQ – asthma quality of life questionnaire; AZ – Arizona; BC – British Columbia; BF – breastfeeding; BG – blood
glucose; BP – blood pressure; BS – benefit score; CA – California; CI – confidence interval; CG – control group; CMCHR – center for maternal and child health research; DHS –
demographic health survey; DST – decision support tool; DV – dependent variable; FNA – final number of articles; FSE – fear of side effects; FT – first trimester; FTPNC – first
trimester prenatal care; f/u – follow up; GA – gestational age; GD – gestational diabetes; HS – high school; IFA – iron and folic acid; IV – independent variable; MD – mean group
difference; MEA – mild epidemic area; MH – mental health; MHS – mental health screening; ModEA – moderate epidemic area; N – number of participants; NA – number of articles;
NM-1 – Dona Ana County; NM-2 – Four County area; NMEA – sample from mild epidemic area; NModEA – sample from moderate epidemic area; NPA – number of published
articles; NS – not stated; NSEA – sample from severe epidemic area; NSS – number of participants who completed satisfaction survey; NUA – number of unpublished articles; OB –
obstetric; OBN – OB nest; OOC – online obstetric consultation; OR – odds ratio; PB – paper-based; PCDST – patient-centered decision support tool; PHE – preventative health exam;
PNC – prenatal care; PRISMA – preferred reporting items for systematic review and meta-analysis; PS – post-secondary; PW – pregnant women; PWA – pregnant women’s
satisfaction; QA – quality assessment; QAT – quality assessment tool; QI – quality improvement; QQS – quality of quantitative studies; RCT – randomized controlled trial; RDPCM –
reduced-frequency prenatal care model; ROC – risk of coronavirus; RS – risk score; SEA – severe epidemic area; SN – social network; SP – screening process; ST – second trimester;
TT – third trimester; TNR – total number of records; TSI – total studies included; TX – Texas; UC – usual care; WG – weight gain; YTT – Yue Yi Tong

PRENATAL CARE EDUCATION

41

Citation

Theory/
Conceptual
Framework

Design/
Method/
Purpose

Sample/ Setting

Major
Variables &
Definitions

Measurement/
Instrumentation

Data
Analysis
(stats used)

Findings/
Results

Shah et al.
(2018)
Improving rates
of early prenatal
care in an
underserved
population

NS; inferred
Danaher
framework

Design: crosssectional

N=428
PNC FT=306
PNC after FT=122

IV1 : Age
IV2 : Gravidity
IV3 : Parity
IV4: GA at
first visit
IV5: GA at
delivery
IV6: Vaginal
delivery

Patient surveys,
focus groups,
stakeholder
feedback

Chi-square,
Student’s ttest, and
MannWhitney U
test.

DV1- PNC FT: 22(7.0)
PNC after FT: 12(10.1)
p value = 0.29

Country:
United States
Funding:
No funding
sources for this
review.
Bias:
None

Purpose:
increase
percentage of
patients
receiving early
PNC

Demographics: all
PW seeking care at
the FQHC location
in Houston.
Setting: FQHC in
Houston, TX
Inclusion:
systematic random
sample of 100 OB
patient charts
selected from
FQHC, every 5th
chart selected.
Exclusion: No
exclusion criteria
stated.

DV1Obstetrical
complications
DV2-Neonatal
complications
different areas

DV2- PNC FT: 29(9.3)
PNC after FT: 18(9.7)
p value = 0.08

Level/ Evidence;
Decision for
practice/
application to
practice
Level of
Evidence: LOE
IV
Strengths:
Practical
approach,
detailed
improvement
strategies, proven
significant
change over just
three months.
Weaknesses:
High patient
population of
single ethnicity &
single
community
clinical setting.
Conclusions:
Patients with
early prenatal

Key: ACQ – asthma control questionnaire; ANC – antenatal care; AQQ – asthma quality of life questionnaire; AZ – Arizona; BC – British Columbia; BF – breastfeeding; BG – blood
glucose; BP – blood pressure; BS – benefit score; CA – California; CI – confidence interval; CG – control group; CMCHR – center for maternal and child health research; DHS –
demographic health survey; DST – decision support tool; DV – dependent variable; FNA – final number of articles; FSE – fear of side effects; FT – first trimester; FTPNC – first
trimester prenatal care; f/u – follow up; GA – gestational age; GD – gestational diabetes; HS – high school; IFA – iron and folic acid; IV – independent variable; MD – mean group
difference; MEA – mild epidemic area; MH – mental health; MHS – mental health screening; ModEA – moderate epidemic area; N – number of participants; NA – number of articles;
NM-1 – Dona Ana County; NM-2 – Four County area; NMEA – sample from mild epidemic area; NModEA – sample from moderate epidemic area; NPA – number of published
articles; NS – not stated; NSEA – sample from severe epidemic area; NSS – number of participants who completed satisfaction survey; NUA – number of unpublished articles; OB –
obstetric; OBN – OB nest; OOC – online obstetric consultation; OR – odds ratio; PB – paper-based; PCDST – patient-centered decision support tool; PHE – preventative health exam;
PNC – prenatal care; PRISMA – preferred reporting items for systematic review and meta-analysis; PS – post-secondary; PW – pregnant women; PWA – pregnant women’s
satisfaction; QA – quality assessment; QAT – quality assessment tool; QI – quality improvement; QQS – quality of quantitative studies; RCT – randomized controlled trial; RDPCM –
reduced-frequency prenatal care model; ROC – risk of coronavirus; RS – risk score; SEA – severe epidemic area; SN – social network; SP – screening process; ST – second trimester;
TT – third trimester; TNR – total number of records; TSI – total studies included; TX – Texas; UC – usual care; WG – weight gain; YTT – Yue Yi Tong

PRENATAL CARE EDUCATION
Citation

Theory/
Conceptual
Framework

Design/
Method/
Purpose

42
Sample/ Setting

Major
Variables &
Definitions

Measurement/
Instrumentation

Data
Analysis
(stats used)

Findings/
Results

Level/ Evidence;
Decision for
practice/
application to
practice
care had better
obstetrical and
neonatal
outcomes;
however, the
results were not
statistically
significant likely
due to the small
sample size
Feasibility:
This QI project
provides various
strategies &
resources for
other
community-based
clinics to
consider when
seeking
improvement in
their rates of
early PNC.

Key: ACQ – asthma control questionnaire; ANC – antenatal care; AQQ – asthma quality of life questionnaire; AZ – Arizona; BC – British Columbia; BF – breastfeeding; BG – blood
glucose; BP – blood pressure; BS – benefit score; CA – California; CI – confidence interval; CG – control group; CMCHR – center for maternal and child health research; DHS –
demographic health survey; DST – decision support tool; DV – dependent variable; FNA – final number of articles; FSE – fear of side effects; FT – first trimester; FTPNC – first
trimester prenatal care; f/u – follow up; GA – gestational age; GD – gestational diabetes; HS – high school; IFA – iron and folic acid; IV – independent variable; MD – mean group
difference; MEA – mild epidemic area; MH – mental health; MHS – mental health screening; ModEA – moderate epidemic area; N – number of participants; NA – number of articles;
NM-1 – Dona Ana County; NM-2 – Four County area; NMEA – sample from mild epidemic area; NModEA – sample from moderate epidemic area; NPA – number of published
articles; NS – not stated; NSEA – sample from severe epidemic area; NSS – number of participants who completed satisfaction survey; NUA – number of unpublished articles; OB –
obstetric; OBN – OB nest; OOC – online obstetric consultation; OR – odds ratio; PB – paper-based; PCDST – patient-centered decision support tool; PHE – preventative health exam;
PNC – prenatal care; PRISMA – preferred reporting items for systematic review and meta-analysis; PS – post-secondary; PW – pregnant women; PWA – pregnant women’s
satisfaction; QA – quality assessment; QAT – quality assessment tool; QI – quality improvement; QQS – quality of quantitative studies; RCT – randomized controlled trial; RDPCM –
reduced-frequency prenatal care model; ROC – risk of coronavirus; RS – risk score; SEA – severe epidemic area; SN – social network; SP – screening process; ST – second trimester;
TT – third trimester; TNR – total number of records; TSI – total studies included; TX – Texas; UC – usual care; WG – weight gain; YTT – Yue Yi Tong

PRENATAL CARE EDUCATION

43
Appendix B
Synthesis Table

Table A2
Study
(Author, year)
SR/ I
RCT/ II
CSS/ IV
Sample

Ashford,
2016
•

Chen,
2020

Desta,
2019
•

•

Country
Framework
Demographics

Catherine,
2019

Kingston,
2017

Ngo,
2020
•

Oliveira,
2017
•

Selchau, Shah,
2017
2018

•

11 studies

739

•
957

United
Kingdom
CBT

Canada
SDF

China

20
articles
Ethiopia

CBT

HBM

636

Tobah,
2019
•

Canada

25
studies
Norway

11
studies
Brazil

HBM

HBM

JBIM

Pre-pregnancy

•
403

•
428

300

United
States
QCF

United
States
DF

United
States
DHIF

•

1st trimester

•

•

•

•

•

•

•

•

•

2nd trimester
3rd trimester

•
•

•

•
•

•
•

•
•

•
•

•
•

•
•

•
•

PP and BF
•
Mean Age
28
LSEB
Limited Education
Low Income
Applicable Measurement
ODLR
Tools

20
•
•
•
Interviews

31

23

27

•
Online ODLR
survey,
PNC
consult

DES with
Likert
scale.

26
•
•
•
ODLR,
DE tool

•
30

ODLR,
DE tool

•
29
•
•
•
Survey

•
•

24
33
•
•
•
Survey Survey,
focus
Likert
groups, scale

Key: BF – breastfeeding; CBE – computer-based education; CBT– cognitive behavioral theory; CSS – cross-sectional study; DE – data extraction; DF – Danaher framework; DHIF
– digital health intervention framework; EEPC – early entry to prenatal care; ES – electronic screening; HBM – health belief model; JBIM – Joanna Briggs Institute Model; LSEB –
low socioeconomic background; MH – mental health; ODLR – online database literature review; OOC – online obstetric counseling; PNC – prenatal care; PP – postpartum; PPHB –
positive prenatal health behaviors; PRS – pregnancy related stress; QCF – quality of care framework; RCT – randomized controlled trial; SDF – social disadvantage framework; SMI
– social media intervention; SR – systematic review

PRENATAL CARE EDUCATION
Independent Variables
PNC frequency
Health Resources
MH Resources
OOC
Social Media
CBE
E-screening
PCDST
Remote Monitoring
Dependent Variables
EEPC
Access to Services - LSEB
Adherence to PPHB
Maternal Depression &
Anxiety, PRS
Maternal Complications
Neonatal/Fetal Complications
Findings

Improved access
to resources/care
Improved patient satisfaction
Improved prenatal education
Improved maternal outcomes
Improved neonatal outcomes
Improved MH outcomes
Increased PNC

44

•
•
•

•

•

•
•

•
•

•
•

•

•
•
•

•
•

•
•
•

•
•

•
•

•
•
•

•

•
•

•

•

•

•

•

•

•
•

•
•
•
•

•

•

•
•
•
•

•
•

•
•
•

•
•
•
•

•
•

•

•

•

•
•

•
•

•
•

•
•

•
•

•

•

•

•
•
•
•

•
•

•
•

•
•

•

•

•
•

Key: BF – breastfeeding; CBE – computer-based education; CBT– cognitive behavioral theory; CSS – cross-sectional study; DE – data extraction; DF – Danaher framework; DHIF
– digital health intervention framework; EEPC – early entry to prenatal care; ES – electronic screening; HBM – health belief model; JBIM – Joanna Briggs Institute Model; LSEB –
low socioeconomic background; MH – mental health; ODLR – online database literature review; OOC – online obstetric counseling; PNC – prenatal care; PP – postpartum; PPHB –
positive prenatal health behaviors; PRS – pregnancy related stress; QCF – quality of care framework; RCT – randomized controlled trial; SDF – social disadvantage framework; SMI
– social media intervention; SR – systematic review

EARLY ENTRY PRENATAL CARE

45
Appendix C

Figure 1

Ajzen (1991)

Theory of Planned Behavior

EARLY ENTRY PRENATAL CARE

46
Appendix D

Figure 2

Iowa Model Collaborative (2017)

The Iowa Model for Evidence-Based Practice

EARLY ENTRY PRENATAL CARE

47
Appendix E

Figure 3

Consent Form English Version

EARLY ENTRY PRENATAL CARE

48
Appendix F

Figure 4

Consent Form Spanish Version

EARLY ENTRY PRENATAL CARE

49
Appendix G

Figure 5

Demographics Survey English Version

EARLY ENTRY PRENATAL CARE

50
Appendix H
Demographics Survey Spanish Version

Figure 6

EARLY ENTRY PRENATAL CARE

51
Appendix I
Recruitment Flyer English Version

Figure 7

EARLY ENTRY PRENATAL CARE

52
Appendix J
Recruitment Flyer Spanish Version

Figure 8

EARLY ENTRY PRENATAL CARE

53
Appendix K
Staff Patient Prompt English Version

Figure 9

EARLY ENTRY PRENATAL CARE

54
Appendix L
Staff Patient Prompt Spanish Version

Figure 10

EARLY ENTRY PRENATAL CARE

55
Appendix M

Figure 11

Prenatal Care Education Survey English Version

EARLY ENTRY PRENATAL CARE

56
Appendix N

Figure 12

Prenatal Care Education Survey Spanish Version

EARLY ENTRY PRENATAL CARE

57
Appendix O
Demographics of Prenatal Patients

Table 1
Demographics of Prenatal Patients
Variable
Age_Range
19-24
25-35
36-45
No Answer
Number_of_living_children
1
0
3
2
No Answer
4
6
Insurance
Yes
AHCCCS
No
No Answer
Level_of_Education
Less than HS
High School
No Answer
College Degree

n

%

7
8
6
2

30
35
26
9

5
3
2
6
5
1
1

22
13
9
26
22
4
4

5
10
7
1

22
43
30
4

4
15
1
3

17
65
4
13

EARLY ENTRY PRENATAL CARE

58
Appendix P

Table 2

Phone Application Survey Question Results

Frequency Table for Prenatal Phone Application Survey Questions 1-9
Variable
Use_Portal
No
Yes
Have_SmartPhone
No
Yes
Internet_Access_on_Phone
No
Yes
Would_use_Phone_App
No
Yes
Missed_Visit
No
Yes
X24_hour_reminder
Yes
No
X2_hour_reminder
Yes
No
App_Helpful
No
Yes
Received_Prenatal_Booklet
Yes
No

n

%

13
10

57
43

3
20

13
87

5
18

22
78

3
20

13
87

17
6

74
26

17
6

74
26

15
8

65
35

2
21

9
91

18
5

78
22

EARLY ENTRY PRENATAL CARE

59
Appendix Q
Prenatal Booklet Survey Question Results

Table 3
Frequency Table for Prenatal Booklet Questions 10-13
Variable
Read_Booklet
Yes
No
Booklet_Helpful
Yes
No
Booklet_Easy_to_read_and_understand
Yes
No
Plan_to_use_booklet
Yes
No

n

%

8
10

44
56

7
11

39
61

7
11

39
61

5
13

28
72

EARLY ENTRY PRENATAL CARE

60
Appendix R
Prenatal Care Education Survey Results

Graph 1

EARLY ENTRY PRENATAL CARE

61
Appendix S
Demographic Survey Results

Graph 2