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Cadernos de Saúde Pública

Print version ISSN 0102-311XOn-line version ISSN 1678-4464

Cad. Saúde Pública vol.35 no.10 Rio de Janeiro  2019  Epub Oct 14, 2019

http://dx.doi.org/10.1590/0102-311x00111218 

ARTICLE

A communication and information strategy in health and preparation for childbirth: a randomized cluster trial (PRENACEL)

Ana Carolina Arruda Franzon1 
http://orcid.org/0000-0003-4333-3326

Lívia Oliveira-Ciabati1 
http://orcid.org/0000-0002-7163-9456

Lívia Pimenta Bonifácio1 
http://orcid.org/0000-0002-4309-0304

Elisabeth Meloni Vieira1 
http://orcid.org/0000-0002-5229-3904

Magna Santos Andrade1 
http://orcid.org/0000-0002-0557-2169

Jazmin Andrea Cifuentes Sanchez1 
http://orcid.org/0000-0002-4552-0443

Giordana Campos Braga1 
http://orcid.org/0000-0002-0719-056X

Vicky Nogueira-Pileggi1 
http://orcid.org/0000-0003-2284-010X

Mariana Fernandes1 
http://orcid.org/0000-0002-4551-7017

João Paulo Souza1 
http://orcid.org/0000-0002-2288-4244

1 Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, São Paulo, Brasil.


Abstract:

PRENACEL is a study that incorporates two innovative approaches to maternal and perinatal health: the need to improve women’s level of satisfaction with the birthing experience and an assessment of the impacts of information and communication technologies in health. The approaches involve a communication program via short cellphone text messages, developed for Brazilian pregnant women in prenatal care in the Brazilian Unified National Health System. The analysis aims to determine whether the program contributes positively to women’s perceived preparedness for childbirth. A randomized cluster trial was performed in 20 primary care units in Ribeirão Preto, São Paulo State, in 2015 and 2016. Data were collected for 1,210 women from interviews and patient charts. The data were submitted to two analytical models, per protocol and intention-to-treat. Women that had received information from the PRENACEL program during pregnancy were more likely to feel prepared for labor and delivery and to feel that prenatal care had helped them feel more prepared. There were also positive impacts on bonding with the newborn and breastfeeding in the delivery room and on knowledge of obstetric interventions. No differences were seen in the other maternal and perinatal outcomes, including women’s satisfaction with the birthing care. PRENACEL can help expand women’s access to strategic information for them to feel better prepared for the birthing experience.

Keywords: Health Communication; Prenatal Education; Randomized Controlled Trial; Text Messaging; Maternal Health

Resumo:

O PRENACEL é uma pesquisa que incorpora duas abordagens inovadoras para a saúde materna e perinatal: a necessidade de melhorar os níveis de satisfação das mulheres com a experiência do parto; e, a avaliação de impactos do uso de tecnologias de informação e comunicação em saúde. Trata-se de um programa de comunicação via mensagens curtas de textos no celular desenvolvido para gestantes brasileiras atendidas no pré-natal do Sistema Único de Saúde. Nesta análise, pretende-se determinar se o programa contribui positivamente para a percepção das mulheres de sentirem-se melhor preparadas para o parto. Um ensaio aleatorizado por conglomerados foi realizado em 20 unidades de saúde da atenção primária de Ribeirão Preto, São Paulo, entre 2015 e 2016. Dados de entrevista e revisão de prontuários foram coletados de 1210 mulheres. Estes foram submetidos a dois modelos de análise, por protocolo e intenção de tratamento. Receber informações do programa PRENACEL durante a gestação foi associado a um aumento na percepção das mulheres de se sentirem melhor preparadas para o parto, e na percepção de que o pré-natal colabora para que se sintam mais preparadas. Também foram observados impactos positivos no estabelecimento do contato pele a pele e aleitamento materno em sala de parto e no conhecimento sobre intervenções obstétricas. Não foram encontradas diferenças nos demais desfechos maternos e perinatais avaliados, incluindo a satisfação das mulheres com o atendimento ao parto. O PRENACEL pode contribuir com a ampliação do acesso das mulheres a informações que lhes sejam estratégicas para que se sintam mais bem preparadas para a experiência do parto.

Palavras-chave: Comunicação em Saúde; Educação Pré-Natal; Ensaio Clínico Controlado Aleatório; Mensagem de Texto; Saúde Materna

Resumen:

PRENACEL es una investigación que incorpora dos abordajes innovadores para la salud materna y perinatal: la necesidad de mejorar los niveles de satisfacción de las mujeres que han vivido la experiencia de un parto; además de la evaluación de los impactos del uso de tecnologías de la información y comunicación en salud. Se trata de un programa de comunicación vía mensajes cortos de texto en el móvil, desarrollado para gestantes brasileñas atendidas en el servicio prenatal del Sistema Único de Salud. En este análisis se pretende determinar si el programa contribuye positivamente a la percepción de las mujeres respecto a sentirse mejor preparadas para el parto. Se realizó un ensayo aleatorizado por conglomerados en 20 unidades de salud de atención primaria en Ribeirão Preto, São Paulo, entre 2015 y 2016. Los datos de entrevista y revisión de registros médicos se recogieron con 1.210 mujeres. Estos se sometieron a dos modelos de análisis, por protocolo e intención de tratamiento. Recibir información del programa PRENACEL durante la gestación se asoció a un aumento de la percepción de las mujeres en cuanto a sentirse mejor preparadas para el parto, y desde la percepción de que el periodo prenatal presta apoyo para que se sientan más preparadas. También se observaron impactos positivos en el establecimiento del contacto piel con piel, lactancia materna en sala de parto, y en el conocimiento sobre intervenciones obstétricas. No se observaron diferencias en los demás desenlaces maternos y perinatales evaluados, incluyendo la satisfacción de las mujeres con la atención durante el parto. PRENACEL puede contribuir a la ampliación del acceso de las mujeres a información que les resulte estratégica para que se sientan mejor preparadas durante la experiencia del parto.

Palabras-clave: Comunicación en Salud; Educación Prenatal; Ensayo Clínico Controlado Aleatorio; Mensaje de Texto; Salud Materna

Introduction

Although the reduction of maternal mortality remains a global target in the sustainable development goal related to women’s health 1, the international community has focused increasing attention on issues beyond surviving the pregnancy 2,3. Growing importance has been assigned to developing solutions that help women achieve their full life potential 4,5. A new milestone in 2018 emphasizes the need to promote and value models of care that ensure more positive birthing experiences. Such models should be based on adequate use of evidence-based interventions and respect for women decisions and emotional and psychological needs 6,7,8.

In Brazil, access to institutional care during the pregnancy and postpartum cycle is considered practically universal, with 99% of births assisted in hospitals 9. Brazil adopted a model of care for pregnancy, childbirth, and postpartum with a medical obstetrician as the principal provider of obstetric care. The model of care has been described as highly interventionist and medicalized 10,11,12, and recent analyses have focused on strengthening the debate on care centered on the women’s needs and preferencees 13. Current population-based data indicate low or varied prevalence of good practices during care for labor (for example, eating and hydration, walking, use of non-pharmacological pain relief methods, completion of the partograph, and presence of an companion of choice) and high prevalence of obstetric interventions during labor and delivery (for example, venous catheter, Oxytocin induction, amniotomy, analgesia, lithotomy position, Kristeller maneuver, episiotomy, and cesarean section). Fewer than 5% of Brazilian women have had the experience of intervention-free birthing 11. Some studies have also suggested that many women are dissatisfied with the quality of care, including complaints of disrespect, abuse, and mistreatment in health services 7,13. On the other hand, health professionals assisting labor and delivery highlight the relevance of women’s preparation for the birthing process 14,15,16,17.

The use of mobile phones to disseminate health information (Mobile Health or mHealth) during the pregnancy and postpartum cycle has been tested in various countries 18,19,20,21. The results of these assessments suggest that communication programs via mobile phones can provide benefits and prevent health problems, especially important for increasing women’s adherence to professional care and essential interventions in the prenatal and postpartum periods 22. Considering such results and the experience of this article’s authors in assessing the effects of text messages on pregnancy and care 23, we formulated the hypothesis that short text messages can help increase women’s knowledge on the pregnancy’s evolution and care during labor and delivery, thereby improving self-confidence in their birthing capacity.

The PRENACEL intervention presented in this article was developed to simulate a public policy in the Brazilian Unified National Health System (SUS), as a complementary resource to the free institutional care during pregnancy, childbirth, and postpartum used by 60% of all Brazilian women. PRENACEL is a health education and information program developed with the aim of improving maternal and perinatal health. Details on the program’s development are provided in a specific article, currently in the peer review process.

The results of the impacts of PRENACEL on prenatal indicators have been published elsewhere 23, demonstrating their usefulness for increasing the coverage in the number of consultations and repetition of serological tests for HIV and syphilis. The aim of the current analysis was to determine whether the program contributes positively to women’s feeling of preparedness for the experience of vaginal or cesarean delivery, a process we refer to here as “perception of birthing capacity”.

Methods

Study design

To assess the effect of the PRENACEL intervention, a randomized parallel cluster trial was performed in health units that provide prenatal and childbirth care in the public healthcare system in the municipality of Ribeirão Preto, São Paulo State, Brazil.

Selection of participating clusters involved the identification of 20 basic health units (UBS in Portuguese) with the highest numbers of pregnant women in prenatal care according to consolidated data from the Municipal Health Department for the year 2013. The health units were randomized to form the intervention versus control groups (10 UBS in each group).

Selection aimed to optimize the study’s cost-benefit ratio in order to reach the number of pregnant women calculated for the sample, without the need to encompass the city’s entire territory.

In addition to participation by UBS and individuals, the study also included the municipality’s four maternity hospitals, which provide childbirth care for the entire study population.

Participants

The study population consisted of all pregnant women 18 years or older with gestational age less than 20 weeks during the recruitment period for the intervention (April to June 2015), as long as they were in prenatal care in the health units selected to participate in the study.

Randomization of clusters involved two stages. First, two balanced groups of clusters were formed, considering the coverage population’s size and situation of vulnerability (assessed as the number of beneficiaries in the Bolsa Família or conditional cash transfer program). A series of random selections were performed, dividing the clusters into two groups. The clusters’ random allocation was considered balanced when the two groups differed by less than 15%. The selections were performed with the randomization function in Microsoft Excel 2013 (https://products.office.com/) - computer-generated number sequences.

The second stage consisted of allocation of the two groups to intervention versus control, using the same software.

Random selection of clusters was chosen to maximize the applicability of evidence to the health unit and minimize contamination due to the research subject’s or health professional’s preference for a given cluster. The balancing was done to optimize the groups’ comparability.

Intervention

At the cluster level, PRENACEL was implemented in 10 health units allocated to the intervention group. In each site, health professionals that provide care during the pregnancy and postpartum cycle participated in a training meeting with the researchers, during which the study’s objectives and hypotheses were presented and the processes were organized for participants’ recruitment. The health professionals were identified to act as the study’s focal points in the respective health service, reporting difficulties and distributing the recruitment materials to the women. These professionals also displayed posters in the health units and delivered book markers to the women with information on PRENACEL before and after the medical consultation.

At the individual level, the intervention consisted of participation in the PRENACEL program, receiving four text messages per week during pregnancy and until the immediate postpartum. Pregnant women interested in participating requested their registration in the study by sending a text messages with the keyword PRENACEL to the project’s contact number. Next, they received a VoIP call (Voice Over Internet Protocol, on Skype: http://www.skype.com/pt-br/) to attend the registration interview (with obstetric data, childbearing history, and sociodemographic data). The registration interviews were audio-recorded (with the Callnote software: https://callnote.net/) and included the moment of agreement to the free and informed consent and activation of their participation. The women then began to receive text messages according to their reported gestational age. Throughout the intervention period, participants could send their doubts and complaints to the research team. All interaction with the pregnant women was via the online information system SISPRENACEL, developed specifically for the project 23.

During the hospital admission for childbirth, all the eligible women were informed about the research project and could consent to participate in the study, even if they had already agreed to participate during their prenatal care. Data from the patient charts and prenatal cards were collected for all the eligible women. Women who agreed to participate in the project were interviewed using a structured script, and data were collected from the medical charts and prenatal cards.

Data collection

Before the beginning of data collection at the maternity hospitals, the interviewers were trained, and for a month they applied a semifinal version in the field with the instrument prepared for the study. From August 2015 to February 2016, data were collected for all the women who had undergone prenatal care in the 20 health units participating in the study, as long as they met the other inclusion criteria, namely: age 18 years or older and gestational age 20 weeks or less from April to June 2015. Field interviewers conducted daily visits to the maternity hospitals to screen all the postpartum women in the hospital and select those eligible to participate in the study.

The eligible women were invited to participate in a structured individual interview, and their prenatal cards and hospital records were reviewed to obtain the pertinent data.

Control group

In health units allocated to the control group, the women received standard prenatal care. Only when they were admitted for labor and delivery, the “control” women were contacted by the research group and learned of the project. The same protocols were followed as for the intervention group to collect consent and review the medical data.

Assessment of the outcome measures

The principal outcome measure in the analysis was women’s reported perception of having reached the end of pregnancy feeling “very prepared for the delivery or cesarean”; “more or less prepared”; or “totally unprepared”. The secondary outcomes in this analysis are listed below.

(i) Maternal and perinatal results: Beginning of labor (spontaneous, induced, or scheduled cesarean); Presence of a companion of choice; Offer and consumption of diet or liquids during labor; Permission to walk and move around; Offer and use of non-pharmacological pain relief methods; Use of corticoids (during the prenatal period and/or at the maternity hospital); Use of venous catheter during labor; Use of oxytocin during labor; Amniotomy; Epidural analgesia; Episiotomy; Kristeller maneuver; Delivery in lithotomy position; Delivery route (vaginal, forceps/vacuum, cesarean); Breastfeeding and skin-to-skin contact in the first hour of life.

(ii) Knowledge of interventions, decisions on delivery, and satisfaction with care: Participation in educational activity during prenatal care (yes or no); Assessment of the relevance of prenatal care in preparedness for birthing (helped or did not help); Knowledge of Kristeller maneuver (whether previous or during this admission); Knowledge of oxytocin for inducing/conducting labor (whether previous or during this admission); Preference for vaginal delivery, at the beginning of pregnancy; Preference for vaginal delivery, at admission; Final decision on delivery route (whether jointly between the woman and the team, or not); Timing of indication for cesarean (whether in labor or not); Quality of obstetric care (very good, good, satisfactory, bad, very bad); Quality of neonatal care (very good, good, satisfactory, bad, very bad); Comfort and privacy (very good, good, satisfactory, bad, very bad); Continuity of care and support received (all of the time, most of the time, only part of the time, or only during examination); Sufficiency of information received (yes or no); Reported prevalence of disrespect, abuse, and mistreatment (yes or no).

Study period

Health units allocated to the intervention group recruited pregnant women for three months (April to June 2015). Women included in the PRENACEL intervention were followed up until hospital discharge, after outcome of the pregnancy. The data collection stage in the maternity hospitals for the entire study population lasted from August 2015 to February 2016. There were a total of 13 months of participants’ follow-up, with daily data collection in the maternity hospitals for seven months.

Sample size

The primary study’s sample size was determined so as to assess the effects of PRENACEL on prenatal care practices. Details of this calculation have been published elsewhere 23. Briefly, 581 women were needed in the sample (145 pregnant women receiving the intervention and 436 in the control group), with the participation of 10 health units in each group.

Statistical analysis

Assessment of the PRENACEL intervention used two analytical approaches: (i) per protocol analysis (PPA), comparing the pregnant women that received the text messages from PRENACEL versus pregnant women from the control health units and (ii) intention-to-treat analysis (ITT), comparing all the women from the health units in the intervention group versus women from the health units in the control group.

The analyses were performed by comparison of the relative risks (RR), with 95% confidence intervals (95%CI). Significance was set at 5% for all the tests. The data were analyzed with the R software, version 3.3.1 (http://www.r-project.org), with calculation of RR and 95%CI by an Excel table with the formula developed by Rob Herbert 24.

Ethical aspects

The study was conducted in compliance with the recommendations in Resolution n. 466/2012 of the Brazilian National Health Council, after administrative approval by the institutions involved and the Institutional Review Board of the Academic Health Center, Ribeirão Preto School of Medicine, University of São Paulo. The trial is registered in the Brazilian Clinical Trials Registry (REBEC code RBR-54zf73).

Results

The study’s complete flowchart and the health units’ characteristics by study group have been reported elsewhere 23. In relation to balancing of the clusters, no differences were observed between the groups as to healthcare coverage, covered population, and proportion of families enrolled in the conditional cash transfer program. However, the health units in the intervention group had a 30% higher proportion of favela residents (80% vs. 50% in the control group), and 90% of the health units in the control group belonged to universities (vs. 50% in the intervention group).

During recruitment of participants, 350 women expressed interest in receiving PRENACEL messages, and 157 women met the eligibility criteria and received the intervention. After giving birth, during the individual interview stage in the maternity hospitals, 1,210 women were included in the analyses of the principal outcomes: 770 in the intervention group and 440 in the control group. Among the women in the intervention group that expressed interest and were enrolled in PRENACEL (157/770; 20.4%), 41 were excluded after reporting that they had not read the messages, resulting in 116 participants analyzed in the PRENACEL group (116/157; 73.9%).

During the follow-up period for eligible pregnant women registered to receive text messages, the computerized program SISPRENACEL sent 21,703 messages programmed for each gestational age. Importantly, during the same period, 1,087 spontaneous messages were received with participants’ doubts and comments. In response to messages, the research team sent 1,230 personalized text messages, most of which with content focused on institutional prenatal care to answer individual clinical questions.

Per protocol analysis

In the comparison of sociodemographic data between women in the PRENACEL group and the control group (n = 116 vs. n = 440), a difference was found in the number of women with marital status “married or living with companion”: 88.8% in the PRENACEL group versus 80% in the control group (p = 0.04). There was a lower proportion of women in the PRENACEL group from higher social classes (5.6% vs. 14.7%, p = 0.02) and that reported illicit substance use during pregnancy (0% vs. 4.3%, p = 0.02). Details on the study participants’ sociodemographic data have been published in table format elsewhere 23.

In the comparison of the principal outcome measures between the groups, having received the program with messages showed a protective effect in perception of preparedness for childbirth (Table 1). Among the PRENACEL women, 59.5% reported feeling very prepared for childbirth, versus 47.1% of the controls (RR = 1.26; 95%CI: 1.05-1.52). The proportions that reported the relevance of prenatal care for this perception were 81.9% among the PRENACEL women versus 66.2% of the controls (RR = 1.24; 95%CI: 1.11-1.38).

Table 1 Knowledge of interventions, woman’s preference and decision on delivery route, perception of preparedness for childbirth. 

Intervention Control ITT PPA
Total PRENACEL
(n = 770) (n = 116) (n = 440)
n (%) n (%) n (%) RR (95%CI) RR (95%CI)
Knowledge on interventions
Available data 708 116 391
Episiotomy 1.01 (0.95-1.08) 1.14 (1.05-1.23)
Yes 571 (80.6) 105(90.5) 311 (79.5)
No 137 (19.4) 11 (9.5) 80 (20.5)
Kristeller 1.16 (1.04- 1.30) 1.19 (1.01-1.41)
Yes 433 (61.2) 73 (62.9) 206 (52.7)
No 275 (38.8) 43 (37.1) 185 (47.3)
Oxytocin 1.06 (0.98-1.15) 1.14 (1.02-1.29)
Yes 509 (71.9) 90 (77.6) 265 (67.8)
No 199 (28.1) 26 (22.4) 126 (32.2)
Initial preference for vaginal delivery 0.99 (0.94-1.04) 0.94 (0.85-1.04)
Available data 681 115 380
Yes 576 (81.7) 93 (80.2) 326 (83.4)
No 105 (18.3) 22 (19.8) 54 (16.6)
Preference for vaginal delivery, at admission 1.00 (0.95-1.06) 1.01 (0.92-1.11)
Available data 674 112 377
Yes 562 (79.8) 94 (81.7) 314 (80.7)
No 112 (20.2) 18 (18.3) 63 (19.3)
Joitn decision on delivery route 0.95 (0.82-1.11) 1.05 (0.82-1.34)
Available data 704 116 389
Yes 271 (38.3) 49 (42.2) 157 (40.4)
No 433 (61.7) 67 (57.8) 232 (59.6)
Women’s decision 131 (18.5) 21 (18.1) 79 (20.3)
Attending team 302 (42.7) 46 (39.7) 153 (39.3)
Indication of cesarean in labor * 1.01 (0.76-1.35) 1.17 (0.74-1.85)
Available data 219 34 142
Yes 78 (35.6) 14 (41.2) 50 (35.2)
No 141 (64.4) 20 (58.8) 92 (64.8)
Prenatal 95 (43.4) 15 (44.1) 74 (52.1)
Admission 32 (14.6) 4 (11.8) 10 (7.0)
Delivery room 14 (6.4) 1 (2.9) 8 (5.6)
Perception of preparedness for childbirth 1.01 (0.89-1.16) 1.26 (1.05-1.52)
Available data 708 116 391
Yes, very prepared 338 (47.7) 69 (59.5) 184 (47.1)
No 370 (52.3) 47 (40.5) 207 (52.9)
Fairly prepared 224 (31.6) 26 (22.4) 116 (29.7)
Unprepared 146 (20.6) 21 (18.1) 91 (23.3)
Prenatal helped prepare for labor and delivery 1.13 (1.04-1.23) 1.24 (1.11-1.38)
Available data 705 116 390
Yes 528 (74.9) 95 (81.9) 258 (66.2)
No 177 (25.1) 21 (18.1) 132 (33.8)
Very little 107 (15.2) 10 (8.6) 74 (19.0)
No 70 (9.9) 11 (9.5) 58 (14.9)

95%CI: 95% confidence interval; ITT: intention-to-treat analysis; PPA: per protocol analysis; RR: relative risk.

* Only women that underwent cesareans (n = 391). Although the indication for cesarean is more frequent during prenatal care, the analysis was done with reference to the indication for cesarean during labor, based on the study’s technical and conceptual parameters.

The intervention was also associated with greater prior knowledge on the three main obstetric interventions during labor and delivery. Among the PRENACEL women, 90.5% reported having knowledge of episiotomy, versus 79.5% of controls (RR = 1.14; 95%CI: 1.05-1.23). Knowledge of the Kristeller maneuver showed a RR = 1.19 (95%CI: 1.01-1.41), and knowledge of oxytocin for inducing/conducting labor showed an RR = 1.14 (95%CI: 1.02-1.29).

There was no difference in the obstetric, maternal, and perinatal characteristics and results (Table 2). Among the process indicators in childbirth care (Table 3), there was a protective effect from the intervention for breastfeeding and skin-to-skin contact in the first hour of life (RR = 1.21; 95%CI: 1.01-1.45) and a negative effect on the reported offer and consumption of diet during labor (RR = 0.79; 95%CI: 0.64-0.98).

Table 2 Obstetric, maternal, and perinatal characteristics and results. 

Intervention Control ITT PPA
Total PRENACEL
(n = 770) (n = 116) (n = 440)
n (%) n (%) n (%) p-value p-value
Type of pregnancy
Singleton 762 (99.1) 116 (100.0) 434 (98.6) 0.56 0.35
Multiple 7 (0.9) 0 (0.0) 6 (1.4)
Information not available 1 0 0
Gestational age (complete weeks)
Early premature: < 34 26 (3.4) 3 (2.6) 15 (3.4) 0.67 0.34
Late premature: 34 < 37 57 (7.4) 2 (1.7) 27 (6.1)
Early term: 37 < 39 179 (23.2) 30 (25.9) 109 (24.8)
Term: 39 < 41 392 (50.9) 66 (56.9) 216 (49.1)
Late term: 41 < 42 103 (13.4) 13 (11.2) 60 (13.6)
Post-term: 42 < 45 13 (1.7) 2 (1.7) 13 (3.0)
Fetal presentation at delivery
Cephalic 724 (96.0) 110 (96.5) 411 (95.2) 0.45 0.39
Breech 26 (3.5) 3 (2.6) 20 (4.6)
Other 4 (0.5) 1 (0.9) 1 (0.2)
Information not available 16 2 8
Beginning of labor
Spontaneous 494 (65.3) 75 (65.8) 281 (65.2) 0.43 0.93
Induced 154 (20.3) 19 (16.7) 78 (18.1)
Without labor 109 (14.4) 20 (17.5) 72 (16.7)
Information not available 13 2 9
Birthweight (g)
≥ 2,500 693 (90.7) 110 (94.8) 398 (91.3) 0.78 * 0.49 *
1,500-2,499 62 (8.1) 6 (5.2) 35 (8.0)
< 1,500 9 (1.2) 0 (0.0) 3 (0.7)
Information not available 6 0 4
5-minute Apgar score
≥ 7 744 (98.8) 114 (99.1) 422 (97.7) 0.22 0.54
< 7 9 (1.2) 1 (0.9) 10 (2.3)
Information not available 17 1 8
Admission to neonatal UCI
Yes 111 (14.5) 11 (9.6) 65 (14.8) 0.96 0.19
No 652 (85.5) 104 (90.4) 373 (85.2)
Information not available 7 1 2
Severe maternal complications
Yes 58 (7.5) 3 (2.6) 35 (8.0) 0.88 0.07
No 712 (92.5) 113 (97.4) 405 (92.0)
Newborn’s status at mother’s discharge
Alive 719 (94.2) 112 (97.4) 410 (93.6) 0.94 * 0.43 *
Transferred 9 (1.2) 1 (0.9) 5 (1.1)
Hospitalized 33 (4.3) 2 (1.7) 22 (5.0)
Deceased 2 (0.3) 0 (0.0) 1 (0.2)
Information not available 7 1 2
Mother’s status at discharge
Alive 767 (99.7) 115 (100.0) 439 (100.0) 0.54 1.00
Transferred 2 (0.3) 0 (0.0) 0 (0.0)
Deceased 0 (0.0) 0 (0.0) 0 (0.0)
Information not available 1 1 1
Mean maternal lenght-of-stay (days) 2.8 (2.04) 2.53 (1.71) 2.93 (2.66) 0.7747 0.8521
Delivery route
Vaginal 522 (67.8) 79 (68.1) 281 (63.9) 0.03 0.21
Forceps/Vacuum 14 (1.8) 2 (1.7) 2 (0.5)
Cesarean 234 (30.4) 35 (30.2) 157 (35.7)

ITT: intention-to-treat analysis; PPA: per protocol analysis.

* Fisher’s exact test.

Table 3 Process indicators for care during labor and delivery. 

Intervention Control ITT PPA
Total PRENACEL
(n = 770) (n = 116) (n = 440)
n (%) n (%) n (%) RR (95%CI) RR (95%CI)
Partograph completed *,** 1.01 (0.97-1.04) 1.00 (0.94-1.07)
Available data 681 100 379
Yes 635 (93.2) 93 (93.0) 351 (92.6)
No 46 (6.8) 7 (7.0) 28 (7.4)
Breastfeeding/skin-to-skin contact 1.17 (1.04-1.32) 1.21 (1.01-1.45)
Available data 700 116 381
Yes 402 (57.4) 69 (59.5) 187 (49.1)
No 298 (42.6) 47 (40.5) 194 (50.9)
Dilatation at admission in early active phase (4-8cm) 1.01 (0.87-1.16) 1.02 (0.80-1.31)
Available data 715 107 416
Yes 303 (42.3) 46 (43.0) 174 (41.8)
No 412 (57.7) 61 (57.0) 242 (58.2)
< 4cm 339 (47.4) 45 (42.0) 206 (49.5)
≥ 8cm 73 (10.3) 16 (15.0) 36 (8.7)
Presence of a companion of choice
Prepartum/Delivery/Postpartum 0.98 (0.90-1.08) 1.05 (0.91-1.21)
Available data 661 110 353
Yes 438 (66.3) 78 (70.9) 238 (67.4)
No 223 (33.7) 32 (29.1) 115 (32.6)
Prepartum 0.99 (0.94-1.04) 0.96 (0.88-1.05)
Available data 663 110 353
Yes 572 (86.3) 92 (83.6) 307 (87.0)
No 91 (13.7) 18 (16.4) 46 (13.0)
Delivery 0.98 (0.92-1.04) 1.00 (0.91-1.11)
Available data 665 111 356
Yes 532 (80.0) 91 (82.0) 291 (81.7)
No 133 (20.0) 20 (18.0) 65 (18.3)
Postpartum 1.01 (0.94-1.08) 1.00 (0.89-1.12)
Available data 665 111 355
Yes 520 (78.2) 86 (77.5) 276 (77.7)
No 145 (21.8) 25 (22.5) 79 (22.3)
Good practics during labor
Eating 0.85 (0.76-0.96) 0.79 (0.64-0.98)
Available data 552 92 292
Yes 305 (55.3) 47 (51.1) 189 (64.7)
No 247 (44.7) 45 (48.9) 103 (35.3)
Movement * 0.99 (0.91-1.07) 1.04 (0.92-1.18)
Available data 529 87 275
Yes 400 (75.6) 69 (79.3) 210 (76.4)
No 129 (24.4) 18 (20.7) 65 (23.6)
Non-pharmacological pain relief * 1.03 (0.95-1.11) 1.02 (0.89-1.16)
Available data 648 94 359
Yes 484 (63.1) 77 (67.0) 261 (59.6)
No 164 (21.4) 17 (14.8) 98 (22.4)
Interventions during labor and delivery *
Corticoids 0.85 (0.67-1.09) 0.70 (0.44-1.13)
Available data 682 108 378
Yes 131 (19.2) 17 (15.7) 85 (22.5)
No 551 (80.8) 91 (84.3) 293 (77.5)
Peripheral venous catheter 1.04 (0.92-1.18) 1.00 (0.81-1.23)
Available data 563 93 305
Yes 324 (57.5) 51 (54.8) 168 (55.1)
No 239 (42.5) 42 (45.2) 137 (44.9)
Oxytocin 0.98 (0.84-1.14) 1.02 (0.81-1.30)
Available data 316 54 161
Yes 191 (60.4) 34 (63.0) 99 (61.5)
No 125 (39.6) 20 (37.0) 62 (38.5)
Amniotomy 1.00 (0.83-1.22) 1.04 (0.76-1.43)
Available data 552 90 302
Yes 189 (34.2) 32 (35.5) 103 (34.1)
No 363 (65.8) 58 (64.5) 199 (65.9)
Epidural analgesia 0.97 (0.86-1.09) 1.09 (0.91-1.30)
Available data 523 87 276
Yes 304 (58.1) 57 (65.5) 166 (60.1)
No 219 (41.9) 30 (34.5) 110 (39.9)
Episiotomy 1.21 (0.82-1.77) 1.36 (0.75-2.47)
Available data 534 83 287
Yes 74 (13.9) 13 (15.7) 33 (11.5)
No 460 (86.1) 70 (84.3) 254 (88.5)
Kristeller maneuver 1.38 (0.89-2.15) 1.49 (0.78-2.85)
Available data 486 83 248
Yes 65 (13.4) 12 (14.5) 24 (9.7)
No 421 (86.6) 71 (85.5) 224 (90.3)
Lithotomy position 1.01 (0.93-1.10) 0.99 (0.87-1.14)
Available data 489 84 249
Yes 380 (77.7) 64 (76.2) 191 (76.7)
No 109 (22.3) 20 (23.8) 58 (23.3)

95%CI: 95% confidence interval; ITT: intention-to-treat analysis; PPA: per protocol analysis; RR: relative risk.

* Only women that entered labor, early active phase;

** Information on patient chart.

No differences were observed between the groups in the assessment of satisfaction with obstetric care in the maternity hospitals (Table 4).

Satisfaction with care received at the maternity hospital. 

Intervention Control ITT PPA
Total PRENACEL
(n = 770) (n = 116) (n = 440)
n (%) n (%) n (%) RR (95%CI) RR (95%CI)
Obstetric care very good or good 0.99 (0.95-1.03) 0.98 (0.91-1.06)
Available data 707 116 390
Yes 628 (88.8) 102 (88.0) 350 (89.8)
No 79 (11.2) 14 (12.0) 40 (10.2)
Very good 381(53.9) 64 (55.2) 219 (56.2)
Good 247 (34.9) 38 (32.8) 131 (33.6)
Satisfactory 59 (8.3) 11 (9.5) 34 (8.7)
Bad 13 (1.8) 1 (0.9) 4 (1.0)
Terrible 7 (1.0) 2 (1.7) 2 (0.5)
Neonatal care very good or goodm 1.01 (0.98-1.04) 1.02 (0.98-1.06)
Available data 704 116 390
Yes 676 (96.0) 112 (96.6) 370 (94.8)
No 28 (4.0) 4 (3.4) 20 (5.2)
Very good 435 (61.8) 75 (64.7) 256 (65.6)
Good 241 (34.2) 37 (31.9) 114 (29.2)
Satisfactory 24 (3.4) 4 (3.4) 18 (4.6)
Bad 3 (0.4) 0 (0.0) 1 (0.3)
Terrible 1 (0.1) 0 (0.0) 1 (0.3)
Comfort and privacy very good or good 0.98 (0.95-1.01) 0.95 (0.88-1.01)
Available data 708 116 390
Yes 651 (92.0) 103 (88.8) 366 (93.1)
No 57 (8.0) 13 (11.2) 24 (6.9)
Very good 312 (44.1) 55 (47.4) 198 (50.8)
Good 339 (47.9) 48 (41.4) 168 (43.1)
Satisfactory 46 (6.5) 12 (10.3) 20 (5.1)
Bad 9 (1.3) 1 (0.9) 3 (0.8)
Terrible 2 (0.3) 0 (0.0) 1 (0.3)
Continuos care and support 0.96 (0.86-1.08) 0.91 (0.74-1.11)
Available data 706 116 390
Yes 375 (53.2) 58 (50.0) 215 (55.1)
No 331 (46.8) 58 (50.0) 175 (44.9)
Most of the time 253 (35.8) 41 (35.3) 134 (34.4)
Little 44 (6.2) 11 (9.5) 16 (4.1)
No 34 (4.8) 6 (5.2) 25 (6.4)
Information received was sufficient 1.02 (0.98-1.06) 0.99 (0.92-1.07)
Available data 707 116 391
Yes 643 (90.9) 103 (88.8) 349 (89.3)
No 64 (9.1) 13 (11.2) 42 (10.7)
Insufficient 49 (6.9) 12 (10.3) 33 (8.4)
No 15 (2.1) 1 (0.9) 9 (2.3)
Disrespect, abuse, and mistreatment 0.95 (0.54-1.68) 0.94 (0.36-2.47)
Available data 707 116 391
Yes 31 (4.4) 5 (4.3) 18 (4.6)
No 676 (95.6) 11 (95.7) 372 (95.1)
Does not know 0 (0.0) 0 (0.0) 1 (0.3)

95%CI: 95% confidence interval; ITT: intention-to-treat analysis; PPA: per protocol analysis; RR: relative risk.

Intention-to-treat analysis

In the comparison of the sociodemographic data between women in the intervention and control groups (n = 770 vs. n = 440), the intervention group showed a lower proportion of women from more affluent social classes (10.1% vs. 14.7% in the control group; p = 0.0002) and a lower proportion of women that reported illicit substance use during pregnancy (2% vs. 4.3% in the control group; p = 0.03). The complete table has been reported in a previous publication on this study 23.

In the approach to the principal outcome measures (Table 1), no difference was found for the variable “feeling very prepared for childbirth”, while the assessment of the relevance of prenatal care for preparedness for childbirth resulted in a RR = 1.13; (95%CI: 1.04-1.38). In the selected triad of obstetric interventions during labor and delivery, PRENACEL produced a protective effect in terms of prior knowledge on the fundal pressure maneuver (RR = 1.16; 95%CI: 1.04-1.30). No differences were found in the other variables concerning knowledge of interventions and perception of preparedness for birthing, or in women’s satisfaction with care in the maternity hospitals (Table 4).

No effects from the intervention were observed on the obstetric, maternal, and perinatal characteristics and outcomes (Table 2). For the process indicators in childbirth care (Table 3), comparison of the intervention and control groups showed a protective effect for breastfeeding and skin-to-skin contact in the first hour of life (RR = 1.17; 95%CI: 1.04-1.32) and a negative effect on the reported offer/consumption of diet during labor (RR = 0.85; 95%CI: 0.76-0.96).

Discussion

The study’s findings suggest that the use of text messages with information on pregnancy, labor, delivery, and their management help improve women’s perception of their birthing capacity. The study also found that receiving text messages contributed to the perception that prenatal care increases the participants’ birthing capacity. Other associations were found with the supply of information to the women: greater knowledge (prior to childbirth) on the use of interventions such as episiotomy, fundal pressure, and oxytocin induction, in addition to better results with early skin-to-skin contact and breastfeeding.

No differences were observed between the groups in the use of obstetric interventions in labor and childbirth, medical outcomes of the pregnancy and birth, or women’s satisfaction with the care.

Although most studies on the effectiveness of mHealth interventions have focused on assessing prenatal and postnatal indicators, the absence of impact on maternal and perinatal outcomes had already been observed in some situations 22, described next. According to a recent systematic review of 27 intervention studies employing communication via mobile technologies, only one study provided information on severe maternal morbidity or maternal mortality. Conducted in Nigeria, the study concluded that the communication technology did not produce differences in the determinants of deaths in the analysis 25. The evaluation of an incentive to consume iron supplements in pregnancy via mHealth showed women’s improved adherence to the protocol, but without resulting in differences in maternal anemia or hemoglobin, hematocrit, and ferritin levels 26. Another study, in Thailand, managed to show better levels of satisfaction, confidence, and anxiety in women that received text messages during prenatal care, but no differences were found in gestational age at delivery or delivery route 27.

Importantly, most of the evidence to date in this area has been produced in settings in which coverage and access to clinical interventions may be insufficient, and thus where “delays” in managing care are common. Such interventions have achieved their objectives by delivering educational information and reminders that stimulate women’s demand for inputs and/or interventions, and in the final analysis they include practices that depend on women active adherence and engagement. Meanwhile, in the context of the PRENACEL study, the health situation of women receiving care in the SUS is characterized by high coverage of essential interventions in prenatal care and childbirth 11,28 and the high human development index in the city where the study was performed 29. Nevertheless, this scenario is quite timely for the proposed test of effectiveness, since PRENACEL confirmed its usefulness for further expanding the coverage of some recommended practices in prenatal care 23 and childbirth, such as early breastfeeding and skin-to-skin contact, besides having promoted the women’s access to relevant information on practices in maternity hospitals.

Another strength in the study was the communications model implemented by PRENACEL. Besides the messages’ educational function, including reminders, the intervention guaranteed the women’s opportunity for two-way communication; that is, during follow-up, the online communication system allowed automatically sending the scheduled text messages and spontaneously receiving the women’s questions and comments (at zero cost to participants), which were answered by the researchers. Active engagement in the spontaneous and individual communication with the study by nearly 40% of the participants may be relevant to the women’s satisfaction and their perception of being included in the decisions on their care. These are important results for our research questions and potential analyses for future publications.

The study’s limitations include a potential selection bias of women interested in receiving text messages as a complement to their regular prenatal care. In addition to the study population’s sociodemographic characteristics, the community in Ribeirão Preto is in constant and varied contact with the university and its research centers. Such factors may have contributed to the absence of impact on most of the target indicators.

Another significant limitation to the study was the demarcation of the PRENACEL target public: since this was a test of effectiveness of a program targeted to healthy pregnant women, it excluded women with a diagnosis of high-risk pregnancy. In addition, the study did not include adolescents under 18 years of age. This decision was based on the age of majority in Brazil. The country’s prevailing legislation would not allow women under 18 to participate spontaneously in the individual intervention or to consent to having their data collected in the maternity hospitals. This suggests an avenue for future studies, which could focus on customizing the information to orient the women. Participants in the current study presented privileged social indicators in terms of social vulnerabilities: most of the women included in the analysis were white or brown, had at least nine years of schooling, were white, and were married or living with a companion.

Considering the high rates of obstetric interventions in childbirth care in Brazil, the study showed the strength of raising women’s awareness concerning good practices for a positive birthing experience. Providing women with knowledge on female physiology and healthcare practices had already been associated with lower rates of early admission in labor, increased use of good practices in care during labor, and reduction of unnecessary cesareans among primiparous women assisted by the SUS 30.

In addition to encouraging compliance with recommendations associated with better outcomes and satisfaction, such as presence of a companion of choice, consumption of diet during labor, and freedom of movement, PRENACEL sought to promote the informed refusal of some interventions such as episiotomy and the lithotomy position during fetal expulsion 6,31. In the context of this study, despite acknowledging women’s limited control over the interventions performed during the process of care, especially in the hospital setting 13,32, we highlight the relevance (for health policies) of the association between receiving educational information and women’s improved perception of their birthing capacity in general, and specifically the finding that prenatal care helps them feel better prepared for childbirth. Health education to prepare for labor and delivery has been highlighted as an effective strategy for including women’s preferences during the decisions. In addition, the literature emphasizes that a positive birthing experience is associated with women’s participation in decisions on their care 7,17. The literature review suggests that this is the first result of cellphone text messages as an intervention to improve perceived birthing capacity.

Conclusion

The improvement of women’s confidence in their birthing capacity and valuing the limited and adequate use of interventions during labor and delivery is a challenge in the cultural context of obstetric care in Brazil. PRENACEL can contribute to the expansion of women’s access to strategic information for them to feel better prepared for the birthing experience.

Acknowledgments

The authors wish to thank: the women that participated in the study; Caio Prado, Simone Diniz, Carolina S. Vieira, Cynthia Pileggi-Castro, Domingos Alves, Elaine Moises, Fabiani Zaratini, Leonardo Moscovici, Maria J. Clapis, Nadia Z. Narchi, Silvana Quintana, Sonia Lansky, and Suzi Volpato for their collaboration; health system professionals, participating institutions, and the Ribeirão Preto Municipal Government; and the Brazilian Graduate Studies Coordinating Board and the Brazilian National Research Council, Capes/CNPq Science Without Borders Program (CSF-PAJT 2514/2013, case review n. 23,038.007622/2013-60).

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Received: June 07, 2018; Revised: March 20, 2019; Accepted: March 29, 2019

Correspondence A. C. A. Franzon Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. Av. Bandeirantes 3900, Ribeirão Preto, SP 14040-900, Brasil. anafranzon@yahoo.com.br

Contributors

A. C. A. Franzon developed the PRENACEL messages, led the expert panel in the assessment and tests with users, elaborated the analytical plan and first draft of the article, and contributed to the study’s implementation, analysis, and/or interpretation. L. Oliveira-Ciabati developed the computerized system for sending and receiving the messages, contributed to the study’s implementation, analysis, and/or interpretation, and revised the article and approved the final version for publication. L. P. Bonifácio, M. S. Andrade, J. A. C. Sanchez, G. C. Braga, V. Nogueira-Pileggi, and M. Fernandes contributed to the study’s implementation, analysis, and/or interpretation and revised the article and approved the final version for publication. E. M. Vieira was responsible for the project’s technical coordination, participated in the study design, fieldwork planning, and development of the instruments. contributed to the study’s implementation, analysis, and/or interpretation, and revised the article and approved the final version for publication. J. P. Souza conceived the research project, elaborated the analytical plan and first draft of the article, contributed to the study’s implementation, analysis, and/or interpretation, and revised the article and approved the final version for publication.

Additional informations

ORCID: Ana Carolina Arruda Franzon (0000-0003-4333-3326); Lívia Oliveira-Ciabati (0000-0002-7163-9456); Lívia Pimenta Bonifácio (0000-0002-4309-0304); Elisabeth Meloni Vieira (0000-0002-5229-3904); Magna Santos Andrade (0000-0002-0557-2169); Jazmin Andrea Cifuentes Sanchez (0000-0002-4552-0443); Giordana Campos Braga (0000-0002-0719-056X); Vicky Nogueira-Pileggi (0000-0003-2284-010X); Mariana Fernandes (0000-0002-4551-7017); João Paulo Souza (0000-0002-2288-4244).

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