Perinatal depression and its impact on infant outcomes and maternal-nurse SMS communication in a cohort of Kenyan women

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Study Justification:
– Perinatal depression affects a significant proportion of pregnant and postpartum women in low- and middle-income countries.
– Mobile health (mHealth) interventions using SMS communication can be a solution to identify and provide appropriate referrals for perinatal depression.
– This study aims to examine the prevalence and correlates of perinatal depression, determine its impact on infant outcomes, and compare SMS communication patterns between women with and without perinatal depression.
Study Highlights:
– 32.9% of the 572 women in the study screened positive for elevated depressive symptoms at some point during pregnancy or postpartum.
– Interpersonal abuse during pregnancy, fewer years of schooling, and maternal unemployment were strong predictors of depressive symptoms.
– Antenatal depressive symptoms were associated with an increased risk of infant illness or hospitalization.
– Women with antenatal or persistent perinatal depressive symptoms sent fewer SMS messages during the study period compared to those without depression.
Recommendations for Lay Reader:
– Screening for perinatal depression is important for pregnant and postpartum women.
– Support and interventions should be provided to women experiencing depressive symptoms, including referrals to mental health resources.
– Tailored support through SMS communication can be beneficial for women with perinatal depression.
Recommendations for Policy Maker:
– Implement routine screening for perinatal depression in antenatal and postpartum care settings.
– Allocate resources for mental health services and support for women experiencing perinatal depression.
– Invest in mHealth interventions, such as SMS communication, to provide tailored support for women with perinatal depression.
Key Role Players:
– Community health workers
– Nurses
– OBGYN physicians
– Social workers
– Researchers
Cost Items for Planning Recommendations:
– Training for nurses and healthcare workers on perinatal depression screening and mHealth interventions
– Mental health resources and services
– Development and implementation of SMS communication platform
– Monitoring and evaluation of the mHealth intervention
– Research and data collection expenses

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong as it is based on a prospective longitudinal cohort study with a large sample size. The study utilized standardized questionnaires and statistical analysis to evaluate the prevalence and correlates of perinatal depression, as well as the association between antenatal depression and infant outcomes. The study also compared SMS communication patterns between women with and without perinatal depression. To improve the evidence, it would be beneficial to include more details about the methodology, such as the specific measures used for assessing depressive symptoms and infant outcomes, as well as the statistical methods employed. Additionally, providing information on the representativeness of the study population and the generalizability of the findings would further strengthen the evidence.

Background: Perinatal depression is broadly defined as depressive symptoms during pregnancy or within the 12 months following delivery, affecting approximately 20–25% of pregnant and postpartum women in low- and middle-income countries. The wide accessibility of mobile phones allows mobile health (mHealth) interventions to be considered a solution to identify perinatal depression and provide appropriate referrals for treatment. This study, nested in a larger SMS communication project, examined the prevalence and correlates of perinatal depression, determined the association between antenatal depression and infant morbidity and mortality, and compared SMS communication patterns between women with and without perinatal depression. Methods: This was a prospective longitudinal cohort study of pregnant women seeking antenatal services at two public sector health clinics in Kenya. SMS messages were sent to participants with educational content related to their pregnancy and infant health and two-way SMS communication occurred with a nurse. Sociodemographic and obstetric characteristics, SMS messaging behaviors, infant health status, and depressive symptoms were assessed by a standardized questionnaire administered at enrollment (30–36 weeks gestation) and follow-up (14 weeks postpartum). Generalized estimating equation (GEE) with Poisson link was used to evaluate correlates of perinatal depressive symptoms, infant outcomes, and frequency of SMS messaging. Results: Of the 572 women with complete follow-up information, 188 (32.9%) screened positive for elevated depressive symptoms (≥10 by EPDS scale) at some time point during pregnancy or postpartum. The strongest predictors of any depressive symptoms included interpersonal abuse during pregnancy, fewer years of schooling, and maternal unemployment. Antenatal depressive symptoms were associated with an increased risk of infant illness or hospitalization (RR = 1.12, 95% CI: 1.11, 1.13). Women with antenatal or persistent perinatal depressive symptoms sent fewer SMS messages during the study period than their counterparts without depression. Conclusions: Prevalence of elevated perinatal depressive symptoms was high in this cohort of Kenyan women. Our findings highlight the importance of screening perinatal women for experiences of symptoms of depression as well as abuse. Differences in messaging frequency between women with vs. without depressive symptoms presents an opportunity to provide more tailored support for those perinatal depression.

This study utilizes data collected from a prospective pilot cohort study, known as Mobile Solutions for Women, Adolescents, and Children’s Health: Neonate (Mobile WACh NEO Pilot). The Mobile WACh NEO Pilot study, designed to support maternal and infant outcomes by promoting facility delivery, infant survival and family planning uptake, enrolled 800 pregnant women seeking antenatal care services from two public facilities in Kenya: Mathare North Health Centre (Nairobi County, peri-urban) or Rachuonyo Sub-County Hospital (Homa Bay County, rural) from December 2017 to January 2019. These two public facilities offer a wide range of services for antenatal, birth center and postpartum care as well as have a high volume of daily antenatal appointments (> 10 new mothers per day) and serve a large community of low-income women and babies at high risk of neonatal morbidity and mortality. The Nairobi site serves women living in a large urban slum, and the Western Kenya site serves women living in a low-income rural area. Mobile WACh NEO Pilot participants received pre-programmed SMS messages from enrollment during pregnancy until 14 weeks postpartum. Mobile WACh NEO is designed for maximal impact on neonatal morbidity. Thus, this intervention was implemented at the time when women and their infants are most at risk for experiencing morbidity and mortality, i.e., the last ANC visit (30–36 weeks) to the first postpartum visit (often delayed to approximately 14 weeks postpartum) in order to support and augment perinatal care in this critical period. Content and frequency of pre-programmed messages were dependent upon the woman’s pregnancy status and were delivered in the participant’s preferred language and time of day. Message content was not altered based on depression status. These messages targeted specific actionable health outcomes and encouraged engagement with the nurse. Participants could communicate with the nurse via SMS at any time free of charge. Study nurses managed the bidirectional SMS communication and used national guidelines and local practice standards for the care of pregnant/postpartum women and their infants when responding to participants’ questions. Prior to the start of the study, nurses were trained in these study procedures by two OBGYN physicians (Drs. Kinuthia and Unger) and the study nurse coordinator (Brenda Wandika). These physicians and nurse were available at all times for consultation. In addition, a twice monthly review of all messages was performed by Dr. Unger, and a message review implemented with the team of nurses. Two interviews, one at the time of enrollment and one post-intervention, were conducted with participants to collect demographic, health outcomes, and study-related information. Mobile WACh NEO is a two-way SMS communication intervention designed to engage women with a health care worker at their local clinic with the aim of improving maternal and neonatal outcomes. Messages are personalized, behavioral theory based and action oriented specific to the time point in pregnancy or postpartum. Participants are encouraged to reply to all messages they receive and initiate their own spontaneous messages throughout the study. A study nurse managed SMS communication with participants. Schematic 1 SMS messaging content and frequency Pregnancy (Enrollment – Delivery) Early neonatal period (Delivery- 4 weeks infant age) Postnatal period (4 weeks – 12 weeks infant age) Pregnant women seeking ANC services from the two sites were recruited to participate in the Mobile WACh NEO Pilot intervention. This source population encompassed both rural and peri-urban areas, an ethnically diverse population, and areas with generally low socioeconomic status and high neonatal mortality. Pregnant women were eligible if they had daily access to a mobile phone, were ≥ 14 years of age, and were between 30 and 36 weeks gestation. If a woman was not sufficiently literate but had access to a partner or family member whom she would be comfortable having read her messages, she was eligible for the study. Pregnant women were recruited by community health workers who introduced the study to potential participants, answered questions, and invited women to participate. We introduced the study to all women attending ANC visits at the two clinics between December 2017 and May 2018, and using a convenience sample, we recruited those who agreed to participation and met inclusion criteria. Women were recruited and enrolled on the same day at these two facilities. It was emphasized that participation was completely voluntary and would not in any way affect their antenatal, postnatal, or infant care services. Women who were referred and willing to participate were given a screening questionnaire in order to assess eligibility. Oral consent was obtained for participation in screening. Eligible women who agreed to participate and receive SMS messages provided written informed consent and were entered into the Mobile WACh system along with their preferences for SMS message delivery. Eligible women who chose not to participate were asked their reasons for non-participation, with responses recorded in the screening questionnaire. Women who screened positive for depressive symptoms were referred to available mental health resources, which was the same referral process utilized by the ANC clinics for women not included in the study and typically involved a social worker. Researchers were blinded to a woman’s depression status until after the study concluded; thus, referrals were made within the standard process of the clinical site without interference from the study itself. Women were followed during pregnancy and for 14 weeks postpartum. Participants were administered a standardized questionnaire at enrollment and one follow-up visit (at 14 weeks postpartum) using a tablet-based system (Open Data Kit, ODK) [17]. Exit surveys were conducted either in-person or via telephone, but data on depressive symptoms was not gathered during the phone exit surveys. We collected patient information including questions pertaining to demographics, medical history, experience with SMS and technology, and depression. The Abuse Assessment Screen (AAS) was used to evaluate maternal experience of violence based on participant reports of experiencing physical abuse during the current pregnancy [18]. The AAS has been used as a measure of intimate partner violence in previous studies but is not specific to abuse inflicted by a sexual partner [19]. Undesired pregnancy was defined as the mother reporting she did not want to have a/another baby at the time of becoming pregnant with the current pregnancy. History of miscarriage was a binary variable consisting of women who had reported at least one spontaneous abortion prior to current pregnancy. SMS communication was collected continuously in the Mobile WACh platform throughout the entirety of the study period. Preterm births were defined as delivery prior to 37 weeks estimated gestational age. The type of delivery was classified as either a vaginal delivery, planned Cesarean section (C-section), or unplanned/emergency C-section, based on self-report. Infant morbidity was defined as a mother affirming her child had been to any clinic/hospital for any illness after delivery but before follow-up at 14 weeks or her child had been admitted to the hospital after delivery. Infant mortality was based on maternal report of infant death. The prevalence of depressive symptoms was assessed by dichotomizing self-reported participant Edinburgh Postnatal Depression Scale (EPDS) scores into: < 10, categorized as “no depression” and ≥ 10, categorized as “depression”. For the purposes of this study, we stratified women in this cohort into four patterns of depressive symptoms: 1) antenatal depression (EPDS score ≥ 10 at enrollment), 2) postpartum depression (EPDS score ≥ 10 at follow-up), 3) persistent perinatal depression (EPDS score ≥ 10 at both time-points) and 4) any perinatal depression (EPDS score ≥ 10 at any time-point) [3, 20]. Therefore, women with postpartum depression could represent new-onset postpartum depression (incident depression) or continuation of depression from the antepartum period [20], while any perinatal depression could represent women with antenatal depression only, postpartum depression only, or persistent perinatal depression. Any perinatal depression is meant to account for the fact that depressive symptoms during the perinatal period are dynamic and have historically not been well-characterized longitudinally but rather only in the antenatal or postpartum periods [3]. All SMS messages sent to and received from participants were recorded in the Mobile WACh messaging platform. The sender of the message was classified as the system, the participant, or the nurse. For the purposes of this analysis, only messages that originated from the participants were used to assess level of interaction with the two-way messaging system. Character counts of messages were documented based on the original text messages sent. Participant SMS messaging by participants was categorized into ever having sent ≥1 SMS during the study period vs. never having sent an SMS. Messages whose character count was ≥10 characters were classified as long SMS messages, in an effort to capture conversational messages rather than messages that simply acknowledged receipt of system message. If a participant sought advice from the study nurse, this initiative was considered a nurse consult in this study. Statistical analysis was performed using the program R studio version 1.2.5001 (Boston, 2019). All tests were considered statistically significant at an alpha level of 0.05. Descriptive analyses for baseline sociodemographic and obstetric characteristics of women who completed a second EPDS at follow-up were conducted. Correlates of depression were identified using univariable and multivariable generalized estimating equation (GEE) with Poisson link clustered by facility, with exchangeable correlation structure and robust standard errors. Poisson regression was used to generate effect estimates that could be interpreted as relative risk despite common outcomes. GEE was used to account for similarities by site. Multivariable models were run to control for potential confounders, determined a priori based on literature review: adolescent age (< 20), marital status, education level, employment status, HIV status, monthly income, number of living children, primigravid status, history of miscarriage, experience of abuse during pregnancy, pregnancy desire, and previous family planning use. The main analysis identified correlates of any perinatal depression and secondary analyses were conducted on correlates of each pattern of depression. For the continuous variable of monthly income, results were interpreted as the relative risk of having the depression comparing mothers with 1000 KSh (~ 10 USD) difference in monthly household income. The relative risk for the variable “living children” was interpreted as relative risk of depression associated with one additional living child. Association of antenatal depression as a predictor of infant outcomes of preterm birth, infant morbidity, and infant mortality was analyzed using GEE with Poisson link, clustered by facility, with exchangeable correlation structure and robust standard errors. Univariable and multivariable regressions were run. Confounders in multivariable analyses were chosen a priori from literature review and included adolescence, marital status, education level, employment status, abuse during pregnancy, HIV status, monthly income, distance from clinic, type of delivery, location of delivery, complications during pregnancy, and complications during delivery. We evaluated association of depression with several measures of participant engagement with the SMS platform: a binary outcome of any SMS message sent over the study period; the total number of SMS messages sent; and the total number of long SMS messages (≥10 characters). Each measure of engagement was compared between women with and without depression using univariable and multivariable GEE with Poisson link, clustering by facility, exchangeable correlation structure and robust standard errors. Only antenatal and persistent perinatal depression were included as depression patterns so that depressive symptoms preceded the outcomes of interest. All women with persistent perinatal depression were included in the antenatal depression cohort given the definitions described above. Chi-squared tests were used to assess differences in study nurse consultation between women with and without depression. Again, only antenatal and persistent perinatal depression were included as these depression patterns preceded the outcomes of interest. Fisher’s exact tests were used when sample sizes were too small to get accurate results from Chi-squared tests.

Based on the information provided, here are some potential innovations that could be used to improve access to maternal health:

1. Mobile Health (mHealth) Interventions: Utilize mobile phones to deliver SMS messages with educational content related to pregnancy and infant health. These messages can provide information on perinatal depression, its symptoms, and available resources for treatment. The messages can be personalized, delivered in the participant’s preferred language, and timed to specific stages of pregnancy or postpartum.

2. Two-Way SMS Communication: Implement a system where pregnant women can communicate with healthcare professionals via SMS. This allows women to ask questions, seek advice, and receive support from nurses or other healthcare providers. The communication can be free of charge and available at any time, providing convenient access to maternal health information and assistance.

3. Screening for Perinatal Depression: Integrate screening for perinatal depression into routine antenatal care services. This can help identify women who may be at risk and in need of additional support or treatment. Screening tools, such as the Edinburgh Postnatal Depression Scale (EPDS), can be used to assess depressive symptoms and determine appropriate referrals.

4. Tailored Support for Women with Depression: Recognize the differences in messaging frequency between women with and without depressive symptoms. Use this information to provide more tailored support for women experiencing perinatal depression. This can include additional check-ins, targeted educational content, and increased communication with healthcare professionals to ensure they receive the necessary care and support.

5. Training for Healthcare Professionals: Provide training for healthcare professionals on perinatal depression, its impact on maternal and infant outcomes, and appropriate management strategies. This can help ensure that healthcare providers are equipped to identify and support women with perinatal depression effectively.

It’s important to note that these recommendations are based on the information provided and may need to be adapted to specific contexts and resources available in the target population.
AI Innovations Description
The recommendation based on the study is to utilize mobile health (mHealth) interventions to improve access to maternal health and identify perinatal depression. This can be achieved through SMS communication between pregnant women and healthcare providers. The study found that SMS communication can be effective in providing educational content related to pregnancy and infant health, as well as offering support for women with perinatal depression. The study also highlighted the importance of screening pregnant women for depressive symptoms and experiences of abuse. By implementing SMS communication interventions, healthcare providers can offer more tailored support and referrals for treatment to women with perinatal depression, ultimately improving access to maternal health services.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations to improve access to maternal health:

1. Implement a comprehensive perinatal depression screening program: Develop and implement a standardized screening program for perinatal depression in antenatal care settings. This program should include routine screening using validated tools, such as the Edinburgh Postnatal Depression Scale (EPDS), and appropriate referral pathways for women identified with depressive symptoms.

2. Strengthen mental health services: Increase the availability and accessibility of mental health services, including counseling and therapy, for pregnant and postpartum women. This can be done by training healthcare providers in perinatal mental health and integrating mental health services into existing maternal health programs.

3. Utilize mobile health (mHealth) interventions: Leverage the widespread use of mobile phones to deliver mHealth interventions for identifying and addressing perinatal depression. This can include sending educational content, providing referrals for treatment, and facilitating communication between healthcare providers and women through SMS messaging.

4. Provide tailored support for women with perinatal depression: Develop personalized support programs for women with perinatal depression, taking into account their specific needs and preferences. This can involve providing additional resources, counseling, and follow-up care to ensure that women receive the necessary support throughout their pregnancy and postpartum period.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could be developed as follows:

1. Define the target population: Identify the specific population of pregnant and postpartum women in low- and middle-income countries who would benefit from improved access to maternal health services, particularly in relation to perinatal depression.

2. Collect baseline data: Gather data on the current state of access to maternal health services, including rates of perinatal depression, availability of mental health services, and utilization of mHealth interventions.

3. Develop a simulation model: Create a simulation model that incorporates the identified recommendations and their potential impact on improving access to maternal health. This model should consider factors such as the reach and effectiveness of the interventions, the scalability of the programs, and the potential barriers and facilitators to implementation.

4. Input data and run simulations: Input the collected baseline data into the simulation model and run multiple simulations to assess the impact of the recommendations on improving access to maternal health. This can involve varying parameters, such as the coverage of screening programs, the availability of mental health services, and the engagement with mHealth interventions.

5. Analyze results: Analyze the results of the simulations to determine the potential impact of the recommendations on improving access to maternal health. This can include assessing changes in rates of perinatal depression, utilization of mental health services, and engagement with mHealth interventions.

6. Refine and validate the model: Refine the simulation model based on the analysis of the results and validate it using additional data and real-world observations. This can involve adjusting parameters and assumptions to better reflect the context and dynamics of the target population.

7. Communicate findings and make recommendations: Present the findings of the simulation study, including the potential impact of the recommendations on improving access to maternal health. Use these findings to make evidence-based recommendations for policymakers, healthcare providers, and other stakeholders involved in maternal health programs.

By following this methodology, policymakers and healthcare providers can gain insights into the potential benefits and challenges of implementing innovations to improve access to maternal health, specifically in relation to perinatal depression.

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