Advances in virtual care for perinatal mental disorders

Postpartum Depression: A Clinical Review of Impact and Current Treatment Solutions

Depression during the first year postpartum (postpartum depression) impacts millions of women and their families worldwide. In this narrative review, we provide a summary of postpartum depression, examining the etiology and consequences, pharmacological and psychological treatments, and potential mechanisms of change and current barriers to care. Psychological treatments are effective and preferred by many perinatal patients over medications, but they often remain inaccessible. Key potential mechanisms underlying their effectiveness include treatment variables (e.g., dosage and therapeutic alliance) and patient behaviors (e.g., activation and avoidance and emotional regulation). Among pharmacological treatments, the selective serotonin reuptake inhibitor (SSRI) sertraline is generally the first-line antidepressant medication recommended to women in the postpartum period due to its minimal passage into breastmilk and the corresponding decades of safety data. Importantly, most antidepressant drugs are considered compatible with breastfeeding. Neurosteroids are emerging as an effective treatment for postpartum depression, although currently this treatment is not widely available. Barriers to widespread access to treatment include those that are systematic (e.g., lack of specialist providers), provider-driven (e.g., lack of flexibility in treatment delivery), and patient-driven (e.g., stigma and lack of time for treatment engagement). We propose virtual care, task-sharing to non-specialist treatment providers, and collaborative care models as potential solutions to enhance the reach and scalability of effective treatments to address the growing burden of postpartum depression worldwide and its negative impact on families and society.

AI and narrative embeddings detect PTSD following childbirth via birth stories

Free-text analysis using machine learning (ML)-based natural language processing (NLP) shows promise for diagnosing psychiatric conditions. Chat Generative Pre-trained Transformer (ChatGPT) has demonstrated preliminary initial feasibility for this purpose; however, whether it can accurately assess mental illness remains to be determined. This study evaluates the effectiveness of ChatGPT and the text-embedding-ada-002 (ADA) model in detecting post-traumatic stress disorder following childbirth (CB-PTSD), a maternal postpartum mental illness affecting millions of women annually, with no standard screening protocol. Using a sample of 1295 women who gave birth in the last six months and were 18+ years old, recruited through hospital announcements, social media, and professional organizations, we explore ChatGPT's and ADA's potential to screen for CB-PTSD by analyzing maternal childbirth narratives. The PTSD Checklist for DSM-5 (PCL-5; cutoff 31) was used to assess CB-PTSD. By developing an ML model that utilizes numerical vector representation of the ADA model, we identify CB-PTSD via narrative classification. Our model outperformed (F1 score: 0.81) ChatGPT and six previously published large text-embedding models trained on mental health or clinical domains data, suggesting that the ADA model can be harnessed to identify CB-PTSD. Our modeling approach could be generalized to assess other mental health disorders.

Integrating Mental Health Care in Ambulatory Obstetrical Practices: Strategies and Models

Perinatal mental health is recognized as a priority component of obstetrical care. Perinatal patients often turn to their obstetrician for help with mental health concerns as they view them as their primary health care provider. Unfortunately, obstetricians face challenges in providing adequate support due to time constraints and limited expertise. Integrated behavioral health care offers a collaborative and cost-effective solution to enhance patient care and clinician satisfaction. Integrated behavioral health clinicians possess fundamental skills to care for patients throughout the reproductive lifespan and assist obstetricians in identifying and managing common mood concerns.

OpenAI's Narrative Embeddings Can Be Used for Detecting Post-Traumatic Stress Following Childbirth Via Birth Stories

Free-text analysis using Machine Learning (ML)-based Natural Language Processing (NLP) shows promise for diagnosing psychiatric conditions. Chat Generative Pre-trained Transformer (ChatGPT) has demonstrated preliminary initial feasibility for this purpose; however, whether it can accurately assess mental illness remains to be determined. This study evaluates the effectiveness of ChatGPT and the text-embedding-ada-002 (ADA) model in detecting post-traumatic stress disorder following childbirth (CB-PTSD), a maternal postpartum mental illness affecting millions of women annually, with no standard screening protocol. Using a sample of 1,295 women who gave birth in the last six months and were 18+ years old, recruited through hospital announcements, social media, and professional organizations, we explore ChatGPT's and ADA's potential to screen for CB-PTSD by analyzing maternal childbirth narratives. The PTSD Checklist for DSM-5 (PCL-5; cutoff 31) was used to assess CB-PTSD. By developing an ML model that utilizes numerical vector representation of the ADA model, we identify CB-PTSD via narrative classification. Our model outperformed (F1 score: 0.82) ChatGPT and six previously published large language models (LLMs) trained on mental health or clinical domains data, suggesting that the ADA model can be harnessed to identify CB-PTSD. Our modeling approach could be generalized to assess other mental health disorders.

Perinatal mental health and COVID-19: Navigating a way forward

The COVID-19 pandemic and its aftermath have increased pre-existing inequalities and risk factors for mental disorders in general, but perinatal mental disorders are of particular concern. They are already underdiagnosed and undertreated, and this has been magnified by the pandemic. Access to services (both psychiatric and obstetric) has been reduced, and in-person contact has been restricted because of the increased risks. Rates of perinatal anxiety and depressive symptoms have increased. In the face of these challenges, clear guidance in perinatal mental health is needed for patients and clinicians. However, a systematic search of the available resources showed only a small amount of guidance from a few countries, with a focus on the acute phase of the pandemic rather than the challenges of new variants and variable rates of infection. Telepsychiatry offers advantages during times of restricted social contact and also as an additional route for accessing a wide range of digital technologies. While there is a strong evidence base for general telepsychiatry, the particular issues in perinatal mental health need further examination. Clinicians will need expertise and training to navigate a hybrid model, flexibly combining in person and remote assessments according to risk, clinical need and individual patient preferences. There are also wider issues of care planning in the context of varying infection rates, restrictions and vaccination access in different countries. Clinicians will need to focus on prevention, treatment, risk assessment and symptom monitoring, but there will also need to be an urgent and coordinated focus on guidance and planning across all organisations involved in perinatal mental health care.

Review of Mobile Apps for Women With Anxiety in Pregnancy: Maternity Care Professionals' Guide to Locating and Assessing Anxiety Apps

Background

Mental health and pregnancy apps are widely available and have the potential to improve health outcomes and enhance women’s experience of pregnancy. Women frequently access digital information throughout their pregnancy. However, health care providers and women have little information to guide them toward potentially helpful or effective apps.

Objective

This review aimed to evaluate a methodology for systematically searching and reviewing commercially available apps that support pregnant women with symptoms of anxiety in order to assist maternity care professionals in identifying resources that they could recommend for these women.

Methods

A stepwise systematic approach was used to identify, select, describe, and assess the most popular and highly user-rated apps available in the United Kingdom from January to March 2021. This included developing a script-based search strategy and search process, writing evaluation criteria, and conducting a narrative description and evaluation of the selected apps.

Results

Useful search terms were identified, which included nonclinical, aspirational, and problem-based phrases. There were 39 apps selected for inclusion in the review. No apps specifically targeted women with anxiety in pregnancy. Of the 39 apps included in the review, 33 (85%) focused solely on mind-body techniques to promote relaxation, stress reduction, and psychological well-being. Only 8 of the 39 (21%) apps included in the review reported that health care professionals had contributed to app development and only 1/39 (3%) provided empirical evidence on the effectiveness and acceptability of the app. The top 12/39 (31%) apps were evaluated by 2 independent reviewers using the developed criteria and scores. There was a small negative correlation between the reviewers’ scores and app user rating scores, with higher user rating scores associated with lower reviewer scores.

Conclusions

App developers, publishers, and maternity care professionals should seek advice from women with lived experience of anxiety symptoms in pregnancy to locate, promote, and optimize the visibility of apps for pregnant women. There is a lack of resources that provide coping strategies based on current evidence for the treatment of anxiety in pregnancy. Maternity care providers are limited in their ability to locate and recommend acceptable and trustworthy apps because of the lack of information on the evidence base, development, and testing of apps. Maternity care professionals and women need access to libraries of trusted apps that have been evaluated against relevant and established criteria.

Remotely Delivered Interventions to Support Women With Symptoms of Anxiety in Pregnancy: Mixed Methods Systematic Review and Meta-analysis

BACKGROUND

Symptoms of anxiety are common in pregnancy, with severe symptoms associated with negative outcomes for women and babies. Low-level psychological therapy is recommended for women with mild to moderate anxiety, with the aim of preventing an escalation of symptoms and providing coping strategies. Remotely delivered interventions have been suggested to improve access to treatment and support and provide a cost-effective, flexible, and timely solution.

OBJECTIVE

This study identifies and evaluates remotely delivered, digital, or web-based interventions to support women with symptoms of anxiety during pregnancy.

METHODS

This mixed methods systematic review followed a convergent segregated approach to synthesize qualitative and quantitative data. The ACM Digital Library, Allied and Complementary Medicine Database, Applied Social Sciences Index and Abstracts, Centre for Reviews and Dissemination database, the Cochrane Central Register of Controlled Trials, the Cochrane Library, CINAHL, Embase, Health Technology Assessment Library, IEEE Xplore, Joanna Briggs Institute, Maternity and Infant Care, MEDLINE, PsycINFO, and the Social Science Citation Index were searched in October 2020. Quantitative or qualitative primary research that included pregnant women and evaluated remotely delivered interventions reporting measures of anxiety, fear, stress, distress, women's views, and opinions were included.

RESULTS

Overall, 3 qualitative studies and 14 quantitative studies were included. Populations included a general antenatal population and pregnant women having anxiety and depression, fear of childbirth, insomnia, and preterm labor. Interventions included cognitive behavioral therapy, problem solving, mindfulness, and educational designs. Most interventions were delivered via web-based platforms, and 62% (8/13) included direct contact from trained therapists or coaches. A meta-analysis of the quantitative data found internet-based cognitive behavioral therapy and facilitated interventions showed a beneficial effect in relation to the reduction of anxiety scores (standardized mean difference -0.49, 95% CI -0.75 to -0.22; standardized mean difference -0.48, 95% CI -0.75 to -0.22). Due to limitations in the amount of available data and study quality, the findings should be interpreted with caution. Synthesized findings found some evidence to suggest that interventions are more effective when women maintain regular participation which may be enhanced by providing regular contact with therapists or peer support, appropriate targeting of interventions involving components of relaxation and cognitive-based skills, and providing sufficient sessions to develop new skills without being too time consuming.

CONCLUSIONS

There is limited evidence to suggest that women who are pregnant may benefit from remotely delivered interventions. Components of interventions that may improve the effectiveness and acceptability of remotely delivered interventions included providing web-based contact with a therapist, health care professional, or peer community. Women may be more motivated to complete interventions that are perceived as relevant or tailored to their needs. Remote interventions may also provide women with greater anonymity to help them feel more confident in disclosing their symptoms.

Does antenatal depression predict post-partum depression and obstetric complications? Results from a longitudinal, long-term, real-world study

BACKGROUND

Main aims of the present paper are to: (1) assess the prevalence of antenatal depression (AD) and identify its predictors; (2) analyse the impact of AD on obstetric outcomes and on the incidence of post-partum depression.

METHODS

All pregnant women referring to the Gynecology and Obstetrics inpatients unit of the University of Campania "Luigi Vanvitelli" were invited to participate. Upon acceptance, women completed the Italian version of the Edinburgh Postnatal Depression Scale and an ad-hoc questionnaire on the women's sociodemographic, gynecological and peripartum characteristics as well as their psychiatric history. Women were assessed at each trimester of pregnancy, immediately after the childbirth and after one, three, 6 and 11 months.

RESULTS

268 pregnant women were recruited, with a mean of 32.2 (±5.81) years. Ninety-seven women (36.2%) reported the presence of depressive symptoms during pregnancy. Predictors of AD were personal history of depression, a family history for depressive disorders and problematic relationships with the partner. The presence of AD was associated to a reduced gestational age at the time of delivery, a lower APGAR score at 1 and 5 min, labor induction and admission of the new-born into neonatal intensive care unit. Mothers with antenatal depression are less likely to natural breastfeed. Lastly, antenatal depression was a risk factor for higher EPDS scores at follow-ups.

CONCLUSIONS

Our results support the idea that women should be screened during pregnancy and post-partum for the presence of depressive and anxiety symptoms. Health professionals should be adequately trained to detect psychiatric symptoms during pregnancy.

Mother Matters: Pilot randomized wait-list controlled trial of an online therapist-facilitated discussion board and support group for postpartum depression symptoms

METHODS

In a pilot randomized waitlist-controlled trial (Ontario, Canada), individuals aged ≥18 years with Edinburgh Postnatal Depression Scale (EPDS) scores greater than 9 and who self-identified as a mother to a child aged 0-12 months were randomized 1:1 to Mother Matters (intervention) or usual care (control), with an opportunity to receive the intervention after the study was complete. The primary outcome was protocol feasibility, evaluated through recruitment feasibility, intervention acceptability, and adherence to study follow-up measures. Secondarily, postintervention EPDS scores and remission rates (EPDS < 10) were compared between groups.

RESULTS

Ninety-eight participants were randomized (n = 50 intervention; n = 48 control) and seventy-seven (78.6%) completed postintervention questionnaires. About 88% of the intervention group (n = 44) logged into Mother Matters. Almost all topics were rated highly for relevance, there was good group cohesion and good satisfaction with the intervention. Mean (SD) EPDS scores decreased from 14.5 (4.07) to 11.3 (4.54) in the intervention group and 15.0 (3.56) to 12.0 (4.79) among controls (adjusted mean difference [aMD] -0.58, 95% confidence interval [CI]: -2.68 to 1.52), with remission in 37.8% versus 25.0% for intervention group and controls, respectively (χ²  = 1.48; p = .224). Among those with EPDS ≥ 16, the aMD was -3.66 (95% CI: -6.65 to -0.67) with remission in 41.2% in the intervention group versus 10.0% among controls (χ²  = 4.50; p = .06).

CONCLUSION

This study supports the pursuit of online, therapist-facilitated, discussion board support group strategies for PPD. A large-scale efficacy and cost-effectiveness evaluation of Mother Matters is warranted.

Perinatal Mental Health Care for Women With Severe Mental Illness During the COVID-19 Pandemic in India-Challenges and Potential Solutions Based on Two Case Reports

The ongoing COVID-19 pandemic in India has created several challenges in the care of women with perinatal mental illness. Access to healthcare has been disrupted by lockdowns, travel restrictions, and the unavailability of outpatient services. This report aims to discuss the challenges faced by women with severe mental illnesses during the perinatal period with the help of two case reports. Accordingly, we have highlighted the role of COVID-19 infection as a traumatic event during childbirth and its role in triggering a psychotic episode in women with vulnerabilities; difficulties faced by women with postpartum psychosis in accessing perinatal psychiatry services; and the challenges of admission into an inpatient Mother-Baby Unit (MBU). Further, we have discussed potential solutions from the perspectives of Lower and Middle-income (LAMI) countries that need to be extended beyond the pandemic. They include offering video consultations, reviewing hospital policies, and evolving strategies to mitigate traumatic experiences for pregnant and postpartum women with severe mental illnesses in both obstetric and psychiatric care.

The Transition From Maternity Blues to Full-Blown Perinatal Depression: Results From a Longitudinal Study

Background: The aims of the present study are to: (1) assess the frequency of maternity blues (MB); (2) identify the clinical and social characteristics more frequently associated with the onset of depressive symptoms after delivery; and (3) verify the hypothesis that the presence of maternity blues is a risk factor for the onset of a full-blown depressive episode in the 12 months after delivery. Methods: This is a longitudinal observational study. All pregnant women who gave birth at the inpatient unit of Gynecology and Obstetrics of the University of Campania "Luigi Vanvitelli" from December 2019 to February 2021 have been invited to participate in the study. Upon acceptance, women were asked to complete the Italian version of the Edinburgh Postnatal Depression Scale along with an ad-hoc questionnaire on the women's sociodemographic, gynecological and peripartum characteristics as well as their psychiatric history. Women have been reassessed after one, 3, 6 and 12 months. Results: A total of 359 women were recruited within 3 days from delivery, with a mean EPDS total score of 5.51 (±4.20). Eighty-three women (23.1%) reported the presence of maternity blues. Mean EPDS total scores were 12.8 (±0.2) in the MB group vs. 4.26 (±0.2) in the group without MB (p <0.0001). MB predictors were the presence of an anxiety disorder with an onset 6 months prior to pregnancy, of preeclampsia, of increased fetal health rate, of conflicts with relatives other than partner and having a partner with an anxiety disorder. At multivariate analyses the presence of MB increased 7-time the risk to have a higher EPDS score at follow-up assessments (OR: 7.79; CI: 6.88-8.70, p <0.000). This risk is almost four times higher 1 months after the delivery (OR: 4.66; CI: 2.54-6.75, p < 0.000), almost three times higher after 3 months (OR: 2.98; CI: 0.50-5.46, p < 0.01) and almost six times higher after 12 months (OR: 5.88; CI: 3.20-8.54, p < 0.000). Conclusions: Although MB was a self-limiting condition in the majority of cases, depressive symptoms arose quite often immediately after the childbirth. Professionals should be trained to monitor symptoms of MB and its transition toward a depressive episode.