App-based interventions for the prevention of postpartum depression: a systematic review and meta-analysis

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Methods We conducted an article search on the electronic databases of the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE via Ovid, Scopus, PsycINFO, CINAHL, and ProQuest Dissertations & Theses A&I on March 26th, 2020. We also searched the International Clinical Trials Platform Search Portal (ICTRP), and Clinical Trials. Results We identified 1581 references, and seven studies were ultimately included in this review. Only one study has assessed the onset of postpartum depression as an outcome. This indicated that after the app intervention, the proportion of women who developed postpartum depression was significantly lower in the intervention group than in the control group (6 weeks postpartum risk ratio (RR)0.79, 95% confidence intervals (95%CI)0.58–1.06; 3 months postpartum RR0.74, 95%CI0.50–1.09; 6 months postpartum RR0.73, 95%CI0.49–1.11 RR0.73, 95%CI0.49–1.11). We performed a meta-analysis of Edinburgh Postnatal Depression Scale (EPDS) scores at each time point. During the immediate (0–8 weeks postpartum) period, the intervention group had significantly lower EPDS scores than the control group (mean differences (MD) -0.59; 95%CI -1.00 to -0.18; P = 0.005). In the short term (9–16 weeks postpartum), there was no significant difference between the intervention and control groups in terms of EPDS score (MD -0.32; 95%CI -10.82 to 1.17; P = 0.20). Limitations: Only one randomized controlled trial (RCT) measured the onset of postpartum depression as an outcome; we performed a meta-analysis only on the EPDS scores. Additionally, there was a high risk of incomplete outcome data due to the high attrition rates in the study. Conclusion The apps, including an automated component for the prevention of postpartum depression, improved the EPDS score; furthermore, they may prevent postpartum depression. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Postpartum depression is defined as depression that develops within the first year postpartum in clinical practice and research [ 1 ]. About 12% of mothers who give birth experience postpartum depression [ 1 , 2 ]. There are many causes of perinatal deaths, but 5–20% of these deaths are due to suicide caused by postpartum depression [ 3 – 5 ]. Postpartum depression seriously effects the development of mothers and children [ 6 ]. Thus, prevention of postpartum depression is essential, but postpartum women are less likely to access prevention and treatment of postpartum depression due to various barriers [ 7 , 8 ]. There are various physical and mental barriers, including the lack of time, stigma, and childcare issues. Treatments without face-to-face contact have been developed to overcome these barriers, such as telemedicine and the use of short message services (SMS), phone calls, and video calls using smartphones. In recent years, digital health technologies have made remarkable progress, and fully automated apps for the treatment and prevention of mental illnesses have emerged. App interventions are effective in improving depressive symptoms and generalised anxiety in the general population [ 9 ]. Furthermore, the NICE recommends computerised cognitive behavioural therapy (CCBT) for mild to moderate depression in the general population. The leading commercial apps, Headspace, Youper, and Wysa, treat depression in the general population [ 10 ]. There are some previous systematic reviews (SR) on treating postpartum depression. Therapist interventions via the Internet significantly improve the symptoms of postpartum depression [ 11 ]. mHealth education significantly improved the Edinburgh Postnatal Depression Scale (EPDS) scores after the intervention [ 12 ]. mHealth education is an educational intervention that provides specific health information, social support, and advice through mobile technology such as SMS, phone calls, and video calls using smartphones and tablets [ 13 ]. Tsai et al. published an SR on treating postpartum depression with a fully automated app but concluded that this did not improve postpartum depression symptoms [ 14 ]. They also evaluated the quality of the apps and stated that a few were of high quality. There has been an SR on treating postpartum depression with a fully automated app [ 14 ], but no SR on prevention has been conducted. Annette Bauer et al. indicated that the present value of total lifetime costs of perinatal depression was £75,728 per woman in the UK [ 15 ]; hence, prevention is more beneficial than treatment after getting sick. Therefore, we conducted an SR focusing on whether apps including an automated component are effective in preventing postpartum depression. Methods We conducted a systematic review and meta-analysis according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines [ 16 ]. Inclusion Criteria We included all RCTs that evaluated the application, including an automated component aimed at preventing postpartum depression by providing psychosocial interventions. An automated component indicates that the app itself has a function aimed at preventing postpartum depression. In this study, we incorporated a combination of automated apps and human interventions (e.g. phone calls and other interventions outside the app). Psychosocial interventions are non-pharmacological interventions that focus on psychological and social aspects, such as counselling, educational programs, social support, cognitive-behavioural therapy, motivational interviewing, and supportive care. We included women from pregnancy to 1 year postpartum and excluded those already diagnosed with depression, taking antidepressants, or suffering from psychiatric disorders. Quasi-randomised trials were excluded. Search Strategy We conducted an article search of the electronic databases of the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE via Ovid, Scopus, PsycINFO, CINAHL, and ProQuest Dissertations & Theses A&I on March 26th, 2020. We also searched the International Clinical Trials Platform Search Portal (ICTRP), and Clinical Trials. The following terms were used: [postpartum depression] [computer software, mobile applications, and computer-assisted therapy]. The search strategy and terms have been presented in Table 1. References cited in the identified RCTs cited references of the identified RCTs, and recent SRs were also searched. Table 1 indicates the search strategies and terms of each electronic database. The electronic databases are the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE via Ovid, Scopus, PsycINFO, CINAHL, ProQuest Dissertations & Theses A&I, the International Clinical Trials Platform Search Portal (ICTRP), and Clinical Trials. Study Selection, Data Extraction, and Risk of Bias Assessment Two independent reviewers screened the titles and abstracts of the identified studies (AS, KJ, TA, YO, and YM), after removing duplicates. All selected studies were subjected to a full-text review and evaluated for meeting the inclusion criteria by two reviewers (KK and YM). In cases of disagreement, the two reviewers discussed and resolved the issues. Disagreements were resolved via discussion with a third reviewer (YO). In these cases, we could not decide whether the study should be included after the full-text review; we contacted the original author. Two reviewers independently assessed the quality of each study using the Cochrane Risk of Bias (ROB) for RCTs. We evaluated random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessments, incomplete outcome data, and selective outcome reporting to rate studies as ‘low risk’, ‘high risk’, or ‘unclear’. Disagreements between the two reviewers were resolved through discussions. Discussions were also held with a third reviewer, as needed. Types of Outcome Measures The primary outcome was postpartum depression onset. Each study defined the onset of postpartum depression by using a clinical diagnostic interview or screening tool. A clinical diagnostic interview for depression is an evaluation conducted by a trained examiner based on an official diagnostic system, such as the Diagnostic and Statistical Manual of Mental Disorders fifth edition (DSM-5), the International Classification of Disease (ICD-10), or other standard methods such as the Research Diagnostic Criteria (RDC) [ 17 ]. For example, screening tools include the EPDS [ 18 ]. Secondary outcomes were scores on the EPDS, the Patient Health Questionnaire-9 (PHQ-9), other depression-related measures (e.g. the Centre for Epidemiologic Studies Depression Scale (CES-D)), and the onset of anxiety and scale scores. Outcomes were assessed in the immediate term (0–8 weeks postpartum), short-term (9–16 weeks postpartum), intermediate-term (17–24 weeks postpartum), and long-term (> 25 weeks postpartum). Data Synthesis and Statistical Analysis A random-effects model for the meta-analyses [ 19 ] was used, as there was clinical heterogeneity in the interventions in this review. Binary variables were calculated using risk ratios (RR) with 95% confidence intervals (95% CIs). Continuous variables were calculated using standardised mean differences (SMDs) with 95%CIs. We analysed these data based on intention-to-treat (ITT). When ITT data were available, they were prioritised over per-protocol or complete data. The missing data were queried by the original authors. Heterogeneity was visually assessed using forest plots. I-square statistics [ 19 ], chi-squared statistics, and their P values were used to measure statistical heterogeneity. Data analysis was performed using Review Manager version 5.4 (Nordic Cochrane Center, Cochrane Collaboration; Copenhagen, Denmark; http://ims.cochrane.org/revman ). Results Figure 1 shows the flow diagram of the study selection process. We conducted an article search on March 26, 2020. We identified 1581 references and removed 282 duplicates. The titles and abstracts were evaluated, and 135 references were included in the full-text review. A total of 123 references were excluded because they did not meet the eligibility criteria, five were ongoing studies, and seven were ultimately included in this review. Characteristics of Included Studies Table 2 presents the characteristics of the studies included. All studies were published after 2015. In five studies, the intervention started prenatally [ 20 – 23 ] and in two studies, the intervention started postpartum [ 24 , 25 ]. Two studies had participants as married couples [ 20 , 24 ]. In one study, only the results for women were available [ 20 ]. Three studies provided the app interventions based on cognitive behavioral therapy [ 21 , 23 , 25 ]. One study used an intervention with an app aimed at preventing perinatal depression [ 26 ]. The app was a fully automated Internet-based program with 44 sessions for preventive intervention for perinatal depressive symptoms. Two studies were interventions in which the app provided educational content like psychoeducation, newborn care, etc. [ 22 , 24 ]. One study was an intervention that provided educational sessions via phone and follow-up sessions via the app [ 20 ]. Four studies provided fully automated apps [ 21 , 23 , 25 , 26 ]. Three studies included an automated app and human intervention (e.g., by phone outside the app) [ 20 , 22 , 24 ]. Of these, the intervention by Shorey et al. allowed non-interactive communication with a healthcare professional, in addition to the automated app [ 24 ]. Another intervention by Shorey et al. had a telephone education session followed by an automated app education session [ 20 ]. Chan et al.’s intervention had an automated app plus an interactive Q and A platform available [ 22 ]. One study has assessed the development of postpartum depression [ 26 ]. Seven studies assessed the Edinburgh Postpartum Depression Scale (EPDS) [ 20 – 26 ]. One study evaluated the Centre for Epidemiologic Studies Depression Scale (CES-D) and Major Depressive Episode (MDE) [ 23 ]. Table 2 indicates these items of each RCT. The items are the country, the number of people included, mean age, the timing of intervention, the format of intervention, the content of interventions and controls, treatment frequency, the timing of follow-up from baseline, the complete rate in the intervention group, and the main outcome. Risk of Bias in the Included Studies The risk of bias graph is shown in Fig. 2 , and the risk of bias summary is shown in Fig. 3 . Random sequence allocation was judged to have a low risk of bias in all studies. Allocation concealment was considered at a low risk of bias in four studies and unclear in three studies. App-based psychosocial interventions are difficult to blind, and all studies rated the risk of bias in blinding participants and personnel high. Blinding of outcome assessment was judged to be at high risk of bias in two studies, unclear in two studies, and low in three studies. Incomplete outcome data were at high risk of bias in five studies and low risk of bias in two studies. Selective reporting bias was judged to be at high risk of bias in two studies, unclear in two studies, and low in three studies. Other biases were at high risk of bias in the study and low risk of bias in the other six studies. Effects of Interventions Primary Outcomes Only one study assessed the onset of postpartum depression as an outcome [ 26 ]. Therefore, a meta-analysis could not be performed on the primary outcomes. Haga et al. evaluated EPDS at 21–25 weeks gestation as a baseline, and at 38 weeks gestation, 6 weeks postpartum (immediate), 3 months postpartum (short-term), and 6 months postpartum (intermediate) [ 26 ]. They defined an EPDS score of 10 or more as the onset of postpartum depression. After the app intervention, the proportion of women who developed postpartum depression was lower in the intervention group than in the control group, but there was no significant difference between the two groups (6 weeks postpartum RR0.79, 95%CI0.58–1.06; 3 months postpartum RR0.74, 95%CI0.50–1.09; 6 months postpartum RR0.73, 95%CI0.49–1.11 RR0.73, 95%CI0.49–1.11). Secondary Outcomes Seven studies measured EPDS scores. Three studies measured the EPDS score in the immediate (0–8 weeks postpartum) and two in the short-term (9–16 weeks postpartum). We performed a meta-analysis of EPDS scores at each time point. During the immediate (0–8 weeks postpartum) period, the intervention group had significantly lower EPDS scores than the control group (MD -0.59; 95%CI -1.00 to -0.18; P = 0.005; Fig. 4 ). There was no evidence of heterogeneity in the effects (I2 = 0%, Chi2 = 0.03, P = 0.99). In the short term (9–16 weeks postpartum), there was no significant difference between the intervention and control groups in terms of EPDS score (MD -0.32; 95%CI -10.82 to 1.17; P = 0.20; Fig. 5 ). There was no evidence of heterogeneity in the effects (I2 = 0%, Chi2 = 0.43, P = 0.51). Barrera et al. measured the EPDS score and calculated the hazard ratio (HR) using EPDS > 10 as the cut-off [ 23 ]. They did not specify when the EPDS was measured, and the results were not available for EPDS as a continuous variable. We did not include their study in the meta-analysis. There was no statistically significant difference in the incidence of postpartum depression (EPDS score ≥ 10) between the intervention and comparison groups (HR0. 598; 95%CI0.339 to 1.022; P = 0.061). Shorey et al. included couples as the participants. On enquiry, EPDS scores by sex were not recorded. We did not include this study in our meta-analysis [ 24 ]. There were no statistically significant differences between the intervention and comparison group (MD, 0.33; 95%CI -1.21 to 0.53; P = 0.45). We did not include Shorey et al. in the meta-analysis because of the high heterogeneity [ 20 ]. The intervention group had a significantly better outcome score for postnatal EPDS than did the control group (MD, 0.91; 95%CI -1.34 to -0.49; P < 0.001). PHQ-9 was not measured in either study. The onset of Anxiety Disorders was not measured in either study. The Hospital Anxiety and Depression Scale (HADS) [ 25 ], State-Trait Anxiety Inventory (STAI) [ 20 ], and Depression Anxiety Stress Scale) [ 22 ] were used as indicators of anxiety. Fonseca et al. found no statistically significant difference in HADS between the intervention and control groups at the time of evaluation (t=-0.12, p = .903, d = 0.002) ( fixed effects with an autoregressive covariance matrix) [ 25 ]. Chan et al. found that anxiety items on the DASS were not significantly different between the intervention and control groups (MD0.01; 95%CI -0.30 to 0.50; P = 0.94) (LOCF: the last observation carried forward method) [ 22 ]. Discussion This systematic review and meta-analysis examined the effectiveness of apps, including automated components, in preventing postpartum depression. We included seven RCTs in the final analysis. One study measured the development of postpartum depression as its primary outcome. This RCT defined an EPDS score of 10 or higher as the onset of postpartum depression, and the app intervention lowered the proportion of women who developed postpartum depression [ 26 ]. We conducted a meta-analysis of EPDS scores. The meta-analysis showed significantly lower EPDS scores in the Immediate (0–8 weeks postpartum) period, but no significant difference in EPDS scores in the short-term (9–16 weeks postpartum) period. The difference from previous studies was in the purpose of the intervention in postpartum depression prevention. Tsai et al. conducted a systematic review and meta-analysis of the treatment of postpartum depression using a fully automated app [ 14 ]. A systematic review showed that apps are ineffective in treating postpartum depression. However, there was high heterogeneity in the incorporated studies; therefore, the results must be carefully interpreted. Our systematic review also differed from previous studies in that the intervention method was an app with an automated component. In a previous systematic review and meta-analysis by Mu et al., the use of the internet to prevent postpartum depression significantly improved the prevalence of postpartum depression [ 11 ]. mHealth education via online or apps significantly improved EPDS scores [ 12 ]. This systematic review showed that interventions using apps with automated components are effective in preventing postpartum depression. This indicates that pregnant and postpartum women may be able to voluntarily engage in the prevention of postpartum depression using a smartphone or tablet device, rather than face-to-face. The recent coronavirus disease-19 (COVID-19) pandemic has had various impacts on pregnant and postpartum women, including fear of COVID-19, fear of infection, lifestyle changes due to lockdown, and social isolation. The decrease in physical activity during the COVID-19 pandemic has increased postpartum depression [ 27 ]. Indeed, the COVID-19 pandemic increased the prevalence of postpartum depression to 34% (95% CI 24–46%) [ 28 ], although the prevalence of postpartum depression was 20.8% (95% CI 17.9–33.8%) in middle-income countries and 25.8% (95% CI 18.4–23.1%) in low-income countries until 2017 [ 29 ]. The COVID-19 pandemic has forced us to limit face-to-face interventions for postpartum depression despite the increasing demand for such interventions. This is a barrier for interventions to prevent postpartum depression, but app-based interventions that include an automated component can be an intervention method that can overcome this barrier. Pregnant and postpartum women can use their smartphones or tablets to voluntarily engage in postpartum depression prevention, rather than face-to-face. During the COVID-19 pandemic, postpartum depression prevention interventions with apps that include an automated component will receive more attention and be utilised. This study had some limitations. Only one RCT measured the onset of postpartum depression as an outcome [ 26 ]. Therefore, we performed a meta-analysis only on EPDS scores. Additionally, there was a high risk of incomplete outcome data due to the high attrition rates in the study. Conclusions This study presents the results of current RCTs on interventions with apps, including an automated component for the prevention of postpartum depression that has been conducted. The apps, including an automated component for the prevention of postpartum depression, improved the EPDS score; furthermore, they may prevent postpartum depression. Additional RCTs like reducing attrition rates and setting the primary outcome onset of postpartum depression are needed. Abbreviations 95%CI: 95% Confidence Intervals CCBT: Computerized Cognitive Behavioral Therapy CENTRAL: the Cochrane Central Register of Controlled Trials CES-D: the Center for Epidemiologic Studies Depression Scale COVID-19: coronavirus disease DASS: the Depression Anxiety Stress Scale DSM-5: the Diagnostic and Statistical Manual of Mental Disorders fifth edition EPDS: the Edinburgh Postnatal Depression Scale HADS: the Hospital Anxiety and Depression Scale HR: Hazard Ratio ICD-10: the International Classification of Disease ICTRP: International Clinical Trials Platform Search Portal ITT: Intention to Treat LOCF: the Lost Observation Carried Forward method MDE: Major Depressive Episode PHQ-9: the Patient Health Questionnaire-9 PRISMA: the Preferred Reporting Items for Systematic Reviews and Meta-Analysis RCT: Randomized Controlled Trial RDC: Research Diagnostic Criteria ROB: Risk of Bias RR: Risk Ration SMD: Standardized Mean Difference SMS: Short Message Service SR: Systematic Review STAI: State-Trait Anxiety Inventory Declarations Ethics approval and consent to participate: Not applicable Consent for publication: Not applicable Availability of data and materials: All data analyzed in this study are included within the article and a list of references. Authors' contributions: YM designed the study; screened titles and abstracts; conducted a full-text review; assessed the quality of each study; interpreted the data and review the manuscript. YO designed the study; screened titles and abstracts; conducted a full-text review; assessed the quality of each study; interpreted the data and review the manuscript. AS screened titles and abstracts and reviewed the manuscript. KK conducted a full-text review; assessed the quality of each study and reviewed the manuscript. KJ screened titles and abstracts. TA designed the study; interpreted the data and reviewed the manuscript. All authors read and approved the final manuscript. Acknowledgements: We would like to thank Editage (www.editage.com) for English language editing. Funding: Not applicable Competing interests: The authors have no competing interests to disclose. Author’s Information: YM is a family physician at Hamamatsu Satocho Clinic. YO is an associate professor in the Department of Healthcare Epidemiology, School of Public Health, Kyoto University. AS is a medical director at the Department of Obstetrics Gynecology, Yodogawa Christian Hospital. KK is a medical director at the Department of Gynecology, Nagano Municipal Hospital. KJ is a medical director at the Department of Obstetrics & Gynecology, Kikugawa General Hospital. TA is a lecturer in the Division of Clinical Epidemiology, Research Center for Medical Sciences, The Jikei University School of Medicine and belongs to the Section of Clinical Epidemiology, Department of Community Medicine, Graduate School of Medicine, Kyoto University References Stewart DE, Vigod SN. Postpartum Depression: Pathophysiology, Treatment, and Emerging Therapeutics. Annu Rev Med. 2019;70:183-96. Shorey S, Chee CYI, Ng ED, Chan YH, Tam WWS, Chong YS. Prevalence and incidence of postpartum depression among healthy mothers: A systematic review and meta-analysis. 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Supplementary Files Table1.xlsx Table2.xlsx Cite Share Download PDF Status: Published Journal Publication published 14 Jun, 2023 Read the published version in BMC Pregnancy and Childbirth → Version 1 posted Editorial decision: Major revision 10 Mar, 2023 Reviews received at journal 17 Feb, 2023 Reviewers agreed at journal 04 Feb, 2023 Reviews received at journal 30 Jan, 2023 Reviewers agreed at journal 30 Jan, 2023 Reviewers invited by journal 28 Jan, 2023 Editor assigned by journal 28 Jan, 2023 Editor invited by journal 16 Jan, 2023 Submission checks completed at journal 16 Jan, 2023 First submitted to journal 31 Dec, 2022 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2431187","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":167962459,"identity":"1bfafcd9-504d-4dc1-aaa6-2155046bd567","order_by":0,"name":"Yumika Miura","email":"","orcid":"","institution":"Hamamatsu Satocho Clinic","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yumika","middleName":"","lastName":"Miura","suffix":""},{"id":167962461,"identity":"d082fcec-99bf-4a20-8d1d-79247d147399","order_by":1,"name":"Yusuke Ogawa","email":"","orcid":"","institution":"Kyoto 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Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ken","middleName":"","lastName":"Joko","suffix":""},{"id":167962469,"identity":"27a56614-9db8-41fe-b073-be431afc1830","order_by":5,"name":"Takuya Aoki","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyklEQVRIiWNgGAWjYHACZoaECjYeCQbGBgiPEOABazlDshbGNgYGCaJdZc9++LDBw3l8MpLtzQ0MP2oY2M0J2sKTlpyQuI2NR5rnYANjzzEGZssGgg7LMT4A0iInkdjAwNvAwGxwgJAW/jdALXOAWuQfNjD+JUqLRI5xQmID0GESjA3MxNly41myQcIxNh7JnsSGwzLHJAj7hb0/+bDkj5pj9hLHjz98+KbGJplgiEHBMTAJdJJEsgGRWmrgLDtitYyCUTAKRsHIAQCqRTYv4h7GjAAAAABJRU5ErkJggg==","orcid":"","institution":"Jikei University School of Medicine","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Takuya","middleName":"","lastName":"Aoki","suffix":""}],"badges":[],"createdAt":"2022-12-31 11:59:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2431187/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2431187/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12884-023-05749-5","type":"published","date":"2023-06-14T21:12:58+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":31694067,"identity":"b279826f-c785-4b45-ac32-e344e49b90a1","added_by":"auto","created_at":"2023-01-17 16:03:12","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":22838,"visible":true,"origin":"","legend":"\u003cp\u003eStudy flow diagram\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-2431187/v1/6ee5540b3887abc711252f91.png"},{"id":31694066,"identity":"d9b859cf-3337-459c-ae3d-6fb160581641","added_by":"auto","created_at":"2023-01-17 16:03:12","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":28064,"visible":true,"origin":"","legend":"\u003cp\u003eRisk of bias graph.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-2431187/v1/7fdf69f0004ef1580a324436.png"},{"id":31694072,"identity":"921e7da2-abe4-482b-acaa-d00a76e99dff","added_by":"auto","created_at":"2023-01-17 16:03:12","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":31982,"visible":true,"origin":"","legend":"\u003cp\u003eRisk of bias summary.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-2431187/v1/906a686aad7469c6acd57557.png"},{"id":31694068,"identity":"90c18b65-6e01-4f3e-8ab9-b5d83d933fdd","added_by":"auto","created_at":"2023-01-17 16:03:12","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":17931,"visible":true,"origin":"","legend":"\u003cp\u003eEffectiveness for EPDS score in the immediate term.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-2431187/v1/963336884fe365bf09c7521d.png"},{"id":31694069,"identity":"a6262287-013f-4e7a-af22-8f5a9899ebde","added_by":"auto","created_at":"2023-01-17 16:03:12","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":15888,"visible":true,"origin":"","legend":"\u003cp\u003eEffectiveness for EPDS score in the short term\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-2431187/v1/026fefae78c2eb44451ccbb7.png"},{"id":44733114,"identity":"e1ee80e3-82e0-470a-aae9-22c6d830d3a5","added_by":"auto","created_at":"2023-10-16 22:04:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":798722,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2431187/v1/ca5a5c53-4b73-4289-99a6-49a2359f5cf6.pdf"},{"id":31694070,"identity":"f6f2f4c4-2437-40d1-9c8c-7cd9b701e18a","added_by":"auto","created_at":"2023-01-17 16:03:12","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":14783,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-2431187/v1/515546e0491aa5b1d285b884.xlsx"},{"id":31695046,"identity":"79e53829-2862-4757-8a49-12bd04c24fce","added_by":"auto","created_at":"2023-01-17 16:11:12","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":13794,"visible":true,"origin":"","legend":"","description":"","filename":"Table2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-2431187/v1/f326f7a7a9215d65f5740bfa.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"App-based interventions for the prevention of postpartum depression: a systematic review and meta-analysis","fulltext":[{"header":"Background","content":"\u003cp\u003ePostpartum depression is defined as depression that develops within the first year postpartum in clinical practice and research [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. About 12% of mothers who give birth experience postpartum depression [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. There are many causes of perinatal deaths, but 5\u0026ndash;20% of these deaths are due to suicide caused by postpartum depression [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Postpartum depression seriously effects the development of mothers and children [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Thus, prevention of postpartum depression is essential, but postpartum women are less likely to access prevention and treatment of postpartum depression due to various barriers [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. There are various physical and mental barriers, including the lack of time, stigma, and childcare issues.\u003c/p\u003e \u003cp\u003eTreatments without face-to-face contact have been developed to overcome these barriers, such as telemedicine and the use of short message services (SMS), phone calls, and video calls using smartphones. In recent years, digital health technologies have made remarkable progress, and fully automated apps for the treatment and prevention of mental illnesses have emerged. App interventions are effective in improving depressive symptoms and generalised anxiety in the general population [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Furthermore, the NICE recommends computerised cognitive behavioural therapy (CCBT) for mild to moderate depression in the general population. The leading commercial apps, Headspace, Youper, and Wysa, treat depression in the general population [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere are some previous systematic reviews (SR) on treating postpartum depression. Therapist interventions via the Internet significantly improve the symptoms of postpartum depression [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. mHealth education significantly improved the Edinburgh Postnatal Depression Scale (EPDS) scores after the intervention [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. mHealth education is an educational intervention that provides specific health information, social support, and advice through mobile technology such as SMS, phone calls, and video calls using smartphones and tablets [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Tsai et al. published an SR on treating postpartum depression with a fully automated app but concluded that this did not improve postpartum depression symptoms [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. They also evaluated the quality of the apps and stated that a few were of high quality.\u003c/p\u003e \u003cp\u003eThere has been an SR on treating postpartum depression with a fully automated app [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], but no SR on prevention has been conducted. Annette Bauer et al. indicated that the present value of total lifetime costs of perinatal depression was \u0026pound;75,728 per woman in the UK [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]; hence, prevention is more beneficial than treatment after getting sick. Therefore, we conducted an SR focusing on whether apps including an automated component are effective in preventing postpartum depression.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eWe conducted a systematic review and meta-analysis according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines [\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\n\u003cdiv class=\"Section2\" id=\"Sec3\"\u003e\n \u003ch2\u003eInclusion Criteria\u003c/h2\u003e\n \u003cp\u003eWe included all RCTs that evaluated the application, including an automated component aimed at preventing postpartum depression by providing psychosocial interventions. An automated component indicates that the app itself has a function aimed at preventing postpartum depression. In this study, we incorporated a combination of automated apps and human interventions (e.g. phone calls and other interventions outside the app). Psychosocial interventions are non-pharmacological interventions that focus on psychological and social aspects, such as counselling, educational programs, social support, cognitive-behavioural therapy, motivational interviewing, and supportive care. We included women from pregnancy to 1 year postpartum and excluded those already diagnosed with depression, taking antidepressants, or suffering from psychiatric disorders. Quasi-randomised trials were excluded.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec4\"\u003e\n \u003ch2\u003eSearch Strategy\u003c/h2\u003e\n \u003cp\u003eWe conducted an article search of the electronic databases of the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE via Ovid, Scopus, PsycINFO, CINAHL, and ProQuest Dissertations \u0026amp; Theses A\u0026amp;I on March 26th, 2020. We also searched the International Clinical Trials Platform Search Portal (ICTRP), and Clinical Trials. The following terms were used: [postpartum depression] [computer software, mobile applications, and computer-assisted therapy]. The search strategy and terms have been presented in Table\u0026nbsp;1.\u003c/p\u003e\n \u003cp\u003eReferences cited in the identified RCTs cited references of the identified RCTs, and recent SRs were also searched.\u003c/p\u003e\n \u003cp\u003eTable 1 indicates the search strategies and terms of each electronic database. The electronic databases are the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE via Ovid, Scopus, PsycINFO, CINAHL, ProQuest Dissertations \u0026amp; Theses A\u0026amp;I, the International Clinical Trials Platform Search Portal (ICTRP), and Clinical Trials.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec5\"\u003e\n \u003ch2\u003eStudy Selection, Data Extraction, and Risk of Bias Assessment\u003c/h2\u003e\n \u003cp\u003eTwo independent reviewers screened the titles and abstracts of the identified studies (AS, KJ, TA, YO, and YM), after removing duplicates. All selected studies were subjected to a full-text review and evaluated for meeting the inclusion criteria by two reviewers (KK and YM). In cases of disagreement, the two reviewers discussed and resolved the issues. Disagreements were resolved via discussion with a third reviewer (YO). In these cases, we could not decide whether the study should be included after the full-text review; we contacted the original author.\u003c/p\u003e\n \u003cp\u003eTwo reviewers independently assessed the quality of each study using the Cochrane Risk of Bias (ROB) for RCTs. We evaluated random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessments, incomplete outcome data, and selective outcome reporting to rate studies as \u0026lsquo;low risk\u0026rsquo;, \u0026lsquo;high risk\u0026rsquo;, or \u0026lsquo;unclear\u0026rsquo;. Disagreements between the two reviewers were resolved through discussions. Discussions were also held with a third reviewer, as needed.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec6\"\u003e\n \u003ch2\u003eTypes of Outcome Measures\u003c/h2\u003e\n \u003cp\u003eThe primary outcome was postpartum depression onset. Each study defined the onset of postpartum depression by using a clinical diagnostic interview or screening tool. A clinical diagnostic interview for depression is an evaluation conducted by a trained examiner based on an official diagnostic system, such as the Diagnostic and Statistical Manual of Mental Disorders fifth edition (DSM-5), the International Classification of Disease (ICD-10), or other standard methods such as the Research Diagnostic Criteria (RDC) [\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e]. For example, screening tools include the EPDS [\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eSecondary outcomes were scores on the EPDS, the Patient Health Questionnaire-9 (PHQ-9), other depression-related measures (e.g. the Centre for Epidemiologic Studies Depression Scale (CES-D)), and the onset of anxiety and scale scores. Outcomes were assessed in the immediate term (0\u0026ndash;8 weeks postpartum), short-term (9\u0026ndash;16 weeks postpartum), intermediate-term (17\u0026ndash;24 weeks postpartum), and long-term (\u0026gt;\u0026thinsp;25 weeks postpartum).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec7\"\u003e\n \u003ch2\u003eData Synthesis and Statistical Analysis\u003c/h2\u003e\n \u003cp\u003eA random-effects model for the meta-analyses [\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e] was used, as there was clinical heterogeneity in the interventions in this review. Binary variables were calculated using risk ratios (RR) with 95% confidence intervals (95% CIs). Continuous variables were calculated using standardised mean differences (SMDs) with 95%CIs.\u003c/p\u003e\n \u003cp\u003eWe analysed these data based on intention-to-treat (ITT). When ITT data were available, they were prioritised over per-protocol or complete data. The missing data were queried by the original authors.\u003c/p\u003e\n \u003cp\u003eHeterogeneity was visually assessed using forest plots. I-square statistics [\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e], chi-squared statistics, and their P values were used to measure statistical heterogeneity. Data analysis was performed using Review Manager version 5.4 (Nordic Cochrane Center, Cochrane Collaboration; Copenhagen, Denmark; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://ims.cochrane.org/revman\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e shows the flow diagram of the study selection process. We conducted an article search on March 26, 2020. We identified 1581 references and removed 282 duplicates. The titles and abstracts were evaluated, and 135 references were included in the full-text review. A total of 123 references were excluded because they did not meet the eligibility criteria, five were ongoing studies, and seven were ultimately included in this review.\u003c/p\u003e\n\u003cdiv class=\"Section2\" id=\"Sec9\"\u003e\n \u003ch2\u003eCharacteristics of Included Studies\u003c/h2\u003e\n \u003cp\u003eTable\u0026nbsp;2 presents the characteristics of the studies included. All studies were published after 2015. In five studies, the intervention started prenatally [\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e] and in two studies, the intervention started postpartum [\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e]. Two studies had participants as married couples [\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e]. In one study, only the results for women were available [\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eThree studies provided the app interventions based on cognitive behavioral therapy [\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e]. One study used an intervention with an app aimed at preventing perinatal depression [\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e]. The app was a fully automated Internet-based program with 44 sessions for preventive intervention for perinatal depressive symptoms. Two studies were interventions in which the app provided educational content like psychoeducation, newborn care, etc. [\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e]. One study was an intervention that provided educational sessions via phone and follow-up sessions via the app [\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eFour studies provided fully automated apps [\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e]. Three studies included an automated app and human intervention (e.g., by phone outside the app) [\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e]. Of these, the intervention by Shorey et al. allowed non-interactive communication with a healthcare professional, in addition to the automated app [\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e]. Another intervention by Shorey et al. had a telephone education session followed by an automated app education session [\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e]. Chan et al.\u0026rsquo;s intervention had an automated app plus an interactive Q and A platform available [\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eOne study has assessed the development of postpartum depression [\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e]. Seven studies assessed the Edinburgh Postpartum Depression Scale (EPDS) [\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e]. One study evaluated the Centre for Epidemiologic Studies Depression Scale (CES-D) and Major Depressive Episode (MDE) [\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eTable 2 indicates these items of each RCT. The items are the country, the number of people included, mean age, the timing of intervention, the format of intervention, the content of interventions and controls, treatment frequency, the timing of follow-up from baseline, the complete rate in the intervention group, and the main outcome.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec10\"\u003e\n \u003ch2\u003eRisk of Bias in the Included Studies\u003c/h2\u003e\n \u003cp\u003eThe risk of bias graph is shown in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, and the risk of bias summary is shown in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. Random sequence allocation was judged to have a low risk of bias in all studies. Allocation concealment was considered at a low risk of bias in four studies and unclear in three studies. App-based psychosocial interventions are difficult to blind, and all studies rated the risk of bias in blinding participants and personnel high. Blinding of outcome assessment was judged to be at high risk of bias in two studies, unclear in two studies, and low in three studies. Incomplete outcome data were at high risk of bias in five studies and low risk of bias in two studies. Selective reporting bias was judged to be at high risk of bias in two studies, unclear in two studies, and low in three studies. Other biases were at high risk of bias in the study and low risk of bias in the other six studies.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec11\"\u003e\n \u003ch2\u003eEffects of Interventions\u003c/h2\u003e\n \u003cdiv class=\"Section3\" id=\"Sec12\"\u003e\n \u003ch2\u003ePrimary Outcomes\u003c/h2\u003e\n \u003cp\u003eOnly one study assessed the onset of postpartum depression as an outcome [\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e]. Therefore, a meta-analysis could not be performed on the primary outcomes.\u003c/p\u003e\n \u003cp\u003eHaga et al. evaluated EPDS at 21\u0026ndash;25 weeks gestation as a baseline, and at 38 weeks gestation, 6 weeks postpartum (immediate), 3 months postpartum (short-term), and 6 months postpartum (intermediate) [\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e]. They defined an EPDS score of 10 or more as the onset of postpartum depression. After the app intervention, the proportion of women who developed postpartum depression was lower in the intervention group than in the control group, but there was no significant difference between the two groups (6 weeks postpartum RR0.79, 95%CI0.58\u0026ndash;1.06; 3 months postpartum RR0.74, 95%CI0.50\u0026ndash;1.09; 6 months postpartum RR0.73, 95%CI0.49\u0026ndash;1.11 RR0.73, 95%CI0.49\u0026ndash;1.11).\u003c/p\u003e\n \u003cp\u003e\u003cspan class=\"Underline\" name=\"Emphasis\" type=\"Underline\"\u003eSecondary Outcomes\u003c/span\u003e\u003c/p\u003e\n \u003cp\u003eSeven studies measured EPDS scores. Three studies measured the EPDS score in the immediate (0\u0026ndash;8 weeks postpartum) and two in the short-term (9\u0026ndash;16 weeks postpartum). We performed a meta-analysis of EPDS scores at each time point.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eDuring the immediate (0\u0026ndash;8 weeks postpartum) period, the intervention group had significantly lower EPDS scores than the control group (MD -0.59; 95%CI -1.00 to -0.18; P\u0026thinsp;=\u0026thinsp;0.005; Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). There was no evidence of heterogeneity in the effects (I2\u0026thinsp;=\u0026thinsp;0%, Chi2\u0026thinsp;=\u0026thinsp;0.03, P\u0026thinsp;=\u0026thinsp;0.99).\u003c/p\u003e\n \u003cp\u003eIn the short term (9\u0026ndash;16 weeks postpartum), there was no significant difference between the intervention and control groups in terms of EPDS score (MD -0.32; 95%CI -10.82 to 1.17; P\u0026thinsp;=\u0026thinsp;0.20; Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). There was no evidence of heterogeneity in the effects (I2\u0026thinsp;=\u0026thinsp;0%, Chi2\u0026thinsp;=\u0026thinsp;0.43, P\u0026thinsp;=\u0026thinsp;0.51).\u003c/p\u003e\n \u003cp\u003eBarrera et al. measured the EPDS score and calculated the hazard ratio (HR) using EPDS\u0026thinsp;\u0026gt;\u0026thinsp;10 as the cut-off [\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e]. They did not specify when the EPDS was measured, and the results were not available for EPDS as a continuous variable. We did not include their study in the meta-analysis. There was no statistically significant difference in the incidence of postpartum depression (EPDS score\u0026thinsp;\u0026ge;\u0026thinsp;10) between the intervention and comparison groups (HR0. 598; 95%CI0.339 to 1.022; P\u0026thinsp;=\u0026thinsp;0.061).\u003c/p\u003e\n \u003cp\u003eShorey et al. included couples as the participants. On enquiry, EPDS scores by sex were not recorded. We did not include this study in our meta-analysis [\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e]. There were no statistically significant differences between the intervention and comparison group (MD, 0.33; 95%CI -1.21 to 0.53; P\u0026thinsp;=\u0026thinsp;0.45).\u003c/p\u003e\n \u003cp\u003eWe did not include Shorey et al. in the meta-analysis because of the high heterogeneity [\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e]. The intervention group had a significantly better outcome score for postnatal EPDS than did the control group (MD, 0.91; 95%CI -1.34 to -0.49; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n \u003cp\u003ePHQ-9 was not measured in either study.\u003c/p\u003e\n \u003cp\u003eThe onset of Anxiety Disorders was not measured in either study.\u003c/p\u003e\n \u003cp\u003eThe Hospital Anxiety and Depression Scale (HADS) [\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e], State-Trait Anxiety Inventory (STAI) [\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e], and Depression Anxiety Stress Scale) [\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e] were used as indicators of anxiety.\u003c/p\u003e\n \u003cp\u003eFonseca et al. found no statistically significant difference in HADS between the intervention and control groups at the time of evaluation (t=-0.12, p\u0026thinsp;=\u0026thinsp;.903, d\u0026thinsp;=\u0026thinsp;0.002) ( fixed effects with an autoregressive covariance matrix) [\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eChan et al. found that anxiety items on the DASS were not significantly different between the intervention and control groups (MD0.01; 95%CI -0.30 to 0.50; P\u0026thinsp;=\u0026thinsp;0.94) (LOCF: the last observation carried forward method) [\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis systematic review and meta-analysis examined the effectiveness of apps, including automated components, in preventing postpartum depression. We included seven RCTs in the final analysis.\u003c/p\u003e \u003cp\u003eOne study measured the development of postpartum depression as its primary outcome. This RCT defined an EPDS score of 10 or higher as the onset of postpartum depression, and the app intervention lowered the proportion of women who developed postpartum depression [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe conducted a meta-analysis of EPDS scores. The meta-analysis showed significantly lower EPDS scores in the Immediate (0\u0026ndash;8 weeks postpartum) period, but no significant difference in EPDS scores in the short-term (9\u0026ndash;16 weeks postpartum) period.\u003c/p\u003e \u003cp\u003eThe difference from previous studies was in the purpose of the intervention in postpartum depression prevention. Tsai et al. conducted a systematic review and meta-analysis of the treatment of postpartum depression using a fully automated app [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. A systematic review showed that apps are ineffective in treating postpartum depression. However, there was high heterogeneity in the incorporated studies; therefore, the results must be carefully interpreted. Our systematic review also differed from previous studies in that the intervention method was an app with an automated component. In a previous systematic review and meta-analysis by Mu et al., the use of the internet to prevent postpartum depression significantly improved the prevalence of postpartum depression [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. mHealth education via online or apps significantly improved EPDS scores [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis systematic review showed that interventions using apps with automated components are effective in preventing postpartum depression. This indicates that pregnant and postpartum women may be able to voluntarily engage in the prevention of postpartum depression using a smartphone or tablet device, rather than face-to-face.\u003c/p\u003e \u003cp\u003eThe recent coronavirus disease-19 (COVID-19) pandemic has had various impacts on pregnant and postpartum women, including fear of COVID-19, fear of infection, lifestyle changes due to lockdown, and social isolation. The decrease in physical activity during the COVID-19 pandemic has increased postpartum depression [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Indeed, the COVID-19 pandemic increased the prevalence of postpartum depression to 34% (95% CI 24\u0026ndash;46%) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], although the prevalence of postpartum depression was 20.8% (95% CI 17.9\u0026ndash;33.8%) in middle-income countries and 25.8% (95% CI 18.4\u0026ndash;23.1%) in low-income countries until 2017 [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The COVID-19 pandemic has forced us to limit face-to-face interventions for postpartum depression despite the increasing demand for such interventions. This is a barrier for interventions to prevent postpartum depression, but app-based interventions that include an automated component can be an intervention method that can overcome this barrier. Pregnant and postpartum women can use their smartphones or tablets to voluntarily engage in postpartum depression prevention, rather than face-to-face. During the COVID-19 pandemic, postpartum depression prevention interventions with apps that include an automated component will receive more attention and be utilised.\u003c/p\u003e \u003cp\u003eThis study had some limitations. Only one RCT measured the onset of postpartum depression as an outcome [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Therefore, we performed a meta-analysis only on EPDS scores. Additionally, there was a high risk of incomplete outcome data due to the high attrition rates in the study.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study presents the results of current RCTs on interventions with apps, including an automated component for the prevention of postpartum depression that has been conducted. The apps, including an automated component for the prevention of postpartum depression, improved the EPDS score; furthermore, they may prevent postpartum depression. Additional RCTs like reducing attrition rates and setting the primary outcome onset of postpartum depression are needed.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e95%CI: 95% Confidence Intervals\u003c/p\u003e\n\u003cp\u003eCCBT: Computerized Cognitive Behavioral Therapy\u003c/p\u003e\n\u003cp\u003eCENTRAL: the Cochrane Central Register of Controlled Trials\u003c/p\u003e\n\u003cp\u003eCES-D: the Center for Epidemiologic Studies Depression Scale\u003c/p\u003e\n\u003cp\u003eCOVID-19: coronavirus disease\u003c/p\u003e\n\u003cp\u003eDASS: the Depression Anxiety Stress Scale\u003c/p\u003e\n\u003cp\u003eDSM-5: the Diagnostic and Statistical Manual of Mental Disorders fifth edition\u003c/p\u003e\n\u003cp\u003eEPDS: the Edinburgh Postnatal Depression Scale\u003c/p\u003e\n\u003cp\u003eHADS: the Hospital Anxiety and Depression Scale\u003c/p\u003e\n\u003cp\u003eHR: Hazard Ratio\u003c/p\u003e\n\u003cp\u003eICD-10: the International Classification of Disease\u003c/p\u003e\n\u003cp\u003eICTRP: International Clinical Trials Platform Search Portal\u003c/p\u003e\n\u003cp\u003eITT: Intention to Treat\u003c/p\u003e\n\u003cp\u003eLOCF: the Lost Observation Carried Forward method\u003c/p\u003e\n\u003cp\u003eMDE: Major Depressive Episode\u003c/p\u003e\n\u003cp\u003ePHQ-9: the Patient Health Questionnaire-9\u003c/p\u003e\n\u003cp\u003ePRISMA: the Preferred Reporting Items for Systematic Reviews and Meta-Analysis\u003c/p\u003e\n\u003cp\u003eRCT: Randomized Controlled Trial\u003c/p\u003e\n\u003cp\u003eRDC: Research Diagnostic Criteria\u003c/p\u003e\n\u003cp\u003eROB: Risk of Bias\u003c/p\u003e\n\u003cp\u003eRR: Risk Ration\u003c/p\u003e\n\u003cp\u003eSMD: Standardized Mean Difference\u003c/p\u003e\n\u003cp\u003eSMS: Short Message Service\u003c/p\u003e\n\u003cp\u003eSR: Systematic Review\u003c/p\u003e\n\u003cp\u003eSTAI: State-Trait Anxiety Inventory\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate:\u0026nbsp;Not applicable\u003c/p\u003e\n\u003cp\u003eConsent for publication:\u0026nbsp;Not applicable\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials:\u0026nbsp;All data analyzed in this study are included within the article and a list of references.\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; contributions:\u0026nbsp;YM designed the study; screened titles and abstracts; conducted a full-text review; assessed the quality of each study; interpreted the data and review the manuscript. YO designed the study; screened titles and abstracts; conducted a full-text review; assessed the quality of each study; interpreted the data and review the manuscript. AS screened titles and abstracts and reviewed the manuscript. KK conducted a full-text review; assessed the quality of each study and reviewed the manuscript. KJ screened titles and abstracts. TA designed the study; interpreted the data and reviewed the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eAcknowledgements:\u0026nbsp;We would like to thank Editage (www.editage.com) for English language editing.\u003c/p\u003e\n\u003cp\u003eFunding:\u0026nbsp;Not applicable\u003c/p\u003e\n\u003cp\u003eCompeting interests:\u0026nbsp;The authors have no competing interests to disclose.\u003c/p\u003e\n\u003cp\u003eAuthor\u0026rsquo;s Information: YM is a family physician at Hamamatsu Satocho Clinic. YO is an associate professor in the Department of Healthcare Epidemiology, School of Public Health, Kyoto University. AS is a medical director at the Department of Obstetrics Gynecology, Yodogawa Christian Hospital. KK is a medical director at the Department of Gynecology, Nagano Municipal Hospital. KJ is a medical director at the Department of Obstetrics \u0026amp; Gynecology, Kikugawa General Hospital. TA is a lecturer in the Division of Clinical Epidemiology, Research Center for Medical Sciences, The Jikei University School of Medicine and belongs to the Section of Clinical Epidemiology, Department of Community Medicine, Graduate School of Medicine, Kyoto University\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eStewart DE, Vigod SN. Postpartum Depression: Pathophysiology, Treatment, and Emerging Therapeutics. Annu Rev Med. 2019;70:183-96.\u003c/li\u003e\n\u003cli\u003eShorey S, Chee CYI, Ng ED, Chan YH, Tam WWS, Chong YS. Prevalence and incidence of postpartum depression among healthy mothers: A systematic review and meta-analysis. J Psychiatr Res. 2018;104:235-48.\u003c/li\u003e\n\u003cli\u003eJago CA, Singh SS, Moretti F. Coronavirus Disease 2019 (COVID-19) and Pregnancy: Combating Isolation to Improve Outcomes. Obstet Gynecol. 2020;136(1):33-6.\u003c/li\u003e\n\u003cli\u003eGrigoriadis S, Wilton AS, Kurdyak PA, Rhodes AE, VonderPorten EH, Levitt A, et al. Perinatal suicide in Ontario, Canada: a 15-year population-based study. Cmaj. 2017;189(34):E1085-e92.\u003c/li\u003e\n\u003cli\u003eLindahl V, Pearson JL, Colpe L. Prevalence of suicidality during pregnancy and the postpartum. Arch Womens Ment Health. 2005;8(2):77-87.\u003c/li\u003e\n\u003cli\u003eKingston D, Kehler H, Austin MP, Mughal MK, Wajid A, Vermeyden L, et al. Trajectories of maternal depressive symptoms during pregnancy and the first 12 months postpartum and child externalizing and internalizing behavior at three years. PLoS One. 2018;13(4):e0195365.\u003c/li\u003e\n\u003cli\u003eO\u0026apos;Mahen HA, Flynn HA. Preferences and perceived barriers to treatment for depression during the perinatal period. J Womens Health (Larchmt). 2008;17(8):1301-9.\u003c/li\u003e\n\u003cli\u003eGoodman JH. Women\u0026apos;s attitudes, preferences, and perceived barriers to treatment for perinatal depression. Birth. 2009;36(1):60-9.\u003c/li\u003e\n\u003cli\u003eLinardon J, Cuijpers P, Carlbring P, Messer M, Fuller-Tyszkiewicz M. The efficacy of app-supported smartphone interventions for mental health problems: a meta-analysis of randomized controlled trials. World Psychiatry. 2019;18(3):325-36.\u003c/li\u003e\n\u003cli\u003eWasil AR, Gillespie S, Shingleton R, Wilks CR, Weisz JR. Examining the Reach of Smartphone Apps for Depression and Anxiety. Am J Psychiatry. 2020;177(5):464-5.\u003c/li\u003e\n\u003cli\u003eMu TY, Li YH, Xu RX, Chen J, Wang YY, Shen CZ. Internet-based interventions for postpartum depression: A systematic review and meta-analysis. Nurs Open. 2021;8(3):1125-34.\u003c/li\u003e\n\u003cli\u003eDol J, Richardson B, Murphy GT, Aston M, McMillan D, Campbell-Yeo M. Impact of mobile health interventions during the perinatal period on maternal psychosocial outcomes: a systematic review. JBI Evid Synth. 2020;18(1):30-55.\u003c/li\u003e\n\u003cli\u003eeHealth WHOGOf. mHealth: new horizons for health through mobile technologies: second global survey on eHealth. Geneva: World Health Organization; 2011.\u003c/li\u003e\n\u003cli\u003eTsai Z, Kiss A, Nadeem S, Sidhom K, Owais S, Faltyn M, et al. Evaluating the effectiveness and quality of mobile applications for perinatal depression and anxiety: A systematic review and meta-analysis. Journal of Affective Disorders. 2022;296:443-53.\u003c/li\u003e\n\u003cli\u003eBauer A, Knapp M, Parsonage M. Lifetime costs of perinatal anxiety and depression. J Affect Disord. 2016;192:83-90.\u003c/li\u003e\n\u003cli\u003ePage MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Bmj. 2021;372:n71.\u003c/li\u003e\n\u003cli\u003eSpitzer RL, Endicott J, Robins E. Research diagnostic criteria: rationale and reliability. Arch Gen Psychiatry. 1978;35(6):773-82.\u003c/li\u003e\n\u003cli\u003eCox JL, Holden JM, Sagovsky R. Detection of postnatal depression. Development of the 10-item Edinburgh Postnatal Depression Scale. Br J Psychiatry. 1987;150:782-6.\u003c/li\u003e\n\u003cli\u003eDerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986;7(3):177-88.\u003c/li\u003e\n\u003cli\u003eShorey S, Ng YPM, Siew AL, Yoong J, M\u0026ouml;relius E. Effectiveness of a Technology-Based Supportive Educational Parenting Program on Parental Outcomes in Singapore: Protocol for a Randomized Controlled Trial. JMIR Res Protoc. 2018;7(1):e4.\u003c/li\u003e\n\u003cli\u003eKalmbach DA, Cheng P, O\u0026apos;Brien LM, Swanson LM, Sangha R, Sen S, et al. A randomized controlled trial of digital cognitive behavioral therapy for insomnia in pregnant women. Sleep Med. 2020;72:82-92.\u003c/li\u003e\n\u003cli\u003eChan KL, Leung WC, Tiwari A, Or KL, Ip P. Using Smartphone-Based Psychoeducation to Reduce Postnatal Depression Among First-Time Mothers: Randomized Controlled Trial. JMIR Mhealth Uhealth. 2019;7(5):e12794.\u003c/li\u003e\n\u003cli\u003eBarrera AZ, Wickham RE, Mu\u0026ntilde;oz RF. Online prevention of postpartum depression for Spanish- and English-speaking pregnant women: A pilot randomized controlled trial. Internet Interv. 2015;2(3):257-65.\u003c/li\u003e\n\u003cli\u003eShorey S, Lau Y, Dennis CL, Chan YS, Tam WWS, Chan YH. A randomized-controlled trial to examine the effectiveness of the \u0026apos;Home-but not Alone\u0026apos; mobile-health application educational programme on parental outcomes. J Adv Nurs. 2017;73(9):2103-17.\u003c/li\u003e\n\u003cli\u003eFonseca A, Alves S, Monteiro F, Gorayeb R, Canavarro MC. Be a Mom, a Web-Based Intervention to Prevent Postpartum Depression: Results From a Pilot Randomized Controlled Trial. Behav Ther. 2020;51(4):616-33.\u003c/li\u003e\n\u003cli\u003eHaga SM, Drozd F, Lis\u0026oslash;y C, Wentzel-Larsen T, Slinning K. Mamma Mia - A randomized controlled trial of an internet-based intervention for perinatal depression. Psychol Med. 2019;49(11):1850-8.\u003c/li\u003e\n\u003cli\u003eDavenport MH, Meyer S, Meah VL, Strynadka MC, Khurana R. Moms Are Not OK: COVID-19 and Maternal Mental Health. Front Glob Womens Health. 2020;1:1.\u003c/li\u003e\n\u003cli\u003eChen Q, Li W, Xiong J, Zheng X. Prevalence and Risk Factors Associated with Postpartum Depression during the COVID-19 Pandemic: A Literature Review and Meta-Analysis. Int J Environ Res Public Health. 2022;19(4).\u003c/li\u003e\n\u003cli\u003eDadi AF, Miller ER, Mwanri L. Postnatal depression and its association with adverse infant health outcomes in low- and middle-income countries: a systematic review and meta-analysis. BMC Pregnancy Childbirth. 2020;20(1):416.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables are available in Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-2431187/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2431187/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThis study aimed to assess whether automated apps are effective in preventing postpartum depression.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted an article search on the electronic databases of the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE via Ovid, Scopus, PsycINFO, CINAHL, and ProQuest Dissertations \u0026amp; Theses A\u0026amp;I on March 26th, 2020. We also searched the International Clinical Trials Platform Search Portal (ICTRP), and Clinical Trials.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWe identified 1581 references, and seven studies were ultimately included in this review. Only one study has assessed the onset of postpartum depression as an outcome. This indicated that after the app intervention, the proportion of women who developed postpartum depression was significantly lower in the intervention group than in the control group (6 weeks postpartum risk ratio (RR)0.79, 95% confidence intervals (95%CI)0.58\u0026ndash;1.06; 3 months postpartum RR0.74, 95%CI0.50\u0026ndash;1.09; 6 months postpartum RR0.73, 95%CI0.49\u0026ndash;1.11 RR0.73, 95%CI0.49\u0026ndash;1.11). We performed a meta-analysis of Edinburgh Postnatal Depression Scale (EPDS) scores at each time point. During the immediate (0\u0026ndash;8 weeks postpartum) period, the intervention group had significantly lower EPDS scores than the control group (mean differences (MD) -0.59; 95%CI -1.00 to -0.18; P\u0026thinsp;=\u0026thinsp;0.005). In the short term (9\u0026ndash;16 weeks postpartum), there was no significant difference between the intervention and control groups in terms of EPDS score (MD -0.32; 95%CI -10.82 to 1.17; P\u0026thinsp;=\u0026thinsp;0.20).\u003c/p\u003e\u003ch2\u003eLimitations:\u003c/h2\u003e \u003cp\u003eOnly one randomized controlled trial (RCT) measured the onset of postpartum depression as an outcome; we performed a meta-analysis only on the EPDS scores. Additionally, there was a high risk of incomplete outcome data due to the high attrition rates in the study.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe apps, including an automated component for the prevention of postpartum depression, improved the EPDS score; furthermore, they may prevent postpartum depression.\u003c/p\u003e","manuscriptTitle":"App-based interventions for the prevention of postpartum depression: a systematic review and meta-analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-01-17 16:03:07","doi":"10.21203/rs.3.rs-2431187/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2023-03-10T07:08:39+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-02-17T20:28:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"0e244a5a-24f8-483c-986c-97d4ca02d09a","date":"2023-02-04T11:23:05+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-01-30T12:27:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"f2cb707c-95e3-4c65-bb6d-1a5c9fc61a3b","date":"2023-01-30T10:49:39+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-01-28T22:07:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-01-28T22:03:48+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2023-01-16T05:56:52+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-01-16T05:54:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pregnancy and Childbirth","date":"2022-12-31T11:44:20+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a1897f60-31c5-4244-bd8c-61d598f952ec","owner":[],"postedDate":"January 17th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-10-16T21:47:15+00:00","versionOfRecord":{"articleIdentity":"rs-2431187","link":"https://doi.org/10.1186/s12884-023-05749-5","journal":{"identity":"bmc-pregnancy-and-childbirth","isVorOnly":false,"title":"BMC Pregnancy and Childbirth"},"publishedOn":"2023-06-14 21:12:58","publishedOnDateReadable":"June 14th, 2023"},"versionCreatedAt":"2023-01-17 16:03:07","video":"","vorDoi":"10.1186/s12884-023-05749-5","vorDoiUrl":"https://doi.org/10.1186/s12884-023-05749-5","workflowStages":[]},"version":"v1","identity":"rs-2431187","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2431187","identity":"rs-2431187","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}