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Digitalized Cognitive Behavioral Interventions for Depressive Symptoms During Pregnancy: Systematic Review
BACKGROUND: Studies have shown a high prevalence of depression during pregnancy, and there is also evidence that cognitive behavioral therapy (CBT) is one of the most effective psychosocial interventions. Emerging evidence from randomized controlled trials (RCTs) has shown that technology has been s...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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JMIR Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8908191/ https://www.ncbi.nlm.nih.gov/pubmed/35195532 http://dx.doi.org/10.2196/33337 |
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author | Wan Mohd Yunus, Wan Mohd Azam Matinolli, Hanna-Maria Waris, Otto Upadhyaya, Subina Vuori, Miika Korpilahti-Leino, Tarja Ristkari, Terja Koffert, Tarja Sourander, Andre |
author_facet | Wan Mohd Yunus, Wan Mohd Azam Matinolli, Hanna-Maria Waris, Otto Upadhyaya, Subina Vuori, Miika Korpilahti-Leino, Tarja Ristkari, Terja Koffert, Tarja Sourander, Andre |
author_sort | Wan Mohd Yunus, Wan Mohd Azam |
collection | PubMed |
description | BACKGROUND: Studies have shown a high prevalence of depression during pregnancy, and there is also evidence that cognitive behavioral therapy (CBT) is one of the most effective psychosocial interventions. Emerging evidence from randomized controlled trials (RCTs) has shown that technology has been successfully harnessed to provide CBT interventions for other populations. However, very few studies have focused on their use during pregnancy. This approach has become increasingly important in many clinical areas due to the COVID-19 pandemic, and our study aimed to expand the knowledge in this particular clinical area. OBJECTIVE: Our systematic review aimed to bring together the available research-based evidence on digitalized CBT interventions for depression symptoms during pregnancy. METHODS: A systematic review of the Web of Science, Cochrane Central Register of Controlled Trials, CINAHL, MEDLINE, Embase, PsycINFO, Scopus, ClinicalTrials.gov, and EBSCO Open Dissertations databases was carried out from the earliest available evidence to October 27, 2021. Only RCT studies published in English were considered. The PRISMA (Preferred Reporting Items of Systematic Reviews and Meta-analyses) guidelines were followed, and the protocol was registered on the Prospective Register of Systematic Reviews. The risk of bias was assessed using the revised Cochrane risk-of-bias tool for randomized trials. RESULTS: The review identified 7 studies from 5 countries (the United States, China, Australia, Norway, and Sweden) published from 2015 to 2021. The sample sizes ranged from 25 to 1342 participants. The interventions used various technological elements, including text, images, videos, games, interactive features, and peer group discussions. They comprised 2 guided and 5 unguided approaches. Using digitalized CBT interventions for depression during pregnancy showed promising efficacy, with guided intervention showing higher effect sizes (Hedges g=1.21) than the unguided interventions (Hedges g=0.14-0.99). The acceptability of the digitalized CBT interventions was highly encouraging, based on user feedback. Attrition rates were low for the guided intervention (4.5%) but high for the unguided interventions (22.1%-46.5%). A high overall risk of bias was present for 6 of the 7 studies. CONCLUSIONS: Our search only identified a small number of digitalized CBT interventions for pregnant women, despite the potential of this approach. These showed promising evidence when it came to efficacy and positive outcomes for depression symptoms, and user feedback was positive. However, the overall risk of bias suggests that the efficacy of the interventions needs to be interpreted with caution. Future studies need to consider how to mitigate these sources of biases. Digitalized CBT interventions can provide prompt, effective, evidence-based interventions for pregnant women. This review increases our understanding of the importance of digitalized interventions during pregnancy, including during the COVID-19 pandemic. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CRD42020216159; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=216159 |
format | Online Article Text |
id | pubmed-8908191 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-89081912022-03-11 Digitalized Cognitive Behavioral Interventions for Depressive Symptoms During Pregnancy: Systematic Review Wan Mohd Yunus, Wan Mohd Azam Matinolli, Hanna-Maria Waris, Otto Upadhyaya, Subina Vuori, Miika Korpilahti-Leino, Tarja Ristkari, Terja Koffert, Tarja Sourander, Andre J Med Internet Res Review BACKGROUND: Studies have shown a high prevalence of depression during pregnancy, and there is also evidence that cognitive behavioral therapy (CBT) is one of the most effective psychosocial interventions. Emerging evidence from randomized controlled trials (RCTs) has shown that technology has been successfully harnessed to provide CBT interventions for other populations. However, very few studies have focused on their use during pregnancy. This approach has become increasingly important in many clinical areas due to the COVID-19 pandemic, and our study aimed to expand the knowledge in this particular clinical area. OBJECTIVE: Our systematic review aimed to bring together the available research-based evidence on digitalized CBT interventions for depression symptoms during pregnancy. METHODS: A systematic review of the Web of Science, Cochrane Central Register of Controlled Trials, CINAHL, MEDLINE, Embase, PsycINFO, Scopus, ClinicalTrials.gov, and EBSCO Open Dissertations databases was carried out from the earliest available evidence to October 27, 2021. Only RCT studies published in English were considered. The PRISMA (Preferred Reporting Items of Systematic Reviews and Meta-analyses) guidelines were followed, and the protocol was registered on the Prospective Register of Systematic Reviews. The risk of bias was assessed using the revised Cochrane risk-of-bias tool for randomized trials. RESULTS: The review identified 7 studies from 5 countries (the United States, China, Australia, Norway, and Sweden) published from 2015 to 2021. The sample sizes ranged from 25 to 1342 participants. The interventions used various technological elements, including text, images, videos, games, interactive features, and peer group discussions. They comprised 2 guided and 5 unguided approaches. Using digitalized CBT interventions for depression during pregnancy showed promising efficacy, with guided intervention showing higher effect sizes (Hedges g=1.21) than the unguided interventions (Hedges g=0.14-0.99). The acceptability of the digitalized CBT interventions was highly encouraging, based on user feedback. Attrition rates were low for the guided intervention (4.5%) but high for the unguided interventions (22.1%-46.5%). A high overall risk of bias was present for 6 of the 7 studies. CONCLUSIONS: Our search only identified a small number of digitalized CBT interventions for pregnant women, despite the potential of this approach. These showed promising evidence when it came to efficacy and positive outcomes for depression symptoms, and user feedback was positive. However, the overall risk of bias suggests that the efficacy of the interventions needs to be interpreted with caution. Future studies need to consider how to mitigate these sources of biases. Digitalized CBT interventions can provide prompt, effective, evidence-based interventions for pregnant women. This review increases our understanding of the importance of digitalized interventions during pregnancy, including during the COVID-19 pandemic. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CRD42020216159; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=216159 JMIR Publications 2022-02-23 /pmc/articles/PMC8908191/ /pubmed/35195532 http://dx.doi.org/10.2196/33337 Text en ©Wan Mohd Azam Wan Mohd Yunus, Hanna-Maria Matinolli, Otto Waris, Subina Upadhyaya, Miika Vuori, Tarja Korpilahti-Leino, Terja Ristkari, Tarja Koffert, Andre Sourander. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 23.02.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Review Wan Mohd Yunus, Wan Mohd Azam Matinolli, Hanna-Maria Waris, Otto Upadhyaya, Subina Vuori, Miika Korpilahti-Leino, Tarja Ristkari, Terja Koffert, Tarja Sourander, Andre Digitalized Cognitive Behavioral Interventions for Depressive Symptoms During Pregnancy: Systematic Review |
title | Digitalized Cognitive Behavioral Interventions for Depressive Symptoms During Pregnancy: Systematic Review |
title_full | Digitalized Cognitive Behavioral Interventions for Depressive Symptoms During Pregnancy: Systematic Review |
title_fullStr | Digitalized Cognitive Behavioral Interventions for Depressive Symptoms During Pregnancy: Systematic Review |
title_full_unstemmed | Digitalized Cognitive Behavioral Interventions for Depressive Symptoms During Pregnancy: Systematic Review |
title_short | Digitalized Cognitive Behavioral Interventions for Depressive Symptoms During Pregnancy: Systematic Review |
title_sort | digitalized cognitive behavioral interventions for depressive symptoms during pregnancy: systematic review |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8908191/ https://www.ncbi.nlm.nih.gov/pubmed/35195532 http://dx.doi.org/10.2196/33337 |
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