Evaluating the effectiveness and cost-effectiveness of a digital, app-based intervention for depression (VMood) in community-based settings in Vietnam : Protocol for a stepped-wedge randomized controlled trial
Copyright: © 2023 Chau et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited..
The COVID-19 pandemic has amplified mental health problems and highlighted inequitable gaps in care worldwide. In response there has been an explosion of digital interventions such as smartphone applications ("apps") to extend care. The objective of this trial is to evaluate the effectiveness and cost-effectiveness of a digital depression intervention (VMood), delivered via a smartphone app. VMood is adapted from an in-person intervention that was delivered by non-specialist providers and shown to be effective in the Vietnamese context in our previous trial (2016-2019). A stepped-wedge, randomized controlled trial will be conducted across eight provinces in Vietnam. Adults aged 18 years and over will be recruited through community-based primary care centres and screened for depression using the embedded Patient Health Questionnaire-9 (primary outcome measure). Participants scoring 10-19, indicating depression caseness, will be randomly allocated to the intervention or control group until the target of 336 is reached. Secondary outcome measures will examine the effect of the intervention on commonly co-occuring anxiety, quality of life and work productivity, along with use of alcohol and tobacco products. Assessments will be administered through an online survey platform (REDCap) at baseline, and at every 3 months until 3 months post-intervention. Intervention-group participants will receive VMood for a 3-month period, with online support provided by social workers. Control-group participants will receive a limited version of the app until they cross into the intervention group. Generalized Linear Mixed-effect Models for clustered measures will be used for all outcomes data. We will conduct a cost-effectiveness analysis alongside the trial to capture VMood's costs and benefits. This trial will provide evidence on the effectiveness and cost-effectiveness of a digital mental health intervention adapted from an in-person intervention. This trial will also contribute important information to the growing and promising field of digital mental health. Trail regulation. Registered at ClinicalTrials.gov, identifier [NCT05783531].
Medienart: |
E-Artikel |
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Erscheinungsjahr: |
2023 |
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Erschienen: |
2023 |
Enthalten in: |
Zur Gesamtaufnahme - volume:18 |
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Enthalten in: |
PloS one - 18(2023), 9 vom: 04., Seite e0290328 |
Sprache: |
Englisch |
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Beteiligte Personen: |
Chau, Leena W [VerfasserIn] |
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Themen: |
Clinical Trial Protocol |
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Anmerkungen: |
Date Completed 07.09.2023 Date Revised 08.09.2023 published: Electronic-eCollection ClinicalTrials.gov: NCT05783531 Citation Status MEDLINE |
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doi: |
10.1371/journal.pone.0290328 |
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funding: |
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PPN (Katalog-ID): |
NLM361669798 |
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520 | |a The COVID-19 pandemic has amplified mental health problems and highlighted inequitable gaps in care worldwide. In response there has been an explosion of digital interventions such as smartphone applications ("apps") to extend care. The objective of this trial is to evaluate the effectiveness and cost-effectiveness of a digital depression intervention (VMood), delivered via a smartphone app. VMood is adapted from an in-person intervention that was delivered by non-specialist providers and shown to be effective in the Vietnamese context in our previous trial (2016-2019). A stepped-wedge, randomized controlled trial will be conducted across eight provinces in Vietnam. Adults aged 18 years and over will be recruited through community-based primary care centres and screened for depression using the embedded Patient Health Questionnaire-9 (primary outcome measure). Participants scoring 10-19, indicating depression caseness, will be randomly allocated to the intervention or control group until the target of 336 is reached. Secondary outcome measures will examine the effect of the intervention on commonly co-occuring anxiety, quality of life and work productivity, along with use of alcohol and tobacco products. Assessments will be administered through an online survey platform (REDCap) at baseline, and at every 3 months until 3 months post-intervention. Intervention-group participants will receive VMood for a 3-month period, with online support provided by social workers. Control-group participants will receive a limited version of the app until they cross into the intervention group. Generalized Linear Mixed-effect Models for clustered measures will be used for all outcomes data. We will conduct a cost-effectiveness analysis alongside the trial to capture VMood's costs and benefits. This trial will provide evidence on the effectiveness and cost-effectiveness of a digital mental health intervention adapted from an in-person intervention. This trial will also contribute important information to the growing and promising field of digital mental health. Trail regulation. Registered at ClinicalTrials.gov, identifier [NCT05783531] | ||
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700 | 1 | |a Xie, Hui |e verfasserin |4 aut | |
700 | 1 | |a Lam, Raymond W |e verfasserin |4 aut | |
700 | 1 | |a Minas, Harry |e verfasserin |4 aut | |
700 | 1 | |a Zheng, Yufei |e verfasserin |4 aut | |
700 | 1 | |a Krebs, Emanuel |e verfasserin |4 aut | |
700 | 1 | |a Hayashi, Kanna |e verfasserin |4 aut | |
700 | 1 | |a Dao, Son |e verfasserin |4 aut | |
700 | 1 | |a Nguyen, Xuan |e verfasserin |4 aut | |
700 | 1 | |a Duong, Viet Anh |e verfasserin |4 aut | |
700 | 1 | |a Fiume, Eugene |e verfasserin |4 aut | |
700 | 1 | |a O'Neil, John |e verfasserin |4 aut | |
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