Feasibility and impact of a mental health chatbot on postpartum mental health: a randomized controlled trial.
artificial intelligence
chatbot
digital therapeutics
mental health
perinatal mood
postpartum depression
smartphone app
telehealth
Journal
AJOG global reports
ISSN: 2666-5778
Titre abrégé: AJOG Glob Rep
Pays: United States
ID NLM: 101777907
Informations de publication
Date de publication:
Aug 2023
Aug 2023
Historique:
medline:
10
8
2023
pubmed:
10
8
2023
entrez:
10
8
2023
Statut:
epublish
Résumé
Perinatal mood disorders are common yet underdiagnosed and un- or undertreated. Barriers exist to accessing perinatal mental health services, including limited availability, time, and cost. Automated conversational agents (chatbots) can deliver evidence-based cognitive behavioral therapy content through text message-based conversations and reduce depression and anxiety symptoms in select populations. Such digital mental health technologies are poised to overcome barriers to mental health care access but need to be evaluated for efficacy, as well as for preliminary feasibility and acceptability among perinatal populations. To evaluate the acceptability and preliminary efficacy of a mental health chatbot for mood management in a general postpartum population. An unblinded randomized controlled trial was conducted at a tertiary academic center. English-speaking postpartum women aged 18 years or above with a live birth and access to a smartphone were eligible for enrollment prior to discharge from delivery hospitalization. Baseline surveys were administered to all participants prior to randomization to a mental health chatbot intervention or to usual care only. The intervention group downloaded the mental health chatbot smartphone application with perinatal-specific content, in addition to continuing usual care. Usual care consisted of routine postpartum follow up and mental health care as dictated by the patient's obstetric provider. Surveys were administered during delivery hospitalization (baseline) and at 2-, 4-, and 6-weeks postpartum to assess depression and anxiety symptoms. The primary outcome was a change in depression symptoms at 6-weeks as measured using two depression screening tools: Patient Health Questionnaire-9 and Edinburgh Postnatal Depression Scale. Secondary outcomes included anxiety symptoms measured using Generalized Anxiety Disorder-7, and satisfaction and acceptability using validated scales. Based on a prior study, we estimated a sample size of 130 would have sufficient (80%) power to detect a moderate effect size (d=.4) in between group difference on the Patient Health Questionnaire-9. A total of 192 women were randomized equally 1:1 to the chatbot or usual care; of these, 152 women completed the 6-week survey (n=68 chatbot, n=84 usual care) and were included in the final analysis. Mean baseline mental health assessment scores were below positive screening thresholds. At 6-weeks, there was a greater decrease in Patient Health Questionnaire-9 scores among the chatbot group compared to the usual care group (mean decrease=1.32, standard deviation=3.4 vs mean decrease=0.13, standard deviation=3.01, respectively). 6-week mean Edinburgh Postnatal Depression Scale and Generalized Anxiety Disorder-7 scores did not differ between groups and were similar to baseline. 91% (n=62) of the chatbot users were satisfied or highly satisfied with the chatbot, and 74% (n=50) of the intervention group reported use of the chatbot at least once in 2 weeks prior to the 6-week survey. 80% of study participants reported being comfortable with the use of a mobile smartphone application for mood management. Use of a chatbot was acceptable to women in the early postpartum period. The sample did not screen positive for depression at baseline and thus the potential of the chatbot to reduce depressive symptoms in this population was limited. This study was conducted in a general obstetric population. Future studies of longer duration in high-risk postpartum populations who screen positive for depression are needed to further understand the utility and efficacy of such digital therapeutics for that population.
Sections du résumé
BACKGROUND
BACKGROUND
Perinatal mood disorders are common yet underdiagnosed and un- or undertreated. Barriers exist to accessing perinatal mental health services, including limited availability, time, and cost. Automated conversational agents (chatbots) can deliver evidence-based cognitive behavioral therapy content through text message-based conversations and reduce depression and anxiety symptoms in select populations. Such digital mental health technologies are poised to overcome barriers to mental health care access but need to be evaluated for efficacy, as well as for preliminary feasibility and acceptability among perinatal populations.
OBJECTIVE
OBJECTIVE
To evaluate the acceptability and preliminary efficacy of a mental health chatbot for mood management in a general postpartum population.
STUDY DESIGN
METHODS
An unblinded randomized controlled trial was conducted at a tertiary academic center. English-speaking postpartum women aged 18 years or above with a live birth and access to a smartphone were eligible for enrollment prior to discharge from delivery hospitalization. Baseline surveys were administered to all participants prior to randomization to a mental health chatbot intervention or to usual care only. The intervention group downloaded the mental health chatbot smartphone application with perinatal-specific content, in addition to continuing usual care. Usual care consisted of routine postpartum follow up and mental health care as dictated by the patient's obstetric provider. Surveys were administered during delivery hospitalization (baseline) and at 2-, 4-, and 6-weeks postpartum to assess depression and anxiety symptoms. The primary outcome was a change in depression symptoms at 6-weeks as measured using two depression screening tools: Patient Health Questionnaire-9 and Edinburgh Postnatal Depression Scale. Secondary outcomes included anxiety symptoms measured using Generalized Anxiety Disorder-7, and satisfaction and acceptability using validated scales. Based on a prior study, we estimated a sample size of 130 would have sufficient (80%) power to detect a moderate effect size (d=.4) in between group difference on the Patient Health Questionnaire-9.
RESULTS
RESULTS
A total of 192 women were randomized equally 1:1 to the chatbot or usual care; of these, 152 women completed the 6-week survey (n=68 chatbot, n=84 usual care) and were included in the final analysis. Mean baseline mental health assessment scores were below positive screening thresholds. At 6-weeks, there was a greater decrease in Patient Health Questionnaire-9 scores among the chatbot group compared to the usual care group (mean decrease=1.32, standard deviation=3.4 vs mean decrease=0.13, standard deviation=3.01, respectively). 6-week mean Edinburgh Postnatal Depression Scale and Generalized Anxiety Disorder-7 scores did not differ between groups and were similar to baseline. 91% (n=62) of the chatbot users were satisfied or highly satisfied with the chatbot, and 74% (n=50) of the intervention group reported use of the chatbot at least once in 2 weeks prior to the 6-week survey. 80% of study participants reported being comfortable with the use of a mobile smartphone application for mood management.
CONCLUSION
CONCLUSIONS
Use of a chatbot was acceptable to women in the early postpartum period. The sample did not screen positive for depression at baseline and thus the potential of the chatbot to reduce depressive symptoms in this population was limited. This study was conducted in a general obstetric population. Future studies of longer duration in high-risk postpartum populations who screen positive for depression are needed to further understand the utility and efficacy of such digital therapeutics for that population.
Identifiants
pubmed: 37560011
doi: 10.1016/j.xagr.2023.100165
pii: S2666-5778(23)00006-0
pmc: PMC10407813
doi:
Types de publication
Journal Article
Langues
eng
Pagination
100165Informations de copyright
© 2023 Published by Elsevier Inc.
Références
Asian J Psychiatr. 2021 Dec;66:102873
pubmed: 34624746
Psychiatr Serv. 2019 May 1;70(5):389-395
pubmed: 30717643
J Clin Psychol. 2008 Jan;64(1):103-18
pubmed: 18161036
Dev Psychopathol. 2009 Spring;21(2):417-39
pubmed: 19338691
J Affect Disord. 2004 Mar;78(3):269-72
pubmed: 15013253
JMIR Ment Health. 2019 Oct 18;6(10):e14166
pubmed: 31628789
BMJ. 2010 Mar 23;340:c869
pubmed: 20332511
Int J Womens Health. 2010 Dec 30;3:1-14
pubmed: 21339932
Obstet Gynecol. 2018 Nov;132(5):e208-e212
pubmed: 30629567
Clin Obstet Gynecol. 2009 Sep;52(3):456-68
pubmed: 19661761
J Affect Disord. 2015 May 15;177:7-21
pubmed: 25743368
JMIR Form Res. 2021 May 11;5(5):e27868
pubmed: 33973854
Matern Child Health J. 2011 Oct;15(7):866-75
pubmed: 18256913
Arch Womens Ment Health. 2014 Feb;17(1):3-15
pubmed: 24240636
Drug Alcohol Depend. 2021 Oct 1;227:108986
pubmed: 34507061
Expert Rev Med Devices. 2022 Apr;19(4):287-301
pubmed: 35748029
J Affect Disord. 2004 Jul;81(1):61-6
pubmed: 15183601
Gen Hosp Psychiatry. 2021 Jan-Feb;68:74-82
pubmed: 33360526
JMIR Ment Health. 2017 Jun 06;4(2):e19
pubmed: 28588005
Clin Psychol Psychother. 2012 Mar-Apr;19(2):134-40
pubmed: 22473762
J Med Internet Res. 2021 Mar 23;23(3):e24850
pubmed: 33755028