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Predictors of Participation in a Perinatal Text Message Screening Protocol for Maternal Depression and Anxiety:
Julia Barnwell1,2, Cindy Hénault Robert2, Tuong-Vi Nguyen2,3,4,5
1Department of Human Genetics, McGill University, Montreal, QC, Canada.
Background:
Universal screening for depression and anxiety in pregnancy has been recommended by several leading medical organizations, but the implementation of such screening protocols may overburden health care systems lacking relevant resources. Text message screening may provide a low-cost, accessible alternative to in-person screening assessments. However, it is critical to understand who is likely to participate in text message-based screening protocols before such approaches can be implemented at the population level.
Objective:
This study aimed to examine sources of selection bias in a texting-based screening protocol that assessed symptoms of depression and anxiety across pregnancy and into the postpartum period.
Methods:
Participants from the Montreal Antenatal Well-Being Study (n=1130) provided detailed sociodemographic information and completed questionnaires assessing symptoms of depression (Edinburgh Postnatal Depression Scale [EPDS]) and anxiety (State component of the State-Trait Anxiety Inventory [STAI-S]) at baseline between 8 and 20 weeks of gestation (mean 14.5, SD 3.8 weeks of gestation). Brief screening questionnaires, more suitable for delivery via text message, assessing depression (Whooley Questions) and anxiety symptoms (Generalized Anxiety Disorder 2-Item questionnaire) were also collected at baseline and then via text message at 14-day intervals. Two-tailed t tests and Fisher tests were used to identify maternal characteristics that differed between participants who responded to the text message screening questions and those who did not. Hurdle regression models were used to test if individuals with a greater burden of depression and anxiety at baseline responded to fewer text messages across the study period.
Results:
Participants who responded to the text messages (n=933) were more likely than nonrespondents (n=114) to self-identify as White (587/907, 64.7% vs 39/96, 40.6%; P<.001), report higher educational attainment (postgraduate: 268/909, 29.5% vs 15/94, 16%; P=.005), and report higher income levels (CAD $150,000 [a currency exchange rate of CAD $1=US $0.76 is applicable] or more: 176/832, 21.2% vs 10/84, 11.9%; P<.001). There were no significant differences in symptoms of depression and anxiety between the 2 groups at baseline or postpartum. However, baseline depression (EPDS) or anxiety (STAI-S) symptoms did predict the total number of text message time points answered by participants, corresponding to a decrease of 1% (eβ=0.99; P<.001) and 0.3% (eβ=0.997; P<.001) in the number of text message time points answered per point increase in EPDS or STAI-S score, respectively.
Conclusions:
Findings from this study highlight the feasibility of text message-based screening protocols with high participation rates. However, our findings also highlight how screening and service delivery via digital technology could exacerbate disparities in mental health between certain patient groups.
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