Table 2.

Summary table of effectiveness, feasibility and acceptability of digital screening in pregnancy and postpartum

ID	Author/Year	Measure	Method/Data Analysis	Comparison Group
3	Diez-Canseco et al. (2018)	Effectiveness	Quantitative: descriptive analyses, frequencies and percentages; Qualitative: Interviews	No
6	Drake et al. (2014)	Effectiveness	Cronbach’s α; Thematic Analysis	No
9	Flynn et al. (2011)	Effectiveness	Cronbach’s α; Quantitative Analysis: Pearson correlations; Comparative AUC for ROC contrasts between EPDS and PHQ	No
10	Fontein-Kuipers & Jomeen (2019)	Effectiveness	Quantitative Analysis; proportion of maternal distress; reliability analysis of Whooley questions; diagnostic accuracy of Whooley items for depression, trait-anxiety, pregnancy-related anxiety; population prevalence of maternal distress; ROC analysis of EDS, STAI and PRAQ-R2 at T1 & T1 (Q1 &2)	No
14	Guevara et al. (2016)	Feasibility Acceptability	Summary statistics on the number of eligible parents, depression screens administered, and positive screens by site were collected; Differences in proportions by site using chi- square statistics; Assessed for trends in the monthly proportion screened using a chi- square test of trend statistic; Thematic Analysis	No
15	Guintivano et al. (2018)	Effectiveness	Descriptive statistics; State-level birth rate data; ICC’s to measure test–retest reliability for continuous variables; Binomial tests to measure agreement for binary variables; Squared weighted Cohen’s kappas to measure test–retest reliability for categorical variables	No
16	Hahn et al. (2021)	Feasibility Acceptability	Univariate analysis (χ2, N and p-value) of the first cohort; Logistic regression coefficients; Socio-demographic variables; birth complications; subjective birth-related trauma; PMS; postpartum blues; stressful life events; breastfeeding; within- and out-of-sample validation study design	Yes—three distinct groups: women with PPD, women with Adjustment Disorder (AD), and healthy controls (HC)
18	Highet et al. (2019)	Effectiveness	Cronbach’s α (EPDS administered digitally); Participant characteristics; psychosocial risk (n & %); mean screening time; rates of depression and anxiety	No
19	Jiménez-Serrano et al. (2015)	Effectiveness	Machine Learning (ML); Pattern Recognition (PR); Naive Bayes Model; Logistic Regression; artificial neural network (ANN); support vector machines (SVM)	Yes – PPD and no PPD
21	Kallem et al. (2019)	Effectiveness	Bivariate analyses (Chi-square and t test) were conducted comparing the maternal and infant factors of mothers who completed the EPDS and did not complete the EPDS; Multivariate logistic regression was used to estimate maternal and infant clinical and sociodemographic factors that predict service use	Yes – women who received services and women who did not receive services
22	Kim et al. (2007)	Feasibility Acceptability	Quantitative outcomes of interest were completion rates for the IVR screening and the percentage of women with mild to severe depressive symptoms. Research outcomes included reports of patient satisfaction (n & %) with the system along with their preferences for an intervention	No
23	Kingston et al. (2017)	Effectiveness Feasibility Acceptability	Adapted version of Renker and Tonkin’s tool of feasibility and acceptability; ITT analysis; Baseline differences in groups were compared using independent t tests (means) and chi-square tests (%); Descriptive data (frequencies and 95% CIs; means and SDs) to describe the sample	Yes – women who completed paper-based screening compared to E-screening
25	Marcano-Belisario et al. (2017)	Feasibility	Completion times (median, mins, secs); proportion; median; chi-square; sample sizes and percentages	No
27	Poleshuck et al. (2015)	Feasibility Acceptability	Analytic plan—growth curve analysis; quadratic effects; cross-sectional mean differences using ANCOVA; moderation effects; latent class analysis	No
28	Quispel et al. (2012)	Effectiveness	Cronbach’s α coefficient; intraclass correlation coefficient, Cohen’s κ and Kendall’s τ-b. Criterion validity NPV; PPV secondary measure; risk profiles and to describe feasibility judgements they used conventional descriptive and comparative statistics; Posthoc Bonferroni adjusted pair wise comparisons were performed to identify any group related difference; Power 0.80 and p value < 0.05	No
29	Martinez-Borba et al. (2019)	Feasibility Acceptability	Descriptive analysis of the sample; Analysis of dropout rates (proportion of women who completed each assessment in relation to women who were registered into the program); Exploration of women’s usability reports and satisfaction with HM	No
30	Shore et al. (2020)	Effectiveness	Descriptive analyses on patient characteristics, process measures and outcome measures (%, N, χ2,df, p-value)	No
31	Tsai et al. (2014)	Effectiveness Feasibility Acceptability	Cronbach’s α coefficient; Pearson correlation coefficient; calculating sensitivity, specificity, and likelihood ratios using standard formulas; ROC curves, calculating the area under the ROC curve (AUC) using the trapezoidal rule and comparing AUC values using the algorithm	No
32	Willey et al. (2020)	Feasibility Acceptability	Thematic analysis – inductive and deductive approach; saturation of themes; hybrid approach to thematic analysis was utilised	No
34	Wright et al. (2020)	Feasibility Acceptability	Descriptive statistics; general inductive approach to thematic analysis of Qualitative themes	No