Implementing a Perinatal Depression Screening in Clinical Routine: Exploring the Patientʼs Perspective

Key words

perinatal depression - screening - Edinburgh Postnatal Depression Scale (EPDS) - acceptance - pregnancy - mental health

Schlüsselwörter

perinatale Depression - Screening - Edinburgh-Postnatal- Depressions-Skala (EPDS) - Akzeptanz - Schwangerschaft - psychische Gesundheit

Introduction

Women commonly suffer from mental health problems during the perinatal period. In particular, depression and anxiety disorders represent frequent manifestations of these problems during pregnancy and after delivery. Indeed, research has revealed a prevalence of 19.2% for perinatal depressive episodes [1] and rates of up to 25% for anxiety symptoms during pregnancy and 15% after delivery [2]. Accordingly, a large-scale retrospective observational database study including more than 38 000 pregnant women in Germany identified a high prevalence of mental health diagnoses and symptoms, with 9.3% suffering from depression and 16.9% from anxiety disorders, 24.2% of the study population showed a somatoform/dissociative disorder, and 11.7% reported to be affected by acute stress [3].

Social factors such as domestic violence or a low socioeconomic status as well as pre-existing physical or mental health problems have been identified as risk factors for perinatal depression (PND) and seem to be indicative of other perinatal mental disorders, too [4]. Antenatal depression in particular has been identified as a strong risk factor for a subsequent postpartum depressive disorder. Remarkably, the prevalence of antenatal depression tends to be even higher than the rates of postpartum depression (17% vs. 13%, respectively) [5]. Mental health problems can have profound adverse effects on mother, infant and father, including preterm delivery, fear of delivery, an increased rate of cesarean sections, low-birthweight infants, neonatal adaptation disorders, developmental delay of the infant and a depressed mood in fathers [3], [6] – [8].

Despite the high prevalence of perinatal mental health problems, the majority of affected women remains undiagnosed. The various symptoms can easily be missed in the context of the often emotionally challenging circumstances of a pregnancy and the postpartum period [8]. As a consequence, affected women do not receive adequate treatment [9]. However, even if diagnosed, a proportion of those women refuse to seek help and treatment because of structural and knowledge barriers [10], including the existing stigma associated with mental disorders [11], [12] and the fear of possible teratogenic effects of drug treatment [13], [14].

Maternity care offers a unique chance to implement a routine mental health assessment, given the frequent routine appointments with health professionals during pregnancy and after childbirth. Therefore, official bodies have recommended a deeper inquiry into womenʼs mental health and have promoted screening for depression during pregnancy and the postpartum period [15], [16]. Previous studies suggest that best practice for early detection of perinatal mental health problems is through routine screenings [17]. Various screening approaches have been tested, most of them using the Edinburgh Postnatal Depression Scale (EPDS) [18] – a screening tool that has proven to be valid and reliable in the antenatal period, too [19], [20].

When implementing screening for PND, it is essential to refer affected women to mental health services with diagnostic and treatment resources [21]. Up to now, however, referral rates are low and only 15% of positively screened pregnant women receive mental health treatment [22]. Research has also shown that women are more likely to seek help when they are asked about their past or present mental health status by a health professional, and especially when they are directly referred to further support services [23].

Although various mental health screening approaches have already been tested, only a few studies have examined the acceptance of a PND screening among perinatal women [24], [25], [26], [27], [28], [29]. The present study therefore aims to add to the literature by examining the following:

1. Based on previous findings, we expected the acceptance rate of implementing a screening program for PND during pregnancy by using the EPDS to be high.

2. We hypothesized that screening acceptance is higher among women with a positive mental health record than women without. To identify more factors that potentially impact screening acceptance, we also investigated medical, obstetric, sociodemographic and self-report characteristics.

3. Lastly, we evaluated womenʼs perspectives on perinatal mental health problems in the perinatal period.

Methods

Study design and sample

The screening was implemented in gynecological and obstetric outpatient practices throughout Baden-Württemberg and at the University Hospitals in Heidelberg and Tübingen between February 2019 and December 2020 as part of the Mind:Pregnancy program, a screening and treatment approach being applied in the federal state of Baden-Württemberg, Germany, and supported by the Federal Joint Committee and several major health care providers (01NVF17 034). German-speaking pregnant women with a singleton pregnancy between the 13th and 27th gestational week were eligible for taking part in the PND screening. The participants completed a paper-based German version of the EPDS during a routine prenatal visit. Women with a positive screening result (EPDS score ≥ 10) were contacted and offered an interdisciplinary psychological and obstetric assessment. Based on the psychological assessment, women were referred for further professional mental health treatment, if indicated, and/or study participation in Mind:Pregnancy was offered. The Mind:Pregnancy program included an electronic mindfulness-based intervention (eMBI), which is currently being examined in a prospective randomized controlled trial [30]. Ethics approval was granted by the ethics committee of Heidelberg University (S-744/2018). Data for this acceptance study were collected under the data privacy terms of the Mind:Pregnancy program, for which informed consent was obtained from all participants.

Our final study sample consisted of N = 732 perinatal women who completed a survey on screening acceptance. This sample was recruited from a larger sample of the Mind:Pregnancy program in December 2019 (total: N = 2659). All participants in Mind:Pregnancy were screened for PND in the second trimester of pregnancy by using the EPDS. Out of these, N = 2094 participants were contacted by email in the further course and received access to the acceptance survey via a personalized link to the platform SoSci Survey. A total of n = 565 (21.2%) participants could not be contacted for the acceptance survey due to missing contact data (email address missing or incorrect). The link to the acceptance questionnaire was accessible from December 2019 to January 2020; a reminder was sent after one month. Due to the cross-sectional study design, the final study sample included both pre- and postpartum women. For reasons of data protection and to keep the registration process for Mind:Pregnancy as simple as possible, no sociodemographic or medical data were collected during the initial EPDS screening. Therefore, these data were not available for nonrespondents of the present acceptance survey.

Measurements

EPDS

The German version of the EPDS [31] was used as a screening instrument for PND. The EPDS is a 10-item, self-rating questionnaire, initially developed as a screening instrument for symptoms of depression in the postpartum period, but afterwards validated for use during pregnancy as well [20]. It has been translated and validated for use in a German-speaking population [31]. With a cutoff value of 10 (EPDS ≥ 10), the sensitivity of detecting a clinically significant depression is 0.96, the specificity is 1.00, and the positive predictive value is 1.00 [18], [31]. The scale reached a good internal consistency in our sample (Cronbachʼs α = 0.88).

Survey on acceptance for PND screening

Our survey on the acceptance for PND screening among perinatal women was a web-based questionnaire using modified items from established questionnaires on acceptance [24], [25], [26], [29], [32] – [35] and self-generated questions. We developed the questionnaire ourselves because so far, no instrument has been established for assessing the acceptance of a PND screening. Our final questionnaire comprised a total of 47 items. In order to analyze the participantsʼ acceptance and perspective on perinatal mental health problems, we focused on the following key questions. If not indicated otherwise, answers were given on a 5-point Likert scale.

1. Usefulness: “How useful is it from your point of view to apply the EPDS to every pregnant woman during pregnancy care?” [24], [29]

2. Difficulty level: “How easy was it for you to complete the EPDS?” [24], [29], [33], [34]

3. Level of comfort: “Did you feel uncomfortable being asked questions about your mental health?” [24], [25], [26], [29], [34]

4. Importance of addressing the subject of mental health: “How important is it from your point of view to address the subject of mental health with each pregnant woman during pregnancy care?” [26]

5. Previous knowledge of perinatal mental health problems: “Before screening, have you ever heard of perinatal mental health problems before?” (yes/no-answer)

6. Stigmatization of perinatal mental health problems: “Do you think that perinatal mental health problems are still a taboo topic in society?” (yes/no-answer)

7. Raising awareness of perinatal mental health problems: “Do you think that a screening for perinatal mental health problems could raise awareness of that issue?” (yes/no-answer) [35]

Furthermore, the questionnaire contained demographic data, data about medical and obstetric history, and items to obtain participantsʼ feedback on the screening and treatment program Mind:Pregnancy itself.

To assess the participantsʼ level of acceptance for PND screening, we focused on the items “usefulness”, “difficulty”, and “comfort”, which are stated in the literature as some of “the main terms used to describe acceptability” [29]. In the present study, “usefulness” represents the key measurement for acceptance.

Statistical analyses

All analyses were conducted using the Statistical Package for Social Sciences (IBM SPSS v. 25.0.0.0) and G*Power (v. 3.1.9.7) [36], [37]. A nonparametric design was chosen due to the nonparametric scale of measurement of most study variables and unequal group sizes and/or skewed distributions (p < 0.05 in Kolmogorov-Smirnov and Shapiro-Wilk tests). Due to dependencies of questionnaire items and scale-specific amounts of missing values, the number of valid cases varied between analyses.

We analyzed the data in three steps by using the following statistical methods:

(1) Descriptive data: We applied descriptive methods to examine the sociodemographic, medical, obstetric, and psychological profile of the sample ([Table 1]). Furthermore, we analyzed the self-report data on screening acceptance (question 1 to 3, see above) and perspective on perinatal mental health problems (questions 4 to 7, see above)

Table 1 Sociodemographic, medical, obstetric, and mental health sample characteristics.

Variable	f	%valid		f	%valid
Location	nvalid = 727		Monthly net household income	nvalid = 714
< 5000 inhabitants	268	36.9	< 1500 €	96	13.4
5000 – under 20 000 inhabitants	219	30.1	1500 – 2999 €	228	31.9
20 000 – under 100 000 inhabitants	159	20.6	3000 – 4999 €	239	33.5
100 000 – under 500 000 inhabitants	78	10.7	5000 – 8000 €	137	19.2
≥ 500 000 inhabitants	12	1.7	> 8000 €	14	2.0
Education level	nvalid = 727		Pre-existing medical conditions	nvalid = 718
No school-leaving qualifications	1	0.1	0	522	72.7
Lower secondary qualification	16	2.2	≥ 1	196	27.3
Higher secondary qualification	110	15.1	Metabolic disease1	75	38.3
University entrance qualification	65	8.9	Diabetes1	23	11.7
Certified professional training	197	27.1	Hypertension1	22	11.2
Advanced technical college	12	1.7	Lung disease1	22	11.2
University degree	287	39.5	Blood disease1	19	9.7
Doctoral degree	39	5.4	Other pre-existing medical conditions1	105	53.6
Gravidity	nvalid = 723		Parity	nvalid = 722
0	350	48.4	0	301	41.7
≥ 1	373	51.6	≥ 1	421	58.3
Obstetric risks during previous pregnancies	nvalid = 541		Obstetric risks during recent pregnancy	nvalid = 723
0	299	55.3	0	524	72.5
≥ 1	242	44.7	≥ 1	199	27.5
Pregnancy-related complications2	66	27.27	Vaginal bleeding3	76	38.2
Pathological CTG2	52	21.49	Hyperemesis gravidarum3	62	31.2
Birth arrest2	47	19.42	Pregnancy-related complications3	33	16.6
Placental remnants requiring curettage2	39	16.12	Premature labor3	23	11.6
Birth injuries2	38	15.70	Suspected fetal malformations3	10	5.0
Other maternal complications2	163	67.36	Other maternal complications3	44	22.1
Previously diagnosed perinatal mental health disorder	nvalid = 539		Current or history of diagnosed mental disorder	nvalid = 718
No4	478	88.7	No5	595	82.9
Depression4	46	6.3	Depression, dysthymia5	79	11.0
Anxiety4	27	3.7	Anxiety5	26	3.6
Other perinatal mental health disorder4	6	1.1	Other mental health disorder in the present or past5	54	7.5
Marital status	nvalid = 728		Previous psychotherapeutic, psychosomatic, or psychiatric treatment	nvalid = 718
Married and living together with partner	570	78.3	No	552	76.9
In a relationship and living together with partner	136	18.7	Yes	166	23.1
In a relationship and living apart from partner	11	1.5	Current psychotherapeutic or psychiatric treatment	nvalid = 718
Single	10	1.4	No	668	93.0
Widowed	1	0.1	Yes	50	7.0
Notes. f = frequency; %valid = percentage of valid case numbers; nvalid = valid case numbers 1 %valid of category refers to n = 196 of positive responses to item “Pre-existing medical conditions”; multiple choices were possible. The category “other” includes further response categories: Musculoskeletal or rheumatic disease, Gastrointestinal disease, Liver or bladder disease, Malignant tumor disease, Nervous system disease, Kidney disease, Gynecological disease, Other disease. 2 %valid of category refers to n = 242 of positive responses to item “Obstetric risks during previous pregnancies”; multiple choices were possible. The category “other” includes further response categories: Disproportion, Preterm birth after 36th gestational week, Preterm birth after 34th gestational week, Preterm birth before 34th gestational week, Slow labor, Strong bleeding requiring blood transfusions, Infant malformations, Infections, Fetal growth restriction, Other complications of the pregnancy, Other fetal complications, Other maternal complications. 3 %valid of category refers to n = 199 of positive responses to item “Obstetric risks during current pregnancy”; multiple choices were possible. The category “other” includes further response categories: Pathological CTG, Maternal infection, Strong psychological distress, Other infant-related or pregnancy-related complications, Other maternal complications. 4 %valid of category refers to n = 539 of responses to item “Previously diagnosed perinatal mental health disorder”; multiple choices were possible. 5 %valid of category refers to n = 718 of responses to item “Diagnosed mental health disorder in the present or past”; multiple choices were possible. The category “other” includes further response categories: Eating disorder, Compulsive disorder, Other disease.

(2) Intergroup comparisons and correlations: Depending on the scale of measurement of the respective variables, we performed intergroup comparisons (Mann-Whitney U test, Kruskal-Wallis test; see [Table 2] for the corresponding variables) or correlation analyses (Spermanʼs ρ; see [Table 3] for the corresponding variables) to identify specific psychological, medical, obstetric, sociodemographic and self-report characteristics of women that are particularly associated with screening acceptance (usefulness).

Table 2 Group differences regarding screening acceptance (usefulness) using the Mann-Whitney U-test.

Grouping variable	Subgroups	n	Mean rank	U	ptwo-tailed	d	1-β for d = 0.20	1-β for d = 0.50
Notes. n = Group sizes; U = Mann-Whitney U; ptwo-tailed = two-tailed empirical significance level; d = Cohenʼs d; 1-β = statistical power to detect small effects (d = 0.20); PMHP = perinatal mental health problems; significant ptwo-tailed values (ptwo-tailed < 0.05) are in bold and marked with an asterisk.
EPDS cutoff	EPDS ≤ 9	534	346.35	42 107	0.1	0.15	0.6	0.99
	EPDS ≥ 10	171	373.76
Pre-existing medical conditions	No	512	349.53	47 631	0.42	0.07	0.64	0.99
	Yes	193	362.21
Diagnosed mental health disorder in the present or past	No	582	342.93	29 933	< 0.01*	0.35	0.5	0.99
	Yes	123	400.65
Previously diagnosed perinatal mental health disorder	No	470	260.62	11 805	0.03*	0.35	0.3	0.94
	Yes	60	303.75
Current psychotherapy or psychiatric treatment	No	655	348.92	13 701	0.04*	0.38	0.26	0.91
	Yes	50	406.49
Previous psychotherapy or psychiatric treatment	No	542	338.53	36 331	< 0.01*	0.36	0.59	0.99
	Yes	163	401.11
Fertility treatment	No	649	353.42	17 898	0.84	0.01	0.29	0.94
	Yes	56	348.1
Obstetric risks during recent pregnancy	No	508	339.77	43 317	< 0.01*	0.28	0.64	0.99
	Yes	197	387.12
Obstetric risks during previous pregnancies	No	290	250.78	30 531	0.01*	0.24	0.61	0.99
	Yes	239	282.26
Gravidity	Primigravida	340	348.89	60 652	0.57	0.03	0.74	0.99
	Multigravida	365	356.83
Parity	Nullipara	291	353.28	59 865	0.93	0.03	0.72	0.99
	Multipara	413	351.95
Previous miscarriages, stillbirths, or early abortions	No	351	266.91	31 271	0.84	0.01	0.57	0.99
	Yes	180	264.23
Previous knowledge about PMHP	No	306	333.62	55 118	0.03*	0.2	0.73	0.99
	Yes	396	365.31
Stigmatization of PMHP	No	198	305.14	40 717	< 0.01*	0.32	0.64	0.99
	Yes	501	367.73

Table 3 Spearmanʼs ρ correlations with screening acceptance (usefulness).

Variable	N	ρ	ptwo-tailed	1-β
Notes. N = Valid case numbers; ρ = Spearmanʼs ρ correlation coefficient; ptwo-tailed = two-tailed empirical significance level; 1-β = statistical power to detect small effects (ρ = 0.10); a. 1-β for medium-sized effects (ρ = 0.30) > 0.99; significant ptwo-tailed values (ptwo-tailed < 0.05) are in bold and marked with an asterisk.
Level of comfort	704	0.15	< 0.01*	0.76a
Importance of addressing the subject of mental health	705	0.69	< 0.01*	0.76a
Maternal age	703	0.02	0.64	0.76a
Location	704	0.07	0.08	0.76a
Education level	704	0.01	0.77	0.76a
Monthly net household income	692	0.06	0.10	0.75a

(3) Prediction of screening acceptance: In the last step, we performed a hierarchical multiple linear regression analysis to identify the most important predictors of a high screening acceptance among the significant results of the intergroup comparisons and correlations (dependent variable: “usefulness”; see [Table 4] for the predictors).

Table 4 Coefficients of the final regression model of study variables onto screening acceptance (usefulness).

	B	S. E.	β	t	ptwo-tailed	95% CI Lower Bound	95% CI Upper Bound	VIF
Notes. B = nonstandardized regression coefficient; S. E. = Standard error of nonstandardized regression coefficient; β = standardized regression coefficient; t = empirical t-value; ptwo-tailed = two-tailed empirical significance level; 95% CI = 95% confidence interval; VIF = Variance inflation factor; significant ptwo-tailed values (ptwo-tailed < 0.05) are in bold and marked with an asterisk.
Constant	0.38	0.21	0.00	1.79	0.07	− 0.04	0.81	/
Previous psychotherapy or psychiatric treatment	0.16	0.07	0.07	2.30	0.02*	0.02	0.29	1.05
Level of comfort	0.10	0.04	0.09	2.81	0.01*	0.03	0.17	1.05
Importance of addressing the subject of mental health	0.75	0.04	0.67	21.00	0.00*	0.68	0.82	1.04

We chose a backward procedure, as forward procedures bear the risk of neglecting small, but significant effects. Thus, predictors are excluded if the change in the F-value of the respective model step is not statistically significant (p ≥ 0.10). Due to the nonparametric analytic design, the regression analysis serves as an approximation.

The two-sided critical α-error was set to α = 0.05. Due to the exploratory nature of the analyses, the α-errors were not Bonferroni-adjusted. To estimate effect sizes, we computed w² (={χ² ∕ N}) for Kruskal-Wallis tests and Cohenʼs d in approximation for Mann-Whitney U tests. For the correlation analyses, the ρ coefficient and for the regression analysis the β coefficient served as estimator for effect sizes. Furthermore, w² = 0.01, d = 0.20, and ρ or β = 0.10 were interpreted as small; w² = 0.09, d = 0.50, and ρ or β = 0.30 as medium-sized; and w² = 0.25, d = 0.80, and ρ or β = 0.50 as large effects [38].

Results

Descriptive analyses

Sample characteristics

The average age of participants was M = 32.4 years (SD = 4.4 years) with a mean gestational age of M = 19.3 weeks (SD = 5.3 weeks) at the time of screening. At the time of completing the acceptance questionnaire, n = 363 women (50.2%) were still pregnant and n = 360 (49.8%) had already delivered their child. The mean overall EPDS score was M = 6.3 (SD = 5.4). In all, n = 182 (24.9%) of the respondents scored above the cutoff (EPDS ≥ 10), with a mean elevated EPDS score of M = 14.0 (SD = 3.5), compared to a mean of M = 3.7 (SD = 2.8) for the n = 550 (75.1%) women scoring below the cutoff.

Further characteristics of the sample, including socioeconomic status, medical, obstetric, and psychological history, are presented in [Table 1].

Participantsʼ ratings on PND screening during pregnancy

In total, 78.7% of the sample (n = 555 of 705 women) rated the EPDS screening as “useful” or “very useful”. In all, 85.4% (n = 606 of 710 women) found it “easy” or “very easy” to complete the EPDS and 88.3% (n = 628 of 711 women) felt “no discomfort” or “no discomfort at all” when answering the questions of the EPDS. Only 1.3% (n = 9 of 711 women) felt “a lot of discomfort” and 1.8% (n = 13 of 711 women) felt “a little discomfort” while 8.6% (n = 62 of 711 women) felt neither discomfort nor no discomfort. The importance of addressing the subject of mental health with each pregnant woman during pregnancy care was confirmed as “important” or “very important” by 86.5% of the sample (n = 610 of 705 women).

Before participating in the screening program, 43.6% (n = 306 of 702 women) had never heard of perinatal mental health problems. Furthermore, 71.7% (n = 501 of 699 women) believed that perinatal mental health problems are still a taboo subject in society. However, a vast majority of the sample (90.1%, n = 630 of 699 women) confirmed that screening for perinatal mental health problems would raise awareness of that issue.

Factors associated with screening acceptance

Intergroup comparisons and correlation analyses were conducted to determine whether certain factors were particularly related to screening acceptance (usefulness).

Intergroup comparisons

Women with a history of or a current mental health diagnosis rated the usefulness of an EPDS screening higher than women without any diagnoses (p < 0.01, [Table 2]). Likewise, women who were previously diagnosed with any perinatal mental health disorder or who were currently receiving or had received psychotherapy or psychosomatic or psychiatric treatment in the past found an EPDS screening more useful than their respective counterparts (p ≤ 0.04, [Table 2]). Moreover, women who bore obstetric risks during their pregnancies evaluated the usefulness of an EPDS screening as higher than women without these risks (p ≤ 0.01, [Table 2]). Furthermore, women who already had knowledge about perinatal mental health problems or women who considered these problems as stigmatizing found an EPDS screening more useful than their respective counterparts (p ≤ 0.03, [Table 2]). The effect sizes of these differences (Cohenʼs d) were small (d ranged from 0.20 to 0.38). The overall comparison between the subgroups divided by family status was statistically significant and indicated a small effect (χ² = 8.036, df = 3, N = 704, p < 0.05, w² = 0.01). This effect mainly refers to the group comparison between married (n = 551, mean rank = 333.65) and unmarried women (n = 131, mean rank = 374.53), both living together with their partner (U = 31 764.00, p = 0.02, d = 0.22), showing that unmarried women rated the usefulness of the EPDS screening higher. None of the other intergroup comparisons reached statistical significance (p ≥ 0.10).

There were no significant group differences regarding the EPDS cutoff (EPDS ≤ 9 vs. EPDS ≥ 10), pre-existing medical conditions, fertility treatment, gravidity, or parity or regarding previous miscarriages or stillbirths ([Table 2]). The statistical power of these tests increased to a minimum 1-β of 0.91 for medium-sized effects (d = 0.50), which can be evaluated as sufficient.

Correlation analyses

The correlation analyses revealed that the variables level of comfort while completing the EPDS and importance of addressing the subject of mental health during pregnancy care were significantly associated with the rating of usefulness (p < 0.01, [Table 3]). There were no statistically significant associations with maternal age, location, educational level, or monthly net household income (p ≥ 0.08, [Table 3]).

Regression analysis

To identify predictors of screening acceptance among the aforementioned significant effects, we performed a hierarchical multiple linear regression analysis. The final model (step 11, R² _change > −0.01; F_change[1,521] = 1.79, p_change = 0.181) contained the variables previous psychotherapy or psychiatric treatment, level of comfort while completing the EPDS, and importance of addressing the subject of mental health during pregnancy care as significant predictors (p ≤ 0.02, [Table 4]) for screening acceptance. Only the effect size of the last predictor can be evaluated as large (β = 0.67), however. The overall model is significant and explains 48.4% of variance for screening acceptance (R² _adj = 0.48, F[3,522] = 165.25, p < 0.01). Multicollinearity seems not to have biased the estimates as the variance inflation factors (VIF) are low (largest VIF in the start model = 2.34; VIFs in the final model ≈ 1.00).

Discussion

The aim of the present study was

1. to evaluate the acceptance of a routine screening program for perinatal depression in pregnancy care,

2. to identify factors that potentially impact screening acceptance, and

3. to evaluate participantsʼ perspectives on mental health problems during the perinatal period.

The overall acceptance of screening was high: 78.7% (n = 555/705) of the participants in our study rated an EPDS screening as useful and easy to complete (85.4%, n = 606/710) with no feeling of discomfort (88.3%, n = 628/711). Surprisingly, only 56.4% (n = 396/702) of the participants were familiar with perinatal mental health problems and most of the women regarded perinatal mental health problems as stigmatizing (71.7%, n = 501/699). However, a vast majority of 90.1% (n = 630/699) believed that implementing a screening program into routine pregnancy care would raise awareness of perinatal mental health problems.

Regarding factors particularly associated with the acceptance for PND screening among perinatal women, screening acceptance (usefulness) was found to be significantly higher among women who suffered from perinatal and/or mental health disorders and/or received mental health treatment than among those without. Furthermore, ratings were also significantly higher in women who had obstetric risks during their current or a past pregnancy compared to their counterparts. In addition, women with knowledge of perinatal mental health problems and those regarding perinatal mental health problems as stigmatizing rated the usefulness of screening significantly higher. Moreover, the more comfortable a woman felt while completing the EPDS or the higher she rated the importance of addressing mental health during pregnancy care, the higher she rated screening acceptance.

With our final regression model explaining 48.4% of the variance for screening acceptance, our regression analysis suggested that previous psychotherapy or psychiatric treatment, the level of comfort while completing the EPDS, and the importance of addressing mental health during pregnancy care are potential predictors for the acceptance of a PND screening.

Our participants rated the EPDS screening as useful, easy, and comfortable to complete, suggesting that overall acceptance is high among these women. Our findings are in line with previous studies. In the study of Gemmill et al. [25], women rated the completion of the EPDS as at least comfortable (81.2%) and 96.7% of 467 women confirmed it to be “a good idea” to screen all new mothers for postnatal depression. In the study of Buist et al. [24], 93% of the 860 participants found it easy to complete the EPDS and 85% experienced no discomfort. The same applies for the study of Kalra et al., in which most of the participants found it comfortable and not distressing to be asked questions about mental health [26]. All studies concluded that acceptance was high for their survey. A direct comparison, however, is difficult due to the different approaches used for measuring acceptance.

One qualitative analysis including 39 postnatal women concluded that the screening was unacceptable due to an inappropriate setting of the screening venue, the fear of stigmatization, and the questionnaire form of the EPDS [39]. However, their study sample was very small and study results could not be replicated so far.

The high overall acceptance in our study is supported by the strong desire of the participants to integrate the survey about mental health into routine pregnancy care (86.5%, n = 610/705), which also turned out to be the strongest predictor for screening acceptance in our regression analyses. The results are in line with a study from Australia in which 78% of the participants agreed that all women should be “checked for depression” during pregnancy [40]. Adding up these findings with the high acceptance rate of an EPDS screening, it seems plausible that establishing a routine screening procedure would constitute a first important step in integrating mental health evaluation into maternity care.

Women with current or past mental health issues and/or obstetric risks considered general screening for PND useful. The same applied to women who were familiar with perinatal mental health problems and the potential stigma associated with them. Furthermore, women who regarded addressing the subject of mental health during pregnancy care as an important issue found a PND screening useful.

In summary, our data imply that women with mental health issues and/or obstetric risks find the EPDS screening most acceptable. These women are generally at higher risk for developing PND: pre-existing physical or mental health problems are identified risk factors for PND [4] and the prevalence of antenatal depression has been reported to be higher especially in high-risk pregnancies than in those without any risks [41], [42]. If women with these risk factors give high ratings for the acceptance of a PND screening, this might also increase their willingness to participate in the screening, thereby increasing early detection of PND in risk groups, and to follow subsequent diagnostic and therapeutic steps as well. Ultimately, those being screened should approve of the screening in the first place to ensure participation and sustainability. Moreover, our study also demonstrated that screening was seen as a chance to raise awareness of perinatal mental health problems and that women who were aware of perinatal mental health problems found the EPDS screening most acceptable. This closes the circle of screening implementation, raising awareness, and increasing acceptance.

Various studies strongly emphasize well-structured screening programs with subsequent referral to more detailed mental health diagnostics and linkage to therapy options to increase acceptance [24], [34], [43], [44]. Since our EPDS screening was integrated into a program with subsequent diagnostic referral, this might have helped to reach the high acceptance rates. One predictor of screening acceptance that we identified was the level of comfort while completing the EPDS: The less discomfort a woman felt when answering questions about her mental health, the higher she rated the usefulness of the screening. Our findings are in contrast to the study of Gemmill et al. [25], which showed that despite experiencing discomfort while completing the questionnaire, women rated a general PND screening as useful. Previous studies identified several characteristics that increase acceptance rates among women for participating in a PND screening, including creating a sensitive setting, clinician engagement and confidence, and an extended timeframe to complete the screening questions. The following factors were also recommended for a successful implementation of a PND screening: training of the clinical staff, ongoing clinical support, and supervision [26], [28]. Additionally, the timing of the screening seems to play an important role. Venkatesh et al. [44] found that women were more likely to undergo a follow-up mental health evaluation when being screened antenatally rather than postnatally. In our study, all participants were screened antenatally between the 13th and 27th gestational week.

Our results revealed that perinatal mental health problems are still regarded as socially stigmatizing by the majority of our study participants. This social stigma may prevent women from overcoming their personal stigma on mental health issues, fostering the vicious circle of denying symptoms and not seeking help while trying to be a good mother at the same time [12], [45]. Fonseca et al. [10] identified different barriers that prevent women from seeking professional help. The most frequently reported barriers were lack of knowledge, such as difficulties in identifying corresponding symptoms, finding appropriate treatment places, and structural barriers related to financial and time constraints. These findings and our results of only 56.4% of participants who had ever heard about perinatal mental health problems before underscore the need to implement a mental health evaluation in maternity care to reduce the stigma on PND. With 90% of our participants confirming that a screening for PND could raise awareness, implementing a screening would help minimize knowledge barriers. Our data even surpass a previously reported rate of 50% of study participants who believed that the screening process raised their awareness of PND [35]. However, key features of an effective screening include a low-threshold routine and universal offer to break down the aforementioned barriers [24].

In Germany, mental health examinations in pregnancy care cannot be billed, therefore they are missing in medical care. Creating a billing position for an EPDS screening would be the first step to implement mental health evaluation into routine pregnancy care. Yet, a screening only makes sense if subsequent confirmatory diagnostic steps and therapy options are guaranteed [21]. But for mentally ill people, the waiting lists in Germany are still long with average waiting times of 5.7 weeks until the first consultation and 19.9 weeks until the start of the actual therapy [46], and that is only under the premise of having found a therapist. Plus, conventional therapies often only treat the maternal depression itself, neglecting pregnancy- and motherhood-related circumstances. Treating maternal depression, however, even successfully, does not necessarily improve an impaired mother–child relationship, having negative effects on parenting and the childʼs development [47]. Therefore, therapy options with an additional focus on the challenges of pregnancy and parenthood are needed. To alleviate the workload of therapists, digital health solutions should also be considered [30].

The EPDS score itself did not show a significant correlation to the rating of usefulness, which is contrary to previous findings [24]. Our results, however, suggest that, regardless of the current clinical (i.e., symptomatic) mental health status of a woman, the usefulness of an EPDS screening is rated high.

In our study sample, 24.9% (n = 182/732) of the participants reached an EPDS score ≥ 10. We set this cutoff point to increase sensitivity and to include symptoms of a minor depression compared to a cutoff of ≥ 13 for symptoms of major depression (as recommended by the authors of the EPDS, among others) [18], [48]. Similarly, a recent study suggested setting the cutoff for routine perinatal screening to an EPDS score ≥ 10 because subclinical symptoms of mental health problems in the antenatal period can also have adverse effects on maternal and infant outcomes [49].

Our study suggests a high prevalence of PND among pregnant women. In another study in Germany using the same EPDS cutoff, 17% (n = 772) exceeded the cutoff 6 to 8 weeks after delivery [50]. In our sample, the proportion of women exceeding the cutoff was higher, but these numbers are not directly comparable because of different study designs, such as antenatal vs. postnatal screening. Moreover, in our study, only women scoring above the EPDS cutoff were referred to subsequent mental health evaluation and treatment within the program Mind:Pregnancy. It is possible that these women were more willing to complete the voluntary acceptance questionnaire because they benefited more from the program and they may have recalled the EPDS questions more precisely, this possible bias leading to our high acceptance rate and to an overrepresentation of positively screened women and thus, a higher PND prevalence in our sample.

One strength of the present study is the large sample size (N = 732). Only few studies on the acceptance of a screening for PND had larger sample sizes [24], [25], while most studies included significantly fewer participants [26], [35], [39].

Furthermore, the outpatient setting in which the screening was performed represented rural and urban areas with women of diverse socioeconomic backgrounds. Nonetheless, the percentage of academics in our sample is over-proportionally high, which might have affected our results. Mind:Pregnancy is the first large-scale screening program for PND in Germany, providing important information for a German population of perinatal women. Almost all studies on screening programs and their acceptability so far were conducted in English-speaking populations.

Despite the strengths of our study, some limitations have to be considered. As participants filled out the acceptance questionnaire voluntarily, we cannot exclude a participation bias. Furthermore, outpatient gynecologists may have tended to recommend those women to the screening program who, in their estimation, would profit most from study participation, possibly causing selection bias. Due to the cross-sectional study design of the acceptance survey, antepartum and postpartum women were included although screening was performed antenatally, causing a varying interval between screening and acceptance survey. Hence, a recall bias cannot be excluded.

The broad definition of the term “acceptance” is reflected in the differing assessment tools used (e.g., qualitative interviews, quantitative instruments, and interpreting response rates) in the sparse literature on acceptance for perinatal mental health screenings since there is no validated, uniform tool to measure screening acceptance [29]. This makes it difficult to compare our self-generated acceptance questionnaire with other tools.

In this study, we were not able to provide information for nonrespondents of the acceptance survey, hence, no analyses of the full sample (N = 2659) could be conducted, limiting the representativity of our study results. Although nonrespondents were registered in Mind:Pregnancy, only their EPDS score, expected date of delivery, and contact details were collected. Due to our data protection policy and in order to keep screening as simple as possible, sociodemographic, or medical data were not collected generally but only in participants who either provided them voluntarily by participating in the acceptance survey or who were screened positively and agreed to study participation in Mind:Pregnancy. Therefore, we did not have any such data for the full sample.

Conclusion

Our study highlights the need to implement routine screening for PND during pregnancy. The overall acceptance of a PND screening among peripartum women was high. Particularly, women with mental health issues, obstetric risks, and those who are aware of perinatal mental health problems and associated potential stigmatization found screening most useful. Further efforts should be invested in implementing a routine screening program for PND in pregnancy care for early identification of women at risk, which may also help destigmatize perinatal mental health problems. To benefit most from a mental health screening, affected women should be referred for subsequent diagnostic testing and therapy options.

Authorsʼ Contributions

T. G. Trinh: study concept, project development, data collection and management, data analysis, manuscript writing and editing. C. E. Schwarze: project development, manuscript writing and editing. M. Müller: Data analysis, manuscript writing and editing. M. Goetz: project development, manuscript editing. K. Hassdenteufel: manuscript editing. M. Wallwiener: manuscript editing. S. Wallwiener: study concept, project development, and manuscript editing.

Funding

This study is part of the project Mind:Pregnancy (DRKS00017210), which is funded by the Joint Federal committee (01NVF17 034) as the highest decision-making body of the joint self-government of physicians, dentists, hospitals, and health insurance funds. The funding body did not play any role in the design of the study, data collection, analysis, interpretation of data, or writing of the manuscript.

Ethical Approval

This study was performed in line with the principles of the Declaration of Helsinki and approved by the Scientific Ethics Committee of the University of Heidelberg (S-744/2018).

• References

• 1 Gavin NI, Gaynes BN, Lohr KN. et al. Perinatal depression: a systematic review of prevalence and incidence. Obstet Gynecol 2005; 106: 1071-1083
• 2 Dennis C-L, Falah-Hassani K, Shiri R. Prevalence of antenatal and postnatal anxiety: Systematic review and meta-analysis. Br J Psychiatry 2017; 210: 315-323
• 3 Wallwiener S, Goetz M, Lanfer A. et al. Epidemiology of mental disorders during pregnancy and link to birth outcome: a large-scale retrospective observational database study including 38,000 pregnancies. Arch Gynecol Obstet 2019; 299: 755-763
• 4 Howard LM, Molyneaux E, Dennis C-L. et al. Non-psychotic mental disorders in the perinatal period. Lancet 2014; 384: 1775-1788
• 5 Underwood L, Waldie K, DʼSouza S. et al. A review of longitudinal studies on antenatal and postnatal depression. Arch Womens Ment Health 2016; 19: 711-720
• 6 Stein A, Pearson RM, Goodman SH. et al. Effects of perinatal mental disorders on the fetus and child. Lancet 2014; 384: 1800-1819
• 7 Staneva A, Bogossian F, Pritchard M. et al. The effects of maternal depression, anxiety, and perceived stress during pregnancy on preterm birth: A systematic review. Women Birth 2015; 28: 179-193
• 8 Schipper-Kochems S, Fehm T, Bizjak G. et al. Postpartum Depressive Disorder – Psychosomatic Aspects. Geburtshilfe Frauenheilkd 2019; 79: 375-381
• 9 Thio IM, Browne MAO, Coverdale JH. et al. Postnatal depressive symptoms go largely untreated. Soc Psychiatry Psychiatr Epidemiol 2006; 41: 814-818
• 10 Fonseca A, Gorayeb R, Canavarro MC. Womenʼs help-seeking behaviours for depressive symptoms during the perinatal period: Socio-demographic and clinical correlates and perceived barriers to seeking professional help. Midwifery 2015; 31: 1177-1185
• 11 OʼMahen HA, Henshaw E, Jones JM. et al. Stigma and Depression During Pregnancy: Does Race Matter?. J Nerv Ment Dis 2011; 199: 257-262
• 12 Sambrook Smith M, Lawrence V, Sadler E. et al. Barriers to accessing mental health services for women with perinatal mental illness: systematic review and meta-synthesis of qualitative studies in the UK. BMJ Open 2019; 9: e024803
• 13 Ram D, Gowdappa B, Ashoka HG. et al. Psychopharmacoteratophobia: Excessive fear of malformation associated with prescribing psychotropic drugs during pregnancy: An Indian perspective. Indian J Pharmacol 2015; 47: 484-490
• 14 Einarson A, Selby P, Koren G. Abrupt discontinuation of psychotropic drugs during pregnancy: fear of teratogenic risk and impact of counselling. J Psychiatry Neurosci 2001; 26: 44-48
• 15 ACOG. Committee Opinion No. 757: Screening for Perinatal Depression. Obstet Gynecol 2018; 132: e208-e212
• 16 RANZCOG. College Statement: Mental Health Care in the Perinatal Period (C-Obs 48). Melbourne: Royal Australian and New Zealand College of Obstetricians and Gynaecologists; 2018
• 17 Accortt EE, Wong MS. It Is Time for Routine Screening for Perinatal Mood and Anxiety Disorders in Obstetrics and Gynecology Settings. Obstet Gynecol Surv 2017; 72: 553-568
• 18 Cox JL, Holden JM, Sagovsky R. Detection of Postnatal Depression: Development of the 10-item Edinburgh Postnatal Depression Scale. Br J Psychiatry 1987; 150: 782-786
• 19 Matthey S, Fisher J, Rowe H. Using the Edinburgh postnatal depression scale to screen for anxiety disorders: conceptual and methodological considerations. J Affect Disord 2013; 146: 224-230
• 20 Murray D, Cox JL. Screening for depression during pregnancy with the edinburgh depression scale (EDDS). J Reprod Infant Psychol 1990; 8: 99-107
• 21 Milgrom J, Gemmill AW. Screening for perinatal depression. Best Pract Res Clin Obstet Gynaecol 2014; 28: 13-23
• 22 Goodman JH, Tyer-Viola L. Detection, treatment, and referral of perinatal depression and anxiety by obstetrical providers. J Womens Health (Larchmt) 2010; 19: 477-490
• 23 Reilly N, Harris S, Loxton D. et al. The impact of routine assessment of past or current mental health on help-seeking in the perinatal period. Women Birth 2014; 27: e20-e27
• 24 Buist A, Condon J, Brooks J. et al. Acceptability of routine screening for perinatal depression. J Affect Disord 2006; 93: 233-237
• 25 Gemmill AW, Leigh B, Ericksen J. et al. A survey of the clinical acceptability of screening for postnatal depression in depressed and non-depressed women. BMC Public Health 2006; 6: 211
• 26 Kalra H, Reilly N, Austin MP. An evaluation of routine antenatal depression screening and psychosocial assessment in a regional private maternity setting in Australia. Aust N Z J Obstet Gynaecol 2018; 58: 629-635
• 27 Kingston DE, Biringer A, McDonald SW. et al. Preferences for Mental Health Screening Among Pregnant Women: A Cross-Sectional Study. Am J Prev Med 2015; 49: e35-e43
• 28 Brealey SD, Hewitt C, Green JM. et al. Screening for postnatal depression – is it acceptable to women and healthcare professionals? A systematic review and meta-synthesis. J Reprod Infant Psychol 2010; 28: 328-344
• 29 El-Den S, OʼReilly CL, Chen TF. A systematic review on the acceptability of perinatal depression screening. J Affect Disord 2015; 188: 284-303
• 30 Müller M, Matthies LM, Goetz M. et al. Effectiveness and cost-effectiveness of an electronic mindfulness-based intervention (eMBI) on maternal mental health during pregnancy: the mindmom study protocol for a randomized controlled clinical trial. Trials 2020; 21: 933
• 31 Bergant AM, Nguyen T, Heim K. et al. [German language version and validation of the Edinburgh postnatal depression scale]. Dtsch Med Wochenschr 1998; 123: 35-40
• 32 Grassl N, Nees J, Schramm K. et al. A Web-Based Survey Assessing the Attitudes of Health Care Professionals in Germany Toward the Use of Telemedicine in Pregnancy Monitoring: Cross-Sectional Study. JMIR Mhealth Uhealth 2018; 6: e10063
• 33 Prescher S, Deckwart O, Winkler S. et al. Telemedical care: feasibility and perception of the patients and physicians: a survey-based acceptance analysis of the Telemedical Interventional Monitoring in Heart Failure (TIM-HF) trial. Eur J Prev Cardiol 2013; 20: 18-24
• 34 Samuels S, Abrams R, Shengelia R. et al. Integration of geriatric mental health screening into a primary care practice: a patient satisfaction survey. Int J Geriatr Psychiatry 2015; 30: 539-546
• 35 Leigh B, Milgrom J. Acceptability of antenatal screening for depression in routine antenatal care. Aust J Adv Nurs 2007; 24: 14-18
• 36 Faul F, Erdfelder E, Lang AG. et al. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods 2007; 39: 175-191
• 37 Faul F, Erdfelder E, Buchner A. et al. Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses. Behav Res Methods 2009; 41: 1149-1160
• 38 Cohen J. Statistical power analysis for the behavioral sciences. Rev. ed. New York: Lawrence Erlbaum Associates, Inc.; 1977
• 39 Shakespeare J, Blake F, Garcia J. A qualitative study of the acceptability of routine screening of postnatal women using the Edinburgh Postnatal Depression Scale. Br J Gen Pract 2003; 53: 614-619
• 40 Highet N, Gemmill A, Milgrom J. Depression in the Perinatal Period: Awareness, Attitudes and Knowledge in the Australian Population. Aust N Z J Psychiatry 2011; 45: 223-231
• 41 Tsakiridis I, Bousi V, Dagklis T. et al. Epidemiology of antenatal depression among women with high-risk pregnancies due to obstetric complications: a scoping review. Arch Gynecol Obstet 2019; 300: 849-859
• 42 Goetz M, Schiele C, Müller M. et al. Effects of a Brief Electronic Mindfulness-Based Intervention on Relieving Prenatal Depression and Anxiety in Hospitalized High-Risk Pregnant Women: Exploratory Pilot Study. J Med Internet Res 2020; 22: e17593
• 43 Bayrampour H, McNeil DA, Benzies K. et al. A qualitative inquiry on pregnant womenʼs preferences for mental health screening. BMC Pregnancy Childbirth 2017; 17: 339
• 44 Venkatesh KK, Nadel H, Blewett D. et al. Implementation of universal screening for depression during pregnancy: feasibility and impact on obstetric care. Am J Obstet Gynecol 2016; 215: 517.e1-517.e8
• 45 Bennett HA, Boon HS, Romans SE. et al. Becoming the best mom that I can: womenʼs experiences of managing depression during pregnancy – a qualitative study. BMC Womens Health 2007; 7: 13
• 46 Bundespsychotherapeutenkammer. Ein Jahr nach der Reform der Psychotherapie-Richtlinie: Wartezeiten 2018. 11.04.2018. Accessed July 21, 2022 at: https://www.bptk.de/wp-content/uploads/2019/01/20180411_bptk_studie_wartezeiten_2018.pdf
• 47 Forman DR, OʼHara MW, Stuart S. et al. Effective treatment for postpartum depression is not sufficient to improve the developing mother–child relationship. Dev Psychopathol 2007; 19: 585-602
• 48 Matthey S, Henshaw C, Elliott S. et al. Variability in use of cut-off scores and formats on the Edinburgh Postnatal Depression Scale – implications for clinical and research practice. Arch Womens Ment Health 2006; 9: 309-315
• 49 Khanlari S, Barnett Am B, Ogbo FA. et al. Re-examination of perinatal mental health policy frameworks for women signalling distress on the Edinburgh Postnatal Depression Scale (EPDS) completed during their antenatal booking-in consultation: a call for population health intervention. BMC Pregnancy Childbirth 2019; 19: 221
• 50 v Ballestrem CL. Strauss M, Kächele H. Contribution to the epidemiology of postnatal depression in Germany–implications for the utilization of treatment. Arch Womens Ment Health 2005; 8: 29-35