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Comparison of two instruments to track depression symptoms during pregnancy in a sample of pregnant teenagers in Southern Brazil
Journal of Affective Disorders 177 (2015) 95–100
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Comparison of two instruments to track depression symptoms during pregnancy in a sample of pregnant teenagers in Southern Brazil Clarissa de Souza Ribeiro Martins, Janaína Vieira dos Santos Motta, Luciana Avila Quevedo, Mariana Bonati de Matos, Karen Amaral Tavares Pinheiro, Luciano Dias de Mattos Souza, Ricardo Azevedo da Silva, Ricardo Tavares Pinheiro, Fábio Monteiro da Cunha Coelho n Programa de Pós-Graduação em Saúde & Comportamento, Centro de Ciências da Vida e da Saúde, Universidade Católica de Pelotas
art ic l e i nf o
a b s t r a c t
Article history: Received 16 January 2015 Accepted 22 January 2015 Available online 3 February 2015
Introduction: Depression during pregnancy in adolescents is increasing significantly. However, instruments for early depression screening during prenatal care are scarce. Faced this fact, the objective of this research is to identify the best cutoff points for the Edinburgh Postnatal Depression Scale (EPDS) and Beck Depression Inventory (BDI) in a sample of pregnant adolescents. Method: 807 pregnant adolescents, with a mean age of 17 years, met in public antenatal services were evaluated. Two screening scales for depression were analyzed, EPDS and the BDI. These scales had their accuracy measured by AUC of their ROC curve, as well as their respective sensitivity and specificity. Results: In the analysis, the best cutoff for the EPDS wasZ10, in which the sensitivity was 81.1% and specificity 82.7%. For the BDI, it was with recognized the cutoff Z11, sensitivity 86.7% and specificity 73.8%. In the analysis of the ROC AUC, values of 0.89 (CI 0.87–0.92) for the EPDS and BDI for 0.87 (CI 0.84–0.89) were identified compared to the MINI. Limitations: The sample was composed majority by middle and low income adolescent and the study was performed only with pregnant women in the second trimester. Conclusions: The results indicate that both scales have good accuracy in screening of depression in adolescent mothers. However, the EPDS scale shows higher AUC ROC and also better sensitivity and specificity values, the latter being more precise and effective for screening for depression in this population. & 2015 Elsevier B.V. All rights reserved.
Keywords: Pregnant teenager Depression Edinburgh Postnatal Depression Scale (EPDS) Beck Depression Inventory (BDI)
1. Introduction Depression during pregnancy has drawn the attention of researchers in the health area, especially when it occurs in adolescence. Due to its high frequency and significant morbidity, pregnancy at this stage has been documented as a public health problem (Chen et al., 2007). Teenage pregnancy can be considered a stressful event and, therefore, is directly related to the development of psychiatric disorders, including depression (Freitas et al., 2008). In this context, researchers highlight the gestational depression as a disorder so frequent as postpartum depression, but still poorly documented among pregnant adolescents (Koleva et al., 2011; Gibson et al., 2009; Reid and Meadows-Oliver, 2007). Towards this
n Correspondence to: Programa de Pós-Graduação em Saúde & Comportamento, Centro de Ciências da Vida e da Saúde, Universidade Católica de Pelotas. Rua Gonçalves Chaves, 373 sala 411C, CEP: 96015-560, Pelotas, RS, Brazil. Tel.: þ 55 53 2128 8404; fax: þ 55 53 2128 8229. E-mail address: [email protected] (F.M.d.C. Coelho).
http://dx.doi.org/10.1016/j.jad.2015.01.051 0165-0327/& 2015 Elsevier B.V. All rights reserved.
context is possible to observe the importance in the development of studies that analyze the multiple factors arising during pregnancy observed among teenagers. In a previous study conducted with pregnant teenagers, it was found that the majority of cases of depression were not diagnosed during pregnancy and consequently these pregnant women received no treatment or support, increasing the risk of adverse perinatal outcomes for the mother–child dyad (Chalem et al., 2012). Furthermore, research has revealed the existence of a gap in terms of early diagnosis, which could be spanned by the use of comprehensive and easy to handle instruments for detecting depressive symptoms during pregnancy. Other authors point out that the scales for screening depressive symptoms in pregnant teenagers are gaining important role in research, because through structured instruments they seek to reduce the degree of subjectivity in both the data collection and in the interpretation of it (Lewis et al., 1992). Moreover, recent research stresses that the scales for screening for perinatal depression shows adequate diagnostic performances, making it possible to incorporate these evaluations to the pregnancy
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period, paving the way for a better engagement in the treatment of depression, and thus achieving better clinical outcomes (Miller et al., 2009). Between the screening scales for perinatal depression two are being widely used in research, the Edinburgh Postnatal Depression Scale (EPDS) and the Beck Depression Inventory (BDI) (Davis et al., 2013). The first emerged as a tool for detection of postpartum depression, but has been widely used to identify gestational depression (Kirkan et al., 2014; Dibaba et al., 2013; Gordon et al., 2006). The second, BDI, is an instrument of self-assessment, widely used in studies, with which is possible to measure the presence and intensity of depressive symptoms (Caliskan et al., 2007). Although there is a significant amount of validated scales for screening depression in pregnant women, studies show that the scales still present significant variability in their cut-off points (Ji et al., 2011; Tandon et al., 2012). These variation can be identified between different populations and also between the different gestational periods (Birkeland et al., 2005; Ji et al., 2011), showing a theoretical gap to be filled by new research, aiming to demonstrate specific and valid cut-off points between pregnant teenagers with different scales. However data on this issue are scarce, which is limited to studies that comprise the postpartum period (Caputo and Bordin, 2007). Also we stress that few studies have been found in literature regarding pregnant teenagers, justifying the relevance and contribution to health care research, especially the ones of screening for depression in pregnant teenagers. Thus, this research aims to identify the best cut-off points of the Edinburgh Postnatal Depression Scale (EPDS) and Beck Depression Inventory (BDI) in a sample of pregnant teenagers, as well as to compare their diagnostic performances.
2. Methods 2.1. Study type and sampling This is a cross-sectional study, conducted from March 2009 to September 2011 in the city of Pelotas, RS, Southern Brazil. For the selection of the sample we used as inclusion criteria being pregnant, being in the second trimester, being between 13 and 19 years old and doing prenatal care by Brazilian Public Healthcare System, in the urban area of Pelotas. The recruitment was conducted in 47 primary care units and 3 public obstetric clinics. After the identification of participants, already with losses and refusals, the sample was composed of 828 pregnant teenagers. Of this total, we excluded 11 pregnant teenagers who had not responded to the screening scales for the symptoms of gestational depression and the structured clinical interview, resulting in 807 pregnant teenagers. After signing the consent form, a household interview was scheduled to collect sociodemographic characteristics, obstetric chart and psychiatric disorders. The interviews, previously scheduled, were performed during the second trimester of pregnancy. 2.2. Data collection 2.2.1. Socio demographic and obstetric questionnaire A self report questionnaire was used to obtain socio demographic information such as age, marital status, education, family income, occupation and socioeconomic status, which was measured from the classification CCEB (Economic Classification Criterion Brazil, being the highest level of income “A” and the lower “E”). In the same instrument there were also questions about the obstetric history, such as gestational age, pregnancy planning, as the parity, compared to the previous occurrence of previous abortion and the existence of intention to abort.
2.2.2. Screening tools of depression 2.2.2.1. Edinburgh Postnatal Depression Scale (EPDS). The Edinburgh Postnatal Depression Scale (EPDS) was one of the instruments used for screening for depression in the sample. It consists on a self administered scale consisting of 10 items related to depressive symptoms observed in the last seven days, frequent on the postpartum. Although it was initially developed for evaluation of depression in postpartum women (Cox et al., 1987), it has been widely used to evaluate depressive symptoms in pregnant women (Tandon et al., 2012). This instrument shows quick and easy applicability, being useful both for use by healthcare professionals, as for use in community studies. Scores range from 0 to 30, with the recommended cutoff pointZ10 for screening for depression andZ11 for moderate to severe cases (Santos et al., 2007). 2.2.2.2. Beck Depression Inventory (BDI). The Beck Depression Inventory (BDI), developed by Beck et al. (1961), was the second scale used in the study. Despite not having been originally developed to evaluate symptoms in pregnant women, it has often been used for this purpose, being considered as an appropriate and valid instrument for screening depressive symptoms during pregnancy (Marcus et al., 2011). BDI is presented as a structured questionnaire composed of 21 categories of symptoms and attitudes, describing affective and somatic cognitive behavioral manifestations of depression, resuming the symptoms in the last two weeks. Scores on the BDI range between 0 and 63, with cutoff points 10–18 suggestive of mild depression and 19–29 suggestive of moderate depression, the authors emphasize the fact that there is a fixed cut-off point for the diagnosis of depression, considering that this should be based on each study and the characteristics of the sample (Beck et al., 1988). 2.2.3. Structured clinical interview 2.2.3.1. Mini International Neuropsychiatric Interview (MINI). For diagnosis of gestational depression, a version validated for Portuguese of the Mini International Neuropsychiatric Interview (Amorim, 2000) was used. The MINI is a relatively short standardized interview, consistent with the DSM-IV criteria, intended for use in clinical practice and research. In this research, we used only the “major depressive episode” (MDE), which identifies if the episode is current. The clinical interview was applied by trained psychologists with expertise in the application of the instrument, and who were blinded to the results of the screening scales applied. 2.3. Analysis Data were entered in Epi Info (Centers for Disease Control and Prevention, Atlanta, USA), with double entry and consistency checking. Univariate analysis was used to obtain the distribution of the simple frequencies of all single categorical variables. Later this analysis was performed for numerical variables, with results being expressed with means and standard deviations (SD). Sensitivity, specificity and cut-off points for EPDS and BDI were established by the Receiver Operating Characteristic (ROC) analysis, which compares the screening scales with the result of structured interview. The ROC results were expressed with the 95% confidence intervals (95% CI). Through the ROC curve it was possible to identify the cut-off point that best discriminate cases of non cases, by checking the value of the Area Under the Curve (AUC) with corresponding sensitivity and specificity. The AUC provided a reference of the screening instrument discrimination power, this area ranges from 0.5 to a null discrimination power by 1, maximum power (DeLong et al., 1988). Finally, we also report
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the positive predictive value (PPV) and the negative predictive value (NPV) for each instrument.
2.4. Ethical aspects This study was approved by the Research Ethics Committee of the Universidade Católica de Pelotas – UCPel, protocol number 2007/95. The ethical aspects were treated according to current law for the practice of health research, in line with all the ethical principles established by the National Health Council, contained in Resolution number 466/12. The pregnant women identified with depression, according to the MINI instrument, were referred to the Mental Health Service of Universidade Católica de Pelotas (UCPel).
3. Results 3.1. Sample's characteristics We identified 871 pregnant adolescents who corresponded to the criteria for inclusion in the study, forty-three (4.94%) refused to participate, leaving a sample of 828 participants. Of this total were identified 807 teenagers who answered the two scales and standardized clinical interview, which is the sample that was used in this study. Table 1 summarizes the main demographic characteristics of the sample. The mean age of participants was 17.3 years old (SD¼ 1.4), with mean family income of approximately R$ 857.35 (SD¼710.40). The majority of them were declared white (67.8%, n¼543), and 63.0% (n¼ 509) in a stable relationship. Regarding the prevalence of psychiatric disorder, depression, prevalence was 17.7% (n¼143) when measured by MINI.
Table 1 Sample distribution according to the socio-demographic characteristics and obstetric history of the pregnant teenagers seen at prenatal services of the Public Healthcare System (SUS) in Southern Brazil (n¼ 807). Variables Age Up to 15 years old 16–17 years old Above 18 years old Living with partner No Yes Occupationn No occupation Work and/or school Socioeconomic statusn Class A and B Class C Class D and E Education Less than 5 years Between 5 and 8 years Between 8 and 11 years Between 11 and 14 years Parity Multiparae Primiparae Planned pregnancy No Yes
n
%
93 299 415
11.5 37.0 51.4
298 509
37.0 63.0
321 446
41.8 58.2
37 484 267
4.7 61.4 33.8
136 335 266 70
16.9 41.5 32.9 8.7
625 177
78.0 21.9
584 223
72.4 27.6
n There were missing values in these variables. Occupation variable is recorded the largest non-response, totaling 40 individuals (4.9%).
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It was found that the pregnant teenagers had a mean of 23.2 gestational weeks (SD ¼ 5.07) and held approximately 3.28 prenatal visits. The majority (72.4%, n ¼584) stated that the pregnancy was not planned and 78.0% (n ¼621) were primiparous. Regarding the intention to abort, 13.4% (n ¼108) thought of abortion and 2.3% (n ¼18) attempted to abort. 3.2. EPDS and BDI ROC AUC analysis After analyzing the data it was found that the EPDS scale features a ROC AUC of 0.90 (95% CI: 0.87–0.92). These values reflect that the test has good diagnostic validity when compared with the standardized interview MINI. Such information can best be seen in the graphical representation of Fig. 1. Regarding the BDI scale, the ROC AUC coefficient was 0.87 (95% CI: 0.84–0.89). Given that the AUC value was greater than 0.80, it can be found that the BDI instrument also shows good diagnostic validity comparing to MINI interview, as can be seen in Fig. 2. Comparing the ROC AUC of EPDS and BDI scales, the calculation showed that there is a significant statistic difference between the two scales (SD ¼ 0.021), and the highest AUC, was found in the EPDS scale. 3.3. EPDS and BDI sensitivity, specificity, PPV and NPV When we perform the evaluation of sensitivity and specificity in the EPDS scale we identified the point Z10 as the best cut-off point for this population, being it the best balance between sensitivity (81.1%) and specificity (82.7%). The choice of this cut-off point is justified by the lower standard deviation value (SD¼1.1) between the two values. Using this cut-off point, we found a prevalence rate of depression symptoms of 28.6% (95% CI: 25.5–31.8). Regarding the BDI scale, we identified the cut-off point Z11. At this point, the scale has sensitivity of 86.7% and specificity of 73.8% when compared with the MINI results. The identification of this cut-off point for the analysis is supported by the shortest amount of variation between the sensitivity and specificity of all the points (SD ¼2.9). When analyzed the prevalence of depressive symptoms in the sample using the BDI cut-off point Z11, we found a rate of 33.5% (95% CI: 30.2–36.8). Table 2 shows the positive predictive values (PPV) and negatives predictive values (NPV), referring to the cut-off point with greater sensitivity and specificity in the EPDS and BDI. The PPV of
Fig. 1. Area under the Receiver Operating Characteristic curve for the Edinburgh Postnatal Depression Scale (EPDS).
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Fig. 2. Area under the Receiver Operating Characteristic curve for the Beck Depression Inventory (BDI).
Table 2 Positive and negative predictive values for depression in the cutoff points with the best values sensitivity and specificity of each scale. Cut-off point
Positive predictive value (95% Negative predictive value (95% CI) CI)
EPDS Z7 Z8 Z9 Z10 Z11 Z12 Z13 Z14
33.8 37.5 40.2 43.6 47.9 50.8 53.5 55.2
(39.0–440–44.5) (43.2–492–49.1) (46.3–523–52.4) (50.2–562–56.8) (55.3–623–62.5) (59.0–660–66.8) (62.5–705–70.9) (65.1–741–74.1)
95.4 95.0 94.5 93.3 91.6 89.8 88.3 86.9
(97.3–983–98.5) (96.9–989–98.2) (96.5–975–97.9) (95.3–963–96.9) (93.8–958–95.6) (92.2–942–94.1) (90.7–927–92.8) (89.4–914–91.6)
BDI Z7 Z8 Z9 Z10 Z11 Z12 Z13 Z14
27.1 30.2 33.6 36.0 37.0 40.8 40.6 43.0
(31.5–365–36.2) (35.0–400–40.1) (39.0–440–44.5) (41.6–476–47.4) (43.0–490–49.1) (47.4–544–54.1) (47.4–544–54.3) (50.3–573–57.6)
95.3 95.0 94.7 94.2 92.8 92.0 90.7 90.0
(97.4–984–98.7) (97.0–980–98.4) (96.7–987–98.1) (96.3–973–97.7) (95.0–960–96.7) (94.3–963–96.0) (93.1–951–95.0) (92.4–944–94.3)
the EPDS in comparison to the BDI were higher in all cut-off points assessed. Regarding NPV, all cut-off points evaluated remained above 50% in both scales.
4. Discussion Based on the results presented above, we found that EPDS and BDI instruments present adequate power of tracking for depressive symptoms when compared to clinical interview MINI in the sample of pregnant teenagers. Regarding the BDI, it is observed that the results of this study are corroborated with the positioning of Marcus et al. (2011). According to the authors, the scale is an instrument sufficiently effective to detect depressive symptoms in pregnant women. It is emphasized that the BDI showed good sensitivity and specificity (81.1%; 76.8%), and good accuracy, according to its AUC
0.87, when applied to pregnant teenagers (Tape, 2008). It is important to bear in mind that this instrument was not originally designed for the pregnant population. However, other studies (Koleva and Stuart, 2014) have already used the BDI in pregnant teenagers. These authors identified as the cut-off point for the BDI an average of 10.93 (SD ¼7.38), and the age in the sample was 19 years old (SD ¼0.59). The results found by Koleva and Stuart (2014) are similar to the results of this research in two respects. First, because of the proximity at the cut-off point used to detect screening depressive symptoms. Second, because of the parity in terms of age of the population studied. Also, we analyze the ideal cut-off point for the BDI scale for screening depressive symptoms in pregnant women, and we found the cut-off Z11, where the average age of the mothers was 17.3 years old. In another study conducted with pregnant women, which were an average of 27.7 years old, the best average cut-off point found by the authors was 9.04 (SD¼ 6.88) (Koleva et al., 2011). It is believed that the observed difference between the two studies referred mainly to the difference in age of the participants of the research. In another study conducted with pregnant women in three different trimesters of pregnancy and a group of non-pregnant, it was identified as ideal cut-off point for BDI Z18 (Caliskan et al., 2007). The cut-off point that also differs from the ideal found in our study (Z11), and this difference may be due to the heterogeneity of the samples, since the sample in Caliskan et al. (2007) was composed of pregnant women of different age groups, different gestational periods, as well as the fact that there was no reference to a standardized clinical interview used as the gold standard. Regarding the EPDS ideal cut-off point for screening depressive symptoms in pregnant adolescents, the best value found in this population were Z10 (AUC 0.89). It is observed that this information is similar to the one found by the authors in the validation of this scale in Brazil (Santos et al., 2007), when studied women in postpartum. Contrasting these findings, Kuan-Pin et al. (2007) found an ideal cut-off point, with adequate sensitivity and specificity, between 13/14 for the second trimester. But the authors point out that the best cut-off point found for this scale was in the third trimester of pregnancy, where the cut-off point was 12/13, AUC 0.93, sensitivity 0.83 and specificity 0.89. The difference between the cut-off points as well as in their respective sensitivity and specificity can be explained by the cultural differences and the age difference of the samples (Tandon et al., 2012). The present study found a rate of major depressive episode of 17.7% among pregnant teenagers when using the MINI, considering that 28.6% showed depressive symptoms when the EPDS scale was applied, with the cut-off point Z10. Fernandes et al. (2011), in a sample of pregnant women, found 14.4% diagnosed for depression, when using the MINI (Plus). It can also be observed that these authors found as ideal cut-off point for the EPDS scale Z13, with sensitivity 100.0%, specificity of 84.9% and AUC of 0.95. These inequalities between the values in the range of cut-off point can be elucidated by ethnic differences, average gestational age in different populations studied, disparity in the percentage of primiparity and average age of the sample. According to the literature, the EPDS scale presents itself as a good alternative for screening depressive symptoms during pregnancy, but its cut-off point can range in different populations studied (Chaudron et al., 2010). Also, Ji et al. (2011) emphasized that the PC may also differ between the different gestational periods. Ji et al. (2011) when considering the ideal cut-off point for pregnant women in different trimesters of pregnancy with multiple scales, found an ideal cut-off point of 13 for the BDI, with a ROC AUC 0.91 (sensitivity 0.91/specificity 0.76). For the EPDS the best cut-off point was 9, with a ROC AUC of 0.87 (sensitivity 0.89/specificity
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0.66). These values were found in the second trimester, in multiparous pregnant women with an average age of 33 years old. In our research, different cut-off points were found for the same scales at the same gestational stage of the study conducted by Ji et al. (2011), as well as different values for sensitivity, specificity and ROC AUC. However, it is noteworthy that our sample had a different age group (17.3 years old) as well as a different number of interviews conducted in the course of pregnancy. In this sense, this research contributes noting that, when given to the effectiveness of scales, both the BDI and the EPDS present themselves as good instruments for screening for depression in pregnant teenagers, according to their ROC AUC (Tape, 2008). However, the EPDS scale has greater sensitivity, specificity, and higher ROC AUC when compared to the BDI in this population. The EPDS scale presents itself as a well accepted tool by the public, quickly and easily applied, and has been widely used in research and health services, and is available in multiple languages (Santos et al., 2007; Miller et al., 2009; Ji et al., 2011). Regarding the BDI, we can identify that this scale is used in studies with teenagers, but the main disadvantage of this instrument is not distinguish somatic symptoms of the pregnancy period and depressive symptoms, which may overestimate the potential percentage of “sick people” (Bennett et al., 2004; Fernandes et al., 2011; Koleva and Stuart, 2014). There are features in this sample that can be considered strengths of the study. Among them we can highlight the relatively large size of the sample, the use of a structured clinical interview and validated for psychiatric evaluation (MINI), and one of the few studies found analyzing the accuracy of different screening scales of depressive symptoms in pregnant teenagers in public health services. Moreover, the establishment of the optimal cut-off point, although applied on this population, provides elements for the identification and early treatment of depression, which can avoid the adverse effects of this prenatal disease for dyad. However, there are some limitations that should be noted. The first is the fact that the population studied belong, for the most part, to the same social strata, reducing the power of generalization of the results. However, it is emphasized that the results can be extended to other populations. Another limitation is directed to the fact that the scales used to detect depressive symptoms in pregnant women were not originally developed to use with teenagers. On this note, we highlight that there are some research (Ji et al., 2011; Koleva and Stuart, 2014), that have already used these scales in pregnant teenagers.
5. Conclusion The results of this study indicate that the scales for screening depressive symptoms EPDS and BDI, seem to be appropriate in the early identification of these symptoms, if their cut-off points are adjusted to this population. These instruments present low cost and easy application, which enables its use in prenatal care services, thereby identifying a larger number of pregnant teenagers at risk of developing depression during pregnancy. With proper use of these scales they can enable early diagnosis and treatment, minimizing the deleterious effects that depression during this period can bring both to the mother and her baby.
Role of funding source Funding for this study was provided by Brazilian research grants from the Brazilian CNPq, CAPES, PRONEX (CNPq/FAPERGS – Project IVAPSA). The funders had no further role in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication.
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Conflict of interest The authors declare that they have no conflict of interest.
Acknowledgments This work was supported by Brazilian research grants from CNPq, Brazil, CAPES, Brazil, PRONEX (CNPq/FAPERGS — Project IVAPSA).
References Amorim, P., 2000. Mini Internacional Neuropsychiatric Interview (MINI): validação de entrevista breve para diagnóstico de transtornos mentais. Rev. Bras. Psiquiatr. 22, 106–115. Beck, A.T., Ward, C.H., Mendelson, M., Mock, J., Erbauch, G., 1961. An inventory for measuring depression. Arch. Gen. Psychiatry 4, 53–63. Beck, A.T., Epstein, N., Brown, G., Steer, R.A., 1988. The Beck ansiety inventory. J. Consult. Clin. Psychol. 56, 893–897. Bennett, H.A., Einarson, A., Taddio, A., Koren, G., Einarson, T.R., 2004. Prevalence of depression during pregnancy: systematic review. Am. Coll. Obst. Gyn. 103, 698–709. Birkeland, R., Thompson, J.K., Phares, V., 2005. Adolescent Motherhood and Postpartum. Depress. J. Clin. Child Adolesc. Psychol. 34, 292–300. Caliskan, D., Oncu, B., Kose, K., Ocaktan, M.E., Ozdemir, O., 2007. Depression scores and associated factors in pregnant and non-pregnant women: a communitybased study in Turkey. J. Psychosom. Obstet. Gynecol. 28, 195–200. Caputo, V.G., Bordin, I.A., 2007. Mental health problems among pregnant and non pregnant youth. Rev. Saúde Pública 41, 573–581. Chalem, E., Mitsuhiro, S.S., Manzolli, P., Barros, M.C.M., Guinsburg, R., Sass, N., Laranjeira, R., Ferri, C.P., 2012. Underdetection of psychiatric disorders during prenatal care: a survey of adolescents in Sao Paulo, Brazil. J. Adolesc. Health 50, 93–96. Chaudron, L.H., Szilagyi, P.G., Tang, W., Anson, E., Talbot, N.L., Wadkins, H.I.M., Xin, T., Wisner, K.L., 2010. Accuracy of depression screening tools for identifying postpartum depression among urban mothers. Pediatrics 125, 609–617. Chen, X.K., Wen, S.W., Fleming, N., Demissie, K., Rhoads, G.G., Walker, M., 2007. Teenage pregnancy and adverse birth outcomes: a large population based retrospective cohort study. Int. J. Epidemiol. 36, 368–373. Cox, J.L., Holden, J.M., Sagovsky, R., 1987. Detection of postnatal depression: development of the 10-item Edinburgh Postnatal Depression Scale. Br. J. Psychiatry 150, 782–786. Davis, K., Pearlstein, T., Stuart, S., O’Hara, M., Zlotnick, C., 2013. Analysis of brief screening tools for the detection of postpartum depression: comparisons of the PRAMS 6-item instrument, PHQ-9, and structured interviews. Arch. Womens Ment. Health 16, 271–277. DeLong, E., DeLong, D.M., Clarke-Pearson, D., 1988. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44, 837–845. Dibaba, Y., Fantahun, M., Hindin, M.J., 2013. The association of unwanted pregnancy and social support with depressive symptoms in pregnancy: evidence from rural Southwestern Ethiopia. BMC Pregnancy Childbirth 13, 135. Fernandes, M.C., Srinivasan, K., Stein, A.L., Menezes, G., Sumithra, R.S., Ramchandani, P.G., 2011. Assessing prenatal depression in the rural developing world: a comparison of two screening measures. Arch. Womens Ment. Health 14, 209–216. Freitas, G.V.S., Cais, C.F.S., Stefanello, S., Botega, N.J., 2008. Psychosocial conditions and suicidal behavior in pregnant teenagers: a case-control study in Brazil. Eur. Child. Adolesc. Psychiatry 17, 336–342. Gibson, J., McKenzie-McHarg, K., Shakespeare, J., Price, J., Gray, R., 2009. A systematic review of studies validating the Edinburgh Postnatal Depression Scale in antepartum and postpartum women. Acta Psychiatr. Scand. 119, 350–364. Gordon, T.E.J., Cardone, I.A., Kim, J.J., Gordon, S.M., Silver, R.K., 2006. Universal perinatal depression screening in an academic medical center. Obstet. Gynecol. 107, 342–347. Ji, S., Longa, Q., Newport, D.J., Na, H., Knight, B., Zach, E.B., Morris, N.J., Kutner, M., Stowe, Z.N., 2011. Validity of depression rating scales during pregnancy and the postpartum period: impact of trimester and parity. J. Psychiatr. Res. 45, 213–219. Kirkan, T.S., Aydin, N., Yazici, E., Aslan, P.A., Acemoglu, H., Daloglu, A.G., 2014. The depression in women in pregnancy and postpartum period: a follow-up study. Int. J. Soc. Psychiatry 27, 01–07. Koleva, H., Stuart, S., 2014. Risk factors for depressive symptoms in adolescent pregnancy in a late-teen subsample. Arch. Womens Ment. Health 17, 155–158. Koleva, H., Stuart, S., O’Hara, M., Bowman-Reif, J., 2011. Risk factors for depressive symptoms during pregnancy. Arch. Womens Ment. Health 14, 99–105. Lewis, G., Pelosi, A.J., Araya, R., Dunn, G., 1992. Measuring psychiatric disorder in the community: a standardized assessment for use by lay interviewers. Psychol. Med. 22, 465–486. Marcus, S., Lopez, J.F., McDonough, S., Mackenzie, M.J., Flynn, H., Neal Jr., C.R., Gahagan, S., Volling, B., Kaciroti, N., Vazquez, D.M., 2011. Depressive symptoms during pregnancy: impact on neuroendocrine and neonatal outcomes. Infant Behav. Dev. 34, 26–34. Miller, L., Shade, M., Vasireddy, V., 2009. Beyond screening: assessment of perinatal depression in a perinatal care setting. Arch. Womens Ment. Health 12, 329–334. Reid, V., Meadows-Oliver, M., 2007. Postpartum depression in adolescent mothers: an integrative review of the literature. J. Pediatr. Health Care 21, 289–298.
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Santos, I.S., Matijasevich, A., Tavares, B.F., Barros, A.J.D., Botelho, I.P., Lapolli, C., Magalhães, P.V.S., Barbosa, A.P.P.N., Barros, F.C., 2007. Validation of the Edinburgh Postnatal Depression Scale (EPDS) in a sample of mothers from the 2004 Pelotas Birth Cohort Study. Cad. Saúde Pública 23, 2577–2588. Kuan-Pin, S., Chiu, T.H., Huang, C.L., Ho, M., Lee, C.C., Wu, P.L., Lin, C.Y., Liau, C.H., Liao, C.C., Chiu, W.C., Pariante, C.M., 2007. Different cutoff points for different trimesters? The use of Edinburgh Postnatal Depression Scale and Beck
Depression Inventory to screen for depression in pregnant Taiwanese women. Gen. Hosp. Psychiatry 29, 436–441. Tandon, S.D., Cluxton-Keller, F., Leis, J., Le, H.N., Perry, D.F., 2012. A comparison of three screening tools to identify perinatal depression among low-income African American women. J. Affect. Disord. 136, 155–162. Tape, T.G., 2008. The area under an ROC curve. 〈http://gim.unmc.edu/dxtests/roc3. htm〉 (accessed 08.09.14).
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Research report
Comparison of two instruments to track depression symptoms during pregnancy in a sample of pregnant teenagers in Southern Brazil Clarissa de Souza Ribeiro Martins, Janaína Vieira dos Santos Motta, Luciana Avila Quevedo, Mariana Bonati de Matos, Karen Amaral Tavares Pinheiro, Luciano Dias de Mattos Souza, Ricardo Azevedo da Silva, Ricardo Tavares Pinheiro, Fábio Monteiro da Cunha Coelho n Programa de Pós-Graduação em Saúde & Comportamento, Centro de Ciências da Vida e da Saúde, Universidade Católica de Pelotas
art ic l e i nf o
a b s t r a c t
Article history: Received 16 January 2015 Accepted 22 January 2015 Available online 3 February 2015
Introduction: Depression during pregnancy in adolescents is increasing significantly. However, instruments for early depression screening during prenatal care are scarce. Faced this fact, the objective of this research is to identify the best cutoff points for the Edinburgh Postnatal Depression Scale (EPDS) and Beck Depression Inventory (BDI) in a sample of pregnant adolescents. Method: 807 pregnant adolescents, with a mean age of 17 years, met in public antenatal services were evaluated. Two screening scales for depression were analyzed, EPDS and the BDI. These scales had their accuracy measured by AUC of their ROC curve, as well as their respective sensitivity and specificity. Results: In the analysis, the best cutoff for the EPDS wasZ10, in which the sensitivity was 81.1% and specificity 82.7%. For the BDI, it was with recognized the cutoff Z11, sensitivity 86.7% and specificity 73.8%. In the analysis of the ROC AUC, values of 0.89 (CI 0.87–0.92) for the EPDS and BDI for 0.87 (CI 0.84–0.89) were identified compared to the MINI. Limitations: The sample was composed majority by middle and low income adolescent and the study was performed only with pregnant women in the second trimester. Conclusions: The results indicate that both scales have good accuracy in screening of depression in adolescent mothers. However, the EPDS scale shows higher AUC ROC and also better sensitivity and specificity values, the latter being more precise and effective for screening for depression in this population. & 2015 Elsevier B.V. All rights reserved.
Keywords: Pregnant teenager Depression Edinburgh Postnatal Depression Scale (EPDS) Beck Depression Inventory (BDI)
1. Introduction Depression during pregnancy has drawn the attention of researchers in the health area, especially when it occurs in adolescence. Due to its high frequency and significant morbidity, pregnancy at this stage has been documented as a public health problem (Chen et al., 2007). Teenage pregnancy can be considered a stressful event and, therefore, is directly related to the development of psychiatric disorders, including depression (Freitas et al., 2008). In this context, researchers highlight the gestational depression as a disorder so frequent as postpartum depression, but still poorly documented among pregnant adolescents (Koleva et al., 2011; Gibson et al., 2009; Reid and Meadows-Oliver, 2007). Towards this
n Correspondence to: Programa de Pós-Graduação em Saúde & Comportamento, Centro de Ciências da Vida e da Saúde, Universidade Católica de Pelotas. Rua Gonçalves Chaves, 373 sala 411C, CEP: 96015-560, Pelotas, RS, Brazil. Tel.: þ 55 53 2128 8404; fax: þ 55 53 2128 8229. E-mail address: [email protected] (F.M.d.C. Coelho).
http://dx.doi.org/10.1016/j.jad.2015.01.051 0165-0327/& 2015 Elsevier B.V. All rights reserved.
context is possible to observe the importance in the development of studies that analyze the multiple factors arising during pregnancy observed among teenagers. In a previous study conducted with pregnant teenagers, it was found that the majority of cases of depression were not diagnosed during pregnancy and consequently these pregnant women received no treatment or support, increasing the risk of adverse perinatal outcomes for the mother–child dyad (Chalem et al., 2012). Furthermore, research has revealed the existence of a gap in terms of early diagnosis, which could be spanned by the use of comprehensive and easy to handle instruments for detecting depressive symptoms during pregnancy. Other authors point out that the scales for screening depressive symptoms in pregnant teenagers are gaining important role in research, because through structured instruments they seek to reduce the degree of subjectivity in both the data collection and in the interpretation of it (Lewis et al., 1992). Moreover, recent research stresses that the scales for screening for perinatal depression shows adequate diagnostic performances, making it possible to incorporate these evaluations to the pregnancy
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period, paving the way for a better engagement in the treatment of depression, and thus achieving better clinical outcomes (Miller et al., 2009). Between the screening scales for perinatal depression two are being widely used in research, the Edinburgh Postnatal Depression Scale (EPDS) and the Beck Depression Inventory (BDI) (Davis et al., 2013). The first emerged as a tool for detection of postpartum depression, but has been widely used to identify gestational depression (Kirkan et al., 2014; Dibaba et al., 2013; Gordon et al., 2006). The second, BDI, is an instrument of self-assessment, widely used in studies, with which is possible to measure the presence and intensity of depressive symptoms (Caliskan et al., 2007). Although there is a significant amount of validated scales for screening depression in pregnant women, studies show that the scales still present significant variability in their cut-off points (Ji et al., 2011; Tandon et al., 2012). These variation can be identified between different populations and also between the different gestational periods (Birkeland et al., 2005; Ji et al., 2011), showing a theoretical gap to be filled by new research, aiming to demonstrate specific and valid cut-off points between pregnant teenagers with different scales. However data on this issue are scarce, which is limited to studies that comprise the postpartum period (Caputo and Bordin, 2007). Also we stress that few studies have been found in literature regarding pregnant teenagers, justifying the relevance and contribution to health care research, especially the ones of screening for depression in pregnant teenagers. Thus, this research aims to identify the best cut-off points of the Edinburgh Postnatal Depression Scale (EPDS) and Beck Depression Inventory (BDI) in a sample of pregnant teenagers, as well as to compare their diagnostic performances.
2. Methods 2.1. Study type and sampling This is a cross-sectional study, conducted from March 2009 to September 2011 in the city of Pelotas, RS, Southern Brazil. For the selection of the sample we used as inclusion criteria being pregnant, being in the second trimester, being between 13 and 19 years old and doing prenatal care by Brazilian Public Healthcare System, in the urban area of Pelotas. The recruitment was conducted in 47 primary care units and 3 public obstetric clinics. After the identification of participants, already with losses and refusals, the sample was composed of 828 pregnant teenagers. Of this total, we excluded 11 pregnant teenagers who had not responded to the screening scales for the symptoms of gestational depression and the structured clinical interview, resulting in 807 pregnant teenagers. After signing the consent form, a household interview was scheduled to collect sociodemographic characteristics, obstetric chart and psychiatric disorders. The interviews, previously scheduled, were performed during the second trimester of pregnancy. 2.2. Data collection 2.2.1. Socio demographic and obstetric questionnaire A self report questionnaire was used to obtain socio demographic information such as age, marital status, education, family income, occupation and socioeconomic status, which was measured from the classification CCEB (Economic Classification Criterion Brazil, being the highest level of income “A” and the lower “E”). In the same instrument there were also questions about the obstetric history, such as gestational age, pregnancy planning, as the parity, compared to the previous occurrence of previous abortion and the existence of intention to abort.
2.2.2. Screening tools of depression 2.2.2.1. Edinburgh Postnatal Depression Scale (EPDS). The Edinburgh Postnatal Depression Scale (EPDS) was one of the instruments used for screening for depression in the sample. It consists on a self administered scale consisting of 10 items related to depressive symptoms observed in the last seven days, frequent on the postpartum. Although it was initially developed for evaluation of depression in postpartum women (Cox et al., 1987), it has been widely used to evaluate depressive symptoms in pregnant women (Tandon et al., 2012). This instrument shows quick and easy applicability, being useful both for use by healthcare professionals, as for use in community studies. Scores range from 0 to 30, with the recommended cutoff pointZ10 for screening for depression andZ11 for moderate to severe cases (Santos et al., 2007). 2.2.2.2. Beck Depression Inventory (BDI). The Beck Depression Inventory (BDI), developed by Beck et al. (1961), was the second scale used in the study. Despite not having been originally developed to evaluate symptoms in pregnant women, it has often been used for this purpose, being considered as an appropriate and valid instrument for screening depressive symptoms during pregnancy (Marcus et al., 2011). BDI is presented as a structured questionnaire composed of 21 categories of symptoms and attitudes, describing affective and somatic cognitive behavioral manifestations of depression, resuming the symptoms in the last two weeks. Scores on the BDI range between 0 and 63, with cutoff points 10–18 suggestive of mild depression and 19–29 suggestive of moderate depression, the authors emphasize the fact that there is a fixed cut-off point for the diagnosis of depression, considering that this should be based on each study and the characteristics of the sample (Beck et al., 1988). 2.2.3. Structured clinical interview 2.2.3.1. Mini International Neuropsychiatric Interview (MINI). For diagnosis of gestational depression, a version validated for Portuguese of the Mini International Neuropsychiatric Interview (Amorim, 2000) was used. The MINI is a relatively short standardized interview, consistent with the DSM-IV criteria, intended for use in clinical practice and research. In this research, we used only the “major depressive episode” (MDE), which identifies if the episode is current. The clinical interview was applied by trained psychologists with expertise in the application of the instrument, and who were blinded to the results of the screening scales applied. 2.3. Analysis Data were entered in Epi Info (Centers for Disease Control and Prevention, Atlanta, USA), with double entry and consistency checking. Univariate analysis was used to obtain the distribution of the simple frequencies of all single categorical variables. Later this analysis was performed for numerical variables, with results being expressed with means and standard deviations (SD). Sensitivity, specificity and cut-off points for EPDS and BDI were established by the Receiver Operating Characteristic (ROC) analysis, which compares the screening scales with the result of structured interview. The ROC results were expressed with the 95% confidence intervals (95% CI). Through the ROC curve it was possible to identify the cut-off point that best discriminate cases of non cases, by checking the value of the Area Under the Curve (AUC) with corresponding sensitivity and specificity. The AUC provided a reference of the screening instrument discrimination power, this area ranges from 0.5 to a null discrimination power by 1, maximum power (DeLong et al., 1988). Finally, we also report
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the positive predictive value (PPV) and the negative predictive value (NPV) for each instrument.
2.4. Ethical aspects This study was approved by the Research Ethics Committee of the Universidade Católica de Pelotas – UCPel, protocol number 2007/95. The ethical aspects were treated according to current law for the practice of health research, in line with all the ethical principles established by the National Health Council, contained in Resolution number 466/12. The pregnant women identified with depression, according to the MINI instrument, were referred to the Mental Health Service of Universidade Católica de Pelotas (UCPel).
3. Results 3.1. Sample's characteristics We identified 871 pregnant adolescents who corresponded to the criteria for inclusion in the study, forty-three (4.94%) refused to participate, leaving a sample of 828 participants. Of this total were identified 807 teenagers who answered the two scales and standardized clinical interview, which is the sample that was used in this study. Table 1 summarizes the main demographic characteristics of the sample. The mean age of participants was 17.3 years old (SD¼ 1.4), with mean family income of approximately R$ 857.35 (SD¼710.40). The majority of them were declared white (67.8%, n¼543), and 63.0% (n¼ 509) in a stable relationship. Regarding the prevalence of psychiatric disorder, depression, prevalence was 17.7% (n¼143) when measured by MINI.
Table 1 Sample distribution according to the socio-demographic characteristics and obstetric history of the pregnant teenagers seen at prenatal services of the Public Healthcare System (SUS) in Southern Brazil (n¼ 807). Variables Age Up to 15 years old 16–17 years old Above 18 years old Living with partner No Yes Occupationn No occupation Work and/or school Socioeconomic statusn Class A and B Class C Class D and E Education Less than 5 years Between 5 and 8 years Between 8 and 11 years Between 11 and 14 years Parity Multiparae Primiparae Planned pregnancy No Yes
n
%
93 299 415
11.5 37.0 51.4
298 509
37.0 63.0
321 446
41.8 58.2
37 484 267
4.7 61.4 33.8
136 335 266 70
16.9 41.5 32.9 8.7
625 177
78.0 21.9
584 223
72.4 27.6
n There were missing values in these variables. Occupation variable is recorded the largest non-response, totaling 40 individuals (4.9%).
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It was found that the pregnant teenagers had a mean of 23.2 gestational weeks (SD ¼ 5.07) and held approximately 3.28 prenatal visits. The majority (72.4%, n ¼584) stated that the pregnancy was not planned and 78.0% (n ¼621) were primiparous. Regarding the intention to abort, 13.4% (n ¼108) thought of abortion and 2.3% (n ¼18) attempted to abort. 3.2. EPDS and BDI ROC AUC analysis After analyzing the data it was found that the EPDS scale features a ROC AUC of 0.90 (95% CI: 0.87–0.92). These values reflect that the test has good diagnostic validity when compared with the standardized interview MINI. Such information can best be seen in the graphical representation of Fig. 1. Regarding the BDI scale, the ROC AUC coefficient was 0.87 (95% CI: 0.84–0.89). Given that the AUC value was greater than 0.80, it can be found that the BDI instrument also shows good diagnostic validity comparing to MINI interview, as can be seen in Fig. 2. Comparing the ROC AUC of EPDS and BDI scales, the calculation showed that there is a significant statistic difference between the two scales (SD ¼ 0.021), and the highest AUC, was found in the EPDS scale. 3.3. EPDS and BDI sensitivity, specificity, PPV and NPV When we perform the evaluation of sensitivity and specificity in the EPDS scale we identified the point Z10 as the best cut-off point for this population, being it the best balance between sensitivity (81.1%) and specificity (82.7%). The choice of this cut-off point is justified by the lower standard deviation value (SD¼1.1) between the two values. Using this cut-off point, we found a prevalence rate of depression symptoms of 28.6% (95% CI: 25.5–31.8). Regarding the BDI scale, we identified the cut-off point Z11. At this point, the scale has sensitivity of 86.7% and specificity of 73.8% when compared with the MINI results. The identification of this cut-off point for the analysis is supported by the shortest amount of variation between the sensitivity and specificity of all the points (SD ¼2.9). When analyzed the prevalence of depressive symptoms in the sample using the BDI cut-off point Z11, we found a rate of 33.5% (95% CI: 30.2–36.8). Table 2 shows the positive predictive values (PPV) and negatives predictive values (NPV), referring to the cut-off point with greater sensitivity and specificity in the EPDS and BDI. The PPV of
Fig. 1. Area under the Receiver Operating Characteristic curve for the Edinburgh Postnatal Depression Scale (EPDS).
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Fig. 2. Area under the Receiver Operating Characteristic curve for the Beck Depression Inventory (BDI).
Table 2 Positive and negative predictive values for depression in the cutoff points with the best values sensitivity and specificity of each scale. Cut-off point
Positive predictive value (95% Negative predictive value (95% CI) CI)
EPDS Z7 Z8 Z9 Z10 Z11 Z12 Z13 Z14
33.8 37.5 40.2 43.6 47.9 50.8 53.5 55.2
(39.0–440–44.5) (43.2–492–49.1) (46.3–523–52.4) (50.2–562–56.8) (55.3–623–62.5) (59.0–660–66.8) (62.5–705–70.9) (65.1–741–74.1)
95.4 95.0 94.5 93.3 91.6 89.8 88.3 86.9
(97.3–983–98.5) (96.9–989–98.2) (96.5–975–97.9) (95.3–963–96.9) (93.8–958–95.6) (92.2–942–94.1) (90.7–927–92.8) (89.4–914–91.6)
BDI Z7 Z8 Z9 Z10 Z11 Z12 Z13 Z14
27.1 30.2 33.6 36.0 37.0 40.8 40.6 43.0
(31.5–365–36.2) (35.0–400–40.1) (39.0–440–44.5) (41.6–476–47.4) (43.0–490–49.1) (47.4–544–54.1) (47.4–544–54.3) (50.3–573–57.6)
95.3 95.0 94.7 94.2 92.8 92.0 90.7 90.0
(97.4–984–98.7) (97.0–980–98.4) (96.7–987–98.1) (96.3–973–97.7) (95.0–960–96.7) (94.3–963–96.0) (93.1–951–95.0) (92.4–944–94.3)
the EPDS in comparison to the BDI were higher in all cut-off points assessed. Regarding NPV, all cut-off points evaluated remained above 50% in both scales.
4. Discussion Based on the results presented above, we found that EPDS and BDI instruments present adequate power of tracking for depressive symptoms when compared to clinical interview MINI in the sample of pregnant teenagers. Regarding the BDI, it is observed that the results of this study are corroborated with the positioning of Marcus et al. (2011). According to the authors, the scale is an instrument sufficiently effective to detect depressive symptoms in pregnant women. It is emphasized that the BDI showed good sensitivity and specificity (81.1%; 76.8%), and good accuracy, according to its AUC
0.87, when applied to pregnant teenagers (Tape, 2008). It is important to bear in mind that this instrument was not originally designed for the pregnant population. However, other studies (Koleva and Stuart, 2014) have already used the BDI in pregnant teenagers. These authors identified as the cut-off point for the BDI an average of 10.93 (SD ¼7.38), and the age in the sample was 19 years old (SD ¼0.59). The results found by Koleva and Stuart (2014) are similar to the results of this research in two respects. First, because of the proximity at the cut-off point used to detect screening depressive symptoms. Second, because of the parity in terms of age of the population studied. Also, we analyze the ideal cut-off point for the BDI scale for screening depressive symptoms in pregnant women, and we found the cut-off Z11, where the average age of the mothers was 17.3 years old. In another study conducted with pregnant women, which were an average of 27.7 years old, the best average cut-off point found by the authors was 9.04 (SD¼ 6.88) (Koleva et al., 2011). It is believed that the observed difference between the two studies referred mainly to the difference in age of the participants of the research. In another study conducted with pregnant women in three different trimesters of pregnancy and a group of non-pregnant, it was identified as ideal cut-off point for BDI Z18 (Caliskan et al., 2007). The cut-off point that also differs from the ideal found in our study (Z11), and this difference may be due to the heterogeneity of the samples, since the sample in Caliskan et al. (2007) was composed of pregnant women of different age groups, different gestational periods, as well as the fact that there was no reference to a standardized clinical interview used as the gold standard. Regarding the EPDS ideal cut-off point for screening depressive symptoms in pregnant adolescents, the best value found in this population were Z10 (AUC 0.89). It is observed that this information is similar to the one found by the authors in the validation of this scale in Brazil (Santos et al., 2007), when studied women in postpartum. Contrasting these findings, Kuan-Pin et al. (2007) found an ideal cut-off point, with adequate sensitivity and specificity, between 13/14 for the second trimester. But the authors point out that the best cut-off point found for this scale was in the third trimester of pregnancy, where the cut-off point was 12/13, AUC 0.93, sensitivity 0.83 and specificity 0.89. The difference between the cut-off points as well as in their respective sensitivity and specificity can be explained by the cultural differences and the age difference of the samples (Tandon et al., 2012). The present study found a rate of major depressive episode of 17.7% among pregnant teenagers when using the MINI, considering that 28.6% showed depressive symptoms when the EPDS scale was applied, with the cut-off point Z10. Fernandes et al. (2011), in a sample of pregnant women, found 14.4% diagnosed for depression, when using the MINI (Plus). It can also be observed that these authors found as ideal cut-off point for the EPDS scale Z13, with sensitivity 100.0%, specificity of 84.9% and AUC of 0.95. These inequalities between the values in the range of cut-off point can be elucidated by ethnic differences, average gestational age in different populations studied, disparity in the percentage of primiparity and average age of the sample. According to the literature, the EPDS scale presents itself as a good alternative for screening depressive symptoms during pregnancy, but its cut-off point can range in different populations studied (Chaudron et al., 2010). Also, Ji et al. (2011) emphasized that the PC may also differ between the different gestational periods. Ji et al. (2011) when considering the ideal cut-off point for pregnant women in different trimesters of pregnancy with multiple scales, found an ideal cut-off point of 13 for the BDI, with a ROC AUC 0.91 (sensitivity 0.91/specificity 0.76). For the EPDS the best cut-off point was 9, with a ROC AUC of 0.87 (sensitivity 0.89/specificity
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0.66). These values were found in the second trimester, in multiparous pregnant women with an average age of 33 years old. In our research, different cut-off points were found for the same scales at the same gestational stage of the study conducted by Ji et al. (2011), as well as different values for sensitivity, specificity and ROC AUC. However, it is noteworthy that our sample had a different age group (17.3 years old) as well as a different number of interviews conducted in the course of pregnancy. In this sense, this research contributes noting that, when given to the effectiveness of scales, both the BDI and the EPDS present themselves as good instruments for screening for depression in pregnant teenagers, according to their ROC AUC (Tape, 2008). However, the EPDS scale has greater sensitivity, specificity, and higher ROC AUC when compared to the BDI in this population. The EPDS scale presents itself as a well accepted tool by the public, quickly and easily applied, and has been widely used in research and health services, and is available in multiple languages (Santos et al., 2007; Miller et al., 2009; Ji et al., 2011). Regarding the BDI, we can identify that this scale is used in studies with teenagers, but the main disadvantage of this instrument is not distinguish somatic symptoms of the pregnancy period and depressive symptoms, which may overestimate the potential percentage of “sick people” (Bennett et al., 2004; Fernandes et al., 2011; Koleva and Stuart, 2014). There are features in this sample that can be considered strengths of the study. Among them we can highlight the relatively large size of the sample, the use of a structured clinical interview and validated for psychiatric evaluation (MINI), and one of the few studies found analyzing the accuracy of different screening scales of depressive symptoms in pregnant teenagers in public health services. Moreover, the establishment of the optimal cut-off point, although applied on this population, provides elements for the identification and early treatment of depression, which can avoid the adverse effects of this prenatal disease for dyad. However, there are some limitations that should be noted. The first is the fact that the population studied belong, for the most part, to the same social strata, reducing the power of generalization of the results. However, it is emphasized that the results can be extended to other populations. Another limitation is directed to the fact that the scales used to detect depressive symptoms in pregnant women were not originally developed to use with teenagers. On this note, we highlight that there are some research (Ji et al., 2011; Koleva and Stuart, 2014), that have already used these scales in pregnant teenagers.
5. Conclusion The results of this study indicate that the scales for screening depressive symptoms EPDS and BDI, seem to be appropriate in the early identification of these symptoms, if their cut-off points are adjusted to this population. These instruments present low cost and easy application, which enables its use in prenatal care services, thereby identifying a larger number of pregnant teenagers at risk of developing depression during pregnancy. With proper use of these scales they can enable early diagnosis and treatment, minimizing the deleterious effects that depression during this period can bring both to the mother and her baby.
Role of funding source Funding for this study was provided by Brazilian research grants from the Brazilian CNPq, CAPES, PRONEX (CNPq/FAPERGS – Project IVAPSA). The funders had no further role in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication.
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Conflict of interest The authors declare that they have no conflict of interest.
Acknowledgments This work was supported by Brazilian research grants from CNPq, Brazil, CAPES, Brazil, PRONEX (CNPq/FAPERGS — Project IVAPSA).
References Amorim, P., 2000. Mini Internacional Neuropsychiatric Interview (MINI): validação de entrevista breve para diagnóstico de transtornos mentais. Rev. Bras. Psiquiatr. 22, 106–115. Beck, A.T., Ward, C.H., Mendelson, M., Mock, J., Erbauch, G., 1961. An inventory for measuring depression. Arch. Gen. Psychiatry 4, 53–63. Beck, A.T., Epstein, N., Brown, G., Steer, R.A., 1988. The Beck ansiety inventory. J. Consult. Clin. Psychol. 56, 893–897. Bennett, H.A., Einarson, A., Taddio, A., Koren, G., Einarson, T.R., 2004. Prevalence of depression during pregnancy: systematic review. Am. Coll. Obst. Gyn. 103, 698–709. Birkeland, R., Thompson, J.K., Phares, V., 2005. Adolescent Motherhood and Postpartum. Depress. J. Clin. Child Adolesc. Psychol. 34, 292–300. Caliskan, D., Oncu, B., Kose, K., Ocaktan, M.E., Ozdemir, O., 2007. Depression scores and associated factors in pregnant and non-pregnant women: a communitybased study in Turkey. J. Psychosom. Obstet. Gynecol. 28, 195–200. Caputo, V.G., Bordin, I.A., 2007. Mental health problems among pregnant and non pregnant youth. Rev. Saúde Pública 41, 573–581. Chalem, E., Mitsuhiro, S.S., Manzolli, P., Barros, M.C.M., Guinsburg, R., Sass, N., Laranjeira, R., Ferri, C.P., 2012. Underdetection of psychiatric disorders during prenatal care: a survey of adolescents in Sao Paulo, Brazil. J. Adolesc. Health 50, 93–96. Chaudron, L.H., Szilagyi, P.G., Tang, W., Anson, E., Talbot, N.L., Wadkins, H.I.M., Xin, T., Wisner, K.L., 2010. Accuracy of depression screening tools for identifying postpartum depression among urban mothers. Pediatrics 125, 609–617. Chen, X.K., Wen, S.W., Fleming, N., Demissie, K., Rhoads, G.G., Walker, M., 2007. Teenage pregnancy and adverse birth outcomes: a large population based retrospective cohort study. Int. J. Epidemiol. 36, 368–373. Cox, J.L., Holden, J.M., Sagovsky, R., 1987. Detection of postnatal depression: development of the 10-item Edinburgh Postnatal Depression Scale. Br. J. Psychiatry 150, 782–786. Davis, K., Pearlstein, T., Stuart, S., O’Hara, M., Zlotnick, C., 2013. Analysis of brief screening tools for the detection of postpartum depression: comparisons of the PRAMS 6-item instrument, PHQ-9, and structured interviews. Arch. Womens Ment. Health 16, 271–277. DeLong, E., DeLong, D.M., Clarke-Pearson, D., 1988. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44, 837–845. Dibaba, Y., Fantahun, M., Hindin, M.J., 2013. The association of unwanted pregnancy and social support with depressive symptoms in pregnancy: evidence from rural Southwestern Ethiopia. BMC Pregnancy Childbirth 13, 135. Fernandes, M.C., Srinivasan, K., Stein, A.L., Menezes, G., Sumithra, R.S., Ramchandani, P.G., 2011. Assessing prenatal depression in the rural developing world: a comparison of two screening measures. Arch. Womens Ment. Health 14, 209–216. Freitas, G.V.S., Cais, C.F.S., Stefanello, S., Botega, N.J., 2008. Psychosocial conditions and suicidal behavior in pregnant teenagers: a case-control study in Brazil. Eur. Child. Adolesc. Psychiatry 17, 336–342. Gibson, J., McKenzie-McHarg, K., Shakespeare, J., Price, J., Gray, R., 2009. A systematic review of studies validating the Edinburgh Postnatal Depression Scale in antepartum and postpartum women. Acta Psychiatr. Scand. 119, 350–364. Gordon, T.E.J., Cardone, I.A., Kim, J.J., Gordon, S.M., Silver, R.K., 2006. Universal perinatal depression screening in an academic medical center. Obstet. Gynecol. 107, 342–347. Ji, S., Longa, Q., Newport, D.J., Na, H., Knight, B., Zach, E.B., Morris, N.J., Kutner, M., Stowe, Z.N., 2011. Validity of depression rating scales during pregnancy and the postpartum period: impact of trimester and parity. J. Psychiatr. Res. 45, 213–219. Kirkan, T.S., Aydin, N., Yazici, E., Aslan, P.A., Acemoglu, H., Daloglu, A.G., 2014. The depression in women in pregnancy and postpartum period: a follow-up study. Int. J. Soc. Psychiatry 27, 01–07. Koleva, H., Stuart, S., 2014. Risk factors for depressive symptoms in adolescent pregnancy in a late-teen subsample. Arch. Womens Ment. Health 17, 155–158. Koleva, H., Stuart, S., O’Hara, M., Bowman-Reif, J., 2011. Risk factors for depressive symptoms during pregnancy. Arch. Womens Ment. Health 14, 99–105. Lewis, G., Pelosi, A.J., Araya, R., Dunn, G., 1992. Measuring psychiatric disorder in the community: a standardized assessment for use by lay interviewers. Psychol. Med. 22, 465–486. Marcus, S., Lopez, J.F., McDonough, S., Mackenzie, M.J., Flynn, H., Neal Jr., C.R., Gahagan, S., Volling, B., Kaciroti, N., Vazquez, D.M., 2011. Depressive symptoms during pregnancy: impact on neuroendocrine and neonatal outcomes. Infant Behav. Dev. 34, 26–34. Miller, L., Shade, M., Vasireddy, V., 2009. Beyond screening: assessment of perinatal depression in a perinatal care setting. Arch. Womens Ment. Health 12, 329–334. Reid, V., Meadows-Oliver, M., 2007. Postpartum depression in adolescent mothers: an integrative review of the literature. J. Pediatr. Health Care 21, 289–298.
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C.d.S.R. Martins et al. / Journal of Affective Disorders 177 (2015) 95–100
Santos, I.S., Matijasevich, A., Tavares, B.F., Barros, A.J.D., Botelho, I.P., Lapolli, C., Magalhães, P.V.S., Barbosa, A.P.P.N., Barros, F.C., 2007. Validation of the Edinburgh Postnatal Depression Scale (EPDS) in a sample of mothers from the 2004 Pelotas Birth Cohort Study. Cad. Saúde Pública 23, 2577–2588. Kuan-Pin, S., Chiu, T.H., Huang, C.L., Ho, M., Lee, C.C., Wu, P.L., Lin, C.Y., Liau, C.H., Liao, C.C., Chiu, W.C., Pariante, C.M., 2007. Different cutoff points for different trimesters? The use of Edinburgh Postnatal Depression Scale and Beck
Depression Inventory to screen for depression in pregnant Taiwanese women. Gen. Hosp. Psychiatry 29, 436–441. Tandon, S.D., Cluxton-Keller, F., Leis, J., Le, H.N., Perry, D.F., 2012. A comparison of three screening tools to identify perinatal depression among low-income African American women. J. Affect. Disord. 136, 155–162. Tape, T.G., 2008. The area under an ROC curve. 〈http://gim.unmc.edu/dxtests/roc3. htm〉 (accessed 08.09.14).