Frontiers in Psychiatry is proud to present our Psychometrics series. This series of Article Collections will deal with the definition and measurement of clinical constructs. The Psychometrics in Perinatal Psychiatry Article Collection aims to collect original research and review articles on new developments and applications of psychometrics and psychiatric assessment in Perinatal Psychiatry. Articles can include, but are not limited to, the following topics: -Clinical psychometrics -The challenge of quantitative psychiatry and measurement -Application, validity, and reliability of psychiatric scales -Measuring and modeling

University of Malaga

Leonard M. Miller School of Medicine, University of Miami

University of Cádiz

Frontiers in Psychiatry

Perinatal Psychiatry

Psychometrics in Psychiatry 2022: Perinatal Psychiatry

IntroductionThere is a need to implement routine perinatal mental health screening in Spain. Therefore, it is necessary to systematise the detection of depressive and anxious symptoms in pregnancy and postpartum using the same instrument. The Edinburgh Postnatal Stress Depression Scale (EPDS) is frequently used as a rapid, effective and cross-culturally validated screening tool for perinatal depression. In several countries, an Anxiety subscale, the EPDS-A, was identified within the EPDS. Although the factorial structure of the EPDS has been investigated in Spanish population, the EPDS-A has not yet been validated. This study aimed to validate the EPDS-A as a measure of perinatal anxiety in Spanish population.</sec>Methods161 women were evaluated with the EPDS and the State–Trait Anxiety Inventory (STAI) during pregnancy and postpartum. Confirmatory factor analysis (CFA) was used to confirm the trifactorial structure of the EPDS, comprising the dimensions of Depression, Anhedonia and Anxiety. Likewise, the invariance of the trifactorial model between pregnancy and postpartum was tested. Finally, the correlations between the EPDS-A and the STAI subscales (State Anxiety and Trait Anxiety) were calculated.</sec>ResultsThe Exploratory factor analysis (EFA) driven three-factor structure of the EPDS, consisting of an Anhedonia factor (Items 1, 2, and 10), an Anxiety factor (Items 3, 4, 5, and 6) and a Depression factor (Items 7, 8, and 9), was the best measurement model for the current data compared to the alternative model tested [χ2 = 34.592, df = 32, p = 0.34; χ2/df = 1.08; RMSEA = 0.023, 90% Confidence Interval [CI] [0.000, 0.064], CFI = 0.996, GFI = 0.960]. The model’s invariance between pregnant and postpartum women was confirmed. The existence of an Anxiety subscale within the EPDS was also confirmed. The scores obtained with the EPDS-A correlated moderately with scores on both subscales of the STAI during pregnancy and after delivery. Using the STAI as a criterion and prioritising the instrument’s sensitivity, a cut-off point of 4 points was established for the EPDS-A.</sec>ConclusionOur results confirm the trifactorial structure of the EPDS in Spanish population. The Anxiety subscale was validated for routine perinatal mental health screening.</sec>

Introduction: There is a need to implement routine perinatal mental health screening in Spain. Therefore, it is necessary to systematise the detection of depressive and anxious symptoms in pregnancy and postpartum using the same instrument. The Edinburgh Postnatal Stress Depression Scale (EPDS) is frequently used as a rapid, effective and cross-culturally validated screening tool for perinatal depression. In several countries, an Anxiety subscale, the EPDS-A, was identified within the EPDS. Although the factorial structure of the EPDS has been investigated in Spanish population, the EPDS-A has not yet been validated. This study aimed to validate the EPDS-A as a measure of perinatal anxiety in Spanish population.Methods: 161 women were evaluated with the EPDS and the State–Trait Anxiety Inventory (STAI) during pregnancy and postpartum. Confirmatory factor analysis (CFA) was used to confirm the trifactorial structure of the EPDS, comprising the dimensions of Depression, Anhedonia and Anxiety. Likewise, the invariance of the trifactorial model between pregnancy and postpartum was tested. Finally, the correlations between the EPDS-A and the STAI subscales (State Anxiety and Trait Anxiety) were calculated.Results: The Exploratory factor analysis (EFA) driven three-factor structure of the EPDS, consisting of an Anhedonia factor (Items 1, 2, and 10), an Anxiety factor (Items 3, 4, 5, and 6) and a Depression factor (Items 7, 8, and 9), was the best measurement model for the current data compared to the alternative model tested [χ2 = 34.592, df = 32, p = 0.34; χ2/df = 1.08; RMSEA = 0.023, 90% Confidence Interval [CI] [0.000, 0.064], CFI = 0.996, GFI = 0.960]. The model’s invariance between pregnant and postpartum women was confirmed. The existence of an Anxiety subscale within the EPDS was also confirmed. The scores obtained with the EPDS-A correlated moderately with scores on both subscales of the STAI during pregnancy and after delivery. Using the STAI as a criterion and prioritising the instrument’s sensitivity, a cut-off point of 4 points was established for the EPDS-A.Conclusion: Our results confirm the trifactorial structure of the EPDS in Spanish population. The Anxiety subscale was validated for routine perinatal mental health screening.

Validation of the anxiety subscale of the Spanish version of the Edinburgh Postnatal Depression Scale (EPDS-A)

BackgroundThere is a rising interest in perinatal mental health studies, and proper psychometric tools to assess autistic traits among this population in Japan are vital.</sec>ObjectiveThis study aimed to clarify the optimal factor structure of the AQ as part of a perinatal mental health research project.</sec>MethodsWe used the Japanese version of the AQ (AQ-J) to measure autistic-like traits in pregnant women. Participants were 4,287 Japanese women who were pregnant or who had given birth within the last month. We performed exploratory factor analysis (EFA) using the first sample group (n = 2,154) to obtain factor structures for the final item selections. We performed confirmatory factor analysis (CFA) using the second sample group (n = 2,133) to obtain a model with good fit, then compared the model to all previously proposed models to determine the best-fitting model.</sec>ResultsThe EFA analysis identified a model consisting of 25 items distributed across three factors. Cronbach’s alpha for the total 25-item AQ-J, 9-item “Social interaction” factor, 11-item “Non-verbal communication” factor, and 5-item “Restricted interest” factor was 0.829, 0.829, 0.755, and 0.576, respectively. McDonald’s omega and its 95% confidence interval were 0.826 (0.821–0.836), 0.835 (0.821–0.837), 0.755 (0.744–0.766), and 0.603 (0.556–0.596), respectively. CFA confirmed that the three-factor structure had an acceptable fit (goodness of fit index: 0.900, comparative fit index: 0.860, root mean square error of approximation: 0.066). These findings indicated that the three-factor model was better than the 13 existing models.</sec>ConclusionThe findings are discussed in relation to the adequacy of the AQ-J for assessing autistic traits in perinatal women. We recommend the use of this 25-item, three-factor AQ-J model for this population owing to its superiority to all previous models.</sec>

Background: There is a rising interest in perinatal mental health studies, and proper psychometric tools to assess autistic traits among this population in Japan are vital.Objective: This study aimed to clarify the optimal factor structure of the AQ as part of a perinatal mental health research project.Methods: We used the Japanese version of the AQ (AQ-J) to measure autistic-like traits in pregnant women. Participants were 4,287 Japanese women who were pregnant or who had given birth within the last month. We performed exploratory factor analysis (EFA) using the first sample group (n = 2,154) to obtain factor structures for the final item selections. We performed confirmatory factor analysis (CFA) using the second sample group (n = 2,133) to obtain a model with good fit, then compared the model to all previously proposed models to determine the best-fitting model.Results: The EFA analysis identified a model consisting of 25 items distributed across three factors. Cronbach’s alpha for the total 25-item AQ-J, 9-item “Social interaction” factor, 11-item “Non-verbal communication” factor, and 5-item “Restricted interest” factor was 0.829, 0.829, 0.755, and 0.576, respectively. McDonald’s omega and its 95% confidence interval were 0.826 (0.821–0.836), 0.835 (0.821–0.837), 0.755 (0.744–0.766), and 0.603 (0.556–0.596), respectively. CFA confirmed that the three-factor structure had an acceptable fit (goodness of fit index: 0.900, comparative fit index: 0.860, root mean square error of approximation: 0.066). These findings indicated that the three-factor model was better than the 13 existing models.Conclusion: The findings are discussed in relation to the adequacy of the AQ-J for assessing autistic traits in perinatal women. We recommend the use of this 25-item, three-factor AQ-J model for this population owing to its superiority to all previous models.

The three-factor structure of the Autism-Spectrum Quotient Japanese version in pregnant women

BackgroundAntenatal depression is a commonly seen mental health concern for women. This study introduced a multicenter cross-sectional survey with a large sample to provide new insights into pregnant women’s depression, its socio-demographic and obstetric characteristics correlates, and its perceived stress among Chinese pregnant women.</sec>MethodsThis study conducted an observational survey according to the STROBE checklist. The multicenter cross-sectional survey was performed from August 2020 to January 2021 by distributing paper questionnaires among pregnant women from five tertiary hospitals in South China. The questionnaire included socio-demographic and obstetrics information, the Edinburgh Postnatal Depression Scale, and the 10-item Perceived Stress Scale. For the analyses, the Chi-square test and Multivariate logistic regression were utilized.</sec>ResultsAmong 2014 pregnant women in their second/third trimester, the prevalence of antenatal depression was 36.3%. 34.4% of pregnant women reported AD in their second trimester of pregnancy, and 36.9% suffered from AD in third trimester of pregnancy. A multivariate logistic regression model indicated that unemployed women, lower levels of education, poor marital relationships, poor parents-in-law relationships, concerns about contracting COVID-19, and higher perceived stress could aggravate antenatal depression among participants (p<0.05).</sec>ConclusionThere is a high proportion of antenatal depression among pregnant women in South China, so integrating depression screening into antenatal care services is worthwhile. Maternal and child health care providers need to evaluate pregnancy-related risk factors (perceived stress), socio-demographic factors (educational and professional status), and interpersonal risk factors (marital relations and relationship with Parents-in-law). In future research, the study also emphasized the importance of providing action and practical support to reduce the experience of antenatal depression among disadvantaged sub-groups of pregnant women.</sec>

Background: Antenatal depression is a commonly seen mental health concern for women. This study introduced a multicenter cross-sectional survey with a large sample to provide new insights into pregnant women’s depression, its socio-demographic and obstetric characteristics correlates, and its perceived stress among Chinese pregnant women.Methods: This study conducted an observational survey according to the STROBE checklist. The multicenter cross-sectional survey was performed from August 2020 to January 2021 by distributing paper questionnaires among pregnant women from five tertiary hospitals in South China. The questionnaire included socio-demographic and obstetrics information, the Edinburgh Postnatal Depression Scale, and the 10-item Perceived Stress Scale. For the analyses, the Chi-square test and Multivariate logistic regression were utilized.Results: Among 2014 pregnant women in their second/third trimester, the prevalence of antenatal depression was 36.3%. 34.4% of pregnant women reported AD in their second trimester of pregnancy, and 36.9% suffered from AD in third trimester of pregnancy. A multivariate logistic regression model indicated that unemployed women, lower levels of education, poor marital relationships, poor parents-in-law relationships, concerns about contracting COVID-19, and higher perceived stress could aggravate antenatal depression among participants (p&lt;0.05).Conclusion: There is a high proportion of antenatal depression among pregnant women in South China, so integrating depression screening into antenatal care services is worthwhile. Maternal and child health care providers need to evaluate pregnancy-related risk factors (perceived stress), socio-demographic factors (educational and professional status), and interpersonal risk factors (marital relations and relationship with Parents-in-law). In future research, the study also emphasized the importance of providing action and practical support to reduce the experience of antenatal depression among disadvantaged sub-groups of pregnant women.

Antenatal depression is associated with perceived stress, family relations, educational and professional status among women in South of China: a multicenter cross-sectional survey

Background and AimFear of childbirth (FOC) is one of the most common mental health concerns among expectant fathers, which can cause adverse consequences for themselves and their families. A valid and accurate tool is the key to the identification of FOC. This study aimed to translate and culturally adapt the fathers’ fear of childbirth scale (FFCS) into simplified Chinese and test the scale’s psychometric properties among expectant fathers in mainland China.</sec>MethodsResearchers obtained translation permission and followed the multiphase translation guidelines to develop the Chinese version of the fathers’ fear of childbirth scale (C-FFCS). Relevant psychometric properties were selected for the scale’s psychometric validation on the basis of the Consensus-based Standards for the Selection of Health Status Measurement Instruments checklist. In this cross-sectional study, two samples of expectant fathers were collected in a university-affiliated hospital in Hangzhou between September and October 2022.</sec>ResultsA total of 381 expectant fathers completed the C-FFCS, resulting in an effective response rate of 95.6%. The C-FFCS is a 3-factor structure consisting of 16 items, which explained 66.374% of the total variance. The content validity index of items ranged from 0.833 to 1.00, and the scale-level content validity index was 0.931. The confirmatory factor analysis confirmed the scale’s 3-factor structure. Evidence of convergent validity (average variance extracted = 0.508–0.780) as well as discriminant validity offered excellent psychometric support. The Cronbach’s α coefficient, McDonald’s ω coefficient, intraclass correlation coefficient, Spearman-Brown coefficient, and Guttman split-half coefficient are within the satisfactory range (> 0.80). Significant correlations between the scores of the C-FFCS and Childbirth Attitude Questionnaire (r = 0.658, p < 0.01) and Fear of Birth Scale (r = 0.555, p < 0.01) both revealed good concurrent validity. The structure of C-FFCS was invariant across different parity groups, with no floor and ceiling effect.</sec>ConclusionThe C-FFCS was demonstrated to be a sound instrument with good reliability and validity for measuring Chinese expectant fathers’ FOC levels. However, further studies are advocated to verify the C-FFCS among a larger sample that is more representative of the Chinese expectant father population.</sec>

Background and Aim: Fear of childbirth (FOC) is one of the most common mental health concerns among expectant fathers, which can cause adverse consequences for themselves and their families. A valid and accurate tool is the key to the identification of FOC. This study aimed to translate and culturally adapt the fathers’ fear of childbirth scale (FFCS) into simplified Chinese and test the scale’s psychometric properties among expectant fathers in mainland China.Methods: Researchers obtained translation permission and followed the multiphase translation guidelines to develop the Chinese version of the fathers’ fear of childbirth scale (C-FFCS). Relevant psychometric properties were selected for the scale’s psychometric validation on the basis of the Consensus-based Standards for the Selection of Health Status Measurement Instruments checklist. In this cross-sectional study, two samples of expectant fathers were collected in a university-affiliated hospital in Hangzhou between September and October 2022.Results: A total of 381 expectant fathers completed the C-FFCS, resulting in an effective response rate of 95.6%. The C-FFCS is a 3-factor structure consisting of 16 items, which explained 66.374% of the total variance. The content validity index of items ranged from 0.833 to 1.00, and the scale-level content validity index was 0.931. The confirmatory factor analysis confirmed the scale’s 3-factor structure. Evidence of convergent validity (average variance extracted = 0.508–0.780) as well as discriminant validity offered excellent psychometric support. The Cronbach’s α coefficient, McDonald’s ω coefficient, intraclass correlation coefficient, Spearman-Brown coefficient, and Guttman split-half coefficient are within the satisfactory range (&gt; 0.80). Significant correlations between the scores of the C-FFCS and Childbirth Attitude Questionnaire (r = 0.658, p &lt; 0.01) and Fear of Birth Scale (r = 0.555, p &lt; 0.01) both revealed good concurrent validity. The structure of C-FFCS was invariant across different parity groups, with no floor and ceiling effect.Conclusion: The C-FFCS was demonstrated to be a sound instrument with good reliability and validity for measuring Chinese expectant fathers’ FOC levels. However, further studies are advocated to verify the C-FFCS among a larger sample that is more representative of the Chinese expectant father population.