Summary diagnostic validity of commonly used maternal major depression disorder case finding instruments in the United States: A meta-analysis

Optimal risk and diagnosis assessment strategies in perinatal depression: A machine learning approach from the life-ON study cohort

This study aimed to assess the concordance of various psychometric scales in detecting Perinatal Depression (PND) risk and diagnosis. A cohort of 432 women was assessed at 10-15th and 23-25th gestational weeks, 33-40 days and 180-195 days after delivery using the Edinburgh Postnatal Depression Scale (EPDS), Visual Analogue Scale (VAS), Hamilton Depression Rating Scale (HDRS), Montgomery-Åsberg Depression Rating Scale (MADRS), and Mini International Neuropsychiatric Interview (MINI). Spearman's rank correlation coefficient was used to assess agreement across instruments, and multivariable classification models were developed to predict the values of a binary scale using the other scales. Moderate agreement was shown between the EPDS and VAS and between the HDRS and MADRS throughout the perinatal period. However, agreement between the EPDS and HDRS decreased postpartum. A well-performing model for the estimation of current depression risk (EPDS > 9) was obtained with the VAS and MADRS, and a less robust one for the estimation of current major depressive episode (MDE) diagnosis (MINI) with the VAS and HDRS. When the EPDS is not feasible, the VAS may be used for rapid and comprehensive postpartum screening with reliability. However, a thorough structured interview or clinical examination remains necessary to diagnose a MDE.

Satisfaction and Perceived Effectiveness on Herbal Decoctions for Postpartum Care: a cross-sectional survey of mother's experience

Objectives

In East Asia, postpartum care has traditionally been considered important for maternal health; however, studies on this are still insufficient. Therefore, we examined the satisfaction and perceived effectiveness of herbal decoctions used in postpartum care in a city in the Republic of Korea (ROK).

Methods

We analyzed anonymized secondary data obtained from a retrospective cross-sectional survey of women who had taken herbal decoctions provided by the support service for women giving birth in a local city in ROK. The questionnaire items consisted of basic information regarding childbirth, the need for the herbal decoction support service, satisfaction, and the effectiveness of the service received.

Results

A total of 68 women were included in the study, and those aged 30-39 accounted for 73.13%. Of the 68 women, 79.37% visited within 3 weeks of childbirth. Women's satisfaction regarding herbal decoction support for postpartum care was 76.47%, and most women (98.53%) responded that they needed it more than twice. More than 50% of women showed improvement in puerperal wind disorders, weight gain, and delayed eliminated lochia.

Conclusion

A large proportion of women who took herbal decoctions reported satisfaction and perceived effectiveness when used to treat puerperal wind disorders. Nevertheless, future well-designed clinical studies are needed to provide information on whether herbal decoctions effectively prevent and treat puerperal wind disorders.

Maternal major depression disorder misclassification errors: Remedies for valid individual- and population-level inference

Individual and population level inference about risk and burden of MDD, particularly maternal MDD, is often made using case-finding tools that are imperfect and prone to misclassification error (i.e. false positives and negatives). These errors or biases are rarely accounted for and lead to inappropriate clinical decisions, inefficient allocation of scarce resources, and poor planning of maternal MDD prevention and treatment interventions. The argument that the use of existing maternal MDD case-finding instruments results in misclassification errors is not new; in fact, it has been argued for decades, but by and large its implications and particularly how to correct for these errors for valid inference is unexplored. Correction of the estimates of maternal MDD prevalence, case-finding tool sensitivity and specificity is possible and should be done to inform valid individual and population-level inferences.

Validated tools to identify common mental disorders in the perinatal period: A systematic review of systematic reviews

BACKGROUND

Uncertainty remains regarding the validity of screening tools to detect common mental disorders (CMDs) during perinatal periods. This umbrella review aims to provide an up-to-date summary of psychometric properties of tools for the identification of perinatal CMDs.

METHODS

Reviews were identified via Ovid MEDLINE, PsychINFO, EMBASE, Global Health and Cochrane Database of Systematic Reviews electronic databases with no date or language restriction. Pooled sensitivity and specificity estimates and ranges were extracted and summarised using forest plots. Quality assessment was conducted using Measurement Tool to Assess Systematic Reviews (AMSTAR-2).

RESULTS

Of 7,891 papers identified, 31 reviews met inclusion criteria. 76 screening tools were identified; most frequently validated were Edinburgh Postnatal Depression Scale (EPDS) (n = 28 reviews), Beck's Depression Inventory (BDI) (n = 13 reviews) and Patient Health Questionnaire (PHQ) (n = 12 reviews). Forest plots demonstrated a pattern of decreasing sensitivity and increasing specificity with increasing cut-off scores. Sub-group analysis of data extracted from low quality reviews demonstrated wider 95% CIs and overall lower specificity. Validity also varied according to ethnicity, socio-economic background and age.

LIMITATIONS

Despite a low Covered Corrected Area (CCA) score the primary studies included within reviews overlapped; therefore we were unable perform meta-analysis.

CONCLUSIONS

The evidence suggests that the EPDS, PHQ and BDI are useful across a range of diverse settings but the context of tool application is a key factor determining validity. This review highlights that utilizing screening tools in clinical practice is complex and requires careful consideration of the population, context, and health system it will be used in.

Screening for perinatal depression with the Patient Health Questionnaire depression scale (PHQ-9): A systematic review and meta-analysis

OBJECTIVES

Perinatal depression (PND) is a prevalent and disabling problem both during pregnancy and the postpartum period. The legacy screening measure has been the Edinburgh Postnatal Depression Scale (EPDS). This systematic review examines the validity of the PHQ-9 as a screener for PND.

METHODS

The following databases were searched from January 2001 (when the PHQ-9 was first published) through June 2020: MEDLINE, Embase, and PsychInfo. Studies that compared the PHQ-9 to a criterion standard psychiatric interview were used to determine the operating characteristics of sensitivity, specificity and area under the curve (AUC). Studies comparing the PHQ-9 to the EPDS and other depression scales evaluated convergent validity.

RESULTS

A total of 35 articles were eligible for criterion (n = 10) or convergent (n = 25) validity. Meta-analysis of the 7 criterion validity studies using the standard PHQ-9 cut point ≥10 showed a pooled sensitivity, specificity and AUC of 0.84, 0.81 and 0.89, respectively. Operating characteristics of the PHQ-9 and EPDS were nearly identical in head-to-head comparison studies. The median correlation between the PHQ-9 and EPDS was 0.59, and categorical agreement was moderate.

CONCLUSIONS

The PHQ-9 appears to be a viable option for perinatal depression screening with operating characteristics similar to the legacy EPDS.

Screening Depressive Disorders With Tree-Drawing Test

Objective: Diagnosis of psychiatric disease is still a major issue. Two key reasons are- there are variations in the opinions of the medical doctors and the presentation of a disease among the patients. Here we introduce a kind of mental projective test, tree-drawing test, trying to extract and analyze objective indexes in tree-drawing test in patients with depression. Methods: The tree-drawing test was administered to 43 patients with major depressive disorders, 48 sub-threshold subjects, and 59 healthy subjects. Features of the drawing trees were analyzed using a kind of computer image recognition and data acquisition software. Quantitative indexes collected from pictures drawn by patients with major depression, patients with sub-threshold depression, and control subjects were compared using the ANOVA test. Results: Five quantitative features (canopy area, canopy height, canopy width, trunk width, and total area of trees) were found to be statistically significant among the groups, while seven other features (trunk area, trunk height, root width, root height, root area, ratio of crown to trunk height, and ratio of crown to trunk area) showed no statistical significance. Further analysis with LSD-t test revealed that six quantitative indexes were significantly related to the depression symptoms, and six others were not statistically significant. Eleven quantitative indexes were not statistically significant when the depressive symptoms were compared with the subthreshold depression group, and the only index with statistical significance was canopy width. Conclusion: Five quantitative indexes in the drawing tree are statistically significant in the depression patients were compared with those of the control subjects. Quantitative indexes of the tree-drawing test are of great value in assisting with the diagnosis of psychiatric disorders.

Are we validly assessing major depression disorder risk and associated factors among mothers of young children? A cross-sectional study involving home visitation programs

Failure to account for misclassification error accruing from imperfect case-finding instruments can produce biased estimates of suspected major depression disorder (MDD) risk factor associations. The objective of this study was to estimate the impact of misclassification error on the magnitude of measures of association between suspected risk factors and MDD assessed using the Center of Epidemiological Studies on Depression—Short Form during the prenatal and postnatal periods. Baseline data were collected from 520 mothers participating in two home visitation studies in Oklahoma City between 2010 and 2014. A Bayesian binomial latent class model was used to compare the prevalence proportion ratio (PPR) between suspected risk factors and MDD with and without adjustment for misclassification error and confounding by period of MDD symptom on-set. Adjustment for misclassification error and confounding by period of MDD on-set (prenatal vs postnatal) showed that the association between suspected risk factors and MDD is underestimated (-) and overestimated (+) differentially in different source populations of low-income mothers. The median bias in the magnitude of PPR estimates ranged between -.47 (95% Bayesian Credible Intervals [BCI]: -10.67, 1.90) for intimate partner violence to +.06 (95%BCI: -0.37, 0.47) for race/ethnicity among native-born US residents. Among recent Hispanic immigrants, bias ranged from -.77 (95%BCI: -15.31, 0.96) for history of childhood maltreatment to +.10 (95%BCI: -0.17, 0.39) for adequacy of family resources. Overall, the extent of bias on measures of association between maternal MDD and suspected risk factors is considerable without adjustment for misclassification error and is even higher for confounding by period of MDD assessment. Consideration of these biases in MDD prevention research is warranted.

Family physicians perceived role in perinatal mental health: an integrative review

Background

Responding to and caring for women who experience mental health problems during the perinatal period, from pregnancy up to one year after birth, is complex and requires a multidisciplinary response. Family physicians are ideally placed to provide an effective response as it is recognised that they are responsible for organising care and supports for women and their families. This paper reports an integrative review undertaken to examine family physicians’ perceived role in perinatal mental health care and concludes with recommendations for health policy, research and practice.

Method

A systematic search of literature in seven databases from January 2000 to March 2016 identified a total of 1125 articles. Qualitative, quantitative and mixed-method studies were eligible for inclusion if they explored family physicians’ experiences of caring for women who experience perinatal mental health problems.

Results

Thirteen articles reporting 11 studies met the inclusion criteria for this review and quality of included studies were assessed using published criteria for the critical appraisal of qualitative and quantitative research methods. Cross-study narrative syntheses of quantitative and qualitative findings are presented under three themes: identification of perinatal mental health problems, management of perinatal mental health problems and barriers to care provision. While family physicians recognise their role in relation to perinatal mental health the collective interpretation revealed that; they receive variable levels of preparation for this role, no consistent approach to screening exists, pharmacological management of mood disorders is the main treatment modality and limited access to specialist perinatal mental health services exists which impacts on pharmacology decisions.

Conclusion

Family physicians require timely access to local integrated care pathways that provide a wide range of services that are culturally sensitive, perinatal mental health specific, support psychological well-being and infant/family mental health. Family physicians are open to incorporating a brief validated screening tool into primary practice supported by succinct guidelines. Research that examines training needs in relation to perinatal mental health could be used to inform family physician training programmes and curriculum development around perinatal mental health.

Impact of misclassification error in the estimation of maternal major depression disorder prevalence in home visitation programs

The objective of this study was to measure the bias introduced by misclassification error when estimating the prevalence of MDD among mothers in two community-based studies. Baseline data were collected from mothers participating in two home visitation study sites in South Central United States between 2010 and 2014. The operational definition of MDD was a Center of Epidemiological Studies-Depression - Short Form (CESD-SF) score of 10 or higher. Misclassification error was adjusted for using CESD-SF sensitivity and specificity priors that were either antepartum or postpartum specific or non-specific. Bias was measured as the difference between the observed and misclassification error-adjusted prevalence estimates using a Binomial Bayesian Latent Class model. The proportion of mothers in the antepartum and postpartum periods confounded the level of bias in estimating MDD prevalence. When using antepartum and postpartum specific sensitivity and specificity of the CESD-SF, misclassification error led to nearly no bias in prevalence estimates. In contrast, ignoring differences in CESD-SF sensitivity and specificity between these periods showed considerable MDD prevalence bias. The use of period of assessment (antepartum versus postpartum) specific case-finding instrument diagnostic performance values is critical to the valid estimation of MDD prevalence among mothers. Studies using other case-finding instruments are needed to support this conclusion.