7 research outputs found
Comparison of major depression diagnostic classification probability using the SCID, CIDI, and MINI diagnostic interviews among women in pregnancy or postpartum: An individual participant data meta-analysis
Objectives A previous individual participant data meta-analysis (IPDMA) identified differences in major depression classification rates between different diagnostic interviews, controlling for depressive symptoms on the basis of the Patient Health Questionnaire-9. We aimed to determine whether similar results would be seen in a different population, using studies that administered the Edinburgh Postnatal Depression Scale (EPDS) in pregnancy or postpartum. Methods Data accrued for an EPDS diagnostic accuracy IPDMA were analysed. Binomial generalised linear mixed models were fit to compare depression classification odds for the Mini International Neuropsychiatric Interview (MINI), Composite International Diagnostic Interview (CIDI), and Structured Clinical Interview for DSM (SCID), controlling for EPDS scores and participant characteristics. Results Among fully structured interviews, the MINI (15 studies, 2,532 participants, 342 major depression cases) classified depression more often than the CIDI (3 studies, 2,948 participants, 194 major depression cases; adjusted odds ratio [aOR] = 3.72, 95% confidence interval [CI] [1.21, 11.43]). Compared with the semistructured SCID (28 studies, 7,403 participants, 1,027 major depression cases), odds with the CIDI (interaction aOR = 0.88, 95% CI [0.85, 0.92]) and MINI (interaction aOR = 0.95, 95% CI [0.92, 0.99]) increased less as EPDS scores increased. Conclusion Different interviews may not classify major depression equivalently
Depression and anxiety in Singaporean high-risk pregnancies - prevalence and screening
10.1016/j.genhosppsych.2012.11.006General Hospital Psychiatry352112-116GHPS
Epidemiology of antenatal depression among women with high-risk pregnancies due to obstetric complications: a scoping review
Data-driven methods distort optimal cutoffs and accuracy estimates of depression screening tools: a simulation study using individual participant data
Objective: To evaluate, across multiple sample sizes, the degree that data-driven methods result in (1) optimal cutoffs different from population optimal cutoff and (2) bias in accuracy estimates.Study design and setting: A total of 1,000 samples of sample size 100, 200, 500 and 1,000 each were randomly drawn to simulate studies of different sample sizes from a database (n = 13,255) synthesized to assess Edinburgh Postnatal Depression Scale (EPDS) screening accuracy. Optimal cutoffs were selected by maximizing Youden's J (sensitivity+specificity-1). Optimal cutoffs and accuracy estimates in simulated samples were compared to population values.Results: Optimal cutoffs in simulated samples ranged from >= 5 to >= 17 for n = 100, >= 6 to >= 16 for n = 200, >= 6 to >= 14 for n = 500, and >= 8 to >= 13 for n = 1,000. Percentage of simulated samples identifying the population optimal cutoff (>= 11) was 30% for n = 100, 35% for n = 200, 53% for n = 500, and 71% for n = 1,000. Mean overestimation of sensitivity and underestimation of specificity were 6.5 percentage point (pp) and -1.3 pp for n = 100, 4.2 pp and -1.1 pp for n = 200, 1.8 pp and -1.0 pp for n = 500, and 1.4 pp and -1.0 pp for n = 1,000.Conclusions: Small accuracy studies may identify inaccurate optimal cutoff and overstate accuracy estimates with data-driven methods. (C) 2021 Elsevier Inc. All rights reserved
The prevalence and incidence of perinatal anxiety disorders among women experiencing a medically complicated pregnancy
Comparison of major depression diagnostic classification probability using the SCID, CIDI, and MINI diagnostic interviews among women in pregnancy or postpartum: An individual participant data meta-analysis
Objectives A previous individual participant data meta-analysis (IPDMA)
identified differences in major depression classification rates between
different diagnostic interviews, controlling for depressive symptoms on
the basis of the Patient Health Questionnaire-9. We aimed to determine
whether similar results would be seen in a different population, using
studies that administered the Edinburgh Postnatal Depression Scale
(EPDS) in pregnancy or postpartum. Methods Data accrued for an EPDS
diagnostic accuracy IPDMA were analysed. Binomial generalised linear
mixed models were fit to compare depression classification odds for the
Mini International Neuropsychiatric Interview (MINI), Composite
International Diagnostic Interview (CIDI), and Structured Clinical
Interview for DSM (SCID), controlling for EPDS scores and participant
characteristics. Results Among fully structured interviews, the MINI (15
studies, 2,532 participants, 342 major depression cases) classified
depression more often than the CIDI (3 studies, 2,948 participants, 194
major depression cases; adjusted odds ratio [aOR] = 3.72, 95%
confidence interval [CI] [1.21, 11.43]). Compared with the
semistructured SCID (28 studies, 7,403 participants, 1,027 major
depression cases), odds with the CIDI (interaction aOR = 0.88, 95% CI
[0.85, 0.92]) and MINI (interaction aOR = 0.95, 95% CI [0.92,
0.99]) increased less as EPDS scores increased. Conclusion Different
interviews may not classify major depression equivalently
Probability of major depression classification based on the SCID, CIDI, and MINI diagnostic interviews: A synthesis of three individual participant data meta-analyses
Introduction: Three previous individual participant data meta-analyses (IPDMAs) reported that, compared to the Structured Clinical Interview for the DSM (SCID), alternative reference standards, primarily the Composite International Diagnostic Interview (CIDI) and the Mini International Neuropsychiatric Interview (MINI), tended to misclassify major depression status, when controlling for depression symptom severity. However, there was an important lack of precision in the results. Objective: To compare the odds of the major depression classification based on the SCID, CIDI, and MINI. Methods: We included and standardized data from 3 IPDMA databases. For each IPDMA, separately, we fitted binomial generalized linear mixed models to compare the adjusted odds ratios (aORs) of major depression classification, controlling for symptom severity and characteristics of participants, and the interaction between interview and symptom severity. Next, we synthesized results using a DerSimonian-Laird random-effects meta-analysis. Results: In total, 69,405 participants (7,574 [11%] with major depression) from 212 studies were included. Controlling for symptom severity and participant characteristics, the MINI (74 studies; 25,749 participants) classified major depression more often than the SCID (108 studies; 21,953 participants; aOR 1.46; 95% confidence interval [CI] 1.11-1.92]). Classification odds for the CIDI (30 studies; 21,703 participants) and the SCID did not differ overall (aOR 1.19; 95% CI 0.79-1.75); however, as screening scores increased, the aOR increased less for the CIDI than the SCID (interaction aOR 0.64; 95% CI 0.52-0.80). Conclusions: Compared to the SCID, the MINI classified major depression more often. The odds of the depression classification with the CIDI increased less as symptom levels increased. Interpretation of research that uses diagnostic interviews to classify depression should consider the interview characteristics.</p