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Background  In South Africa, the prevalence of symptoms of common mental disorders (CMD), i.e. depression, anxiety and suicidal thoughts are high. This study aimed to use a cognitive interviewing technique to validate the content and structure of a 4-item screening tool, to adapt the tool accordingly, and to use receiver operating curve (ROC) analysis to determine the optimum cut-point for identifying pregnant women with symptoms of CMD.    Methods  We conducted a mixed method study at a Midwife Obstetric Unit in Cape Town. Women attending the clinic for their first antenatal visit during the recruitment period, whose first language was English, Afrikaans or isiXhosa, were invited to participate. A 4-item screening tool was administered in the first language of the interviewee, after which a cognitive interviewing technique was used to examine the question-response processes and considerations used by respondents as they formed answers to the screening tool questions. The Edinburgh Postnatal Depression Scale (EPDS) was used to identify women with symptoms of CMD.    Results  A 2-week recall period performed well. Questions about (1) being unable to stop worrying, or thinking too much, (2) feeling down, depressed or hopeless, and (3) having thoughts and plans to harm yourself, were well understood. The question that referred to feeling little interest or pleasure in doing things, was poorly understood across all languages. Using ROC analysis with the EPDS as the reference standard, and a cut-point of ≥13, we showed that a 3-item version of the screening tool was able to correctly classify 91% of the women screened.    Conclusions  Cognitive interviewing enabled testing and refining of the language and constructs of an ultra-brief screening tool. The shortened, 3-item tool is well understood and effective at identifying pregnant women with symptoms of CMD, across the three most commonly spoken languages and cultures in Cape Town.

Validation of a brief mental health screening tool for pregnant women in a low socio-economic setting