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Supporting routine psychosocial assessment in the perinatal period: The concurrent and predictive validity of the
Nicole Reilly1, Dusan Hadzi-Pavlovic2, Deborah Loxton3
1Centre for Health Service Development, Australian Health Services Research Institute, University of Wollongong, NSW, Australia; Perinatal and Women's Mental Health Unit, St John of God Burwood Hospital, Australia; School of Psychiatry, UNSW Medicine, NSW, Australia.
Background:
Australian clinical practice guidelines support comprehensive psychosocial assessment as a routine component of maternity care.
Aim:
To examine the concurrent and predictive validity of the Antenatal Risk Questionnaire-Revised (ANRQ-R) when used across the perinatal period.
Methods:
Women completed the ANRQ-R and a diagnostic reference standard (SAGE-SR) in the second and third trimesters and at 3-months postpartum. ANRQ-R test performance for cut-off scores at each time-point was assessed using Receiver Operator Characteristic (ROC) analysis.
Findings:
Overall sample sizes were N=1166 (second trimester), N=957 (third trimester) and N=796 (3-month postpartum). 6.5%, 5.6% and 6.2% of women met SAGE-SR criteria for any depressive or anxiety disorder at these time-points ('cases'), respectively. ROC analysis yielded acceptable areas under the curve (AUC) when the ANRQ-R was used to detect current (AUC=0.789-0.798) or predict future (AUC=0.705-0.789) depression or anxiety. Using an example cut-off score of 18 or more, the ANRQ-R correctly classified 72-76% of concurrent 'cases' and 'non-cases' (sensitivity=0.70-0.74, specificity=0.72-0.76) and correctly predicted 74-78% of postnatal 'cases' and 'non-cases' (sensitivity=0.52-0.72, specificity=0.75-0.79). Completion of the ANRQ-R earlier in pregnancy yielded greater positive likelihood ratios for predicting depression or anxiety at 3-months postpartum (cut-off ≥18: second trimester=3.8; third trimester=2.2).
Conclusion:
The ANRQ-R is a structured psychosocial assessment questionnaire that can be scored to provide an overall measure of psychosocial risk. Cut-off scores need not be uniform across settings. Such decisions should be guided by factors including diagnostic prevalence rates, local needs and resource availability.
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