Characteristics of women calling the PANDA Perinatal Anxiety & Depression Australia National Helpline: a cross-sectional study.
Touran ShafieiLaura J BiggsRhonda SmallHelen L McLachlanDella A ForsterPublished in: Archives of women's mental health (2018)
The PANDA Perinatal Anxiety & Depression Australia National Helpline provides support for people affected by perinatal mental health issues. To describe the characteristics of women contacting the Helpline, specifically callers' health, past history and assessed risk factors. Analysis of routinely collected de-identified data of women making initial calls between July 2010 and October 2013. Five thousand eight hundred eighteen women made an initial call to the Helpline. Most were between 25 and 40 years old (79%) and married/partnered (94%); 52% were having or had their first child; and 23% were pregnant. Over half had no prior mental health diagnosis at the time of their initial call, and 40% were assessed as 'high needs'-experiencing significant bio-psychosocial symptoms, complex situations and/or inadequate care and support. There was a 70% increase in calls to PANDA over the data collection period. Concerns recorded by PANDA staff from the initial risk assessment included inadequate treatment for a mental health condition (31%), women not feeling connected to their baby (31%), low functioning (26%) and general thoughts of suicide (18%). The Helpline experienced a significant increase in demand during the study period, and a substantial proportion of callers had complex mental health needs. PANDA plays a major role in providing support to a large number of women experiencing perinatal mental health problems.
Keyphrases
- mental health
- polycystic ovary syndrome
- mental illness
- pregnancy outcomes
- risk assessment
- risk factors
- pregnant women
- cervical cancer screening
- healthcare
- sleep quality
- depressive symptoms
- quality improvement
- breast cancer risk
- type diabetes
- social media
- electronic health record
- insulin resistance
- physical activity
- health information
- deep learning