Applying a we al-li educaring framework to address histories of violence with Aboriginal women

An Aboriginal woman living in a remote area is 45 times more likely to experience domestic violence than their white peers. (Gordon et al, 2002) The nature of that violence is multi-layered, complex and incorporates a history of intergenerational loss, grief, trauma and the impact of colonisation, as discussed by Atkinson, C (2008). It involves women, children, families, communities. It is a story about people, many of whom find themselves in trouble with the legal system. Of the 25 male parents who killed their children in a domestic violence context five identified as Aboriginal (20%) (NSW Domestic Violence Death Review Team Annual Report, 2015, p.17). The percentage of women in Victorian prisons who have been victims of sexual, physical or emotional abuse has been reported to be 87% (Johnson, 2004). This figure is supported by the latest Ombudsman’s report on Victorian Prisons (2015).None of the 17 females who killed their children identified as Aboriginal or Torres Strait Islander (NSW Domestic Violence Death Review Team Annual Report 2015, p.18). The most common charge/offence for both Aboriginal men and women is an act intended to cause injury (see Figure 2).The stories of women in this program and anecdotal evidence from people working in the field reveals that most of this violence is lateral, ie within families and communities which is not an uncommon occurrence where there is a history of colonisation.

Is there scope for community health nurses to address lifestyle risk factors? The community nursing SNAP trial

Background
This paper examines the opportunity and need for lifestyle interventions for patients attending generalist community nursing services in Australia. This will help determine the scope for risk factor management within community health care by generalist community nurses (GCNs).

Methods
This was a quasi-experimental study conducted in four generalist community nursing services in NSW, Australia. Prior to service contacts, clients were offered a computer-assisted telephone interview to collect baseline data on socio-demographics, health conditions, smoking status, physical activity levels, alcohol consumption, height and weight, fruit and vegetable intake and 'readiness-to-change' for lifestyle risk factors.

Results
804 clients participated (a response rate of 34.1%). Participants had higher rates of obesity (40.5% vs 32.1%) and higher prevalence of multiple risk factors (40.4% vs 29.5%) than in the general population. Few with a SNAPW (S moking-N utrition-A lcohol-P hysical-Activity-Weight) risk factor had received advice or referral in the previous 3 months. The proportion of clients identified as at risk and who were open to change (i.e. contemplative, in preparation or in action phase) were 65.0% for obese/overweight; 73.8% for smokers; 48.2% for individuals with high alcohol intake; 83.5% for the physically inactive and 59.0% for those with poor nutrition.

Conclusions
There was high prevalence of lifestyle risk factors. Although most were ready to change, few clients recalled having received any recent lifestyle advice. This suggests that there is considerable scope for intervention by GCNs. The results of this trial will shed light on how best to implement the lifestyle risk factor management in routine practice.